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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 1,153 records · Page 64

All sources NASA NTRS DOE OSTI

NASA NTRS2008

NASA Tech Briefs, June 2008

Topics covered include: Charge-Control Unit for Testing Lithium-Ion Cells; Measuring Positions of Objects Using Two or More Cameras; Lidar System for Airborne Measurement of Clouds and Aerosols; Radiation-Insensitive Inverse Majority Gates; Reduced-Order Kalman Filtering for Processing Relative Measurements; Spaceborne Processor Array; Instrumentation System Diagnoses a Thermocouple; Chromatic Modulator for a High-Resolution CCD or APS; Commercial Product Activation Using RFID; Cup Cylindrical Waveguide Antenna; Aerobraking Maneuver (ABM) Report Generator; ABM Drag_Pass Report Generator; Transformation of OODT CAS to Perform Larger Tasks; Visualization Component of Vehicle Health Decision Support System; Mars Reconnaissance Orbiter Uplink Analysis Tool; Problem Reporting System; G-Guidance Interface Design for Small Body Mission Simulation; DSN Scheduling Engine; Replacement Sequence of Events Generator; Force-Control Algorithm for Surface Sampling; Tool for Merging Proposals Into DSN Schedules; Micromachined Slits for Imaging Spectrometers; Fabricating Nanodots Using Lift-Off of a Nanopore Template; Making Complex Electrically Conductive Patterns on Cloth; Special Polymer/Carbon Composite Films for Detecting SO2; Nickel-Based Superalloy Resists Embrittlement by Hydrogen; Chemical Passivation of Li+-Conducting Solid Electrolytes; Organic/Inorganic Polymeric Composites for Heat-Transfer Reduction; Composite Cathodes for Dual-Rate Li-Ion Batteries; Improved Descent-Rate Limiting Mechanism; Alignment-Insensitive Lower-Cost Telescope Architecture; Micro-Resistojet for Small Satellites; Using Piezoelectric Devices to Transmit Power through Walls; Miniature Latching Valve; Apparatus for Sampling Surface Contamination; Novel Species of Non-Spore-Forming Bacteria; Chamber for Aerosol Deposition of Bioparticles; Hyperspectral Sun Photometer for Atmospheric Characterization and Vicarious Calibrations; Dynamic Stability and Gravitational Balancing of Multiple Extended Bodies; Simulation of Stochastic Processes by Coupled ODE-PDE; Cluster Inter-Spacecraft Communications; Genetic Algorithm Optimizes Q-LAW Control Parameters; Low-Impact Mating System for Docking Spacecraft; Non-Destructive Evaluation of Materials via Ultraviolet Spectroscopy; Gold-on-Polymer-Based Sensing Films for Detection of Organic and Inorganic Analytes in the Air; and Quantum-Inspired Maximizer.

Source record↗

NASA NTRS2021

Multi-Pass Sequential Mini-Batch Stochastic Gradient Descent Algorithms for Noise Covariance Estimation in Adaptive Kalman Filtering

Estimation of unknown noise covariances in a Kalman filter is a problem of significant practical interest in a wide array of applications. Although this problem has a long history, reliable algorithms for their estimation were scant, and necessary and sufficient conditions for identifiability of the covariances were in dispute until recently. Necessary and sufficient conditions for covariance estimation and a batch estimation algorithm were presented in our previous study. This paper presents stochastic gradient descent algorithms for noise covariance estimation in adaptive Kalman filters that are an order of magnitude faster than the batch method for similar or better root mean square error. More significantly, these algorithms are applicable to non-stationary systems where the noise covariances can occasionally jump up or down by an unknown magnitude. The computational efficiency of the new algorithms stems from adaptive thresholds for convergence, recursive fading memory estimation of the sample cross-correlations of the innovations, and accelerated stochastic gradient descent algorithms. The comparative evaluation of the proposed methods on a number of test cases demonstrates their computational efficiency and accuracy.

