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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Protection of Conductive and Non-conductive Advanced Polymer-based Paints from Highly Aggressive Oxidative Environments

Research has been continued to further improve the space durability of conductive and non-conductive polymer-based paints and of conductive thermal control paints for space applications. Efforts have been made to enhance the space durability and stability of functional Characteristics in ground-based space environment imitating conditions, using specially developed surface modification treatment. The results of surface modification of new conductive paints, including the ground-based testing in aggressive oxidative environments, such as atomic oxygen/UV and oxygen plasma, and performance evaluation are presented. Functional properties and performance characteristics, such as thermal optical properties (differential solar absorptance and thermal emittance representing the thermal optical performance of thermal control paints) and surface resistivity characteristics of pristine, surface modified, and tested materials were verified. Extensive surface analysis studies have been performed using complementary surface analyses including SEM/EDS and XPS. Test results revealed that the successfully treated materials exhibit reduced mass loss and no surface morphology change, thus indicating good protection from the severe oxidative environment. It was demonstrated that the developed surface modification treatment could be applied successfully to charge dissipative and conductive paints.

Gudimenko, Y.↗
NASA NTRS2007

Digital Signal Processing Techniques for the GIFTS SM EDU

The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) Sensor Module (SM) Engineering Demonstration Unit (EDU) is a high resolution spectral imager designed to measure infrared (IR) radiance using a Fourier transform spectrometer (FTS). The GIFTS instrument employs three Focal Plane Arrays (FPAs), which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The raw interferogram measurements are radiometrically and spectrally calibrated to produce radiance spectra, which are further processed to obtain atmospheric profiles via retrieval algorithms. This paper describes several digital signal processing (DSP) techniques involved in the development of the calibration model. In the first stage, the measured raw interferograms must undergo a series of processing steps that include filtering, decimation, and detector nonlinearity correction. The digital filtering is achieved by employing a linear-phase even-length FIR complex filter that is designed based on the optimum equiripple criteria. Next, the detector nonlinearity effect is compensated for using a set of pre-determined detector response characteristics. In the next stage, a phase correction algorithm is applied to the decimated interferograms. This is accomplished by first estimating the phase function from the spectral phase response of the windowed interferogram, and then correcting the entire interferogram based on the estimated phase function. In the calibration stage, we first compute the spectral responsivity based on the previous results and the ideal Planck blackbody spectra at the given temperatures, from which, the calibrated ambient blackbody (ABB), hot blackbody (HBB), and scene spectra can be obtained. In the post-calibration stage, we estimate the Noise Equivalent Spectral Radiance (NESR) from the calibrated ABB and HBB spectra. The NESR is generally considered as a measure of the instrument noise performance, and can be estimated as the standard deviation of calibrated radiance spectra from multiple scans. To obtain an estimate of the FPA performance, we developed an efficient method of generating pixel performance assessments. In addition, a random pixel selection scheme is developed based on the pixel performance evaluation. This would allow us to perform the calibration procedures on a random pixel population that is a good statistical representation of the entire FPA. The design and implementation of each individual component will be discussed in details.

Tian, Jialin↗
DOE OSTI2016

Development and Scale-Up of Copper-Based Chemical Looping with Oxygen Uncoupling

The University of Utah has been researching chemical looping with oxygen uncoupling of coal since 2007, focusing on copper-based carriers and a system configuration based on two interconnected circulating fluidized bed reactors. R&D has combined fundamental, lab-scale systems with operation of CLOU reactor systems at various scales and computational simulations for performance evaluation and reactor scale-up. Development has progressed from small lab scale through bench scale with a 10 kW dual bed research reactor to semi-pilot scale with a recently-inaugurated 220 kW chemical looping combustion process development unit. One of the challenges of scaling up copper-based CLOU technology is acquiring enough oxygen carrier material to support operation in larger reactor systems. The UofU CLC PDU, for example, requires 150-200 kg of inventory, so the oxygen carrier must be readily available in large quantities at comparatively low cost. Because no supplier capable of delivering 1+ tons of copper-based oxygen carrier material could be identified, an inexpensive oxygen carrier material was developed in-house and the carrier production process was scaled to produce large quantities of material sufficient for the CLC PDU. This presentation describes development of the CLOU process at the University of Utah, including evaluation of fundamental processes key to performance of CLOU, modeling and scale-up of the process, large-scale production of copper based oxygen carrier material and experience to date with the world’s largest dedicated CLOU reactor.

