DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Examiner Note
Examiner cites particular columns, paragraphs, figures and line numbers in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner. The entire reference is considered to provide disclosure relating to the claimed invention. The claims & only the claims form the metes & bounds of the invention. Office personnel are to give the claims their broadest reasonable interpretation in light of the supporting disclosure. Unclaimed limitations appearing in the specification are not read into the claim. Prior art was referenced using terminology familiar to one of ordinary skill in the art. Such an approach is broad in concept and can be either explicit or implicit in meaning. Examiner's Notes are provided with the cited references to assist the applicant to better understand how the examiner interprets the applied prior art. Such comments are entirely consistent with the intent & spirit of compact prosecution.
Claim Objections
Claim 1 is objected to because of the following informalities: the limitation “exchange information across the plurality of software applications including updated information received any one of the plurality of software applications and the industrial metaverse application;” is grammatically incorrect and requires a connecting word between “received” and “any”. Appropriate correction is required. For compact prosecution, the limitation will be interpreted as “…received from any…”.
Claim 5 is objected to because of the following informalities: there is a stray period after “industrial system”. The claim will be interpreted as having the period replaced by a comma.
Claim Interpretation
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that use the word “means” or “step” but are nonetheless not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph because the claim limitation(s) recite(s) sufficient structure, materials, or acts to entirely perform the recited function. Such claim limitation(s) is/are: “a metaverse development pipeline comprising a plurality of software applications of dissimilar platforms configured to generate information related to objects under design for an industrial facility;”, “an industrial metaverse application configured to generate a virtual environment representation of the objects under design and the industrial facility;”, and “a metaverse knowledge graph engine configured to: instantiate and manage a metaverse knowledge graph describing semantics and relationships between the plurality of applications, and exchange information across the plurality of software applications including updated information received (from) any one of the plurality of software applications and the industrial metaverse application;” in claim 1.
Because these claim limitation(s) is/are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are not being interpreted to cover only the corresponding structure, material, or acts described in the specification as performing the claimed function, and equivalents thereof.
If applicant intends to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to remove the structure, materials, or acts that performs the claimed function; or (2) present a sufficient showing that the claim limitation(s) does/do not recite sufficient structure, materials, or acts to perform the claimed function.
Limitations of claim 1 are not being interpreted under 35 U.S.C. 112(f) because the placeholder terms “a metaverse development pipeline”, “an industrial metaverse application”, and “a metaverse knowledge graph engine” are not generic in the art and imply structure.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 2, 3, 7, 9 and 10 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 2 recites the limitation "the industrial system" in line 3. There is insufficient antecedent basis for this limitation in the claim.
Claim 3 recites the limitation "the at least one design application" in lines 2-3. There is insufficient antecedent basis for this limitation in the claim.
Claim 9 recites the limitation "the scene description" in line 2. There is insufficient antecedent basis for this limitation in the claim.
Regarding claims 7 and 10, the limitation “adding a bidirectional metaverse knowledge graph connection to a new software application” is indefinite because it is unclear how a bidirectional graph connection can be added to a software application. The “metaverse knowledge graph” of claim 1 is defined as “describing semantics and relationships between the plurality of applications.” For the purpose of compact prosecution, the limitation will be interpreted as adding a graph node representing the new software application to the “metaverse knowledge graph”, and adding a corresponding bidirectional edge to the “metaverse knowledge graph”.
Claim Rejections - 35 USC § 102
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 (i.e., changing from AIA to pre-AIA ) 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.
Claim(s) 1-3, 6-7 is/are rejected under 35 U.S.C. 102(a)(1) as being --anticipated-- by Motie et al. (“Interoperability Based Dynamic Data Mediation using Adaptive Multi-Agent Systems for Co-Simulation”, 2018).
Regarding Claim 1, Motie et al. teaches:
A computer based system for development of an industrial metaverse (Motie Introduction, “[2] described a new co-simulation framework interoperability based FMI (Functional Mock up Interface) standard for the structural interoperability part and data mediation for semantic interoperability part. In this work, we propose a dynamic mediation for adaptation of the data which allows to go further towards the development of global and open simulation environment.”)
used in engineering by computer aided design, (Motie pg. 239, “We took as example some simulators using different kinds of data. One, implemented in Matlab Simulink…”) Motie recites “Matlab Simulink”, which is an example of engineering CAD software.
