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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Collaborative Research: A Model of Partially Ionized Plasma Flows with Kinetic Treatment of Neutral Atoms and Nonthermal Ions

Interactions of flows of partially ionized, magnetized plasma are frequently accompanied by the presence of both thermal and non-thermal (pickup) ion components. Such interactions cannot be modeled using traditional MHD equations and require more advanced approaches to treat them. If a nonthermal component of ions is formed due to charge exchange and collisions between the thermal (core) ions and neutrals, it experiences the action of magnetic field, its distribution function is isotropized, and it soon acquires the velocity of the ambient plasma without being thermodynamically equilibrated. This situation, e. g., takes place in the outer heliosphere –- the part of interstellar space beyond the solar system whose properties are determined by the solar wind interaction with the local interstellar medium. This is also possible in laboratory, at million degrees and above, when plasma is conducting electricity far too well, which makes Ohmic heating ineffective. To attain the target temperatures one needs additional heating eventually playing a dominant role. Among such sources is a so-called neutral particle beam heating. This is a wide-spread technique (Joint European Torus and International Thermonuclear Experimental Reactor experiments) based on the injection of powerful beams of neutral atoms into ohmically preheated plasma. In this project we have investigated the energy and density separation between the thermal and nonthermal components in the solar wind and interstellar plasmas. A new model has been developed in which we solve the ideal MHD equations for mixture of all ions and the kinetic Boltzmann equation to describe the transport of neutral atoms. As a separate capability, we can treat the flow of neutral atoms in a multi-component fashion, where neutral atoms born in each thermodynamically distinct region are governed by the Euler gas dynamic equations. We also describe the behavior of pickup ions either kinetically, using the Fokker--Planck equation, or as a separate fluid. Our numerical simulations have demonstrated that pickup ions play a major role in the interaction of the solar wind and (partially ionized) interstellar medium plasmas. Our teams have investigated the stability of the surface (the heliopause) that separates the solar wind from the local interstellar medium, the transport of galactic cosmic rays, the properties of the heliotail flow, and modifications to the bow wave in front of the heliopause due to charge exchange between the neutral H atoms born in the solar wind and interstellar ions. Modeling results have been validated against observational data, such as obtained by the Interstellar Boundary Explorer (IBEX), and made it possible to shed light on the structure of energetic neutral atom maps created by this spacecraft.. We have also demonstrated that charge-exchange modulated heliosphere is a source of anisotropy of the multi-TeV cosmic ray flux observed in a number of Earth-bound air shower experiments. Newly developed codes are implemented within a Multi-Scale Fluid-Kinetic Simulation Suite (MS-FLUKSS), a publicly available code being developed by our team for over 12 years. MS-FLUKSS scales well up to 160,000 computing cores and has been ported on major supercomputers in the country. Efficient parallelization and data choreography in the continuum simulation modules are provided by Chombo, an adaptive mesh refinement framework managed by Phillip Colella's team at LBNL. We have implemented in-house, hybrid (MPI+OpenMP) parallelization of the kinetic modules that solve the Boltzmann equation with a Monte Carlo method. Currently, the kinetic modules are being rewritten to take advantage of the modern CPU-GPU supercomputer architecture. The scope of the project allowed us to enhance plasma research and education in such broad, multidisciplinary field as physics of partially ionized plasma and its application to space physics and fusion science. Besides the impact on the modeling of complex physical systems, our approach to computational resource management for complex codes utilizing multiple algorithm technologies appears to be a major advance on current approaches. The development of sophisticated resource management will be essential for all future modeling efforts that incorporate a diversity of scales and physical processes. Our effort provided leadership in promoting computational science and plasma physics within the UAH and FIT campuses and, through the training of a broad spectrum of scientists and engineers, fostering new technologies across the country.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

