DETAILED ACTION
1. Claims 1-20 have been presented for examination.
Notice of Pre-AIA or AIA Status
2. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
PRIORITY
3. Acknowledgment is made of applicant's claim for priority based on an application PRO 63/376,898 filed September 23, 2022.
Information Disclosure Statement
4. The information disclosure statements (IDS) submitted on February 9, 2023 and April 25, 2024 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the Examiner has considered the IDS as to the merits.
Claim Rejections – 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
5. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e. abstract idea) without anything significantly more.
i) In view of Step 1 of the analysis, independent claim 1 is directed to a statutory category as a process, independent claim 11 is directed to a statutory category as a manufacture, and independent claim 20 is directed to a statutory category as a machine, which each represent a statutory category of invention. Therefore, claims 1-20 are directed to patent eligible categories of invention.
ii) In view of Step 2A, Prong One, independent claims 1, 11, and 20 recite the abstract idea of generating a multi-building layout for a site, which constitutes an abstract idea based on Mental Processes: concepts performed in the human mind or with the aid of pencil and paper.
As to claims 1, 11, and 20, the limitation of “instantiating a plurality of agents representing a plurality of buildings located on the site based on a set of boundary conditions associated with the site” would be analogous to a person drawing buildings located on a site based on a set of boundary conditions associated with the site on paper, which would represent a mental process;
the limitation of “iteratively updating a plurality of states associated with the plurality of agents based on the set of boundary conditions and a plurality of behaviors associated with the plurality of agents” would be analogous to a person drawing to update the buildings’ positions and orientations based on the set of boundary conditions and an alignment, a separation, or a global orientation associated with all the buildings on paper, which would represent a mental process;
and the limitation of “generating a layout for the site based on the plurality of states, wherein the layout comprises a plurality of building footprints for the plurality of
buildings” would be analogous to a person drawing a layout, comprising building footprints for the buildings, for the site based on the buildings’ positions and orientations on paper, which would represent a mental process.
As to claim 1, other than reciting “a computer-implemented method for generating a multi-building layout for a site,” nothing in the claim elements precludes the step from practically being performed in the mind as a Mental Process.
As to claim 11, other than reciting “one or more non-transitory computer-readable media storing instructions” and “one or more processors,” nothing in the claim elements precludes the step from practically being performed in the mind as a Mental Process.
As to claim 20, other than reciting “a system,” “one or more memories that store instructions,” and “one or more processors that are coupled to the one or more memories,” nothing in the claim elements precludes the step from practically being performed in the mind as a Mental Process.
Dependent claims 2-10 and 12-19 further narrow the abstract ideas of Mental Processes identified in the independent claims. Additionally, dependent claims 4, 14, and 15 also recite the abstract ideas of Mathematical Concepts. All the dependent claims do not introduce further additional elements for consideration beyond those addressed above.
iii) In view of Step 2A, Prong Two, the judicial exception is not integrated into a practical application. The additional element of “a computer-implemented method for generating a multi-building layout for a site” in independent claim 1, the additional elements of “one or more non-transitory computer-readable media storing instructions” and “one or more processors” in independent claim 11, and the additional elements of “a system,” “one or more memories that store instructions,” and “one or more processors that are coupled to the one or more memories” in independent claim 20 merely use computer device as a tool to perform the abstract idea (MPEP 2106.05(f)). Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general-purpose computer or computer components after the fact to an abstract idea (e.g., a mental process) does not integrate a judicial exception into a practical application (MPEP 2106.05(f)(2)). Additionally, the limitation of “a computer-implemented method for generating a multi-building layout for a site” in claim 1, the limitation of “one or more non-transitory computer-readable media storing instructions that, when executed by one or more processors, cause the one or more processors to perform the steps” in claim 11, and the limitation of “a system, comprising: one or more memories that store instructions, and one or more processors that are coupled to the one or more memories and, when executing the instructions, are configured to perform the steps” in claim 20 alternatively can be viewed as insignificant extra-solution activity, specifically pertaining to mere data gathering/output necessary to perform the abstract idea (MPEP 2106.05(g)) and is not sufficient to integrate the judicial exception into a practical application. This is akin to selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, which has been identified as extra solution activity. Therefore, the judicial exception is not integrated into a practical application.
Dependent claims 2-10 and 12-19 further narrow the abstract ideas of Mental Processes identified in the independent claims. Additionally, dependent claims 4, 14, and 15 also recite the abstract ideas of Mathematical Concepts. All the dependent claims do not introduce further additional elements for consideration beyond those addressed above.
iv) In view of Step 2B, independent claims 1, 11, and 20 do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The limitation in claim 1 of “a computer-implemented method for generating a multi-building layout for a site,” the limitation in claim 11 of “one or more non-transitory computer-readable media storing instructions that, when executed by one or more processors, cause the one or more processors to perform the steps,” and the limitation in claim 20 of “a system, comprising: one or more memories that store instructions, and one or more processors that are coupled to the one or more memories and, when executing the instructions, are configured to perform the steps” are mere method/instructions to implement an abstract idea using a computer in its ordinary capacity, or merely uses the computer as a tool to perform the identified abstract idea (MPEP 2106.05(f)). Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general-purpose computer or computer components after the fact to an abstract idea (e.g., a mental process) does not integrate a judicial exception into a practical application (MPEP 2106.05(f)(2)). Additionally, the limitation of “a computer-implemented method for
generating a multi-building layout for a site” in claim 1, the limitation of “one or more non-transitory computer-readable media storing instructions that, when executed by one or
more processors, cause the one or more processors to perform the steps” in claim 11, and the limitation of “a system, comprising: one or more memories that store instructions, and one or more processors that are coupled to the one or more memories and, when executing the instructions, are configured to perform the steps” in claim 20 alternatively can be viewed as insignificant extra-solution activity, specifically pertaining to mere data gathering/output necessary to perform the abstract idea (MPEP 2106.05(g)) and is not sufficient to integrate the judicial exception into a practical application. This is akin to selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, which has been identified as extra solution activity. Therefore, the claim as a whole does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, when considered alone or in combination, do not amount to significantly more than the judicial exception. As stated in Section I.B. of the December 16, 2014 101 Examination Guidelines, “[t]o be patent-eligible, a claim that is directed to a judicial exception must include additional features to ensure that the claim describes a process or product that applies the exception in a meaningful way, such that it is more than a drafting effort designed to monopolize the exception.”
The dependent claims include the same abstract ideas recited in the independent claims, and merely incorporate additional details that narrow the abstract ideas and fail to add significantly more to the claims.
Dependent claims 2-10 and 12-19 further define the way to generate a multi-building site layout of respective claims 1 and 11, which merely narrows the abstract idea identified as a mental process.
Additionally, dependent claims 4, 14, and 15 also define the data or calculations of generating a multi-building site layout, which merely recites the abstract idea identified as a mathematical concept.
Dependent claim 2 further defines the type of methodology of the multi-building site layout generation of respective claim 1: “instantiating the plurality of agents comprises, for each agent included in the plurality of agents, determining an initial position and an initial orientation of a corresponding building located on the site,” which would be analogous to a person drawing to determine a building’s initial position and initial orientation on the site on paper. Thus, claim 2 merely narrows the abstract idea identified as a mental process in claim 1.
Dependent claim 3 further defines the type of methodology of the multi-building site layout generation of respective claim 1: “iteratively updating the plurality of states associated with the plurality of agents comprises updating a position of a building represented by an agent based on a separation between the building and one or more other buildings included in the plurality of buildings,” which would be analogous to a person drawing to update a position of a building based on a distance between the building and one or more other buildings on paper. Thus, claim 3 merely narrows the abstract idea identified as a mental process in claim 1.
Dependent claim 4 further defines the type of methodology of the multi-building site layout generation of respective claim 1: “the position of the building is updated via a force vector that is determined based on the separation between the building and the one or more other buildings,” which would be analogous to a person drawing to update the position of the building after calculating a force vector based on the distance between the building and the one or more other buildings on paper. Additionally, dependent claim 4 also defines the following data of the multi-building site layout generation: “a force vector that is determined based on the separation between the building and the one or more other buildings,” which recites a vector quantity calculated based on a spatial measurement associated with the buildings and falls under mathematical formulas or equations as well as calculations. Thus, claim 4 merely narrows the abstract idea identified as a mental process in claim 1 and recites the abstract idea identified as a mathematical concept.
Dependent claim 5 further defines the type of methodology of the multi-building site layout generation of respective claim 1: “iteratively updating the plurality of states associated with the plurality of agents comprises updating an orientation of a building represented by an agent based on an alignment of the building with one or more entities associated with the layout,” which would be analogous to a person drawing to update an orientation of a building based on an alignment of the building with one or more entities associated with the layout on paper. Thus, claim 5 merely narrows the abstract idea identified as a mental process in claim 1.
