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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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At least 1,693 records · Page 94

DEVELOPING A TRAFFIC SIGNAL ECO-COOPERATIVE ADAPTIVE CRUISE CONTROL SYSTEM FOR BATTERY ELECTRIC VEHICLES

This study developed an eco-driving strategy for battery electric vehicles (BEVs) in the vicinity of signalized intersections, known as BEV Eco-Cooperative Adaptive Cruise Control at Intersections (Eco-CACC-I). The system computes a real-time, energy-optimized vehicle trajectory using a BEV vehicle dynamics and energy consumption model. In the proposed approach, the relationship between vehicle speed, acceleration level, and tractive/resistance forces on the vehicle follows the vehicle dynamics model. The Virginia Tech Comprehensive Power-based Electric Vehicle Energy Consumption Model (VT-CPEM) is used to compute the instantaneous battery energy consumption, with the consideration of battery energy regeneration during braking. The Eco-CACC-I energy-optimum trajectory computation is formulated as an optimization problem with constraints. Considering that the optimization solution needs to be computed at a rapid frequency (e.g., 10 Hz) for real-time applications, an A-star algorithm was used here to expedite the computational speed. Lastly, the proposed BEV Eco-CACC-I system was tested in simulation by considering the impacts of various road grades, speed limits, and signal timings. Simulations for an Internal Combustion Engine Vehicles (ICEVs) was conducted to compare with the BEV test results. The results of the comparison indicate that the energy-optimum solution for BEVs is different from that for ICEVs and thus demonstrating the need for vehicle-tailored optimum trajectories.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Roadmap for warm dense matter physics

This roadmap presents the state-of-the-art, current challenges and near future developments anticipated in the thriving field of warm dense matter (WDM) physics. Originating from strongly coupled plasma physics, high pressure physics and high energy density science, the WDM physics community has recently taken a giant leap forward. This is due to spectacular developments in laser technology, diagnostic capabilities, and computer simulation techniques. Only in the last decade has it become possible to perform accurate enough simulations & experiments to truly verify theoretical results as well as to reliably design experiments based on predictions. Consequently, this roadmap discusses recent developments of and contemporary challenges for theoretical methods and experimental techniques needed to describe, create and diagnose WDM. A large part of this roadmap is dedicated to specific WDM systems and applications in astrophysics, inertial confinement fusion and novel material synthesis.

dense astrophysical objects↗

A combined ensemble-volume average homogenization method for lattice structures with defects under dynamic and static loading

In the study of lattices structures, both experiments and numerical simulations are often conducted with small samples. Using combined ensemble and volume averaging, this work introduces a method to extract a macroscopic constitutive response of a lattice material from numerical simulations performed in periodic domains. The domain size needed to obtain statistically accurate results is investigated. Similar to molecular dynamics, the concept of the virial stress is introduced after homogenized equations are derived using the ensemble averaging method. Under static conditions, the virial stress is shown to agree with the volume averaged solid stress. Using the homogenization method, constitutive relations for this stress can be obtained from systems with uniform strains. Application of such obtained constitutive relations to more general cases results in an error proportional to the square of the ratio between the lattice length scale and the macroscopic length scale. Taking advantage of this property, numerical simulations are performed in systems with a uniform gradient of the average velocity. The volume average method is then used to accelerate convergence when studying lattices with defects. To avoid the artificial numerical time scale from the size of a representative volume element divided by the wave speed, a numerical scheme is developed to enforce a spatially uniform velocity gradient within the computational domain while allowing fluctuations of the velocity or displacement to develop naturally. To account for probability distribution of lattice defects, the stress is calculated as the ensemble-volume averaged value. For dynamic systems, energy dissipation properties are also studied.

36 MATERIALS SCIENCE↗

A high-order multiscale finite-element method for time-domain acoustic-wave modeling

Accurate and efficient wave equation modeling is vital for many applications in such as acoustics, electromagnetics, and seismology. However, solving the wave equation in large-scale and highly heterogeneous models is usually computationally expensive because the computational cost is directly proportional to the number of grids in the model. We develop a novel high-order multiscale finite-element method to reduce the computational cost of time-domain acoustic-wave equation numerical modeling by solving the wave equation on a coarse mesh based on the multiscale finite-element theory. In contrast to existing multiscale finite-element methods that use only first-order multiscale basis functions, our new method constructs high-order multiscale basis functions from local elliptic problems which are closely related to the Gauss–Lobatto–Legendre quadrature points in a coarse element. Essentially, these basis functions are not only determined by the order of Legendre polynomials, but also by local medium properties, and therefore can effectively convey the fine-scale information to the coarse-scale solution with high-order accuracy. Numerical tests show that our method can significantly reduce the computation time while maintain high accuracy for wave equation modeling in highly heterogeneous media by solving the corresponding discrete system only on the coarse mesh with the new high-order multiscale basis functions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Application-specific I/O Optimizations on Petascale Supercomputers

