DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1-20 are presented for examination.
Claims 1-20 are rejected under 35 U.S.C. 101.
Claims 1-2, 4-5, 9,11, and 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Li, Quhao, et al. "Structural topology optimization considering connectivity constraint." Structural and Multidisciplinary Optimization 54.4 (2016), in the view of Liu, Shutian, et al. "An identification method for enclosed voids restriction in manufacturability design for additive manufacturing structures." Frontiers of Mechanical Engineering 10.2 (2015):
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Li, Quhao, et al. "Structural topology optimization considering connectivity constraint." Structural and Multidisciplinary Optimization 54.4 (2016), in the view of Liu, Shutian, et al. "An identification method for enclosed voids restriction in manufacturability design for additive manufacturing structures." Frontiers of Mechanical Engineering 10.2 (2015), further in the view of Bendsoe, Martin Philip, and Ole Sigmund. Topology optimization: theory, methods, and applications. Springer Science & Business Media, 2013.
Claims 6-8 are rejected under 35 U.S.C. 103 as being unpatentable over Li, Quhao, et al. "Structural topology optimization considering connectivity constraint." Structural and Multidisciplinary Optimization 54.4 (2016), in the view of Liu, Shutian, et al. "An identification method for enclosed voids restriction in manufacturability design for additive manufacturing structures." Frontiers of Mechanical Engineering 10.2 (2015), further in the view of Yamada, Takayuki, et al. "A topology optimization method based on the level set method incorporating a fictitious interface energy." Computer Methods in Applied Mechanics and Engineering 199.45-48 (2010).
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Li, Quhao, et al. "Structural topology optimization considering connectivity constraint." Structural and Multidisciplinary Optimization 54.4 (2016), in the view of Liu, Shutian, et al. "An identification method for enclosed voids restriction in manufacturability design for additive manufacturing structures." Frontiers of Mechanical Engineering 10.2 (2015), further in the view of Youshi, Motahareh. "Topology Optimization for Multiple Materials with Structural and Thermal Objectives to Design 3D Printed Building Panels." (2022).
Claims 12-13 are rejected under 35 U.S.C. 103 as being unpatentable over Li, Quhao, et al. "Structural topology optimization considering connectivity constraint." Structural and Multidisciplinary Optimization 54.4 (2016), in the view of Liu, Shutian, et al. "An identification method for enclosed voids restriction in manufacturability design for additive manufacturing structures." Frontiers of Mechanical Engineering 10.2 (2015), further in the view of Wang, Weiming, and Yi Xia. "Topology optimization-based channel design for powder-bed additive manufacturing." Additive Manufacturing 54 (2022):
Claims 16 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Li, Quhao, et al. "Structural topology optimization considering connectivity constraint." Structural and Multidisciplinary Optimization 54.4 (2016) in the view of Youshi, Motahareh. "Topology Optimization for Multiple Materials with Structural and Thermal Objectives to Design 3D Printed Building Panels." (2022), further in the view of Mirzendehdel, Amir M., Morad Behandish, and Saigopal Nelaturi. "Topology optimization with accessibility constraint for multi-axis machining." Computer-Aided Design 122 (2020).
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Li, Quhao, et al. "Structural topology optimization considering connectivity constraint." Structural and Multidisciplinary Optimization 54.4 (2016) in the view of Youshi, Motahareh. "Topology Optimization for Multiple Materials with Structural and Thermal Objectives to Design 3D Printed Building Panels." (2022), further in the view of Mirzendehdel, Amir M., Morad Behandish, and Saigopal Nelaturi. "Topology optimization with accessibility constraint for multi-axis machining." Computer-Aided Design 122 (2020), further in the view of Yamada, Takayuki, et al. "A topology optimization method based on the level set method incorporating a fictitious interface energy." Computer Methods in Applied Mechanics and Engineering 199.45-48 (2010)
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Li, Quhao, et al. "Structural topology optimization considering connectivity constraint." Structural and Multidisciplinary Optimization 54.4 (2016) in the view of Youshi, Motahareh. "Topology Optimization for Multiple Materials with Structural and Thermal Objectives to Design 3D Printed Building Panels." (2022), further in the view of Mirzendehdel, Amir M., Morad Behandish, and Saigopal Nelaturi. "Topology optimization with accessibility constraint for multi-axis machining." Computer-Aided Design 122 (2020), further in the view of Wang, Weiming, and Yi Xia. "Topology optimization-based channel design for powder-bed additive manufacturing." Additive Manufacturing 54 (2022):
This action is Non-final rejection.
Priority
Acknowledgment is made for a domestic priority date of PRO application 63/398636, filing date 08/17/2022.
Information Disclosure Statement
The IDS filed on 12/21/2022 is reviewed and considered. See attached file.
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.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is
directed to mental process without any additional element that provide a practical or amount to significant more than the abstract idea.
Step 1: Yes : claims 1-20 recites method and system, so claims 1-20 falls into a statutory category of a process.
