Abstract: One embodiment of the present invention sets forth a technique for generating a modular design for a construction project. The technique includes executing generating a plurality of design options for the construction project, where each design option includes a site layout and a set of building designs for a set of buildings included in the site layout. The technique also includes computing a first set of performance metrics for the site layout associated with each design option and a second set of performance metrics for the set of building designs associated with each design option, and aggregating the first and second sets of performance metrics into a set of overall performance metrics for each design option. The technique further includes generating a set of candidate designs for the construction project based on the plurality of design options and the overall performance metrics associated with the plurality of design options.

Abstract: One embodiment of the present invention sets forth a technique for generating a multi-building layout for a site. The technique includes instantiating a plurality of agents representing a plurality of buildings located on the site based on a set of boundary conditions associated with the site. The techniques also include iteratively updating a plurality of states associated with the plurality of agents based on the set of boundary conditions and a plurality of behaviors associated with the plurality of agents. The techniques further include generating a layout for the site based on the plurality of states, wherein the layout comprises a plurality of building footprints for the plurality of buildings.

Abstract: One embodiment of the present invention sets forth a technique for generating a layout for a building. The technique includes determining a space occupied by the building and one or more rules associated with one or more example building layouts. The technique also includes iteratively assigning one or more sets of cells within the space to one or more building modules based on the one or more rules, where the one or more building modules represent one or more types of interior space within the building. The technique further includes generating the layout for the building based on the one or more sets of cells assigned to the one or more building modules.

Abstract: An urban design pipeline automatically generates design options for an urban design project. The urban design pipeline includes a geometry engine and an evaluation engine. The geometry engine analyzes design criteria, design objectives, and design heuristics associated with the urban design project and then generates numerous candidate designs. The design criteria specify a property boundary associated with a region of land to be developed. The design objectives indicate a specific type of topology that is derived from an existing urban layout. The design heuristics include different sets of construction rules for generating designs with specific types of topologies. The geometry engine generates candidate designs that conform to the property boundary and have topological characteristics in common with the existing urban layout.

Abstract: A design analysis engine analyzes a CAD assembly to generate a topological model. The topological model is a graph of nodes coupled together via a set of edges. Each node represents a different CAD model in the CAD assembly and each edge represents a different connection between two such CAD models. The design analysis engine also analyzes the CAD assembly to generate a data model corresponding to the topological model. The data model is a structured dataset that includes component entries and connection entries. A component entry includes design data associated with a CAD model in the CAD assembly and a connection entry includes design data associated with a physical or logical connection between two or more such CAD models. A user interacts with the topological model to navigate the CAD assembly, obtain CAD model data, and initiate automatically-performed design tasks.

Abstract: An urban design pipeline automatically generates design options for an urban design project. The urban design pipeline includes a geometry engine and an evaluation engine. The geometry engine analyzes design criteria, design objectives, and design heuristics associated with the urban design project and then generates numerous candidate designs. The design criteria specify a property boundary associated with a region of land to be developed. The design objectives indicate a specific type of topology that is derived from an existing urban layout. The design heuristics include different sets of construction rules for generating designs with specific types of topologies. The geometry engine generates candidate designs that conform to the property boundary and have topological characteristics in common with the existing urban layout.

Abstract: Various embodiments set forth systems and techniques for assessing sustainability of a building design. The techniques include receiving a building design for a budding and sustainability certification data describing a plurality of sustainability certification systems; selecting one or more particular sustainability certification systems from the plurality of sustainability certification systems; computing a respective sustainability certification value for each sustainability certification system of the one or more particular sustainability certification systems; and performing one or more building design operations based on sustainability certification system values for the one or more particular sustainability certification systems.

Abstract: A design application is configured to generate a latent space representation of a fleet of pre-existing vehicles. The design application encodes vehicle designs associated with the fleet of pre-existing vehicles into the latent space representation to generate a first latent space location. The first latent space location represents the characteristic style associated with the fleet of pre-existing vehicles. The design application encodes a sample design provided by a user into the latent space representation to produce a second latent space location. The design application then determines a distance between the first latent space location and the second latent space location. Based on the distance, the design application generates a style metric that indicates the aesthetic similarity between the sample design and the vehicle designs associated with the fleet of pre-existing vehicles. The design application can also generate new vehicle designs based on the latent space representation and the sample design.

Abstract: Various embodiments set forth systems and techniques for determining expandability of a budding design. The techniques include receiving a building geometry indicating a size of a building and a shape of the building; receiving building placement data indicating a placement of the building within a site; identifying one or more remaining spaces within the site based at least on the size of the building, the shape of the building, and the placement of the building within the site; for each remaining space of the one or more remaining spaces: determining whether the remaining space is a usable space; based on the determining whether the remaining space is a usable space, generating a space expansion value corresponding to the remaining space; and computing, based on space expansion values corresponding to the one or more remaining spaces, one or more aggregate expansion values associated with the building geometry and the building placement.

Abstract: In various embodiments, an automobile modeling application generates automobile designs. In operation, the automobile modeling application determines a first parameter value associated with a first instance of a first parameterized automobile component. The automobile modeling application then computes a second parameter value associated with a second instance of a second parameterized automobile component based on a structural relationship between the first instance and the second instance. Subsequently, the automobile modeling application generates a computer-aided design (CAD) geometry model for an automobile based on the first parameter value, the second parameter value, and one or more functional relationships defined between two or more instances included in a set of parameterized automobile component instances.

