Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design and manufacture of physical structures using toolpaths generated by reinforcement learning for use with subtractive manufacturing systems and techniques, include: obtaining, in a computer aided design or manufacturing program, a three dimensional model of a manufacturable object; generating toolpaths that are usable by a computer-controlled manufacturing system to manufacture at least a portion of the manufacturable object by providing at least a portion of the three dimensional model to a machine learning algorithm that employs reinforcement learning, wherein the machine learning algorithm includes one or more scoring functions that include rewards that correlate with desired toolpath characteristics comprising toolpath smoothness, toolpath length, and avoiding collision with the three dimensional model; and providing the toolpaths to the computer-controlled manufacturing system to manufacture at le

Abstract: A method and system provides the ability to connect steel elements. A design intent model is acquired and consists of a building information model of a skeleton of a building without connections between steel elements that have geometric characteristics. A structural analysis of the structure of the model is performed and generates output consisting of member end forces at intersections of the steel elements. Via a user interface, rules are defined, that associate a potential connection with a structural steel profile. Via a user interface, a script is defined, that dictate where connections should be placed by: identifying second geometric characteristics of the potential connection, identifying forces for steel elements to be connected, comparing the design intent model, the structural analysis output and the rules to the structural steel profile, and autonomously generating and placing, based on the comparison, connections on the BIM model at applicable intersections.

Abstract: A method and system provide the ability to process source computer instructions. The source computer instructions are obtained and include input statements that consist of two functions and one or more arguments. The two functions are competing with each other for consumption of the one or more arguments. For an input statement, an inherent numeric precedence weight is determined for each function and argument. All possible legal configurations of the functions and arguments are determined and consist of different groupings of the functions and arguments. A score is assigned to each grouping and consists of a sum of the weights within each different grouping. The grouping and legal configuration having the highest score is selected. The input statements are compiled into executable code using the selected different grouping.

Abstract: A method and system provide the ability to estimate the vulnerability of a repairable infrastructure system. A survival curve is constructed for one or more assets. A rehabilitation plan is prescribed for one or more failure states of the repairable infrastructure system. A cost estimation model is constructed for costs associated with the repairs for each of the failure states. A planning basis is specified. A multiple probability simulation is conducted that estimates a potential restoration cost for a possible failure. The simulation is repeated to acquire a distribution of potential restoration costs. A vulnerability estimation is determined and provided based on the distribution.

Abstract: A computer-implemented method and system provide the ability to determine and provide a safety risk analysis for construction. Construction related data is obtained and includes textual data and a visual artifact for the construction project. A construction safety context is identified based on the construction related data. Based on the construction safety context, a safety participant risk score that assigns a numerical safety risk participant value to any entity involved in the construction project is determined. Based on the safety risk participant score, a safety project score that assigns a risk level on a per-project basis is determined. The safety risk analysis is presented based on the safety participant risk score and safety project score, via a graphical user interface.

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: An automated robot design pipeline facilitates the overall process of designing robots that perform various desired behaviors. The disclosed pipeline includes four stages. In the first stage, a generative engine samples a design space to generate a large number of robot designs. In the second stage, a metric engine generates behavioral metrics indicating a degree to which each robot design performs the desired behaviors. In the third stage, a mapping engine generates a behavior predictor that can predict the behavioral metrics for any given robot design. In the fourth stage, a design engine generates a graphical user interface (GUI) that guides the user in performing behavior-driven design of a robot. One advantage of the disclosed approach is that the user need not have specialized skills in either graphic design or programming to generate designs for robots that perform specific behaviors or express various emotions.

Abstract: A method and system provide the ability to generate and use synthetic data to extract elements from a floor plan drawing. A room layout is generated. Room descriptions are used to generate and place synthetic instances of symbol elements in each room. A floor plan drawing is obtained and pre-processed to determine a drawing area. Based on the synthetic data symbols in the floor plan drawing are detected. Orientations of the detected symbols are also detected. Based on the detected symbols and orientations, building information model (BIM) elements are fetched and placed in the floor plan drawing.

Abstract: A simulation suggestion system comprising a server connected with a plurality of clients via a network. The server executes a design engine for generating designs, a simulation suggestion engine for identifying suggested simulations for the designs, and a simulation engine for performing the suggested simulations on the designs. The simulation engine includes one or more simulation tools for performing one or more suggested simulations on a design. A user completes a design of an object via the design engine. The simulation suggestion engine automatically identifies one or more simulation tools that are appropriate for the completed design based on at least one characteristic of the design. The simulation suggestion engine automatically identifies and loads simulation parameters (boundary conditions) for the suggested simulation tools. The suggested simulation tools are then performed on the completed design via the simulation engine.

Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design of physical structures using generative design processes, where the 3D models of the physical structures are produced so as to facilitate manufacturing of the physical structures using 2.5-axis subtractive manufacturing systems and techniques, include: obtaining a design space, design criteria, and in-use case(s); iteratively modifying a generatively designed shape in the design space in accordance with the design criteria and the in-use case(s) using a density-based representation of the generatively designed shape and including adjusting the density-based representation of the generatively designed three dimensional shape in accordance with a milling direction of a 2.

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 method and system provide the ability to design a terrain surface. A triangular surface mesh representative of an existing surface is obtained and consists of triangles that are connected by vertices and edges. A drain intention is specified for the terrain surface through a geometry that is a point or line. The drain intention defines a drainage flow that influences a shape of the terrain surface. The mesh is modified using a Voronoi diagram that prevents a drain conflict between mesh triangles. A drain direction is autonomously determined a for each of the mesh triangles based on the drain intention. The determination generates a drain pattern that is used to shape the terrain surface.

Abstract: A method and system provide the ability to manage data. Property sets consisting of property set objects are created based on a schema that defines a type and a version of the objects. The property sets are organized hierarchically to form a property tree. A commit graph stores the property set objects via an append only data structure. The commit graph provides a topology of changes between states of the objects as commit nodes organized as parent commit nodes and child commit nodes. Change sets represent a change between two commit nodes. Each change set tracks changes made on the objects, and the changes specify permitted basic operations including insert, remove, or modify operations that are applied on each state to get to a next state of the objects.

Abstract: In various embodiments, a training application generates a trained encoder that automatically generates shape embeddings having a first size and representing three-dimensional (3D) geometry shapes. First, the training application generates a different view activation for each of multiple views associated with a first 3D geometry based on a first convolutional neural network (CNN) block. The training application then aggregates the view activations to generate a tiled activation. Subsequently, the training application generates a first shape embedding having the first size based on the tiled activation and a second CNN block. The training application then generates multiple re-constructed views based on the first shape embedding. The training application performs training operation(s) on at least one of the first CNN block and the second CNN block based on the views and the re-constructed views to generate the trained encoder.

Abstract: A system and method for generating a submittal register for various construction projects or other items is disclosed. Among other things, the system and method include inputting the construction project specifications in a file format, such as PDF, into a web application interface to convert the specification to a text file, applying an algorithm to the text file based on a set of rules, that are iteratively revised using machine learning, to identify all required submittals, generating a final submittal register, and delivering the final submittal register.

Abstract: Design process that performs geometry synthesis on a 3D model of a product based on a design problem statement and manufacturing constraints associated with a manufacturing machine intended to manufacture the product. The manufacturing constraints may include dimensions for a tool bit, dimensions for a tool head, a set of machining directions of the manufacturing machine, or any combination thereof. For a 5-axis manufacturing machine, the set of machining directions may be determined by a “NormalSearch” algorithm and/or a “HeatSearch” algorithm. The geometry synthesis produces a design solution comprising a final 3D model of the product, whereby each point on the boundary of the final 3D model is determined to be accessible by a tool bit and/or tool head in at least one machining direction of the manufacturing machine. Thus, the design solution for the product is more easily and directly manufacturable by the manufacturing machine.

Abstract: A design engine implements a probabilistic approach to generating designs that exposes automatically-generated design knowledge to the user during operation. The design engine interactively generates successive populations of designs based on a problem definition associated with a design problem and/or a previously-generated population of designs. During the above design process, the design engine generates a design knowledge graphical user interface (GUI) that graphically exposes various types of design knowledge to the user. In particular, the design engine generates a design variable dependency GUI that visualizes various dependencies between designs variables. The design engine also generates a design evolution GUI that animates the evolution of designs across the successive design populations. Additionally, the design engine generates a design exploration GUI that facilitates the user exploring various statistical properties of automatically-generated designs.

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: In one embodiment of the present invention, a method for multiple device interaction includes detecting an orientation of a first device relative to a second device. The method also includes detecting a first gesture performed with either the first device or the second device, wherein the first gesture causes a first action that is based at least in part on the orientation of the first device relative to the second device.

Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for designing three dimensional lattice structures include, in one aspect, a method including: obtaining a mechanical problem definition including a 3D model of an object; generating a numerical simulation model for the 3D model of the object using one or more loading cases and one or more isotropic solid materials identified as a baseline material model for a design space; predicting performance of different lattice settings in different orientations in the design space using a lattice structural behavior model in place of the baseline material model in the numerical simulation model; and presenting a set of lattice proposals for the design space based on the predicted performance of the different lattice settings in the different orientations; wherein the lattice structural behavior model has been precomputed for the different lattice settings, which are generable by the 3D modeling program.