Jean-Luc Bouvard

Review of Hierarchical Multiscale Modeling to Describe the Mechanical Behavior of Amorphous Polymers

Modern computational methods have proved invaluable for the design and analysis of structural components using lightweight materials. The challenge of optimizing lightweight materials in the design of industrial components relates to incorporating structure-property relationships within the computational strategy to incur robust designs. One effective methodology of incorporating structure-property relationships within a simulation-based design framework is to employ a hierarchical multiscale modeling strategy. This paper reviews techniques of multiscale modeling to predict the mechanical behavior of amorphous polymers. Hierarchical multiscale methods bridge nanoscale mechanisms to the macroscale/continuum by introducing a set of structure-property relationships. This review discusses the current state of the art and challenges for three distinct scales: quantum, atomistic/coarse graining, and continuum mechanics. For each scale, we review the modeling techniques and tools, as well as discuss important recent contributions. To help focus the review, we have mainly considered research devoted to amorphous polymers.

The anisotropic compressive mechanical properties of the rabbit patellar tendon.

In this study, we examine the transverse and longitudinal compressive mechanical behavior of the rabbit patellar tendon. The anisotropic compressive properties are of interest, because compression occurs where the tendon attaches to bone and where the tendon wraps around bone leading to the development of fibro-cartilaginous matrices. We quantified the time dependent viscoelastic and anisotropic behavior of the tendon under compression. For both orientations, sections of patellar tendon were drawn from mature male white New Zealand rabbits in preparation for testing. The tendons were sequentially compressed to 40% strain at strain rates of 0.1, 1 and 10% strain(s) using a computer-controlled stepper motor driven device under physiological conditions. Following monotonic loading, the tendons were subjected to stress relaxation. The tendon equilibrium compressive modulus was quantified to be 19.49+/-11.46 kPa for the transverse direction and 1.11+/-0.57 kPa for the longitudinal direction. The compressive modulus at applied strain rates of 0.1, 1 and 10% strain(s) in the transverse orientation were 13.48+/-2.31, 18.24+/-4.58 and 20.90+/-8.60 kPa, respectively. The compressive modulus at applied strain rates of 0.1, 1 and 10% strain/s in the longitudinal orientation were 0.19+/-0.11, 1.27+/-1.38 and 3.26+/-3.49 kPa, respectively. The modulus values were almost significantly different for the examination of the effect of orientation on the equilibrium modulus (p=0.054). Monotonic loading of the tendon showed visual differences of the strain rate dependency; however, no significant difference was shown in the statistical analysis of the effect of strain rate on compressive modulus. The statistical analysis of the effect of orientation on compressive modulus showed a significant difference. The difference shown in the orientation analysis validated the anisotropic nature of the tendon.

Coupled experiment/finite element analysis on the mechanical response of porcine brain under high strain rates

This paper presents a coupled experimental/modeling study of the mechanical response of porcine brain under high strain rate loading conditions. Essentially, the stress wave propagation through the brain tissue is quantified. A Split-Hopkinson Pressure Bar (SPHB) apparatus, using a polycarbonate (viscoelastic) striker bar was employed for inducing compression waves for strain rates ranging from 50 to 750 s(-1). The experimental responses along with high speed video showed that the brain tissues response was nonlinear and inelastic. Also, Finite Element Analysis (FEA) of the SHPB tests revealed that the tissue underwent a non-uniform stress state during testing when glue is used to secure the specimen with the test fixture. This result renders erroneous the assumption of uniaxial loading. In this study, the uniaxial volume averaged stress-strain behavior was extracted from the FEA to help calibrate inelastic constitutive equations.

Data mining and knowledge discovery in materials science and engineering

In this study, data mining and knowledge discovery techniques were employed to validate their efficacy in acquiring information about the viscoelastic properties of vapor-grown carbon nanofiber (VGCNF)/vinyl ester (VE) nanocomposites solely from data derived from a designed experimental study. Formulation and processing factors (VGCNF type, use of a dispersing agent, mixing method, and VGCNF weight fraction) and testing temperature were utilized as inputs and the storage modulus, loss modulus, and tan delta were selected as outputs. The data mining and knowledge discovery algorithms and techniques included self-organizing maps (SOMs) and clustering techniques. SOMs demonstrated that temperature had the most significant effect on the output responses followed by VGCNF weight fraction. SOMs also showed how to prepare different VGCNF/VE nanocomposites with the same storage and loss modulus responses. A clustering technique, i.e., fuzzy C-means algorithm, was also applied to discover certain patterns in nanocomposite behavior after using principal component analysis as a dimensionality reduction technique. Particularly, these techniques were able to separate the nanocomposite specimens into different clusters based on temperature and tan delta features as well as to place the neat VE specimens (i.e., specimens containing no VGCNFs) in separate clusters. Most importantly, the results from data mining are consistent with previous response surface characterizations of this nanocomposite system. This work highlights the significance and utility of data mining and knowledge discovery techniques in the context of materials informatics.