Abstract: A design engine is configured to interact with potential occupants of a structure in order to generate data that defines the usage preferences of those occupants. The design engine generates multiple candidate designs for the structure via a generative design process, and then evaluates each candidate design using a set of metrics determined relative to the usage preferences. Based on these evaluations, the design engine selects at least one candidate design that optimizes the set of metrics across all potential occupants.

Abstract: A design analysis engine analyzes a CAD assembly to generate a topological model. The topological model is a graph of nodes coupled together via a set of edges. Each node represents a different CAD model in the CAD assembly and each edge represents a different connection between two such CAD models. The design analysis engine also analyzes the CAD assembly to generate a data model corresponding to the topological model. The data model is a structured dataset that includes component entries and connection entries. A component entry includes design data associated with a CAD model in the CAD assembly and a connection entry includes design data associated with a physical or logical connection between two or more such CAD models. A user interacts with the topological model to navigate the CAD assembly, obtain CAD model data, and initiate automatically-performed design tasks.

Abstract: A computer-implemented method for computationally determining ventilation efficiency when generating a building design comprises: generating a first three-dimensional (3D) mesh based on a first 3D building model; performing a first fluid dynamic computer simulation based on the first 3D mesh and first environmental data associated with the first 3D building model to generate a first output data set; and computing, based on the first output data set, a first value for a ventilation performance metric that is associated with the first 3D building model.

Abstract: A computer-implemented method for computationally determining ventilation efficiency when generating a building design comprises: generating a first three-dimensional (3D) mesh based on a first 3D building model; performing a first fluid dynamic computer simulation based on the first 3D mesh and first environmental data associated with the first 3D building model to generate a first output data set; and computing, based on the first output data set, a first value for a ventilation performance metric that is associated with the first 3D building model.

Abstract: In various embodiments, a generative design application generates and evaluates automotive designs. In operation, the generative design application computes a first set of metric values based on a set of metrics associated with design goal(s) and a first set of parameter values for a parameterized automobile model. The generative design application then performs optimization operation(s) on the first set of parameter values based on the first set of metric values to generate a second set of parameter values. Subsequently, the generative design application generates at least one design based on the second set of parameter values that is more convergent with respect to at least one of the design goals than a previously generated design. Advantageously, less time and effort are required to generate and evaluate multiple designs and then optimize those designs relative to more manual prior art approaches.

Abstract: A design application is configured to generate a latent space representation of a fleet of pre-existing vehicles. The design application encodes vehicle designs associated with the fleet of pre-existing vehicles into the latent space representation to generate a first latent space location. The first latent space location represents the characteristic style associated with the fleet of pre-existing vehicles. The design application encodes a sample design provided by a user into the latent space representation to produce a second latent space location. The design application then determines a distance between the first latent space location and the second latent space location. Based on the distance, the design application generates a style metric that indicates the aesthetic similarity between the sample design and the vehicle designs associated with the fleet of pre-existing vehicles. The design application can also generate new vehicle designs based on the latent space representation and the sample design.

Abstract: A design engine is configured to interact with potential occupants of a structure in order to generate data that defines the usage preferences of those occupants. The design engine generates multiple candidate designs for the structure via a generative design process, and then evaluates each candidate design using a set of metrics determined relative to the usage preferences. Based on these evaluations, the design engine selects at least one candidate design that optimizes the set of metrics across all potential occupants.

Abstract: In various embodiments, a generative design application generates and evaluates automotive designs. In operation, the generative design application computes a first set of metric values based on a set of metrics associated with design goal(s) and a first set of parameter values for a parameterized automobile model. The generative design application then performs optimization operation(s) on the first set of parameter values based on the first set of metric values to generate a second set of parameter values. Subsequently, the generative design application generates at least one design based on the second set of parameter values that is more convergent with respect to at least one of the design goals than a previously generated design. Advantageously, less time and effort are required to generate and evaluate multiple designs and then optimize those designs relative to more manual prior art approaches.

Abstract: A design application is configured to generate a latent space representation of a fleet of pre-existing vehicles. The design application encodes vehicle designs associated with the fleet of pre-existing vehicles into the latent space representation to generate a first latent space location. The first latent space location represents the characteristic style associated with the fleet of pre-existing vehicles. The design application encodes a sample design provided by a user into the latent space representation to produce a second latent space location. The design application then determines a distance between the first latent space location and the second latent space location. Based on the distance, the design application generates a style metric that indicates the aesthetic similarity between the sample design and the vehicle designs associated with the fleet of pre-existing vehicles. The design application can also generate new vehicle designs based on the latent space representation and the sample design.

Abstract: Techniques are disclosed for designing manufacturing facilities. A design application imports a computer-aided design (CAD) model and metadata associated with a manufacturing facility to generate a data set that specifies geometric and manufacturing constraints of the manufacturing facility. The design application performs optimization operations based on the data set to identify one or more high-performing designs that assign components to docks in the manufacturing facility. The optimization operations can include genetic optimization operations that generate multiple generations of designs, each of which is evaluated based on a travel distance, congestion, and number of turns associated with paths traversed by components for the design.