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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Shearography for Non-Destructive Evaluation with Applications to BAT Mask Tile Adhesive Bonding and Specular Surface Honeycomb Panels

In this report we examine the applicability of shearography techniques for nondestructive inspection and evaluation in two unique application areas. In the first application, shearography is used to evaluate the quality of adhesive bonds holding lead tiles to the BAT gamma ray mask for the NASA Swift program. By exciting the mask with a vibration, the more poorly bonded tiles can be distinguished by their greater displacement response, which is readily identifiable in the shearography image. A quantitative analysis is presented that compares the shearography results with a destructive pull test measuring the force at bond failure. Generally speaking, the results show good agreement. Further investigation would be useful to optimize certain test parameters such as vibration frequency and amplitude. The second application is to evaluate the bonding between the skin and core of a honeycomb structure with a specular (mirror-like) surface. In standard shearography techniques, the object under test must have a diffuse surface to generate the speckle patterns in laser light, which are then sheared. A novel configuration using the specular surface as a mirror to image speckles from a diffuser is presented, opening up the use of shearography to a new class of objects that could not have been examined with the traditional approach. This new technique readily identifies large scale bond failures in the panel, demonstrating the validity of this approach. For the particular panel examined here, some scaling issues should be examined further to resolve the measurement scale down to the very small size of the core cells. In addition, further development should be undertaken to determine the general applicability of the new approach and to establish a firm quantitative foundation.

Lysak, Daniel B.↗
NASA NTRS2010

High-Performance CCSDS Encapsulation Service Implementation in FPGA

The Consultative Committee for Space Data Systems (CCSDS) Encapsulation Service is a convergence layer between lower-layer space data link framing protocols, such as CCSDS Advanced Orbiting System (AOS), and higher-layer networking protocols, such as CFDP (CCSDS File Delivery Protocol) and Internet Protocol Extension (IPE). CCSDS Encapsulation Service is considered part of the data link layer. The CCSDS AOS implementation is described in the preceding article. Recent advancement in RF modem technology has allowed multi-megabit transmission over space links. With this increase in data rate, the CCSDS Encapsulation Service needs to be optimized to both reduce energy consumption and operate at a high rate. CCSDS Encapsulation Service has been implemented as an intellectual property core so that the aforementioned problems are solved by way of operating the CCSDS Encapsulation Service inside an FPGA. The CCSDS En capsula tion Service in FPGA implementation consists of both packetizing and de-packetizing features

Clare, Loren P.↗
DOE OSTI2017

The HEPCloud Facility: elastic computing for High Energy Physics – The NOvA Use Case

The need for computing in the HEP community follows cycles of peaks and valleys mainly driven by conference dates, accelerator shutdown, holiday schedules, and other factors. Because of this, the classical method of provisioning these resources at providing facilities has drawbacks such as potential overprovisioning. As the appetite for computing increases, however, so does the need to maximize cost efficiency by developing a model for dynamically provisioning resources only when needed. To address this issue, the HEPCloud project was launched by the Fermilab Scientific Computing Division in June 2015. Its goal is to develop a facility that provides a common interface to a variety of resources, including local clusters, grids, high performance computers, and community and commercial Clouds. Initially targeted experiments include CMS and NOvA, as well as other Fermilab stakeholders. In its first phase, the project has demonstrated the use of the “elastic” provisioning model offered by commercial clouds, such as Amazon Web Services. In this model, resources are rented and provisioned automatically over the Internet upon request. In January 2016, the project demonstrated the ability to increase the total amount of global CMS resources by 58,000 cores from 150,000 cores - a 25 percent increase - in preparation for the Recontres de Moriond. In March 2016, the NOvA experiment has also demonstrated resource burst capabilities with an additional 7,300 cores, achieving a scale almost four times as large as the local allocated resources and utilizing the local AWS s3 storage to optimize data handling operations and costs. NOvA was using the same familiar services used for local computations, such as data handling and job submission, in preparation for the Neutrino 2016 conference. In both cases, the cost was contained by the use of the Amazon Spot Instance Market and the Decision Engine, a HEPCloud component that aims at minimizing cost and job interruption. This paper describes the Fermilab HEPCloud Facility and the challenges overcome for the CMS and NOvA communities.