Step 2A prong 1: Yes: claims 1 -20 recites abstract idea, abstract ideas in each claim are bolded.
Regarding claim 1:
optimizing a topology of the part in the physics solver by enforcing the one or more physical constraints and the one or more connectivity constraints while satisfying a primary objective function that optimizes the physical performance of the part; (under its broadest interpretation, this claim limitation recites a mental process. A human mind can perform optimization of a topology part by iterative refinement and setting objective function to check its performance by changing the physical constraints using a pen and paper. Therefore this limitation recites a mental process, since a human mind can perform topology optimization of the part by observing, evaluating and making judgment to find the optimized performance using a physical aid).
Regarding claim 9:
wherein optimizing the topology further comprises representing the part and the complement space as respective super-level and sub-level sets of a density field ( this claim limitation further defines abstract idea of optimizing topology as it was listed above on claim 1, by assigning density field for the part and complementary space)
Regarding claim 10:
Assigning different weights to each of the one or more connectivity constraints and the one or more physical constraints to emphasize one of the physical performance of the part or the connectivity (this claim limitation recites a mental process. A person of ordinary skill in the art can apply a weight on a physical constraint of the physics solver. A human can assign a weight on equations variable (physical constraints) using a pen and paper and evaluate the weighted equation to analyze the performance).
Regarding claim 16
weighting the first and second sensitivity fields to relatively emphasize one of the physical performance of the part or the connectivity; ((this claim limitation recites a mental process. A person of ordinary skill in the art can apply a weight on gathered data into the physics solver. A human can assign a weight on equations variable (physical constraints- sensitivity) using a pen and paper and evaluate the weighted equation to analyze the performance).
updating the intermediate design based on optimizing an objective function that relates to the physical performance of the part, the optimizing the objective function based on the weighted first and second sensitivity fields; (under its broadest reasonable interpretation this claim limitation recites a mental process. A human mind can make a changes on the design (drawing) based on the new optimized weighted parameters. A human can iteratively update the design using a pan and paper based on the objective function related to the performance).
determining a convergence criterion that indicates that the updated intermediate design approaches an optimized topology of the part, and terminating the
optimization loop with a final design if the convergence criterion meets a threshold; (under its broadest reasonable interpretation this claim limitation recites a mental process. By performing observation, evaluation and judgment, a person of ordinary skill in the art can determine the criterion to stop iterative designing after it finds an optimal parameters that can create an optimal design by comparing the set threshold).
Step 2A prong 2: NO
The claims do not recite additional elements that integrate the exception into a
practical application of the exception because the claim do not have additional elements or a combination of additional elements that apply, rely on, or use the judicial exception in a manner that impose a meaningful limit on the judicial exception.
Claims recites gathering data which is insignificant extra solution activity. Adding insignificant extra-solution activity to the judicial exception, e.g., mere data gathering in conjunction with a law of nature or abstract idea such as a step of obtaining information
about credit card transactions so that the information can be analyzed by an abstract mental process, as discussed in CyberSource V. Retail Decisions, Inc., 654 F.3d 1366, 1375, 99 USPQ2d 1690, 1694 (Fed. Cir. 2011) (see MPEP § 2106.05(g), and claims also recites data manipulation by “displaying” outputs - Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016); MPEP 2106.05(g).
The claim limitations which recites data gatherings, and manipulation are listed
Below
Claim 1
defining one or more physical constraints selected from a plurality of physical constraints for the part, the one or more physical constraints for use by a physics solver
defining a physical performance of the part; ( insignificant extra-solution
activity – data gathering, such as 'obtaining information'. See MPEP 2106.05(g).)
defining one or more connectivity constraints for use by the physics solver, the one or more connectivity constraints enforcing connectivity to or from at least one region over a complement space of the part, the one or more connectivity constraints comprising locally differentiable violation measures that are modeled after at least one of the physical constraints ( insignificant extra-solution activity – data gathering, such as 'obtaining information'. See MPEP 2106.05(g).)
producing (insignificant extra-solution activity – data gathering, such as 'outputting
data'. See MPEP 2106.05(g).)
Claim 2:
wherein the connection is between an inner region of the part and a boundary of the part ( insignificant extra-solution activity – data gathering, such as 'obtaining information'. See MPEP 2106.05(g).)
Claim 3:
wherein the connection is between two inner regions of the part( insignificant extra-solution activity – data gathering, such as 'obtaining information'. See MPEP 2106.05(g).)
Claim 4:
wherein the connectivity constraints comprise a virtual load applied on a boundary of the region ( insignificant extra-solution activity – data gathering, such as 'obtaining information'. See MPEP 2106.05(g).)
Claim 5:
wherein the connectivity constraints comprise a thermal boundary condition applied on a boundary of the region ( insignificant extra-solution activity – data gathering, such as 'obtaining information'. See MPEP 2106.05(g).)
