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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Neutronics Analysis of Cold Critical KRUSTY Experiments using MCNP and Serpent

Kilowatt Reactor Using Stirling Technology (KRUSTY) is a prototype designed as a proof of concept for NASA’s Kilo power program, which was funded in order to create a small reactor for various space applications such as providing power for a colony on Mars or the moon and eventually as a possible option for powering rockets on deep space missions. KRUSTY was tested at the National Criticality Experiments Research Center (NCERC) located at the Nevada National Security Site (NNSS) from November 2017, through March 2018. The experimental campaign was conducted in four phases: com ponent critical experiments, cold critical experiments, warm critical runs, and high temperature demonstration. The component critical and cold critical experiments were used to determine the worth of the beryllium oxide (BeO) reflector rings and the boron carbide (B4C) control rod disks under different conditions. These conditions were altered by the addition and subtraction of other components in the assembly. The component critical phase was performed at atmospheric pressure and had four solid support rods spanning the center core; whereas the cold critical phase had the center core placed in a vacuum chamber and eight sodium-filled heat pipes spanning the center core region. This summary discusses the static neutronic analysis completed on the cold critical phase of the campaign using MCNP ® and Serpent. These two codes were used to assess any potential differences or biases in the simulation results. Understanding these potential biases is a key step toward the final goal of being able to fully analyze the transient experiments performed during phases 3 and 4 of the campaign.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Spatial and Spin Symmetry Breaking in Semidefinite-Programming-Based Hartree–Fock Theory

The Hartree–Fock problem was recently recast as a semidefinite optimization over the space of rank-constrained two-body reduced-density matrices (RDMs) [ Phys. Rev. A 2014, 89, 010502(R)]. This formulation of the problem transfers the nonconvexity of the Hartree–Fock energy functional to the rank constraint on the two-body RDM. We consider an equivalent optimization over the space of positive semidefinite one-electron RDMs (1-RDMs) that retains the nonconvexity of the Hartree–Fock energy expression. The optimized 1-RDM satisfies ensemble N-representability conditions, and ensemble spin-state conditions may be imposed as well. The spin-state conditions place additional linear and nonlinear constraints on the 1-RDM. We apply this RDM-based approach to several molecular systems and explore its spatial (point group) and spin (Ŝ 2 and Ŝ 3 ) symmetry breaking properties. When imposing Ŝ 2 and Ŝ 3 symmetry but relaxing point group symmetry, the procedure often locates spatial-symmetry-broken solutions that are difficult to identify using standard algorithms. For example, the RDM-based approach yields a smooth, spatial-symmetry-broken potential energy curve for the well-known Be–H 2 insertion pathway. We also demonstrate numerically that, upon relaxation of Ŝ 2 and Ŝ 3 symmetry constraints, the RDM-based approach is equivalent to real-valued generalized Hartree–Fock theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Conditions for the Solvability of the Linear Programming Formulation for Constrained Discounted Markov Decision Processes

We consider a discrete-time constrained discounted Markov decision process (MDP) with Borel state and action spaces, compact action sets, and lower semi-continuous cost functions. We introduce a set of hypotheses related to a positive weight function which allow us to consider cost functions that might not be bounded below by a constant, and which imply the solvability of the linear programming formulation of the constrained MDP. In particular, we establish the existence of a constrained optimal stationary policy. Our results are illustrated with an application to a fishery management problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Porting Adaptive Ensemble Molecular Dynamics Workflows to the Summit Supercomputer

Molecular dynamics (MD) simulations must take very small (femtosecond) integration steps in simulation-time to avoid numerical errors. Efficient use of parallel programming models and accelerators in state-of-the art MD programs now is pushing Moore’s limit for time-per-MD step. As a result, directly simulating timescales beyond milliseconds will not be attainable directly, even at exascale. However, concepts from statistical physics can be used to combine many parallel simulations to provide information about longer timescales and to adequately sample the simulation space, while preserving details about the dynamics of the system. Implementing such an approach requires a workflow program that allows adaptable steering of task assignments based on extensive statistical analysis of intermediate results. Here we report the implementation of such an adaptable workflow program to drive simulations on the Summit IBM Power System AC922, a pre-exascale supercomputer at the Oak Ridge Leadership Computing Facility (OLCF). We compare to experiences on Titan, Summit’s predecessor, report the performance of the workflow and its components, and describe the porting process. We find that using a workflow program managed by a Mongo database can provide the fault tolerance, scalable performance, task dispatch rate, and reconfigurability required for robust and portable implementation of ensemble simulations such as are used in enhanced-sampling molecular dynamics. This type of workflow generator can also be used to provide adaptive steering of ensemble simulations for other applications in addition to MD.

