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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Combining cross-pivot flexures to generate improved kinematically equivalent flexure systems

In this work, we show that new kinematic equivalents with improved performance of standard flexure elements can be systematically synthesized by combination of cross-pivot flexures. Cross-pivot flexures provide a unique feature of kinematic stability under both high loading and large displacement conditions which can be exploited to synthesize a range of kinematic equivalents to standard flexure elements which retain much greater stiffness, load capacity and range capacity than the traditional elements. Cross-pivot synthetic elements provide a means to expand the performance of a large range of flexure-based structures including motion stages, manufacturing equipment and optical systems. This could result in better data collection, smaller systems, and less distortion in operation.

42 ENGINEERING↗
DOE OSTI2023

Mechanistic Modeling of Creep and Aging for Time Extrapolation in LPBF 316 SS - LANL

A polycrystal constitutive model was extended to quantify the effects heterogeneity in the microstructure, porosity, and internal stresses on the mechanical response (creep, tensile) of 316H steel processed by additive manufacturing. The starting point is a recently developed and fully calibrated advanced microstructuresensitive mechanistic constitutive model fit to literature data pertaining to conventionally processed steels. The model is embedded within the full field fast Fourier transform framework (LApx) and several hundred simulations were performed. Synthetic microstructures with different grain aspect ratios were generated using the Neper package to study the role of grain morphology on the mechanical responses. The effect of initial cell interior dislocation density, cell-wall density, precipitate content, porosity, and internal stresses on creep rates are quantified for different polycrystalline microstructures. The study allowed to prospectively quantify the role of distinct features of the microstructure on the mechanical response under tension and creep loading scenarios. Critically it is found that minor anisotropies in the tensile response of samples, emanating from the aspect ratio of grains correlated into significant differences in creep rate as a function of loading directions. The study also allows to identify initial microstructure porosities below which the materials response only moderately degraded by the initial microstructure.

36 MATERIALS SCIENCE↗
NASA NTRS1996

Active Sonic Boom Control

A theory and simulation code are developed to study nonsteady sources as means to control sonic booms of supersonic aircraft. A key result is that the source of sonic boom pressure is not confined to the length of the aircraft but occupies an extensive segment of flight path. An aircraft in nonsteady flight functions as a synthetic aperture antenna, generating complex acoustic waves with no simple relation to instantaneous volume or lift distributions. The theory applies linear acoustics to slender nonsteady sources but requires no far field approximation. The solution for pressure contains a term not seen in Whitham's theory for sonic booms of distant supersonic aircraft. The term describes a pressure field that decays algebraically behind the Mach cone and, in the case of steady flight, integrates to a ground load equal to the weight of the aircraft. The algebraic term is separate from those that describe the sonic boom. Two nonsteady source phenomena are evaluated: periodic velocity changes (surge), and periodic longitudinal lift redistribution (slosh). Surge can attenuate a sonic boom and convert it into prolonged weak reverberation, but accelerations needed to produce the phenomenon seem too large for practical use. Slosh may be practical and can alter sonic booms but does not, on the average, result in boom attenuation. The conclusion is that active sonic boom abatement is possible in theory but maybe not practical

