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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

The scanning modulation collimator experiment on the HEAO-1

The purpose of this experiment is to localize celestial sources of X-rays to a precision of 5 to 20 arcsec, so that they may be identified with optical or radio counterparts. We also study their angular size and structure, to elucidate the X-ray emission mechanism. Four grids, wound with nickel alloy wires, are aligned to produce a modulated X-ray signal when the spacecraft rotation carries the collimator field of view across an X-ray source. An image dissector star camera and rate integrating gyroscopes are used to deduce the celestial position from which a peak X-ray signal arises. On-orbit performance and thermal stability have been very good. Based on the first six weeks of quick look data, we have the following results: the location of an X-ray burst source within a globular cluster; the location of 4U1608-52, a unique object which shows bursting, transient, and steady X-ray behavior and is also an optical source; the location of the X-ray transient H1705-25, which provided Anglo-Australian astronomers the basis for an optical identification with a nova-like object; the location of the X-ray transient H1743-32 in the galactic center; and a precise measurement of the angular extent of the Crab Nebula.

Schwartz, D. A.↗
DOE OSTI2024

Medium-Duty Delivery Truck Integrated Bidirectional Wireless Power Transfer System With Grid and Stationary Energy Storage System Connectivity

Electric vehicles (EVs) can provide power to the grid or buildings similar to distributed energy resources (DER) for energy balancing applications or optimizing the operation of the microgrids in harmony with the other DER assets. This article presents the operating modes of a bidirectional wireless power transfer (WPT) system designed for a medium-duty package delivery vehicle. The WPT system designed for this study can transfer 20 kW of power across 11 in of air gap using custom-designed double-D (DD) couplers with LCC–LCC tuning networks. The proposed system utilizes a 480-V three-phase grid connection, a plug-in hybrid delivery truck with bidirectional WPT, and a stationary energy storage system (SESS) that can be connected to the primary-side dc link. Due to the differences in primary and secondary dc bus voltages, and considering the voltage of the SESS, asymmetric voltage gains were used in the system. Sensitivity analyses of this system with respect to these voltage levels are presented. Five different operating modes of the grid, SESS, and the EV battery are investigated with experimental results. Control algorithms are described for grid-to-vehicle (G2V) and vehicle-to-grid (V2G) operating modes. A bidirectional WPT system is operated with a power factor of 0.99 on the grid side in every operating mode. The EV battery was charged with 20.3 kW with an overall efficiency of 93.02% in the G2V operating mode. Finally, in the V2G operating mode, the WPT system provided 12.82 kW of power back to the grid with an overall efficiency of 89.08%.

25 ENERGY STORAGE↗
DOE OSTI2025

Final Technical Report of a Feasibility Investigation of a Hydropower Flexibility Upgrade Kit

The project studied the feasibility of a concept for a flexibility upgrade kit called h-Dynamyk to improve the flexibility of U.S. hydropower plants and assessed its potential impact on the U.S. hydropower industry. This concept addresses the growing need for grid flexibility amid rising renewable energy adoption, such as wind and solar, which often introduce intermittency. The upgrade kit is intended to address challenges posed by aging turbine designs in meeting modern grid demands for flexibility services like frequency response, voltage control, spinning reserve, and black-start capabilities. Key features of the h-Dynamyk kit include siphon turbine assemblies, medium-voltage variable frequency drives (VFDs), and smart controls integrated with plant systems to optimize operations and extend equipment life. This nine-month discovery project successfully achieved its objectives by defining a baseline design and performance metrics for the h-Dynamyk flexibility upgrade kit, analyzing this baseline, and incorporating lessons learned from this analysis into a modified set of metrics and recommendations for future design and testing, which were further guided by field site studies.

