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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Structural and optical properties for typical solid mirror shapes

A method is developed to determine the weight, center of gravity, areal properties, and mass inertial properties for typical mirrors. A number of support conditions were considered to examine optical surface deflections, surface quality, and fundamental natural frequency for single- and double-arch mirror shapes. Structural performance estimates were made with the NASTRAN program, and optical performances were evaluated with the FRINGE program, using an SXA 40-in mirror. To show the behavior of element types from the NASTRAN program, finite element validity and sensitivity studies were performed in optical model applications. Material parameters, contoured back shapes, and support locations are shown to have significant effects on structural and optical performances. Optimal support locations and support points are given. Fundamental natural frequencies for some shapes are found with the closed-form solution. The plate models results may not be acceptable for determining real mirror optical performances.

Cho, Myung K.↗
NASA NTRS1993

Programs To Optimize Simulated Trajectories (POST\6DPOST)

Designed for optimizing simulated trajectories, POST is point mass, three degrees-of-freedom program while extended 6DPOST permits rigid-body six degrees-of-freedom models. Handles sophisticated problems such as ascent, orbital maneuvers, and reentry.

Brauer, Garry L.↗
NASA NTRS1993

Advanced booster guidance studies

This report is a summary of work done under Grant NAG1-946 for the period 19 December 1988 through 15 August 1992. Most of the technical work is described in the paper produced, including the NASA Contractor Report 4393 - 'Optimal Control Problems with Switching Points'. In the following pages we present a list of the papers along with a brief abstract. The technical work during the last months of the grant has not yet been submitted for publication so we present a summary of that work in an Appendix.

Cliff, Eugene M.↗
NASA NTRS2000

Inviscid Design of Hypersonic Wind Tunnel Nozzles for a Real Gas

A straightforward procedure has been developed to quickly determine an inviscid design of a hypersonic wind tunnel nozzle when the test crash is both calorically and thermally imperfect. This real gas procedure divides the nozzle into four distinct parts: subsonic, throat to conical, conical, and turning flow regions. The design process is greatly simplified by treating the imperfect gas effects only in the source flow region. This simplification can be justified for a large class of hypersonic wind tunnel nozzle design problems. The final nozzle design is obtained either by doing a classical boundary layer correction or by using this inviscid design as the starting point for a viscous design optimization based on computational fluid dynamics. An example of a real gas nozzle design is used to illustrate the method. The accuracy of the real gas design procedure is shown to compare favorably with an ideal gas design based on computed flow field solutions.

Korte, J. J.↗
NASA NTRS2000

HTMT-class Latency Tolerant Parallel Architecture for Petaflops Scale Computation

Computational Aero Sciences and other numeric intensive computation disciplines demand computing throughputs substantially greater than the Teraflops scale systems only now becoming available. The related fields of fluids, structures, thermal, combustion, and dynamic controls are among the interdisciplinary areas that in combination with sufficient resolution and advanced adaptive techniques may force performance requirements towards Petaflops. This will be especially true for compute intensive models such as Navier-Stokes are or when such system models are only part of a larger design optimization computation involving many design points. Yet recent experience with conventional MPP configurations comprising commodity processing and memory components has shown that larger scale frequently results in higher programming difficulty and lower system efficiency. While important advances in system software and algorithms techniques have had some impact on efficiency and programmability for certain classes of problems, in general it is unlikely that software alone will resolve the challenges to higher scalability. As in the past, future generations of high-end computers may require a combination of hardware architecture and system software advances to enable efficient operation at a Petaflops level. The NASA led HTMT project has engaged the talents of a broad interdisciplinary team to develop a new strategy in high-end system architecture to deliver petaflops scale computing in the 2004/5 timeframe. The Hybrid-Technology, MultiThreaded parallel computer architecture incorporates several advanced technologies in combination with an innovative dynamic adaptive scheduling mechanism to provide unprecedented performance and efficiency within practical constraints of cost, complexity, and power consumption. The emerging superconductor Rapid Single Flux Quantum electronics can operate at 100 GHz (the record is 770 GHz) and one percent of the power required by convention semiconductor logic. Wave Division Multiplexing optical communications can approach a peak per fiber bandwidth of 1 Tbps and the new Data Vortex network topology employing this technology can connect tens of thousands of ports providing a bi-section bandwidth on the order of a Petabyte per second with latencies well below 100 nanoseconds, even under heavy loads. Processor-in-Memory (PIM) technology combines logic and memory on the same chip exposing the internal bandwidth of the memory row buffers at low latency. And holographic storage photorefractive storage technologies provide high-density memory with access a thousand times faster than conventional disk technologies. Together these technologies enable a new class of shared memory system architecture with a peak performance in the range of a Petaflops but size and power requirements comparable to today's largest Teraflops scale systems. To achieve high-sustained performance, HTMT combines an advanced multithreading processor architecture with a memory-driven coarse-grained latency management strategy called "percolation", yielding high efficiency while reducing the much of the parallel programming burden. This paper will present the basic system architecture characteristics made possible through this series of advanced technologies and then give a detailed description of the new percolation approach to runtime latency management.