comprising: a processor; and (Motie pg. 240, “We should mention that CosiMate allows execution in the native simulation environment… We can also use remote procedure: if the model is to be run on a remote machine. The CosiMate Spy tool is used to monitor and control the co-simulation components and processes.”)
a non-transitory memory having stored thereon modules executed by the processor, (Motie pg. 240, “We should mention that CosiMate allows execution in the native simulation environment… We can also use remote procedure: if the model is to be run on a remote machine. The CosiMate Spy tool is used to monitor and control the co-simulation components and processes.”)
the modules comprising: a metaverse development pipeline comprising a plurality of software applications of dissimilar platforms (Motie pg. 239-240, “We took as example some simulators using different kinds of data. One, implemented in Matlab Simulink… Another, implemented with the Powersims toolbox of Simulink [14] using Maximum Power Point Tracking… Another, implemented in Cooja Contiki…”)
configured to generate information related to objects under design for an industrial facility; (Motie pg. 239, “One, implemented in Matlab Simulink, works on reducing the energetic consumption using a black box neural network heat pump model… It requires from sensors the Electric power (Kw) and the indoor temperature and provides the optimal temperature with a specific timestep.”) (Motie pg. 239, “We took the neOCampus operation [1] as use case because it’s considered as a smart city where several data streams come from heterogeneous sensors placed inside and outside the buildings (CO2, temperature, humidity, luminosity, human presence, energy and fluid consumption, ...). It’s also a complex system as each expert interacts with data differently using a specific field within simulation to design the campus of the future, that eases campus users life, reduces the ecological impact by controlling energy and fluids consumption.”)
an industrial metaverse application configured to generate a virtual environment representation of the objects under design and the industrial facility; (Motie Introduction, “[2] described a new co-simulation framework interoperability based FMI (Functional Mock up Interface) standard for the structural interoperability part and data mediation for semantic interoperability part. In this work, we propose a dynamic mediation for adaptation of the data which allows to go further towards the development of global and open simulation environment.”)
and a metaverse knowledge graph engine (Motie pg. 238, “A Subsystem-to-Subsystem Graph Model (SSGM) is a connection graph between the subsystems, encapsulated in FMUs, which displays their communications bridges and therefore describes which outputs from one subsystem are connected to the inputs of another.”)
configured to: instantiate and manage a metaverse knowledge graph describing semantics and relationships between the plurality of applications, and (Motie pg. 238, “A Subsystem-to-Subsystem Graph Model (SSGM) is a connection graph between the subsystems, encapsulated in FMUs, which displays their communications bridges and therefore describes which outputs from one subsystem are connected to the inputs of another.”) (Motie pg. 238, “”) (Motie pg. 241, “DREAM, as a black box, offers openness and self-healing features (make new connections and replace lost connections on the fly) to our co-simulation framework when combined with an self-adaptive data translator will provide autonomous semantic interoperability.”)
exchange information across the plurality of software applications including updated information received any one of the plurality of software applications and the industrial metaverse application; (Motie pg. 238, “A Subsystem-to-Subsystem Graph Model (SSGM) is a connection graph between the subsystems, encapsulated in FMUs, which displays their communications bridges and therefore describes which outputs from one subsystem are connected to the inputs of another.”) (Motie pg. 235, “The progress of the simulated time in each simulation unit is controlled by an orchestrator, called also a master algorithm. This last one, based upon a co-simulation scenario, moves data from outputs to inputs.”)
wherein the virtual environment is updated by the industrial metaverse application based on updates to the metaverse knowledge graph. (Motie pg. 238, “we extend DREAM’s agents with a filtering behavior in order to discard the links (dynamics correlations) between the data streams of the same subsystem and links between data streams of the same type (input-input, output-output), because such links are irrelevant to build a subsystem-to-subsystem graph model (figure 3-b). Besides, we leave to the users the choice, if desired, of a specific subsystem to which they want to link, resulting in the subsystem-to subsystem graph model (figure 3-c).”)
