MD-HM: Memoization-based Molecular Dynamics Simulations on Big Memory System
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Computer science↗
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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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Demystifying and Optimizing the Performance of HPC Applications on NVM-based Memory Systems
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Computer science↗
Edge at the Pier: EPCAPE Software-Defined Sensing Field Campaign Report
The Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) was aimed to enhance the understanding of cloud and aerosol properties in the region surrounding La Jolla, California. To address challenges in data collection and processing from various instruments, an edge computing device known as Waggle Sage Node (WSN) was deployed at the Ellen Browning Scripps Memorial Pier. WSN is a distributed-sensing platform designed to collect and analyze environmental data at the edge. Sage is a multi-agency-supported project that designs and builds a new kind of national-scale reusable cyberinfrastructure to enable artificial intelligence (AI) at the edge based on the Waggle platform. Sponsors include the U.S. Department of Energy (DOE) Advanced Scientific Computing Research (ASCR), DOE National Nuclear Security Administration (NNSA), DOE Biological and Environmental Research (BER) through DOE Artificial Intelligence for Earth System Predictability (AI4ESP), Argonne Laboratory-Directed Research and Development (LDRD). Sage (https://sagecontinuum.org/) is funded as a National Science Foundation Mid-Scale Research Infrastructure (MSRI) project (https://www.nsf.gov/awardsearch/showAward?AWD_ID=1935984). This robust, multi-architecture edge computing platform facilitated environmental monitoring during the campaign. This report details the scientific objectives, deployment process, and key results of integrating Waggle into the EPCAPE field campaign.
54 ENVIRONMENTAL SCIENCES↗
Validation of a 2.5D CFD model for cylindrical gas–solids fluidized beds
The 2.5D model recently proposed by Li et al. (Li, T., Benyahia, S., Dietiker, J., Musser, J., and Sun, X., 2015. A 2.5D computational method to simulate cylindrical fluidized beds. Chemical Engineering Science. 123, 236-246.) was validated for two cylindrical gas-solids bubbling fluidized bed systems. Different types of particles tested under various flow conditions were simulated using the traditional 2D model and the 2.5D model. Detailed comparison against the experimental measurements on solid concentration and velocity were conducted. Comparing to the traditional Cartesian 2D flow simulation, the 2.5D model yielded better agreement with the experimental data especially for the solid velocity prediction in the column wall region.
Numerical simulation↗
Quantum simulation algorithms that optimally exploit problem structure [Slides]
The overarching goal is to improve quantum algorithms for the simulation of quantum systems.
97 MATHEMATICS AND COMPUTING↗
Elastic Workflows with PMIx [Slides]
Scientific workflows increasing in complexity. Elastic workflows promise improved application and system performance.
97 MATHEMATICS AND COMPUTING↗
In Situ Visualization for Computational Science (Dagstuhl Seminar 18271)
In situ visualization, i.e., visualizing simulation data as it is generated, is an emerging processing paradigm in response to trends in the area of high-performance computing. This paradigm holds great promise in its ability to access increased spatio-temporal resolution and leverage extensive computational power. However, the paradigm is also widely viewed as limiting when it comes to exploration-oriented use cases and further will require visualization systems to become more and more complicated and constrained. Additionally, there are many open research topics with in situ visualization. The Dagstuhl seminar 18271 “In Situ Visualization for Computational Science” brought together researchers and practitioners from three communities (computational science, high-performance computing, and scientific visualization) to share interesting findings, to identify lines of open research, and to determine a medium-term research agenda that addresses the most pressing problems. This report summarizes the outcomes and findings of the seminar.
97 MATHEMATICS AND COMPUTING↗
Accelerating the discovery of low-energy structure configurations: A computational approach that integrates first-principles calculations, Monte Carlo sampling, and Machine Learning
Finding Minimum Energy Configurations (MECs) is essential in fields such as physics, chemistry, and materials science, as they represent the most stable states of the systems. In particular, identifying such MECs in multi-component alloys considered candidate PFMs is key because it determines the most stable arrangement of atoms within the alloy, directly influencing its phase stability, structural integrity, and thermo-mechanical properties. However, since the search space grows exponentially with the number of atoms considered, obtaining such MECs using computationally expensive first-principles DFT calculations often results in a cumbersome task. To escape the above compromise between physical fidelity and computational efficiency, we have developed a novel physics-based data-driven approach that combines Monte Carlo sampling, first-principles DFT calculations, and Machine Learning to accelerate the discovery of MECs in multi-component alloys. More specifically, we have leveraged well-established Cluster Expansion (CE) techniques with Local Outlier Factor models to establish strategies that enhance the reliability of the CE method. In this work, we demonstrated the capabilities of the proposed approach for the particular case of a tungsten-based quaternary high-entropy alloy. However, the method is applicable to other types of alloys and enables a wide range of applications.
