A method for designing fiber-composite parts in which part performance and manufacturing efficiency can be traded-off against one another to provide an “optimized” design for a desired use case. In some embodiments, the method involves generating an idealized fiber map, wherein the orientation of fibers throughout the prospective part align with the anticipated load conditions throughout the part, and then modifying the idealized fiber map by various fabrication constraints to generate a process-compensated preform map.

A method for maintaining a physical asset based on recommendations generated by analyzing operational data and a composite model of a plurality of models representing the physical asset includes constructing, by a computing device, using a port-reduced static condensation reduced basis element approximation of at least a portion of a partial differential equation, the composite model. The computing device analyzes an error indicator associated with at least one model within the composite model to determine that the error indicator exceeds a tolerance level and increases a number of basis functions in the port-reduced static condensation reduced basis element approximation accordingly. The computing device receives first operational data associated with at least one region of the physical asset and updates the composite model. The computing device provides a recommendation for maintaining the physical asset, based upon the updated composite model.

A method for generating a 3D model for fabricating a multi-material object using additive manufacturing. The method comprises providing a first volumetric model of an object in a deformed configuration, generating a second volumetric model from the first volumetric model and assigning materials to the second volumetric model by: a) defining a cluster of elementary volumetric elements of the second volumetric model, b) selecting a cluster object material in the database of object materials by minimizing a cost function determined by computing a deformed configuration of the second volumetric model under a set of predefined loads and constraints, c) partitioning the elementary volumetric elements of the cluster in two sub-clusters based on the deformed configuration, d) repeating step b) for each sub-clusters. The method further comprises generating a 3D model for fabricating an object from the second volumetric model and the assigned materials.

Methods of designing a plybook for a composite component are disclosed. Included method comprising: defining a component volume corresponding to the composite component to be manufactured; defining a plurality of successive plies of composite material to fill the component volume; simulating at least some of the plurality of successive plies of composite material based on an estimate of variable cured ply thickness, wherein the variable cured ply thickness is estimated by: simulating at least a portion of a respective ply of composite material; and estimating a cured ply thickness for the portion of composite material at least partly based on local conditions of the portion. A plybook is defined based on the plurality of simulated plies.

A computer-implemented method is for designing a composite material in which reinforcement fiber base materials are laminated. The composite material includes a hole extending in a lamination direction of the reinforcement fiber base materials and a reinforcement part provided around the hole. The method includes calculating a strain value generated in the composite material based on design factors and a predetermined load condition, the design factors including a shape of the hole, a shape of the reinforcement part, and an orientation angle of each of the reinforcement fiber base materials in respective layers of the reinforcement part; and optimizing the design factors based on a genetic algorithm such that the calculated strain value tends to decrease.

One embodiment of the present invention sets forth a technique for performing a draping simulation of a fabric that includes obtaining a problem definition that includes a fabric cell size, a spring constant ratio, and a three-dimensional (3D) surface. The technique also includes representing the fabric as a set of fabric cells with dimensions that adhere to the fabric cell size, modeling the fabric cells based on a set of side springs and a set of diagonal springs, and setting a first spring constant of the side springs and a second spring constant of the diagonal springs based on the spring constant ratio. The technique further includes propagating the fabric cells along the 3D surface according to the fabric cell size, the first spring constant, and the second spring constant to generate a result of the draping simulation.

Conventional approaches of physical experiments for the effects of cure kinetics in composites materials may lack in capturing lower length scale effects at bulk level. The computational state of the art approaches has not focused on the issue of scale bridging between multiple length scales for manufacturing effects in composites. This limits its usability for specific materials or situations. Embodiments of the present disclosure provide systems and methods that implement a multiscale analysis for determining residual stress and deformation profiles in molded parts comprising composite material. More specifically, present disclosure implements the multiscale analysis wherein a thermal chemical analysis and thermal mechanical analysis are linked to achieve two-way coupling for curing effects at each node/point of molded parts having composite material to provide flexibility and versatility in terms of exploring multiple material combinations without major modification in the approach.

A method and apparatus for obtaining a composite laminate that has plies each composed of a matrix and a filler includes receiving a model and load conditions of a mechanical part to be produced from the composite laminate, predicting properties of a candidate laminate based on features thereof by machine learning, evaluating a performance of the mechanical part produced in accordance with the model from the candidate laminate when subject to the load conditions, based on the predicted properties, optimizing the performance of the mechanical part by varying the features of the candidate laminate and repeating the predicting and evaluating steps until a desired performance is achieved; and determining the candidate laminate thus optimized as the composite laminate for manufacturing the mechanical part, where the method and apparatus can automatically obtain an optimum composite material for a given design task.

A system and methods are disclosed for designing components made from fiber-reinforced anisotropic materials. In accordance with one embodiment, each of a plurality of finite elements of a physical design space are associated with a respective index value that quantifies inclusion of the finite element in a fiber-reinforced component. Each of the finite elements along a longitudinal axis of a fiber of the component are associated with a respective vector specifying a direction of the fiber within the finite element. One or more inputs are provided to a Finite Element Analysis (FEA) simulation for execution by the FEA simulation, where the input(s) are based on the index values and the vectors. A computer system determines a shape for the component and an orientation of the fiber based on one or more outputs of the FEA simulation.

A computer-implemented method for designing a 3D modeled object. The 3D modeled object represents a mechanical part formed in a material having an anisotropic behavior with respect to a physical property. The method includes obtaining a 3D finite element mesh and data associated to the 3D finite element mesh. The data associated to the 3D finite element mesh includes a plurality of forces and boundary conditions. The plurality of forces forms multiple load cases. The method further comprises optimizing an orientation field distributed on the 3D finite element mesh with respect to an objective function. The objective function rewards orientation continuity with respect to the physical property. The optimizing is based on the 3D finite element mesh and on the data associated to the 3D finite element mesh. This constitutes an improved method for designing a 3D modeled object.