The Scientific Impact of the Exascale Computing Project

The recent arrival of the Frontier Supercomputer at Oak Ridge National Laboratory officially marked the dawn of the exascale computing era. Its successful deployment coincided with the culmination of the U.S. Department of Energy Exascale Computing Project (ECP), an ambitious, complex, and risky research and development effort that integrated contributions from a broad and diverse subset of the high-performance computing community. The success of ECP will ultimately be judged by the scientific and engineering advances that it enabled. In conclusion, this Special Issue is focused on showcasing early successes in the use of exascale resources to enable breakthroughs in key areas of science in engineering.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

NASA Earth Exchange – Current overview of climate and wildfire-oriented works

NASA Earth Exchange (NEX) combines state-of-the-art supercomputing, Earth system modeling, and NASA remote sensing data feeds to deliver a work environment for exploring and analyzing petabyte-scale datasets covering large regions, continents, or the globe. As an accessible platform, NEX can accelerate fundamental research, develop new applications, and reduce overall project costs by providing the research community with data, software, and high-end computing power. Two research thrusts for the NEX community are developing and distributing the NEX-GDDP-CMIP6 downscaled climate dataset and the community-driven wildfire research. NEX-GDDP-CMIP6 dataset is comprised of global downscaled climate scenarios derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 6 (CMIP6) and across two of the four “Tier 1” greenhouse gas emissions scenarios known as Shared Socioeconomic Pathways (SSPs). The wildfire research thrust leverages geostationary and low earth orbit remote sensing platforms and advanced modeling (WRF). We present a high-level overview of the NEX community, discuss relevant datasets and show several visualization techniques of data used in the wildfire research activity.

NEX↗
DOE OSTI2016

Collaborative Research: A Model of Partially Ionized Plasma Flows with Kinetic Treatment of Neutral Atoms and Nonthermal Ions

Interactions of flows of partially ionized, magnetized plasma are frequently accompanied by the presence of both thermal and non-thermal (pickup) ion components. Such interactions cannot be modeled using traditional MHD equations and require more advanced approaches to treat them. If a nonthermal component of ions is formed due to charge exchange and collisions between the thermal (core) ions and neutrals, it experiences the action of magnetic field, its distribution function is isotropized, and it soon acquires the velocity of the ambient plasma without being thermodynamically equilibrated. This situation, e. g., takes place in the outer heliosphere - the part of interstellar space beyond the solar system whose properties are determined by the solar wind interaction with the local interstellar medium. This is also possible in laboratory, at million degrees and above, when plasma is conducting electricity far too well, which makes Ohmic heating ineffective. To attain the target temperatures one needs additional heating eventually playing a dominant role. Among such sources is a so-called neutral particle beam heating. This is a wide-spread technique (Joint European Torus and International Thermonuclear Experimental Reactor experiments) based on the injection of powerful beams of neutral atoms into ohmically preheated plasma. In this project we have investigated the energy and density separation between the thermal and nonthermal components in the solar wind and interstellar plasmas. A new model has been developed in which we solve the ideal MHD equations for mixture of all ions and the kinetic Boltzmann equation to describe the transport of neutral atoms. As a separate capability, we can treat the flow of neutral atoms in a multi-component fashion, where neutral atoms born in each thermodynamically distinct regions are governed by the Euler gas dynamic equations. We also describe the behavior of pickup ions either kinetically, using the Fokker–Planck equation, or as a separate fluid. Our numerical simulations have demonstrated that pickup ions play a major role in the interaction of the solar wind and (partially ionized) interstellar medium plasmas. Our teams have investigated the stability of the surface (the heliopause) that separates the solar wind from the local interstellar medium, the transport of galactic cosmic rays, the properties of the heliotail flow, and modifications to the bow wave in front of the heliopause due to charge exchange between the neutral H atoms born in the solar wind and interstellar ions. Modeling results have been validated against observational data, such as obtained by the Interstellar Boundary Explorer (IBEX), and made it possible to shed light on the structure of energetic neutral atom maps created by this spacecraft.. We have also demonstrated that charge-exchange modulated heliosphere is a source of anisotropy of the multi-TeV cosmic ray flux observed in a number of Earth-bound air shower experiments. Newly developed codes are implemented within a Multi-Scale Fluid-Kinetic Simulation Suite (MS-FLUKSS), a publicly available code being developed by our team for over 12 years. MS-FLUKSS scales well up to 160,000 computing cores and has been ported on major supercomputers in the country. Efficient parallelization and data choreography in the continuum simulation modules are provided by Chombo, an adaptive mesh refinement framework managed by Phillip Colella’s team at LBNL. We have implemented in-house, hybrid (MPI+OpenMP) parallelization of the kinetic modules that solve the Boltzmann equation with a Monte Carlo method. Currently, the kinetic modules are being rewritten to take advantage of the modern CPU-GPU supercomputer architecture. The scope of the project allowed us to enhance plasma research and education in such broad, multidis- ciplinary field as physics of partially ionized plasma and its application to space physics and fusion science. Besides the impact on the modeling of complex physical systems, our approach to computational resource management for complex codes utilizing multiple algorithm technologies appears to be a major advance on current approaches. The development of sophisticated resource management will be essential for all future modeling efforts that incorporate a diversity of scales and physical processes. Our effort provided leadership in promoting computational science and plasma physics within the UAH and FIT campuses and, through the training of a broad spectrum of scientists and engineers, foster new technologies across the country.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2017

