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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

A Hierarchical VLSM-Based Demand Response Strategy for Coordinative Voltage Control between Transmission and Distribution Systems

This paper presents a two-stage hierarchical voltage-load sensitivity matrix (VLSM)-based demand response (DR) algorithm for regulating the voltage at distribution feeders while fulfilling the transmission system DR requests. This allows distributed energy resources be aggregated to provide transmission-level services without causing operational issues in the distribution grids. At the beginning of each operation interval, a transmission system controller will issue DR commands to distribution system controllers. In the first stage, the distribution system controller uses a VLSM-based dispatch algorithm to dispatch the available DR resources on the distribution feeder with an objective to minimize the total voltage deviations at the lowest cost. Then, power flow studies are conducted assuming that the DR commands have been executed. If voltage violations are detected, a second-stage VLSM-based DR dispatch will be performed to remove those violations. After that, the upper and lower DR limits calculated for the next operation interval are sent back to the transmission system controller so the transmission optimization algorithm can use them as operational constraints to make subsequent decisions. The DR resources include smart photovoltaic (PV) inverters that can curtail real power and provide reactive power support, controllable loads and capacitor banks. In conclusion, the IEEE 123-bus test system with 5-minute PV and load data is used to evaluate the performance of the algorithm. In conclusion, simulation results show that the proposed algorithm can fulfill the transmission-level DR requests while maintaining the voltage in the distribution system within limits.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Whole-tree dormant season nitrogen pools for different species receiving combinations of fertilization and irrigation after one short rotation

Our understanding of the accretion and distribution of tree tissue nitrogen (N) pools across a variety of species and genotypes suitable for short-rotation woody crop (SRWC) production in response to water and N availability remains limited. We measured dormant-season, rotation-length, whole-tree N pools for five tree genotypes from four species (two eastern cottonwood, Populus deltoides Bartr., genotypes; American sycamore, Platanus occidentalis L.; American sweetgum, Liquidambar styraciflua L.; and loblolly pine, Pinus taeda L.) receiving irrigation (I), fertilization (F), their combination (IF), or no resources manipulation (C). Our results demonstrate that foliar nitrogen concentration [N] responded to fertilization but was constrained within genotype-specific ranges and varied temporally. Tree genotypes differed in their composite and component tissue N content (N C ), and these differences mostly reflected tissue mass (i.e., larger components and trees resulted in higher N C ). Resource amendments (I, F, IF) resulted in up to 3.8-fold increases in N C compared with C, which were most pronounced for sycamore and sweetgum with F and IF treatments, respectively. By the end of the rotation, forest stands accumulated 73 to 452 kg N ha –1 in tree tissues with 40 – 78 % distributed aboveground and 22 – 60 % distributed belowground. A critical difference between genotypes was that all hardwoods exhibited larger belowground N distributions than the evergreen conifer. Our results stress the importance of belowground N pools and highlight differences among genotypes. Furthermore, our study underscores valuable information about N pools across genotypes suitable for SRWC production, which can be leveraged to inform fertilization plans and devise sustainable nutrient management as production expands across marginal lands.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Bias Correcting NOAA's High-Resolution Rapid Refresh (HRRR) Wind Resource Data for Grid Integration Applications [Slides]

Many weather years of high-quality wind data are widely accepted in the grid integration community to be important for studying wind energy technical potential, energy system operations, and grid resilience. NREL makes high-quality wind and solar resource data available. NREL's Grid-Atmosphere workshop (March 2024) identified NREL National Solar Radiation Database as widely used in grid integration modeling, but there is less agreement on commonly used wind datasets. One important factor identified by ESIG's 2023 report 'Weather Dataset Needs for Planning and Analyzing Modern Power Systems' for gold standard wind data is regular updates. To address the need for regular updates, NREL's team can now process all currently available and regularly updated High-Resolution Rapid Refresh (HRRR) outputs. HRRR is an hourly-updated operational forecast product produced by the National Oceanic and Atmospheric Administration (NOAA) (Dowell et al., 2022). One barrier to NREL using HRRR is systematic bias and consistency with NREL's existing wind datasets (e.g. WIND Toolkit, 'WTK') across weather years. To address this barrier, we show that the HRRR can be interpolated and bias-corrected to be consistent with NRE's existing datasets. We call the new dataset BC-HRRR (bias-corrected HRRR). As with historical datasets like the WTK, BC-HRRR is intended for use in grid integration modeling (e.g., capacity expansion, production cost, and resource adequacy modeling). BC-HRRR's (2015-present) consistency with WTK (2007-2013) allows NREL to extend internal grid integration tooling with 15+ weather years of wind data with low-overhead extensibility to future years as they are made available by NOAA. The rest of this slide deck documents the BC-HRRR processing methods, validation, and its implications for intended use.