36 MATERIALS SCIENCE↗
Development of a Methodology to Assess the Impact of Non-Conventional Waste Streams Following a Radiological Incident - 18271
The Environmental Protection Agency's (EPA's) Waste Estimation Support Tool (WEST) is a Geographic Information System (GIS)-based decision support tool for estimating waste generated from remediation and cleanup activities following a radiological incident. WEST uses the Federal Emergency Management Agency's (FEMA's) Hazus-MH software's infrastructure information combined with image classification capabilities to estimate the quantity of waste and debris that may result from a radiological incident. WEST can be used to create customized decontamination strategies that allow end-users to evaluate different means of decontamination and how those strategies may impact the resulting waste stream in each geographical locality. This capability can potentially reduce the response/recovery time frame and cost. One of the key observations from past applications of WEST is that planning scenarios are site-specific, especially when dealing with chemical, biological, radiological, or nuclear (CBRN) waste management issues. Furthermore, site-specific issues are not limited to resource limitations or response bottlenecks but should also account for differences in an area's geography and urban footprint, a phenomenon observed during the Fukushima response. For instance, a recent WEST case study found that the amount of waste generated per unit of affected area, for a given decontamination approach, is largely a function of the building surface area in the affected area (relative to the ground surfaces). However, differences in the geometry and density of contaminated objects in the landscape may impact the amount and characteristics of the waste stream. Although buildings typically constitute a large portion of the surface area in urban environments, other objects such as vehicles and trees can be just as prominent. For example, seasonal changes in the amount of foliage present can alter the non-structural surface area calculated for an area like New York City by 20-30%. Very little is known about the impact that these non-conventional waste streams have on overall remediation strategies, or to what extent differences in characteristics of urban versus rural environments, traffic activities, or seasonal variations may have on these factors. This paper will present the proposed methodology to incorporate into WEST the impacts that niche, nonconventional waste streams might have from rural and urban environments following a nuclear power plant incident or detonation of a radiological dispersal device or improvised nuclear device. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Unitary Qubit Lattice Algorithms for Plasma Physics
This final technical report summarizes research conducted under DOE Award DE-SC0021653 to develop unitary Quantum Lattice Algorithms for modeling electromagnetic wave propagation and scattering in complex media, including plasmas. The project developed and validated quantum-inspired formulations of Maxwell's equations that preserve unitary evolution and can be evaluated on classical high-performance computing systems while providing a foundation for future quantum-computing implementations. Major accomplishments include the development of two- and three-dimensional algorithms for electromagnetic scattering; scalable, distributed-memory implementations demonstrated on the Perlmutter supercomputer; formulations for nonlinear lossless fluid dynamics and cold, lossless, inhomogeneous magnetized plasmas; and an explicit quantum algorithm for a time-discretized Lorenz model. Simulations reproduced a range of characteristic wave phenomena, including transient effects that are not readily apparent in conventional frequency-domain studies, demonstrating the effectiveness of the proposed approach for modeling complex electromagnetic and plasma systems. The work establishes a unified theoretical and computational framework for quantum and quantum-inspired simulation and provides a foundation for future implementation on fault-tolerant quantum systems.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Quantum electron transport in degenerate donor–acceptor systems
In this work, we develop a mathematically rigorous theory for the quantum transfer processes in degenerate donor–acceptor dimers in contact with a thermal environment. We explicitly calculate the transfer rates and the acceptor population efficiency. The latter depends critically on the initial donor state. Additionally, we show that quantum coherence in the initial state enhances the transfer process. If the electron is initially shared coherently by the donor levels, then the efficiency can reach values close to 100%, while an incoherent initial donor state will significantly suppress the efficiency. The results are useful for a better understanding of the quantum electron transport in many chemical, solid state, and biological systems with complex degenerate and quasi-degenerate energy landscapes.
36 MATERIALS SCIENCE↗
Analytical Cost Metrics : Days of Future Past
As we move towards the exascale era, the new architectures must be capable of running the massive computational problems efficiently. Scientists and researchers are continuously investing in tuning the performance of extreme-scale computational problems. These problems arise in almost all areas of computing, ranging from big data analytics, artificial intelligence, search, machine learning, virtual/augmented reality, computer vision, image/signal processing to computational science and bioinformatics. With Moore’s law driving the evolution of hardware platforms towards exascale, the dominant performance metric (time efficiency) has now expanded to also incorporate power/energy efficiency. Therefore the major challenge that we face in computing systems research is: “how to solve massive-scale computational problems in the most time/power/energy efficient manner?”
