Venkat Aitharaju - Academia.edu (original) (raw)

Papers by Venkat Aitharaju

Reliability Engineering & System Safety, Jul 1, 2023

Composites Part A-applied Science and Manufacturing, May 1, 2023

The use of continuous carbon fiber composites in load bearing automotive applications can potenti... more The use of continuous carbon fiber composites in load bearing automotive applications can potentially offer significant benefits in weight reduction provided that the key issues regarding the prediction of energy absorption and crash energy management are thoroughly addressed. In this paper, the development of a framework to address the challenges in modeling the crush of non-crimp carbon fiber composites (NCF) is presented. Material models for intra and inter-laminar damage mechanisms were first developed and validated with tensile, bending, and impact experiments. Furthermore, these models were extended to dynamic axial crush of flat specimens and the predicted results were correlated with the experimental results for samples with and without delamination suppression. Good correlations were observed for the crush load and crush morphology, allowing one to unambiguously assess the accuracy of the developed models.

American Society for Composites 2020

SAE Technical Paper Series, 2007

International Journal for Numerical Methods in Engineering, 2020

This paper presents an approach for characterizing and estimating statistical dependence between ... more This paper presents an approach for characterizing and estimating statistical dependence between a large number of observables in a composite material system. Conditional regression is carried out using the estimated joint density function, permitting a systematic exploration of interdependence between fine scale and coarse observables that can be used for both prognosis and design of complex material systems. An example demonstrates the integration of experimental data with a computational database. The statistical approach is based on the probabilistic learning on manifolds recently developed by the authors. This approach leverages intrinsic structure detected through diffusion on graphs with projected stochastic differential equations to generate samples constrained to that structure.

American Society for Composites 2020

Conformally soft gluons are conserved currents of the Celestial Conformal Field Theory (CCFT) and... more Conformally soft gluons are conserved currents of the Celestial Conformal Field Theory (CCFT) and generate a Kac-Moody algebra. We study celestial amplitudes of Yang-Mills theory, which are Mellin transforms of gluon amplitudes and take the double soft limit of a pair of gluons. In this manner we construct the Sugawara energy-momentum tensor of the CCFT. We verify that conformally soft gauge bosons are Virasoro primaries of the CCFT under the Sugawara energy-momentum tensor. The Sugawara tensor though does not generate the correct conformal transformations for hard states. In Einstein-Yang-Mills (EYM) theory, we consider an alternative construction of the energy-momentum tensor, similar to the double copy construction which relates gauge theory amplitudes with gravity ones. This energy momentum tensor has the correct properties to generate conformal transformations for both soft and hard states. We extend this construction to supertranslations.

American Society for Composites 2017

Performance prediction of off-axis laminates is of significant interest in designing composite st... more Performance prediction of off-axis laminates is of significant interest in designing composite structures for energy absorption. Phenomenological models available in most of the commercial programs, where the fiber and resin properties are smeared, are very efficient for large scale structural analysis, but lack the ability to model the complex nonlinear behavior of the resin and fail to capture the complex load transfer mechanisms between the fiber and the resin matrix. On the other hand, high fidelity meso-scale models, where the fiber tows and matrix regions are explicitly modeled, have the ability to account for the complex behavior in each of the constituents of the composite. However, creating a finite element model of a larger scale composite component could be very time consuming and computationally very expensive. In the present study, a threedimensional meso-scale model of non-crimp composite laminates was developed for various laminate schemes. The resin material was modeled as an elastic-plastic material with nonlinear hardening. The fiber tows were modeled with an orthotropic material model with brittle failure. In parallel, new stress based failure criteria combined with several damage evolution laws for matrix stresses were proposed for a phenomenological model. The results from both the meso-scale and phenomenological models were compared with the experiments for a variety of off-axis laminates.