Whitty, Kevin J.↗
DOE OSTI2013

Evaluation of Early Performance Results for Massachusetts Homes in the National Grid Pilot Deep Energy Retrofit Program

This research project evaluates post-retrofit performance measurements, energy use data and construction costs for 13 projects that participated in the National Grid Deep Energy Retrofit Pilot program. The projects implemented a package of measures defined by performance targets for building enclosure components and building enclosure air tightness. Nearly all of the homes reached a post-retrofit air tightness result of 1.5 ACH 50. Homes that used the chainsaw retrofit technique along with roof insulation, and wall insulation applied to the exterior had the best air tightness results and the lowest heating and cooling source energy use. Analysis of measure costs and project objectives yielded a categorization of costs relative to energy performance objectives. On average about ½ of the energy-related measure costs correspond primarily to energy-related objectives, and 20% of energy-related measure costs relate primarily to non-energy objectives.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Evaluation of Early Performance Results for Massachusetts Homes in the National Grid Pilot Deep Energy Retrofit Program

This research project evaluates post-retrofit performance measurements, energy use data and construction costs for 13 projects that participated in the National Grid Deep Energy Retrofit Pilot program. The projects implemented a package of measures defined by performance targets for building enclosure components and building enclosure air tightness. Nearly all of the homes reached a post-retrofit air tightness result of 1.5 ACH 50. Homes that used the chainsaw retrofit technique along with roof insulation, and wall insulation applied to the exterior had the best air tightness results and the lowest heating and cooling source energy use. Analysis of measure costs and project objectives yielded a categorization of costs relative to energy performance objectives. On average about 1/2 of the energy-related measure costs correspond primarily to energy-related objectives, and 20% of energy-related measure costs relate primarily to non-energy objectives.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Evaluation of a Bioabsorbable Self-Expandable Vein Stent-Base Made of Poly(l-lactide) In Vitro and In Vivo

PurposeThis study was designed to evaluate performance and tissue response to a self-expandable bioabsorbable vein stent-base cut from a tube with enhanced stiffness and strength in vitro and in vivo.MethodsA diamond-shaped stent-base was cut from a sequential biaxially strained poly(l-lactide) (PLLA) tube for optimized performance. The performance of the stent-base was evaluated in a finite element analysis model, and validation was attempted in vitro through a cyclic flat-plate compression and radial force measurement. The performance of the stent-base was tested in vivo using 3 sheep with 2 implants each for 2 and 3½ weeks, respectively.ResultsIn vitro the stent-base showed an elliptical deformation but no fractures. In vivo the stent-base showed adequate radial force and no migration. All implanted stent-bases showed multiple fractures not only at the predicted stress zones but at all connecting points. Fragments of the caudal stent-base stayed in the vein wall indicating sufficient tissue coverage to avoid embolization of the fractured stent pieces, whereas fragments from the cranial device remaining were few. Neointima formation was confirmed histologically at 2 and 3½ weeks.ConclusionA bioabsorbable self-expandable stent-base made from PLLA for large veins seems feasible, but over time, the PLLA used in this study appears too stiff and lacks the sufficient flexibility to move with the vena cava, causing multiple fractures.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Evaluation of Optimal Net Load Management in Microgrids Using Hardware-in-the-Loop Simulation

This paper presents the performance evaluation of a net load management (NLM) engine that balances load and generation in an isolated community to power a critical facility after a grid interruption event (e.g., the loss of a large generation unit). This NLM engine is particularly important for microgrid systems because it provides a high-speed, cost-optimal control solution to coordinate grid-forming inverters and to dispatch grid-following inverters and deferrable loads in microgrid systems to enhance grid resilience and reliability. The NLM algorithm cost-optimally dispatches the grid-following inverters and deferrable loads based on the demanded power and load priorities, and the grid-forming inverters use droop control to form system voltages and share active and reactive power. A controller-hardware-in-the-loop platform is developed to evaluate the control performance of the NLM algorithm with two sequential contingency events of lost generation units. The experimental results indicate that the NLM engine can maintain system stability, achieve the targeted system voltage and frequency, and balance load and generation to serve the critical facility with improved system resilience and reliability.

grid-following inverter↗
DOE OSTI2022

Evaluation of Optimal Net Load Management in Microgrids Using Hardware-in-the-Loop Simulation