Dependent claim 6 further defines the type of methodology of the multi-building site layout generation of respective claim 1: “the one or more entities comprise at least one of a second building that is adjacent to the building, a boundary of the site, or the plurality of buildings located on the site,” which would be analogous to a person drawing at least one of a second building that is adjacent to the building, a boundary of the site, or other buildings on the site on paper. Thus, claim 6 merely narrows the abstract idea identified as a mental process in claim 1.
Dependent claim 7 further defines the type of methodology of the multi-building site layout generation of respective claim 1: “iteratively updating the plurality of states associated with the plurality of agents comprises: determining a plurality of building positions and a plurality of building orientations included in the plurality of states; and adjusting a plurality of building dimensions included in the plurality of states based on the plurality of building positions, the plurality of building orientations, and the set of boundary conditions,” which would be analogous to a person drawing to determine building positions and building orientations and adjust building dimensions based on building positions, building orientations, and the set of boundary conditions on paper. Thus, claim 7 merely narrows the abstract idea identified as a mental process in claim 1.
Dependent claim 8 further defines the type of methodology of the multi-building site layout generation of respective claim 1: “the plurality of behaviors includes at least one of determining a separation between a building and an edge of the site or determining a separation between buildings,” which would be analogous to a person drawing to at least determine a separation between a building and an edge of the site or determine a separation between buildings on paper. Thus, claim 8 merely narrows the abstract idea identified as a mental process in claim 1.
Dependent claim 9 further defines the type of methodology of the multi-building site layout generation of respective claim 1: “the plurality of behaviors includes at least one of determining an alignment between a building and the site, determining an alignment between buildings, or determining a global orientation associated with the plurality of buildings,” which would be analogous to a person drawing to at least determine an alignment between a building and the site, an alignment between buildings, or determine a global orientation associated with all the buildings on paper. Thus, claim 9 merely narrows the abstract idea identified as a mental process in claim 1.
Dependent claim 10 further defines the type of methodology of the multi-building site layout generation of respective claim 1: “the set of boundary conditions includes at least one of a site boundary, a setback requirement, a minimum separation between buildings, a maximum separation between buildings, a minimum building size, a maximum building size, a minimum building dimension, a maximum building dimension, or a number of buildings to place on the layout,” which would be analogous to a person drawing at least one of a site boundary, a setback requirement, a minimum separation between buildings, a maximum separation between buildings, a minimum building size, a maximum building size, a minimum building dimension, a maximum building dimension, or a number of buildings to place on the layout on paper. Thus, claim 10 merely narrows the abstract idea identified as a mental process in claim 1.
Dependent claim 12 further defines the type of methodology of the multi-building site layout generation of respective claim 11: “instantiating the plurality of agents comprises, for each agent included in the plurality of agents, determining an initial position and an initial orientation of a corresponding building on the site,” which would be analogous to a person drawing to determine a building’s initial position and initial orientation on the site on paper. Thus, claim 12 merely narrows the abstract idea identified as a mental process in claim 11.
Dependent claim 13 further defines the type of methodology of the multi-building site layout generation of respective claim 11: “the initial position and the initial orientation are determined based on at least one of the set of boundary conditions or a set of random values,” which would be analogous to a person drawing to determine the initial building position and the initial orientation based on at least one of the set of boundary conditions or a set of random values on paper. Thus, claim 13 merely narrows the abstract idea identified as a mental process in claim 11.
Dependent claim 14 further defines the type of methodology of the multi-building site layout generation of respective claim 11: “iteratively updating the plurality of states associated with the plurality of agents comprises: computing a force vector associated with a building based on the plurality of states, the plurality of behaviors, and the set of boundary conditions; and updating at least one of a position of the building or an orientation of the building based on the force vector,” which would be analogous to a person calculating a force vector associated with a building based on its position and orientation, an alignment, a separation, or a global orientation associated with all the buildings, and the set of boundary conditions and drawing to update at least one of a position of the building or an orientation of the building based on the force vector on paper. Additionally, dependent claim 14 also defines the following calculations of the multi-building site layout generation: “computing a force vector associated with a building based on the plurality of states, the plurality of behaviors, and the set of boundary conditions” and “updating at least one of a position of the building or an orientation of the building based on the force vector,” which recite a calculation of a vector quantity associated with a building based on multi-building site layout measurements and a calculation of some of the multi-building site layout measurements based on the calculated vector quantity and fall under mathematical formulas or equations as well as calculations. Thus, claim 14 merely narrows the abstract idea identified as a mental process in claim 11 and recites the abstract idea identified as a mathematical concept.
Dependent claim 15 further defines the type of methodology of the multi-building site layout generation of respective claim 11: “computing the force vector comprises dampening the force vector based on a number of iterative updates to the plurality of states,” which would be analogous to a person calculating the reduction of the magnitude of the force vector based on a number of iterative updates to the building positions and building orientations. Additionally, dependent claim 15 also defines the following calculation of the multi-building site layout generation of dependent claim 14: “dampening the force vector based on a number of iterative updates to the plurality of states,” which recites a reduction of a vector quantity based on a number of iterative updates to some of the multi-building site layout measurements and falls under mathematical formulas or equations as well as calculations. Thus, claim 15 merely narrows the abstract idea identified as a mental process in claim 11 and the abstract idea identified as a mathematical concept in claim 14.
Dependent claim 16 further defines the type of methodology of the multi-building site layout generation of respective claim 11: “iteratively updating the plurality of states associated with the plurality of agents comprises adjusting a plurality of dimensions for the plurality of buildings based on the set of boundary conditions, a plurality of building positions included in the plurality of states, and a plurality of building orientations included in the plurality of states,” which would be analogous to a person drawing to adjust building dimensions based on the set of boundary conditions, building positions, and building orientations on paper. Thus, claim 16 merely narrows the abstract idea identified as a mental process in claim 11.
Dependent claim 17 further defines the type of methodology of the multi-building site layout generation of respective claim 11: “the plurality of behaviors comprises at least one of determining a separation between a building and an edge of the site or determining a separation between buildings,” which would be analogous to a person drawing to at least determine a separation between a building and an edge of the site or determine a separation between buildings on paper. Thus, claim 17 merely narrows the abstract idea identified as a mental process in claim 11.
Dependent claim 18 further defines the type of methodology of the multi-building site layout generation of respective claim 11: “the plurality of behaviors includes at least one of determining an alignment between a building and the site, determining an alignment between buildings, or determining a global orientation associated with the plurality of buildings,” which would be analogous to a person drawing to at least determine an alignment between a building and the site, an alignment between buildings, or determine a global orientation associated with all the buildings on paper. Thus, claim 18 merely narrows the abstract idea identified as a mental process in claim 11.
Dependent claim 19 further defines the type of methodology of the multi-building site layout generation of respective claim 11: “the layout further includes at least one of a plurality of building heights for the plurality of buildings, a plurality of building positions for the plurality of buildings, or a plurality of building orientations for the plurality of buildings,” which would be analogous to a person drawing to determine building heights, building positions, and building orientations on paper. Thus, claim 19 merely narrows the abstract idea identified as a mental process in claim 11.
v) Accordingly, claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e. an abstract idea) without anything significantly more.
Appropriate correction is required.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
6. Claims 1-3, 5-13, and 16-20 are rejected under 35 U.S.C. 102(a)(1) as being clearly anticipated by Xu, Xiaodong, Chenhuan Yin, Wei Wang, Ning Xu, Tianzhen Hong, and Qi Li. “Revealing Urban Morphology and Outdoor Comfort through Genetic Algorithm-Driven Urban Block Design in Dry and Hot Regions of China.” Sustainability 11.13, 3683 (2019): 1-19, hereafter Xu et al.