Adaptive Kalman filtering↗

DOE OSTI2025

Preserving nonlinear constraints in variational flow filtering data assimilation

Data assimilation aims to estimate the states of a dynamical system by optimally combining sparse and noisy observations of the physical system with uncertain forecasts produced by a computational model. The states of many dynamical systems of interest obey nonlinear physical constraints, and the corresponding dynamics is confined to a certain sub-manifold of the state space. Standard data assimilation techniques applied to such systems yield posterior states lying outside the manifold, violating the physical constraints. This work focuses on particle flow filters which use stochastic differential equations to evolve state samples from a prior distribution to samples from an observation-informed posterior distribution. The variational Fokker-Planck (VFP)—a generic particle flow filtering framework—is extended to incorporate non-linear, equality state constraints in the analysis. To this end, two algorithmic approaches that modify the VFP stochastic differential equation are discussed: (i) VFPSTAB, to inexactly preserve constraints with the addition of a stabilizing drift term, and (ii) VFPDAE, to exactly preserve constraints by treating the VFP dynamics as a stochastic differential-algebraic equation (SDAE). Additionally, an implicit-explicit time integrator is developed to evolve the VFPDAE dynamics. The strength of the proposed approach for constraint preservation in data assimilation is demonstrated on three test problems: the double pendulum, Korteweg-de-Vries, and the incompressible Navier-Stokes equations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Force-Free Identification of Minimum-Energy Pathways and Transition States for Stochastic Electronic Structure Theories

Here, the accurate mapping of potential energy surfaces (PESs) is crucial to our understanding of the numerous physical and chemical processes mediated by atomic rearrangements, such as conformational changes and chemical reactions, and the thermodynamic and kinetic feasibility of these processes. Stochastic electronic structure theories, e.g., Quantum Monte Carlo (QMC) methods, enable highly accurate total energy calculations that in principle can be used to construct the PES. However, their stochastic nature poses a challenge to the computation and use of forces and Hessians, which are typically required in algorithms for minimum-energy pathway (MEP) and transition state (TS) identification, such as the nudged elastic band (NEB) algorithm and its climbing image formulation. Here, we present strategies that utilize the surrogate Hessian line-search method, previously developed for QMC structural optimization, to efficiently identify MEP and TS structures without requiring force calculations at the level of the stochastic electronic structure theory. By modifying the surrogate Hessian algorithm to operate in path-orthogonal subspaces and at saddle points, we show that it is possible to identify MEPs and TSs by using a force-free QMC approach. We demonstrate these strategies via two examples, the inversion of the ammonia (NH 3 ) molecule and the nucleophilic substitution (S N 2) reaction F – + CH 3 F → FCH 3 + F – . We validate our results using Density Functional Theory (DFT)- and Coupled Cluster (CCSD, CCSD(T))-based NEB calculations. We then introduce a hybrid DFT-QMC approach to compute thermodynamic and kinetic quantities, free energy differences, rate constants, and equilibrium constants that incorporates stochastically optimized structures and their energies, and show that this scheme improves upon DFT accuracy. Our methods generalize straightforwardly to other systems and other high-accuracy theories that similarly face challenges computing energy gradients, paving the way for highly accurate PES mapping, transition state determination, and thermodynamic and kinetic calculations at significantly reduced computational expense.

Iyer, Gopal R.↗

DOE OSTI2024

Parallel interior-point solver for block-structured nonlinear programs on SIMD/GPU architectures

Here, we investigate how to port the standard interior-point method to new exascale architectures for block-structured nonlinear programs with state equations. Computationally, we decompose the interior-point algorithm into two successive operations: the evaluation of the derivatives and the solution of the associated Karush-Kuhn-Tucker (KKT) linear system. Our method accelerates both operations using two levels of parallelism. First, we distribute the computations on multiple processes using coarse parallelism. Second, each process uses SIMD/GPU accelerators locally to accelerate the operations using fine-grained parallelism. The KKT system is reduced by eliminating the inequalities and the state variables from the corresponding equations. We demonstrate our method's capability on the supercomputer Polaris, a testbed for the future exascale Aurora system. Each node is equipped with four GPUs, a setup amenable to our two-level approach. Our experiments on the stochastic optimal power flow problem show that the reduction method is 50x faster than the sparse linear solver HSL MA57 running in serial on the CPU, and 6x faster than Pardiso running in parallel on CPU on the same number of processes.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Volt-VAR Optimization in Distribution Networks Using Twin Delayed Deep Reinforcement Learning