13 HYDRO ENERGY↗
DOE OSTI2024

Deer Park Energy Center Natural Gas Combined Cycle Carbon Capture System Front-End Engineering Design Study (Final Scientific/Technical Report – Unlimited)

Calpine Texas CCUS Holdings, LLC (Calpine), Shell Catalysts & Technologies (SCT), Technip Energies (TEN), and Sargent & Lundy, LLC (S&L) have conducted a Front-End Engineering Design (FEED) Study to integrate a new carbon capture system at Calpine’s Deer Park Energy Center (DKEC). The DKEC facility is a nominal 1200 MW gas-fired co-generation power plant situated at the Shell Chemical Manufacturing (Shell) Facility located in Deer Park, Texas. Steam is produced for use by the adjacent Shell Chemical Manufacturing Facility as well as by the onsite steam turbine for electrical generation. The power output from DKEC is provided to the Electric Reliability Council of Texas (ERCOT) operated power grid. DKEC provides power to industrial and commercial customers via this interconnection.

03 NATURAL GAS↗
DOE OSTI2024

Hybrid power plant design for low-carbon hydrogen in the United States

In this study, we provide a nationwide techno-economic analysis of clean hydrogen production powered by a hybrid renewable energy plant for over 50,000 locations in the United States. We leverage the open-source Hybrid Optimization Performance Platform (HOPP) tool to simulate the hourly performance of an off-grid wind-solar plant integrated with a 1-GW polymer exchange membrane electrolyzer system. The levelized cost of hydrogen is calculated for varying technology costs, and tax credits to explore cost sensitivities independent of plant design, performance, and site selection. Our findings suggest that strategies for cost reduction include selecting sites with abundant wind resources, complementary wind and solar resources, and optimizing the sizing of wind and solar assets to maximize the hybrid plant capacity factor. These strategies are linked to increased hydrogen production and reduced electrolyzer stack replacements, thereby lowering the overall cost of hydrogen.

08 HYDROGEN↗
NASA NTRS1979

Low-frequency broadband noise generated by a model rotor

Low-frequency broadband noise generated by model rotors is attributed to the interaction of ingested turbulence with the rotor blades. The influence of free-stream turbulence in the low-frequency broadband noise radiation from model rotors has been experimentally investigated. The turbulence was generated in the M.I.T. anechoic wind tunnel facility with the aid of bipolar grids of various sizes. The spectra and the intensity of the low-frequency broadband noise have been studied as a function of parameters which characterize the turbulence and of helicopter performance parameters. The location of the peak intensity was observed to be strongly dependent on the rotor-tip velocity and on the longitudinal integral scale of turbulence. The size scale of turbulence had negligible effect on the intensity of low-frequency broadband noise. The experimental data show good agreement with an ad hoc model based on unsteady aerodynamics.

Aravamudan, K. S.↗
NASA NTRS1993

Navier-Stokes computations on full-span wing-body configuration with oscillating control surfaces

Unsteady Navier-Stokes simulations have been performed for vortical flows over an 'arrow-wing' configuration of a supersonic transport in the transonic regime. Computed steady pressures and integrated force coefficients with and without control surface deflection at a moderate angle of attack are compared with experiment. For unsteady cases, oscillating trailing-edge control surfaces are modeled by using moving grids. Response characteristics between symmetric and anti-symmetric oscillatory motions of the control surfaces on the left and right wings are studied. The anti-symmetric case produces higher lift than the steady case with no deflection, and the unsteady symmetric case produces higher lift than the anti-symmetric case. The detailed analysis of the wake structure revealed a strong interaction between the primary vortex and the wake vortex sheet from the flap region when the flap is deflected up.