Regarding Claim 1: Xu et al discloses a computer-implemented method for generating a multi-building layout for a site (Xu et al. Page 6, Section 2.3.1, 1st paragraph, “This study focuses on a computer-aided optimization process based on the Rhino & Grasshopper platform with the help of parameterized design plugs-in such as Ladybug, Butterfly, Galapagos and OpenFOAM. In this study, a parameterized urban block is generalized with four basic building types using Rhinoceros software and then Grasshopper embedded in Rhinoceros is applied to link the urban block to the analysis software tools.” See also Figure 4 on Page 6 from Xu et al or below. Examiner notes: A computer-aided optimization process based on the Rhino & Grasshopper platform that creates an urban block layout of multiple buildings in Figure 4 from Xu et al discloses the claimed computer-implemented method for generating a multi-building layout for a site.), the method comprising:
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instantiating a plurality of agents representing a plurality of buildings located on the site based on a set of boundary conditions associated with the site; (Xu et al. Page 6, Section 2.2.3, 1st paragraph, “There are six dot-type blocks of 16-floor buildings, two plate-type blocks of 16-floor buildings, and several strip-type 6-floor residential buildings in the selected case.” See also Figure 4 on Page 6 from Xu et al or above. Page 6, Section 2.3.1, 1st paragraph, “In this study, a parameterized urban block is generalized with four basic building types using Rhinoceros software and then Grasshopper embedded in Rhinoceros is applied to link the urban block to the analysis software tools.” Page 7, Section 2.3.3, 1st paragraph, “The ideal research base has 5 × 5 grids (250 m × 250 m), thereby, cell boundary is 50 m × 50 m.” “[…]” “The optimization boundary condition is shown in Figure 5.” “[…]” “The final boundary is that the urban building density and plot ratio are fixed for the ideal model as 0.32 and 3.” See also Figure 5 on Page 7 from Xu et al or below. Examiner notes: The Rhinoceros software used to generalize a parameterized urban block of buildings, represented by virtual building models in Figure 4, from Xu et al discloses the claimed instantiated plurality of agents representing a plurality of buildings located on the site. The optimization boundary condition associated with the urban block in Figure 5 from Xu et al and other boundaries associated with the urban block in Figure 4 from Xu et al disclose the claimed set of boundary conditions associated with the site.)
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iteratively updating a plurality of states associated with the plurality of agents based on the set of boundary conditions and a plurality of behaviors associated with the plurality of agents; (Xu et al. Pages 3-4, Section 2.1, 1st paragraph, “Figure 1 shows the overview of this study, which consists of three phases. In the first phase, this study generates the urban block model and this study selected two models – ideal urban block model and actual urban block model. Also, this phase discusses the four generic building forms that generate the two models. The ideal model is applied for investigating optimization performance during urban block design, while the actual case model is used for validating the optimization performance in prefixed urban forms. The second phase proposed three parameters, building form, height, and open space layout, to optimize the urban block model with the aim of minimizing outdoor thermal comfort index, which is represented as UTCI. Additionally, this phase includes the model setup, climate condition, and the details of case study. In the last phase, this study outputs the simulation results and recommends the corresponding urban design strategies. See also Figure 1 on Page 4 from Xu et al or below. Page 6, Section 2.3.1, 1st paragraph, “In this study, a parameterized urban block is generalized with four basic building types using Rhinoceros software and then Grasshopper embedded in Rhinoceros is applied to link the urban block to the analysis software tools.” See also Figure 4 on Page 6 from Xu et al or above. Page 7, Section 2.3.3, 1st paragraph, “The ideal research base has 5 × 5 grids (250 m × 250 m), thereby, cell boundary is 50 m × 50 m.” “[…]” “The optimization boundary condition is shown in Figure 5.” “[…]” “The final boundary is that the urban building density and plot ratio are fixed for the ideal model as 0.32 and 3.” See also Figure 5 from Xu et al on Page 7 or above. Page 8, Section 3.1, 1st paragraph, “This study obtains the variation trend of the average UTCI (Universal Thermal Climate Index) of pillar, strip, dot, and courtyard-type blocks in Figure 6 and presents the poorest and best building block design with the four block types in Figure 7.” See also Figure 7 on Page 9 from Xu et al or below. Examiner notes: The urban morphology optimization illustrated in the overview of the study in Figure 1 from Xu et al is an iterative process of changes made to the states of the virtual building models, the buildings generalized by the Rhinoceros software, in each block type from the poorest to the best building block design in Figure 7 from Xu et al, which discloses the claimed iteratively updated plurality of states associated with the plurality of agents. The optimization boundary condition associated with the urban block in Figure 5 from Xu et al and other boundaries associated with the urban block in Figure 4 from Xu et al disclose the claimed set of boundary conditions associated with the site. The behaviors associated with the virtual building models in Figure 4 from Xu et al disclose the claimed plurality of behaviors associated with the plurality of agents.)
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and generating a layout for the site based on the plurality of states, wherein the layout comprises a plurality of building footprints for the plurality of buildings. (Xu et al. See Figure 4 on Page 6 from Xu et al or above and Figure 5 on Page 6 from Xu et al or above. Examiner notes: The block layout based on the states of the virtual building models, wherein the layout includes building footprints, in Figure 4 from Xu et al discloses the claimed generated layout for the site based on the plurality of states, wherein the layout comprises a plurality of building footprints for the plurality of buildings.)
Regarding Claim 2: Xu et al discloses the computer-implemented method of claim 1, wherein instantiating the plurality of agents comprises, for each agent included in the plurality of agents, determining an initial position and an initial orientation of a corresponding building located on the site. (Xu et al. Page 7, Section 2.3.3, 1st paragraph, “By analyzing, abstracting, and condensing the block textures and building forms of this base, we eventually select three basic building types with different fragmentation degrees: the dot basic-type (4-mass) of 1–5 floors, the strip basic-type (2-mass) of 6–10 floors, and the pillar basic-type (1-mass) of more than 10 floors. The ideal research base has 5 × 5 grids (250 m × 250 m), thereby, cell boundary is 50 m × 50 m. By conducting random mixed distribution of the three basic types, we explored the impacts of different combination modes on the average outdoor thermal comfort of the human body in the block.” “[…]” “For the building orientation, it could vary from 0 to 90◦ with a granularity of 5◦.” See also Figure 5 on Page 7 from Xu et al or above. Examiner notes: The initial position of a building on the block determined by random mixed distribution of the three basic types above and the cell boundary of 50 m × 50 m, and the initial orientation of a building on the block varying from 0 to 90◦ with a granularity of 5◦ for each virtual building model from Xu et al disclose the claimed determined initial position and initial orientation of a corresponding building located on the site for each agent included in the plurality of agents.)
Regarding Claim 3: Xu et al discloses the computer-implemented method of claim 1, wherein iteratively updating the plurality of states associated with the plurality of agents comprises updating a position of a building represented by an agent based on a separation between the building and one or more other buildings included in the plurality of buildings. (Xu et al. Page 7, Section 2.3.3, 1st paragraph, “By analyzing, abstracting, and condensing the block textures and building forms of this base, we eventually select three basic building types with different fragmentation degrees: the dot basic-type (4-mass) of 1–5 floors, the strip basic-type (2-mass) of 6–10 floors, and the pillar basic-type (1-mass) of more than 10 floors. The ideal research base has 5 × 5 grids (250 m × 250 m), thereby, cell boundary is 50 m × 50 m. By conducting random mixed distribution of the three basic types, we explored the impacts of different combination modes on the average outdoor thermal comfort of the human body in the block.” Page 8, Section 3.1, 1st paragraph, “This study obtains the variation trend of the average UTCI of pillar, strip, dot, and courtyard-type blocks in Figure 6 and presents the poorest and best building block design with the four block types in Figure 7.” See also Figure 7 on Page 9 from Xu et al or above. Page 8, Section 3.1, 2nd paragraph, “According to Figure 1, this study would like to output the urban block design parameter to figure out indicators of those parameters when the UTCI achieve the optimal solution, including street orientation, SVF, building height distribution, open space layout, respectively for urban block design parameters, and mean radiation temperature, average wind speed, and UTCI, respectively for urban climatic parameters.” See also Figure 1 on Page 4 from Xu et al or above. Examiner notes: The position of a building, represented by a virtual building model, that is updated by random mixed distribution of the three basic types above and the cell boundary of 50 m × 50 m in each block type from the poorest to the best building block design in Figure 7 from Xu et al discloses the claimed updated position of a building, represented by an agent. The open space layout from Xu et al is an arrangement of non-building areas between a building and an edge of the block or between buildings in each block type from the poorest to the best building block design in Figure 7 from Xu et al, which discloses the claimed separation between the building and one or more other buildings included in the plurality of buildings.)
Regarding Claim 5: Xu et al discloses the computer-implemented method of claim 1, wherein iteratively updating the plurality of states associated with the plurality of agents comprises updating an orientation of a building represented by an agent based on an alignment of the building with one or more entities associated with the layout. (Xu et al. Page 6, Section 2.3.2, 1st paragraph, “Along with this process, the Galapagos module, producing optimization process with a genetic algorithm, is applied to minimize UTCI as the optimization objective with optimization form parameters, which are building height, orientation, length, and width as the genes.” Page 7, Section 2.3.3, 1st paragraph, “By analyzing, abstracting, and condensing the block textures and building forms of this base, we eventually select three basic building types with different fragmentation degrees: the dot basic-type (4-mass) of 1–5 floors, the strip basic-type (2-mass) of 6–10 floors, and the pillar basic-type (1-mass) of more than 10 floors. The ideal research base has 5 × 5 grids (250 m × 250 m), thereby, cell boundary is 50 m × 50 m. By conducting random mixed distribution of the three basic types, we explored the impacts of different combination modes on the average outdoor thermal comfort of the human body in the block.” “[…]” “For the building orientation, it could vary from 0 to 90◦ with a granularity of 5◦.” See also Figure 5 on Page 7 from Xu et al or above. Page 8, Section 3.1, 1st paragraph, “This study obtains the variation trend of the average UTCI of pillar, strip, dot, and courtyard-type blocks in Figure 6 and presents the poorest and best building block design with the four block types in Figure 7.” See also Figure 7 on Page 9 from Xu et al or above. Examiner notes: The orientation of a building, represented by a virtual building model, that is updated to any number from 0 to 90◦ with a granularity of 5◦ in each block type from the poorest to the best building block design in Figure 7 from Xu et al discloses the claimed updated orientation of a building, represented by an agent. The way the buildings are positioned (random mixed distribution of the three basic types above and the cell boundary of 50 m × 50 m) and oriented (from 0 to 90◦ with a granularity of 5◦) relative to each other or relative to the block in each block type from the poorest to the best building block design in Figure 7 from Xu et al discloses the claimed alignment of the building with one or more entities associated with the layout.)