American Society for Composites 2017

This paper will present a general methodology by which weave draping manufacturing simulation res... more This paper will present a general methodology by which weave draping manufacturing simulation results can be utilized to include the effects of weave draping and scissor angle in a structural multiscale simulation. While the methodology developed is general in nature, this paper will specifically demonstrate the methodology applied to a truncated pyramid, utilizing manufacturing simulation weave draping results from ESI PAM-FORM, and multiscale simulation using Altair Multiscale Designer (MDS) and OptiStruct. From a multiscale simulation perspective, the weave draping manufacturing simulation results will be used to develop a series of woven unit cells which cover the range of weave scissor angles existing within the part. For each unit cell, a multiscale material model will be developed, and applied to the corresponding spatial locations within the structural simulation mesh. In addition, the principal material orientation will be mapped from the wave draping manufacturing simulation mesh to the structural simulation mesh using Altair HyperMesh mapping technology. Results of the coupled simulation will be compared and verified against experimental data of the same available via General Motors (GM) Department of Energy (DOE) project.

American Society for Composites 2019, 2019

Advantages such as ultra-lightweighting, parts consolidation, and using newly available fast-curi... more Advantages such as ultra-lightweighting, parts consolidation, and using newly available fast-curing resin formulations are driving the need to develop improved understanding of carbon fiber composites. Towards this end, the present segment of research is focused on developing a multi-scale model to predict the performance of non-orthogonal woven fabric composites. Woven fabrics (where the fiber tows are orthogonal) are used extensively to manufacture components with complex geometries due to their excellent drapability. However, during draping, the fiber tows in the composite preform reorient themselves to conform to the part geometry (the fiber tows are sheared to become non-orthogonal), and the fiber directions may change drastically compared to the original preform, resulting in significant changes in strength and stiffness of the final composite. The ability to include these processing induced effects in predicting the structural performance of these non-orthogonal fabric composites allows us to improve the accuracy of the prediction and optimize the designs. In this paper, a multi-scale modeling approach was developed to predict the performance of composites made using non-orthogonal woven fabrics. Sample coupons molded with and without a pre-determined amount of shearing were evaluated in tensile and three-point bend experiments, and the numerical predictions were compared with the experimental results. A good correlation was observed, validating the developed model.

American Society for Composites 2017, 2017

Composite materials are being used at an increasing rate in the automotive industry due to their ... more Composite materials are being used at an increasing rate in the automotive industry due to their superior mechanical properties at low densities leading to lightweight components. Continuing this trend requires the identification of manufacturing processes for these components that have short cycle times along with delivering reproducible parts. The modeling of these processes is essential in order to prevent the excessive experimentation currently required to develop the process parameters. One of the manufacturing processes currently under consideration is compression resin transfer molding (C-RTM). Recently, General Motors and ESI, NA Group have been working together in developing a state of the art computational tool for process simulation of composites in a project supported by the Department of Energy (DOE). This section of work on the development and validation of a simulation tool for the CRTM process is under the broad scope of the above DOE project. Current development for C-RTM simulation introduces two new technologies embedded into the current PAM-RTM solver: - Fluid-Solid mechanics coupling to determine the preform deformations during the compression-injection process, and - An Inter-Penetrating Mesh providing the ability to handle the vanishing gap during the closing of the mold. This paper will focus on the development and validation of the proposed simulation software using resin flow experiments in a truncated pyramid tool manufactured at General Motors Research and Development Labs.

American Society for Composites 2017, 2017

Design of non-crimp fabric composites (NCF) entails major challenges pertaining to (1) the comple... more Design of non-crimp fabric composites (NCF) entails major challenges pertaining to (1) the complex fine-scale morphology of the constituents, (2) the manufacturingproduced inconsistency of this morphology spatially and across the layers, and thus (3) the ability to build reliable, robust, and efficient computational surrogate models to account for this complex nature. Traditional approaches to construct computational surrogate models have been to average over the fluctuations of the material properties up along the scale length. This fails to account for the fine-scale features and fluctuations in morphology, material properties of the constituents, as well as fine-scale phenomena such as damage and cracks. In addition, it fails to accurately predict the scatter in macroscopic properties, which is vital to the design process and behavior prediction. In this paper, we present an approach for addressing these challenges with minimum assumptions, by relying on polynomial chaos representations of both input parameters and material properties at different scales. Moreover, we emphasize the efficiency and robustness of integrating the polynomial chaos expansion with multiscale tools to perform multiscale assimilation, characterization, propagation, and prediction, all of which are necessary to construct the data-driven surrogate models required to design under the uncertainty of composites. These data-driven constructions provide an accurate map from parameters (and their uncertainties) at all scales and the system-level behavior relevant for design. While this perspective is quite general and applicable to all multiscale systems, NCF composites present a particular hierarchy of scales that permits the efficient implementation of these concepts.

