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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Modified optimal control pilot model for computer-aided design and analysis

This paper presents the theoretical development of a modified optimal control pilot model based upon the optimal control model (OCM) of the human operator developed by Kleinman, Baron, and Levison. This model is input compatible with the OCM and retains other key aspects of the OCM, such as a linear quadratic solution for the pilot gains with inclusion of control rate in the cost function, a Kalman estimator, and the ability to account for attention allocation and perception threshold effects. An algorithm designed for each implementation in current dynamic systems analysis and design software is presented. Example results based upon the analysis of a tracking task using three basic dynamic systems are compared with measured results and with similar analyses performed with the OCM and two previously proposed simplified optimal pilot models. The pilot frequency responses and error statistics obtained with this modified optimal control model are shown to compare more favorably to the measured experimental results than the other previously proposed simplified models evaluated.

Davidson, John B.↗
NASA NTRS1989

Collisional dynamics of perturbed particle disks in the solar system

Theoretical and computational studies were carried out on galactic and planetary disks. With the goal of addressing important open questions centered on galactic structure, the cloudy interstellar medium, giant molecular clouds, and star formation in galactic disks and the collisional dynamics of perturbed particulate matter in planetary disks, focus was largely on the self-gravitational effects, dissipative effects, and collisional dynamics of cloud-particle disks. N-body, 'cloud-particle' computational algorithms were developed for the purpose of isolating the role of gaseous self gravity from the roles of other dominant physical mechanisms and dynamical processes, e.g. the collisional dynamics and dissipative processes. The efforts focused largely on galactic disks show that observational constraints provide stringent tests of the numerical simulation techniques developed. Self gravitational effects of the galactic interstellar medium's gas clouds are included by means of Fourier Transform technique.

Roberts, William W., Jr.↗
DOE OSTI2021

Adapting Secure MultiParty Computation to Support Machine Learning in Radio Frequency Sensor Networks

In this project we developed and validated algorithms for privacy-preserving linear regression using a new variant of Secure Multiparty Computation (MPC) we call "Hybrid MPC" (hMPC). Our variant is intended to support low-power, unreliable networks of sensors with low-communication, fault-tolerant algorithms. In hMPC we do not share training data, even via secret sharing. Thus, agents are responsible for protecting their own local data. Only the machine learning (ML) model is protected with information-theoretic security guarantees against honest-but-curious agents. There are three primary advantages to this approach: (1) after setup, hMPC supports a communication-efficient matrix multiplication primitive, (2) organizations prevented by policy or technology from sharing any of their data can participate as agents in hMPC, and (3) large numbers of low-power agents can participate in hMPC. We have also created an open-source software library named "Cicada" to support hMPC applications with fault-tolerance. The fault-tolerance is important in our applications because the agents are vulnerable to failure or capture. We have demonstrated this capability at Sandia's Autonomy New Mexico laboratory through a simple machine-learning exercise with Raspberry Pi devices capturing and classifying images while flying on four drones.

42 ENGINEERING↗
NASA NTRS1989

Active microwave classification of sea ice

Radar backscatter studies of Arctic sea ice have been carried out over a number of years with the intent to acquire physical property information through the examination of microwave signatures. The breadth of these studies continues to expand; as an example, measurements are now conducted at frequencies from 500 MHz to about 100 GHz. One of the scientific goals of this work has been to develop an improved outstanding of the scattering processes at play. A second, equally important goal has been to apply the knowledge gained in examining the backscatter response of ice and snow made in conjunction with the detailed scene characterizations, the insight gained through theoretical modeling and parametric study, and the data entered into the radar signature library to develop procedures to convert microwave signal information (available in the very near future) into valuable data products. This should ultimately provide a better understanding of the environment. The author discusses what has been learned through the many efforts associated with the near-surface scatterometer measurement programs and how the knowledge gained is assisting in the development of future sea ice type satellite algorithms. The logic and mechanisms used in discriminating sea ice types are presented.

Onstott, Robert G.↗
NASA NTRS2011

Verification of Small Hole Theory for Application to Wire Chaffing Resulting in Shield Faults

Our work is focused upon developing methods for wire chafe fault detection through the use of reflectometry to assess shield integrity. When shielded electrical aircraft wiring first begins to chafe typically the resulting evidence is small hole(s) in the shielding. We are focused upon developing algorithms and the signal processing necessary to first detect these small holes prior to incurring damage to the inner conductors. Our approach has been to develop a first principles physics model combined with probabilistic inference, and to verify this model with laboratory experiments as well as through simulation. Previously we have presented the electromagnetic small-hole theory and how it might be applied to coaxial cable. In this presentation, we present our efforts to verify this theoretical approach with high-fidelity electromagnetic simulations (COMSOL). Laboratory observations are used to parameterize the computationally efficient theoretical model with probabilistic inference resulting in quantification of hole size and location. Our efforts in characterizing faults in coaxial cable are subsequently leading to fault detection in shielded twisted pair as well as analysis of intermittent faulty connectors using similar techniques.

