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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Validation of Microgrid Algorithms using At-Scale Simulation and Emulation Real-Time (ASSERT) Framework

This paper presents a novel framework for validating microgrid algorithms using a At-Scale Simulation and Emulation Real-Time (ASSERT) setup. The proposed universal microgrid validation framework was developed at Advanced Research on Integrated Energy Systems (ARIES) platform at National Renewable Energy Laboratory in Golden, Colorado, USA. As the number of intercommunicating devices grow in power systems, along with more integration of inverter-based resources, developing and validating microgrid operation and control algorithms is becoming complex and time-consuming task. The ASSERT framework is designed to provide a comprehensive, accurate, and efficient solution for validating microgrid algorithms. It combines at-scale simulations and real-time emulation to create a virtual environment that closely mimics the behavior of a physical microgrids which are characteristic of future smart distribution systems, such as: (1) increasing variability in the physical size of new energy technologies; (2) requiring control large numbers of interconnected devices, and (3) integrating diverse technologies that have not previously worked together. The paper describes the technical details of the ASSERT framework, its validation process, and its benefits over traditional validation methods. The framework's ability to validate the performance of various algorithms is demonstrated through a case study, which shows that it can effectively identify the weaknesses of an algorithm and optimize its performance. Overall, the ASSERT framework is a promising tool that can significantly enhance the development and validation of microgrid algorithms, leading to more reliable and efficient microgrid operation.

at-scale↗
NASA NTRS2004

Improved Timing Scheme for Spaceborne Precipitation Radar

An improved timing scheme has been conceived for operation of a scanning satellite-borne rain-measuring radar system. The scheme allows a real-time-generated solution, which is required for auto targeting. The current timing scheme used in radar satellites involves pre-computing a solution that allows the instrument to catch all transmitted pulses without transmitting and receiving at the same time. Satellite altitude requires many pulses in flight at any time, and the timing solution to prevent transmit and receive operations from colliding is usually found iteratively. The proposed satellite has a large number of scanning beams each with a different range to target and few pulses per beam. Furthermore, the satellite will be self-targeting, so the selection of which beams are used will change from sweep to sweep. The proposed timing solution guarantees no echo collisions, can be generated using simple FPGA-based hardware in real time, and can be mathematically shown to deliver the maximum number of pulses per second, given the timing constraints. The timing solution is computed every sweep, and consists of three phases: (1) a build-up phase, (2) a feedback phase, and (3) a build-down phase. Before the build-up phase can begin, the beams to be transmitted are sorted in numerical order. The numerical order of the beams is also the order from shortest range to longest range. Sorting the list guarantees no pulse collisions. The build-up phase begins by transmitting the first pulse from the first beam on the list. Transmission of this pulse starts a delay counter, which stores the beam number and the time delay to the beginning of the receive window for that beam. The timing generator waits just long enough to complete the transmit pulse plus one receive window, then sends out the second pulse. The second pulse starts a second delay counter, which stores its beam number and time delay. This process continues until an output from the first timer indicates there is less than one transmit pulse width until the start of the next receive event. This blocks future transmit pulses in the build-up phase. The feedback phase begins with the first timer paying off and starting the first receive window. When the first receive window is complete, the timing generator transmits the next beam from the list. When the second timer pays off, the second receive event is started. Following the second receive event, the timing generator will transmit the next beam on the list and start an additional timer. The timers work in a circular buffer fashion so there only need to be enough to cover the maximum number of echoes in flight.

Berkun, Andrew↗
NASA NTRS1973

Fatigue-test acceleration with flight-by-flight loading and heating to simulate supersonic-transport operation

Possibilities for reducing fatigue-test time for supersonic-transport materials and structures were studied in tests with simulated flight-by-flight loading. In order to determine whether short-time tests were feasible, the results of accelerated tests (2 sec per flight) were compared with the results of real-time tests (96 min per flight). The effects of design mean stress, the stress range for ground-air-ground cycles, simulated thermal stress, the number of stress cycles in each flight, and salt corrosion were studied. The flight-by-flight stress sequences were applied to notched sheet specimens of Ti-8Al-1Mo-1V and Ti-6Al-4V titanium alloys. A linear cumulative-damage analysis accounted for large changes in stress range of the simulated flights but did not account for the differences between real-time and accelerated tests. The fatigue lives from accelerated tests were generally within a factor of two of the lives from real-time tests; thus, within the scope of the investigation, accelerated testing seems feasible.