This presentation discusses the performance evaluation of a net load management (NLM) engine that balances load and generation in an isolated community to power a critical facility after a grid interruption event (e.g., the loss of a large generation unit). This NLM engine is particularly important for microgrid systems because it provides a high-speed, cost-optimal control solution to coordinate grid-forming inverters and to dispatch grid-following inverters and deferrable loads in microgrid systems to enhance grid resilience and reliability. The NLM algorithm cost-optimally dispatches the grid-following inverters and deferrable loads based on the demanded power and load priorities, and the grid-forming inverters use droop control to form system voltages and share active and reactive power. A controller-hardware-in-the-loop platform is developed to evaluate the control performance of the NLM algorithm with two sequential contingency events of lost generation units. The experimental results indicate that the NLM engine can maintain system stability, achieve the targeted system voltage and frequency, and balance load and generation to serve the critical facility with improved system resilience and reliability.

droop control↗
DOE OSTI2023

Accelerating Random Forest Classification on GPU and FPGA

Random Forests (RFs) are a commonly used machine learning method for classification and regression tasks spanning a variety of application domains, including bioinformatics, business analytics, and software optimization. While prior work has focused primarily on improving performance of the training of RFs, many applications, such as malware identification, cancer prediction, and banking fraud detection, require fast RF classification. In this work, we accelerate RF classification on GPU and FPGA. In order to provide efficient support for large datasets, we propose a hierarchical memory layout suitable to the GPU/FPGA memory hierarchy. We design three RF classification code variants based on that layout, and we investigate GPU- and FPGA-specific considerations for these kernels. Our experimental evaluation, performed on an Nvidia Xp GPU and on a Xilinx Alveo U250 FPGA accelerator card using publicly available datasets on the scale of millions of samples and tens of features, covers various aspects. First, we evaluate the performance benefits of our hierarchical data structure over the standard compressed sparse row (CSR) format. Second, we compare our GPU implementation with cuML, a machine learning library targeting Nvidia GPUs. Third, we explore the performance/accuracy tradeoff resulting from the use of different tree depths in the RF. Finally, we perform a comparative performance analysis of our GPU and FPGA implementations. Our evaluation shows that for high accuracy targets, our GPU implementation yields 5-9x speedup over CSR, and up to a 2x speedup over cuML.

FPGA, Xilinx FPGA, GPU, Random Forest classificati↗
NASA NTRS1994

Evaluating Multi-Input/Multi-Output Digital Control Systems

Controller-performance-evaluation (CPE) methodology for multi-input/multi-output (MIMO) digital control systems developed. Procedures identify potentially destabilizing controllers and confirm satisfactory performance of stabilizing ones. Methodology generic and used in many types of multi-loop digital-controller applications, including digital flight-control systems, digitally controlled spacecraft structures, and actively controlled wind-tunnel models. Also applicable to other complex, highly dynamic digital controllers, such as those in high-performance robot systems.

Pototzky, Anthony S.↗
DOE OSTI2022

Evaluation of Optimal Net Load Management in Microgrids Using Hardware-in-the-Loop Simulation: Preprint

This paper presents the performance evaluation of a net load management (NLM) engine that balances load and generation in an isolated community to power a critical facility after a grid interruption event (e.g., lost a large generation unit). The NLM engine is a central dispatch control system that provides high-speed cost-optimal coordination of a set of net loads (combination of generation and deferrable loads) connected to the same electrical network. The NLM algorithm cost-optimally dispatches the grid-following inverters and deferrable loads based on the demanded power and load priorities, and the grid-forming inverters use droop control to form system voltages and share active and reactive power. A controller-hardware-in-the-loop platform is developed to evaluate the control performance of the NLM algorithm. The experimental results indicate that the NLM engine can achieve the targeted system voltage and frequency and balance load and generation to serve the critical facility.

droop control↗
NASA NTRS2019

High-Performance Computing Optimization for Aladyn – Adaptive Neural Network Molecular Dynamics Mini-Application

