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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Model Validation and Demonstration of a Hydrogen Fuel Cell Parcel Delivery Truck

With an emphasis on reducing fossil fuel consumption and emissions, major delivery service corporations have begun deploying and operating Class 6 battery electric delivery vans. Fuel cell hybrid delivery vans offer a zero emissions solution with extended range and route planning flexibility. This paper follows a prior publication [1] on the vehicle modeling and design and presents demonstration data and a validation of the prior modeling and design effort. Here, the validation exercise shows that the modeling tools predict performance and energy efficiency within 5% for most of the routes, while the demonstration data shows that in service operation fuel economy was over 14 km/kg of hydrogen gas. In addition, results from a range test showed the vehicle design and onboard hydrogen storage was able to surpass the design target range of 200 km.

08 HYDROGEN↗
DOE OSTI2022

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

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

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

RAVIS: Resource Forecast and Ramp Visualization for Situational Awareness - An Introduction to the Open-Source Tool and Use Cases

The Resource Forecast and Ramp Visualization for Situational Awareness (RAVIS) is an open-source tool for visualizing variable renewable resource forecasts and ramp alerts for significant up/down ramps in renewable resource and the consequent net-load. The modular dashboard of RAVIS contains configurable panes for viewing- probabilistic time series forecasts, ramp event alerts on the look-ahead timeline, spatially resolved resource sites and forecasts, and system simulation and market clearing data such as transmission lines utilization, nodal prices and available generation flexibility. RAVIS uses a technology suite that is assembled to provide optimum visualization facility while maintaining a wide pool of potential deployment and client environments. The tool is designed to take advantage of web application technologies, open source visualization libraries and tooling. Utilizing this technology will enable deployment in any environment, using any operating system, and is scalable to much higher spatial and temporal scales of visualization. As a prototype of the tool and demonstrating a use case of variable renewable integration, RAVIS currently integrates site-specific solar power forecasts in the California Independent System Operator (CAISO) and Mid-continent ISO (MISO) footprint from the IBM WattSun forecasting platform, and also superimposes market simulation data for CAISO footprint from as in-house NREL market clearing tool. The tool has the ability to alert the viewer for excessive up or down ramps for both individual solar sites as well as regionally aggregated net-load ramps, and alerts can also be qualified with respect to available flexible generation. This report will provide an introduction to the RAVIS tool, and summarize the above mentioned capabilities, typical use cases and possible extensions of the tool. The RAVIS development team believes there are likely to be high economic and reliability benefits of integrating probabilistic forecasts of variable renewables into control center visualizations and improved ramp events situational awareness for system operators and forecasting teams in the ISOs and electric utilities in comparison with their business as usual practices.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2022

“Water–in–Eutectogel” Electrolytes for Quasi–Solid–State Aqueous Lithium–Ion Batteries

The development of high safety lithium-ion batteries (LIBs) is greatly impeded by the flammability and leakage concerns of typical organic solvent-based electrolytes. As one of the alternative classes of electrolytes, hydrogel electrolytes exhibit high safety, high flexibility, low cost, and are benign to the environment. However, the narrow electrochemical stability window (ESW) of typical hydrogel electrolytes restricts the operating voltage of battery cells. Here, a new class of “water-in-eutectogel (WiETG)” electrolyte is reported, fabricated by combining a hydrogel with a “deep eutectic solvent” (LiTFSI in acetamide). The obtained WiETG electrolyte exhibits non-flammability, high ionic conductivity, and a wide ESW. LiMn 2 O 4 ||Li 4 Ti 5 O 12 cells with the WiETG electrolyte exhibit good cycling stability, high flexibility, and high safety. This newly developed WiETG electrolyte not only broadens the ESW of typical hydrogel electrolytes, but also opens a new perspective on future directions and guidance for the design of high safety electrolytes for flexible LIBs and beyond.