Imig, L. A.↗
NASA NTRS1995

Optimal guidance law development for an advanced launch system

The objective of this research effort was to develop a real-time guidance approach for launch vehicles ascent to orbit injection. Various analytical approaches combined with a variety of model order and model complexity reduction have been investigated. Singular perturbation methods were first attempted and found to be unsatisfactory. The second approach based on regular perturbation analysis was subsequently investigated. It also fails because the aerodynamic effects (ignored in the zero order solution) are too large to be treated as perturbations. Therefore, the study demonstrates that perturbation methods alone (both regular and singular perturbations) are inadequate for use in developing a guidance algorithm for the atmospheric flight phase of a launch vehicle. During a second phase of the research effort, a hybrid analytic/numerical approach was developed and evaluated. The approach combines the numerical methods of collocation and the analytical method of regular perturbations. The concept of choosing intelligent interpolating functions is also introduced. Regular perturbation analysis allows the use of a crude representation for the collocation solution, and intelligent interpolating functions further reduce the number of elements without sacrificing the approximation accuracy. As a result, the combined method forms a powerful tool for solving real-time optimal control problems. Details of the approach are illustrated in a fourth order nonlinear example. The hybrid approach is then applied to the launch vehicle problem. The collocation solution is derived from a bilinear tangent steering law, and results in a guidance solution for the entire flight regime that includes both atmospheric and exoatmospheric flight phases.

Calise, Anthony J.↗
NASA NTRS2013

Space Weather Monitoring for ISS Geomagnetic Storm Studies

The International Space Station (ISS) space environments community utilizes near real time space weather data to support a variety of ISS engineering and science activities. The team has operated the Floating Potential Measurement Unit (FPMU) suite of plasma instruments (two Langmuir probes, a floating potential probe, and a plasma impedance probe) on ISS since 2006 to obtain in-situ measurements of plasma density and temperature along the ISS orbit and variations in ISS frame potential due to electrostatic current collection from the plasma environment (spacecraft charging) and inductive (vxB) effects from the vehicle motion across the Earth s magnetic field. An ongoing effort is to use FPMU for measuring the ionospheric response to geomagnetic storms at ISS altitudes and investigate auroral charging of the vehicle as it passes through regions of precipitating auroral electrons. This work is challenged by restrictions on FPMU operations that limit observation time to less than about a third of a year. As a result, FPMU campaigns ranging in length from a few days to a few weeks are typically scheduled weeks in advance for ISS engineering and payload science activities. In order to capture geomagnetic storm data under these terms, we monitor near real time space weather data from NASA, NOAA, and ESA sources to determine solar wind disturbance arrival times at Earth likely to be geoeffective (including coronal mass ejections and high speed streams associated with coronal holes) and activate the FPMU ahead of the storm onset. Using this technique we have successfully captured FPMU data during a number of geomagnetic storm periods including periods with ISS auroral charging. This presentation will describe the strategies and challenges in capturing FPMU data during geomagnetic storms, the near real time space weather resources utilized for monitoring the space weather environment, and provide examples of auroral charging data obtained during storm operations.