Ossyra, John R.↗
DOE OSTI2020

Two Delayed Critical 15-Inch-Diameter Interacting Enriched (93.14) Uranium Metal Cylinders without Moderator and Reflector

This report documents very accurately the configuration and the materials for experiments with two unmoderated, unreflected, interacting, coaxial, highly enriched, 15-in.-diameter, uranium metal cylinders performed at the Oak Ridge Critical Experiments Facility (ORCEF) in May to Aug 1963 and described in logbook E-19 and E -20 associated with experiments in the East cell of ORCEF. Measurements were also performed in April and May of 1965 and described in logbooks E-22 and E-23 The information is sufficiently accurate that it can be used as the basis for preparation of benchmarks for International Criticality Safety Benchmark Program (ICSBEP) at Idaho National laboratory. The thickness of the cylinders was varied and the spacing between them was adjusted to achieve a delayed critical configuration. The average enrichment of the uranium metal was 94.14 wt. % 235 U. The heights of the 15-in.-diameter, equal-height cylinders varied from 1-5/8 to 3.0-inches. All interacting cylinders were assembled coaxially with their flat faces parallel and their combined masses varied between 182 and 325 kilograms of HEU metal. The data from these 12 experiments described would be acceptable for use as criticality safety benchmark experiments for the ICSBEP and EURATOM’s Nuclear Energy Agency nuclear criticality safety benchmark program, once the uncertainty analysis is completed. Based on previous ICSBEP benchmarks with this enriched uranium metal at ORCEF, it is expected that the uncertainties in k eff could be as low as ± 0.0002.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Three Delayed Critical 15-Inch-Diameter Interacting Enriched (93.14) Uranium Metal Cylinders Without Moderator and Reflector

This report documents very accurately the configuration and the materials for experiments with three unmoderated, unreflected, interacting, coaxial, highly enriched, 15-in.-diameter, uranium metal cylinders performed at the Oak Ridge Critical Experiments Facility (ORCEF) in August and September 1963 and described in logbook E 20 associated with experiments in the East cell of ORCEF. The information is sufficiently accurate that it can be used as the basis for preparation of benchmarks for International Criticality Safety Benchmark Program (ICSBEP) at Idaho National laboratory. The thickness of the cylinders was varied and the spacing between them was adjusted to achieve a delayed critical configuration. The average enrichment of the uranium metal was 94.14 wt. % 235U. The heights of the 15-in.-diameter, equal-height cylinders varied from 1-1/8to 2.00 inches. All interacting cylinders were assembled coaxially with their flat faces parallel and their combined masses varied between 182 and 325 kilograms of HEU metal. The data from these six experiments described are judged to be acceptable for use as criticality safety benchmark experiments for the ICSBEP and EURATOM’s Nuclear Energy Agency nuclear criticality safety benchmark program, once the uncertainty analysis is completed. Based on previous ICSBEP benchmarks with this enriched uranium metal at ORCEF, it is expected that the uncertainties in measured keff could be as low as ± 0.0002.

36 MATERIALS SCIENCE↗
DOE OSTI2022

DFSynthesizer: Dataflow-based Synthesis of Spiking Neural Networks to Neuromorphic Hardware