25 ENERGY STORAGE↗
DOE OSTI2023

Rethinking the Price Formation Problem–Part 2: Rewarding Flexibility and Managing Price Risk

In this study, part 1 of this two-part paper describes the impact that uncertainty has on the design and analysis of price formation policies in the non-convex auctions conducted by U.S. wholesale electricity market operators. Using first a toy model and then a large-scale test system, Part 2 demonstrates the difference in prices under the idealized benchmark of ex ante convex hull pricing defined in Part 1 versus existing methods, in particular documenting the potential for suppression of volatility and therefore under-compensation of flexibility by existing methods. The examples highlight that inefficient spot price formation can induce inefficient forward commitments of generators, necessitating out-of-market intervention to restore a reliable and efficient operating plan.Given the potential side effects of existing policies for investment and operation, we suggest two elements in a reoriented approach to the price formation problem: first ensuring that prices exhibit full-strength volatility, and second ensuring that risk-averse market participants have sufficient ability to manage this volatility.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Flexible linkages for thermal management at cryogenic temperatures

Cryogenic system design often presents the competing requirements of thermal coupling between components while de-coupling them structurally. Good thermal coupling is necessary for adequate thermal management during cryogenic operation of the system and to reduce the cooldown time from the ambient to cryogenic temperature. Structural de-coupling is essential to reduce thermal stresses during cooldown, mitigate the trasmission of vibration and loads to sensitive and/or fragile components, and compensate for integration misalignments. Flexible thermal links (FTLs) are an essential component of cryogenic systems that provides a balance between thermal coupling and structural isolation.

42 ENGINEERING↗
DOE OSTI2020

RECENT RESULTS AND OPPORTUNITIES AT THE IOTA FACILITY

The Integrable Optics Test Accelerator (IOTA) was recently commissioned as part of the Fermilab Accelerator Science and Technology (FAST) facility. The IOTA ring was briefly operated with electrons at 47 MeV followed by a 6-months run with 100 MeV electrons. The main goal of the first runwas to study beam dynamics in the integrable lattices with elliptical nonlinear magnets and in the quasi-integrable case with profiled octupole channel. The flexibility of the IOTA ring allowed a wide range of complementary studies, such as experiments with a single electron; studies of fluctuations in undulator radiation and operation with low emittance beams. Over the next year the proton injector will be installed and two runs carried out. One run will be dedicated to the refinement of nonlinear experiments and another will be dedicated to the proof-of-principle demonstration of Optical Stochastic Cooling.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Next steps in high-repetition-rate laser development for Thomson scattering

Design of a next generation high-rep-rate laser system is underway, aiming for a maximum rep rate of 100 kHz for 1 ms. This will be a "pulse-burst" laser, which is a type of heat-capacity laser. Heat-capacity laser operation is characterized by a burst of pulses of limited duration, with burst length ≤100 ms and pulse rep rate ≥1 kHz. Waste heat accumulates in the laser rod during the burst. This heat is deposited evenly throughout the rod volume, with very little heat removed during the burst, such that temperature rises evenly across the rod radius. Thus beam distortion due to thermal gradients is small. Heat is removed from the rod after the burst, with typically tens of seconds between bursts. Pulse-burst operation of flashlamp pumped Nd:YAG lasers is a cost-effective route to high-rep-rate capability. Pulse-burst laser systems with "fast burst" rep rates in the range of 10–20 kHz have been built for the Thomson scattering diagnostics on MST, NSTX-U, and LHD. For Thomson scattering diagnostic application, the typical requirements are 1064 nm, 1–2 J/pulse, ≤30 ns FWHM pulse, with a top-hat beam profile. A major requirement for this next generation laser system is flexibility in burst sequence programs, ranging from 1 kHz for 100 ms to 100 kHz for 1 ms, and a variety of scenarios in between so that operation can be tailored to plasma experiment requirements. Flashlamp pumping will be used for this next generation laser because it is inexpensive and flexible. A new switch-regulated flashlamp driver will provide improved flashlamp control at lower cost. Additional design issues such as the optimum flashlamp pumping spectrum and optimum Nd doping will be addressed. The use of commercial off-the-shelf components will be maximized in this laser system so that pulse-burst systems can be developed and built by others for new applications.