Obayashi, Shigeru↗
DOE OSTI2023

Multi-Timescale Integrated Dynamics and Scheduling for Solar (MIDAS-Solar) (Final Technical Report)

Solar photovoltaic (PV) installations have experienced unprecedented growth in the United States. PV will become not only an energy producer but also a necessary provider of ancillary services at multiple timescales. Conventional methods to simulate power systems operations - such as long-term production simulation (which typically considers schedules from hours to minutes by using an optimization framework) and short-term transient studies (which simulate dynamics from seconds to sub-seconds using state variables and differential equations) - are not sufficient for studying the multiple-timescale variation of solar generation and its impact on system reliability. Long-term system economics and short-term system dynamics are highly coupled, particularly when the penetration level of renewable generation is extremely high, because the uncertainty and variability of solar generation will impact both power system steady-state and dynamic performance. This project helps meet and exceed the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Solar Energy Technologies Office goal of systems integration by directly addressing this stability and reliability challenge for power grid planning and operation. We have developed a temporally comprehensive, closed-loop simulation model, named Multi-timescale Integrated Dynamics and Scheduling (MIDAS), that seamlessly simulates power system operations from economic scheduling (day-ahead to hours) to dynamic response analysis (seconds to sub-seconds). For schedules with very high levels of inverter-based resources (IBRs), up to and including 100%, the stability of grid controls has been evaluated through electromagnetic transient (EMT) simulations and power-hardware-in-the-loop (PHIL) simulations of key transient events at key schedule points. Specifically, MIDAS provides: 1) a closed-loop simulation framework for simulating timescales from economic scheduling to dynamic stability analysis; 2) machine learning-based stability assessment; 3) EMT modeling and analysis for large-scale power systems; 4) MIDAS PHIL test bed. We worked with Hawaii Electric Companies to apply the MIDAS study framework to a Maui grid study. The entire island's transmission system was modeled in detail - from a yearly scheduling model, to a second-level frequency dynamic model, down to a sub-second-scale EMT model to address critical stability issues. The project demonstrated how MIDAS can help system planners and operators assess system reliability and stability while the power grid is marching toward a high-renewable, high-IBR future. In this Maui grid study, we found that 100% instantaneous IBR operation is achievable in EMT simulation and PHIL testing, and grid planners and operators might need new analysis/simulation tools to assess grid reliability and stability in the scheduling stage. MIDAS will bring Maui and other systems closer to 100% clean and stable energy futures. (In this study, we examined transient stability. Other topics necessary for 100% IBR operation, such as protection and resource adequacy, were not examined.)

100% Renewables↗
DOE OSTI2023

Continental Scale Hydrostratigraphy: Comparing Geologically Informed Data Products to Analytical Solutions

Abstract This study synthesizes two different methods for estimating hydraulic conductivity (K) at large scales. We derive analytical approaches that estimate K and apply them to the contiguous United States. We then compare these analytical approaches to three‐dimensional, national gridded K data products and three transmissivity (T) data products developed from publicly available sources. We evaluate these data products using multiple approaches: comparing their statistics qualitatively and quantitatively and with hydrologic model simulations. Some of these datasets were used as inputs for an integrated hydrologic model of the Upper Colorado River Basin and the comparison of the results with observations was used to further evaluate the K data products. Simulated average daily streamflow was compared to daily flow data from 10 USGS stream gages in the domain, and annually averaged simulated groundwater depths are compared to observations from nearly 2000 monitoring wells. We find streamflow predictions from analytically informed simulations to be similar in relative bias and Spearman's rho to the geologically informed simulations. R ‐squared values for groundwater depth predictions are close between the best performing analytically and geologically informed simulations at 0.68 and 0.70 respectively, with RMSE values under 10 m. We also show that the analytical approach derived by this study produces estimates of K that are similar in spatial distribution, standard deviation, mean value, and modeling performance to geologically‐informed estimates. The results of this work are used to inform a follow‐on study that tests additional data‐driven approaches in multiple basins within the contiguous United States.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1977

A computer software system for integration and analysis of grid-based remote sensing data with other natural resource data

This report describes a computer-based information system designed to assist in the integration of commonly available spatial data for regional planning and resource analysis. The Resource Analysis Program (RAP) provides a variety of analytical and mapping phases for single factor or multi-factor analyses. The unique analytical and graphic capabilities of RAP are demonstrated with a study conducted in Windsor Township, Eaton County, Michigan. For this study, soil, land cover/use, topographic and geological maps were used as a data base to develop an eleven map portfolio. The major themes of the portfolio are land cover/use, nonpoint water pollution, waste disposal, and ground water recharge.