17 WIND ENERGY↗
NASA NTRS2016

Human Exploration System Test-Bed for Integration and Advancement (HESTIA) Support of Future NASA Deep-Space Missions

The Engineering Directorate at the NASA - Johnson Space Center is outfitting a 20-Foot diameter hypobaric chamber in Building 7 to support future deep-space Environmental Control & Life Support System (ECLSS) research as part of the Human Exploration System Test-bed for Integration and Advancement (HESTIA) Project. This human-rated chamber is the only NASA facility that has the unique experience, chamber geometry, infrastructure, and support systems capable of conducting this research. The chamber was used to support Gemini, Apollo, and SkyLab Missions. More recently, it was used to conduct 30-, 60-, and 90-day human ECLSS closed-loop testing in the 1990s to support the International Space Station and life support technology development. NASA studies show that both planetary surface and deep-space transit crew habitats will be 3-4 story cylindrical structures driven by human occupancy volumetric needs and launch vehicle constraints. The HESTIA facility offers a 3-story, 20-foot diameter habitat consistent with the studies' recommendations. HESTIA operations follow stringent processes by a certified test team that including human testing. Project management, analysis, design, acquisition, fabrication, assembly and certification of facility build-ups are available to support this research. HESTIA offers close proximity to key stakeholders including astronauts, Human Research Program (who direct space human research for the agency), Mission Operations, Safety & Mission Assurance, and Engineering Directorate. The HESTIA chamber can operate at reduced pressure and elevated oxygen environments including those proposed for deep-space exploration. Data acquisition, power, fluids and other facility resources are available to support a wide range of research. Recently completed HESTIA research consisted of unmanned testing of ECLSS technologies. Eventually, the HESTIA research will include humans for extended durations at reduced pressure and elevated oxygen to demonstrate very high reliability of critical ECLSS and other technologies.

Marmolejo, Jose↗
DOE OSTI2014

Coupled Physics Environment (CouPE) library - Design, Implementation, and Release

Over several years, high fidelity, validated mono-­physics solvers with proven scalability on peta-­scale architectures have been developed independently. Based on a unified component-­based architecture, these existing codes can be coupled with a unified mesh-­data backplane and a flexible coupling-­strategy-­based driver suite to produce a viable tool for analysts. In this report, we present details on the design decisions and developments on CouPE, an acronym that stands for Coupled Physics Environment that orchestrates a coupled physics solver through the interfaces exposed by MOAB array-­based unstructured mesh, both of which are part of SIGMA (Scalable Interfaces for Geometry and Mesh-­Based Applications) toolkit. The SIGMA toolkit contains libraries that enable scalable geometry and unstructured mesh creation and handling in a memory and computationally efficient implementation. The CouPE version being prepared for a full open-­source release along with updated documentation will contain several useful examples that will enable users to start developing their applications natively using the native MOAB mesh and couple their models to existing physics applications to analyze and solve real world problems of interest. An integrated multi-­physics simulation capability for the design and analysis of current and future nuclear reactor models is also being investigated as part of the NEAMS RPL, to tightly couple neutron transport, thermal-­hydraulics and structural mechanics physics under the SHARP framework. This report summarizes the efforts that have been invested in CouPE to bring together several existing physics applications namely PROTEUS (neutron transport code), Nek5000 (computational fluid-dynamics code) and Diablo (structural mechanics code). The goal of the SHARP framework is to perform fully resolved coupled physics analysis of a reactor on heterogeneous geometry, in order to reduce the overall numerical uncertainty while leveraging available computational resources. The design of CouPE along with motivations that led to implementation choices are also discussed. The first release of the library will be different from the current version of the code that integrates the components in SHARP and explanation on the need for forking the source base will also be provided. Enhancements in the functionality and improved user guides will be available as part of the release. CouPE v0.1 is scheduled for an open-­source release in December 2014 along with SIGMA v1.1 components that provide support for language-agnostic mesh loading, traversal and query interfaces along with scalable solution transfer of fields between different physics codes. The coupling methodology and software interfaces of the library are presented, along with verification studies on two representative fast sodium-­cooled reactor demonstration problems to prove the usability of the CouPE library.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1983

Finite element approximations in transient analysis

Alternative techniques for finite element models for transient analyses are explored, using as an example a pinned-pinned beam. Attention is given to the relationships between desired accuracy and the available computer resources. Stiffness, mass, damping, and loading components approximations are examined with note taken of optimization methods. Generation of regular grid results indicates a linear relationship between the number of elements or degrees of freedom and the number of eigenvalues for a given accuracy. Comparisons of the finite element models in terms of accuracy/element or accuracy/degree of freedom were found to be inaccurate for determining model efficiency. Higher accuracies were available from lumped mass and damping models than assumptions of consistent loading, which was preferred to statically equivalent loading.