Regarding Claim 6: Xu et al discloses the computer-implemented method of claim 5, wherein the one or more entities comprise at least one of a second building that is adjacent to the building, a boundary of the site, or the plurality of buildings located on the site. (Xu et al. See Figure 7 on Page 9 from Xu et al or above. Examiner notes: Each building that is adjacent to another building, a boundary of the block, or multiple buildings on the block in each block type from the poorest to the best building block design in Figure 7 from Xu et al discloses the claimed at least one of a second building that is adjacent to the building, a boundary of the site, or the plurality of buildings located on the site.)
Regarding Claim 7: Xu et al discloses the computer-implemented method of claim 1, wherein iteratively updating the plurality of states associated with the plurality of agents comprises: determining a plurality of building positions and a plurality of building orientations included in the plurality of states; and adjusting a plurality of building dimensions included in the plurality of states based on the plurality of building positions, the plurality of building orientations, and the set of boundary conditions. (Xu et al. Page 7, Section 2.3.3, 1st paragraph, “By analyzing, abstracting, and condensing the block textures and building forms of this base, we eventually select three basic building types with different fragmentation degrees: the dot basic-type (4-mass) of 1–5 floors, the strip basic-type (2-mass) of 6–10 floors, and the pillar basic-type (1-mass) of more than 10 floors. The ideal research base has 5 × 5 grids (250 m × 250 m), thereby, cell boundary is 50 m × 50 m. By conducting random mixed distribution of the three basic types, we explored the impacts of different combination modes on the average outdoor thermal comfort of the human body in the block. The optimization boundary condition is shown in Figure 5. In this study, for the form parameter, building height was set as 3 m for each floor while the floor range was from 1 to 30. The granularity of length and width for each building was 5 m while those two parameters should be smaller than 50 m (basic size of cell). For the building orientation, it could vary from 0 to 90◦ with a granularity of 5◦.” Page 8, Section 3.1, 1st paragraph, “This study obtains the variation trend of the average UTCI of pillar, strip, dot, and courtyard-type blocks in Figure 6 and presents the poorest and best building block design with the four block types in Figure 7.” See also Figure 4 on Page 6 from Xu et al or above, Figure 5 on Page 7 from Xu et al or above, and Figure 7 on Page 9 from Xu et al or above. Examiner notes: The building positions determined by random mixed distribution of the three basic types above and the cell boundary of 50 m × 50 m and building orientations varying from 0 to 90◦ with a granularity of 5◦ in Figure 5 from Xu et al, included in the states of the virtual building models, in each block type from the poorest to the best building block design in Figure 7 from Xu et al disclose the claimed determined plurality of building positions and plurality of building orientations included in the plurality of states. The building dimensions in Figure 5 from Xu et al, included in the states of the virtual building models, that are adjusted (building height: set as 3 m for each floor while the floor range was from 1 to 30, building length: smaller than 50 m, and building width: smaller than 50 m) disclose the claimed adjusted plurality of building dimensions included in the plurality of states. The building positions and building orientations in Figure 5 from Xu et al in each block type from the poorest to the best building block design in Figure 7 from Xu et al, the optimization boundary condition in Figure 5 from Xu et al, and other boundaries associated with the urban block in Figure 4 from Xu et al disclose the claimed plurality of building positions, plurality of building orientations, and set of boundary conditions.)
Regarding Claim 8: Xu et al discloses the computer-implemented method of claim 1, wherein the plurality of behaviors includes at least one of determining a separation between a building and an edge of the site or determining a separation between buildings. (Xu et al. Page 8, Section 3.1, 1st paragraph, “This study obtains the variation trend of the average UTCI of pillar, strip, dot, and courtyard-type blocks in Figure 6 and presents the poorest and best building block design with the four block types in Figure 7.” See also Figure 7 on Page 9 from Xu et al or above. Pages 11-12, Section 3.1.1.d, 1st paragraph, “The grid of the research base is 5 m × 5 m and by naming grid space in the order from 1 to 25, we can obtain the open space distribution of the four block types as shown in Figure 11. Along with the optimization of outdoor thermal comfort, the open spaces of different blocks finally lie at different locations. The open spaces of the pillar-type block are mainly distributed in the north, south, and middle of the land parcel, and also the pillar-type shares the biggest area of open space. The open spaces of the strip-type block are mainly distributed in the west and middle of the base. The open spaces of the dot-type block are mainly distributed in the south and in the north. The open spaces of the courtyard-type block are mainly distributed in the north, and the west-south. In addition, in the better building layouts, there are generally higher buildings around the open spaces for screening, thus bringing shade to the open spaces.” See also Figure 11 on Page 12 from Xu et al or below. Examiner notes: The open space (grey area in Figure 11) layout from Xu et al, determined by naming grid space in the order from 1 to 25 for the 5 m x 5 m grid of the research base for the urban block of buildings, is an arrangement of non-building areas between a building and an edge of the block or between buildings in each block type from the poorest to the best building block design in Figure 7 from Xu et al, which discloses the claimed determined separation between a building and an edge of the site or separation between buildings.)
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Regarding Claim 9: Xu et al discloses the computer-implemented method of claim 1, wherein the plurality of behaviors includes at least one of determining an alignment between a building and the site, determining an alignment between buildings, or determining a global orientation associated with the plurality of buildings. (Xu et al. Page 7, Section 2.3.3, 1st paragraph, “By analyzing, abstracting, and condensing the block textures and building forms of this base, we eventually select three basic building types with different fragmentation degrees: the dot basic-type (4-mass) of 1–5 floors, the strip basic-type (2-mass) of 6–10 floors, and the pillar basic-type (1-mass) of more than 10 floors. The ideal research base has 5 × 5 grids (250 m × 250 m), thereby, cell boundary is 50 m × 50 m. By conducting random mixed distribution of the three basic types, we explored the impacts of different combination modes on the average outdoor thermal comfort of the human body in the block.” “[…]” “For the building orientation, it could vary from 0 to 90◦ with a granularity of 5◦.” See also Figure 5 on Page 7 from Xu et al or above. Page 8, Section 3.1, 1st paragraph, “This study obtains the variation trend of the average UTCI of pillar, strip, dot, and courtyard-type blocks in Figure 6 and presents the poorest and best building block design with the four block types in Figure 7.” See also Figure 7 on Page 9 from Xu et al or above. Examiner notes: The way the buildings are positioned (random mixed distribution of the three basic types above and the cell boundary of 50 m × 50 m) and oriented (from 0 to 90◦ with a granularity of 5◦) relative to the block or relative to each other in each block type from the poorest to the best building block design in Figure 7 from Xu et al discloses the claimed determined alignment between a building and the site or alignment between buildings. The building orientation varying from 0 to 90◦ with a granularity of 5◦ in Figure 5 from Xu et al discloses the claimed global orientation associated with the plurality of buildings.)