Minow, Joseph I.↗
NASA NTRS2013

Space Weather Monitoring for ISS Geomagnetic Storm Studies

The International Space Station (ISS) space environments community utilizes near real time space weather data to support a variety of ISS engineering and science activities. The team has operated the Floating Potential Measurement Unit (FPMU) suite of plasma instruments (two Langmuir probes, a floating potential probe, and a plasma impedance probe) on ISS since 2006 to obtain in-situ measurements of plasma density and temperature along the ISS orbit and variations in ISS frame potential due to electrostatic current collection from the plasma environment (spacecraft charging) and inductive (vxB) effects from the vehicle motion across the Earth s magnetic field. An ongoing effort is to use FPMU for measuring the ionospheric response to geomagnetic storms at ISS altitudes and investigate auroral charging of the vehicle as it passes through regions of precipitating auroral electrons. This work is challenged by restrictions on FPMU operations that limit observation time to less than about a third of a year. As a result, FPMU campaigns ranging in length from a few days to a few weeks are typically scheduled weeks in advance for ISS engineering and payload science activities. In order to capture geomagnetic storm data under these terms, we monitor near real time space weather data from NASA, NOAA, and ESA sources to determine solar wind disturbance arrival times at Earth likely to be geoeffective (including coronal mass ejections and high speed streams associated with coronal holes) and activate the FPMU ahead of the storm onset. Using this technique we have successfully captured FPMU data during a number of geomagnetic storm periods including periods with ISS auroral charging. This presentation will describe the strategies and challenges in capturing FPMU data during geomagnetic storms, the near real time space weather resources utilized for monitoring the space weather environment, and provide examples of auroral charging data obtained during storm operations.

Minow, Joseph I.↗
DOE OSTI2025

A Hybrid Dynamic/Steady-State Tool With Protection Simulation for Cascading-Outage Analysis of Extreme Events in Power Systems

The bulk electric power grid is subject to vulnerabilities from component outages, which in certain combinations (extreme events) might lead to cascading outages. Some of these outages can be severe enough to trigger brownouts and blackouts. Much is known about mitigating the first few failures near the beginning of a cascade, but there are few established methods and tools for directly analyzing the risks of cascading component outages over a longer time scale. Current power system tools have limited ability to perform detailed and accurate cascading-outage analysis, which could be computationally intensive. The Dynamic Contingency Analysis Tool (DCAT) enables power system planning engineers to more realistically assess the consequences of extreme contingencies and potential cascading events across their systems and interconnections. DCAT has several unique features: (i) detailed hybrid dynamic and steady-state analysis of power systems to mimic real-world cascading outages, (ii) detailed modeling of protection systems embedded in the dynamic simulation, (iii) simulation of corrective action after transients, (iv) simulation of islanding , and (v) high-performance computing capability to simulate a large number of contingencies in a reasonable time. DCAT outputs will help find technically sound solutions to reduce the risk of cascading outages. This paper provides details of DCAT methodology and shows its capabilities with extreme events on real-world cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1974

A fluctuating surface pressure test technique utilizing Mach number sweeps at transonic speeds

A multichannel on-line RMS data acquisition and reduction system has been developed using commercial RMS computing modules and a programmable calculator. Details of this system, which has the capability of acquiring 96 channels of RMS data and computing and printing desired parameters in near real-time, are presented. In addition, raw data can be recorded at a much higher rate for computation and printing later. Results are presented showing the benefits of this system in 'sweep' tests where one parameter such as Mach number or angle of attack is slowly varied with time.

Hanly, R. D.↗
DOE OSTI2026

pyRMG: A framework for high-throughput, large-cell DFT calculations on supercomputers

Exascale computing delivers the raw power to simulate ever larger and more chemically realistic systems, but realizing this potential requires codes that can efficiently use thousands of processors. Our real-space multigrid (RMG) density functional theory (DFT) code’s grid-decomposition approach scales nearly linearly with the number of graphics processing units (GPUs), even for simulations exceeding thousands of atoms. This scalability makes RMG a compelling tool for high-throughput DFT studies of materials that would otherwise be bottlenecked in other codes (for example, by global fast Fourier transforms in plane-wave DFT). However, the limited workflow infrastructure for RMG has thus far constrained its adoption to a small user community. In this work, we present pyRMG, a Python package designed to streamline the setup and execution of RMG DFT calculations. Built on the pymatgen and ASE (Atomic Simulation Environment) computational materials science Python packages, pyRMG automates input generation and convergence checking, and it integrates with modern job schedulers (e.g., Flux) on leadership-class platforms such as Frontier and Perlmutter. Here, we demonstrate pyRMG for a high-throughput study of strain effects in 2D 2L-Bi 2 Se 3 /2L-NbSe 2 heterostructures, which offers chemical insights into this system and shows that RMG-based workflows can converge with limited user intervention.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Statistical uncertainties of the v n { 2 k } harmonics from Q cumulants