Schuet, Stefan R.↗
DOE OSTI2025

A Two-Stage Quantum Reinforcement Learning Method for Multi-Objective Transmission Switching

Multi-objective transmission switching (MO-TS) problems involve the strategic reconfiguration of network topology to simultaneously optimize multiple objectives. As the system scale increases, finding feasible solutions becomes increasingly challenging due to the problem's nonlinearity and high computational complexity. To address these challenges, this paper proposes a two-stage quantum reinforcement learning method that leverages potential quantum advantages for MO-TS. In the first stage, candidate switching lines are identified using a graph-theoretical approach to reduce the problem's dimensionality. The second stage introduces a quantum-classical reinforcement learning framework, where a learnable measurement-based CNN-ResVQC architecture is developed to effectively reduce the input dimension for quantum processing, mitigate vanishing gradients, and enhance trainability while improving the quantum circuit's flexibility in modeling complex decision policies for MO-TS. Numerical studies on IEEE 14-bus, 57-bus, and 118-bus systems demonstrate that the proposed algorithm achieves superior training stability and faster convergence with approximately 1% of the network parameters required by classical algorithms, highlighting its effectiveness, efficiency, and scalability. Furthermore, the practicality is validated through its stable convergence under three common quantum noise channels.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Quantum Advantage in Trading: A Game-Theoretic Approach

Quantum games, like quantum algorithms, exploit quantum entanglement to establish strong correlations between strategic player actions. This paper introduces quantum game-theoretic models applied to trading and demonstrates their implementation on an ion-trap quantum computer. The results showcase a quantum advantage, previously known only theoretically, realized as higher-paying market Nash equilibria. This advantage could help uncover alpha in trading strategies, defined as excess returns compared to established benchmarks. These findings suggest that quantum computing could significantly influence the development of financial strategies.

Khan, Faisal Shah [Taqtics LLC, USA, Rethinc. Labs↗
DOE OSTI2021

Effects of as-received defects on ceramic matrix composites properties using high-fidelity microstructures with periodic boundary conditions

The presence of microstructural defects in as-received specimens of ceramic matrix composites (CMCs) significantly influences their constitutive response and damage, highlighting the importance of characterization and quantification of these defects for accurate assessment of damage and failure in the service environment. In a recent effort, the authors developed an algorithm to generate stochastic representative volume elements (SRVEs) of Carbon fiber Silicon-Carbide-Nitride matrix (C/SiNC) CMCs based on extensive multiscale material and defect characterization data. This paper implements this algorithm within a commercial finite element solver with periodic boundary conditions (PBCs) for high-fidelity micromechanics analysis and investigation of macroscopic material behavior of C/SiNC composites. Different loading directions are used to predict the global mechanical properties, and the results are in excellent agreement with theoretical (rule of mixture) predictions. Subsequently, the effects of as-received defects on the global and local responses are investigated. The results show that intratow porosity has pronounced degradation effects on the global elastic properties and results in complex stress localization patterns, which can be attributed to potential damage initiation sites.

Khafagy, Khaled H.↗
NASA NTRS1990

Dynamics of three-dimensional space crane - Motion requirements and computational considerations

Preliminary design requirements for a space crane are surveyed and some theoretical and computational issues that need to be addressed in support of the design activities are identified. Computational experiments conducted so far on rigid space crane models indicate that the sizing of joint actuators and operational constraints can be assessed by quasi-static rigid crane maneuvering simulations. Limited numerical experiments on flexible crane models raise several difficulties in developing control strategies, maneuvering speeds, maximum torque sustainable, and modeling detailed flexibility effects on the tip positioning accuracy. Computational algorithms development that will alleviate some of these difficulties are discussed and illustrated via example test runs.