Sterling, Thomas↗
NASA NTRS2004

Applications of Response Surface-Based Methods to Noise Analysis in the Conceptual Design of Revolutionary Aircraft

Due to the growing problem of noise in today's air transportation system, there have arisen needs to incorporate noise considerations in the conceptual design of revolutionary aircraft. Through the use of response surfaces, complex noise models may be converted into polynomial equations for rapid and simplified evaluation. This conversion allows many of the commonly used response surface-based trade space exploration methods to be applied to noise analysis. This methodology is demonstrated using a noise model of a notional 300 passenger Blended-Wing-Body (BWB) transport. Response surfaces are created relating source noise levels of the BWB vehicle to its corresponding FAR-36 certification noise levels and the resulting trade space is explored. Methods demonstrated include: single point analysis, parametric study, an optimization technique for inverse analysis, sensitivity studies, and probabilistic analysis. Extended applications of response surface-based methods in noise analysis are also discussed.

Hill, Geoffrey A.↗
NASA NTRSDate not supplied

Thermoradiative Conversion for Space Power Systems

The thermoradiative cell is a new method for converting heat energy to electrical power, first detailed by Strandberg in 2015. The cell is structurally similar to a photovoltaic cell, in that it is a p-n junction semiconductor device, but thermodynamically operates in the reverse direction, converting the thermal dark current into electrical power by utilizing the recombination radiation from thermally-generated electron hole pairs to radiate waste heat to space. This technology may have application for space missions in converting thermal energy produced by a radioisotope source or from a nuclear reactor into power. The power and efficiency can be calculated as a function of bandgap in the detailed-balance case (the Shockley-Queisser limit), in which all of the thermal emissivity of the cell is due to the recombination of thermally generated electron-hole pairs, and all other recombination losses are ignored. The current produced is directly proportional to the recombination radiation, and thus the more thermally generated pairs, the higher the current. The voltage is proportional to the external bias. These two constraints allow optimization of the optimum bias point for maximum power, and allow calculation of the efficiency at maximum power point. Unlike photovoltaic cells, the maximum power operating point is not the same as the maximum efficiency point, and higher efficiency can be achieved at a higher (negative) bias in the ideal case. Incorporating non-ideal losses, however, shifts the maximum efficiency point toward lower bias. Since a thermoradiative cell operates by radiating directly to space, the current produced by a themoradiative cells will increase with the Stefan-Boltzman radiative efficiency; roughly the fourth power of the temperature. Thus, in contrast to a photovoltaic converter, the power produced is highest at high operating temperatures. Likewise, in contrast to conventional thermal conversion, high radiator temperature increases, rather than decreases the efficiency. Thus, the thermoradiative conversion may fill a mission niche in which small radiator size is required. The basic operation will be summarized, applications to space power discussed, and the requirements for further research outlined.