Crow, Steven C.↗
DOE OSTI2021

Nominal and adversarial synthetic PMU data for standard IEEE test systems

GridSTAGE (Spatio-Temporal Adversarial scenario GEneration) is a framework for the simulation of adversarial scenarios and the generation of multivariate spatio-temporal data in cyber-physical systems. GridSTAGE is developed based on Matlab and leverages Power System Toolbox (PST) where the evolution of the power network is governed by nonlinear differential equations. Using GridSTAGE, one can create several event scenarios that correspond to several operating states of the power network by enabling or disabling any of the following: faults, AGC control, PSS control, exciter control, load changes, generation changes, and different types of cyber-attacks. Standard IEEE bus system data is used to define the power system environment. GridSTAGE emulates the data from PMU and SCADA sensors. The rate of frequency and location of the sensors can be adjusted as well. Detailed instructions on generating data scenarios with different system topologies, attack characteristics, load characteristics, sensor configuration, control parameters are available in the Github repository - https://github.com/pnnl/GridSTAGE. There is no existing adversarial data-generation framework that can incorporate several attack characteristics and yield adversarial PMU data. The GridSTAGE framework currently supports simulation of False Data Injection attacks (such as a ramp, step, random, trapezoidal, multiplicative, replay, freezing) and Denial of Service attacks (such as time-delay, packet-loss) on PMU data. Furthermore, it supports generating spatio-temporal time-series data corresponding to several random load changes across the network or corresponding to several generation changes. A Koopman mode decomposition (KMD) based algorithm to detect and identify the false data attacks in real-time is proposed in https://ieeexplore.ieee.org/document/9303022. Machine learning-based predictive models are developed to capture the dynamics of the underlying power system with a high level of accuracy under various operating conditions for IEEE 68 bus system. The corresponding machine learning models are available at https://github.com/pnnl/grid_prediction.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Heterogeneous energetic material damage simulator (HEDS): A deep learning approach to simulate damage–sensitivity linkages

Damage in the microstructures of energetic materials (EMs), such as propellants and plastic bonded explosives (PBXs), can significantly alter their response to external loads. Both sensitization and desensitization can occur, causing concerns with safety and performance in the field; predictive models that connect damage and the sensitivity of EMs can enable design and provide confidence in their robustness and reliability. However, modeling of damage evolution is challenging for real microstructures of EMs; samples of damaged EMs are difficult to obtain, thereby hindering experiments and direct numerical simulations to determine the sensitivity of EMs at various stages of damage. Here, we develop an approach to generate synthetic, i.e., in silico produced, damaged microstructures for use in simulations to connect damage levels to sensitivity. The development of the present workflow to generate and impose varying levels of damage in microstructures, known as HEDS (Heterogeneous Energetic Material Damage Simulator), begins with a small set of images of damaged PBXs and combines a collection of deep neural network techniques to generate microstructures with varying levels of damage. By making the synthetic microstructures conform closely to those observed in available real, imaged microstructures, we develop an ensemble of damaged microstructures that can be used for in silico shock experiments. HEDS develops these microstructure ensembles as level set fields, which are directly employed in a sharp interface Eulerian hydrocode where shock simulations are performed to quantify the energy release rate from hotspot fields generated in the microstructure. These capabilities can be useful for the analysis and assessment of changes in the sensitivity of EMs and to design formulations that are less susceptible to damage-induced changes in sensitivity and performance.

Fang, Irene (ORCID:0009000844557122)↗
DOE OSTI2025

PowerModel-AI: A First On-the-Fly Machine-Learning Predictor for AC Power Flow Solutions

The real-time creation of machine-learning models via active or on-the-fly learning has attracted considerable interest across various scientific and engineering disciplines. These algorithms enable machines to build models autonomously while remaining operational. Through a series of query strategies, the machine can evaluate whether newly encountered data fall outside the scope of the existing training set. In this study, we introduce PowerModel-AI, an end-to-end machine learning software designed to accurately predict AC power flow solutions. We present detailed justifications for our model design choices and demonstrate that selecting the right input features effectively captures load flow decoupling inherent in power flow equations. Our approach incorporates on-the-fly learning, where power flow calculations are initiated only when the machine detects a need to improve the dataset in regions where the model’s suboptimal performance is based on specific criteria. Otherwise, the existing model is used for power flow predictions. This study includes analyses of five Texas A&M synthetic power grid cases, encompassing the 14-, 30-, 37-, 200-, and 500-bus systems. The training and test datasets were generated using PowerModels.jl, an open-source power flow solver/optimizer developed at Los Alamos National Laboratory, NM, USA.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