Modern distribution grids are undergoing new challenges due to the stochastic nature of distributed energy resources (DERs). High penetration of DERs has a significant impact on Volt-VAR profile and system power losses. This work proposes a deep reinforcement learning (DRL)-based Volt-VAR optimization approach for improving voltage profile and reducing system power loss under high penetration of distributed energy resources, such as battery energy storage and solar photovoltaic units in distribution grids. The twin delayed deep deterministic policy gradient (TD3) method-based DRL agent is proposed to configure optimal set-points of reactive power outputs of fast responding smart inverters. The agent schedules the reactive power of inverters according to their physical capabilities, such as minimum allowed power factor, e.g., 0.9 leading/lagging. The reward function of the proposed DRL scheme is designed carefully to ensure a proper voltage profile of the grids with effective scheduling of reactive power outputs from inverters. The performance of the proposed model is verified on modified IEEE 34- and 123-bus systems and compared with base case with no reactive supply by inverters, and local droop Volt-VAR control approach. The results show that the proposed method performs better than the local droop control and deep deterministic policy gradient (DDPG)-based DRL method for reducing voltage fluctuation and minimizing power loss.

Hossain, Rakib↗

DOE OSTI2023

Mechanisms of Pacific decadal variability in ESMs: the roles of stochastic forcing, feedbacks & external forcing

This project explored how and why climate patterns in the Pacific Ocean—specifically Pacific Decadal Variability (PDV)—change over time, and how well leading Earth System Models (ESMs) capture these changes under different climate scenarios. By analyzing large climate model datasets and running new simulations, the team investigated how ocean and atmosphere processes interact to shape PDV. The study tested a leading scientific hypothesis using both simplified and complex models, helping to uncover the key mechanisms that drive long-term climate swings in the Pacific. This work improves our ability to detect, predict, and understand how human-driven climate change may influence major ocean-climate patterns in the future.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1978

Navigation capability for an ion drive rendezvous with Halley's Comet

Navigation accuracies are presented for a 1985 rendezvous with Halley's Comet using an ion propulsion system. Individual error sources are examined to determine their relative contributions to final delivery errors. The sensitivity of delivery accuracy to stochastic thrust variations is demonstrated by considering a baseline thrust error model and a more benign alternative model. Also studied are the effects of increased comet ephemeris uncertainties and of operational time delays between the orbit determination process and the guidance implementation.

Thornton, C. L.↗

NASA NTRS1979

An 'adding' algorithm for the Markov chain formalism for radiation transfer

An adding algorithm is presented, that extends the Markov chain method and considers a preceding calculation as a single state of a new Markov chain. This method takes advantage of the description of the radiation transport as a stochastic process. Successive application of this procedure makes calculation possible for any optical depth without increasing the size of the linear system used. It is determined that the time required for the algorithm is comparable to that for a doubling calculation for homogeneous atmospheres. For an inhomogeneous atmosphere the new method is considerably faster than the standard adding routine. It is concluded that the algorithm is efficient, accurate, and suitable for smaller computers in calculating the diffuse intensity scattered by an inhomogeneous planetary atmosphere.

Esposito, L. W.↗

NASA NTRS1988

Dual adaptive control: Design principles and applications

The design of an actively adaptive dual controller based on an approximation of the stochastic dynamic programming equation for a multi-step horizon is presented. A dual controller that can enhance identification of the system while controlling it at the same time is derived for multi-dimensional problems. This dual controller uses sensitivity functions of the expected future cost with respect to the parameter uncertainties. A passively adaptive cautious controller and the actively adaptive dual controller are examined. In many instances, the cautious controller is seen to turn off while the latter avoids the turn-off of the control and the slow convergence of the parameter estimates, characteristic of the cautious controller. The algorithms have been applied to a multi-variable static model which represents a simplified linear version of the relationship between the vibration output and the higher harmonic control input for a helicopter. Monte Carlo comparisons based on parametric and nonparametric statistical analysis indicate the superiority of the dual controller over the baseline controller.