Claim 6 and 17:
wherein the one or more connectivity constraints comprise a virtual energy function or a virtual compliance of a hypothetical structure representing the complement space of the part ( insignificant extra-solution activity – data gathering, such as 'obtaining information'. See MPEP 2106.05(g).))
Claim 7:
wherein enforcing the one or more connectivity constraints comprises minimizing the virtual energy function ( insignificant extra-solution activity – data gathering, such as 'obtaining information'. See MPEP 2106.05(g).))
Claim 8:
wherein the connectivity constraints comprises both Neumann and Dirichlet boundary conditions. ( insignificant extra-solution activity – data gathering, such as 'obtaining information'. See MPEP 2106.05(g).))
Claims 12,13 and 18
connectivity constraints ensure channels exist in the part, the channels are
configured for at least one of: routing wires through the part …(( insignificant extra-solution activity – data gathering, such as 'obtaining information'. See MPEP 2106.05(g).))
Claim 14 and 19
wherein the physics solver comprises a finite element solver ( insignificant extra-solution activity – it is goes defines what the physical solver comprises)
Step 2B :No:
The claim do not recite additional elements which are significantly more than the abstract idea. As out lined above the claim merely use a computer components, software like CAD, and manufacturing machine to perform abstract idea. Merly using of a computer, software or manufacturing machine and applying abstract ideas into a system without making improvement to the functionality of a computer, software or manufacturing machine is not a significantly more.
Claim 1 and 16 uses a software (CAD) use to output the abstract idea, and as it is listed on claim 15 and 20, the process also uses a memory and processor but it is merely using of a software or computer component, to implement abstract idea with out making improvement in the software or the computer itself.
Claim 1, 11 and 16 also uses a manufacturing instrument as a tool to produce the part but this does not significantly more since it is used merely as a tool and there is no improvement is claimed on the manufacturing machine.
Though the claim recites additional elements as it is outlined above, they are not significantly more than abstract idea since the additional elements are merely used as a tool and it does not make improvement to the functioning of the additional elements, see MPEP 2106.05(a), Improvements to the Functioning of a Computer or To Any Other Technology or Technical Field [R-07.2022]
Therefore, it is concluded that the claims 1-20 are not found eligible under 35
U.S.C 101.
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.
Claims 1-2, 4-5, 9,11, and 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Li, Quhao, et al. "Structural topology optimization considering connectivity constraint." Structural and Multidisciplinary Optimization 54.4 (2016), in the view of Liu, Shutian, et al. "An identification method for enclosed voids restriction in manufacturability design for additive manufacturing structures." Frontiers of Mechanical Engineering 10.2 (2015):
As of claim 1, Li teaches A method of designing a part, comprising: defining one or more physical constraints selected from a plurality of physical constraints for the part, the one or more physical constraints for use by a physics solver defining a physical performance of the part; (abstract, In this paper, we propose a novel topology optimization model with manufacturing process related connectivity constraints. A generalized method, named as virtual scalar field method (VSFM), is developed for describing and enforcing desired connectivity constraint. As an illustrative example, the connectivity constraint can be converted to an equivalent maximum temperature constraint when temperature is chosen as the scalar field…section 2.2 Virtual scalar field Laplacian equation as physics solver).As cited above temperature is used as a physical constraint and a mathematical model like the Laplacian equation is used as a physical solver.
defining one or more connectivity constraints for use by the physics solver, (section 3.2, The global stiffness matrix K and temperature load vector Q for the finite element-based structural response analyses behind the optimization can now be calculated by
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where V is the (global level) element stiffness matrix, KTe is the (global level) element heat conduction matrix, QTe is the (global level) element load vector, and m is the number of elements). the one or more connectivity constraints enforcing connectivity to or from at least one region over a complement space of the part, (section 2.2, the simply-connected constraint, which avoids enclosed voids, can be formulated as
u max ≤ū
where ū max is the maximum value for the scalar field and ū is a small number representing the threshold of the required value that separates simply-connectivity and multiply-connectivity)
the one or more connectivity constraints comprising locally differentiable violation measures that are modeled after at least one of the physical constraints;( section 2.1 Thus the maximum temperature value of the virtual steady temperature model can be used as a criterion to determine the connectivity of a structure, simply- or multiply-connected. Therefore, the simply connected constraint, which avoids enclosed voids, can be formulated as
T max ≤ T
where T max is the maximum temperature value for the special steady virtual temperature field and T is a small number representing the threshold of the required temperature that separates simply-connectivity and multiply-connectivity).
and the one or more connectivity constraints while satisfying a primary objective function that optimizes the physical performance of the part; (section 3, we consider the simplest type of design problem formulation, namely, to minimize the compliance of a structure subject to a volume constraint and relevant manufacturing process constraints in this paper).
producing a computer-aided design of the part based on the optimized topology, the computer-aided design used to produce the part via a manufacturing instrument (section 5.4 and figure 21, The CAD models of the four optimized results for different manufacturing constraints are established, shown in Fig. 21. Dimension Elite 3D Printer which is driven by FDM Technology and prints real ABSplus thermoplastic is used to fabricate these structures).
