Materials Modeling and Simulation

In addition to hands-on material capabilities, CAVS' facilities also have equipment that allows CAVS researchers the ability to model a range of materials, including metals, polymers, bio-materials and cementitious materials. CAVS' design and optimization abilities allow our researchers to evaluate the materials while involved in a variety of tests, including fatigue and fracture, crashworthiness, corrosion and heat treatment, then to adjust the materials in order to reach prime material optimization.

Multiscale Modeling and Simulation


Multiscale modeling techniques employed at CAVS allow the simulation of materials, including novel metal alloys, from the scale of individual atoms and their electronic structure all the way to complete finished structure. To learn more, click the link below:


CAVS researchers are exploring the use of polymers as a prime candidate for future engineering applications. Constructed of highly complex arrangements, polymers can lead the way to highly complex mechanical properties. Increased insight into polymer properties will lead to expansion of polymer usage in high stress and high impact situations.

By using Integrated Computational Materials Engineering (ICME) to study polymer properties, researchers can reduce the cost associated with other methods, while predicting mechanical behavior of polymers through material models and internal state variables (ISV). These variables can be found at the macroscale down to simulations performed at the atomic level.

Microscopic Polymer Image

Areas of application for polymer modeling and simulation include organo-metallic interface study and reinforced polymeric material study.

Polymer Simulation Dataflow


Researchers at the Center for Advanced Vehicular Systems conduct state-of-the-art traumatic brain injury (TBI) research, related to head injuries from contact sports, blast incidents and highway accidents. Our research efforts involve multiscale biomechanical experimentation and computational modeling that assists in TBI diagnostic techniques, injury biomechanics and human-centric engineering design. Additionally, our research also focuses on multiscale experimentation across diverse strain rates and stress states relevant to TBI, as well as on surrogate porcine tissues, in vivo neuron cell cultures and in vivo rodent models. The data obtained from biomechanical experiments feeds into a microstructure-based multiscale constitutive model for the brain to accurately capture primary and secondary injuries arising from TBI.

Image of Table of Data for TBI

The complex nature of TBI necessitates that computational modeling also include nanoscale mechanical aspects. By performing molecular dynamics to simulate the membrane during injury scenarios, nanoscale mechanical and physiological damage can be elucidated and incorporated into the microstructure-based multiscale constitutive model for the brain.

Skull X-ray and simulation
Strain State Deformation Simulation Data

Strain State Deformation Simulation Overview And Membrane Failure Limit Diagram Result. Based on figures from Murphy, M.A. et al. 2018. “Molecular Dynamics Simulations Showing 1-Palmitoyl-2-Oleoyl-Phosphatidylcholine (POPC) Membrane Mechanoporation Damage under Different Strain Paths.” Journal of Biomolecular Structure and Dynamics.

Biomaterials Simulation Dataflow Chart

Multiscale Modelling Hierarchy for Traumatic Brain Injury. Modified from Murphy, Michael A. et al. 2016. “Nanomechanics of Phospholipid Bilayer Failure under Strip Biaxial Stretching Using Molecular Dynamics.” Modelling and Simulation in Materials Science and Engineering 24(5): 055008.

Design and Optimization

Fatigue and Fracture

Crack-Growth Based Fatigue Modeling

Researchers at CAVS have shown that fatigue-life prediction, based on the crack-growth approach, can be considered as an efficient and reliable method for materials fabricated via Additive Manufacturing (AM) process Additive Manufactured (AM) materials. Crack growth based modeling of fatigue appears to be a promising technique for analyzing the life of AM materials under cyclic loading, considering that the cracks already exist in the AM materials (i.e. process induced voids).

To perform fatigue-life calculations, effective stress intensity factor, ΔKeff, as a function of crack growth rate, da/dN, should be obtained from the large-crack data. The plasticity-induced crack-closure model, FASTRAN, is able to predict the fatigue lives based on the size and geometry of initial flaws, as well as the fracture mechanic properties of the material. The variation of fatigue lives with respect to the defect size and shape (i.e. aspect ratio) can also be evaluated by changing the geometry of initial flaw, based on the variations observed in characteristics of defects.

Figure 1 Experimental data and graphs

Figure 1. Experimental data and calculated fatigue curves for L-PBF Inconel 718 in using FASTRAN code.

Multistage Fatigue(MSF) Modeling

The multistage model was developed as a physically-based framework to evaluate sensitivity of fatigue response to various microstructural features. The MSF model also supports materials process design and component-specific tailoring of fatigue resistant materials.

Figure 2 Experimental data and graphs

Figure 2. Predicted upper and lower bounds of total fatigue life for completely reversed, strain-controlled fatigue of 7075-T651 Al alloy (D: particle inclusion size).

MSF approach decomposes fatigue life into four consecutive stages (i.e. crack incubation, propagation of a microstructurally and physically small cracks, and long crack) based on the microstructural details of fatigue crack growth. In addition to the capability of predicting accurate upper and low bounds based on the defect size, this model can conceptually predict the variability due to grain size and orientation.