47 OTHER INSTRUMENTATION↗
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

Multifunctional Nanofiber Reinforcement for Improved Thermomechanical and Chemical Stability of Perovskite Solar Cells

This project focused on the development of metal halide perovskite-polymeric nanofiber nanocomposites for robust and efficient solar cells. Metal halide perovskite solar cells are a potentially disruptive technology with high efficiencies and low-cost solution processability amenable with roll-to-roll fabrication of flexible devices. However, perovskites exhibit extreme brittleness, high internal film stresses, and chemical instabilities that significantly limit service lifetimes under normal operating conditions. To date, most work addressing these shortcomings has been focused on encapsulating devices between thick layers of rigid materials such as glass, which increases the total weight and cost of devices. Furthermore, these rigid and heavy encapsulants do not translate well to emerging solar markets vital for national security, including integrated mobile power, emergency deployments for disaster relief and military engagement, and lightweight power for space. It is therefore critical to improve the thermomechanical and chemical stability of perovskite devices in a way that is compatible with flexible and lightweight substrates. In this project, we integrated nylon-6,6 nanofibers into MAPbI3 to mechanically reinforce the perovskite, demonstrating films that exhibited fracture energies 5-fold greater than pristine MAPbI3 while also maintaining similar power conversion efficiencies due to beneficial light scattering effects from the polymeric nanofibers. These results required successful development of approaches to control the deposition thickness of nanofiber mats down to 100s of nanometers, and to ensure the polymer nanofibers did not inhibit charge transport to the at the perovskite-transport layer interface.

14 SOLAR ENERGY↗
DOE OSTI2025

Expanding market opportunities: cogeneration strategies for integrated PWR and thermal energy storage systems

We assess the economic viability of nuclear cogeneration by investigating three different modes—fixed dispatch, fully flexible dispatch, and flexible dispatch with minimum heat supply requirements. The analysis focuses on an existing pressurized water reactor (PWR) integrated with thermal energy storage (TES). Heat production costs are estimated under these modes for two U.S. electricity markets: the Electric Reliability Council of Texas (ERCOT) and the Pennsylvania–New Jersey–Maryland Interconnection (PJM). A sensitivity analysis examines profitability at varying heat market prices. Results indicate that fixed heat dispatch inflates heat production costs, often rendering projects economically feasible only at higher heat price levels. Fully-flexible dispatch lowers heat production costs by an average of 43 % compared to fixed dispatch. However, the current 30 % thermal dispatch limit may be insufficient to serve high baseline industrial demands cost‐effectively; higher maximum dispatch rates could enhance project economics. Markets with higher and more volatile electricity prices (e.g., ERCOT) offer greater total energy sales potential (i.e., heat and electricity), but also increase opportunity costs when heat production scheduling restrictions are imposed. In contrast, lower-price, less volatile markets (e.g., PJM) experience smaller impacts from such constraints and provide greater flexibility in accommodating varying cogeneration modes. In conclusion, these findings provide a framework to guide nuclear plant operators in aligning cogeneration strategies with industrial process requirements and electricity market conditions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

STREAM: A technology planning and capacity expansion model for the industrial sector

The Strategic Technology Roadmapping and Energy, Environmental, and Economic Analysis Model—STREAM—is an optimization-based modeling tool and analysis framework to assist with strategic planning and technology investments of the industrial sector. This open-source framework is written in Julia using the JuMP package, which enables users to model future “pathways” for incumbent and future production technologies, costs, fuels and energy carriers, and energy and non-energy environmental impacts from industries as they transform in pursuit of a robust and competitive manufacturing sector. The model starts with an initial stock of industrial production technologies and assets at a facility level and then determines pathways that minimize cost, subject to an array of possible constraints on demand, market shares, environmental flows, and other exogenously specified operational considerations such as capacity utilization rates or regional energy costs. Key features of the framework include flexibility to model a wide range of industries and industrial technologies/processes at varying levels of granularity, ability to perform parametric sensitivity analyses, and ability to visualize model results using visualization objects.