American Society for Composites 2018, 2018

We apply manifold learning and sampling to the tasks of fabrication, manufacturing, and testing o... more We apply manifold learning and sampling to the tasks of fabrication, manufacturing, and testing of composites. We specifically address the challenge associated with statistical inference on these tasks from a small size sample. Limitations on the sample size could emanate from constraints on computational resources as well as constraints on physical experiments. In either case, the analyst is typically presented with a short table that contains observations of environmental conditions and quantities of interest (QoI). In the case of numerical simulations, the QoIs can be at the discretion of the analyst while in a laboratory setting these are typically limited by access to sensing devices. We augment the statistical knowledge captured by the available dataset with knowledge of physics constraints (eg conservation laws) in order to enhance the predictive value of the dataset. Imposing these constraints typically requires additional experiments (either physical or numerical). We proceed differently as we discover, within the dataset, an intrinsic structure that is consistent with the manner in which the available data is interrelated. To that end, we rely on diffusion maps, a recent data-analytics procedure. This allows us to rapidly characterize feasible domains for complex phenomena involving multiscale and Multiphysics interactions. We augment the diffusion map procedure with a stochastic sampler guaranteed to sample on the manifold, thus allowing us to impute a very large sample that is consistent with the statistics of the original dataset and its learned intrinsic features.

Proceedings of the VII European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS Congress 2016), 2016

American Society for Composites 2017, 2017

Woven fabric composites are extensively used in molding complex geometrical shapes due to their h... more Woven fabric composites are extensively used in molding complex geometrical shapes due to their high conformability compared to other fabrics. Preforming is an important step in the overall process. In this step, the two-dimensional fabric is draped to become the three-dimensional shape of the part prior to resin injection. During preforming, the orientation of the tows may change significantly compared to the initial orientations. Accurate prediction of the tow orientations after molding is important for evaluating the structural performance of the final part. This paper investigates the fiber angle changes for carbon fiber woven fabrics during draping over a truncated pyramid tool designed and fabricated at the General Motors Research Labs. This aspect of study is a subset of the broad study conducted under the purview of a Department of Energy project funded to GM in developing state of the art computational tools for integrated manufacturing and structural performance prediction of carbon fiber composites. Fabric bending, picture frame testing, and bias-extension evaluations were carried out to determine the material parameters for these fabrics. The PAM-FORM computer program was used to model the draping behavior of these fabrics. Following deformation, fiber angle changes at different locations on the truncated pyramid were measured experimentally. The predicted angles matched the experimental results well as measured along the centerline and at several different locations on the deformed fabric. Details of the test methods used as well as the numerical results with various simulation parameters will be provided.

American Society for Composites 2018, 2018

Extensive calculations of properties of supernova matter are presented, using the extended Nuclea... more Extensive calculations of properties of supernova matter are presented, using the extended Nuclear Statistical Equilibrium model of Ref. [1] based on a statistical distribution of Wigner-Seitz cells modeled using realistic nuclear mass and level density tables, complemented with a non-relativistic Skyrme functional for unbound particles and beyond drip-line nuclei. Both thermodynamic quantities and matter composition are examined as a function of baryonic density, temperature, and proton fraction, within a large domain adapted for applications in supernova simulations. The results are also provided in the form of a table, with grid mesh and format compatible with the CompOSE platform [2] for direct use in supernova simulations. Detailed comparisons are also presented with other existing databases, all based on relativistic mean-field functionals, and the differences between the different models are outlined. We show that the strongest impact on the predictions is due to the different hypotheses used to define the cluster functional and its modifications due to the presence of a nuclear medium.