Analytic formulas to calculate statistical uncertainties of v n { 2 k } harmonics extracted from the Q cumulants are presented. The Q cumulants are multivariate polynomial functions of the weighted means of 2m-particle azimuthal correlations, $\langle\langle 2 m \rangle\rangle$. Variances and covariances of the $\langle\langle 2 m \rangle\rangle$ are included in the analytic formulas of the uncertainties that can be calculated simultaneously with the calculations of the v n { 2 k } harmonics. The calculations are performed using a simple toy model, which roughly simulates elliptic flow azimuthal anisotropy with magnitudes around 0.05. The results are compared with the results obtained by the many data subsets, and by the bootstrapping method. The first one is a common way of estimation of the statistical uncertainties of the v n { 2 k } harmonics in a real experiment. In order to increase precision in the measurement of the v n { 2 k } harmonics, a large number of 15 000 subsets and the same number of the resampling in the bootstrap method is used. Unlike the other ways of the analytic calculation of the v n { 2 k } statistical uncertainties, our proposal that includes the use of squared weights in the calculation of both the variances and covariances, gives the best agreement with the results obtained from the subsets and bootstrap method. Additionally, a recurrence equation between Q cumulants of any order is also presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Dose optimization of an adjuvanted peptide-based personalized neoantigen melanoma vaccine

The advancements in next-generation sequencing have made it possible to effectively detect somatic mutations, which has led to the development of personalized neoantigen cancer vaccines that are tailored to the unique variants found in a patient’s cancer. These vaccines can provide significant clinical benefit by leveraging the patient’s immune response to eliminate malignant cells. However, determining the optimal vaccine dose for each patient is a challenge due to the heterogeneity of tumors. To address this challenge, we formulate a mathematical dose optimization problem based on a previous mathematical model that encompasses the immune response cascade produced by the vaccine in a patient. We propose an optimization approach to identify the optimal personalized vaccine doses, considering a fixed vaccination schedule, while simultaneously minimizing the overall number of tumor and activated T cells. To validate our approach, we perform in silico experiments on six real-world clinical trial patients with advanced melanoma. We compare the results of applying an optimal vaccine dose to those of a suboptimal dose (the dose used in the clinical trial and its deviations). Our simulations reveal that an optimal vaccine regimen of higher initial doses and lower final doses may lead to a reduction in tumor size for certain patients. Our mathematical dose optimization offers a promising approach to determining an optimal vaccine dose for each patient and improving clinical outcomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Autoencoder Neural Network for chemically reacting systems

Incorporating detailed chemical kinetic models is critical for accurate simulations of reacting flows. However, detailed models involve a large number of thermochemical (TC) state variables. Solving the governing equations to evolve these TC variables becomes impractical for real-world applications. In this work, we propose an autoencoder (AE) neural network (NN)-based reduced model to accelerate such simulations. The AE NN is first trained to find a low-dimensional latent representation of the TC states. Then, the evolving state of a chemical system can be tracked by solving the equations of the latent variables instead of the original TC equations. We demonstrate the reduced model in a syngas CO/H 2 combustion system, using training data collected from canonical perfectly stirred reactors (PSRs). It is found that the AE model can reduce the dimension of the combustion system from 12 to 2 while maintaining low reconstruction error and excellent elemental mass conservation for the test dataset. In the a posteriori test, the combustion states obtained from solving the two latent equations are compared to those from solving the 12 equations of the full model. The AE reduced method is found to be able to capture the diverse combustion states on the top two branches of the S-curve well including the extinction turning point, but with higher prediction errors for states near the ignition turning point.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1976