capacity expansion↗
DOE OSTI2024

Exploring mounting solutions for cryogenically cooled thin crystal optics in high power density x-ray free electron lasers

This study investigates three mounting methods—clamping, soldering, and a hybrid clamping–soldering approach—for cryogenically cooled thin diamond crystals crucial to stable operation of X-ray Free Electron Laser (XFEL) systems. While clamping methods exhibit temperature resilience and flexibility, meticulous design is required to prevent stress-induced warping and reduce thermal contact area. Soldering methods offer reliable mechanical and thermal bonding but encounter challenges due to the coefficient of thermal expansion mismatch at cryogenic temperatures. The hybrid method, integrating clamping and soldering with strain relief cuts, effectively mitigates overall distortion caused by mounting and XFEL thermal loads. These findings offer a novel mounting solution for high-performance x-ray optics in XFEL research and applications, ensuring stability and optimal functionality in cryogenic conditions.

Instruments & Instrumentation↗
DOE OSTI2024

Harnessing large language models’ zero-shot and few-shot learning capabilities for regulatory research

Abstract Large language models (LLMs) are sophisticated AI-driven models trained on vast sources of natural language data. They are adept at generating responses that closely mimic human conversational patterns. One of the most notable examples is OpenAI's ChatGPT, which has been extensively used across diverse sectors. Despite their flexibility, a significant challenge arises as most users must transmit their data to the servers of companies operating these models. Utilizing ChatGPT or similar models online may inadvertently expose sensitive information to the risk of data breaches. Therefore, implementing LLMs that are open source and smaller in scale within a secure local network becomes a crucial step for organizations where ensuring data privacy and protection has the highest priority, such as regulatory agencies. As a feasibility evaluation, we implemented a series of open-source LLMs within a regulatory agency’s local network and assessed their performance on specific tasks involving extracting relevant clinical pharmacology information from regulatory drug labels. Our research shows that some models work well in the context of few- or zero-shot learning, achieving performance comparable, or even better than, neural network models that needed thousands of training samples. One of the models was selected to address a real-world issue of finding intrinsic factors that affect drugs' clinical exposure without any training or fine-tuning. In a dataset of over 700 000 sentences, the model showed a 78.5% accuracy rate. Our work pointed to the possibility of implementing open-source LLMs within a secure local network and using these models to perform various natural language processing tasks when large numbers of training examples are unavailable.

Biochemistry & Molecular Biology↗
DOE OSTI2022

Autoregressive Neural Network for Simulating Open Quantum Systems via a Probabilistic Formulation

The theory of open quantum systems lays the foundation for a substantial part of modern research in quantum science and engineering. Rooted in the dimensionality of their extended Hilbert spaces, the high computational complexity of simulating open quantum systems calls for the development of strategies to approximate their dynamics. In this Letter, we present an approach for tackling open quantum system dynamics. Using an exact probabilistic formulation of quantum physics based on positive operator-valued measure, we compactly represent quantum states with autoregressive neural networks; such networks bring significant algorithmic flexibility due to efficient exact sampling and tractable density. We further introduce the concept of string states to partially restore the symmetry of the autoregressive neural network and improve the description of local correlations. Efficient algorithms have been developed to simulate the dynamics of the Liouvillian superoperator using a forward-backward trapezoid method and find the steady state via a variational formulation. Our approach is benchmarked on prototypical one-dimensional and two-dimensional systems, finding results which closely track the exact solution and achieve higher accuracy than alternative approaches based on using Markov chain Monte Carlo method to sample restricted Boltzmann machines. Our Letter provides general methods for understanding quantum dynamics in various contexts, as well as techniques for solving high-dimensional probabilistic differential equations in classical setups.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