Park, K. C.↗
NASA NTRS2001

Improving Simulated Annealing by Recasting it as a Non-Cooperative Game

The game-theoretic field of COllective INtelligence (COIN) concerns the design of computer-based players engaged in a non-cooperative game so that as those players pursue their self-interests, a pre-specified global goal for the collective computational system is achieved "as a side-effect". Previous implementations of COIN algorithms have outperformed conventional techniques by up to several orders of magnitude, on domains ranging from telecommunications control to optimization in congestion problems. Recent mathematical developments have revealed that these previously developed game-theory-motivated algorithms were based on only two of the three factors determining performance. Consideration of only the third factor would instead lead to conventional optimization techniques like simulated annealing that have little to do with non-cooperative games. In this paper we present an algorithm based on all three terms at once. This algorithm can be viewed as a way to modify simulated annealing by recasting it as a non-cooperative game, with each variable replaced by a player. This recasting allows us to leverage the intelligent behavior of the individual players to substantially improve the exploration step of the simulated annealing. Experiments are presented demonstrating that this recasting improves simulated annealing by several orders of magnitude for spin glass relaxation and bin-packing.

Wolpert, David↗
DOE OSTI2020

Detection prospects for the second-order weak decays of 124 Xe in multi-tonne xenon time projection chambers

We investigate the detection prospects for two-neutrino and neutrinoless second-order weak decays of 124 Xe – double-electron capture (0/2νECEC), electron capture with positron emission (0/2νECβ + ) and double-positron emission (0/2νβ + β + ) – in multi-tonne xenon time projection chambers. We simulate the decays in a liquid xenon medium and develop a reconstruction algorithm which uses the multi-particle coincidence in these decays to separate signal from background. This is used to compute the expected detection efficiencies as a function of position resolution and energy threshold for planned experiments. In addition, we consider an exhaustive list of possible background sources and find that they are either negligible in rate or can be greatly reduced using our topological reconstruction criteria. In particular, we draw two conclusions: First, with a theoretical half-life of $T^{2νECβ^+}_{1/2}$= (1.7 ± 0.6) ∙10 23 year, the 2νECβ + decay of 124 Xe will likely be detected in upcoming Dark Matter experiments (e.g. XENONnT or LZ), and their major background will be γ-rays from detector construction materials. Second, searches for the 0νECβ + decay mode will likely be background-free, and new parameter space may be within reach. To this end we investigate two different scenarios of existing experimental constraints on the effective neutrino mass. The necessary 500 kg-year exposure of 124 Xe could be achieved by the baseline design of the DARWIN observatory, or by extracting and using the 124 Xe from the tailings of the nEXO experiment. We demonstrate how a combination of 124 Xe results with those from 0νβ - β - searches in 136 Xe could help to identify the neutrinoless decay mechanism.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1990

The mGA1.0: A common LISP implementation of a messy genetic algorithm

Genetic algorithms (GAs) are finding increased application in difficult search, optimization, and machine learning problems in science and engineering. Increasing demands are being placed on algorithm performance, and the remaining challenges of genetic algorithm theory and practice are becoming increasingly unavoidable. Perhaps the most difficult of these challenges is the so-called linkage problem. Messy GAs were created to overcome the linkage problem of simple genetic algorithms by combining variable-length strings, gene expression, messy operators, and a nonhomogeneous phasing of evolutionary processing. Results on a number of difficult deceptive test functions are encouraging with the mGA always finding global optima in a polynomial number of function evaluations. Theoretical and empirical studies are continuing, and a first version of a messy GA is ready for testing by others. A Common LISP implementation called mGA1.0 is documented and related to the basic principles and operators developed by Goldberg et. al. (1989, 1990). Although the code was prepared with care, it is not a general-purpose code, only a research version. Important data structures and global variations are described. Thereafter brief function descriptions are given, and sample input data are presented together with sample program output. A source listing with comments is also included.

Goldberg, David E.↗
NASA NTRS1992

Analysis of whisker-toughened CMC structural components using an interactive reliability model

Realizing wider utilization of ceramic matrix composites (CMC) requires the development of advanced structural analysis technologies. This article focuses on the use of interactive reliability models to predict component probability of failure. The deterministic William-Warnke failure criterion serves as theoretical basis for the reliability model presented here. The model has been implemented into a test-bed software program. This computer program has been coupled to a general-purpose finite element program. A simple structural problem is presented to illustrate the reliability model and the computer algorithm.

Duffy, Stephen F.↗
NASA NTRS1991

Determination of the coronal magnetic field from vector magnetograph data

A new algorithm was developed, tested, and applied to determine coronal magnetic fields above solar active regions. The coronal field above NOAA active region AR5747 was successfully estimated on 20 Oct. 1989 from data taken at the Mees Solar Observatory of the Univ. of Hawaii. It was shown that observational data can be used to obtain realistic estimates of coronal magnetic fields. The model has significantly extended the realism with which the coronal magnetic field can be inferred from observations. The understanding of coronal phenomena will be greatly advanced by a reliable technique, such as the one presented, for deducing the detailed spatial structure of the coronal field. The payoff from major current and proposed NASA observational efforts is heavily dependent on the success with which the coronal field can be inferred from vector magnetograms. In particular, the present inability to reliably obtain the coronal field has been a major obstacle to the theoretical advancement of solar flare theory and prediction. The results have shown that the evolutional algorithm can be used to estimate coronal magnetic fields.