Fireballs in the Sky: An Augmented Reality Citizen Science Program

Fireballs in the Sky is an innovative Australian citizen science program that connects the public with the research of the Desert Fireball Network (DFN). This research aims to understand the early workings of the solar system, and Fireballs in the Sky invites people around the world to learn about this science, contributing fireball sightings via a user-friendly augmented reality mobile app. Tens of thousands of people have downloaded the app world-wide and participated in the science of meteoritics. The Fireballs in the Sky app allows users to get involved with the Desert Fireball Network research, supplementing DFN observations and providing enhanced coverage by reporting their own meteor sightings to DFN scientists. Fireballs in the Sky reports are used to track the trajectories of meteors - from their orbit in space to where they might have landed on Earth. Led by Phil Bland at Curtin University in Australia, the Desert Fireball Network (DFN) uses automated observatories across Australia to triangulate trajectories of meteorites entering the atmosphere, determine pre-entry orbits, and pinpoint their fall positions. Each observatory is an autonomous intelligent imaging system, taking 1000 by 36 megapixel all-sky images throughout the night, using neural network algorithms to recognize events. They are capable of operating for 12 months in a harsh environment, and store all imagery collected. We developed a completely automated software pipeline for data reduction, and built a supercomputer database for storage, allowing us to process our entire archive. The DFN currently stands at 50 stations distributed across the Australian continent, covering an area of 2.5 million square kilometers. Working with DFN's partners at NASA's Solar System Exploration Research Virtual Institute, the team is expanding the network beyond Australia to locations around the world. Fireballs in the Sky allows a growing public base to learn about and participate in this exciting research.

Day, Brian↗
DOE OSTI2019

Aurora: Argonne’s Next-Generation Exascale Supercomputer

Argonne National Laboratory’s next-generation supercomputer, Aurora, will be one of the world’s first exascale systems when it arrives in 2021. The exascale supercomputer, developed in partnership with Intel and Cray, will dramatically accelerate scientific discovery and usher in new technological capabilities, furthering the United States’ scientific leadership position globally. Aurora will be housed at the Argonne Leadership Computing Facility, a U.S. Department of Energy Office of Science User Facility and a premier source of world-class computing resources for open science research since 2006.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1994

High speed civil transport: Sonic boom softening and aerodynamic optimization

An improvement in sonic boom extrapolation techniques has been the desire of aerospace designers for years. This is because the linear acoustic theory developed in the 60's is incapable of predicting the nonlinear phenomenon of shock wave propagation. On the other hand, CFD techniques are too computationally expensive to employ on sonic boom problems. Therefore, this research focused on the development of a fast and accurate sonic boom extrapolation method that solves the Euler equations for axisymmetric flow. This new technique has brought the sonic boom extrapolation techniques up to the standards of the 90's. Parallel computing is a fast growing subject in the field of computer science because of its promising speed. A new optimizer (IIOWA) for the parallel computing environment has been developed and tested for aerodynamic drag minimization. This is a promising method for CFD optimization making use of the computational resources of workstations, which unlike supercomputers can spend most of their time idle. Finally, the OAW concept is attractive because of its overall theoretical performance. In order to fully understand the concept, a wind-tunnel model was built and is currently being tested at NASA Ames Research Center. The CFD calculations performed under this cooperative agreement helped to identify the problem of the flow separation, and also aided the design by optimizing the wing deflection for roll trim.