American Society for Composites 2018, 2018

American Society for Composites 2020, 2020

Reliability Engineering & System Safety, Jul 1, 2023

Composites Part A-applied Science and Manufacturing, May 1, 2023

The use of continuous carbon fiber composites in load bearing automotive applications can potenti... more The use of continuous carbon fiber composites in load bearing automotive applications can potentially offer significant benefits in weight reduction provided that the key issues regarding the prediction of energy absorption and crash energy management are thoroughly addressed. In this paper, the development of a framework to address the challenges in modeling the crush of non-crimp carbon fiber composites (NCF) is presented. Material models for intra and inter-laminar damage mechanisms were first developed and validated with tensile, bending, and impact experiments. Furthermore, these models were extended to dynamic axial crush of flat specimens and the predicted results were correlated with the experimental results for samples with and without delamination suppression. Good correlations were observed for the crush load and crush morphology, allowing one to unambiguously assess the accuracy of the developed models.

American Society for Composites 2020

SAE Technical Paper Series, 2007

International Journal for Numerical Methods in Engineering, 2020

This paper presents an approach for characterizing and estimating statistical dependence between ... more This paper presents an approach for characterizing and estimating statistical dependence between a large number of observables in a composite material system. Conditional regression is carried out using the estimated joint density function, permitting a systematic exploration of interdependence between fine scale and coarse observables that can be used for both prognosis and design of complex material systems. An example demonstrates the integration of experimental data with a computational database. The statistical approach is based on the probabilistic learning on manifolds recently developed by the authors. This approach leverages intrinsic structure detected through diffusion on graphs with projected stochastic differential equations to generate samples constrained to that structure.

American Society for Composites 2020

Conformally soft gluons are conserved currents of the Celestial Conformal Field Theory (CCFT) and... more Conformally soft gluons are conserved currents of the Celestial Conformal Field Theory (CCFT) and generate a Kac-Moody algebra. We study celestial amplitudes of Yang-Mills theory, which are Mellin transforms of gluon amplitudes and take the double soft limit of a pair of gluons. In this manner we construct the Sugawara energy-momentum tensor of the CCFT. We verify that conformally soft gauge bosons are Virasoro primaries of the CCFT under the Sugawara energy-momentum tensor. The Sugawara tensor though does not generate the correct conformal transformations for hard states. In Einstein-Yang-Mills (EYM) theory, we consider an alternative construction of the energy-momentum tensor, similar to the double copy construction which relates gauge theory amplitudes with gravity ones. This energy momentum tensor has the correct properties to generate conformal transformations for both soft and hard states. We extend this construction to supertranslations.

American Society for Composites 2017

Performance prediction of off-axis laminates is of significant interest in designing composite st... more Performance prediction of off-axis laminates is of significant interest in designing composite structures for energy absorption. Phenomenological models available in most of the commercial programs, where the fiber and resin properties are smeared, are very efficient for large scale structural analysis, but lack the ability to model the complex nonlinear behavior of the resin and fail to capture the complex load transfer mechanisms between the fiber and the resin matrix. On the other hand, high fidelity meso-scale models, where the fiber tows and matrix regions are explicitly modeled, have the ability to account for the complex behavior in each of the constituents of the composite. However, creating a finite element model of a larger scale composite component could be very time consuming and computationally very expensive. In the present study, a threedimensional meso-scale model of non-crimp composite laminates was developed for various laminate schemes. The resin material was modeled as an elastic-plastic material with nonlinear hardening. The fiber tows were modeled with an orthotropic material model with brittle failure. In parallel, new stress based failure criteria combined with several damage evolution laws for matrix stresses were proposed for a phenomenological model. The results from both the meso-scale and phenomenological models were compared with the experiments for a variety of off-axis laminates.