Mikic, Zoran↗
NASA NTRS1985

Glass breaking strength: The role of surface flaws and treatments

Although the intrinsic strength of silicon dioxide glass is of the order of 10 to the 6th power lb/sq in, the practical strength is roughly two orders of magnitude below this theoretical limit, and depends almost entirely on the surface condition of the glass, that is, the number and size of flaws and the residual surface compression (temper) in the glass. Glass parts always fail in tension when these flaws grow under sustained loading to some critical size. Research associated with glass encapsulated crystalline-Si photovoltaic (PV) modules has greatly expanded our knowledge of glass breaking strength and developed sizeable data base for commercially available glass types. A detailed design algorithm is developed for thickness sizing of rectangular glass plates subject to pressure loads. Additional studies examine the strength of glass under impact loading conditions such as that caused by hail. Although the fundamentals of glass breakage are directly applicable to thin film modules, the fracture strength of typical numerical glass must be replaced with data that reflect the high temperature tin oxide processing, laser scribing, and edge processing peculiar to thin film modules. The fundamentals of glass breakage applicable to thin film modules and preliminary fracture strength data for a variety of 1 ft square glass specimens representing preprocessed and post processed sheets from current amorphous-Si module manufacturers are presented.

Moore, D.↗
NASA NTRS2009

A Local Scalable Distributed Expectation Maximization Algorithm for Large Peer-to-Peer Networks

This paper offers a local distributed algorithm for expectation maximization in large peer-to-peer environments. The algorithm can be used for a variety of well-known data mining tasks in a distributed environment such as clustering, anomaly detection, target tracking to name a few. This technology is crucial for many emerging peer-to-peer applications for bioinformatics, astronomy, social networking, sensor networks and web mining. Centralizing all or some of the data for building global models is impractical in such peer-to-peer environments because of the large number of data sources, the asynchronous nature of the peer-to-peer networks, and dynamic nature of the data/network. The distributed algorithm we have developed in this paper is provably-correct i.e. it converges to the same result compared to a similar centralized algorithm and can automatically adapt to changes to the data and the network. We show that the communication overhead of the algorithm is very low due to its local nature. This monitoring algorithm is then used as a feedback loop to sample data from the network and rebuild the model when it is outdated. We present thorough experimental results to verify our theoretical claims.

Bhaduri, Kanishka↗
DOE OSTI2024

Feature selection with distance correlation

Choosing which properties of the data to use as input to multivariate decision algorithms—also known as feature selection—is an important step in solving any problem with machine learning. While there is a clear trend towards training sophisticated deep networks on large numbers of relatively unprocessed inputs (so-called automated feature engineering), for many tasks in physics, sets of theoretically well-motivated and well-understood features already exist. Working with such features can bring many benefits, including greater interpretability, reduced training and run time, and enhanced stability and robustness. We develop a new feature selection method based on distance correlation, and demonstrate its effectiveness on the tasks of boosted top- and W -tagging. Using our method to select features from a set of over 7,000 energy flow polynomials, we show that we can match the performance of much deeper architectures, by using only ten features and two orders-of-magnitude fewer model parameters. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
NASA NTRS2003

Estimation of Instantaneous TOA Albedo at 670 nm over Ice Clouds from POLDER Multidirectional Measurements

An algorithm that determines the 670-nm top-of-atmosphere (TOA) albedo of ice clouds over ocean using Polarization and Directionality of the Earth's Reflectance ( POLDER) multidirectional measurements is developed. A plane-parallel layer of ice cloud with various optical thicknesses and light scattering phase functions is assumed. For simplicity, we use a double Henyey-Greenstein phase function to approximate the volume-averaged phase function of the ice clouds. A multidirectional reflectance best-fit match between theoretical and POLDER reflectances is used to infer effective cloud optical thickness, phase function and TOA albedo. Sensitivity tests show that while the method does not provide accurate independent retrievals of effective cloud optical depth and phase function, TOA albedo retrievals are accurate to within similar to 3% for both a single layer of ice clouds or a multilayer system of ice clouds and water clouds. When the method is applied to POLDER measurements and retrieved albedos are compared with albedos based on empirical angular distribution models (ADMs), zonal albedo differences are generally smaller than similar to 3%. When albedos are compared with those on the POLDER-I ERB and Cloud product, the differences can reach similar to 15% at small solar zenith angles.

Sun, W.↗