Spiking Neural Networks (SNNs) are an emerging computation model that uses event-driven activation and bio-inspired learning algorithms. SNN-based machine learning programs are typically executed on tile-based neuromorphic hardware platforms, where each tile consists of a computation unit called a crossbar, which maps neurons and synapses of the program. However, synthesizing such programs on an off-the-shelf neuromorphic hardware is challenging. This is because of the inherent resource and latency limitations of the hardware, which impact both model performance, e.g., accuracy, and hardware performance, e.g., throughput. We propose DFSynthesizer, an end-to-end framework for synthesizing SNN-based machine learning programs to neuromorphic hardware. The proposed framework works in four steps. First, it analyzes a machine learning program and generates SNN workload using representative data. Second, it partitions the SNN workload and generates clusters that fit on crossbars of the target neuromorphic hardware. Third, it exploits the rich semantics of the Synchronous Dataflow Graph (SDFG) to represent a clustered SNN program, allowing for performance analysis in terms of key hardware constraints such as number of crossbars, dimension of each crossbar, buffer space on tiles, and tile communication bandwidth. Finally, it uses a novel scheduling algorithm to execute clusters on crossbars of the hardware, guaranteeing hardware performance. We evaluate DFSynthesizer with 10 commonly used machine learning programs. Our results demonstrate that DFSynthesizer provides a much tighter performance guarantee compared to current mapping approaches.

Computer Science↗
DOE OSTI2021

Deterministic symbolic regression with derivative information: General methodology and application to equations of state

Symbolic regression methods simultaneously determine the model functional form and the regression parameter values by generating expression trees. Symbolic regression can capture the complexity of real–world phenomena but the use of deterministic optimization for symbolic regression has been limited due to the complexity of the search space of existing formulations. Herein we present a novel deterministic mixed–integer nonlinear programming formulation for symbolic regression that incorporates derivative constraints through auxiliary expression trees. By applying the chain rule to mathematical operations, binary expression trees are capable of representing the calculation of first and second derivatives. We apply this formulation to illustrative examples using derivative information to show increased model discrimination capability. In addition, we perform a case study of a thermodynamic equation of state to gain insight on valid functional forms with thermodynamics–based constraints on the first and second derivatives.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Adrastea: An Efficient FPGA Design Environment for Heterogeneous Scientific Computing and Machine Learning

We present Adrastea, an efficient FPGA design environment for developing scientific machine learning applications. FPGA development is challenging, from deployment, proper toolchain setup, programming methods, interfacing FPGA kernels, and more importantly, the need to explore design space choices to get the best performance and area usage from the FPGA kernel design. Adrastea provides an automated and scalable design flow to parameterize, implement, and optimize complex FPGA kernels and associated interfaces. We show how virtualization of the development environment via virtual machines is leveraged to simplify the setup of the FPGA toolchain while deploying the FPGA boards and while scaling up the automated design space exploration to leverage multiple machines concurrently. Adrastea provides an automated build and test environment of FPGA kernels. By exposing design space hyper-parameters, Adrastea can automatically search the design space in parallel to optimize the FPGA design for a given metric, usually performance or area. Adrastea simplifies the task of interfacing with the FPGA kernels with a simplified interface API. To demonstrate the capabilities of Adrastea, we implement a complex random forest machine learning kernel with 10,000 input features while achieving extremely low computing latency without loss of prediction accuracy, which is required by a scientific edge application at SNS. We also demonstrate Adrastea using an FFT kernel and show that for both applications Adrastea is able to systematically and efficiently evaluate different design options, which reduced the time and effort required to develop the kernel from months of manual work to days of automatic builds.

Young, Aaron↗
DOE OSTI2020

On the ATLAS top mass measurements and the potential for stealth stop contamination

The discovery of the stop — the Supersymmetric partner of the top quark — is a key goal of the physics program enabled by the Large Hadron Collider. Although much of the accessible parameter space has already been probed, all current searches assume the top mass is known. This is relevant for the “stealth stop” regime, which is characterized by decay kinematics that force the final state top quark off its mass shell; such decays would contaminate the top mass measurements. We investigate the resulting bias imparted to the template method based ATLAS approach. A careful recasting of these results shows that effect can be as large as 2.0 GeV, comparable to the current quoted uncertainty on the top mass. Thus, a robust exploration of the stealth stop splinter requires the simultaneous consideration of the impact on the top mass. Additionally, we explore the robustness of the template technique, and point out a simple strategy for improving the methodology implemented for the semi-leptonic channel.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Structure determination of oxamic acid from laboratory powder X-Ray diffraction data and energy minimization by DFT-D