Tilmann, S. E.↗
DOE OSTI2020

Mathematical Models for Optimization of Grid-Integrated Energy Storage Systems

Energy storage has been proven to yield positive effects on planning, operation and control of electric grids. It has become a crucial task to properly model the energy storage systems (ESS) under the framework of grid optimization on transmission and distribution networks including microgrids. This paper presents a review on mathematical models and test cases of ESSs used for grid optimization studies, where the network constraints of power systems are included. The existing ESS models are mainly classified into two categories – linear and nonlinear models. The two main categories are further divided into several subcategories respectively; such as mixed-integer linear and convex nonlinear sub-categories. Based on the review and discussions, this paper aims at providing suggestions for choosing proper ESS models for specific grid optimization studies considering the chosen power network model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Adaptive Load Shedding for Grid Emergency Control via Deep Reinforcement Learning

Emergency control, typically such as under-voltage load shedding (UVLS), is broadly used to grapple with low voltage and voltage instability issues in real-world power systems under contingencies. However, existing emergency control schemes are rule-based and cannot be adaptively applied to uncertain and floating operating conditions. Here, we propose an adaptive UVLS algorithm for emergency control via deep reinforcement learning (DRL) and expert systems. We first construct dynamic components for picturing the power system operation as the environment. The transient voltage recovery criteria, which poses time-varying requirements to UVLS, is integrated into the states and reward function to advise the learning of deep neural networks. The proposed method has no tuning issue of coefficients in reward functions, and this issue was regarded as a deficiency in the existing DRL-based algorithms. Case studies illustrate that the proposed method outperforms the traditional UVLS relay in both the timeliness and efficacy for emergency control.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Deterministic and Monte Carlo Nuclear Data Adjustment Methods [Slides]

For the Bayesian Monte Carlo methodology, a need to understand convergence of the posterior moments as a function of the number of parameter realizations is required. In high-dimensional systems, it can be very costly to sample entire parameter space and perform functional evaluation for every realization. Bayesian Monte Carlo allows one to relax the GLLS approximations of model linearity and prior/posterior PDF shape. The Bayesian Stochastic Collocation Method is a deterministic approach to “sample” the parameter space. It allows one to relax the GLLS approximations of model linearity and posterior PDF shape. Higher-order posterior moments (i.e., skewness, kurtosis, etc.) can be studied through polynomial expansion. Tensor product quadrature scales poorly and can use sparse grid quadrature methods.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Short-term electricity load forecasting: Application-driven evaluation of machine learning models across spatial and temporal scales

As we transition towards a decarbonized economy, the integration of variable renewable energy resources and new demands (e.g., electric vehicles, heat pumps) into the electricity grid places unprecedented pressure on grid operators to effectively anticipate and manage peak load. In this context, machine learning algorithms are proving to be indispensable for accurate short-term load forecasting, a crucial task to address these challenges. This study benchmarks 6 machine learning algorithms, including three neural networks and three tree-based algorithms, across various levels of spatial aggregation and time horizons (1, 4, 8, 24, and 48 h). The central contribution of this work is the comparison and analysis of load forecasting models not only based on statistical metrics, but also based on a novel error metric, which evaluates the cost implications of forecast errors for power system stakeholders. Results show that tree-based models outperform neural networks, based on statistical metrics, and yield less skewed error distributions for most spatial scales. However, through the lens of the novel error metric, neural networks are the more competitive choice, especially for forecast horizons that exceed 8 h. The study concludes with actionable recommendations to grid operators and highlights the need for the development of error metrics that link forecasting accuracy to operational costs. To promote transparency and open science, the datasets and Python code are open-sourced via a supplementary repository.