Cheung, Samson↗
DOE OSTI2024

HydraGNN_Predictive_GFM_2024 - Ensemble of predictive graph foundation models for ground state atomistic materials modeling

We provide the ensemble of fifteen pre-trained graph foundation models (GFMs) for atomistic materials modeling applications. Each one of the fifteen GFMs has been trained on five open-source datasets that (once aggregated) amount to over 154 million atomistic structures, which cover over two-thirds of the natural elements of the periodic table and that comprises a broad set of organic and inorganic compounds. This vast set of atomistic structures comprises ground state configurations that are dynamically stable (i.e., equilibrated structures with atomic forces approximately close to zero values) as well as dynamically unstable structures (i.e., non-equilibrium structures with non-negligible non-zero values of atomic forces). The ensemble of datasets aggregated does NOT include excited states. The datasets have been curated to remove atomistic structures with spectral norm of the force tensor above 100 eV/angstrom. Moreover, a linear term of the energy was computed for each dataset using a linear regression model that uses the chemical concentration of each natural element as regressor. The linear term predicted by the linear regression model has been subtracted from each original energy value to perform a re-alignment of the energy values across different electronic structures approximation theories performed to generate the diverse multi-source, multi-fidelity datasets. The folder "ADIOS_files" contains the set of pre-processed datasets in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used for the development and training of GFMs in this work. The "ADIOS_files" directory contains 6 sub-directories named as follows: - ANI1x-v3.bp - MPTrj-v3.bp - OC2020-20M-v3.bp - OC2020-v3.bp - OC2022-v3.bp - qm7x-v3.bp Each sub-directory contains the pre-processed datasets converted in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used to the development, training, and performance testing of the ensemble go predictive graph foundation models. Each GFM was developed using HydraGNN (https://github.com/ORNL/HydraGNN) as underlying graph neural network (GNN) architecture. The multi-task learning (MTL) capability of HydraGNN was used to simultaneously train the GFMs on labeled values for direct predictions of energy (a total system property of an atomistic structure that measures the chemical stability) and atomic forces (an atomic level property of an atomistic structure that measures the dynamical stability). The hyper parameters of the GFM have been tuned using scalable hyperparameter optimization (HPO) algorithms implemented in the software DeepHyper (https://github.com/deephyper/deephyper). The pre-training of each HPO trial was performed using distributed data parallelism (DDP) to scale the training across 128 compute nodes of the exascale OLCF supercomputer Frontier. Each HPO trial was trained only for 10 epochs and an early stopping was performed to avoid wasting significant computational resources on GNN architectures that were clearly underperforming. For each HPO trial, the 'omnistat' tool developed by (AMD Research - Advanced Micro Device) was used to measure the total energy consumption in kWh. The ensemble of GFMs was obtained by selecting the fifteen best performing HPO trials. Four models have been selected for their clear advantage in accuracy, and these are the GFMs with IDs 229, 156, 147, 260. Additional eleven models have been selected based on judicious balance between accuracy and energy consumption needed for training, and these are the GFMs with IDs 165, 78, 137, 1, 175, 171, 181, 67, 179, 167, 351. Each selected GFM of the ensemble was continued to cumulate a total of at most 30 epochs. In some cases, the total number of epochs actually performed was les than 30 due to two combined factors: (1) the size of the GFM (i.e., the number of model parameters to train) and (2) the total wall-clock time for which the computational resources could be allocated on OLCF-Frontier. The "Ensemble_of_models" directory contains 15 sub-directories named as follows: - gfm_0.229 - gfm_0.156 - gfm_0.147 - gfm_0.260 - gfm_0.165 - gfm_0.78 - gfm_0.137 - gfm_0.1 - gfm_0.175 - gfm_0.171 - gfm_0.181 - gfm_0.67 - gfm_0.179 - gfm_0.167 - gfm_0.351 Each one of these sub-directories refers to one of the fifteen HPO trials that have been selected to continue the pre-training with at most 30 epochs. With each sub-directory associated with a specific HPO trial, the following files can be found: - config.json: file for argument parsing to develop and train an HydraGNN architecture - gfm_0.ID_epoch_N.pk: file with model parameters for HPO ID trial after N epochs of training The ensemble of fifteen GFM architectures was used for (1) ensemble averaging to stabilize the predictions of energy and atomic forces after pre-training for post-processing analysis and (2) ensemble uncertainty quantification (UQ). The code used to develop, pre-train, and load the pre-trained models for post-processing analysis is available on the ORNL-GitHub at the following link: https://github.com/ORNL/HydraGNN/tree/Predictive_GFM_2024