Regarding Claim 2, Motie et al. teaches:
The system of claim 1, wherein the plurality of software applications includes at least one artificial intelligence (AI)-based surrogate model application configured to learn a surrogate model of the industrial system using machine learning. (Motie pg. 239, “One, implemented in Matlab Simulink, works on reducing the energetic consumption using a black box neural network heat pump model and ensuring a comfortable desired temperature in the rooms by heating and cooling when it is necessary”)
Regarding Claim 3, Motie et al. teaches:
The system of claim 2, wherein the metaverse knowledge graph stores information related to the engineering design or geometry as generated by the at least one design application, and any surrogate models for the design as generated by the at least one surrogate model application. (Motie pg. 237, “AMOEBA3 [4] is composed of agents that build an agnostic
(without knowledge of the meaning) model of AMOEBA inputs, or ”percepts”, on the fly. These agents, called contexts, can be summarized as sets of percepts data ranges wherein each data point from one percept range corresponds to the data in all the other percept ranges (see figure1-a). All the context agents constitute a mapping of co-occurring data in the whole data space (see figure1-b). Moreover, a context agent has a confidence proportional to its percepts data co-occurring frequency.”) The context agents of Motie et al. store precept data, which is related to the “engineering design or geometry” given broadest reasonable interpretation, as changes to the “engineering design or geometry” would change the percept data.
Regarding Claim 6, Motie et al. teaches:
The system of claim 1, wherein the metaverse knowledge graph engine is configured to run update queries received from the plurality of software applications (Motie pg. 237-238, “a new component for dynamic data mediation, called ”DreAMoeba” (see figure 2), operating as follows: 1) Use DREAM to link the subsystems dynamically, each link is described with an (Output, Input) couple (IV-A). 2) For each data couple query, use AMOEBA to translate the data form Output to Input (IV-B).”)
to synchronize metaverse entities of different platforms in the metaverse development pipeline (Motie pg. 240, “We used CosiMate (a co-simulation environment), as in [2], to save the efforts of dealing with synchronization between our subsystems”)
Regarding Claim 7, Motie et al. teaches:
The system of claim 1, wherein scalability of the metaverse knowledge graph is achieved by adding a bidirectional metaverse knowledge graph connection to a new software application being added to the metaverse development pipeline. (Motie pg. 238, “In addition, DREAM is self-adaptive to its environment (see III-B). In other words, it can update the SSGM on-the-fly. This continuous adaptation allows our co-simulation framework to cope with changes occurring in the cyberphysical environment. These changes are: • the evolution of the existing subsystems inputs and outputs… the arrival of new subsystems. DREAM provides, for the new subsystems, links with existing subsystems and replaces previous links with stronger ones, if found.”)
Claim Rejections - 35 USC § 103
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 (i.e., changing from AIA to pre-AIA ) 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.
Claims 4-5 are rejected under 35 U.S.C. 103 as being unpatentable over Motie et al. as applied to claim 1 above, and further in view of Main et al. (US 0220066755 A1, March 3, 2022).
Regarding claim 4, in addition to the limitations of claim 1 taught by Motie et al., Main et al. teaches the following limitations:
The system of claim 1, wherein the plurality of software applications includes at least one simulation application configured to generate a computational fluid dynamics (CFD) simulation model (Main [0029], “The embodiments described herein can be used to create one or more computer programs that can perform the simulations in FIG. 1… For example, the computer program can perform simulations based on computational fluid dynamics (CFD) or other types of physics based or engineering simulations known in the art.”)
corresponding to a particular design geometry for the object under design. (Main [0028], “The embodiments described herein can be used to obtain solutions for models of a physical system, where the models are based on a set of one or more equations such as partial differential equations. These models can be used in simulations of physical objects and physical systems in order to determine whether a particular design of the physical object or physical system satisfies particular requirements for the object or system.”)
Motie et al. and Main et al. are analogous art because they are in the same field of endeavor: modeling graph structures of virtual simulated environments for computer aided design. Therefore, it would have been obvious to one with ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Motie with the additional engineering models and simulations of Main et al. The motivation is that Main seeks to automatically create links between simulations of physical systems (Main [0004], “This disclosure describes various embodiments that can use one or more computation graphs, such as a graph in the form of a directed acyclic graph, to develop software for use in physics based simulations. An embodiment of a method can create a directed acyclic graph (DAG) from a programmer specified set of computation units to solve, in a computer program, physics based simulations of physical systems, and the DAG can be used to analyze and debug the computer program. In this method, the computer program can be created by automatically determining dependency relationships in the set of computation units defined by the one or more programmers and automatically schedule their execution.”).