Regarding Claim 10: Xu et al discloses the computer-implemented method of claim 1, wherein the set of boundary conditions includes at least one of a site boundary, a setback requirement, a minimum separation between buildings, a maximum separation between buildings, a minimum building size, a maximum building size, a minimum building dimension, a maximum building dimension, or a number of buildings to place on the layout. (Xu et al. Page 7, Section 2.3.3, 1st paragraph, “The ideal research base has 5 × 5 grids (250 m × 250 m), thereby, cell boundary is 50 m × 50 m. By conducting random mixed distribution of the three basic types, we explored the impacts of different combination modes on the average outdoor thermal comfort of the human body in the block. The optimization boundary condition is shown in Figure 5. In this study, for the form parameter, building height was set as 3 m for each floor while the floor range was from 1 to 30. The granularity of length and width for each building was 5 m while those two parameters should be smaller than 50 m (basic size of cell).” See also Figure 4 on Page 6 from Xu et al or above and Figure 5 on Page 7 from Xu et al or above. Examiner notes: The physical boundary of 250 m x 250 m of the block in Figure 5 from Xu et al discloses the claimed at least one of a site boundary. The nearest building, represented as a white virtual building model, to a block boundary, represented as one of the four black sides of a square on which the virtual building model is placed, in Figure 4 from Xu et al discloses the claimed setback requirement. The nearest building to another building (both are represented as white virtual building models) in Figure 4 from Xu et al discloses the claimed minimum separation between buildings. The furthest building to another building (both are represented as white virtual building models) in Figure 4 from Xu et al discloses the claimed maximum separation between buildings. The smallest building, represented as a white virtual building model, in Figure 4 from Xu et al discloses the claimed minimum building size. The largest building, represented as a white virtual building model, in Figure 4 from Xu et al discloses the claimed maximum building size. The building height set as 3 m for each floor while the floor range was from 1 to 30 and the building length and width being smaller than 50 m from Xu et al disclose the claimed minimum building dimension and maximum building dimension. Forty-one buildings, represented as white virtual building models, on the block layout, represented as a square with four black sides, in Figure 4 from Xu et al disclose the claimed number of buildings to place on the layout.)
Regarding Claim 11: Xu et al discloses one or more non-transitory computer-readable media storing instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of: (Xu et al. Page 6, Section 2.3.1, 1st paragraph, “This study focuses on a computer-aided optimization process based on the Rhino & Grasshopper platform with the help of parameterized design plugs-in such as Ladybug, Butterfly, Galapagos and OpenFOAM. Examiner notes: The terms “non-transitory computer-readable medium” and “processor” are not explicitly defined in the specification. Under the broadest reasonable interpretation consistent with the specification (MPEP § 2111), “non-transitory computer-readable medium” comprises any part of a computer that holds data or instructions in a physical, persistent form for the computer to read, retrieve, and use, and “processor” comprises any component in a computer that carries out instructions from software. Xu et al discloses a computer-aided optimization process based on the Rhino & Grasshopper platform with the help of parameterized design plugs-in such as Ladybug, Butterfly, Galapagos and OpenFOAM (Xu et al. Page 6, Section 2.3.1, 1st paragraph), which meets the limitations of “one or more non-transitory computer-readable media” and “one or more processors” under this interpretation.)
instantiating a plurality of agents representing a plurality of buildings located on a site based on a set of boundary conditions associated with the site; (Xu et al. Page 6, Section 2.2.3, 1st paragraph, “There are six dot-type blocks of 16-floor buildings, two plate-type blocks of 16-floor buildings, and several strip-type 6-floor residential buildings in the selected case.” See also Figure 4 on Page 6 from Xu et al or above. Page 6, Section 2.3.1, 1st paragraph, “In this study, a parameterized urban block is generalized with four basic building types using Rhinoceros software and then Grasshopper embedded in Rhinoceros is applied to link the urban block to the analysis software tools.” Page 7, Section 2.3.3, 1st paragraph, “The ideal research base has 5 × 5 grids (250 m × 250 m), thereby, cell boundary is 50 m × 50 m.” “[…]” “The optimization boundary condition is shown in Figure 5.” “[…]” “The final boundary is that the urban building density and plot ratio are fixed for the ideal model as 0.32 and 3.” See also Figure 5 on Page 7 from Xu et al or above. Examiner notes: The Rhinoceros software used to generalize a parameterized urban block of buildings, represented by virtual building models in Figure 4, from Xu et al discloses the claimed instantiated plurality of agents representing a plurality of buildings located on the site. The optimization boundary condition associated with the urban block in Figure 5 and other boundaries associated with the urban block in Figure 4 from Xu et al disclose the claimed set of boundary conditions associated with the site.)
iteratively updating a plurality of states associated with the plurality of agents based on the set of boundary conditions and a plurality of behaviors associated with the plurality of agents; (Xu et al. Pages 3-4, Section 2.1, 1st paragraph, “Figure 1 shows the overview of this study, which consists of three phases. In the first phase, this study generates the urban block model and this study selected two models – ideal urban block model and actual urban block model. Also, this phase discusses the four generic building forms that generate the two models. The ideal model is applied for investigating optimization performance during urban block design, while the actual case model is used for validating the optimization performance in prefixed urban forms. The second phase proposed three parameters, building form, height, and open space layout, to optimize the urban block model with the aim of minimizing outdoor thermal comfort index, which is represented as UTCI. Additionally, this phase includes the model setup, climate condition, and the details of case study. In the last phase, this study outputs the simulation results and recommends the corresponding urban design strategies. See also Figure 1 on Page 4 from Xu et al or above. Page 6, Section 2.3.1, 1st paragraph, “In this study, a parameterized urban block is generalized with four basic building types using Rhinoceros software and then Grasshopper embedded in Rhinoceros is applied to link the urban block to the analysis software tools.” See also Figure 4 on Page 6 from Xu et al or above. Page 7, Section 2.3.3, 1st paragraph, “The ideal research base has 5 × 5 grids (250 m × 250 m), thereby, cell boundary is 50 m × 50 m.” “[…]” “The optimization boundary condition is shown in Figure 5.” “[…]” “The final boundary is that the urban building density and plot ratio are fixed for the ideal model as 0.32 and 3.” See also Figure 5 on Page 7 from Xu et al or above. Page 8, Section 3.1, 1st paragraph, “This study obtains the variation trend of the average UTCI (Universal Thermal Climate Index) of pillar, strip, dot, and courtyard-type blocks in Figure 6 and presents the poorest and best building block design with the four block types in Figure 7.” See also Figure 7 on Page 9 from Xu et al or above. Examiner notes: The urban morphology optimization illustrated in the overview of the study in Figure 1 from Xu et al is an iterative process of changes made to the states of the virtual building models, the buildings generalized by the Rhinoceros software, in each block type from the poorest to the best building block design in Figure 7 from Xu et al, which discloses the claimed iteratively updated plurality of states associated with the plurality of agents. The optimization boundary condition associated with the urban block in Figure 5 and other boundaries associated with the urban block in Figure 4 from Xu et al disclose the claimed set of boundary conditions associated with the site. The behaviors associated with the virtual building models in Figure 4 from Xu et al disclose the claimed plurality of behaviors associated with the plurality of agents.)
and generating a layout for the site based on the plurality of states, wherein the layout comprises a plurality of building footprints for the plurality of buildings. (Xu et al. See Figure 4 on Page 6 from Xu et al or above and Figure 5 on Page 6 from Xu et al or above. Examiner notes: The block layout based on the states of the virtual building models, wherein the layout includes building footprints, in Figure 4 from Xu et al discloses the claimed generated layout for the site based on the plurality of states, wherein the layout comprises a plurality of building footprints for the plurality of buildings.)
Regarding Claim 12: Xu et al discloses the one or more non-transitory computer-readable media of claim 11, wherein instantiating the plurality of agents comprises, for each agent included in the plurality of agents, determining an initial position and an initial orientation of a corresponding building on the site. (Xu et al. Page 7, Section 2.3.3, 1st paragraph, “By analyzing, abstracting, and condensing the block textures and building forms of this base, we eventually select three basic building types with different fragmentation degrees: the dot basic-type (4-mass) of 1–5 floors, the strip basic-type (2-mass) of 6–10 floors, and the pillar basic-type (1-mass) of more than 10 floors. The ideal research base has 5 × 5 grids (250 m × 250 m), thereby, cell boundary is 50 m × 50 m. By conducting random mixed distribution of the three basic types, we explored the impacts of different combination modes on the average outdoor thermal comfort of the human body in the block.” “[…]” “For the building orientation, it could vary from 0 to 90◦ with a granularity of 5◦.” See also Figure 5 on Page 7 from Xu et al or above. Examiner notes: The initial position of a building on the block determined by random mixed distribution of the three basic types above and the cell boundary of 50 m × 50 m, and the initial orientation of a building on the block varying from 0 to 90◦ with a granularity of 5◦ for each virtual building model from Xu et al disclose the claimed initial position and initial orientation of a corresponding building on the site for each agent included in the plurality of agents.)