The modified model does not explicitly teach optimizing a topology of the part in the physics solver by enforcing the one or more physical constraints.
While Liu teaches optimizing a topology of the part in the physics solver by enforcing the one or more physical constraints (section 4, For convenience, the problem treated in this paper employed the simplest type of design problem formulation to minimize the compliance of a structure subject to a volume constraint and simply-connected constraint (i.e., maximum temperature constraint). The corresponding optimization problem is formulated as
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where c is the compliance objective function, u is the displacement vector, f is the external load vector, K is the global stiffness matrix, ve is the element volume, pe is the density variable, γ is the allowed solid volume fraction and V is the volume of the design domain.
Li and Liu is considered as analogous to the claimed invention because it focus on topology optimization. Therefore it would be obvious for a person of ordinary skill in art, before the effective filling date to integrate Liu’s teaching into Li’s model to optimize topology based on connectivity constraints and by enforcing the one or more physical constraints.
The motivation would have been by using equivalent description of connectivity constraint based on a special temperature model allows to easily use the connectivity constraint which is equivalent to a maximum temperature constraint and the problem of minimum compliance topology optimization with the new equivalent constraint is considered (Li, conclusion) and by using virtual temperature method, it can be easily use to formulate the simply-connected constraint in topology optimization and to minimize the compliance of a structure subject to a volume constraint and simply-connected constraint (i.e., maximum temperature constraint) (Liu, abstract and section 4).
As of claim 2 the modified model teaches all the limitations of claim 1 and Li also teaches wherein the connection is between an inner region of the part and a boundary of the part.( section 1,
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As of claim 4, the modified model teaches all the limitations of claim1, and Li also teaches , wherein the connectivity constraints comprise a virtual load applied on a boundary of the region (section 3.1, The topology optimization problem is formulated as …where c is the objective function representing the compliance, m is the number of elements, K is the global stiffness matrix, u is the displacement vector and f is the external load vector).
As of claim 5, the modified model teaches all the limitations of claim 1, and Li also teaches wherein the connectivity constraints comprise a thermal boundary condition applied on a boundary of the region. ( section 2.1 Therefore, the simply connected constraint, which avoids enclosed voids, can be formulated as
T max ≤T
where T max is the maximum temperature value for the special steady virtual temperature field and T is a small number representing the threshold of the required temperature that separates simply-connectivity and multiply-connectivity.
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As shown on figure 2, T is applied on the boundary .
As of claim 9, the modified model teaches all the limitations of claim 1, but it does not explicitly teach wherein optimizing the topology further comprises representing the part and the complement space as respective super-level and sub-level sets of a density field.
While Liu teaches wherein optimizing the topology further comprises representing the part and the complement space as respective super-level and sub-level sets of a density field (section 2 and figure 2, A background mesh is introduced and the structure is projected onto the mesh, as shown in Fig. 2. If the projected region contains the center of a mesh element, the density of the element is defined as 1 (_ ¼ 1), else defined as 0 (_ ¼ 0). density 1 is interpreted as a super level and density 0 is interpreted as a sub level.
Liu is considered as analogous to the claimed invention because it focus on topology optimization. Therefore it would be obvious to try for a person of ordinary skill in art, before the effective filling date to integrate Liu’s teaching with the combined model to differentiate the density of 1 on the part as a super level and density of 0 on the complement as a sub level.
The motivation would have been by using virtual temperature method, the method can easily use to formulate the simply-connected constraint in topology optimization and to minimize the compliance of a structure subject to a volume constraint and simply-connected constraint (i.e., maximum temperature constraint) (Liu, abstract and section 4).
As of claim 11 the modified model teaches all the limitations of claim 1, and Li also teaches wherein the one or more connectivity constraints ensure accessibility of a manufacturing machine when manufacturing the part (Figure 21, use a 3D printer to manufacture, section 5.3, Dimension Elite 3D Printer which is driven by FDM Technology and prints real ABSplus thermoplastic is used to fabricate these structures).
As of claim 14, the modified model teaches all the limitations of claim 1 and Li also teaches wherein the physics solver comprises a finite element solver. ( section 2.2 Several numerical methods, for example, finite element method, finite difference method etc., have been developed to solve the Laplacian equation.)
As of claim 15 ,the modified model teaches all the limitations of claim 1, and Li also teaches A system comprising a memory storing instructions and a processor, the processor operable via the instructions to perform the method of claim 1 (Section 5.3, The CAD models of the four optimized results for different manufacturing constraints are established, shown in Fig. 21). As it cited above Li perform simulation and use CAD model which use a computer and computer inherits a memory and processor.