Data-intensive science frontiers and challenges are emerg ing as computer technology has evolved substantially. Large-scale simu lations demand significant I/O workload, and as a result the I/O performance often becomes a bottleneck preventing high performance in scientific applications. In this paper we introduce a variety of I/O optimization techniques developed and imple mented when scaling a seismic application to petascale. These techniques include file system striping, data aggreg ation, reader/writer limit ing and less interleaving of data, collective MPI-IO, and data staging. The optimizations result in nearly perfect scalability of the target applicat ion on some of the most advanced petascale systems. The techniques introduced in this paper are applicab le to other scientific applications facing similar petascale I/O challenges.

97 MATHEMATICS AND COMPUTING↗

Transport properties of (Ca{sub 1−x}Sr{sub x})Mn{sub 0.95}Sb{sub 0.05}O{sub 3} perovskites

The transport properties as a function of composition and temperature of (Ca{sub 1−x}Srx)Mn{sub 0.95}Sb0.{sub 05}O{sub 3} perovskite compounds have been investigated for the first time using extended rigid ion model (ERIM). (Ca{sub 1−x}Srx)Mn{sub 0.95}Sb0.{sub 05}O{sub 3} (x = 0.0, 0.10, 0.15 and 0.17) exhibit a single phase with an orthorhombic perovskite structure (Pnma). Furthermore, to understand better the thermodynamical properties of the present system, ERIM is developed and applied to study the specific heat for these compounds over a wide range of temperature. The trends of variation of computed thermodynamical and transport properties have shown remarkable good agreement with corresponding experimental data.

36 MATERIALS SCIENCE↗

Transmission in situ and operando high temperature X-ray powder diffraction in variable gaseous environments

In this paper, we describe a device for time-resolved synchrotron-based in situ and operando X-ray powder diffraction measurements at elevated temperatures under controllable gaseous environments. The respective gaseous sample environment is realized via a gas-tight capillary-in-capillary design, where the gas flow is achieved through an open-end 0.5 mm capillary located inside a 0.7 mm capillary filled with a sample powder. Thermal mass flow controllers provide appropriate gas flows and computer-controlled on-the-fly gas mixing capabilities. The capillary system is centered inside an infrared heated, proportional integral differential-controlled capillary furnace allowing access to temperatures up to 1000 °C.

36 MATERIALS SCIENCE↗

Periodic training of creeping solids

Significance It is well appreciated that many disordered materials deform their shape irreversibly (plastically) under an external load (e.g., memory foam). Here, we show that this plasticity can be exploited to train materials to develop novel elastic responses by straining them periodically. By applying different periodic strains to a common viscoelastic material, we are able to design a number of different responses. These include a maximally negative Poisson’s ratio, bistable behavior, and nonlocal bond-specific responses. In contrast to computer-aided design, we rely on plasticity to self-organize the system in response to local stresses. This approach shows promise to achieve an unprecedented control over behavior at large strains well beyond the linear-response regime.

36 MATERIALS SCIENCE↗

On-line vs. Off-line Coupling of Meteorological and Transport & Dispersion Models: Background, Advantages, Limitations, and Issues

This report discusses the advantages and limitations of on-line coupling of meteorological (Met) or computational fluid dynamics (CFD) codes with transport and dispersion (T&D) models for the simulation of chemical, biological, radiological, and nuclear (CBRN) plume dispersion at the meso- and urban-scales as compared to the more standard off-line coupling approach. In an off-line modeling system the Met/CFD and T&D codes are separate executables, the Met/CFD code is first run to completion, output files are written to hard disk, and then the T&D model reads in the Met/CFD files and is run to completion. An on-line modeling system is defined as having the T&D and Met/CFD codes running concurrently, sharing input and output between the models via computer random access memory (RAM) and in many cases the Met/CFD and T&D models are embedded in the same code.

54 ENVIRONMENTAL SCIENCES↗

Final Report Collaborative Project. Improving the Representation of Coastal and Estuarine Processes in Earth System Models

This project aimed to improve long term global climate simulations by resolving and enhancing the representation of the processes involved in the cycling of freshwater through estuaries and coastal regions. This was a collaborative multi-institution project consisting of physical oceanographers, climate model developers, and computational scientists. It specifically targeted the DOE objectives of advancing simulation and predictive capability of climate models through improvements in resolution and physical process representation. The main computational objectives were: 1. To develop computationally efficient, but physically based, parameterizations of estuary and continental shelf mixing processes for use in an Earth System Model (CESM). 2. To develop a two-way nested regional modeling framework in order to dynamically downscale the climate response of particular coastal ocean regions and to upscale the impact of the regional coastal processes to the global climate in an Earth System Model (CESM). 3. To develop computational infrastructure to enhance the efficiency of data transfer between specific sources and destinations, i.e., a point-to-point communication capability, (used in objective 1) within POP, the ocean component of CESM.