Regarding Claim 13: Xu et al discloses the one or more non-transitory computer-readable media of claim 12, wherein the initial position and the initial orientation are determined based on at least one of the set of boundary conditions or a set of random values. (Xu et al. Page 7, Section 2.3.3, 1st paragraph, “By analyzing, abstracting, and condensing the block textures and building forms of this base, we eventually select three basic building types with different fragmentation degrees: the dot basic-type (4-mass) of 1–5 floors, the strip basic-type (2-mass) of 6–10 floors, and the pillar basic-type (1-mass) of more than 10 floors. The ideal research base has 5 × 5 grids (250 m × 250 m), thereby, cell boundary is 50 m × 50 m. By conducting random mixed distribution of the three basic types, we explored the impacts of different combination modes on the average outdoor thermal comfort of the human body in the block.” “[…]” “For the building orientation, it could vary from 0 to 90◦ with a granularity of 5◦.” See also Figure 5 on Page 7 from Xu et al or above. Examiner notes: The initial position of a building on the block determined by random mixed distribution of the three basic types above, the physical boundary of 250 m x 250 m, and the cell boundary of 50 m × 50 m (Optimization Boundary Condition in Figure 5), and the initial orientation of a building on the block varying from 0 to 90◦ with a granularity of 5◦ (Optimization Boundary Condition in Figure 5) for each virtual building model from Xu et al disclose the claimed initial position and initial orientation that are determined based on at least one of the set of boundary conditions or a set of random values.)
Regarding Claim 16: Xu et al discloses the one or more non-transitory computer-readable media of claim 11, wherein iteratively updating the plurality of states associated with the plurality of agents comprises adjusting a plurality of dimensions for the plurality of buildings based on the set of boundary conditions, a plurality of building positions included in the plurality of states, and a plurality of building orientations included in the plurality of states. (Xu et al. Page 7, Section 2.3.3, 1st paragraph, “By analyzing, abstracting, and condensing the block textures and building forms of this base, we eventually select three basic building types with different fragmentation degrees: the dot basic-type (4-mass) of 1–5 floors, the strip basic-type (2-mass) of 6–10 floors, and the pillar basic-type (1-mass) of more than 10 floors. The ideal research base has 5 × 5 grids (250 m × 250 m), thereby, cell boundary is 50 m × 50 m. By conducting random mixed distribution of the three basic types, we explored the impacts of different combination modes on the average outdoor thermal comfort of the human body in the block. The optimization boundary condition is shown in Figure 5. In this study, for the form parameter, building height was set as 3 m for each floor while the floor range was from 1 to 30. The granularity of length and width for each building was 5 m while those two parameters should be smaller than 50 m (basic size of cell). For the building orientation, it could vary from 0 to 90◦ with a granularity of 5◦.” Page 8, Section 3.1, 1st paragraph, “This study obtains the variation trend of the average UTCI of pillar, strip, dot, and courtyard-type blocks in Figure 6 and presents the poorest and best building block design with the four block types in Figure 7.” See also Figure 4 on Page 6 from Xu et al or above, Figure 5 on Page 7 from Xu et al or above, and Figure 7 on Page 9 from Xu et al or above. Examiner notes: The building dimensions in Figure 5 from Xu et al, included in the states of the virtual building models, that are adjusted (building height: set as 3 m for each floor while the floor range was from 1 to 30, building length: smaller than 50 m, and building width: smaller than 50 m) disclose the claimed adjusted plurality of building dimensions included in the plurality of states. The optimization boundary condition in Figure 5 from Xu et al and other boundaries associated with the urban block in Figure 4 from Xu et al, the building positions determined by random mixed distribution of the three basic types above and the cell boundary of 50 m × 50 m, and the building orientations varying from 0 to 90◦ with a granularity of 5◦ in Figure 5 from Xu et al in each block type from the poorest to the best building block design in Figure 7 from Xu et al disclose the claimed set of boundary conditions, plurality of building positions included in the plurality of states, and plurality of building orientations included in the plurality of states.)
Regarding Claim 17: Xu et al discloses the one or more non-transitory computer-readable media of claim 11, wherein the plurality of behaviors comprises at least one of determining a separation between a building and an edge of the site or determining a separation between buildings. (Xu et al. Page 8, Section 3.1, 1st paragraph, “This study obtains the variation trend of the average UTCI of pillar, strip, dot, and courtyard-type blocks in Figure 6 and presents the poorest and best building block design with the four block types in Figure 7.” See also Figure 7 on Page 9 from Xu et al or above. Pages 11-12, Section 3.1.1.d, 1st paragraph, “The grid of the research base is 5 m × 5 m and by naming grid space in the order from 1 to 25, we can obtain the open space distribution of the four block types as shown in Figure 11. Along with the optimization of outdoor thermal comfort, the open spaces of different blocks finally lie at different locations. The open spaces of the pillar-type block are mainly distributed in the north, south, and middle of the land parcel, and also the pillar-type shares the biggest area of open space. The open spaces of the strip-type block are mainly distributed in the west and middle of the base. The open spaces of the dot-type block are mainly distributed in the south and in the north. The open spaces of the courtyard-type block are mainly distributed in the north, and the west-south. In addition, in the better building layouts, there are generally higher buildings around the open spaces for screening, thus bringing shade to the open spaces.” See also Figure 11 on Page 12 from Xu et al or above. Examiner notes: The open space (grey area in Figure 11) layout from Xu et al, determined by naming grid space in the order from 1 to 25 for the 5 m x 5 m grid of the research base for the urban block of buildings, is an arrangement of non-building areas between a building and an edge of the block or between buildings in each block type from the poorest to the best building block design in Figure 7 from Xu et al, which discloses the claimed determined separation between a building and an edge of the site or separation between buildings.)
Regarding Claim 18: Xu et al discloses the one or more non-transitory computer-readable media of claim 11, wherein the plurality of behaviors includes at least one of determining an alignment between a building and the site, determining an alignment between buildings, or determining a global orientation associated with the plurality of buildings. (Xu et al. Page 7, Section 2.3.3, 1st paragraph, “By analyzing, abstracting, and condensing the block textures and building forms of this base, we eventually select three basic building types with different fragmentation degrees: the dot basic-type (4-mass) of 1–5 floors, the strip basic-type (2-mass) of 6–10 floors, and the pillar basic-type (1-mass) of more than 10 floors. The ideal research base has 5 × 5 grids (250 m × 250 m), thereby, cell boundary is 50 m × 50 m. By conducting random mixed distribution of the three basic types, we explored the impacts of different combination modes on the average outdoor thermal comfort of the human body in the block.” “[…]” “For the building orientation, it could vary from 0 to 90◦ with a granularity of 5◦.” See also Figure 5 on Page 7 from Xu et al or above. Page 8, Section 3.1, 1st paragraph, “This study obtains the variation trend of the average UTCI of pillar, strip, dot, and courtyard-type blocks in Figure 6 and presents the poorest and best building block design with the four block types in Figure 7.” See also Figure 7 on Page 9 from Xu et al or above. Examiner notes: The way the buildings are positioned (random mixed distribution of the three basic types above and the cell boundary of 50 m × 50 m) and oriented (from 0 to 90◦ with a granularity of 5◦) relative to the block or relative to each other in each block type from the poorest to the best building block design in Figure 7 from Xu et al discloses the claimed determined alignment between a building and the site or alignment between buildings. The building orientation varying from 0 to 90◦ with a granularity of 5◦ in each block type from the poorest to the best building block design in Figure 7 from Xu et al discloses the claimed global orientation associated with the plurality of buildings.)
Regarding Claim 19: Xu et al discloses the one or more non-transitory computer-readable media of claim 11, wherein the layout further includes at least one of a plurality of building heights for the plurality of buildings, a plurality of building positions for the plurality of buildings, or a plurality of building orientations for the plurality of buildings. (Xu et al. Page 7, Section 2.3.3, 1st paragraph, “By analyzing, abstracting, and condensing the block textures and building forms of this base, we eventually select three basic building types with different fragmentation degrees: the dot basic-type (4-mass) of 1–5 floors, the strip basic-type (2-mass) of 6–10 floors, and the pillar basic-type (1-mass) of more than 10 floors. The ideal research base has 5 × 5 grids (250 m × 250 m), thereby, cell boundary is 50 m × 50 m. By conducting random mixed distribution of the three basic types, we explored the impacts of different combination modes on the average outdoor thermal comfort of the human body in the block.” “[…]” “In this study, for the form parameter, building height was set as 3 m for each floor while the floor range was from 1 to 30.” “[…]” “For the building orientation, it could vary from 0 to 90◦ with a granularity of 5◦.” See also Figure 5 on Page 7 from Xu et al or above. Examiner notes: The building heights for the buildings in Figure 5 from Xu et al disclose the claimed plurality of building heights for the plurality of buildings. The building positions and building orientations for the buildings in Figure 5 from Xu et al disclose the claimed plurality of building positions for the plurality of buildings and the claimed plurality of building orientations for the plurality of buildings.)
