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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Assessing wind power operating costs in the United States: Results from a survey of wind industry experts

This paper draws on a survey of wind industry professionals to clarify trends in the operational expenditures (OpEx) of U.S. land-based wind power plants. We find that average all-in lifetime OpEx has declined from approximately $80/kW-yr (~$35/MWh) for projects built in the late 1990s to a level approaching $40/kW-yr (~$11/MWh) for projects built in 2018. Turbine operations and maintenance costs represent the single largest component of overall OpEx and the primary source of cost reductions. We observe wide ranges of OpEx over time; respondents cite a range in average expected costs for recently commissioned projects from $33/kW-yr to $59/kW-yr. We also use historical OpEx learning rates, showing a 9% OpEx reduction for each doubling of global wind capacity, to project a further $5-$8/kW-yr reduction from 2018 to 2040. These findings suggest that continued OpEx reductions may contribute 10% or more of the expected reductions in land-based wind's levelized cost of energy. Moreover, these estimates understate the importance of OpEx owing to the multiplicative effects through which operational advancements influence not only operations and maintenance costs but also component reliability, performance, and plant-level availability - thereby also affecting levelized costs by enhancing annual energy production and plant lifetimes. Given the limited quantity and comparability of previously available OpEx data, the trends reported here may inform OpEx assumptions used by electric planners, analysts, and modelers. The results may also provide useful benchmarks to the wind industry, helping developers and asset owners compare their expectations with historical experience and other industry projections.

17 WIND ENERGY↗
DOE OSTI2013

Long-Term Instrumentation, Information, and Control Systems (II&C) Modernization Future Vision and Strategy

Life extension beyond 60 years for the U.S operating nuclear fleet requires that instrumentation and control (I&C) systems be upgraded to address aging and reliability concerns. It is impractical for the legacy systems based on 1970’s vintage technology operate over this extended time period. Indeed, utilities have successfully engaged in such replacements when dictated by these operational concerns. However, the replacements have been approached in a like-for-like manner, meaning that they do not take advantage of the inherent capabilities of digital technology to improve business functions. And so, the improvement in I&C system performance has not translated to bottom-line performance improvement for the fleet. Therefore, wide-scale modernization of the legacy I&C systems could prove to be cost-prohibitive unless the technology is implemented in a manner to enable significant business innovation as a means of off-setting the cost of upgrades. A Future Vision of a transformed nuclear plant operating model based on an integrated digital environment has been developed as part of the Advanced Instrumentation, Information, and Control (II&C) research pathway, under the Light Water Reactor (LWR) Sustainability Program. This is a research and development program sponsored by the U.S. Department of Energy (DOE), performed in close collaboration with the nuclear utility industry, to provide the technical foundations for licensing and managing the long-term, safe and economical operation of current nuclear power plants. DOE’s program focus is on longer-term and higher-risk/reward research that contributes to the national policy objectives of energy security and environmental security . The Advanced II&C research pathway is being conducted by the Idaho National Laboratory (INL). The Future Vision is based on a digital architecture that encompasses all aspects of plant operations and support, integrating plant systems, plant work processes, and plant workers in a seamless digital environment to enhance nuclear safety, increase productivity, and improve overall plant performance. The long-term goal is to transform the operating model of the nuclear power plants (NPP)s from one that is highly reliant on a large staff performing mostly manual activities to an operating model based on highly integrated technology with a smaller staff. This digital transformation is critical to addressing an array of issues facing the plants, including aging of legacy analog systems, potential shortage of technical workers, ever-increasing expectations for nuclear safety improvement, and relentless pressure to reduce cost. The Future Vision is based on research is being conducted in the following major areas of plant function: 1. Highly integrated control rooms 2. Highly automated plant 3. Integrated operations 4. Human performance improvement for field workers 5. Outage safety and efficiency. Pilot projects will be conducted in each of these areas as the means for industry to collectively integrate these new technologies into nuclear plant work activities. The pilot projects introduce new digital technologies into the nuclear plant operating environment at host operating plants to demonstrate and validate them for production usage. In turn, the pilot project technologies serve as the stepping stones to the eventual seamless digital environment as described in the Future Vision.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2013