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Li, Quhao, et al. "Structural topology optimization considering connectivity constraint." Structural and Multidisciplinary Optimization 54.4 (2016), in the view of Liu, Shutian, et al. "An identification method for enclosed voids restriction in manufacturability design for additive manufacturing structures." Frontiers of Mechanical Engineering 10.2 (2015), further in the view of Bendsoe, Martin Philip, and Ole Sigmund. Topology optimization: theory, methods, and applications. Springer Science & Business Media, 2013.
As of claim 3, the combined model teaches all the limitations of claim 1, but it does not explicitly teach wherein the connection is between two inner regions of the part.
While Bendsoe teaches wherein the connection is between two inner regions of the part ( page 3, figure 1.2 (a),
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the two regions are a point with no material and a point with a fixed material and they are connected by the general shape design.
Bendsoe is considered to be analogous to the claimed invention, since it focus on topology optimization. Therefore it would be obvious for a person of ordinary skill in the art before the effective filling date to combine Bendsoe’s teaching of having two connected inner regions into the combined model.
The motivation would have been to find the optimal thickness distribution of a linearly elastic plate or the optimal member areas in a truss structure by addressing different aspects of the structural design problem using sizing, shape, and topology optimization. The optimal thickness distribution minimizes (or maximizes) a physical quantity such as the mean compliance (external work), peak stress, deflection, etc.,(Bendsoe, page 1).
Claims 6-8 are rejected under 35 U.S.C. 103 as being unpatentable over Li, Quhao, et al. "Structural topology optimization considering connectivity constraint." Structural and Multidisciplinary Optimization 54.4 (2016), in the view of Liu, Shutian, et al. "An identification method for enclosed voids restriction in manufacturability design for additive manufacturing structures." Frontiers of Mechanical Engineering 10.2 (2015), further in the view of Yamada, Takayuki, et al. "A topology optimization method based on the level set method incorporating a fictitious interface energy." Computer Methods in Applied Mechanics and Engineering 199.45-48 (2010).
As of claim 6, the modified model teaches all the limitations of claim 1, but it does not explicitly teach wherein the one or more connectivity constraints comprise a virtual energy function or a virtual compliance of a hypothetical structure representing the complement space of the part.
While Yamada teaches wherein the one or more connectivity constraints comprise a virtual energy function or a virtual compliance of a hypothetical structure representing the complement space of the part ( Abstract, a topology optimization problem is formulated based on the level set method, and the method of regularizing the optimization problem by introducing fictitious interface energy is explained). The virtual energy function is mapped to fictitious interface energy and the modified model teaches the connectivity constraints.
Yamada is considered to be analogous to the claimed invention, since it focus on topology optimization. Therefore it would be obvious to try for a person of ordinary skill in the art to apply Yamada’s teaching of a fictitious interface energy into the modified model of connected constraint.
The motivation would have been by introducing the fictitious interface energy in the phase field model to regularize the topology optimization problem and proposed topology optimization method, minimum mean compliance problems, optimum design problem of compliant mechanisms, and lowest eigen frequency maximization problems were formulated and this helps to confirmed a smooth and clear optimal configurations were obtained (Yamada, section .1 and conclusion).
As of claim 7, the modified model teaches all the limitations of claim 6, and Yamada also teaches, wherein enforcing the one or more connectivity constraints comprises minimizing the virtual energy function (conclusions, A topology optimization method was formulated, incorporating level set boundary expressions, where the optimization problem is handled as a problem to minimize the energy functional including a fictitious interface energy).
As of claim 8, The modified model teaches all the limitations of claim 6, and Li also teaches wherein the connectivity constraints comprises both Neumann and Dirichlet boundary conditions (section 2.2, The boundary condition is given by:
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)
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Li, Quhao, et al. "Structural topology optimization considering connectivity constraint." Structural and Multidisciplinary Optimization 54.4 (2016), in the view of Liu, Shutian, et al. "An identification method for enclosed voids restriction in manufacturability design for additive manufacturing structures." Frontiers of Mechanical Engineering 10.2 (2015), further in the view of Youshi, Motahareh. "Topology Optimization for Multiple Materials with Structural and Thermal Objectives to Design 3D Printed Building Panels." (2022).
As of claim 10, the modified model teaches all the limitations of claim 1, but it does not explicitly teach assigning different weights to each of the one or more connectivity constraints and the one or more physical constraints to emphasize one of the physical performance of the part or the connectivity.
While Youshi teaches assigning different weights to each of the one or more connectivity constraints and the one or more physical constraints to emphasize one of the physical performance of the part or the connectivity page 41 and 42 , page 49, table 9 and 10, As trade-off solutions across the structural and thermal disciplines needed to be studied, both the structural displacement and thermal resistance constraints were reformulated as TO objectives, by minimal structural compliance and maximal thermal compliance, respectively. Consequently, the stress constraints were kept as constraints. Using different weight factors for the two objectives, Pareto fronts were used to look up the situations for which one or both of the objectives met their related practical constraints).
