Scientific Grand Challenges: Crosscutting Technologies for Computing at the Exascale - February 2-4, 2010, Washington, D.C.

The goal of the "Scientific Grand Challenges - Crosscutting Technologies for Computing at the Exascale" workshop in February 2010, jointly sponsored by the U.S. Department of Energy’s Office of Advanced Scientific Computing Research and the National Nuclear Security Administration, was to identify the elements of a research and development agenda that will address these challenges and create a comprehensive exascale computing environment. This exascale computing environment will enable the science applications identified in the eight previously held Scientific Grand Challenges Workshop Series

A Hierarchical Upscaling Method for Predicting Strength of Materials under Thermal, Radiation and Mechanical loading - Irradiation Strengthening Mechanisms in Stainless Steels

Stainless steels based on Fe-Cr-Ni alloys are the most popular structural materials used in reactors. High energy particle irradiation of in this kind of polycrystalline structural materials usually produces irradiation hardening and embrittlement. The development of predictive capability for the influence of irradiation on mechanical behavior is very important in materials design for next-generation reactors. Irradiation hardening is related to structural information crossing different length scale, such as composition, dislocation, crystal orientation distribution and so on. To predict the effective hardening, the influence factors along different length scales should be considered. A multiscale approach was implemented in this work to predict irradiation hardening of iron based structural materials. Three length scales are involved in this multiscale model: nanometer, micrometer and millimeter. In the microscale, molecular dynamics (MD) was utilized to predict on the edge dislocation mobility in body centered cubic (bcc) Fe and its Ni and Cr alloys. On the mesoscale, dislocation dynamics (DD) models were used to predict the critical resolved shear stress from the evolution of local dislocation and defects. In the macroscale, a viscoplastic self-consistent (VPSC) model was applied to predict the irradiation hardening in samples with changes in texture. The effects of defect density and texture were investigated. Simulated evolution of yield strength with irradiation agrees well with the experimental data of irradiation strengthening of stainless steel 304L, 316L and T91. This multiscale model we developed in this project can provide a guidance tool in performance evaluation of structural materials for next-generation nuclear reactors. Combining with other tools developed in the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the models developed will have more impact in improving the reliability of current reactors and affordability of new reactors

Computational Efficient Upscaling Methodology for Predicting Thermal Conductivity of Nuclear Waste forms

This study evaluated different upscaling methods to predict thermal conductivity in loaded nuclear waste form, a heterogeneous material system. The efficiency and accuracy of these methods were compared. Thermal conductivity in loaded nuclear waste form is an important property specific to scientific researchers, in waste form Integrated performance and safety code (IPSC). The effective thermal conductivity obtained from microstructure information and local thermal conductivity of different components is critical in predicting the life and performance of waste form during storage. How the heat generated during storage is directly related to thermal conductivity, which in turn determining the mechanical deformation behavior, corrosion resistance and aging performance. Several methods, including the Taylor model, Sachs model, self-consistent model, and statistical upscaling models were developed and implemented. Due to the absence of experimental data, prediction results from finite element method (FEM) were used as reference to determine the accuracy of different upscaling models. Micrographs from different loading of nuclear waste were used in the prediction of thermal conductivity. Prediction results demonstrated that in term of efficiency, boundary models (Taylor and Sachs model) are better than self consistent model, statistical upscaling method and FEM. Balancing the computation resource and accuracy, statistical upscaling is a computational efficient method in predicting effective thermal conductivity for nuclear waste form

Characterization of Sound Transmission Loss of Laminated Glass with Analytical and Experimental Approaches

In this project, we have developed the general formation for calculating transmission loss of sound waves through multi-layered structures. Full factorial design method has also been used to investigate the relative effect of various geometric and material parameters on the transmission loss. It was found that within the range of practical interest, the most effect way of increasing transmission loss is by increasing either the glass thickness or increasing the inner layer mass density. Experimental measurements of sound transmission loss (in decibels) for four laminated glass samples have been made in accordance to SAE J1400, in third-octave bands between 125 Hz and 8 kHz