Properties of Cathodoluminescence for Cryogenic Applications of SiO2-based Space Observatory Optics and Coatings

Disordered thin film SiO2SiOx coatings undergoing electron-beam bombardment exhibit cathodoluminescence, which can produce deleterious stray background light in cryogenic space-based astronomical observatories exposed to high-energy electron fluxes from space plasmas. As future observatory missions push the envelope into more extreme environments and more complex and sensitive detection, a fundamental understanding of the dependencies of this cathodoluminescence becomes critical to meet performance objectives of these advanced space-based observatories. Measurements of absolute radiance and emission spectra as functions of incident electron energy, flux, and power typical of space environments are presented for thin (60-200 nm) SiO2SiOx optical coatings on reflective metal substrates over a range of sample temperatures (40-400 K) and emission wavelengths (260-5000 nm). Luminescent intensity and peak wavelengths of four distinct bands were observed in UVVISNIR emission spectra, ranging from 300 nm to 1000 nm. A simple model is proposed that describes the dependence of cathodoluminescence on irradiation time, incident flux and energy, sample thickness, and temperature.

electron-beam bombardment↗
DOE OSTI2018

Verification of Pilger Mill Performance

The Nuclear Technology Research & Development program of the Office of Nuclear Energy has implemented a program to develop an advanced reactor cladding fabrication capability by using the extrusion and pilgering processes. Oxide-dispersion strengthened (ODS) steels are a promising class of advanced materials, but processes need to be developed to produce tubing for these advanced alloys. The Pacific Northwest National Laboratory (PNNL) has converted its rolling mill into a lab-scale pilger mill, which required designing pilger tooling and rolls that contained multiple pilgering grooves and designing a servo-driven feed mechanism. Upon assembling and checking out the system, initial pilgering runs were completed. This report will provide verification of the design and performance of the lab-scale pilger mill.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Optics & Materials Science & Technology (OMST) Organization at LLNL

The Optics and Materials Science & Technology (OMST) organization at Lawrence Livermore National Laboratory (LLNL) supplies optics, recycles optics, and performs the materials science and technology to advance optics and optical materials for high-power and high-energy lasers for a variety of missions. The organization is a core capability at LLNL. We have a strong partnership with many optical fabricators, universities and national laboratories to accomplish our goals. The organization has a long history of performing fundamental optical materials science, developing them into useful technologies, and transferring them into production both on-site and off-site. We are successfully continuing this same strategy today.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Advanced Computing Annual Report 2023

In 2023, advanced computing saw the arrival of Kestrel, the National Renewable Energy Laboratory's (NREL's) newest high-performance computing (HPC) system. Kestrel will accelerate clean energy research at a pace and scale more than five times greater than Eagle, with approximately 44 petaflops of computing power. Kestrel's heterogeneous architecture - which includes both CPU-only and GPU-accelerated nodes - is designed to bring a much greater GPU capacity to EERE workloads compared to Eagle, enabling rapidly advancing applications in artificial intelligence and expanding research in new directions for computing. In Fiscal Year (FY) 2023, 333 projects utilized NREL's HPC system, advancing the U.S. Department of Energy's (DOE's) Office of Energy Efficiency and Renewable Energy (EERE) mission across 13 funding areas. Cross-disciplinary collaboration among researchers yielded more than 800 technical outputs, including 177 peer-reviewed journal articles in FY 2023. All this great work continues to advance the science of energy efficiency and renewable energy. This report highlights research that utilized HPC resources in FY 2023.

advanced computing↗
DOE OSTI2018

Development of Fleet Energy Savings Evaluation Tools for Smart Mobility: Smart Vehicle Energy Technology (SVET) Model for Passenger Fleets and Freight Fleet Level Energy Estimation Tool (FFLEET) for Freight Fleets

As part of the U.S. Department of Energy’s (DOE) Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility Initiative, the Oak Ridge National Laboratory (ORNL) led a study to develop web-based tools intended to enable vehicle fleet operators, including both passenger and freight fleets, to quantify the energy savings achievable by implementing advanced transportation technologies. By developing a profile of a fleet’s existing vehicle inventory and providing data about how and where the vehicles are driven, fuel consumption can be calculated for the entire fleet and users can perform “what if” scenarios to evaluate the energy savings that can be realized when replacing existing vehicles and implementing new technologies.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRSDate not supplied