Regarding claim 5, in addition to the limitations of claim 1 taught by Motie et al., Main et al. teaches the following limitations:
The system of claim 1, wherein the industrial metaverse application comprises: a universal scene description framework to virtually represent the object under design and related industrial system, facility (Main [0033], “Then in operation 105, the data processing system can present (e.g., display on a display device) a directed acyclic graph (DAG) that represents the computation units with their determined dependencies; in this context the DAG is a computation graph. Each node in the DAG can represent one of the computation units. The sequence of the nodes in the graph specify a computational flow that is an ordered sequence or series of computations that run to produce a set of outputs, and the flow of processing (execution of the computation units) can be based upon the dependency relationships determined in operation 103. FIG. 3E shows an example of a DAG having nodes, each node representing one of the computation units.”) The nodes of Main et al. represent different simulations, and the DAG of Main et al. represents the “object under design and related industrial system”.
and user interactions in the metaverse; and a user interactions artifact for tracking information of user interactions with the industrial metaverse. (Main [0030], “The program development environment 75 can be used to create a computer program that includes an input component 77, such as a software user interface configured to receive, through a keyboard or touchscreen or other known input device, definitions of the computation units; for example, an input component 77 of the computer program can receive the definition of a set of computation units from operation 51 in FIG. 2A. The computer program can also include a component 79 which includes a dependency analyzer and an execution scheduler which can perform operations 53 and 55 shown in FIG. 2A. Component 79 uses the definition of the set of computation units provided by one or more programmers to determine a set of dependency relationships among the computation units based upon all of the variables in all of the computation units in the simulation.”)
Motie et al. and Main et al. are analogous art because they are in the same field of endeavor: modeling graph structures of virtual simulated environments for computer aided design. Therefore, it would have been obvious to one with ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Motie with the additional engineering models and simulations of Main et al. The motivation is that Main seeks to automatically create links between simulations of physical systems (Main [0004], “This disclosure describes various embodiments that can use one or more computation graphs, such as a graph in the form of a directed acyclic graph, to develop software for use in physics based simulations. An embodiment of a method can create a directed acyclic graph (DAG) from a programmer specified set of computation units to solve, in a computer program, physics based simulations of physical systems, and the DAG can be used to analyze and debug the computer program. In this method, the computer program can be created by automatically determining dependency relationships in the set of computation units defined by the one or more programmers and automatically schedule their execution.”).
Claim(s) 8-10 are rejected under 35 U.S.C. 103 as being unpatentable over Motie et al. in view of Main et al., and further in view of Canedo et al (US 20140019112 A1, Jan. 16, 2014).
Regarding claim 8, Motie et al. teaches:
A computer-implemented method for developing a virtual environment of an industrial metaverse, (Motie Introduction, “[2] described a new co-simulation framework interoperability based FMI (Functional Mock up Interface) standard for the structural interoperability part and data mediation for semantic interoperability part. In this work, we propose a dynamic mediation for adaptation of the data which allows to go further towards the development of global and open simulation environment.”)
generating, by a knowledge graph engine, an ontology to describe the entities and relationships between the engineering artifacts, simulation model or artificial intelligence (AI) surrogate model; and (Motie pg. 238, “A Subsystem-to-Subsystem Graph Model (SSGM) is a connection graph between the subsystems, encapsulated in FMUs, which displays their communications bridges and therefore describes which outputs from one subsystem are connected to the inputs of another.”) (Motie pg. 235, “The progress of the simulated time in each simulation unit is controlled by an orchestrator, called also a master algorithm. This last one, based upon a co-simulation scenario, moves data from outputs to inputs.”)
instantiating, by the knowledge graph engine, a metaverse knowledge graph with the engineering artifacts, simulation model or AI surrogate model information; and (Motie pg. 238, “A Subsystem-to-Subsystem Graph Model (SSGM) is a connection graph between the subsystems, encapsulated in FMUs, which displays their communications bridges and therefore describes which outputs from one subsystem are connected to the inputs of another.”) (Motie pg. 235, “The progress of the simulated time in each simulation unit is controlled by an orchestrator, called also a master algorithm. This last one, based upon a co-simulation scenario, moves data from outputs to inputs.”)
generating, by an industrial metaverse application, a virtual environment representation of the object under design for an industrial system based on the metaverse knowledge graph; (Motie Introduction, “[2] described a new co-simulation framework interoperability based FMI (Functional Mock up Interface) standard for the structural interoperability part and data mediation for semantic interoperability part. In this work, we propose a dynamic mediation for adaptation of the data which allows to go further towards the development of global and open simulation environment.”)
wherein the virtual environment is updated by the industrial metaverse application based on updates to the metaverse knowledge graph. (Motie pg. 238, “we extend DREAM’s agents with a filtering behavior in order to discard the links (dynamics correlations) between the data streams of the same subsystem and links between data streams of the same type (input-input, output-output), because such links are irrelevant to build a subsystem-to-subsystem graph model (figure 3-b). Besides, we leave to the users the choice, if desired, of a specific subsystem to which they want to link, resulting in the subsystem-to subsystem graph model (figure 3-c).”)