Melosh, R. J.↗
DOE OSTI2018

A New Approach for Short-Term Solar Radiation Forecasting Using the Estimation of Cloud Fraction and Cloud Albedo

Solar generation is an increasing part of the energy portfolio in the United States. An accurate forecast of the available solar resource and power is essential to managing the electric grid, market operations, and reducing the cost of solar energy. High-frequency forecasts of solar radiation in intra-hour horizons is important for real-time electric power system energy management, especially at the distribution level. Conventional Numerical Weather Prediction models perform poorly in intra-hour, high-frequency forecasts because of the limits on real-time computing, spatial resolution, and infrequent availability of observations. Although a number of alternative technologies, e.g., time-series analysis and machine learning, have been used to fill this gap, the smart persistence model is among the top-performing models in short-term forecasting and therefore often serves as the baseline to evaluate other forecasting models. Although the smart persistence model often serves as the baseline model in these intra-hour forecasts, obvious uncertainties exist in the current smart persistence model: (1) clear-sky index does not respond to the variation of the solar incident angle when cloud conditions are persistent within the forecast horizon, and (2) cloud coverage is inherently persistent though it is constrained by cloud advection. In this study, we developed a Physics-Based Smart Persistence Model for Intra-Hour Solar Forecasting (PSPI) that integrates cloudy property estimation, a radiative transfer model, and cloud fraction forecasts to improve the performance of the smart persistence model. Compared to the smart persistence model, PSPI does not require additional observations of various atmospheric parameters past global horizontal irradiance, but it is customizable because additional observations, if available, can be ingested to further improve the forecast. Our results show that the PSPI outperforms the persistence and smart persistence model on 5-minute, 15-minute, and 30-minute forecast horizons. The software package of PSPI is flexible to users' needs and provides low computational time to run at site-specific locations across the continental United States.

14 SOLAR ENERGY↗
DOE OSTI2023

Nuclear data resources and initiatives for nuclear astrophysics

Research into the cosmic synthesis of the elements, the evolution and explosion of stars, the nature of the early Universe, and other important topics in nuclear astrophysics are at the forefront of nuclear science. These studies are motivating laboratory measurements and theoretical calculations that, after significant investments, are pushing the boundaries of what is possible. The latest nuclear results, however, must be specially prepared before they can be used to advance our knowledge of the cosmos. This processing requires a set of resources unique to nuclear astrophysics, and an impressive collection of nuclear reaction and nuclear structure datasets, processing codes, thermonuclear reaction rate libraries, and simulation codes and services have been developed for the field. There are, however, some serious challenges to these efforts that will only worsen in the future, making it important to develop strategies and act now to ensure a sustainable future for this work. After detailing the specific data types needed for nuclear astrophysics and the available data resources, the major challenges in this work and their implications are discussed. A set of initiatives are proposed to meet those challenges along with suggested implementations and possible ways that they may advance our understanding of the Universe and strengthen the field of nuclear astrophysics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Reliability Barriers to Enhanced Solar PV Deployment: Selected Research Findings - State Outreach Technical Sessions

This presentation provides summaries of three reports selected from a body of work that examines potential reliability challenges related to planning future power systems with higher solar photovoltaic (PV) penetrations in the western United States. The three topics covered are 1) Power system flexibility requirements and supply; 2) Resource adequacy and the capacity credit of solar; 3) Simulating distributed energy resource responses to transmission system-level faults considering IEEE 1547 performance categories on three major WECC transmission paths. The full reports and related resources are available at the project website, https://www.westernenergyboard.org/western-interstate-energy-board/barrier-mitigation-to-enhanced-distributed-solar-photovoltaic/. This presentation is targeted toward a technical audience. A companion policy presentation provides higher-level summaries of the same material.

distributed energy resource↗
DOE OSTI2021

Reliability Barriers to Enhanced Solar PV Deployment: Selected Research Findings - State Outreach Policy Sessions