American Society for Composites 2017

This paper will present a general methodology by which weave draping manufacturing simulation res... more This paper will present a general methodology by which weave draping manufacturing simulation results can be utilized to include the effects of weave draping and scissor angle in a structural multiscale simulation. While the methodology developed is general in nature, this paper will specifically demonstrate the methodology applied to a truncated pyramid, utilizing manufacturing simulation weave draping results from ESI PAM-FORM, and multiscale simulation using Altair Multiscale Designer (MDS) and OptiStruct. From a multiscale simulation perspective, the weave draping manufacturing simulation results will be used to develop a series of woven unit cells which cover the range of weave scissor angles existing within the part. For each unit cell, a multiscale material model will be developed, and applied to the corresponding spatial locations within the structural simulation mesh. In addition, the principal material orientation will be mapped from the wave draping manufacturing simulation mesh to the structural simulation mesh using Altair HyperMesh mapping technology. Results of the coupled simulation will be compared and verified against experimental data of the same available via General Motors (GM) Department of Energy (DOE) project.

American Society for Composites 2019, 2019

Advantages such as ultra-lightweighting, parts consolidation, and using newly available fast-curi... more Advantages such as ultra-lightweighting, parts consolidation, and using newly available fast-curing resin formulations are driving the need to develop improved understanding of carbon fiber composites. Towards this end, the present segment of research is focused on developing a multi-scale model to predict the performance of non-orthogonal woven fabric composites. Woven fabrics (where the fiber tows are orthogonal) are used extensively to manufacture components with complex geometries due to their excellent drapability. However, during draping, the fiber tows in the composite preform reorient themselves to conform to the part geometry (the fiber tows are sheared to become non-orthogonal), and the fiber directions may change drastically compared to the original preform, resulting in significant changes in strength and stiffness of the final composite. The ability to include these processing induced effects in predicting the structural performance of these non-orthogonal fabric composites allows us to improve the accuracy of the prediction and optimize the designs. In this paper, a multi-scale modeling approach was developed to predict the performance of composites made using non-orthogonal woven fabrics. Sample coupons molded with and without a pre-determined amount of shearing were evaluated in tensile and three-point bend experiments, and the numerical predictions were compared with the experimental results. A good correlation was observed, validating the developed model.

American Society for Composites 2017, 2017

Composite materials are being used at an increasing rate in the automotive industry due to their ... more Composite materials are being used at an increasing rate in the automotive industry due to their superior mechanical properties at low densities leading to lightweight components. Continuing this trend requires the identification of manufacturing processes for these components that have short cycle times along with delivering reproducible parts. The modeling of these processes is essential in order to prevent the excessive experimentation currently required to develop the process parameters. One of the manufacturing processes currently under consideration is compression resin transfer molding (C-RTM). Recently, General Motors and ESI, NA Group have been working together in developing a state of the art computational tool for process simulation of composites in a project supported by the Department of Energy (DOE). This section of work on the development and validation of a simulation tool for the CRTM process is under the broad scope of the above DOE project. Current development for C-RTM simulation introduces two new technologies embedded into the current PAM-RTM solver: - Fluid-Solid mechanics coupling to determine the preform deformations during the compression-injection process, and - An Inter-Penetrating Mesh providing the ability to handle the vanishing gap during the closing of the mold. This paper will focus on the development and validation of the proposed simulation software using resin flow experiments in a truncated pyramid tool manufactured at General Motors Research and Development Labs.

American Society for Composites 2017, 2017

Design of non-crimp fabric composites (NCF) entails major challenges pertaining to (1) the comple... more Design of non-crimp fabric composites (NCF) entails major challenges pertaining to (1) the complex fine-scale morphology of the constituents, (2) the manufacturingproduced inconsistency of this morphology spatially and across the layers, and thus (3) the ability to build reliable, robust, and efficient computational surrogate models to account for this complex nature. Traditional approaches to construct computational surrogate models have been to average over the fluctuations of the material properties up along the scale length. This fails to account for the fine-scale features and fluctuations in morphology, material properties of the constituents, as well as fine-scale phenomena such as damage and cracks. In addition, it fails to accurately predict the scatter in macroscopic properties, which is vital to the design process and behavior prediction. In this paper, we present an approach for addressing these challenges with minimum assumptions, by relying on polynomial chaos representations of both input parameters and material properties at different scales. Moreover, we emphasize the efficiency and robustness of integrating the polynomial chaos expansion with multiscale tools to perform multiscale assimilation, characterization, propagation, and prediction, all of which are necessary to construct the data-driven surrogate models required to design under the uncertainty of composites. These data-driven constructions provide an accurate map from parameters (and their uncertainties) at all scales and the system-level behavior relevant for design. While this perspective is quite general and applicable to all multiscale systems, NCF composites present a particular hierarchy of scales that permits the efficient implementation of these concepts.