Limitations of claim 8 not taught by Motie et al. are taught by Main et al.:
comprising: generating, by a design software application, engineering artifacts during geometry design of an industrial system; (Main [0029], “Once the schedule of execution has been determined, the data processing system in operation 57 can store an executable representation of the computation units, with their execution order specified in the representation, in a computer program that can be used to perform simulations based on the equations embodied in the computation units. For example, the computer program can perform simulations based on computational fluid dynamics (CFD) or other types of physics based or engineering simulations known in the art. In one embodiment, operation 57 could include storing the available computational units in compiled form so that a schedule and execution order can be determined automatically when the executable object code deployed to customers or licensees of the computer program is executed. The executable representation of the computation units can be part of a larger package of software that performs CAD or CAE, such as Fluent, HFSS, Icepak, or other software products from ANSYS Inc.”)
extracting information from a simulation model or an AI surrogate model; (Main [0029], “Once the schedule of execution has been determined, the data processing system in operation 57 can store an executable representation of the computation units, with their execution order specified in the representation, in a computer program that can be used to perform simulations based on the equations embodied in the computation units. For example, the computer program can perform simulations based on computational fluid dynamics (CFD) or other types of physics based or engineering simulations known in the art. In one embodiment, operation 57 could include storing the available computational units in compiled form so that a schedule and execution order can be determined automatically when the executable object code deployed to customers or licensees of the computer program is executed. The executable representation of the computation units can be part of a larger package of software that performs CAD or CAE, such as Fluent, HFSS, Icepak, or other software products from ANSYS Inc.”)
Motie et al., Main et al., and Canedo et al. are analogous art because they are in the same field of endeavor: modeling via graph structures of model subcomponents in virtual simulated environments for computer aided design. Therefore, it would have been obvious to one with ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Motie with the additional engineering models and simulations of Main et al. The motivation is that Main seeks to automatically create links between simulations of physical systems (Main [0004], “This disclosure describes various embodiments that can use one or more computation graphs, such as a graph in the form of a directed acyclic graph, to develop software for use in physics based simulations. An embodiment of a method can create a directed acyclic graph (DAG) from a programmer specified set of computation units to solve, in a computer program, physics based simulations of physical systems, and the DAG can be used to analyze and debug the computer program. In this method, the computer program can be created by automatically determining dependency relationships in the set of computation units defined by the one or more programmers and automatically schedule their execution.”). Canedo’s motivation is to capture all system information in a single model (Canedo [0016], “A function-based mechatronics object can capture and effectively reuse all data that are relevant to design the concept of a mechatronics system in one file. Such a mechatronics object can include data for 3D design including sub-assemblies, kinematics, and dynamics…”).
Limitations of Claim 8 not taught by Motie et al. in view of Main et al. are taught by Canedo et al.:
extracting geometry of the engineering artifacts from the design software application;
(Canedo [0045], “Simulation code (numerical simulation model 220) can be generated from logical modes through a topological model since it is built on the principle of interconnection between components and energy conservation between its ports.”)
Motie et al., Main et al., and Canedo et al. are analogous art because they are in the same field of endeavor: modeling via graph structures of model subcomponents in virtual simulated environments for computer aided design. Therefore, it would have been obvious to one with ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Motie with the additional engineering models and simulations of Main et al. The motivation is that Main seeks to automatically create links between simulations of physical systems (Main [0004], “This disclosure describes various embodiments that can use one or more computation graphs, such as a graph in the form of a directed acyclic graph, to develop software for use in physics based simulations. An embodiment of a method can create a directed acyclic graph (DAG) from a programmer specified set of computation units to solve, in a computer program, physics based simulations of physical systems, and the DAG can be used to analyze and debug the computer program. In this method, the computer program can be created by automatically determining dependency relationships in the set of computation units defined by the one or more programmers and automatically schedule their execution.”). Canedo’s motivation is to capture all system information in a single model (Canedo [0016], “A function-based mechatronics object can capture and effectively reuse all data that are relevant to design the concept of a mechatronics system in one file. Such a mechatronics object can include data for 3D design including sub-assemblies, kinematics, and dynamics…”).