Physics-Guided Deep Learning for Complex System Health Management and Decision Making

The landscape of complex engineered systems is rapidly evolving, from smart manufacturing facilities to next-generation transportation vehicles. As these systems become increasingly sophisticated and interconnected, the need for advanced health management systems grows ever more critical. These systems must go beyond simple monitoring, actively predicting potential failures before they occur. This paradigm shift from fixed maintenance schedules to condition-based predictions is key to optimizing system performance, enhancing safety, and paving the way for autonomous decision-making across various industries. Whether in industrial processes, energy systems, or advanced transportation, the ability to anticipate and prevent failures is becoming a cornerstone of operational excellence. To accurately predict the future health of any complex system, knowledge of its current health state and future operational conditions is essential. Recent advancements in data-driven algorithms have generated growing interest in artificial intelligence for industrial applications. However, the limitations of pure data-driven methods, particularly in industries where data acquisition is costly and limited, have become apparent. This has led to a focus on blending physics with data-driven algorithms, mitigating the drawbacks of both approaches while emphasizing their respective advantages. This research proposes a novel framework for integrating physics-based performance models with deep learning algorithms for the prognostics of complex safety-critical systems. In this approach, physics-based models serve as a blueprint, capturing fundamental system behaviors, while deep learning algorithms, leveraging real-world sensor data, fill in gaps and identify subtle patterns indicative of potential problems. This hybrid methodology, utilizing techniques such as Physics-Informed Neural Networks (PINNs), offers a powerful solution for predicting system health. By fusing domain knowledge with data-driven insights, this approach promises more accurate, adaptable, and reliable models for health prediction. The resulting framework is versatile, applicable across various sectors including aerospace, manufacturing, and energy systems, ultimately contributing to safer, more efficient operations in our increasingly complex technological landscape.

Diagnostics↗
DOE OSTI2023

Multiphysics simulations of Self-Regulating performance of an optimized molten metal fuel microreactor design

Advanced microreactors are expected to play an indispensable role in reliable energy solutions for civilian/ military applications in off-grid regions and space applications such as power supplies for Lunar and Mars bases. An innovative fast neutron spectrum heat pipe microreactor (HP-MR) concept was recently proposed with two unique features: molten U-Mn fuel and heat pipes as the heat removal mechanism. The microreactor was designed to be self-regulated, solely relying on reactivity feedbacks from fuel temperature. The reactor design has been further optimized to provide sufficient engineering safety margin and effective heat removal. In this study, the self-regulating performance of the optimized molten metal fuel microreactor was investigated by multi-physics simulations (neutronics, heat-transfer and heat pipe modeling) based on the MOOSE MultiApps system. In conclusion, the responses of the reactor to a series of transient scenarios were simulated to demonstrate the exceptional and inherent safety features of the novel microreactor concept.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Seminar 13 - Advanced Methods for Grid Integration of High-Performance Residential Communities

High-performance residential communities such as net-zero energy (NZE) and NZE-ready communities are emerging across the United States as many cities and states have committed to achieve ambitious energy efficiency and renewable energy goals between now and 2050. The achievement of these goals will transform the nation's communities into the holistic paradigms consisting of pervasive solar photovoltaics (PVs) and other renewable distributed energy resources, energy storage and flexible loads. However, integrating residential communities with high PV penetration may bring many challenges to the grid. For example, during many hours of the year, electric power is flowing out of PV-enabled homes and back into the grid. When this happens simultaneously in many nearby homes, distribution feeder voltage can be raised significantly. Intermittent solar power can also cause voltage flickers, leading to potential damages on both distribution feeder and home appliances. Existing solutions, such as PV curtailment, battery storage, and direct load control, are not able to address all the challenges in a cost-effective way. Better understanding is needed on how to deploy rooftop PV, how to predict building loads, and how to coordinate the homes in a community to enhance grid reliability. This seminar consists of four integral presentations that cover different aspects of a solution to these challenges. First, we will present an automated method to identify the best surfaces to deploy PV and size PV according to the PV penetration goals in a community. Second, we will present a streamlined way to create gray-box building models that are suitable for large-scale building-grid co-simulation. Next, we will present a data-driven method to estimate the end-use energy consumption to better coordinate the behind-the-meter resources to reduce utility cost, provide grid services, and improve renewable energy integration. Lastly, we will present a hierarchical control system that integrates the building models and the estimated non-dispatchable loads into the decision-making process to enhance the reliability and resilience of the residential community. Simulation results from an NZE-ready community in Fort Collins, Colorado will be presented in all four presentations and the guidelines on better grid integration of residential communities will be provided.