36 MATERIALS SCIENCE↗
NASA NTRS1991

Interactive atmospheric data access via high-speed networks

The VIS-5D system running on large workstations lets scientists interactively explore atmospheric simulation data sets containing up to 5 x 10(exp 7) points. A distributed version of VIS-5D running on a workstation and a supercomputer will make it possible to interactively explore data sets containing up to 10(exp 10) points. Wide area gigabit networks will bring this capability to scientists at most academic and research institutions. This software will help scientists to interactively develop numerical models of atmospheric phenomena.

Hibbard, William↗
DOE OSTI2016

2016 High Performance Computing Annual Report

Sandia National Laboratories’ California site is celebrating its 60th anniversary (1956 to 2016), and high performance computing has been a key enabler for its scientists and engineers throughout much of its history. Since its founding, Sandia California has helped pioneer the use of HPC platforms including hosting Sandia’s first Cray-1 supercomputer in the 1970s and supporting development of scalable cluster computing platforms to create a new paradigm for cost-effective supercomputing in the 1990s. Recent decades of investment in creation of scalable application frameworks for scientific computing have also enabled new generations of modeling and simulation codes. These resources have facilitated computational analysis of complex phenomena in diverse applications spanning national defense, energy, and homeland security. Today, Sandia California researchers work with partners in academia, industry, and national labs to evolve the state-of-the-art in HPC, modeling, and data analysis (including foundational capabilities for exascale computing platforms) and apply them in transformational ways. Research efforts include mitigating the effects of silent hardware failures that can jeopardize the results of large-scale computations, developing exascale-capable asynchronous task-parallel programming models and runtime systems, formulating new techniques to better explore and analyze extreme-scale data sets, and increasing our understanding of materials and chemical sciences which has applications spanning nuclear weapons stockpile stewardship to more efficient automobile engines. The following section highlights some of these research and applications projects and further illustrates the breadth of our HPC capabilities.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1988

The CSM testbed software system: A development environment for structural analysis methods on the NAS CRAY-2

The Computational Structural Mechanics (CSM) Activity at Langley Research Center is developing methods for structural analysis on modern computers. To facilitate that research effort, an applications development environment has been constructed to insulate the researcher from the many computer operating systems of a widely distributed computer network. The CSM Testbed development system was ported to the Numerical Aerodynamic Simulator (NAS) Cray-2, at the Ames Research Center, to provide a high end computational capability. This paper describes the implementation experiences, the resulting capability, and the future directions for the Testbed on supercomputers.