An Integrated Indexing and Search Service for Distributed File Systems

Data services such as search, discovery, and management in scalable distributed environments have traditionally been decoupled from the underlying file systems, and are often deployed using external databases and indexing services. However, modern data production rates, looming data movement costs, and the lack of metadata, entail revisiting the decoupled file system-data services design philosophy. In this article, we present TagIt, a scalable data management service framework aimed at scientific datasets, which can be integrated into prevalent distributed file system architectures. A key feature of TagIt is a scalable, distributed metadata indexing framework, which facilitates a flexible tagging capability to support data discovery. Furthermore, the tags can also be associated with an active operator, for pre-processing, filtering, or automatic metadata extraction, which we seamlessly offload to file servers in a load-aware fashion. We have integrated TagIt into two popular distributed file systems, i.e., GlusterFS and CephFS. Our evaluation demonstrates that TagIt can expedite data search operation by up to 10× over the extant decoupled approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects by Incorporating Machine Learning Techniques

The overall objective of this project is to develop a framework for reliable characterization and prediction of the state of stress in the overburden and underburden (including the basement) in CO 2 storage reservoirs using machine learning and integrated geomechanics and geophysical methods. Specifically, we propose to develop workflow encompassing of technologies and/or methods to predict stress and pressure changes due to CO 2 injection in an active tertiary recovery site and their impacts on subtle fault activation, fractures and occurrence of microseismic events and compare responses to field observations. In this project, we anticipate using dataset from the Farnsworth field Unit (FWU) which is operated by Purdure Petroleum. A novel elastic-waveform VSP inversion technique will be used to estimate high-resolution spatial and temporal changes of elastic moduli in CO 2 storage reservoirs, which will be combined with velocity-stress relationship derived from laboratory tests to obtain subsurface pressure and stress. Clustered microseismic data will be jointly inverted for improved focal mechanisms. Least-squares reverse-time migration of microseismic waveform data will be performed to directly image fracture/fault zones. Additionally, a deep neural network machine learning technique with convolutional and recurrent layers will be used for learning the spectro-temporal structures in microseismic waveforms. The results of this geotechnical data analysis will be integrated to develop a high-resolution 3D mechanical earth model extending from the overburden sealing formations to the underburden including the basement. Mechanical properties will be derived through integration of mechanical logs, tests, available results from chemo-mechanical laboratory tests, and elastic inversion of seismic data using a combination of Bayesian and stochastic methods as well as machine learning technique. Failure features (faults/fractures) will be represented and/or modeled based on seismic and core data analysis. A transient hydrodynamic-geomechanical model will be developed through coupling with the calibrated FWU reservoir simulation model. The full physics coupled model will be used to train a reduced order proxy model using machine learning algorithm for estimating stress which will then be used with appropriate constitutive relationships and forward seismological models to simulate pressure changes and induced microseismicity. An advanced optimization framework will be developed to perform a history match to minimize error between field observations and simulated. The history matched proxy model will be verified against the full-physics equivalent. The field observations that will be used in the coupled model calibration process include pressure/stress inverted from VSP, moment magnitude from microseismic analysis, real time downhole pressure measurements, production and injection data. Parameter sensitivity and uncertainty analysis will be performed to characterize the impact of model parameter uncertainty on stress estimates. The proposed project will have significant impact on future field implementation of the proposed technology. Because the project field site is an ongoing CO 2 EOR development, the value of the new technology will be demonstrated in an operational context and evaluated as a viable risk mitigation strategy. Cost/benefit will be evaluated together with the various commercial incentives for CO 2 sequestration available to oil and gas operators. The extensive available dataset and ongoing data acquisition under the SWP Phase III work plan provides flexibility for investigation of multiple approaches and reduces technical risk.

58 GEOSCIENCES↗
DOE OSTI2025

Design of a System Interface for Flexible Thermal Power Extraction from Two Advanced Reactors

This report presents the design of system interfaces enabling flexible thermal power extraction from two advanced nuclear reactor concepts: a sodium-cooled fast reactor (SFR) operating on a Rankine cycle, and a gas-cooled reactor (GCR) utilizing a Brayton cycle. The study addresses the dual challenge of ensuring reliable base-load electricity generation while meeting the variable high-temperature steam demands of industrial processes (IPs).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