14 SOLAR ENERGY↗
DOE OSTI2022

Recoil imaging for dark matter, neutrinos, and physics beyond the Standard Model

Recoil imaging entails the detection of spatially resolved ionization tracks generated by particle interactions. This is a highly sought-after capability in many classes of detector, with broad applications across particle and astroparticle physics. However, at low energies, where ionization signatures are small in size, recoil imaging only seems to be a practical goal for micro-pattern gas detectors. This white paper outlines the physics case for recoil imaging, and puts forward a decadal plan to advance towards the directional detection of low-energy recoils with sensitivity and resolution close to fundamental performance limits. The science case covered includes: the discovery of dark matter into the neutrino fog, directional detection of sub-MeV solar neutrinos, the precision study of coherent-elastic neutrino-nucleus scattering, the detection of solar axions, the measurement of the Migdal effect, X-ray polarimetry, and several other applied physics goals. We also outline the R&D programs necessary to test concepts that are crucial to advance detector performance towards their fundamental limit: single primary electron sensitivity with full 3D spatial resolution at the $\sim$100 micron-scale. These advancements include: the use of negative ion drift, electron counting with high-definition electronic readout, time projection chambers with optical readout, and the possibility for nuclear recoil tracking in high-density gases such as argon. We also discuss the readout and electronics systems needed to scale-up such detectors to the ton-scale and beyond.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Renewable Fuels and Lubricants Laboratory (Fact Sheet)

This fact sheet describes the Renewable Fuels and Lubricants (ReFUEL) Laboratory at the U.S. Department of Energy National Renewable Energy Laboratory (NREL) is a state-of-the-art research and testing facility for advanced fuels and vehicles. Research and development aims to improve vehicle efficiency and overcome barriers to the increased use of renewable diesel and other nonpetroleum-based fuels, such as biodiesel and synthetic diesel derived from biomass. The ReFUEL Laboratory features a chassis dynamometer for vehicle performance and emissions research, two engine dynamometer test cells for advanced fuels research, and precise emissions analysis equipment. As a complement to these capabilities, detailed studies of fuel properties, with a focus on ignition quality, are performed at NREL's Fuel Chemistry Laboratory.

09 BIOMASS FUELS↗
DOE OSTI2022

Full-Scale Hydrogen Mitigation Installation and Testing at Nevada Solar One

This project was performed under a Cooperative Research & Development Agreement (CRADA) between the National Renewable Energy Laboratory (NREL) and Acciona Energy USA (AE). The purpose was to advance an NREL TRL 3 technology that was developed during the previous CRADA from completed laboratory testing to full-scale process installation and testing at AE's Nevada Solar One (NSO) power plant. The project's objective was to complete full-scale implementation and performance verification of the NREL hydrogen mitigation technology at the Nevada Solar One (NSO) power plant in Boulder City, Nevada.

08 HYDROGEN↗
DOE OSTI2025

Enhancing The Thermal Resistivity of Rigid Polyisocyanurate Foam Insulation

The development of rigid polyurethane foam insulation has garnered considerable attention because of its promising applications in the buildings and construction industry. Its low thermal conductivity makes it an attractive choice for improving energy performance in buildings. Current Rigid Polyurethane foams have thermal resistivity (R-value/in.) 5.5 to 6.5 h.ft2F/BTU/in.· that could be further improved by diminishing the heat transfer through the foam matrix. Nevertheless, minimizing both conduction (through gas and solid) and radiation simultaneously in porous solids is a significant challenge due to the trade-off between these two mechanisms. This study focuses on improving the R-value of the insulation foams via several strategies: such as type and the amount of the surfactants, blowing agent content and precooling and premixing polyol mixture. These methods optimized thermal properties of the PIR foams, achieving R/in. as high as 8.3. This excellent R/in. is anticipated to be a critical factor in significantly advancing the thermal insulation performance of rigid polyurethane cellular foams, thereby enhancing their efficacy in energy-efficient building applications.