54 ENVIRONMENTAL SCIENCES↗

Technical Characterization and Benefit Evaluation of 5G-Enabled Grid Data Transport and Applications

This report summarizes the Year 1 work of Pacific Northwest National Laboratory’s (PNNL’s) 5G Fabricated Resource and Asset Management Encompassment for energy infrastructure (Energy FRAME) project funded by the Department of Energy Office of Science’s Advanced Scientific Computing Research Program. 5G is a breakthrough technology that enables a fully mobile and connected society, and a 5G-enabled digital continuum will be one of the critical foundations for a clean energy economy and grid modernization. In collaboration with PNNL’s Advanced Wireless Communication team and Center for Advanced Technology Evaluation team, the project team has been evaluating the system performance of 5G testbeds in the PNNL 5G Innovation Studio, and has formulated a co-simulation test case of power system transmission, distribution, and communication (T&D&C) networks considering 5G technology and high penetration of distributed energy resources. The methodology developed in the 5G Energy FRAME project can be customized to fit different future grid scenarios to evaluate multiple (dynamic) configurations (computing, sensing, communication, environment) for different stakeholders. In summary, our main technical highlights in project Year 1 are as follows: 1) Technical characterization of 5G standalone architectures, 2) Formulation of co-simulation test case of T&D&C networks embedded with 5G, 3) Initial benefit evaluation of 5G communication platform for grid use cases, and 4) Additional extended discussions on edge computing, artificial intelligence and machine learning, and high-performance computing and cloud computing adoptions. In addition, a collection of system performance data is shared through the publicly available weblink, https://www.pnnl.gov/projects/5g-energy-frame/publications

24 POWER TRANSMISSION AND DISTRIBUTION↗

An ICME Modeling Framework for Metal Matrix Composites Focusing on Ultrahigh Temperature Matrix Material and Tungsten Carbide Reinforcement Particulate (Final CRADA Report)

Ultra High Temperature Metal Matrix Composites (UHT-MMCs) are of interest to the due to their potential defense and aerospace applications. These materials consist of a metal matrix reinforced with a stiff ceramic or cermet. Based on a preliminary literature survey, this project will focused on a pure titanium (Ti) matrix reinforced with tungsten carbide-cobalt (WC-Co). UHT-MMC technology is still at a nascent stage of development and requires extensive experimental work to optimize the structure and resulting material properties of a particular UHT-MMC material system. An accurate and complete high-performance computing (HPC) model of the Ti/WC-Co material system could greatly accelerate the development and deployment Ti/WC-Co materials by connecting processing parameters to material properties. This type of model could then be used in an integrated computational materials engineering approach to optimize the material structure to achieve a targeted level of performance.

36 MATERIALS SCIENCE↗

Feature-based Data Assimilation in Geophysics

Many applications in science require that computational models and data be combined. In a Bayesian framework, this is usually done by denying likelihoods based on the mismatch of model outputs and data. However, matching model outputs and data in this way can be unnecessary or impossible. Using large amounts of steady state data is unnecessary because these data are redundant. It is impossible to assimilate data of complex systems into low-dimensional models, or to assimilate data, collected over long time scales, into chaotic models. One can address these issues by denying likelihoods based on suitable low-dimensional \features" of the data, rather than by the mismatch of model output and \raw" data. Our goal is to contribute to a more fundamental understanding of such a feature-based approach to data assimilation. We present noise models based on perturbed observations to de ne feature-based likelihood functions that lead to computationally efficient solutions. We also explain how a feature-based approach enables us to effectively assimilate selected aspects of data into models, and how this can be interpreted by a reduction in effective dimension. Numerical implementation of these ideas are illustrated in four examples.

