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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 451 records · Page 25

Earth Sciences Applications for Energy and Global Security: A Few Vignettes [Slides]

Understanding the physics of flow and transport in the subsurface environment is crucial to several National Security applications. In the Energy Security realm, some examples include characterizing radioactive waste disposal, exploring natural gas extraction and sequestering CO2. An example in the Global Security arena is to be able to distinguish between anthropogenic and naturally occurring seismic disturbances, the former being of particular concern as underground nuclear testing activity has seen an increase in recent years. A common theme across these applications is the ability to accurately model fluid flow in porous and/or fractured subsurface media. For decades, researchers have grappled with how to include the effects of uncertainties in these models, including but not limited to heterogeneity, unknown initial and boundary conditions and issues with scalability. More recently advances in computing and machine learning methodologies have allowed a broader exploration of the uncertainty space as we strive for real time decision making. I will present an overview of the field and discuss a few examples of how my own research in these topics has evolved over nearly two decades.

58 GEOSCIENCES↗

Underground Hydrogen Storage: Transforming Subsurface Science into Sustainable Energy Solutions

As the global economy moves toward net-zero carbon emissions, large-scale energy storage becomes essential to tackle the seasonal nature of renewable sources. Underground hydrogen storage (UHS) offers a feasible solution by allowing surplus renewable energy to be transformed into hydrogen and stored in deep geological formations such as aquifers, salt caverns, or depleted reservoirs, making it available for use on demand. This study thoroughly evaluates UHS concepts, procedures, and challenges. This paper analyzes the most recent breakthroughs in UHS technology and identifies special conditions needed for its successful application, including site selection guidelines, technical and geological factors, and the significance of storage characteristics. The integrity of wells and caprock, which is important for safe and efficient storage, can be affected by the operating dynamics of the hydrogen cycle, notably the fluctuations in pressure and stress within storage formations. To evaluate its potential for broader adoption, we also examined economic elements such as cost-effectiveness and the technical practicality of large-scale storage. We also reviewed current UHS efforts and identified key knowledge gaps, primarily in the areas of hydrogen–rock interactions, geochemistry, gas migration control, microbial activities, and geomechanical stability. Resolving these technological challenges, regulatory frameworks, and environmental sustainability are essential to UHS’s long-term and extensive integration into the energy industry. This article provides a roadmap for UHS research and development, emphasizing the need for further research to fully realize the technology’s promise as a pillar of the hydrogen economy.

25 ENERGY STORAGE↗

Department of Energy: Office of Scientific and Technical Information

The international acquisitions functions and activities of the Office of Scientific and Technical Information (OSTI) are described. There are four mechanisms for obtaining foreign information related to energy and nuclear science: The Energy Technology Data Exchange consisting of 14 member countries and 2 associate members; the International Nuclear Information System consisting of 86 countries and 17 international organizations; the Nuclear Energy Agency's 19 member countries provide reports for departmental scientists' use; bilateral agreements with countries such as Germany, the Nordic Consortium, and Australia result in records of foreign research in progress.

Grissom, Catherine↗

NASA Tech Briefs, Summer 1978, Volume 3, No. 2

Topics covered include: NASA TU Services: Technology Utilization services that can assist you in learning about and applying NASA technology; New Product Ideas: A summary of selected innovations of value to manufacturers for the development of new products; Electronic Components and Circuits; Electronic Systems; Physical Sciences; Solar Energy; Materials; Life Sciences; Mechanics; Machinery; Fabrication Technology; Mathematics and Information Sciences.

Source record↗

Studies to Improve the Sensitivity to Low Energy Interactions in Dual-Phase Xenon Dark Matter Detectors. Department of Energy Office of Science Graduate Student Research (SCGSR) Program, Final project report

Noble liquid time projection chambers (TPCs) are some of the most sensitive particle detectors ever developed. They see use in searches for new physics with neutrinos, or for new particles like dark matter. They work by sensing light and charge signals left behind by particle interactions in a volume of liquified xenon or argon. TPCs are so sensitive that even a single electron liberated in an interaction can be readily detected. However this sensitivity to signals comes with a sensitivity to background noise, with one example being single electrons that arrive long after the signals from a true particle interaction. This type of noise has been the subject of multiple studies, which have concluded that single electron backgrounds are well correlated with prior events in the TPC, as well as impurities in the detection medium. At Lawrence Livermore National Laboratory (LLNL), the XeNu TPC is a testbed for a novel study of these backgrounds by generating data with new components made of aluminum and Shapal--the latter being an exotic ceramic which can be machined using standard tools. These materials were selected to replace plastic components which introduce impurities in the TPC during operation. Without plastic, the hope is that electron backgrounds will be reduced, leaving new opportunities for studying their origins and dependence on impurities. The SCGSR fellowship served as a springboard to help meet these objectives. Over the course of a year, the new components were designed, fabricated, and installed in XeNu. Following their installation, data was taken for use in a future study that will enable the electron background contributions from plastic components to be studied directly. In the interim, preliminary analysis results indicate that electron backgrounds with the new components are roughly 50% lower. This has established the efficacy of Shapal as a low-background replacement for plastic components where electrical and thermal stability are needed

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Fully Convolutional Spatio-Temporal Models for Representation Learning in Plasma Science

We have trained a fully convolutional spatio-temporal model for fast and accurate representation learning in the challenging exemplar application area of fusion energy plasma science. The onset of major disruptions is a critically important fusion energy science issue that must be resolved for advanced tokamak plasmas such as the $25B burning plasma international thermonuclear experimental reactor (ITER) experiment. While a variety of statistical methods have been used to address the problem of tokamak disruption prediction and control, recent approaches based on deep learning have proven particularly compelling. In the present paper, we introduce further improvements to the fusion recurrent neural network (FRNN) software suite, which delivered cross-machine disruption predictions with unprecedented accuracy using a large database of experimental signals from two major tokamaks. Up to now, FRNN was based on the long short-term memory (LSTM) variant of recurrent neural networks to leverage the temporal information in the data. Here, we implement and apply the "temporal convolutional neural network (TCN)" architecture to the time-dependent input signals. Furthermore, this allows highly optimized convolution operations to carry the majority of the computational load of training, thus enabling a reduction in training time, and the effective use of high-performance computing resources for hyperparameter tuning. At the same time, the TCN-based architecture achieves better predictive performance when compared with the LSTM architecture for various tasks for a representative fusion database.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