Youshi is considered as analogous to the claimed invention because it focus on topology optimization. Therefore it would be obvious to a person of ordinary skill in the art , before the effective filling date to apply weighting on connectivity constraints as Youshi’s teaches into the modified model.
The motivation would have been by weighted objective function and combined with a volume constraint to limit the material usage of the design and this is simple to implement and gives a fast convergence process (Youshi, page 48-49).
Claims 12-13 are rejected under 35 U.S.C. 103 as being unpatentable over Li, Quhao, et al. "Structural topology optimization considering connectivity constraint." Structural and Multidisciplinary Optimization 54.4 (2016), in the view of Liu, Shutian, et al. "An identification method for enclosed voids restriction in manufacturability design for additive manufacturing structures." Frontiers of Mechanical Engineering 10.2 (2015), further in the view of Wang, Weiming, and Yi Xia. "Topology optimization-based channel design for powder-bed additive manufacturing." Additive Manufacturing 54 (2022):
As of claim 12 the modified model teaches all the limitations of claim 1, but it does not explicitly teach wherein the one or more connectivity constraints ensure channels exist in the part.
While Wang teaches wherein the one or more connectivity constraints ensure channels exist in the part (section 3.1, As a result, a large amount of remaining powder is inevitable using the powder-based 3D printing method. In order to discharge the remaining powder in these closed voids, it is necessary to design channels connecting the closed voids to outlets. Through the following procedures, the proposed approach generates channels for these investigated models in an automatic and convenient manner).
Wang is considered as analogous to the claimed invention, because it focus on topology optimization. Therefore it would be obvious for a person of ordinary skill in the art, before the effective filling date to create a channel of exit on the modified model according to Wang’s teaching.
The motivation would have been in order to effectively discharged through the generated channels by effectively generates channels for the printing structure with complex geometry and a large number of closed voids and the generated channel connects all closed voids and outlets while remaining inside the structure (Wang, conclusions).
As of claim 13, the modified model teaches all the limitations of claim 12, and Wang also teaches wherein the channels are configured for at least one of: routing wires through the part; removing powder from the part after a manufacturing process; and flowing coolant through the part during use of the part (Abstract, In this paper, a method based on topology optimization (TO) is proposed to automatically generate channels between closed voids and outlets, by which the remaining powder of the powder-based printing structures can be discharged).
Claims 16 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Li, Quhao, et al. "Structural topology optimization considering connectivity constraint." Structural and Multidisciplinary Optimization 54.4 (2016) in the view of Youshi, Motahareh. "Topology Optimization for Multiple Materials with Structural and Thermal Objectives to Design 3D Printed Building Panels." (2022), further in the view of Mirzendehdel, Amir M., Morad Behandish, and Saigopal Nelaturi. "Topology optimization with accessibility constraint for multi-axis machining." Computer-Aided Design 122 (2020).
As of claim 16, Li teaches defining a physical constraint for the part, the physical constraint for use by a physics solver defining a physical performance of the part; (Abstract, In this paper, we propose a novel topology optimization model with manufacturing process related connectivity constraints. A generalized method, named as virtual scalar field method (VSFM), is developed for describing and enforcing desired connectivity constraint. As an illustrative example, the connectivity constraint can be converted to an equivalent maximum temperature constraint when temperature is chosen as the scalar field…section 2.2 Virtual scalar field Laplacian equation as physics solver).As cited above temperature is used as a physical constraint and a mathematical model like the Laplacian equation is used as a physical solver.
defining one or more connectivity constraints for use by the physics solver, (section 3.2, The global stiffness matrix K and temperature load vector Q for the finite element-based structural response analyses behind the optimization can now be calculated by
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where V is the (global level) element stiffness matrix, KTe is the (global level) element heat conduction matrix, QTe is the (global level) element load vector, and m is the number of elements). the one or more connectivity constraints enforcing connectivity to or from at least one region over a complement space of the part, (section 2.2, the simply-connected constraint, which avoids enclosed voids, can be formulated as
u max ≤ū
where ū max is the maximum value for the scalar field and ū is a small number representing the threshold of the required value that separates simply-connectivity and multiply-connectivity)
the connectivity constraint comprising locally differentiable violation measures that are modeled after one or more physical constraints (section 2.1 Thus the maximum temperature value of the virtual steady temperature model can be used as a criterion to determine the connectivity of a structure, simply- or multiply-connected. Therefore, the simply connected constraint, which avoids enclosed voids, can be formulated as
T max ≤T
where T max is the maximum temperature value for the special steady virtual temperature field and T is a small number representing the threshold of the required temperature that separates simply-connectivity and multiply-connectivity).
for each intermediate design of the part in an optimization loop: (Figure 7, The iterative history. A iteration history of the objective; b iteration history of constraint g2) The process is performed iteratively(loop).