NPP Simulators for Coupled Thermal and Electric Power Dispatch

The Light Water Reactor Sustainability (LWRS) program within the United States Department of Energy supports extending the operation of the U.S. commercial nuclear power plant (NPP) fleet. Within the LWRS program, the Flexible Plant Operation and Generation (FPOG) Pathway works to diversify the revenue streams of light water reactors (LWRs) by opening opportunities for the co-generation of non-electric products in addition to supplying electrical power to the grid. Recent events have added greater motivation to these efforts. For example, the recent Inflation Reduction Act (IRA) passed by the U.S. federal government offers substantial tax incentives for producing clean hydrogen, the technology readiness level of dispatchable and high-efficiency hydrogen production has dramatically increased in a short time, and societal response to world climate change is driving a transition away from fossil fuels. Producing hydrogen with maximum efficiency using nuclear power requires dispatching both electrical and thermal power from the nuclear plant to the hydrogen plant, so testing concepts of operations for combined electrical and thermal power dispatch (TPD) from an NNP to a hydrogen plant is of interest. This report documents achievement of the Light Water Reactor Sustainability (LWRS) program milestone “Install and demonstrate a vendor-developed simulator on the Human Systems Simulation Laboratory (HSS) for dispatch of LWR electrical power to a close-coupled electrolysis plant” with a due date of Dec. 22, 2022. Several factors provide motivation for this effort. Coupling the power generation deck of a nuclear power plant to a hydrogen production facility introduces new possibilities for operational transients that must be addressed. In particular, the performance of the integrated system during startup and shutdown of the hydrogen production facility, as well as offnormal conditions, need to be evaluated to ensure there are no adverse effects on the operation of the existing NPP. The concept of operations involving the NPP, the hydrogen plant, and the electric power grid must be tested using NPP simulators and operating procedures that have been modified for TPD operations. These tests must also include dynamic simulations of the coupled tertiary thermal and electric loads as well as coordinated activities with NPP operators, tertiary load operators and grid power coordinators. The report summarizes progress in developing and testing full-scope NPP simulators at the HSSL, including a generic BWR simulator from GSE Systems, Inc. and generic PWR simulator from Westinghouse. In the case of the TPD-GBWR Simulator from GSE Systems, Inc., a BWR is thermally coupled to a high temperature electrolysis (HTE) plant that produces hydrogen and oxygen from de-ionized water. The hydrogen plant is not explicitly simulated but only included as a transient heat sink. A thermal power dispatch (TPD) system transfers heat between the steam systems at the BWR and the hydrogen plant. Operational results from two versions of the modified simulator are presented. The first version uses synthetic oil as a heat transfer fluid in a closed delivery heat loop (DHL) that generates steam at the hydrogen plant. The second version uses steam as the heat transfer fluid in a delivery steam line (DSL) to provide steam to the hydrogen plant. For both versions, the estimated thermal power delivery distance is approximately one kilometer. The amount of thermal power dispatched in the simulators is 15% of the total reactor thermal power such that the simulators provide a tool to study the feasibility of coupling a BWR to industrial processes that benefit from a combination electrical and thermal power dispatch. Ongoing work within a CRADA is also developing a full-scope PWR simulator provided by Westinghouse for both thermal and electric power coupling. This simulator is based on a PWR plant with two three-loop Westinghouse reactors. Westinghouse PWRs are sufficiently similar that a simulator of a three-loop reactor is an appropriate representation for two-loop and four-loop PWR reactors. The three-loop simulator will initially be modified for close-coupling to a 100 MW HTE hydrogen production plant that will require approximately 25 MW of thermal power while operating at its maximum rated capacity. The simulator testing will include full coupling to dynamic simulations of a hydrogen production plant and a representative bulk electric grid. The simulator provided by Westinghouse is similar to the GPWR simulator that INL has already obtained from GSE Systems but has a few important added benefits. First, the Westinghouse simulator is based on digital controls and has additional screens that can be called up to show parameter trends to assist operators in decision-making. The Westinghouse simulator also has upgrades to the controls and hardware representations, such as valve actuators, that make it more realistic and flexible in terms of accurately sim