Photovoltaic Cell↗
NASA NTRSDate not supplied

Analysis of Thermoradiative Thermal Energy Conversion

The thermoradiative cell is a new method for converting heat energy to electrical power, first detailed by Strandberg in 2015. The cell is a p-n junction semiconductor device, similar to a photovoltaic cell but thermodynamically operating in the reverse direction, converting the thermal dark current into electrical power while radiating waste heat to space. The power and efficiency can be calculated as a function of bandgap in the Shockley-Queisser detailed-balance limit, in which the thermal emissivity of the cell is due to the recombination of electron-hole pairs, and all other recombination losses are ignored. The current produced is directly proportional to the recombination radiation. The fundamental loss mechanism for the thermoradiative cell is the energy carried by the infrared radiation into space from band-to-band recombination of carriers injected across the junction. In an ideal cell, to maximize the efficiency, the emission energy of these photons would precisely equal the bandgap. This can be achieved, for example, using dielectric filters or meta-material filters to recycle emission at other wavelengths back into the cell. The voltage is proportional to the external bias. These two constraints allow optimization of the optimum bias point for maximum power. Unlike photovoltaic cells, the maximum power operating point is not the same as the maximum efficiency point, and higher efficiency can be achieved at a higher (negative) bias in the ideal case. Incorporating non-ideal losses, however, shifts the maximum efficiency point toward lower bias. Unlike in photovoltaic cells, non-radiative recombination (e.g., Auger losses) will reduce the output current, but will not reduce the conversion efficiency, since the recombination energy is retained in the cell in the form of heat. Since a thermoradiative cell operates by radiating directly to space, the current produced by themoradiative cells will increase as Stefan-Boltzmann radiation; roughly the fourth power of the temperature. Thus, the power produced is highest at high operating temperatures, and, unlike conventional thermal conversion, increasing radiator temperature increases, the efficiency. Thus, the choice of technology will be toward semiconductors resistant to degradation at high temperature.

Thermoradiative↗
DOE OSTI2022

Learning Local Volt/VAR Controllers Toward Efficient Network Operation with Stability Guarantees: Preprint

This paper considers the problem of voltage regulation in distribution network. The primary motivation is to keep voltages within pre-assigned operating limits by commanding the reactive power output of distributed energy resources (DERs) deployed in the grid. We develop a framework for developing local Volt/Var control that comprises of two main steps. In the first, exploiting historical data and for each DER, we learn a function representing desirable equilibrium points for the power network. These points approximate solutions of an Optimal Power Flow problem. In the second, we propose a control scheme for steering the network towards these favorable configurations. Theoretical conditions are derived to formally guarantee the stability of the developed control scheme and numerical simulations illustrate the effectiveness of the proposed approach.

data-driven control↗
DOE OSTI2024

A Bayesian Learning Approach to Wireless Outdoor Heatmap Construction using Deep Gaussian Process

We present a novel Bayesian learning approach to outdoor radio heatmap construction utilizing deep Gaussian process (GP). The proposed approach employs a two-layer hierarchy which consists of two cascaded Gaussian processes that are capable of modeling more complex input-output relations than standard single-layer Gaussian processes. Since deriving the exact model likelihood is challenging, a lower bound is optimized instead so that gradient descent-based methods can be performed to find out the optimal model parameters. Typically, inducing points are used in GPs to facilitate low-rank approximation of covariance (kernel) matrices for computation speedup. However, the inaccuracy induced by inducing points can accumulate when stacking multiple layers of GP which may hinder the performance of deep GP. Moreover, since inducing points need to be learned, having them at all layers of deep GP also incurs computational burden. To overcome the above challenges, in contrast to the canonical deep GP model, we use a modified architecture where a full standard GP resides in the first layer and inducing points are only introduced for the second layer. This modified architecture strikes a balance between model accuracy and training complexity. In the proposed model, the noise parameter of the first GP layer is also eliminated to improve the training efficiency as the noise parameter at the output of the second layer suffices to model the uncertainty in the output. The proposed approach is evaluated on real-world datasets, in the form of location-Received Signal Strength (RSS) pairs, collected from the Platform for Open Wireless Data-driven Experimental Research (POWDER) located at the campus of the University of Utah. Experiment results show that the proposed approach can achieve smaller prediction errors on various training and testing data configurations than DNN-based and GP-based methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Porting the Nonlinear Optimization Library HiOp to Accelerator-Based Hardware Architectures