evaluating a virtual response based on the connectivity constraints applied to the complement space (abstract, In this method, suppose that the voids in structure are filled with a virtual heating material with high heat conductivity and solid areas are filled with another virtual material with low heat conductivity), the virtual response is interpreted as heat conductivity.
defining a first and second sensitivity fields based respectively on the real response and the virtual response; ( section 4.1, In order to use the gradient-based optimization, the sensitivities of the objective function and constraint functions with respect to the design variables are derived in this section. Some details in numerical implementation are also presented).
determining a convergence criterion that indicates that the updated intermediate design approaches an optimized topology of the part ( section 5.2 Variation of λ= [5, 4, 3, 2, 1] is performed in the optimization process. The convergence criterion is chosen as max ‖ρj + 1 −ρj‖<10− 3 and the maximum iteration number is set to be 300. The optimized design results with different boundary conditions of the temperature model are shown in Fig. 11)
after the termination of the optimization loop, producing a computer-aided design of the part based on the final design, the computer-aided design used to produce the part via a manufacturing instrument (Figure 21 and section 5.4 The CAD models of the four optimized results for different manufacturing constraints are established, shown in Fig. 21. Dimension Elite 3D Printer which is driven by FDM Technology and prints real ABSplus thermoplastic is used to fabricate these structures).
While Li does not explicitly teach evaluating a real response based on the physical performance of the part; weighting the first and second sensitivity fields to relatively emphasize one of the physical performance of the part or the connectivity; updating the intermediate design based on optimizing an objective function that relates to the physical performance of the part, the optimizing the objective function based on the weighted first and second sensitivity fields; and terminating the optimization loop with a final design if the convergence criterion meets a threshold;
While Youshi teaches evaluating a real response based on the physical performance of the part (page 10, To investigate the structural performance, the first objective is considered as the minimization of a structure's compliance, which is equivalent to the minimization of strain energy and maximization of the total structural
stiffness. Following this classical approach in structural topology optimization, the overall structural compliance is minimized, constraining the problem to a certain amount of material volume. Considering the vector x combining all elements' densities, the structural compliance function is defined as the product of the external force and the displacement field). In this context the displacement field is considered as a real response.
the optimizing the objective function based on the weighted first and second sensitivity fields; (page 18, calculate objective function Cs and Ct
page 11, In order to define a multi-objective framework, the linear combination of the two mentioned compliance functions is considered. Each of these objectives is weighted by weighting factors w and w th such that their sum equals 1).
terminating the optimization loop with a final design if the convergence criterion meets a threshold (page 18, In the loops of calculations, objective and constraint functions, as well as their sensitivities are computed based on the updated density of the loop. After obtaining the filtered densities, the convergence criterion is checked to determine whether the optimization algorithm must continue or stop)
Li and Youshi are considered as analogous to the claimed invention because it focus on topology optimization. Therefore it would be obvious to a person of ordinary skill in the art , before the effective filling date to combine Li teaching of topology optimization considering connectivity constraint with Youshi teaching of multi-objective topology optimization problem.
The motivation would have been by using equivalent description of connectivity constraint based on a special temperature model allows to easily use the connectivity constraint which is equivalent to a maximum temperature constraint and the problem of minimum compliance topology optimization with the new equivalent constraint is considered (Li, conclusion) and weighted objective function combined with a volume constraint to limit the material usage of the design and this is simple to implement and gives a fast convergence process (Youshi, page 48-49).
The modified model does not explicitly teach weighting the first and second sensitivity fields to relatively emphasize one of the physical performance of the part or the connectivity , updating the intermediate design based on optimizing an objective function that relates to the physical performance of the part.
While Mirzendehdel teaches weighting the first and second sensitivity fields to relatively emphasize one of the physical performance of the part or the connectivity (section 2.2, To incorporate the accessibility constraint for multi-axis machining, we modify the sensitivity field SΩ as follows:
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where 0 ≤ wacc < 1 is the filtering weight for accessibility, and can be either a constant or adaptively updated based on the secluded volume VΓ(O). Sϕ is the normalized sensitivity field with respect to the objective function).
updating the intermediate design based on optimizing an objective function that relates to the physical performance of the part (section 2.1, TO typically starts with an initial design Ω := Ω0 ⊂ R3 (called the design domain) and incrementally updates the design Ω ⊆ Ω0 such that it remains within the design domain while minimizing the specified objective function and satisfying the specified constraints. These constraints may include performance criteria (e.g., stiffness or strength), evaluated by a physics solver such as FEA, as well as kinematic constraints (e.g., machine tool accessibility), which require spatial analysis).
Mirzendehdel is considered to be analogous to the claimed invention since it focus on topology optimization. Therefore it would be obvious for a person of ordinary skill in the art, before the effective filling date to integrate Mirzendehdel ‘s teaching of updating model based on the objective function into the modified model for to perform topology optimization considering connectivity constraint.
The motivation would have been incrementally updates the design such that it remains within the design domain while minimizing the specified objective function and it helps to satisfying the specified constraints (Mirzendehdel, section 2.1).