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Optimal mitigation and control over power system dynamics for stochastic grid resilience

Optimal mitigation planning for highly disruptive contingencies to a transmission-level power system requires optimization with dynamic power system constraints, due to the key role of dynamics in system stability to major perturbations. We formulate a generalized disjunctive program to determine optimal grid component hardening choices for protecting against major failures, with differential algebraic constraints representing system dynamics (specifically, differential equations representing generator and load behavior and algebraic equations representing instantaneous power balance over the transmission system). We optionally allow stochastic optimal pre-positioning across all considered failure scenarios, and optimal emergency control within each scenario. This novel formulation allows, for the first time, analyzing the resilience interdependencies of mitigation planning, preventive control, and emergency control. Using all three strategies in concert is particularly effective at maintaining robust power system operation under severe contingencies, as we demonstrate on the western system coordinating council 9-bus test system using synthetic multi-device outage scenarios.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

A Unified Analytical Method to Quantify Three Types of Fast Frequency Response from Inverter-Based Resources

With more inverter-based resources (IBRs), our power systems have lower frequency nadirs following N-1 contingencies, and undesired under-frequency load shedding (UFLS) can occur. To address this challenge, IBRs can be programmed to provide at least three types of fast frequency response (FFR), e.g., step response, proportional response (P/f droop response), and derivative response (synthetic inertia). However, these heterogeneous FFR challenge the study of power system frequency dynamics. Thus, this paper develops an analytical frequency nadir prediction method that allows for the consideration of all three potential forms of FFR provided by IBRs. The proposed method provides fast and accurate frequency nadir estimation after N-1 generation tripping contingencies. Our method is grounded on the closed-form solution for the frequency nadir, which is solved from the second-order system frequency response model considering the governor dynamics and three types of FFR. The simulation results in the IEEE 39-bus system with different types of FFR demonstrate that the proposed method provides an accurate and fast prediction of the frequency nadir under various disturbances.

fast frequency response↗
DOE OSTI2020

Synthetic residential load models for smart city energy management simulations

The ability to control tens of thousands of residential electricity customers in a coordinated manner has the potential to enact system-wide electric load changes, such as reduce congestion and peak demand, among other benefits. To quantify the potential benefits of demand-side management and other power system simulation studies (e.g. home energy management, large-scale residential demand response), synthetic load datasets that accurately characterize the system load are required. This study designs a combined top-down and bottom-up approach for modelling individual residential customers and their individual electric assets, each possessing their own characteristics, using time-varying queueing models. The aggregation of all customer loads created by the queueing models represents a known city-sized load curve to be used in simulation studies. The three presented residential queueing load models use only publicly available data. An open-source Python tool to allow researchers to generate residential load data for their studies is also provided. The simulation results presented consider the ComEd region (utility company from Chicago, IL) and demonstrate the characteristics of the three proposed residential queueing load models, the impact of the choice of model parameters, and scalability performance of the Python tool.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Dynamics Informed Optimization for Resilient Energy Systems

Optimal mitigation planning for highly disruptive contingencies to a transmission-level power system requires optimization with dynamic power system constraints, due to the key role of dynamics in system stability to major perturbations. We formulate a generalized disjunctive program to determine optimal grid component hardening choices for protecting against major failures, with differential algebraic constraints representing system dynamics (specifically, differential equations representing generator and load behavior and algebraic equations representing instantaneous power balance over the transmission system). We optionally allow stochastic optimal pre-positioning across all considered failure scenarios, and optimal emergency control within each scenario. This novel formulation allows, for the first time, analyzing the resilience interdependencies of mitigation planning, preventive control, and emergency control. Using all three strategies in concert is particularly effective at maintaining robust power system operation under severe contingencies, as we demonstrate on the Western System Coordinating Council (WSCC) 9-bus test system using synthetic multi-device outage scenarios. Towards integrating our modeling framework with real threats and more realistic power systems, we explore applying hybrid dynamics to power systems. Our work is applied to basic RL circuits with the ultimate goal of using the methodology to model protective tripping schemes in the grid. Finally, we survey mitigation techniques for HEMP threats and describe a GIS application developed to create threat scenarios in a grid with geographic detail.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Uncovering the role of boronic acids and boroxines in the catalytic hydroboration of alkenes