Fuess, S.↗
DOE OSTI2023

Learning to Branch with Interpretable Machine Learning Models

Machine learning is being increasingly used in improving decisions made within branch-and-bound algorithms for solving mixed-integer programs (MIPs). Branching is a key component in branch-and-bound algorithms, this work presents IDAES-core project update on building simple and interpretable machine learning models for branching and improving decision-making tools applied for the optimization of advanced energy systems.

Bayramoglu, Selin↗
DOE OSTI2020

Mixed-precision iterative refinement using tensor cores on GPUs to accelerate solution of linear systems

Double-precision floating-point arithmetic (FP64) has been the de facto standard for engineering and scientific simulations for several decades. Problem complexity and the sheer volume of data coming from various instruments and sensors motivate researchers to mix and match various approaches to optimize compute resources, including different levels of floating-point precision. In recent years, machine learning has motivated hardware support for half-precision floating-point arithmetic. A primary challenge in high-performance computing is to leverage reduced-precision and mixed-precision hardware. We show how the FP16/FP32 Tensor Cores on NVIDIA GPUs can be exploited to accelerate the solution of linear systems of equations Ax = b without sacrificing numerical stability. The techniques we employ include multiprecision LU factorization, the preconditioned generalized minimal residual algorithm (GMRES), and scaling and auto-adaptive rounding to avoid overflow. We also show how to efficiently handle systems with multiple right-hand sides. On the NVIDIA Quadro GV100 (Volta) GPU, we achieve a 4×-5× performance increase and 5× better energy efficiency versus the standard FP64 implementation while maintaining an FP64 level of numerical stability.

GMRES↗
DOE OSTI2017

Optimized pulses for Raman excitation through the continuum: Verification using the multiconfigurational time-dependent Hartree-Fock method

Here, we have verified a mechanism for Raman excitation of atoms through continuum levels previously obtained by quantum optimal control using the multiconfigurational time-dependent Hartree-Fock (MCTDHF) method. For the optimal control, which requires running multiple propagations to determine the optimal pulse sequence, we used the computationally inexpensive time-dependent configuration interaction singles (TDCIS) method. TDCIS captures all of the necessary correlation of the desired processes but assumes that ionization pathways reached via double excitations are not present. MCTDHF includes these pathways and all multiparticle correlations in a set of time-dependent orbitals. The mechanism that was determined to be optimal in the Raman excitation of the Ne 1s 2 2s 2 2p 5 3p 1 valence state via the metastable 1s 2 2s 1 2p 6 3p 1 resonance state involves a sequential resonance-valence excitation. First, a long pump pulse excites the core-hole state, and then a shorter Stokes pulse transfers the population to the valence state. This process represents the first step in a multidimensional x-ray spectroscopy scheme that will provide a local probe of valence electronic correlations. Although at the optimal pulse intensities at the TDCIS level of theory the MCTDHF method predicts multiple ionization or excitation ionization of the atom, at slightly lower intensities (reduced by a factor of about 4) the TDCIS mechanism is shown to hold qualitatively. Quantitatively, the MCTDHF populations are reduced from the TDCIS calculations by a factor of 4.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Exploiting Geometric Partitioning in Task Mapping for Parallel Computes

We present a new method for mapping applications' MPI tasks to cores of a parallel computer such that applications' communication time is reduced. We address the case of sparse node allocation, where the nodes assigned to a job are not necessarily located in a contiguous block nor within close proximity to each other in the network, although our methods generalize to contiguous allocations as well. The goal is to assign tasks to cores so that interdependent tasks are performed by "nearby' cores, thus lowering the distance messages must travel, the amount of congestion in the network, and the overall cost of communication. Our new method applies a geometric partitioning algorithm to both the tasks and the processors, and assigns task parts to the corresponding processor parts. We also present a number of algorithmic optimizations that exploit specific features of the network or application. We show that, for the structured finite difference mini-application MiniGhost, our mapping methods reduced communication time up to 75% relative to MiniGhost's default mapping on 128K cores of a Cray XK7 with sparse allocation. For the atmospheric modeling code E3SM/HOMME, our methods reduced communication time up to 31% on 32K cores of an IBM BlueGene/Q with contiguous allocation.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1992

Weight optimization of an aerobrake structural concept for a lunar transfer vehicle

An aerobrake structural concept for a lunar transfer vehicle was weight optimized through the use of the Taguchi design method, finite element analyses, and element sizing routines. Six design parameters were chosen to represent the aerobrake structural configuration. The design parameters included honeycomb core thickness, diameter-depth ratio, shape, material, number of concentric ring frames, and number of radial frames. Each parameter was assigned three levels. The aerobrake structural configuration with the minimum weight was 44 percent less than the average weight of all the remaining satisfactory experimental configurations. In addition, the results of this study have served to bolster the advocacy of the Taguchi method for aerospace vehicle design. Both reduced analysis time and an optimized design demonstrated the applicability of the Taguchi method to aerospace vehicle design.

