Third Annual Texas A&M Research Computing Symposium
Last Updated: May 8, 2019
Mesoscale Modeling of High Burn-up Structure (HBS) Formation and Evolution in UO2
Author(s): M. Gomaa Abdoelatef, F. Badry, Karim Ahmed, Sudipta Biswas2, Andrea Jokisaari, Daniel Schwen, Yongfeng Zhang, Cody Permann
Department: Nuclear Engineering
Simulation and Crash Testing of Rubber Mounted Concrete Barrier
Author(s): Akram Abu-Odeh
Department: Texas A&M Transportation Institute
Advances in energy storage materials driven by high performance computing
Author(s): Perla B. Balbuena (email@example.com)
Department: Department of Chemical Engineering, Texas A&M University, Chemical Engineering
Abstract: The need for advanced research in energy storage technologies has been widely recognized in the US and all over the world, especially due to the advent of renewable energies useful for multiple societal needs including transportation, medicine, and all sort of electronics for multiple applications. In particular, advanced battery technologies require the analysis and test of new chemistries and alternative materials to achieve higher energy densities and higher power densities. In this talk, I will discuss the main problems that need to be solved in the context of batteries that go “beyond lithium-ion” technologies, and how high performance computers help in this task. I will provide examples of problems where our research delivers effective guidelines for materials design.
Probing the hidden details of biomolecular motion
Author(s): Wonmuk Hwang
Reconstructing 3D Heterogeneous Mechanical Property Distribution using Surface Displacement
Author(s): Baik Jin Kim, Dr. Sevan Goenezen
Department: Mechanical Engineering
Abstract: The feasibility of reconstructing 3D heterogenous mechanical property distribution is presented. This is done utilizing only measured surface displacement data and inverse algorithms without making any assumptions about local homogeneities or the material property distribution. This inverse approach finds its application in the field of manufacturing and material science for non-destructive testing of materials and material characterization. 3D problems of the cube with multiple stiff inclusions are tested with utilizing both simulated and experimental displacement data. The inverse method can reconstruct the shear modulus values in the inclusions and background well and reveals the shape and location of the inclusions clearly. Solving the inverse problem requires high computational power. With efficient incorporation of MPI parallelization algorithms at various stages of computation, the required computational time is significantly reduced.
On the feasibility of estimating 3D material parameters of transversely isotropic material using plane stress boundary value problems and Digital Image Correlation (DIC).
Author(s): Maulik Kotecha, Dr. Sevan Goenezen
Department: TEXAS A&M UNIVERSITY
Applications of population genomics to agricultural pest management
Author(s): Tyler Raszick, Ashley Tessnow, C. Michael Dickens, and Gregory Sword
Abstract: Agricultural insect pests can account for up to 23% of crop losses annually. Modern approaches to integrated pest management (IPM) have taken a holistic view of pest control, and as such, necessitate a robust understanding of pest population dynamics and population genetic structure. Population genomics can provide insight into pest biology and address questions related to movement, pesticide resistance, comparative genomics, and pest diagnostics. However, population genomic investigations often involve multiple terabytes of data and require significant computational power. Here, we discuss research on two major pest species, the fall armyworm (Spodoptera frugiperda) and the boll weevil (Anthonomus grandis), conducted using HPRC resources. The fall armyworm is a major global pest of row crops. In the US, this species is comprised of two morphologically identical host strains that are pests on different suites of host plants. The C strain is a primary pest of corn and sorghum, whereas the R strain is primarily a pest on Bermuda grass and pastureland. The objective of this study was to use population genomics to implicitly test hypotheses related to host strain hybridization and spatiotemporal population structure of fall armyworm populations. The boll weevil is infamous for its devastation of the southern United States’ economy in the 1900s. The economic impact of this species led to the development of the Boll Weevil Eradication Program, which eventually eliminated the pest from 97% of its range in the US. Despite the success of this program; however, the boll weevil remains a pest along the US-Mexico border, and occasional re-infestations of previously eradicated areas demonstrate the persistent threat of the boll weevil to US cotton production. Here, we present the use of population genomic methods to estimate likely source populations for this re-infestation. To carry out both studies, we used ddRADseq to identify genome-wide SNP markers. We then used principal component analyses to determine patterns of differentiation between each of our sampled populations.
Patterns of global soil moisture drydown
Author(s): Vinit Sehgal, Nandita Gaur, Binayak Mohanty
Department: Texas A&M University
Generation of concrete microstructures and analysis of long-term performance
Author(s): Christa E. Torrence, Zachary Grasley
Department: Texas A&M University
Modeling Controllable Gene Drive Systems
Author(s): Josef Zapletal, Neda Najmitabrizi, Madhav Erraguntla, Kevin Myles, Mark Lawley, Zach Adelman
Department: Industrial and Systems Engineering