97 MATHEMATICS AND COMPUTING↗
Modeling COVID-19 Impacts on Prison Population
The goal of this project was to develop a unique, high-level, concept model that will (1) help examine the consequences COVID-19 has had on prison population and flow dynamics in Illinois and (2) explore (to the extent possible) how that will unfold in the short- and mid-term future. Argonne has unique expertise in dynamic systems modeling and highly specialized simulation capabilities, which will be helpful in developing such a model. The ultimate objective of this CRADA is to develop with the Illinois Public Sentencing Policy Advisory Council (SPAC) the capability to identify and understand factors and interactions associated with prison population and flow dynamics in Illinois. This understanding will then potentially lead to improvements in the allocation of various resources and services. This approach would also be useful to other states.
59 BASIC BIOLOGICAL SCIENCES↗
ADIOS 2: The Adaptable Input Output System. A framework for high-performance data management
Not Available
97 MATHEMATICS AND COMPUTING↗
Neutron Activation Foil and Thermoluminescent Dosimeter Responses to a Polyethylene Reflected Pulse of the CEA Valduc SILENE Critical Assembly
This benchmark experiment was conducted as a joint venture between the US Department of Energy (DOE) and the French Commissariat à l'Energie Atomique (CEA). Staff at the Oak Ridge National Laboratory (ORNL) in the US and the Centre de Valduc in France planned this experiment. The experiment was conducted on October 19, 2010 in the SILENE critical assembly facility at Valduc. Several other organizations contributed to this experiment and the subsequent evaluation, including CEA Saclay, Lawrence Livermore National Laboratory (LLNL), the Y-12 National Security Complex (NSC), Babcock International Group in the United Kingdom, and Los Alamos National Laboratory (LANL). The goal of this experiment was to measure neutron activation and thermoluminescent dosimeter (TLD) doses from a source similar to a fissile solution critical excursion. The resulting benchmark can be used for validation of computer codes and nuclear data libraries as required when performing analysis of criticality accident alarm systems (CAASs). A secondary goal of this experiment was to qualitatively test performance of two CAAS detectors similar to those currently and formerly in use in some US DOE facilities. The detectors tested were the CIDAS MkX and the Rocky Flats NCD-91. The CIDAS detects gammas with a Geiger-Muller tube and the Rocky Flats detects neutrons via charged particles produced in a thin 6 LiF disc depositing energy in a Si solid state detector. These detectors were being evaluated to determine whether they would alarm, so they were not expected to generate benchmark quality data.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Evolution of microstructures in radiation fields using a coupled binary-collision Monte Carlo phase field approach
The simulation of radiation effects in materials broadly falls into two categories. At short time and length scales lies the modeling of primary radiation damage, such as point defect creation, energy deposition, and ballistic mixing. This is followed by the modeling at longer time scales of thermally activated microstructure evolution and defect reactions, such as recombination, clustering, and coarsening. The binary collision Monte Carlo method is an established, numerically efficient method for the computation of primary radiation damage. Conversely, the phase field method is a state of the art method for microstructure evolution on longer time and length scales. Here we present a concurrent coupling of these two methods, overcoming the difference between the discrete object Monte Carlo paradigm for primary radiation damage and the continuum field variable approach for microstructure evolution. The coupling is bidirectional, in which the microstructure evolution in the MOOSE finite element frame- work provides the spatial scattering data set for the charged particle trans- port and receives point defect, mass transport, and heat source terms from the simulated collision cascades that contribute to the field variable evolution. The concurrent coupling scheme is implemented in the code Magpie and demonstrated by investigating patterning for a model irradiated immiscible binary alloy. The results from the coupled binary collision Monte Carlo/phase field simulations reproduce the results of analytical models for phase separation, phase mixing, and patterning, supporting the approach and indicating its utility for modeling real materials systems.
36 MATERIALS SCIENCE↗
Steady state likelihood ratio sensitivity analysis for stiff kinetic Monte Carlo simulations
Kinetic Monte Carlo simulation is an integral tool in the study of complex physical phenomena present in applications ranging from heterogeneous catalysis to biological systems to crystal growth and atmospheric sciences. Sensitivity analysis is useful for identifying important parameters and rate-determining steps, but the finite-difference application of sensitivity analysis is computationally demanding. Techniques based on the likelihood ratio method reduce the computational cost of sensitivity analysis by obtaining all gradient information in a single run. However, we show that disparity in time scales of microscopic events, which is ubiquitous in real systems, introduces drastic statistical noise into derivative estimates for parameters affecting the fast events. In this work, the steady-state likelihood ratio sensitivity analysis is extended to singularly perturbed systems by invoking partial equilibration for fast reactions, that is, by working on the fast and slow manifolds of the chemistry. Derivatives on each time scale are computed independently and combined to the desired sensitivity coefficients to considerably reduce the noise in derivative estimates for stiff systems. The approach is demonstrated in an analytically solvable linear system.
Núñez, M.↗