Bush, Lance B.↗
DOE OSTI2025

SymProp: Scaling Sparse Symmetric Tucker Decomposition via Symmetry Propagation

Sparse symmetric tensors are an important class of tensors, and their decompositions serve as powerful tools for revealing low-rank structures. This paper introduces SymProp, a novel approach for scaling sparse symmetric Tucker decomposition by propagating symmetry through intermediate computations. SymProp optimizes two key computational kernels: Sparse Symmetric Tensor Times Same Matrix chain (S3 TTMc) for Higher-Order Orthogonal Iteration (HOOI) and Sparse Symmetric Tensor Times Same Matrix chain Times Core (S3 TTMcTC) for Higher-Order QR Iteration (HOQRI). Our method employs a metaprogramming-based index iteration approach to efficiently handle the upper triangular parts of intermediate dense symmetric tensors. SymProp achieves up to 50.9× speedup over SPLATT and up to 360.8× over Compressed Sparse Symmetric (CSS) format on the S3 TTMc operation. Moreover, our S3 TTMc and S3 TTMcTC implementations support tensor orders four levels higher than state-of-the-art methods. Our HOQRI demonstrates superior scalability and up to a 33.6× speedup over optimized HOOI. By enabling more scalable Tucker decompositions for higher orders, decomposition ranks, and dimension sizes, SymProp opens new possibilities for analyzing complex hypergraph structures in fields such as network science, data mining, and machine learning.

Li, Zecheng [North Carolina State University]↗
NASA NTRS2002

Optimal Extraction with Sub-sampled Line-Spread Functions

STIS long-slit medium resolution spectra reduced in CALSTIS extended-source mode with narrow extraction heights (GWIDTH=3 pixels) show photometric uncertainties of +/- 3% relative to point-source extractions. These uncertainties are introduced through interpolation in the spectral image rectification processing stage, and are correlated with the number of pixel crossings the spectral profile core encounters in the spatial direction. The line-spread-function may be determined as a function of pixel crossing- position from calibration data sub-sampled in the spatial direction. This line spread function will be applied to science data to perform optimal extractions and point- source de-blending. Wavelength and breathing effects will be studied. Viability of the method to de-convolve extended source 'blobs' will be investigated.

Collins, Nicholas R.↗
NASA NTRS2000

Deep Internal Structure of Mars and the Geophysical Package of Netlander

Our present understanding of the interior structure of Mars is mostly based on the interpretation of gravity and rotation data, the chemistry of the SNC (shergottites, nakhlites, chassignites) meteoroids, and a comparison with the much better-known interior structure of the Earth. However geophysical information from previous missions have been insufficient to determine the deep internal structure of the planet. Therefore the state and size of the core and the depth and type of mantle discontinuities are unknown. Most previous seismic experiments have indeed failed, either due to a launch failure (as for the Optimism seismometer onboard the small surface stations of Mars 96) or after failure on Mars (as for the Viking 1 seismometer). The remaining Viking 2 seismometer did not produce a convincing marsquake detection, basically due to too strong wind sensitivity and too low resolution in the teleseismic frequency band. After almost a decade of continuous activity and proposals, the first network mission to Mars, NetLander (NL), is expected to be launched between 2005 and 2007. One of the main scientific objectives of this four-lander network mission will be the determination of the internal structure of the planet using a geophysical package. This package will have a seismometer, a magnetometer, and a geodetic experiment, allowing a complementary approach that will yield many new constraints on the mineralogy and temperature of the mantle and core of the planet.