While interior point method has been the centerpiece of nonlinear programming tools used in science and engineering, its reliance on linear solvers that can tackle sparse symmetric indefinite and highly ill-conditioned problems made it difficult to implement it effectively on hardware accelerators. HiOp optimization package attempts to provide an implementation of the interior point method suitable for hardware accelerators by compressing the original sparse problem to produce an underlying linear problem that is dense and of manageable size. Implementations of dense linear solvers are more mature and utilize hardware accelerators better than their sparse counterparts. There is a number of important domain problems, such as optimal power flow analysis for power grids, where the sparse problem can be effectively compressed and deploying dense linear solver within the interior point method can improve performance. Here we describe a portable implementation of HiOp optimization engine, which uses a linear solver from Magma library and runs entirely on hardware accelerators. To compress the problem, HiOp uses customized mixed dense-sparse linear algebra. All HiOp kernels are implemented using Umpire and RAJA portability libraries. We describe details of the implementation and discuss trade-offs between performance, portability and development cost.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2010

Optimal Low Energy Earth-Moon Transfers

The optimality of a low-energy Earth-Moon transfer is examined for the first time using primer vector theory. An optimal control problem is formed with the following free variables: the location, time, and magnitude of the transfer insertion burn, and the transfer time. A constraint is placed on the initial state of the spacecraft to bind it to a given initial orbit around a first body, and on the final state of the spacecraft to limit its Keplerian energy with respect to a second body. Optimal transfers in the system are shown to meet certain conditions placed on the primer vector and its time derivative. A two point boundary value problem containing these necessary conditions is created for use in targeting optimal transfers. The two point boundary value problem is then applied to the ballistic lunar capture problem, and an optimal trajectory is shown. Additionally, the ballistic lunar capture trajectory is examined to determine whether one or more additional impulses may improve on the cost of the transfer.

Griesemer, Paul Ricord↗
DOE OSTI2025

Semi-analytical covariance matrices for two-point correlation function for DESI 2024 data

We present an optimized way of producing the fast semi-analytical covariance matrices for the Legendre moments of the two-point correlation function, taking into account survey geometry and mimicking the non-Gaussian effects. We validate the approach on simulated (mock) catalogs for different galaxy types, representative of the Dark Energy Spectroscopic Instrument (DESI) Data Release 1, used in 2024 analyses. We find only a few percent differences between the mock sample covariance matrix and our results, which can be expected given the approximate nature of the mocks, although we do identify discrepancies between the shot-noise properties of the DESI fiber assignment algorithm and the faster approximation (emulator) used in the mocks. Importantly, we find a close agreement (≤ 8% relative differences) in the projected errorbars for distance scale parameters for the baryon acoustic oscillation measurements. This confirms our method as an attractive alternative to simulation-based covariance matrices, especially for non-standard models or galaxy sample selections, making it particularly relevant to the broad current and future analyses of DESI data.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2017