Regarding claim 9, in addition to the limitations of claim 8 taught by Motie in view of Main and further in view of Canedo, the following limitations are taught by Main:
The method of claim 8, further comprising: logging user interactions or changes to the scene description; (Main [0031], “the comparison can be used to show changes caused by the addition of new computation units or removal of computation units, and the comparison can also be used to show changes within a computation unit…”)
generating an update query for the changes made to the log; (Main [0031], “In one embodiment, these one or more comparisons can also be presented during the process of defining a revised set of computation units if a user is diagnosing or debugging the simulator or computer program.”)
reading the current state of the knowledge graph; (Main [0031], “the comparison can be used to show changes caused by the addition of new computation units or removal of computation units, and the comparison can also be used to show changes within a computation unit…”) Reading a current state is inherent to “comparison”.
reading the update query and updating the models with a query response. (Main [0031], “the comparison can be used to show changes caused by the addition of new computation units or removal of computation units”)
Motie et al., Main et al., and Canedo et al. are analogous art because they are in the same field of endeavor: modeling via graph structures of model subcomponents in virtual simulated environments for computer aided design. Therefore, it would have been obvious to one with ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Motie with the additional engineering models and simulations of Main et al. The motivation is that Main seeks to automatically create links between simulations of physical systems (Main [0004], “This disclosure describes various embodiments that can use one or more computation graphs, such as a graph in the form of a directed acyclic graph, to develop software for use in physics based simulations. An embodiment of a method can create a directed acyclic graph (DAG) from a programmer specified set of computation units to solve, in a computer program, physics based simulations of physical systems, and the DAG can be used to analyze and debug the computer program. In this method, the computer program can be created by automatically determining dependency relationships in the set of computation units defined by the one or more programmers and automatically schedule their execution.”). Canedo’s motivation is to capture all system information in a single model (Canedo [0016], “A function-based mechatronics object can capture and effectively reuse all data that are relevant to design the concept of a mechatronics system in one file. Such a mechatronics object can include data for 3D design including sub-assemblies, kinematics, and dynamics…”).
Regarding claim 10, in addition to the limitations of claim 8 taught by Motie in view of Main and further in view of Canedo, the following limitations are taught by Motie:
The method of claim 8, further comprising: adding a bidirectional metaverse knowledge graph connection to a new software application being added to a metaverse development pipeline. (Motie pg. 238, “A Subsystem-to-Subsystem Graph Model (SSGM) is a connection graph between the subsystems, encapsulated in FMUs, which displays their communications bridges and therefore describes which outputs from one subsystem are connected to the inputs of another.”) (Motie pg. 238, “In addition, DREAM is self-adaptive to its environment (see III-B). In other words, it can update the SSGM on-the-fly … the arrival of new subsystems. DREAM provides, for the new subsystems, links with existing subsystems”) Given broadest reasonable interpretation of “bidirectional”, the limitation is being interpretated as bidirected graph edge, which is taught by the directed edges of Motie.
Motie et al., Main et al., and Canedo et al. are analogous art because they are in the same field of endeavor: modeling via graph structures of model subcomponents in virtual simulated environments for computer aided design. Therefore, it would have been obvious to one with ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Motie with the additional engineering models and simulations of Main et al. The motivation is that Main seeks to automatically create links between simulations of physical systems (Main [0004], “This disclosure describes various embodiments that can use one or more computation graphs, such as a graph in the form of a directed acyclic graph, to develop software for use in physics based simulations. An embodiment of a method can create a directed acyclic graph (DAG) from a programmer specified set of computation units to solve, in a computer program, physics based simulations of physical systems, and the DAG can be used to analyze and debug the computer program. In this method, the computer program can be created by automatically determining dependency relationships in the set of computation units defined by the one or more programmers and automatically schedule their execution.”). Canedo’s motivation is to capture all system information in a single model (Canedo [0016], “A function-based mechatronics object can capture and effectively reuse all data that are relevant to design the concept of a mechatronics system in one file. Such a mechatronics object can include data for 3D design including sub-assemblies, kinematics, and dynamics…”).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Sudev et al. (EP 3796109 A1, 2021) teaches an asset simulation model utilizing components containing design data, engineering data, and simulation data.
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/HENRY JOYNER GOLD/ Examiner, Art Unit 2189
/REHANA PERVEEN/Supervisory Patent Examiner, Art Unit 2189
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