Gillian, Ronnie E.↗
DOE OSTI2025

WorkflowHub: a registry for computational workflows

The rising popularity of computational workflows is driven by the need for repetitive and scalable data processing, sharing of processing know-how, and transparent methods. As both combined records of analysis and descriptions of processing steps, workflows should be reproducible, reusable, adaptable, and available. Workflow sharing presents opportunities to reduce unnecessary reinvention, promote reuse, increase access to best practice analyses for non-experts, and increase productivity. In reality, workflows are scattered and difficult to find, in part due to the diversity of available workflow engines and ecosystems, and because workflow sharing is not yet part of research practice. WorkflowHub provides a unified registry for all computational workflows that links to community repositories, and supports both the workflow lifecycle and making workflows findable, accessible, interoperable, and reusable (FAIR). By interoperating with diverse platforms, services, and external registries, WorkflowHub adds value by supporting workflow sharing, explicitly assigning credit, enhancing FAIRness, and promoting workflows as scholarly artefacts. The registry has a global reach, with hundreds of research organisations involved, and more than 800 workflows registered.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

ParFlow Sand Tank: A tool for groundwater exploration

The ParFlow Sand Tank model is an open source application designed to allow users to interactively simulate and visualize groundwater movement through the subsurface. The app is designed for both research and education; teaching hydrogeology concepts and making it easy explore and run sophisticated groundwater simulations. Our goal is to support increased accessibility and usability of research grade hydrology tools for research and teaching. The Sand Tank application simulates groundwater and surface water fluxes as well as contaminant transport in real time using the integrated physical hydrology model ParFlow (Kollet & Maxwell, 2006; Maxwell & Miller, 2005; Osei-Kuffuor et al., 2014) and the particle tracking code EcoSlim (Maxwell et al., 2019). ParFlow is a numerical hydrology model that simulates spatially distributed groundwater and surface water flow. It is a well established research tool with more than 90 publications documenting its development use to advance our understanding of groundwater dynamics and groundwater surface water interactions from the hillslope to the continental scale e.g. (Condon et al., 2020; Condon & Maxwell, 2019; Maxwell & Condon, 2016). It is designed for efficient parallel computation and has been run on many platforms spanning from laptops to supercomputers. However, one of the challenges of ParFlow is that it requires significant training and hydrologic expertise to develop simulations. The Sand Tank application makes this model accessible to anyone for education and exploration. Our application uses ParFlow for its simulation backend and ParaView for the data loading and processing. The communication infrastructure relies on the ParaViewWeb framework. We use model templates deployed in Docker images to setup the Sand Tank framework. Users can build the application locally or interact with it through our web deployment. When interacting with a template users can interactively change model parameters like subsurface processes or pump/inject water into the subsurface and watch the system respond to their changes in real time as the simulation runs. Additionally, our template setup will allow more advanced users to build custom templates of increasing complexity for both research and educational purposes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Navigating Exascale Operational Data Analytics: From Inundation to Insight

In this paper, we address the challenges in achieving sustainable data-driven efficiency by providing a detailed exploration of the end-to-end operational data analytics (ODA) framework that evolved through two generations of supercomputer systems at the Oak Ridge Leadership Computing Facility (OLCF). This framework addresses large data streams ingested from heavily instrumented HPC environment that accumulates multi-terabytes per day. We outline the multifaceted data life cycle across HPC procurement, operations, and research & development, identifying key obstacles and design decisions that shape effective strategies in building and supporting data pipelines end-to-end. By sharing key insights and lessons learned from our experience, we offer recommendations for the HPC community on enabling sustainable operational data analytics and beyond. Our contributions aim to bridge the gap between potential and real benefits of operational data, guiding future efforts towards integrated and sustainable operational intelligence in high-performance computing environments.

Shin, Woong↗
DOE OSTI2021

FY 2021 Mid-Year HPC Utilization Report M3UF-21IN0701018

Idaho National Laboratory (INL), supported by the Department of Energy Office of Nuclear Energy (DOE-NE) through the Nuclear Science User Facilities, provides access to supercomputer systems and data storage along with support staff for system management, software installation, cybersecurity and user support to the broader DOE-NE user community. Users include individuals at universities, industry, and government laboratories enabling a wide range of research and development and mission-supporting activities. The availability of high-performance computing (HPC) capabilities is a key foundation of collaboration and innovation in nuclear energy systems research. HPC resources and INL directly support the mission and objectives of DOE-NE. From October 2020 through March 2021, INL HPC capabilities were utilized by a diverse set of computing and applied researchers, for a wide range of research and engineering activities. This report focuses on current INL HPC systems and utilization from October 1, 2020 through March 31, 2021.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1994