Lognonne, P.↗
DOE OSTI2022

Transformational Challenge Reactor – On the Application of Design for Additive Manufacturing (DfAM) Techniques to the Conception of Nuclear Core

Additive manufacturing (AM) technologies are radically changing the way objects are designed and manufactured. They allow building by deposition and solidification of material layer by layer, enabling the possibility to create simple and complex features alike, almost seamlessly. Generally, the design optimization process requires to define objectives, design variables and constraints. Additive manufacturing does not challenge this process per se but does allow designers to completely redefine the constraints space as the ones originating from fabrication can be considerably relaxed compared to more “traditional” manufacturing. Thus, design optimization becomes naturally far more responsive to the actual physics being solved and considerably less influenced by fabrication limitations, leading to dramatically different designs. To take advantage of these new opportunities, so-called Designing for Additive Manufacturing (DfAM) techniques are emerging. Development of design techniques specifically tailored for additive manufacturing is warranted because, considering AM, the design space is typically considerably larger than with traditional manufacturing. The ability to explore the design space efficiently is of paramount importance for designers. This study proposes to investigate and apply some of these DfAM techniques to the conception of nuclear core. The goal being to assess if these new methods can be applied to core design and if core design could benefits from additive manufacturing technologies. After a brief investigation on the pertinence of some DfAM techniques for core design, algorithms are proposed and a workflow is established to carry neutronics and steady-state thermal-hydraulics analyses. To diminish the work load, the workflow has been automated using python modules. These modules allow the rapid creation of input files, post-treatment of output files and visualization. To test the pertinence of the proposed workflow, three test cases have been investigated: a research and test reactor, a micro-reactor and a space propulsion reactor. These test cases offered a variety of objectives, constraints and operating conditions. It is observed that the proposed workflow is capable of converging quickly and efficiently to valid design solutions. It is then concluded that DfAM techniques can be applied to core design.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2013

Quasi-Linear Circuit

This work involved developing spacequalifiable switch mode DC/DC power supplies that improve performance with fewer components, and result in elimination of digital components and reduction in magnetics. This design is for missions where systems may be operating under extreme conditions, especially at elevated temperature levels from 200 to 300 degC. Prior art for radiation-tolerant DC/DC converters has been accomplished utilizing classical magnetic-based switch mode converter topologies; however, this requires specific shielding and component de-rating to meet the high-reliability specifications. It requires complex measurement and feedback components, and will not enable automatic re-optimization for larger changes in voltage supply or electrical loading condition. The innovation is a switch mode DC/DC power supply that eliminates the need for processors and most magnetics. It can provide a well-regulated voltage supply with a gain of 1:100 step-up to 8:1 step down, tolerating an up to 30% fluctuation of the voltage supply parameters. The circuit incorporates a ceramic core transformer in a manner that enables it to provide a well-regulated voltage output without use of any processor components or magnetic transformers. The circuit adjusts its internal parameters to re-optimize its performance for changes in supply voltage, environmental conditions, or electrical loading at the output

Bradley, William↗
DOE OSTI2022

Reduced Order Models Generation for HTGRs Pebble Shuffling Procedure Optimization Studies

This report provides an initial study for producing reduced-order models (ROMs) of pebble-bed high temperature gas reactor (HTGR) models for the purposes of design optimization. As an initial study, this work is meant to be exploratory---identifying useful workflows and methods for ROM generation---and not meant to be a catch-all analysis of HTGR ROM generation and usage for optimization. This report summarizes three tasks performed in Fiscal Year 2022: 1) the creation of HTGR model, 2) the sensitivity analysis of model design parameters, and 3) an introduction to ROM generation techniques. The representative HTGR model created in this work is a multiphysics equilibrium-core using the BlueCRAB (comprehensive reactor analysis bundle) reactor analysis application, coupling four physical phenomena: neutronics, streamline depletion, porous flow thermal hydraulics, and pebble heat conduction. Part of the model creation was identifying some design parameters and quantities of interest that are relevant in an optimization analysis and adjustable in the model. The sensitivity analysis utilized a polynomial chaos expansion methodology to compute global sensitivity metrics. This analysis showed that thermal hydraulics parameters and quantities of interest had a relatively small impact on simulation results. Finally, the ROM generation work involved exploring three different ROM methodologies: polynomial regression, a Gaussian process, and artificial neural networks. Using a cross-validation technique to characterize ROM performance, the Gaussian process and single-layer artificial neural networks showed the most promising results. Overall, this study was insightful and the lessons learned will be invaluable for the eventual development of an HTGR design optimization workflow.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A Dynamic Risk Framework for the Physical Security of Nuclear Power Plants