This report provides a description and performance evaluation of the optimization techniques for high performance computing (HPC) implementation of the open source Computational Materials mini-application Aladyn (https://github.com/nasa/aladyn). Aladyn is a basic molecular dynamics code written in FORTRAN 2003, which is designed to demonstrate the use of adaptive neural networks (ANNs) in atomistic simulations. The role of ANNs is to efficiently reproduce the very complex energy landscape resulting from the atomic interactions in materials with the accuracy of the more expensive quantum mechanics-based calculations. The ANN is trained on a large set of atomic structures calculated using the density functional theory (DFT) method. While achieving orders of magnitude faster computational performance than DFT, the ANN-based approach was still very computationally demanding compared to the conventional approach of using empirically fitted energy functions. After its initial development, Aladyn was evaluated and optimized by experts at the NASA Advanced Supercomputing (NAS) division to exploit modern supercomputer architectures. The code has been optimized for execution on multicore central processing units (CPUs), including Intel® Skylake microarchitecture, and on graphic accelerators, such as Nvidia® V100 graphic processing units (GPUs), using Open Multi-Processing (OpenMP) and Open Accelerators (OpenACC) programming interfaces. The optimization achieved a speedup of 4.7 times the baseline version on CPU performance and an additional 2.4 times on CPU+GPU performance. Atomistic computer simulations are a fundamental tool in materials research to model material properties form physics-based first principles. Atomic interaction, governed by Quantum Mechanics (QM) require sophisticated and highly computationally demanding mathematical models to calculate [1]. Classical methods use approximate functional forms, empirically fitted through a set of variable parameters to emulate atomic energies as direct functions of atomic coordinates [2]. While empirical potentials are computationally much simpler, allowing simulations of large-scale systems of up to a trillion (1012) atoms [3], they are substantially less accurate compared to quantum calculations and applicable only to very specific atomic configurations or predefined crystallographic phases. A recently suggested approach is to use heuristic machine learning methods [4], such as those based on Adaptive Neural Networks (ANNs) to predict atomic energies, after being trained on a sufficiently large database of QM-calculated structures [5,6]. This approach reduces significantly the computational complexity, allowing for simulations of orders of magnitude larger systems compared to QM-based methods without compromising accuracy. Still, compared to classical methods using empirical energy functions, ANN methods remain two- to three orders of magnitude more computationally demanding. Hence, the computational cost of simulations, together with the need for extensive training of ANNs, still makes the practical implementation of ANN-based methods quite challenging. The purpose of the Aladyn mini-application software [7], available as open source at https://github.com/nasa/aladyn, is to be a testbed for exploring possible optimization strategies to develop highly scalable parallel algorithms for ANN-based atomistic simulations. Aladyn is aimed at utilizing the architecture of the high-end modern highperformance computing (HPC) hardware based on multicore central processing units (CPUs) equipped with graphic processing unit (GPU) accelerators. Specifically, the goal is to optimize the performance on a single HPC compute node, before implementing scaling to multi-node parallelization using message passing interface (MPI). At the same time, the open source code of Aladyn can serve as a training model for students and professors in academia.

Yamakov, Vesselin I.↗
DOE OSTI2014

Evaluating iterative reconstruction performance in computed tomography

Purpose: Iterative reconstruction (IR) offers notable advantages in computed tomography (CT). However, its performance characterization is complicated by its potentially nonlinear behavior, impacting performance in terms of specific tasks. This study aimed to evaluate the performance of IR with both task-specific and task-generic strategies. Methods: The performance of IR in CT was mathematically assessed with an observer model that predicted the detection accuracy in terms of the detectability index (d′). d′ was calculated based on the properties of the image noise and resolution, the observer, and the detection task. The characterizations of image noise and resolution were extended to accommodate the nonlinearity of IR. A library of tasks was mathematically modeled at a range of sizes (radius 1–4 mm), contrast levels (10–100 HU), and edge profiles (sharp and soft). Unique d′ values were calculated for each task with respect to five radiation exposure levels (volume CT dose index, CTDI{sub vol}: 3.4–64.8 mGy) and four reconstruction algorithms (filtered backprojection reconstruction, FBP; iterative reconstruction in imaging space, IRIS; and sinogram affirmed iterative reconstruction with strengths of 3 and 5, SAFIRE3 and SAFIRE5; all provided by Siemens Healthcare, Forchheim, Germany). The d′ values were translated into the areas under the receiver operating characteristic curve (AUC) to represent human observer performance. For each task and reconstruction algorithm, a threshold dose was derived as the minimum dose required to achieve a threshold AUC of 0.9. A task-specific dose reduction potential of IR was calculated as the difference between the threshold doses for IR and FBP. A task-generic comparison was further made between IR and FBP in terms of the percent of all tasks yielding an AUC higher than the threshold. Results: IR required less dose than FBP to achieve the threshold AUC. In general, SAFIRE5 showed the most significant dose reduction potentials (11–54 mGy, 77%–84%), followed by SAFIRE3 (7–36 mGy, 50%–61%) and IRIS (6–26 mGy, 37%–50%). The dose reduction potentials highly depended on task size and task contrast, with tasks of lower contrasts and smaller sizes, i.e., more challenging tasks, indicating higher dose reductions. Softer edge profile showed higher dose reduction potentials with SAFIRE3 and SAFIRE5, but not with IRIS. The task-generic comparison between IR and FBP demonstrated the overall superiority of IR performance, as IR allowed a larger percent of tasks to exceed the threshold AUC: IRIS, 8%–12%; SAFIRE3, 10%–16%; and SAFIRE5, 20%–33%. The improvement with IR was generally more pronounced at lower dose levels. Conclusions: Expanding beyond traditional contrast and noise based assessments of IR, we performed both task-specific and task-generic evaluations of IR performance. The task-specific evaluation demonstrated the dependency of IR’s dose reduction potential on task attributes, which can be employed to optimize IR for clinical indications with specific range of size and contrast. The task-generic evaluation demonstrated IR’s overall superiority over FBP in terms of the range of tasks exceeding a threshold performance level, which can be employed for general comparisons between algorithms.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Geant4 Computing Performance Benchmarking and Monitoring