Improvement of Automated POST Case Success Rate Using Support Vector Machines

During early conceptual design of complex systems, concept down selection can have a large impact upon program life-cycle cost. Therefore, any concepts selected during early design will inherently commit program costs and affect the overall probability of program success. For this reason it is important to consider as large a design space as possible in order to better inform the down selection process. For conceptual design of launch vehicles, trajectory analysis and optimization often presents the largest obstacle to evaluating large trade spaces. This is due to the sensitivity of the trajectory discipline to changes in all other aspects of the vehicle design. Small deltas in the performance of other subsystems can result in relatively large fluctuations in the ascent trajectory because the solution space is non-linear and multi-modal [1]. In order to help capture large design spaces for new launch vehicles, the authors have performed previous work seeking to automate the execution of the industry standard tool, Program to Optimize Simulated Trajectories (POST). This work initially focused on implementation of analyst heuristics to enable closure of cases in an automated fashion, with the goal of applying the concepts of design of experiments (DOE) and surrogate modeling to enable near instantaneous throughput of vehicle cases [2]. Additional work was then completed to improve the DOE process by utilizing a graph theory based approach to connect similar design points [3]. The conclusion of the previous work illustrated the utility of the graph theory approach for completing a DOE through POST. However, this approach was still dependent upon the use of random repetitions to generate seed points for the graph. As noted in [3], only 8% of these random repetitions resulted in converged trajectories. This ultimately affects the ability of the random reps method to confidently approach the global optima for a given vehicle case in a reasonable amount of time. With only an 8% pass rate, tens or hundreds of thousands of reps may be needed to be confident that the best repetition is at least close to the global optima. However, typical design study time constraints require that fewer repetitions be attempted, sometimes resulting in seed points that have only a handful of successful completions. If a small number of successful repetitions are used to generate a seed point, the graph method may inherit some inaccuracies as it chains DOE cases from the non-global-optimal seed points. This creates inherent noise in the graph data, which can limit the accuracy of the resulting surrogate models. For this reason, the goal of this work is to improve the seed point generation method and ultimately the accuracy of the resulting POST surrogate model. The work focuses on increasing the case pass rate for seed point generation.

Zwack, Matthew R.↗
NASA NTRS1986

Analysis of the SOR iteration for the 9-point Laplacian

The SOR iteration for solving linear systems of equations depends upon an overrelaxation factor omega. A theory for determining omega was given by Young (1950) for consistently ordered matrices. Here the optimal omega is determined for the 9-point stencil for the model problem of Laplace's equation on a square. Several orderings of the equations are considered, including the natural rowwise and multicolor orderings, all of which lead to non-consistently ordered matrices, and two equivalence classes of orderings are found with different convergence behavior and optimal omega's. The results for the natural rowwise ordering are compared to those of Garabedian (1956) and it is explained why both results are, in a sense, correct, even though they differ. Also analyzed is a pseudo SOR method for the model problem and it is shown that it is not as effective as the SOR methods. Finally, the point SOR methods are compared to known results for line SOR methods for this problem.

Loyce M. Adams↗
NASA NTRS1977

An explicit solution to the exoatmospheric powered flight guidance and trajectory optimization problem for rocket propelled vehicles

A derivation of an explicit solution to the two point boundary-value problem of exoatmospheric guidance and trajectory optimization is presented. Fixed initial conditions and continuous burn, multistage thrusting are assumed. Any number of end conditions from one to six (throttling is required in the case of six) can be satisfied in an explicit and practically optimal manner. The explicit equations converge for off nominal conditions such as engine failure, abort, target switch, etc. The self starting, predictor/corrector solution involves no Newton-Rhapson iterations, numerical integration, or first guess values, and converges rapidly if physically possible. A form of this algorithm has been chosen for onboard guidance, as well as real time and preflight ground targeting and trajectory shaping for the NASA Space Shuttle Program.

Jaggers, R. F.↗
DOE OSTI2023

Parameter Transfer for Quantum Approximate Optimization of Weighted MaxCut

Finding high-quality parameters is a central obstacle to using the quantum approximate optimization algorithm (QAOA). Previous work partially addresses this issue for QAOA on unweighted MaxCut problems by leveraging similarities in the objective landscape among different problem instances. However, we show that the more general weighted MaxCut problem has significantly modified objective landscapes, with a proliferation of poor local optima. Our main contribution is a simple rescaling scheme that overcomes these deleterious effects of weights. Here we show that for a given QAOA depth, a single “typical” vector of QAOA parameters can be successfully transferred to weighted MaxCut instances. This transfer leads to a median decrease in the approximation ratio of only 2.0 percentage points relative to a considerably more expensive direct optimization on a dataset of 34,701 instances with up to 20 nodes and multiple weight distributions. This decrease can be reduced to 1.2 percentage points at the cost of only 10 additional QAOA circuit evaluations with parameters sampled from a pretrained metadistribution, or the transferred parameters can be used as a starting point for a single local optimization run to obtain approximation ratios equivalent to those achieved by exhaustive optimization in 96.35% of our cases.

97 MATHEMATICS AND COMPUTING↗