Mookerjee, Purusottam↗

NASA NTRS2008

Light Echos in Kerr Geometry: A Source of High Frequency QPOs from Random X-ray Bursts

We propose that high frequency quasi-periodic oscillations (HFQPOs) can be produced from randomly-formed X-ray bursts (flashes) by plasma interior to the ergosphere of a rapidly-rotating black hole. We show by direct computation of their orbits that the photons comprising the observed X-ray light curves, if due to a multitude of such flashes, are affected significantly by the black hole's dragging of inertial frames; the photons of each such burst arrive to an observer at infinity in multiple (double or triple), distinct 'bunches' separated by a roughly constant time lag of t/M approximately equal to 14, regardless of the bursts' azimuthal position. We argue that every other such 'bunch' represents photons that follow trajectories with an additional orbit around the black hole at the photon circular orbit radius (a photon 'echo'). The presence of this constant lag in the response function of the system leads to a QPO feature in its power density spectra, even though the corresponding light curve consists of a totally stochastic signal. This effect is by and large due to the black hole spin and is shown to gradually diminish as the spin parameter a decreases or the radial position of the burst moves outside the static limit surface (ergosphere). Our calculations indicate that for a black hole with Kerr parameter of a/M=0.99 and mass of M=10*Msun the QPO is expected at a frequency of approximately 1.3-1.4 kHz. We discuss the plausibility and observational implications of our model/results as well as its limitations.

Fukumura, K.↗

NASA NTRS2008

Light Echoes in Kerr Geometry: A Source of High Frequency QPOs from Random X-ray Bursts

We propose that high frequency quasi-periodic oscillations (HFQPOs) can be produced from randomly-formed X-ray bursts (flashes) by plasma interior to the ergosphere of a rapidly-rotating black hole. We show by direct computation of their orbits that the photons comprising the observed X-ray light curves, if due to a multitude of such flashes, are affected significantly by the black hole's dragging of inertial frames; the photons of each such burst arrive to an observer at infinity in multiple (double or triple), distinct "bunches" separated by a roughly constant time lag of Deltat(t(sub lag))/M approx. 14, regardless of the bursts' azimuthal position. We argue that every other such "bunch" represents photons that follow trajectories with an additional orbit around the black hole at the photon circular orbit radius (a photon "echo"). The presence of this constant lag in the response function of the system leads to a QPO feature in its power density spectra, even though the corresponding light curve consists of a totally stochastic signal. This effect is by and large due to the black hole spin and is shown to gradually diminish as the spin parameter a decreases or the radial position of the burst moves outside the static limit surface (ergosphere). Our calculations indicate that for a black hole with Kerr parameter of a/M = 0.99 and mass of M = 10Stellar Mass the QPO is expected at a frequency of v(sub QPO) approx. 1.3 - 1.4 kHz. We discuss the plausibility and observational implications of our model/results as well as its limitations. Subject headings: accretion, accretion disks - black hole physics - X-rays: galaxies - stars: oscillations

Fukumura, Keigo↗

NASA NTRS2006

Stochastic Representation of Chaos Using Terminal Attractors

A nonlinear version of the Liouville equation based on terminal attractors is part of a mathematical formalism for describing postinstability motions of dynamical systems characterized by exponential divergences of trajectories leading to chaos (including turbulence as a form of chaos). The formalism can be applied to both conservative systems (e.g., multibody systems in celestial mechanics) and dissipative systems (e.g., viscous fluids). The development of the present formalism was undertaken in an effort to remove positive Lyapunov exponents. The means chosen to accomplish this is coupling of the governing dynamical equations with the corresponding Liouville equation that describes the evolution of the flow of error probability. The underlying idea is to suppress the divergences of different trajectories that correspond to different initial conditions, without affecting a target trajectory, which is one that starts with prescribed initial conditions.