Investigation of Pearl River data collection system

The reliability of employing NASA developed remote sensing for in situ near real time monitoring of water quality in the Pearl River is evaluated. The placement, operation and maintenance of a number of NASA developed data collection platforms (DCP's) on the Pearl River are described. The reception, processing, and retransmission of water quality data from an ERTS satellite to the Mississippi Air and Water Pollution Control Commission (MAWPCC) via computer linkup are assessed.

Source record↗
NASA NTRS1978

X10: A FORTRAN direct access data management system

The XIO system is a set of subroutines that provide generalized data management capability for FORTRAN programs using a direct access file. Arrays of integer, real, double precision, and character data may be stored, each logical group of data identified by a unique matrix number. A matrix may be organized and stored as batches to reduce core requirements. Batches may be accessed randomly or sequentially. The file may be checkpointed and retained, allowing for restarts with stored values. The XIO subroutines operate on either IBM 360-370/OS/VS or DEC PDP-11/RSX computing systems.

Roland, D. P.↗
NASA NTRS1983

Computer program for analysis of split-Stirling-cycle cryogenic coolers

A computer program for predicting the detailed thermodynamic performance of split-Stirling-cycle refrigerators has been developed. The mathematical model includes the refrigerator cold head, free-displacer/regenerator, gas transfer line, and provision for modeling a mechanical or thermal compressor. To allow for dynamic processes (such as aerodynamic friction and heat transfer) temperature, pressure, and mass flow rate are varied by sub-dividing the refrigerator into an appropriate number of fluid and structural control volumes. Of special importance to modeling of cryogenic coolers is the inclusion of real gas properties, and allowance for variation of thermo-physical properties such as thermal conductivities, specific heats and viscosities, with temperature and/or pressure. The resulting model, therefore, comprehensively simulates the split-cycle cooler both spatially and temporally by reflecting the effects of dynamic processes and real material properties.

Brown, M. T.↗
NASA NTRS1986

Wide binaries in the direction of Andromeda

A statistically well-defined sample of candidate binary stars with separations that are expected to be mostly in the range 0.01-0.1 pc is presented. The 36 candidate pairs are all brighter than apparent visual magnitude 12; about half of the projected pairs are expected to be physically associated. After the candidates are studied spectroscopically and photometrically to establish which pairs are real binaries and to measure their physical characteristics, the sample can be used to help determine the dependence of number density on semimajor axis for wide binaries, a function that is of considerable theoretical interest.

Bahcall, J. N.↗
NASA NTRS1989

Designing Corrector Optics

Image-spot radii reduced by factors ranging from 5 to 25. Corrector Surface Design Software (CORFIG) calculates optimum figure of corrector surface for optical system based on real ray traces. Generates corrector figure in form of spline data-point table and/or list of polynomial coefficients. Number of spline data points as well as number of coefficients specified by user. Optimizes figure of corrector surface for on-axis images at single wavelength only. CORFIG also significantly improves quality of field images and images formed at wavelengths other than design wavelength. Written completely in VAX FORTRAN.

Dantzler, A.↗
NASA NTRS1991

Autoclass: An automatic classification system

The task of inferring a set of classes and class descriptions most likely to explain a given data set can be placed on a firm theoretical foundation using Bayesian statistics. Within this framework, and using various mathematical and algorithmic approximations, the AutoClass System searches for the most probable classifications, automatically choosing the number of classes and complexity of class descriptions. A simpler version of AutoClass has been applied to many large real data sets, has discovered new independently-verified phenomena, and has been released as a robust software package. Recent extensions allow attributes to be selectively correlated within particular classes, and allow classes to inherit, or share, model parameters through a class hierarchy. The mathematical foundations of AutoClass are summarized.

Stutz, John↗