This presentation provides high-level summaries of three reports selected from a body of work that examines potential reliability challenges related to planning future power systems with higher solar photovoltaic (PV) penetrations in the western United States. The three topics covered are 1) Power system flexibility requirements and supply; 2) Resource adequacy and the capacity credit of solar; 3) Simulating distributed energy resource responses to transmission system-level faults considering IEEE 1547 performance categories on three major WECC transmission paths. The full reports and related resources are available at the project website, https://www.westernenergyboard.org/western-interstate-energy-board/barrier-mitigation-to-enhanced-distributed-solar-photovoltaic/. This presentation is targeted toward policy decision makers. A companion technical presentation provides more in-depth summaries of the same material.

distributed energy resource↗
DOE OSTI2023

An autoencoder compression approach for accelerating large-scale inverse problems

Abstract Partial differential equation (PDE)-constrained inverse problems are some of the most challenging and computationally demanding problems in computational science today. Fine meshes required to accurately compute the PDE solution introduce an enormous number of parameters and require large-scale computing resources such as more processors and more memory to solve such systems in a reasonable time. For inverse problems constrained by time-dependent PDEs, the adjoint method often employed to compute gradients and higher order derivatives efficiently requires solving a time-reversed, so-called adjoint PDE that depends on the forward PDE solution at each timestep. This necessitates the storage of a high-dimensional forward solution vector at every timestep. Such a procedure quickly exhausts the available memory resources. Several approaches that trade additional computation for reduced memory footprint have been proposed to mitigate the memory bottleneck, including checkpointing and compression strategies. In this work, we propose a close-to-ideal scalable compression approach using autoencoders to eliminate the need for checkpointing and substantial memory storage, thereby reducing the time-to-solution and memory requirements. We compare our approach with checkpointing and an off-the-shelf compression approach on an earth-scale ill-posed seismic inverse problem. The results verify the expected close-to-ideal speedup for the gradient and Hessian-vector product using the proposed autoencoder compression approach. To highlight the usefulness of the proposed approach, we combine the autoencoder compression with the data-informed active subspace (DIAS) prior showing how the DIAS method can be affordably extended to large-scale problems without the need for checkpointing and large memory.

Mathematics↗
DOE OSTI2020

Solar+ Optimizer: A Model Predictive Control Optimization Platform for Grid Responsive Building Microgrids

With the falling costs of solar arrays and battery storage and reduced reliability of the grid due to natural disasters, small-scale local generation and storage resources are beginning to proliferate. However, very few software options exist for integrated control of building loads, batteries and other distributed energy resources. The available software solutions on the market can force customers to adopt one particular ecosystem of products, thus limiting consumer choice, and are often incapable of operating independently of the grid during blackouts. In this paper, we present the “Solar+ Optimizer” (SPO), a control platform that provides demand flexibility, resiliency and reduced utility bills, built using open-source software. SPO employs Model Predictive Control (MPC) to produce real time optimal control strategies for the building loads and the distributed energy resources on site. SPO is designed to be vendor-agnostic, protocol-independent and resilient to loss of wide-area network connectivity. The software was evaluated in a real convenience store in northern California with on-site solar generation, battery storage and control of HVAC and commercial refrigeration loads. Preliminary tests showed price responsiveness of the building and cost savings of more than 10% in energy costs alone.

14 SOLAR ENERGY↗
DOE OSTI2022

SolarPlus-Optimizer v0.1

With the falling costs of solar arrays and battery storage and reduced reliability of the grid due to natural disasters, small-scale local generation and storage resources are beginning to proliferate. However, very few software options exist for integrated control of building loads, batteries and other distributed energy resources. The available software solutions on the market can force customers to adopt one particular ecosystem of products, thus limiting consumer choice, and are often incapable of operating independently of the grid during blackouts. In this software package, we present the "Solar+ Optimizer" (SPO), a control platform that provides demand flexibility, resiliency and reduced utility bills, built using open-source software. SPO employs Model Predictive Control (MPC) to produce real time optimal control strategies for the building loads and the distributed energy resources on site. SPO is designed to be vendor-agnostic, protocol-independent and resilient to loss of wide-area network connectivity. The software was evaluated in a real convenience store in northern California with on-site solar generation, battery storage and control of HVAC and commercial refrigeration loads. Preliminary tests showed price responsiveness of the building and cost savings of more than 10% in energy costs alone.