Zak, Michail↗

DOE OSTI2020

System for authenticating an additively manufactured object

A method for authenticating an additively manufactured (AM) object is disclosed herein. A computing device obtains a measurement that is indicative of a stochastic distribution of dopant incorporated into the AM object. The computing device generates authentication data for the AM object based upon the measurement, and authenticates the AM object based upon the authentication data.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Probabilistic Look-ahead Contingency Analysis Integration with Commercial Tool and Practical Data

This paper presents an initial effort of integrating a smart sampling-based probabilistic look-ahead contingency analysis algorithm with General Electric (GE) Grid Solutions’ commercial energy management system (EMS) tool as a proof-of-concept for a seamless research tool integration using real world large-scale grid data. With the increasing impact of random forces such as variable generation and load, their stochastic behaviors cannot be ignored. However, the current practices are still dominated by deterministic tools. They are becoming increasingly inadequate for the future grid. The developed look-ahead contingency analysis algorithm incorporates forecast errors of variable energy and load to address the challenges brought by the increasing uncertainty of power system. The algorithm can reveal the potential violations caused by the variance of variable energy and load that are not normally detected by traditional deterministic approaches. To test its performance under practical environments ( real data with real commercial tool), significant efforts have been made to prepare test cases, modify GE EMS tool, and adapt an extreme value distribution algorithm to analyze the GE EMS’s violation-only outputs. The test results clearly demonstrate the effectiveness of the developed algorithm as new transformer violations that were not previously detected have been identified. This performance provides better situational awareness to engineers for their decision-making process under uncertainty. Moreover, with the discussion of computational performance and future work, this paper has shown a clear path for integrating the probabilistic algorithm with commercial tools to make us better equipped for the changing power system.

Modeling and simulation of power systems, constrai↗

DOE OSTI2022

Generating Sequential PV Deployment Scenarios for High Renewable Distribution Grid Planning: Preprint

This paper introduces a novel approach for generating solar photovoltaic (PV) plant deployment scenarios for grid integration planning. The approach guarantees consistency among scenarios of the same deployment by ensuring that higher penetration scenarios contain PV units deployed in lower penetration scenarios. It also constrains the size and spatial distribution of the PV plants and considers three placement types. A case study on a real-world distribution system proves that the precepts of scenario consistency, deployment diversity, and placement are met. The study further investigates the impact of the resulting scenarios via a stochastic hosting capacity analysis. Results indicate that the ratio between PV and load sizes, referred to as the nodal PV penetration factor (NPPF), is a key driver of the grid integration impact. By reducing the NPPF from 5 to 2, the maximum hosting capacity increased by at least 112%. The study also reveals that scenarios under random placement can lead to higher hosting capacity values.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗

DOE OSTI2022

Generating Sequential PV Deployment Scenarios for High Renewable Distribution Grid Planning

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗

DOE OSTI2022

Tri-level hybrid interval-stochastic optimal scheduling for flexible residential loads under GAN-assisted multiple uncertainties

Various building loads, such as heating, ventilation, and air conditioners (HVACs), electric water heaters (EWHs), and electric vehicles (EVs), can introduce opportunities for improving the flexibility of electricity consumption while satisfying the needs of building owners as well as benefiting the resilience of distribution system. To utilize such flexibility, a tri-level distribution market framework is established, including residential consumers, load aggregators (LAs), and the distribution system operator (DSO). In this work, the uncertainties from all three levels are considered. The random consumption behavior at the consumer level is modeled as a Gaussian noise that is also aggregated and transmitted to the LA level. The weather temperature in the LA level is forecasted as an interval, and the photovoltaic (PV) power in the market-clearing level is modeled by a set of power scenarios generated by Generative Adversarial Networks (GANs). Then, a hybrid interval-stochastic programming is proposed to transform the uncertain problems in the first two levels into deterministic ones. For real-time implementations, a rolling horizon optimization (RHO) scheme is employed to continuously optimize the power consumption based on the latest operating information. Finally, case studies on a modified IEEE 69-bus system validate the effectiveness of the proposed uncertainty modeling strategies and the RHO scheme.

24 POWER TRANSMISSION AND DISTRIBUTION↗