Performance evaluation and analysis of large scale computing applications is essential for optimal use of resources. As detector simulation is one of the most compute intensive tasks and Geant4 is the simulation toolkit most widely used in contemporary high energy physics (HEP) experiments, it is important to monitor Geant4 through its development cycle for changes in computing performance and to identify problems and opportunities for code improvements. All Geant4 development and public releases are being profiled with a set of applications that utilize different input event samples, physics parameters, and detector configurations. Results from multiple benchmarking runs are compared to previous public and development reference releases to monitor CPU and memory usage. Observed changes are evaluated and correlated with code modifications. Besides the full summary of call stack and memory footprint, a detailed call graph analysis is available to Geant4 developers for further analysis. The set of software tools used in the performance evaluation procedure, both in sequential and multi-threaded modes, include FAST, IgProf and Open|Speedshop. In conclusion, the scalability of the CPU time and memory performance in multi-threaded application is evaluated by measuring event throughput and memory gain as a function of the number of threads for selected event samples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Temporal Cyber Attack Detection.

Rigorous characterization of the performance and generalization ability of cyber defense systems is extremely difficult, making it hard to gauge uncertainty, and thus, confidence. This difficulty largely stems from a lack of labeled attack data that fully explores the potential adversarial space. Currently, performance of cyber defense systems is typically evaluated in a qualitative manner by manually inspecting the results of the system on live data and adjusting as needed. Additionally, machine learning has shown promise in deriving models that automatically learn indicators of compromise that are more robust than analyst-derived detectors. However, to generate these models, most algorithms require large amounts of labeled data (i.e., examples of attacks). Algorithms that do not require annotated data to derive models are similarly at a disadvantage, because labeled data is still necessary when evaluating performance. In this work, we explore the use of temporal generative models to learn cyber attack graph representations and automatically generate data for experimentation and evaluation. Training and evaluating cyber systems and machine learning models requires significant, annotated data, which is typically collected and labeled by hand for one-off experiments. Automatically generating such data helps derive/evaluate detection models and ensures reproducibility of results. Experimentally, we demonstrate the efficacy of generative sequence analysis techniques on learning the structure of attack graphs, based on a realistic example. These derived models can then be used to generate more data. Additionally, we provide a roadmap for future research efforts in this area.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1975

JANNAF boundary layer integral matrix procedure

Accurate predictions of the thrust loss due to boundary layer effects and of the wall heat flux are very important to the design and performance evaluation of rocket nozzles. A method used in analytical procedures for liquid fuel rocket engine performance prediction and evaluation is presented. A computer program is examined that is a fast and accurate procedure for solving the set of boundary layer equation (momentum, energy, and species) for laminar or turbulent, chemically reacting flows with a wide variety of boundary conditions. Results of comparison of the various turbulent models are presented. A summary of the modifications and additions to the program is examined.

Evans, R. M.↗
NASA NTRS1973

Strapdown system performance optimization test evaluations (SPOT), volume 1

A three axis inertial system was packaged in an Apollo gimbal fixture for fine grain evaluation of strapdown system performance in dynamic environments. These evaluations have provided information to assess the effectiveness of real-time compensation techniques and to study system performance tradeoffs to factors such as quantization and iteration rate. The strapdown performance and tradeoff studies conducted include: (1) Compensation models and techniques for the inertial instrument first-order error terms were developed and compensation effectivity was demonstrated in four basic environments; single and multi-axis slew, and single and multi-axis oscillatory. (2) The theoretical coning bandwidth for the first-order quaternion algorithm expansion was verified. (3) Gyro loop quantization was identified to affect proportionally the system attitude uncertainty. (4) Land navigation evaluations identified the requirement for accurate initialization alignment in order to pursue fine grain navigation evaluations.

Blaha, R. J.↗