Regarding Claim 20: Xu et al discloses a system, comprising:
one or more memories that store instructions, and one or more processors that are coupled to the one or more memories and, when executing the instructions, are configured to perform the steps of: (Xu et al. Page 6, Section 2.3.1, 1st paragraph, “This study focuses on a computer-aided optimization process based on the Rhino & Grasshopper platform with the help of parameterized design plugs-in such as Ladybug, Butterfly, Galapagos and OpenFOAM. Examiner notes: The terms “memory” and “processor” are not explicitly defined in the specification. Under the broadest reasonable interpretation consistent with the specification (MPEP § 2111), “memory” comprises any part of a computer in which data or program instructions can be stored for retrieval, and “processor” comprises any component in a computer that carries out instructions from software. Xu et al discloses a computer-aided optimization process based on the Rhino & Grasshopper platform with the help of parameterized design plugs-in such as Ladybug, Butterfly, Galapagos and OpenFOAM (Xu et al. Page 6, Section 2.3.1, 1st paragraph), which meets the limitations of “one or more memories” and “one or more processors” under this interpretation.)
instantiating a plurality of agents representing a plurality of buildings located on a site based on a set of boundary conditions associated with the site; (Xu et al. Page 6, Section 2.2.3, 1st paragraph, “There are six dot-type blocks of 16-floor buildings, two plate-type blocks of 16-floor buildings, and several strip-type 6-floor residential buildings in the selected case.” See also Figure 4 on Page 6 from Xu et al or above. Page 6, Section 2.3.1, 1st paragraph, “In this study, a parameterized urban block is generalized with four basic building types using Rhinoceros software and then Grasshopper embedded in Rhinoceros is applied to link the urban block to the analysis software tools.” Page 7, Section 2.3.3, 1st paragraph, “The ideal research base has 5 × 5 grids (250 m × 250 m), thereby, cell boundary is 50 m × 50 m.” “[…]” “The optimization boundary condition is shown in Figure 5.” “[…]” “The final boundary is that the urban building density and plot ratio are fixed for the ideal model as 0.32 and 3.” See also Figure 5 on Page 7 from Xu et al or above. Examiner notes: The Rhinoceros software used to generalize a parameterized urban block of buildings, represented by virtual building models in Figure 4, from Xu et al discloses the claimed instantiated plurality of agents representing a plurality of buildings located on the site. The optimization boundary condition associated with the urban block in Figure 5 and other boundaries associated with the urban block in Figure 4 from Xu et al disclose the claimed set of boundary conditions associated with the site.)
iteratively updating a plurality of states associated with the plurality of agents based on the set of boundary conditions and a plurality of behaviors associated with the plurality of agents; (Xu et al. Pages 3-4, Section 2.1, 1st paragraph, “Figure 1 shows the overview of this study, which consists of three phases. In the first phase, this study generates the urban block model and this study selected two models – ideal urban block model and actual urban block model. Also, this phase discusses the four generic building forms that generate the two models. The ideal model is applied for investigating optimization performance during urban block design, while the actual case model is used for validating the optimization performance in prefixed urban forms. The second phase proposed three parameters, building form, height, and open space layout, to optimize the urban block model with the aim of minimizing outdoor thermal comfort index, which is represented as UTCI. Additionally, this phase includes the model setup, climate condition, and the details of case study. In the last phase, this study outputs the simulation results and recommends the corresponding urban design strategies. See also Figure 1 on Page 4 from Xu et al or above. Page 6, Section 2.3.1, 1st paragraph, “In this study, a parameterized urban block is generalized with four basic building types using Rhinoceros software and then Grasshopper embedded in Rhinoceros is applied to link the urban block to the analysis software tools.” See also Figure 4 on Page 6 from Xu et al or above. Page 7, Section 2.3.3, 1st paragraph, “The ideal research base has 5 × 5 grids (250 m × 250 m), thereby, cell boundary is 50 m × 50 m.” “[…]” “The optimization boundary condition is shown in Figure 5.” “[…]” “The final boundary is that the urban building density and plot ratio are fixed for the ideal model as 0.32 and 3.” See also Figure 5 on Page 7 from Xu et al or above. Page 8, Section 3.1, 1st paragraph, “This study obtains the variation trend of the average UTCI (Universal Thermal Climate Index) of pillar, strip, dot, and courtyard-type blocks in Figure 6 and presents the poorest and best building block design with the four block types in Figure 7.” See also Figure 7 on Page 9 from Xu et al or above. Examiner notes: The urban morphology optimization illustrated in the overview of the study in Figure 1 from Xu et al is an iterative process of changes made to the states of the virtual building models, the buildings generalized by the Rhinoceros software, in each block type from the poorest to the best building block design in Figure 7 from Xu et al, which discloses the claimed iteratively updated plurality of states associated with the plurality of agents. The optimization boundary condition associated with the urban block in Figure 5 and other boundaries associated with the urban block in Figure 4 from Xu et al disclose the claimed set of boundary conditions associated with the site. The behaviors associated with the virtual building models in Figure 4 from Xu et al disclose the claimed plurality of behaviors associated with the plurality of agents.)
and generating a layout for the site based on the plurality of states, wherein the layout comprises a plurality of building footprints for the plurality of buildings. (Xu et al. See Figure 4 on Page 6 from Xu et al or above and Figure 5 on Page 6 from Xu et al or above. Examiner notes: The block layout based on the states of the virtual building models, wherein the layout includes building footprints, in Figure 4 from Xu et al discloses the claimed generated layout for the site based on the plurality of states, wherein the layout comprises a plurality of building footprints for the plurality of buildings.)
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the
claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103(a) are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or non-obviousness.
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
7. Claims 4 and 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Xu, Xiaodong, Chenhuan Yin, Wei Wang, Ning Xu, Tianzhen Hong, and Qi Li. “Revealing Urban Morphology and Outdoor Comfort through Genetic Algorithm-Driven Urban Block Design in Dry and Hot Regions of China.” Sustainability 11.13, 3683 (2019): 1-19, hereafter Xu et al, in view of Zhang, Aishe, Cuilan Gao, and Ling Zhang. “Numerical simulation of the wind field around different building arrangements.” Journal of Wind Engineering and Industrial Aerodynamics 93.12 (2005): 891-904, hereafter Zhang et al.
Regarding Claim 4: Xu et al discloses the computer-implemented method of claim 3. (Xu et al. Page 6, Section 2.3.1, 1st paragraph, “This study focuses on a computer-aided optimization process based on the Rhino & Grasshopper platform with the help of parameterized design plugs-in such as Ladybug, Butterfly, Galapagos and OpenFOAM. In this study, a parameterized urban block is generalized with four basic building types using Rhinoceros software and then Grasshopper embedded in Rhinoceros is applied to link the urban block to the analysis software tools.” See also Figure 4 on Page 6 from Xu et al or above. Examiner notes: A computer-aided optimization process based on the Rhino & Grasshopper platform that creates an urban block layout of multiple buildings in Figure 4 from Xu et al discloses the claimed computer-implemented method of claim 3.)
Xu et al does not explicitly disclose details about building position updates, wherein the position of the building is updated via a force vector that is determined based on the separation between the building and the one or more other buildings.
However, Zhang et al discloses, in the analogous art area of simulation, the position of the building updated via a force vector that is determined based on the separation between the building and the one or more other buildings. (Zhang et al. Page 902, Section 4, 5th paragraph - 8th paragraph, “Figs. 6–8 show the normalized velocity fields at the pedestrian level of 2m from the ground for Schemes I, II and III, respectively, for the S–N (South) wind direction. As the wind blows against the broad sides of buildings, it generates very large and strong horseshoe vortices. This is the reason why the wind in front of the buildings at the pedestrian level blows downward and away from the buildings.” “[…]” “By integrating the velocity field over all the alleyways’ area, an increase of 25.6% for the general velocity for Scheme II is produced as compared to that for Scheme I, but about a reduction of 7.9% is obtained in comparison with the velocity for Scheme III.
For the SE–NW (Southeast) wind direction, the velocity fields at 2m level above the ground for Schemes I, II and III are shown in Figs. 9–11, respectively, which depict the effect of wind direction on the velocity distribution. By integrating the velocity over all the alleyways’ area, the increase of 132.3% for Scheme I, 112.8% for Scheme II, and 100.9% for Scheme III in this wind direction as compared to the corresponding situations for the S–N wind are produced. For the SE–NW wind, the overall velocity magnitude increase of 13.7% and 3.8% for the overall velocity for Scheme III by comparison with Schemes I and II, respectively, are obtained.
In the summer, the S–N and SE–NW wind prevails on the site. By comparing Figs. 6–11, it can be seen that the staggered group arrangement (Scheme III) helps to introduce more wind into the site in the two wind directions.” See also Fig. 1 on Page 893 from Zhang et al or below and Figs. 6-11 on Pages 899-802 from Zhang et al or below. Examiner notes: The position of a building in each scheme in Fig. 1 updated (from Scheme I to Scheme II and Scheme III) via a force vector (wind speed and wind direction) determined based on the distance between the building and one or more other buildings in each scheme in Figs. 6-11 from Zhang et al discloses the claimed position of the building updated via a force vector that is determined based on the separation between the building and the one or more other buildings.)