As of claim 19, the modified model teaches all the limitations of claim 16, and Li also teaches wherein the physics solver comprises a finite element solver. ( section 2.2 Several numerical methods, for example, finite element method, finite difference method etc., have been developed to solve the Laplacian equation.)
As of claim 20, the modified model teaches all the limitations of claim 16, and Mirzendehdel also teaches A system comprising a memory storing instructions and a processor, the processor operable via the instructions to perform the method of claim 16 (section 3, All examples are run on a desktop machine with Intel⃝R CoreTM i7-7820X CPU with 8 processors running at 4.5 GHz, 32 GB of host memory, and an NVIDIA⃝R GeForce⃝R GTX 1080 GPU with 2560 CUDA cores and 8 GB of device memory).
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Li, Quhao, et al. "Structural topology optimization considering connectivity constraint." Structural and Multidisciplinary Optimization 54.4 (2016) in the view of Youshi, Motahareh. "Topology Optimization for Multiple Materials with Structural and Thermal Objectives to Design 3D Printed Building Panels." (2022), further in the view of Mirzendehdel, Amir M., Morad Behandish, and Saigopal Nelaturi. "Topology optimization with accessibility constraint for multi-axis machining." Computer-Aided Design 122 (2020), further in the view of Yamada, Takayuki, et al. "A topology optimization method based on the level set method incorporating a fictitious interface energy." Computer Methods in Applied Mechanics and Engineering 199.45-48 (2010)
As of claim 17, the modified model teaches all the limitations of claim 16, but it does not explicitly teach wherein the one or more connectivity constraints comprise a virtual energy function or a virtual compliance of a hypothetical structure representing the complement space of the part.
While Yamada teaches wherein the one or more connectivity constraints comprise a virtual energy function or a virtual compliance of a hypothetical structure representing the complement space of the part ( Abstract, a topology optimization problem is formulated based on the level set method, and the method of regularizing the optimization problem by introducing fictitious interface energy is explained). The virtual energy function is mapped to fictitious interface energy and the modified model teaches the connectivity constraints.
Yamada is considered to be analogous to the claimed invention, since it focus on topology optimization. Therefore it would be obvious to try for a person of ordinary skill in the art to apply Yamada’s teaching of a fictitious interface energy into the modified model of connected constraint.
The motivation would have been by introducing the fictitious interface energy in the phase field model to regularize the topology optimization problem and proposed topology optimization method, minimum mean compliance problems, optimum design problem of compliant mechanisms, and lowest eigen frequency maximization problems were formulated and this helps to confirmed a smooth and clear optimal configurations were obtained (Yamada, section .1 and conclusion).
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Li, Quhao, et al. "Structural topology optimization considering connectivity constraint." Structural and Multidisciplinary Optimization 54.4 (2016) in the view of Youshi, Motahareh. "Topology Optimization for Multiple Materials with Structural and Thermal Objectives to Design 3D Printed Building Panels." (2022), further in the view of Mirzendehdel, Amir M., Morad Behandish, and Saigopal Nelaturi. "Topology optimization with accessibility constraint for multi-axis machining." Computer-Aided Design 122 (2020), further in the view of Wang, Weiming, and Yi Xia. "Topology optimization-based channel design for powder-bed additive manufacturing." Additive Manufacturing 54 (2022):
As of claim 18, the modified model teaches all the limitations of claim 16, but it does not explicitly teach wherein the one or more connectivity constraints ensure channels exist in the part.
while Wang teaches wherein the one or more connectivity constraints ensure channels exist in the part (section 3.1, As a result, a large amount of remaining powder is inevitable using the powder-based 3D printing method. In order to discharge the remaining powder in these closed voids, it is necessary to design channels connecting the closed voids to outlets. Through the following procedures, the proposed approach generates channels for these investigated models in an automatic and convenient manner).
Wang is considered as analogous to the claimed invention, because it focus on topology optimization. Therefore it would be obvious for a person of ordinary skill in the art, before the effective filling date to create a channel of exit on the modified model according to Wang’s teaching.
The motivation would have been in order to effectively discharged through the generated channels by effectively generates channels for the printing structure with complex geometry and a large number of closed voids and the generated channel connects all closed voids and outlets while remaining inside the structure (Wang, conclusions).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Anand; Sundaraman (US 20170372480 A1, Date Published, 2017-12-28) this application is similar to the claimed invention since it teaches topology optimization in additive manufacturing and it include performing a boundary tracing operation on the sectional snapshots.
MIRZENDEHDEL A (US 20180079149 A1, Date Published, 2018-03-22) this application is similar to the claimed invention since it teaches topology optimization for Additive Manufacturing (AM) by updating the intermediate design iteratively.
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/ABRHAM ALEHEGN TAMIRU/ Examiner, Art Unit 2188
/RYAN F PITARO/Supervisory Patent Examiner, Art Unit 2188
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