Prakash, AnandKrishnan↗
NASA NTRS1997

Massively Parallel and Scalable Implicit Time Integration Algorithms for Structural Dynamics

Explicit codes are often used to simulate the nonlinear dynamics of large-scale structural systems, even for low frequency response, because the storage and CPU requirements entailed by the repeated factorizations traditionally found in implicit codes rapidly overwhelm the available computing resources. With the advent of parallel processing, this trend is accelerating because of the following additional facts: (a) explicit schemes are easier to parallelize than implicit ones, and (b) explicit schemes induce short range interprocessor communications that are relatively inexpensive, while the factorization methods used in most implicit schemes induce long range interprocessor communications that often ruin the sought-after speed-up. However, the time step restriction imposed by the Courant stability condition on all explicit schemes cannot yet be offset by the speed of the currently available parallel hardware. Therefore, it is essential to develop efficient alternatives to direct methods that are also amenable to massively parallel processing because implicit codes using unconditionally stable time-integration algorithms are computationally more efficient when simulating the low-frequency dynamics of aerospace structures.

Farhat, Charbel↗
DOE OSTI2020

Performance analysis of hybrid power configurations: Impact on primary energy intensity, carbon dioxide emissions, and life cycle costs

In this work, utilization of Natural gas and Hydrogen to support current and future building energy needs to offset the total electric demand while improving the grid resiliency and energy efficiency was investigated. Demand side energy management will play an important role in efficiently managing the available energy resources. Performance assessment of different power generation and energy management configurations is presented in this paper. Development of solutions in addressing grid resiliency by providing the ability to design suitable configurations for meeting individual building energy needs is discussed. Primary movers (PM) such as internal combustion engines (ICE) and fuel cells (FC) along with small scale auxiliary renewable energy source such as photovoltaics (PV) were considered. Key attributes of total carbon foot-print, life cycle costs including capital and operational expenditure, electric grid offset or peak shaving capability, thermal energy availability and its further potential to offset total electric demand, and primary energy intensity are analyzed and discussed in detail.

08 HYDROGEN↗
NASA NTRS1992

A Ground-based Search for Lunar Resources Using High-resolution Imaging in the Infrared

When humans return to the Moon, lunar resources will play an important role in the successful deployment and maintenance of the lunar base. Previous studies have illustrated the abundance of resource materials available on the surface of the Moon, as well as their ready accessibility. Particularly worth considering are the lunar regional (2,000-30,000 sq km) pyroclastic deposits scattered about the lunar nearside. These 30-50-m-thick deposits are composed of fine-grained unconsolidated titanium- and iron-rich mafic glasses and may be used as bulk feedstock for the beneficiation of oxygen, iron, titanium, sulfur, and other solar wind gases, or simply used as is for construction and shielding purposes. A groundbased observing survey of the resource-rich regions on the lunar nearside using a new imaging technique designed to obtain much higher resolution images, and more precise compositional analyses than previously obtainable is proposed.

Coombs, C. R.↗
DOE OSTI2015

Performance of fuel cell for energy supply of passive house

Hydrogen technology and passive house represent two concepts with a remarkable role for the efficiency and decarbonisation of energy systems in the residential buildings area. Through design and functionality, the passive house can make maximum use of all available energy resources. One of the solutions to supply energy of these types of buildings is the fuel cell, using this technology integrated into a system for generating electricity from renewable primary sources, which take the function of backup power (energy reserve) to cover peak load and meteorological intermittents. In this paper is presented the results of the case study that provide an analysis of the energy, environmental and financial performances regarding energy supply of passive house by power generation systems with fuel cell fed with electrolytic hydrogen produced by harnessing renewable energy sources available. Hybrid systems have been configured and operate in various conditions of use for five differentiated locations according to the main areas of solar irradiation from the Romanian map. Global performance of hybrid systems is directly influenced by the availability of renewable primary energy sources - particular geo-climatic characteristics of the building emplacement.

08 HYDROGEN↗
DOE OSTI2022

Nanosecond machine learning regression with deep boosted decision trees in FPGA for high energy physics

We present a novel application of the machine learning / artificial intelligence method called boosted decision trees to estimate physical quantities on field programmable gate arrays (FPGA). The software package fwXmachina features a new architecture called parallel decision paths that allows for deep decision trees with arbitrary number of input variables. It also features a new optimization scheme to use different numbers of bits for each input variable, which produces optimal physics results and ultraefficient FPGA resource utilization. Problems in high energy physics of proton collisions at the Large Hadron Collider (LHC) are considered. Estimation of missing transverse momentum (E T miss ) at the first level trigger system at the High Luminosity LHC (HL-LHC) experiments, with a simplified detector modeled by Delphes, is used to benchmark and characterize the firmware performance. The firmware implementation with a maximum depth of up to 10 using eight input variables of 16-bit precision gives a latency value of $\mathcal{O}$(10) ns, independent of the clock speed, and $\mathcal{O}$(0.1)% of the available FPGA resources without using digital signal processors.

Instruments & Instrumentation↗