The structure determination from laboratory X-ray powder diffraction data of oxamic acid, a derivative of the biologically active oxalic acid and the simplest organic acid containing an amide group, is presented in this contribution. An energy minimization analysis by DFT-D was carried out. The structure was determined with the program TALP and refined by the Rietveld method with GSAS-II in space group Cc (No. 9). The final unit-cell parameters are a = 9.4989 (6), b = 5.43796 (9), c = 6.8637 (9) Å, β = 107.152 (5)°, V = 338.772 (10) Å3, Z = 4. The refinement converged to the figures of merit: Re = 0.01674, Rp = 0.03270, Rwp = 0.05652 and GoF = 3.378 with a good fit between the calculated pattern of the structural model and the experimental pattern. The DFT-D calculations show an excellent reproduction of the experimental structure, validating the correctness of the structure. Furthermore, the non-centrosymmetric nature of the structure was confirmed by SHG measurements. In the crystal structure, the molecules are close to planar and form a complex 2D hydrogen-bonding pattern based on the cyclic amide-acid heterosynthon.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Room temperature neutron diffraction and magnetic studies of multiferroic Pb{sub 0.9}Bi{sub 0.1}Fe{sub 0.55}Nb{sub 0.45}O{sub 3} solid solution

The Pb{sub 0.9}Bi{sub 0.1}Fe{sub 0.55}Nb{sub 0.45}O{sub 3} (PBFNO) solid solution was synthesized by single step solid state reaction method and the optimized parameters are 700°C for 2hr (calcination) and 800°C for 3hr (sintering). The formation of desired material was confirmed using X-Ray Diffraction (XRD) and Neutron Diffraction (ND) studies. The structural and magnetic properties of the sintered pellets were investigated at room temperature (RT) through XRD, ND and Magnetic (M-H) studies. The structural analysis was carried out by Rietveld refinement through the Full Prof program. Rietveld refined XRD and ND patterns confirms the monoclinic structure with Cm space group and obtained cell parameters from the ND data are a = 5.651(2) Å, b = 5.658(2) Å, c = 4.005(1) Å and α = 90°, β = 89.98(1)°, γ = 90°. RT M-H curve studies have been carried out. It shows the clear opening of hysteresis (M–H) loop, is evidenced as the existence of weak ferromagnetism at RT. The M-H data shows existence weak ferromagnetism embedded in an antiferromagnetic matrix structure. The dielectric constant with frequency shows the formation of barrier layers at the grain and grain boundary interfaces gives rise to interfacial space charge polarization.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Portable Radiation Package (PRP) Instrument Handbook

The Portable Radiation Package (PRP) was developed to provide basic radiation information in locations such as ships at sea where proper exposure is remote and difficult, the platform is in motion, and azimuth alignment is not fixed. Development of the PRP began at Brookhaven National Laboratory (BNL) in the mid-1990s and versions of it were deployed on ships in the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s Nauru-99 project. The PRP was deployed on ships in support of the National Aeronautics and Space Administration (NASA) Sensor Intercomparison for Marine Biological and Interdisciplinary Ocean Studies (SIMBIOS) program. Over the years the measurements have remained the same while the post-processing data analysis, especially for the FRSR, has evolved. This document describes the next-generation Portable Radiation Package (PRP2) that was developed for the DOE ARM Facility, under contract no. 9F-31462 from Argonne National Laboratory (ANL). The PRP2 has the same scientific principles that were well validated in prior studies, but has upgraded electronic hardware. The PRP2 approach is completely modular, both in hardware and software. Each sensor input is treated as a separate serial stream into the data collection computer. In this way the operator has complete access to each component of the system for purposes of error checking, calibration, and maintenance. The resulting system is more reliable, easier to install in complex situations, and more amenable to upgrade.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

SST-GPU: An Execution -Driven CUDA Kernel Scheduler and Streaming-Multiprocessor Compute Model