Houben, Nikolaus↗
NASA NTRS1993

Two-dimensional CFD modeling of wave rotor flow dynamics

A two-dimensional Navier-Stokes solver developed for detailed study of wave rotor flow dynamics is described. The CFD model is helping characterize important loss mechanisms within the wave rotor. The wave rotor stationary ports and the moving rotor passages are resolved on multiple computational grid blocks. The finite-volume form of the thin-layer Navier-Stokes equations with laminar viscosity are integrated in time using a four-stage Runge-Kutta scheme. The Roe approximate Riemann solution scheme or the computationally less expensive Advection Upstream Splitting Method (AUSM) flux-splitting scheme are used to effect upwind-differencing of the inviscid flux terms, using cell interface primitive variables set by MUSCL-type interpolation. The diffusion terms are central-differenced. The solver is validated using a steady shock/laminar boundary layer interaction problem and an unsteady, inviscid wave rotor passage gradual opening problem. A model inlet port/passage charging problem is simulated and key features of the unsteady wave rotor flow field are identified. Lastly, the medium pressure inlet port and high pressure outlet port portion of the NASA Lewis Research Center experimental divider cycle is simulated and computed results are compared with experimental measurements. The model accurately predicts the wave timing within the rotor passage and the distribution of flow variables in the stationary inlet port region.

Welch, Gerard E.↗
NASA NTRS1994

Two-dimensional CFD modeling of wave rotor flow dynamics

A two-dimensional Navier-Stokes solver developed for detailed study of wave rotor flow dynamics is described. The CFD model is helping characterize important loss mechanisms within the wave rotor. The wave rotor stationary ports and the moving rotor passages are resolved on multiple computational grid blocks. The finite-volume form of the thin-layer Navier-Stokes equations with laminar viscosity are integrated in time using a four-stage Runge-Kutta scheme. Roe's approximate Riemann solution scheme or the computationally less expensive advection upstream splitting method (AUSM) flux-splitting scheme is used to effect upwind-differencing of the inviscid flux terms, using cell interface primitive variables set by MUSCL-type interpolation. The diffusion terms are central-differenced. The solver is validated using a steady shock/laminar boundary layer interaction problem and an unsteady, inviscid wave rotor passage gradual opening problem. A model inlet port/passage charging problem is simulated and key features of the unsteady wave rotor flow field are identified. Lastly, the medium pressure inlet port and high pressure outlet port portion of the NASA Lewis Research Center experimental divider cycle is simulated and computed results are compared with experimental measurements. The model accurately predicts the wave timing within the rotor passages and the distribution of flow variables in the stationary inlet port region.

Welch, Gerard E.↗
NASA NTRS2005

The Closure of the Ocean Mixed Layer Temperature Budget using Level-Coordinate Model Fields

Entrainment is an important element of the mixed layer mass, heat, and temperature budgets. Conventional procedures to estimate entrainment heat advection often do not permit the closure of heat and temperature budgets because of inaccuracies in its formulation. In this study a rigorous approach to evaluate the effect of entrainment using the output of a general circulation model (GCM) that does not have an explicit prognostic mixed layer model is described. The integral elements of the evaluation are 1) the rigorous estimates of the temperature difference between mixed layer water and entrained water at each horizontal grid point, 2) the formulation of the temperature difference such that the budget closes over a volume greater than one horizontal grid point, and 3) the apparent warming of the mixed layer during the mixed layer shoaling to account for the weak vertical temperature gradient within the mixed layer. This evaluation of entrainment heat advection is compared with the estimates by other commonly used ad hoc formulations by applying them in three regions: the north-central Pacific, the Kuroshio Extension, and the Nino-3 areas in the tropical Pacific. In all three areas the imbalance in the mixed layer temperature budget by the ad hoc estimates is significant, reaching a maximum of about 4 K yr(exp -1).

temperature gradient↗