Hosoya and Wiener Index of Zero-Divisor Graph of Z pm q2

In this work, we study zero-divisor graph of the ring Zpmq2 and give some properties of this graph. Furthermore we find Hosoya polynomial and Wiener index for this graph

A Distributed Electrochemistry Modeling Tool for Simulating SOFC Performance and Degradation

This report presents a distributed electrochemistry (DEC) model capable of investigating the electrochemistry and local conditions with the SOFC MEA based on the local microstructure and multi-physics. The DEC model can calculate the global current-voltage (I-V) performance of the cell as determined by the spatially varying local conditions through the thickness of the electrodes and electrolyte. The simulation tool is able to investigate the electrochemical performance based on characteristics of the electrode microstructure, such as particle size, pore size, electrolyte and electrode phase volume fractions, and triple-phase-boundary length. It can also investigate performance as affected by fuel and oxidant gas flow distributions and other environmental/experimental conditions such as temperature and fuel gas composition. The long-term objective for the DEC modeling tool is to investigate factors that cause electrode degradation and the decay of SOFC performance which decrease longevity

Large Scale DD Simulation Results for Crystal Plasticity Parameters in Fe-Cr And Fe-Ni Systems

The development of viable nuclear energy source depends on ensuring structural materials integrity. Structural materials in nuclear reactors will operate in harsh radiation conditions coupled with high level hydrogen and helium production, as well as formation of high density of point defects and defect clusters, and thus will experience severe degradation of mechanical properties. Therefore, the main objective of this work is to develop a capability that predicts aging behavior and in-service lifetime of nuclear reactor components and, thus provide an instrumental tool for tailoring materials design and development for application in future nuclear reactor technologies. Towards this end goal, the long term effort is to develop a physically based multiscale modeling hierarchy, validated and verified, to address outstanding questions regarding the effects of irradiation on materials microstructure and mechanical properties during extended service in the fission and fusion environments. The focus of the current investigation is on modern steels for use in nuclear reactors including high strength ferritic-martensitic steels (Fe-Cr-Ni alloys). The effort is to develop a predicative capability for the influence of irradiation on mechanical behavior. Irradiation hardening is related to structural information crossing different length scales, such as composition, dislocation, and crystal orientation distribution. To predict effective hardening, the influence factors along different length scales should be considered. Therefore, a hierarchical upscaling methodology is implemented in this work in which relevant information is passed between models at three scales, namely, from molecular dynamics to dislocation dynamics to dislocation-based crystal plasticity. The molecular dynamics (MD) was used to predict the dislocation mobility in body centered cubic (bcc) Fe and its Ni and Cr alloys. The results are then passed on to dislocation dynamics to predict the critical resolved shear stress (CRSS) from the evolution of local dislocation and defects. In this report the focus is on the results obtained from large scale dislocation dynamics simulations. The effect of defect density, materials structure was investigated, and evolution laws are obtained. These results will form the bases for the development of evolution and hardening laws for a dislocation-based crystal plasticity framework. The hierarchical upscaling method being developed in this project can provide a guidance tool to evaluate performance of structural materials for next-generation nuclear reactors. Combined with other tools developed in the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the models developed will have more impact in improving the reliability of current reactors and affordability of new reactors

Analysis of Percent On-Cell Reformation of Methane in SOFC Stacks: Thermal, Electrical and Stress Analysis

This report summarizes a parametric analysis performed to determine the effect of varying the percent on-cell reformation (OCR) of methane on the thermal and electrical performance for a generic, planar solid oxide fuel cell (SOFC) stack design. OCR of methane can be beneficial to an SOFC stack because the reaction (steam-methane reformation) is endothermic and can remove excess heat generated by the electrochemical reactions directly from the cell. The heat removed is proportional to the amount of methane reformed on the cell. Methane can be partially pre-reformed externally, then supplied to the stack, where rapid reaction kinetics on the anode ensures complete conversion. Thus, the thermal load varies with methane concentration entering the stack, as does the coupled scalar distributions, including the temperature and electrical current density. The endotherm due to the reformation reaction can cause a temperature depression on the anode near the fuel inlet, resulting in large thermal gradients. This effect depends on factors that include methane concentration, local temperature, and stack geometry