Programmable accelerators have become commonplace in modern computing systems. Advances in programming models and the availability of massive amounts of data have created a space for massively parallel acceleration where the context for thousands of concurrent threads are resident on-chip. These threads are grouped and interleaved on a cycle-by-cycle basis among several massively parallel computing cores. The design of future supercomputers relies on an ability to model the performance of these massively parallel cores at scale. To address the need for a scalable, decentralized GPU model that can model large GPUs, chiplet-based GPUs and multi-node GPUs, this report details the first steps in integrating the open-source, execution driven GPGPU-Sim into the SST framework. The first stage of this project, creates two elements: a kernel scheduler SST element accepts work from SST CPU models and schedules it to an SM-collection element that performs cycle-by-cycle timing using SSTs Mem Hierarchy to model a flexible memory system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Balar: A SST GPU Component for Performance Modeling and Profiling

Programmable accelerators have become commonplace in modern computing systems. Advances in programming models and the availability of massive amounts of data have created a space for massively parallel accelerators capable of maintaining context for thousands of concurrent threads resident on-chip. These threads are grouped and interleaved on a cycle-by-cycle basis among several massively parallel computing cores. One path for the design of future supercomputers relies on an ability to model the performance of these massively parallel cores at scale. The SST framework has been proven to scale up to run simulations containing tens of thousands of nodes. A previous report described the initial integration of the open-source, execution-driven GPU simulator, GPGPU-Sim, into the SST framework. This report discusses the results of the integration and how to use the new GPU component in SST. It also provides examples of what it can be used to analyze and a correlation study showing how closely the execution matches that of a Nvidia V100 GPU when running kernels and mini-apps.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

SST-GPU: A Scalable SST GPU Component for Performance Modeling and Profiling

Programmable accelerators have become commonplace in modern computing systems. Advances in programming models and the availability of unprecedented amounts of data have created a space for massively parallel accelerators capable of maintaining context for thousands of concurrent threads resident on-chip. These threads are grouped and interleaved on a cycle-by-cycle basis among several massively parallel computing cores. One path for the design of future supercomputers relies on an ability to model the performance of these massively parallel cores at scale. The SST framework has been proven to scale up to run simulations containing tens of thousands of nodes. A previous report described the initial integration of the open-source, execution-driven GPU simulator, GPGPU-Sim, into the SST framework. This report discusses the results of the integration and how to use the new GPU component in SST. It also provides examples of what it can be used to analyze and a correlation study showing how closely the execution matches that of a Nvidia V100 GPU when running kernels and mini-apps.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A Case Study of Luminaire-Level Lighting Control: Lighting the Northwest Energy Efficiency Alliance (NEEA) Office in Portland, OR

What happens when advanced lighting and control systems are installed in the real world? Are the advantages and energy savings realized? By observing the design, installation, commissioning, and ongoing use of connected lighting systems in real-world settings, it is possible to identify the strengths, challenges, and points of human-technology interaction that may be new or unfamiliar to those responsible for implementing or maintaining the lighting system. Ultimately, understanding and experiencing each stakeholder’s interaction with the technology can allow the research team to synthesize feedback for manufacturers, improve industry understanding of the technology, and increase adoption. The Northwest Energy Efficiency Alliance (NEEA) office in Portland, OR, is a single-floor installation that puts tunable-white, interoperability, and luminaire-level advanced control capabilities to the test. Compared to simpler, “out-of-the-box” systems that minimize field-adjustable settings, the system utilized in this space allowed for granular field adjustments which required the system specifier, client, and programming agent to make additional decisions regarding system operation while the system was being programmed. This report communicates the observational findings from the installation, programming, and ongoing operation of an advanced office LLLC system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Summary of Massachusetts Clean Energy Center's Workforce Needs Assessment for the City of Lawrence

In July 2023, the Massachusetts Clean Energy Center (MassCEC) published an employment report titled “Powering the Future: A Massachusetts Clean Energy Workforce Needs Assessment.” This report was intended to support the State in meeting its 2030 decarbonization goals by identifying both existing workforce and training resources as well as gaps and barriers that need to be addressed in order to scale the State’s workforce to meet future demand. The following is a summary of the content that is relevant to Lawrence, MA. This was completed as part of the US Department of Energy’s Communities LEAP (Local Energy Action Program) Pilot supporting the Lawrence Stakeholders Coalition (LSC) led by Browning the Green Space in partnership with Groundwork Lawrence, All In Energy, and the City of Lawrence.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