The catalytic hydroboration of alkenes with pinacolborane (HBpin) represents a valuable yet challenging transformation in main-group catalysis, furnishing alkyl pinacol boronic esters of broad synthetic utility. In this article, we demonstrate that simple, commercially available aryl and alkyl boronic acids and their corresponding boroxines act as efficient pre-catalysts for the anti-Markovnikov hydroboration of terminal alkenes with HBpin under solvent-free conditions. In particular, 3,4,5-trifluorophenylboronic acid promotes hydroboration at low loadings, displays broad functional-group tolerance, and operates under operationally simple conditions. Detailed 11 B NMR spectroscopic studies reveal that boronic acids and boroxines are not the catalysts themselves, instead they react with HBpin to generate the transient species RBH 2 ·BH 2 R and B 2 H 6 , which serve as catalytically active intermediates. These species rapidly undergo alkene hydroboration followed by transborylation with HBpin to regenerate the catalytically competent hydridoboranes and release the alkyl pinacol boronic ester products. At elevated temperature and in the absence of alkene substrate, B 2 H 6 undergoes thermal fragmentation into the catalytically inactive borane clusters B 5 H 9 and B 10 H 14 . Limitations in the hydroboration of internal alkenes are traced to the formation of sterically congested trialkylboranes that do not undergo transborylation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2007

Estimation of Forest Fuel Load from Radar Remote Sensing

Understanding fire behavior characteristics and planning for fire management require maps showing the distribution of wildfire fuel loads at medium to fine spatial resolution across large landscapes. Radar sensors from airborne or spaceborne platforms have the potential of providing quantitative information about the forest structure and biomass components that can be readily translated to meaningful fuel load estimates for fire management. In this paper, we used multifrequency polarimetric synthetic aperture radar imagery acquired over a large area of the Yellowstone National Park (YNP) by the AIRSAR sensor, to estimate the distribution of forest biomass and canopy fuel loads. Semi-empirical algorithms were developed to estimate crown and stem biomass and three major fuel load parameters, canopy fuel weight, canopy bulk density, and foliage moisture content. These estimates when compared directly to measurements made at plot and stand levels, provided more than 70% accuracy, and when partitioned into fuel load classes, provided more than 85% accuracy. Specifically, the radar generated fuel parameters were in good agreement with the field-based fuel measurements, resulting in coefficients of determination of R(sup 2) = 85 for the canopy fuel weight, R(sup 2)=.84 for canopy bulk density and R(sup 2) = 0.78 for the foliage biomass.

Saatchi, Sassan↗
DOE OSTI2025

Reducing Coke and Increasing Bio-Oil Yield during Catalytic Fast Pyrolysis of Biomass Using Phosphorus-Modified Zeolite Catalysts

Catalytic fast pyrolysis (CFP) is a promising strategy for producing hydrocarbon transportation fuels from biomass feedstocks. However, catalyst development is needed to increase bio-oil yields and enhance process economics. In this work, we demonstrate how post synthetic modification of formed ZSM-5 with phosphorus shifts CFP selectivity from coke and light gases toward the desired bio-oil product. Microscale experiments demonstrated reduced coke production relative to unmodified ZSM-5 and identified an optimal P loading. Extensive catalyst characterization revealed that P interacted with Al sites to reduce the acid site density, with preferential binding to the strongest acid sites. Insights from the microscale experiments were leveraged to produce kilogram quantities of formed P-ZSM-5 for evaluation in a larger semi-integrated process. These experiments generated liters of bio-oil that was hydrotreated and fractionated into gasoline, diesel, and jet cuts. The phosphorus-modified ZSM-5 improved CFP bio-oil yield, resulting in an 11% relative increase in the carbon yield from biomass to aviation fuel and a 14% decrease in the minimum fuel selling price. These results highlight the impact targeted changes in catalyst acidity, achieved by adding 2.5 wt % P, can have on the carbon efficiency and feasibility of fuel production from biomass feedstocks.

