Abstract: Conventionally, manufacturing of molded parts using composite materials has led to poor dimensional accuracy and tensile strength due to improper curing thus resulting in rejection or early/premature failure of composite part. Embodiments of the present disclosure provide simulation-based systems and methods for manufacturing/generating molded parts using reinforced composite materials. The optimized cure cycle is computed for a given component without carrying out numerous experiments. The present disclosure implements multiscale method and surrogate modeling in virtual testing for more accurate and faster manufacturing of molded parts. Process parameters for specified qualities (e.g., minimum residual stresses, minimum deformation, etc.) required for a part are determined along with least process manufacturing time. The resulting optimized time dependent cure cycle for each thermal zone of the heated mold is transferred to a master controller (e.g.

Abstract: Conventionally material selection of composite structure is performed by using discrete materials available in manufacturer's databases. Thus, tailorable nature of composite materials is not exploited to achieve superior performance. Further, conventional methods perform material selection and sizing separately and do not take into account the influence of sizing on material selection and vice versa. Embodiments of the present disclosure provide systems and methods for multiscale material selection for designing of mechanical systems that incorporates tailoring of material microstructures and sizing to achieve improved solutions. The microstructure properties are obtained by using analytical and computational models for various composite materials. These models compute structure-property relations between bulk material properties and their micro-structural constituents.

Abstract: This disclosure generally relates to the field of structural health monitoring, and, more particularly, to a method and system for evaluating residual life of components made of composite materials. Existing methods require performing computational methods such as Finite Element Analysis (FEA) on the results of Non-Destructive Testing (NDT) every time a component is inspected. This makes the process expensive and time-consuming. Thus, embodiments of present disclosure provide a method wherein NDT is performed using different sensing methods such as ultrasound, ultrasound pulse echo, thermography to determine type of defect, location of defect and depth of defect in a test component which are then fed into a pre-trained machine learning model to predict residual life of the component. Testing time is greatly reduced since the pre-trained machine learning model is trained offline using results of the computational methods.

Abstract: Conventionally, manufacturing of molded parts using composite materials has led to poor dimensional accuracy and tensile strength due to improper curing thus resulting in rejection or early/premature failure of composite part. Embodiments of the present disclosure provide simulation-based systems and methods for manufacturing/generating molded parts using reinforced composite materials. The optimized cure cycle is computed for a given component without carrying out numerous experiments. The present disclosure implements multiscale method and surrogate modeling in virtual testing for more accurate and faster manufacturing of molded parts. Process parameters for specified qualities (e.g., minimum residual stresses, minimum deformation, etc.) required for a part are determined along with least process manufacturing time. The resulting optimized time dependent cure cycle for each thermal zone of the heated mold is transferred to a master controller (e.g.

Abstract: 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.

Abstract: Conventionally material selection of composite structure is performed by using discrete materials available in manufacturer's databases. Thus, tailorable nature of composite materials is not exploited to achieve superior performance. Further, conventional methods perform material selection and sizing separately and do not take into account the influence of sizing on material selection and vice versa. Embodiments of the present disclosure provide systems and methods for multiscale material selection for designing of mechanical systems that incorporates tailoring of material microstructures and sizing to achieve improved solutions. The microstructure properties are obtained by using analytical and computational models for various composite materials. These models compute structure-property relations between bulk material properties and their micro-structural constituents.

Abstract: Engineered structures include materials in certain arrangement and proportions to make a composite that provides desired properties to a structure. The mechanical and physical properties of the materials are measured through expensive and time consuming mechanical testing, and structural design is carried out using these properties thus warranting more time and cost spent on physical testing. Embodiments of the present disclosure provide multi-scale modeling and simulation techniques (MSMST) for design of composite materials with desired macro-scale properties wherein the (lower) MSMST are interconnected and each can pass on corresponding desired outputs to higher length-scales, which in turn evaluate macro-scale physical and mechanical properties/either to scale up the structure simulation, or to fine tune computational materials parameters thereby predicting behaviour of the structure based on determined properties of composite materials of the structure.

Abstract: Engineered structures include materials in certain arrangement and proportions to make a composite that provides desired properties to a structure. The mechanical and physical properties of the materials are measured through expensive and time consuming mechanical testing, and structural design is carried out using these properties thus warranting more time and cost spent on physical testing. Embodiments of the present disclosure provide multi-scale modeling and simulation techniques (MSMST) for design of composite materials with desired macro-scale properties wherein the (lower) MSMST are interconnected and each can pass on corresponding desired outputs to higher length-scales, which in turn evaluate macro-scale physical and mechanical properties/either to scale up the structure simulation, or to fine tune computational materials parameters thereby predicting behaviour of the structure based on determined properties of composite materials of the structure.