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It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to utilize the force vector as per Zhang et al for the method in Xu et al because it would allow for “a numerical simulation for evaluating the wind field under different building arrangements and wind conditions” (Zhang et al. Page 903, Section 5, 1st paragraph) whereby “computational results are generally in good agreement with the experimental data for the locations experimentally tested. The results also show that the numerical method is a relatively more economical and faster tool to evaluate the wind environment.” (Zhang et al. Page 903, Section 5, 1st paragraph)
Regarding Claim 14: Xu et al discloses the one or more non-transitory computer-readable media of claim 11. (Xu et al. Page 6, Section 2.3.1, 1st paragraph, “This study focuses on a computer-aided optimization process based on the Rhino & Grasshopper platform with the help of parameterized design plugs-in such as Ladybug, Butterfly, Galapagos and OpenFOAM. Examiner notes: The terms “non-transitory computer-readable medium” and “processor” are not explicitly defined in the specification. Under the broadest reasonable interpretation consistent with the specification (MPEP § 2111), “non-transitory computer-readable medium” comprises any part of a computer that holds data or instructions in a physical, persistent form for the computer to read, retrieve, and use, and “processor” comprises any component in a computer that carries out instructions from software. Xu et al discloses a computer-aided optimization process based on the Rhino & Grasshopper platform with the help of parameterized design plugs-in such as Ladybug, Butterfly, Galapagos and OpenFOAM (Xu et al. Page 6, Section 2.3.1, 1st paragraph), which meets the limitations of “one or more non-transitory computer-readable media” and “one or more processors” under this interpretation.)
Xu et al does not explicitly disclose details about the process of iteratively updating the plurality of states associated with the plurality of agents, wherein iteratively updating the plurality of states associated with the plurality of agents comprises: computing a force vector associated with a building based on the plurality of states, the plurality of behaviors, and the set of boundary conditions; and updating at least one of a position of the building or an orientation of the building based on the force vector.
However, Zhang et al discloses, in the analogous art area of simulation, the process of iteratively updating the plurality of states associated with the plurality of agents that comprises: computing a force vector associated with a building based on the plurality of states, the plurality of behaviors, and the set of boundary conditions; (Zhang et al. Page 897, Section 4, 1st paragraph and 4th paragraph, “In this section, the velocity fields around the buildings for all the schemes are presented.”
“[…]”
“In Figs. 4 and 5, the similar comparisons of numerical predictions with the experimental results (the vertical profile variations of the velocity magnitude at
different points as shown in Fig. 1) for Schemes II and III in the two wind directions (S-N and SE-NW) are shown, respectively.” See also Fig. 1 on Page 893 from Zhang et al or above and Fig. 5 on Page 899 from Zhang et al or below. Examiner notes: The computed force vector (wind speed and wind direction) associated with a building of Scheme III in Fig. 5 based on the plurality of states (the building positions, building orientations, and building dimensions of Scheme III in Fig. 1), the plurality of behaviors (distances between buildings of Scheme III in Fig. 1), and the set of boundary conditions (the smallest building dimension of Scheme III in Fig. 1) from Zhang et al disclose the claimed computed force vector associated with a building based on the plurality of states, the plurality of behaviors, and the set of boundary conditions.)
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and updating at least one of a position of the building or an orientation of the building based on the force vector. (Zhang et al. See Fig. 1 on Page 893 from Zhang et al or above and Figs. 6-11 on Pages 899-802 from Zhang et al or above. Examiner notes: The position of the building in each scheme in Fig. 1 updated (from Scheme I to Scheme II and Scheme III) based on the force vector (wind speed and wind direction) in Figs. 6-11 from Zhang et al discloses the claimed at least one of an updated position of the building or an updated orientation of the building based on the force vector.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to utilize the computed force vector as per Zhang et al for the method in Xu et al because it would allow for “a numerical simulation for evaluating the wind field under different building arrangements and wind conditions” (Zhang et al. Page 903, Section 5, 1st paragraph) whereby “by comparing different building schemes, it is found that the wind field depends strongly on the building layout and the wind direction. Scheme III (the staggered group arrangement) helps to introduce more wind into the site in the two wind directions for S–N and SE–NW wind directions. Consequently, Scheme III can provide a good wind environment and potential to use natural ventilation.” (Zhang et al. Page 903, Section 5, 2nd paragraph)
Regarding Claim 15: Xu et al discloses the one or more non-transitory computer-readable media of claim 14. (Xu et al. Page 6, Section 2.3.1, 1st paragraph, “This study focuses on a computer-aided optimization process based on the Rhino & Grasshopper platform with the help of parameterized design plugs-in such as Ladybug, Butterfly, Galapagos and OpenFOAM. Examiner notes: The terms “non-transitory computer-readable medium” and “processor” are not explicitly defined in the specification. Under the broadest reasonable interpretation consistent with the specification (MPEP § 2111), “non-transitory computer-readable medium” comprises any part of a computer that holds data or instructions in a physical, persistent form for the computer to read, retrieve, and use, and “processor” comprises any component in a computer that carries out instructions from software. Xu et al discloses a computer-aided optimization process based on the Rhino & Grasshopper platform with the help of parameterized design plugs-in such as Ladybug, Butterfly, Galapagos and OpenFOAM (Xu et al. Page 6, Section 2.3.1, 1st paragraph), which meets the limitations of “one or more non-transitory computer-readable media” and “one or more processors” under this interpretation.)
Xu et al does not explicitly disclose details about the process of computing the force vector, wherein computing the force vector comprises dampening the force vector based on a number of iterative updates to the plurality of states.
However, Zhang et al discloses, in the analogous art area of simulation, the process of computing the force vector that comprises dampening the force vector based on a number of iterative updates to the plurality of states. (Zhang et al. Page 897, Section 3, 7th paragraph, “An iterative procedure is used for the solution of the discretization equations. The finite difference linear equations (inner iteration) are solved by Strong Implicit Procedure (SIP).” Page 897, Section 4, 4th paragraph, “It can be seen that, for the aspect ratio, B1=H, of 0.7, the vertical normalized wind velocity for P2 was reduced for Scheme III (staggered building configuration) as compared to Scheme II (‘‘regular’’ building configuration) for both the S–N and SE–NW wind directions, although the wind velocity was a little changed for P1 and P3.” See also Fig. 1 on Page 893 from Zhang et al or above, Fig. 4 on Page 898 from Zhang et al or below, and Fig. 5 on Page 899 from Zhang et al or above. Examiner notes: The force vector (wind speed and wind direction) being reduced for Scheme III as compared to Scheme II based on a number of iterative changes to the states (from the building positions, building orientations, and building dimensions of Scheme II to those of Scheme III) from Zhang et al discloses the claimed force vector being dampened based on a number of iterative updates to the plurality of states.)
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It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to utilize the dampened force vector as per Zhang et al for the method in Xu et al because it would allow for “a numerical simulation for evaluating the wind field under different building arrangements and wind conditions” (Zhang et al. Page 903, Section 5, 1st paragraph) whereby “by comparing different building schemes, it is found that the wind field depends strongly on the building layout and the wind direction. Scheme III (the staggered group arrangement) helps to introduce more wind into the site in the two wind directions for S–N and SE–NW wind directions. Consequently, Scheme III can provide a good wind environment and potential to use natural ventilation.” (Zhang et al. Page 903, Section 5, 2nd paragraph)
Conclusion
8. All Claims are rejected.
9. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
i) U.S. Patent No. 20210150092 A1 – includes relevant technical concepts: computer-aided layout generation for building design and dimension growth under boundary conditions.
ii) Whiting, Emily J. “Geometric, Topological & Semantic Analysis of Multi-Building Floor Plan Data.” Thesis (S.M.) - Massachusetts Institute of Technology, Department of Architecture (2006): Pages 1-74 – includes relevant technical concepts: multi-building footprint arrangement and agent-based generative site planning.
iii) Semnani, Samaneh Hosseini, Anton H. J. de Ruiter, and Hugh H. T. Liu. “Force-Based Algorithm for Motion Planning of Large Agent.” Institute of Electrical and Electronics Engineers (2020): Pages 654-665 – includes relevant technical concepts: force-vector style iterative updates and constraint-based spatial packing and placement.
10. Any inquiry concerning this communication or earlier communications from the
examiner should be directed to Khang Huynh whose telephone number is (571) 270-0680. The
examiner can normally be reached on Monday-Friday, 8:00am-5:00pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s
supervisor, Renee Chavez, can be reached at (571) 270-1104. The fax phone number for the
organization where this application or proceeding is assigned is (571) 273-8300.
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/KHANG THIEN GIA HUYNH/Examiner, Art Unit 2186
/RENEE D CHAVEZ/Supervisory Patent Examiner, Art Unit 2186
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