American Society for Composites 2018, 2018

We apply manifold learning and sampling to the tasks of fabrication, manufacturing, and testing o... more We apply manifold learning and sampling to the tasks of fabrication, manufacturing, and testing of composites. We specifically address the challenge associated with statistical inference on these tasks from a small size sample. Limitations on the sample size could emanate from constraints on computational resources as well as constraints on physical experiments. In either case, the analyst is typically presented with a short table that contains observations of environmental conditions and quantities of interest (QoI). In the case of numerical simulations, the QoIs can be at the discretion of the analyst while in a laboratory setting these are typically limited by access to sensing devices. We augment the statistical knowledge captured by the available dataset with knowledge of physics constraints (eg conservation laws) in order to enhance the predictive value of the dataset. Imposing these constraints typically requires additional experiments (either physical or numerical). We proceed differently as we discover, within the dataset, an intrinsic structure that is consistent with the manner in which the available data is interrelated. To that end, we rely on diffusion maps, a recent data-analytics procedure. This allows us to rapidly characterize feasible domains for complex phenomena involving multiscale and Multiphysics interactions. We augment the diffusion map procedure with a stochastic sampler guaranteed to sample on the manifold, thus allowing us to impute a very large sample that is consistent with the statistics of the original dataset and its learned intrinsic features.

Proceedings of the VII European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS Congress 2016), 2016

American Society for Composites 2017, 2017

Woven fabric composites are extensively used in molding complex geometrical shapes due to their h... more Woven fabric composites are extensively used in molding complex geometrical shapes due to their high conformability compared to other fabrics. Preforming is an important step in the overall process. In this step, the two-dimensional fabric is draped to become the three-dimensional shape of the part prior to resin injection. During preforming, the orientation of the tows may change significantly compared to the initial orientations. Accurate prediction of the tow orientations after molding is important for evaluating the structural performance of the final part. This paper investigates the fiber angle changes for carbon fiber woven fabrics during draping over a truncated pyramid tool designed and fabricated at the General Motors Research Labs. This aspect of study is a subset of the broad study conducted under the purview of a Department of Energy project funded to GM in developing state of the art computational tools for integrated manufacturing and structural performance prediction of carbon fiber composites. Fabric bending, picture frame testing, and bias-extension evaluations were carried out to determine the material parameters for these fabrics. The PAM-FORM computer program was used to model the draping behavior of these fabrics. Following deformation, fiber angle changes at different locations on the truncated pyramid were measured experimentally. The predicted angles matched the experimental results well as measured along the centerline and at several different locations on the deformed fabric. Details of the test methods used as well as the numerical results with various simulation parameters will be provided.

American Society for Composites 2018, 2018

Extensive calculations of properties of supernova matter are presented, using the extended Nuclea... more Extensive calculations of properties of supernova matter are presented, using the extended Nuclear Statistical Equilibrium model of Ref. [1] based on a statistical distribution of Wigner-Seitz cells modeled using realistic nuclear mass and level density tables, complemented with a non-relativistic Skyrme functional for unbound particles and beyond drip-line nuclei. Both thermodynamic quantities and matter composition are examined as a function of baryonic density, temperature, and proton fraction, within a large domain adapted for applications in supernova simulations. The results are also provided in the form of a table, with grid mesh and format compatible with the CompOSE platform [2] for direct use in supernova simulations. Detailed comparisons are also presented with other existing databases, all based on relativistic mean-field functionals, and the differences between the different models are outlined. We show that the strongest impact on the predictions is due to the different hypotheses used to define the cluster functional and its modifications due to the presence of a nuclear medium.

American Society for Composites 2018, 2018

American Society for Composites 2020, 2020