This paper describes ongoing work within the Light Water Reactor Sustainability pathway at Idaho National Laboratory (INL) to optimize the security and cost of nuclear power plants. It introduces the dynamic risk assessment tool developed at INL, Event Modeling Risk Assessment using Linked Diagrams (EMRALD). EMRALD is leveraged to optimize the security posture of a nuclear power plant by integrating force-on-force (FOF) simulations and operator mitigation actions, including dynamic and flexible coping strategies (FLEX). To illustrate the methodology, four attack scenarios are modeled in a commercially available FOF simulation tool using a hypothetical nuclear power plant facility. The simulation results provide valuable insights into possible attack outcomes, as well as the probabilistic risk of a core damage event given these outcomes. Safety mitigation procedures are modeled in EMRALD dependent on the attack outcomes by considering human operator uncertainties. The results demonstrate that the number of armed responders can be optimized, while still maintaining the same protection level as the initial security posture. The proposed modeling and simulation framework of integrating FLEX equipment with FOF models enables the nuclear power plants to credit FLEX portable equipment in the plant security posture, resulting in an efficient and optimized physical security system.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

A Dynamic Risk Framework for the Optimization of Physical Security Posture of Nuclear Power Plants

This paper describes an ongoing work within the Light Water Reactor Sustainability pathway at Idaho National Laboratory (INL) to optimize security and cost of nuclear power plants. It introduces the dynamic risk assessment tool developed at INL, Event Modeling Risk Assessment using Linked Diagrams (EMRALD). EMRALD was leveraged to optimize the security posture of a nuclear power plant by integrating force-on-force (FOF) simulations and operator mitigation actions including the dynamic and flexible coping strategies (FLEX). To illustrate the methodology, four attack scenarios were modeled in a commercially available FOF simulation tool using a hypothetical nuclear power plant facility. The simulation results provide valuable insights into possible attack outcomes, as well as the probabilistic risk of core damage event given these outcomes. Safety mitigation procedures were modeled in EMRALD dependent on the attack outcomes by considering human operator uncertainties. The results demonstrate that the number of armed responders can be optimized, while still maintaining the same protection level as the initial security posture. The proposed modeling and simulation framework of integrating FLEX equipment with FOF models enables the nuclear power plants to credit FLEX portable equipment in the plant security posture, resulting in an efficient and optimized physical security system.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

A generalized approach for determining electric machine drive switching schemes using evolutionary optimization algorithms

The number of inverter switching events in one fundamental cycle of an electric machine can be limited by many factors such as inverter switching frequency, rotational speed, and computational time required by control algorithms. Even at low and moderate speeds, switching harmonics cause distortion in the phase current, which can lead to increased torque ripple and core losses when compared to operation with ideal waveforms. Furthermore, as rotational speed increases and voltage limitations are encountered, overmodulation schemes must be implemented to overcome increasing reactance and back-EMF (or pseudo back-EMF). The goal of this paper is to establish a framework and demonstrate methods for determining optimal switching times for a set number of switching events in a fundamental cycle using particle swarm optimization and multivariable fitness functions.

Burress, Timothy↗
DOE OSTI2021

Mesocrystallizing Nanograins for Enhanced Li + Storage

Morphology and crystallinity of electrode materials have a major effect on their charge carrier storage properties when applied in rechargeable batteries. While nanosizing electrode particles (with larger surface area) and maintaining electrode integrity are both good for performance enhancement, they seem to contradict each other and can be hardly well-balanced. Herein, we designed electrode particles consisting of numerous nanograins with uniform crystalline orientation to guarantee both high surface area and high structural integrity, allowing the significant improvement of Li + storage kinetics and performance. Applying this “mesocrystallizing” strategy to a NiCo 2 O 4 -based anode, resulting in various degrees of pseudocapacitance response, the long-term cyclability and rate performance of this material have been largely enhanced. Impressively, the mesocrystalline NiCo 2 O 4 electrode exhibits a high reversible capacity of 1403 mAh g -1 after 200 cycles at 1.6 A g -1 (a rate of 1.8 C). The growth mechanism of mesocrystalline materials with different morphologies is identified to be a topotactic strctural transition process featuring a gradual edge-to-core corrasion process. This work presents an important synthetic clue to balance the morpholgy and crystallinity of battery electrode materials for their perforamnce optimization and is expected to inspire future structural design for battery materials beyond the one prototyped here.

25 ENERGY STORAGE↗