97 MATHEMATICS AND COMPUTING↗

Free Energy Landscapes of Membrane Transport Proteins

Molecular dynamics (MD) is now a widespread tool for investigating biochemical and biomolecular systems, its prevalence, in no small part, being due to significant advances in computational hardware over the last few decades. Even non-experts can now routinely use MD for protein and nucleic acid structure refinement, studying conformational switching events, and investigating solvation effects due to ligand/drug binding. Nonetheless, the vast majority of simulations being done today utilize only rudimentary algorithmic approaches – so-called “brute force” MD – which only permit access to a small fraction of what the approach has to offer. This is largely because the core algorithm is simple, while advanced techniques can require everything from more sophisticated models and data structures to complicated on-the-fly analysis. A core goal of this early science project is to bring one such advanced MD approach into the broader arena of high-performance computing.In particular, the powerful method of constant-pH MD has long been a relegated to experienced users and specialized model systems. In this work we develop and implement a constant-pH MD algorithm in the NAMD simulation engine making it suitable for deployment on large-scale, next-generation supercomputers as well as ambitious, cutting-edge biological applications. We report,for the first time, constant-pH simulations of a membrane transport protein and use the results to analyze its free energy landscape for ion-selectivity.

59 BASIC BIOLOGICAL SCIENCES↗

A kinetic-based regularization method for data science applications

We propose a physics-based regularization technique for function learning, inspired by statistical mechanics. By drawing an analogy between optimizing the parameters of an interpolator and minimizing the energy of a system, we introduce corrections that impose constraints on the lower-order moments of the data distribution. This minimizes the discrepancy between the discrete and continuum representations of the data, in turn allowing to access more favorable energy landscapes, thus improving the accuracy of the interpolator. Our approach improves performance in both interpolation and regression tasks, even in high-dimensional spaces. Unlike traditional methods, it does not require empirical parameter tuning, making it particularly effective for handling noisy data. We also show that thanks to its local nature, the method offers computational and memory efficiency advantages over Radial Basis Function interpolators, especially for large datasets.

97 MATHEMATICS AND COMPUTING↗

Low Distortion Lens Design for Large Scintillators

Tomographic imaging of large objects from an x-ray source require a 240 mm square scintillator that is imaged onto a 90 mm square charge-coupled device (CCD) with <0.01% distortion. A large pellicle and internal folding mirror keep the optical elements and the CCD camera out of the x-ray beam path to minimize shielding requirements. Better imaging is needed for 2-D digital radiography and computer tomography (3-D) on the Los Alamos National Laboratory’s Microtron x-ray–generating source, a bremsstrahlung source with endpoint energies of 6, 10, 15, and 20 MeV. Large objects are placed into the x-ray beam and rotated between radiographs. X-rays are deposited into scintillators that are viewed with digital cameras. Better light gathering is needed because the scintillators emit low levels of light. Earlier imaging techniques used film in contact with the scintillator. Our design goal is to match the resolution of the digital camera system to that of the film. 3-D tomography requires extremely low distortion of the collected images.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NARAC Dispersion Model Product Integration With RadResponder

Work on enhanced cooperation and interoperability of Nuclear Incident Response Teams (NIRT) is a joint effort between DHS/FEMA, DOE/NNSA and EPA. One such effort was the integration between the RadResponder Network, a resource sponsored by FEMA for the management of radiological data during an emergency, and the National Atmospheric Advisory Center (NARAC), a DOE/NNSA modeling resource whose predictions are used to aid radiological emergency preparedness and response. Working together under a FEMA-sponsored project these two radiological response assets developed a capability to read and display plume model prediction results from the NARAC computer system in the RadResponder software tool. As a result of this effort, RadResponder users have been provided with NARAC modeling predictions of contamination areas, radiological dose levels, and protective action areas (e.g., areas warranting worker protection or sheltering/evacuation) to help guide protective action decisions and field monitoring surveys, and gain key situation awareness following a radiological/nuclear accident or incident (e.g., nuclear power plant accident, radiological dispersal device incident, or improvised nuclear detonation incident). This document describes the details of this integration effort.

54 ENVIRONMENTAL SCIENCES↗

Preserving Command Line Workflow for a Package Management System using ASCII DAG Visualization

Package managers provide ease of access to applications by removing the time-consuming and sometimes completely prohibitive barrier of successfully building, installing, and maintaining the software for a system. A package dependency contains dependencies between all packages required to build and run the target software. Package management system developers, package maintainers, and users may consult the dependency graph when a simple listing is insufficient for their analyses. However, users working in a remote command line environment must disrupt their workflow to visualize dependency graphs in graphical programs, possibly needing to move files between devices or incur forwarding lag. Such is the case for users of Spack, an open source package management system originally developed to ease the complex builds required by supercomputing environments. To preserve the command line workflow of Spack, we develop an interactive ASCII visualization for its dependency graphs. Through interviews with Spack maintainers, we identify user goals and corresponding visual tasks for dependency graphs. We evaluate the use of our visualization through a command line-centered study, comparing it to the system's two existing approaches. We observe that despite the limitations of the ASCII representation, our visualization is preferred by participants when approached from a command line interface workflow.

97 MATHEMATICS AND COMPUTING↗