09 BIOMASS FUELS↗
DOE OSTI2020

Biomimetic Catalysts Based on Au@ZnO–Graphene Composites for the Generation of Hydrogen by Water Splitting

For some decades, the scientific community has been looking for alternatives to the use of fossil fuels that allow for the planet’s sustainable and environmentally-friendly development. To do this, attempts have been made to mimic some processes that occur in nature, among which the photosystem-II stands out, which allows water splitting operating with different steps to generate oxygen and hydrogen. This research presents promising results using synthetic catalysts, which try to simulate some natural processes, and which are based on Au@ZnO–graphene compounds. These catalysts were prepared by incorporating different amounts of gold nanoparticles (1 wt.%, 3 wt.%, 5 wt.%, 10 wt.%) and graphene (1 wt.%) on the surface of synthesized zinc oxide nanowires (ZnO NWs), and zinc oxide nanoparticles (ZnO NPs), along with a commercial form (commercial ZnO) for comparison purposes. The highest amount of hydrogen (1127 μmol/hg) was reported by ZnO NWs with a gold and graphene loadings of 10 wt.% and 1 wt.%, respectively, under irradiation at 400 nm. Quantities of 759 μmol/hg and 709 μmol/hg were obtained with catalysts based on ZnO NPs and commercial ZnO, respectively. The photocatalytic activity of all composites increased with respect to the bare semiconductors, being 2.5 times higher in ZnO NWs, 8.8 times higher for ZnO NPs, and 7.5 times higher for commercial ZnO. The high photocatalytic activity of the catalysts is attributed, mainly, to the synergism between the different amount of gold and graphene incorporated, and the surface area of the composites.

Machín, Abniel (ORCID:0000000341343344)↗
DOE OSTI2020

Database Management Module Framework for Dynamic Contingency Analysis and Visualization

The Dynamic Contingency Analysis Tool (DCAT) is being developed to mimic the response of generation dynamics, protection, and load components to extreme contingencies in power systems. Currently, DCAT generates a huge data set, with the analysis results stored in multiple subfolders using a great many files in different formats (power flow cases, time series, figures, spreadsheets). To help power system engineers thoroughly understand and analyze system behavior under many scenarios and contingencies, we developed a database management module (DBM) that enables future integration of DCAT with industry-grade Big Data analytical and interactive visualization platforms. In this paper, we demonstrate the DBM framework with interactive analytics and visualization for DCAT on the synthetic South Carolina 500-bus power system model using hurricane contingencies that capture possibilities for an extreme contingency. DCAT’s advanced data management and interactive visualization can help planning engineers to visually explore and analyze system behavior, all in one view.

Cascading, dynamic simulations, database managemen↗
DOE OSTI2021

Final Report for ARPA-E NODES "Real-Time Optimization and Control of Next-Generation Distribution Infrastructure" Project

The project examined next-generation power distribution systems with high levels of power- electronics-interfaced distributed energy resources (DERs) that include: renewable energy systems (RESs), energy-storage devices, electric vehicles, fuel cells, small-scale diesel generators, and controllable loads. The project developed a comprehensive distribution- network management framework that unifies real-time voltage and frequency control with network-wide energy management under an integrated framework. The aim of the project was to: i) systematically optimize network-wide operation and congruently regulate voltages and frequency in the face of high volatility induced by rapidly varying RES and uncontrolled loads; ii) facilitate high renewable integration beyond 50% on an energy basis; iii) meet power-quality requirements and operational constraints; and, iv) respect response, ramp- time, and hold-time requirements for synthetic frequency and regulating reserves via fast- and longer-term dynamic energy management.

24 POWER TRANSMISSION AND DISTRIBUTION↗