Wanasinghe Mudiyanselage Pahala Gedara, Shiwanka V↗
NASA NTRS2007

Lithium Iron Phosphate Cell Performance Evaluations for Lunar Extravehicular Activities

Lithium-ion battery cells are being evaluated for their ability to provide primary power and energy storage for NASA s future Exploration missions. These missions include the Orion Crew Exploration Vehicle, the Ares Crew Launch Vehicle Upper Stage, Extravehicular Activities (EVA, the advanced space suit), the Lunar Surface Ascent Module (LSAM), and the Lunar Precursor and Robotic Program (LPRP), among others. Each of these missions will have different battery requirements. Some missions may require high specific energy and high energy density, while others may require high specific power, wide operating temperature ranges, or a combination of several of these attributes. EVA is one type of mission that presents particular challenges for today s existing power sources. The Portable Life Support System (PLSS) for the advanced Lunar surface suit will be carried on an astronaut s back during eight hour long sorties, requiring a lightweight power source. Lunar sorties are also expected to occur during varying environmental conditions, requiring a power source that can operate over a wide range of temperatures. Concepts for Lunar EVAs include a primary power source for the PLSS that can recharge rapidly. A power source that can charge quickly could enable a lighter weight system that can be recharged while an astronaut is taking a short break. Preliminary results of Al23 Ml 26650 lithium iron phosphate cell performance evaluations for an advanced Lunar surface space suit application are discussed in this paper. These cells exhibit excellent recharge rate capability, however, their specific energy and energy density is lower than typical lithium-ion cell chemistries. The cells were evaluated for their ability to provide primary power in a lightweight battery system while operating at multiple temperatures.

Reid, Concha↗
DOE OSTI2021

Performance Evaluation of Distributed Energy Resource Management Algorithm in Large Distribution Networks

This paper presents performance evaluation of hierarchical optimization and control for distributed energy resource management system (DERMS) in large distribution networks via an advanced hardware-in-the-loop (HIL) platform. The HIL platform provides realistic testing in a laboratory environment, including the accurate modeling of a full-scale distribution system of 11,000 nodes, the DERMS software controller, and 90 power hardware photovoltaics (PVs) and battery inverters. The applied DERMS algorithm is designed based on a realtime optimal power flow algorithm and implemented with acceleration design that performs fast dispatch of simulated PVs and real physical hardware DER devices every 4 seconds.

DERMS↗
DOE OSTI2018

PIMS: Memristor-Based Processing-in-Memory-and-Storage.

Continued progress in computing has augmented the quest for higher performance with a new quest for higher energy efficiency. This has led to the re-emergence of Processing-In-Memory (PIM) ar- chitectures that offer higher density and performance with some boost in energy efficiency. Past PIM work either integrated a standard CPU with a conventional DRAM to improve the CPU- memory link, or used a bit-level processor with Single Instruction Multiple Data (SIMD) control, but neither matched the energy consumption of the memory to the computation. We originally proposed to develop a new architecture derived from PIM that more effectively addressed energy efficiency for high performance scientific, data analytics, and neuromorphic applications. We also originally planned to implement a von Neumann architecture with arithmetic/logic units (ALUs) that matched the power consumption of an advanced storage array to maximize energy efficiency. Implementing this architecture in storage was our original idea, since by augmenting storage (in- stead of memory), the system could address both in-memory computation and applications that accessed larger data sets directly from storage, hence Processing-in-Memory-and-Storage (PIMS). However, as our research matured, we discovered several things that changed our original direc- tion, the most important being that a PIM that implements a standard von Neumann-type archi- tecture results in significant energy efficiency improvement, but only about a O(10) performance improvement. In addition to this, the emergence of new memory technologies moved us to propos- ing a non-von Neumann architecture, called Superstrider, implemented not in storage, but in a new DRAM technology called High Bandwidth Memory (HBM). HBM is a stacked DRAM tech- nology that includes a logic layer where an architecture such as Superstrider could potentially be implemented.

97 MATHEMATICS AND COMPUTING↗