Modeling the mechanical behavior and impact properties of polypropylene and copolymer polypropylene

We present a general internal state variable (ISV) elastic-viscoplastic constitutive model that was initially applied to amorphous polymers (Bouvard et al J Eng Mater Technol 131(4), 041206, 2013) but has been extended to apply to semi-crystalline polymers along with a fracture criterion. In this work, we experimentally calibrated and validated the mechanical behavior of two semi-crystalline polymers (a polypropylene (PP) and a copolymer polypropylene (co-PP)) under different stress states, temperatures, and nominal strain rates. The experiments included compression, tension, impact, and three point bending tests with the notion of capturing the time, temperature, stress state dependence, and failure mechanisms under large strains. The ISV model was integrated into a finite element (FE) code and the FE simulations agreed very well with the PP and co-PP mechanical behavior under compression, impact, and three point bending thus exercising the model under different nominal strain rates, temperatures, and stress states. Two failure criteria were determined from the numerical simulations to build failure criteria maps that distinguished brittle and ductile failure as validated by the experimental observations. This study illustrates the generality of the Bouvard et al. (J Eng Mater Technol 131(4), 041206, 2013), which was previously employed to analyze an amorphous polycarbonate polymer.

Simulation of impact tests on polycarbonate at different strain rates and temperatures

The use of lighter and impact resistant materials, such as polymers, in vehicular systems is an important motivation for the automotive industry as these materials would make vehicles more fuel-efficient without compromising safety standards. In general, polymers exhibit a rich variety of material behavior originating from their particular microstructural (long molecular chains) behavior that is strongly temperature, pressure, and time dependent. To capture such intricate behavior, a number of polymer constitutive models have been proposed and implemented into finite element codes in an effort to solve complex engineering problems (see [1] for a review of these models). However, developing improved constitutive models for polymers that are physically-based is always a challenging area that has important implications for the design of polymeric structural components.

Development of an internal state variable model to describe the mechanical behavior of amorphous polymer and its application to impact testing

The use of lighter and impact resistant materials, such as polymers, in vehicular systems is an important motivation for the automotive industry as these materials would make vehicles more fuel-efficient without compromising safety standards. In general, polymers exhibit a rich variety of material behavior originating from their particular microstructural (long molecular chains) behavior that is strongly temperature, pressure, and time dependent. To capture such intricate behavior, a number of polymer constitutive models have been proposed and implemented into finite element codes in an effort to solve complex engineering problems (see [1] for a review of these models). However, developing improved constitutive models for polymers that are physically-based is always a challenging area that has important implications for the design of polymeric structural components.

Traumatic Brain Injury: Coupled Experiment/Finite Element Simulation on High Rate Mechanical Response of Porcine Brain

Traumatic Brain Injury (TBI), due to recursive concussions, is prevalent in professional sports. Martland was first to report neuropathological conditions related to recursive TBI in professional boxing; while Omalu et al. were the first to report similar neuropathogical conditions, in NFL professionals [1, 2]. Both Martland and Omalu et al. reported long-term neurodegeneration leading to dementia and Alzheimer’s disease [1, 2]. Professional athletes with recursive TBI were observed to have developed speech difficulties, memory lapses, Parkinsons’s-like syndrome with drooling, tremors, and emotional volatility. Although clinical and experimental studies have been carried out to advance the understanding of pathophysiological mechanisms following TBI, limited progress has been made in understanding the effect of stress waves on the neuropathology of TBI using Finite Element Analysis (FEA).Copyright

Mechanical Testing and Material Modeling of Thermoplastics: Polycarbonate, Polypropylene and Acrylonitrile-Butadiene-Styrene

The work presents some results of an ongoing research program aimed at building a material database and material models for specific types of polymers. Results for three thermoplastics are the focus of the present article: polycarbonate, polypropylene, and acrylonitrile-butadiene-styrene. Uniaxial compression / tension tests at room temperature and different strain rates have been performed to characterize their mechanical response. A rate-dependent material model has been developed and implemented in a finite element code ABAQUS to predict such mechanical behavior. The model predictions have shown good agreement with the tests results. Mots clefs: thermoplastiques, essais mecaniques, modelisation numerique