Design of orbital debris shields for oblique hypervelocity impact

A new impact debris propagation code was written to link CTH simulations of space debris shield perforation to the Lagrangian finite element code DYNA3D, for space structure wall impact simulations. This software (DC3D) simulates debris cloud evolution using a nonlinear elastic-plastic deformable particle dynamics model, and renders computationally tractable the supercomputer simulation of oblique impacts on Whipple shield protected structures. Comparison of three dimensional, oblique impact simulations with experimental data shows good agreement over a range of velocities of interest in the design of orbital debris shielding. Source code developed during this research is provided on the enclosed floppy disk. An abstract based on the work described was submitted to the 1994 Hypervelocity Impact Symposium.

Fahrenthold, Eric P.↗
NASA NTRS1991

Development of ISO connection-oriented/correctionless gateways

The project had two goals, establishment of a gateway between French and U.S. academic networks and studies of issues related to the development of ISO connection-oriented/connectionless (CO/CL) gateways. The first component involved installation of a 56K bps line between Princeton Univ. and INRIA in France. The end-points of these lines were connected by Vitalink link level bridges. The Princeton end was then connected to the NSFNET via the John Von Neumann Supercomputer Center. The French end was connected to Transpac, the French X.25 public data network and to the French IP research internet. U.S. users may communicate with users of the French internet by e-mail and may access computational and data resources in France by use of remote login and file transfer. The connection to Transpac enables U.S. users to access the SIMBAD astronomical database outside of Paris. Access to this database from the U.S. can be via TCP/IP or DECNET (via a DECNET to TCP/IP gateway) protocols utilizing a TCP/IP to X.25 gateway developed and operated by INRIA. The second component of the project involved experiments aimed at understanding the issues involved is ISO CO/CL gateways. An experimental gateway was developed at Wisconsin and a preliminary report was prepared. Because of the need to devote most resources to the first component of the project, work in this area did not go beyond development of a prototype gateway.

Landweber, Lawrence H.↗
DOE OSTI2016

Modelling the local atomic structure of molybdenum in nuclear waste glasses with ab initio molecular dynamics simulations

The nature of chemical bonding of molybdenum in high level nuclear waste glasses has been elucidated by ab initio molecular dynamics simulations. Two compositions, (SiO2)57.5 – (B2O3)10 – (Na2O)15 – (CaO)15 – (MoO3)2.5 and (SiO2)57.3 – (B2O3)20 – (Na2O)6.8 – (Li2O)13.4 – (MoO3)2.5 , were considered in order to investigate the effect of ionic and covalent components on the glass structure and the formation of the crystallisation precursors (Na2MoO4 and CaMoO4). The coordination environments of Mo cations and the corresponding bond lengths calculated from our model are in excellent agreement with experimental observations. The analysis of the first coordination shell reveals two different types of molybdenum host matrix bonds in the lithium sodium borosilicate glass. Based on the structural data and the bond valence model, we demonstrate that the Mo cation can be found in a redox state and the molybdate tetrahedron can be connected with the borosilicate network in a way that inhibits the formation of crystalline molybdates. These results significantly extend our understanding of bonding in Mo-containing nuclear waste glasses and demonstrate that tailoring the glass composition to specific heavy metal constituents can facilitate incorporation of heavy metals at high concentrations. K.K. was supported through the Impact Studentship scheme at UCL co-funded by the IHI Corporation and UCL. P.V.S. thanks the Royal Society, which supported preliminary work on this project, and the Laboratory Directed Research and Development program at PNNL, a multiprogram national laboratory operated by Battelle for the U.S. Department of Energy. Via our membership of the UK's HEC Materials Chemistry Consortium, which is funded by EPSRC (EP/L000202), this work used the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