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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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Beginner's Guide to Understanding Power System Model Results for Long-Term Resource Plans

This guide was developed to improve decision-making in the electricity planning process by strengthening dialogue between electricity system planners and stakeholders throughout the process. This document was created for anyone who is first getting exposed to scenario results from power system planning models, or for those who are beginning to interact with power system modelers. It does not assume any experience with power system modeling, or familiarity with electricity planning concepts. This guide can be helpful to a wide range of people, including but not limited to state utility commissioners and commission staff, state energy offices, and intervenors in the planning process. It is targeted to those who are evaluating or reviewing model results presented by a utility, which typically span utility-scale generation and storage (and associated transmission) assets. This guide is designed to provide enough background and guidance that stakeholders can formulate and ask questions to evaluate model results through a deeper understanding of the key assumptions, data, and methods that drive decision outcomes. The ultimate purpose of this work is to increase transparency in the electricity planning process by enabling stakeholders to better engage and evaluate model results. A follow-on guide will provide a deeper dive into emerging topics, which are expected to become more prominent in the electricity planning process, but whose methods and approaches are still being refined.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

From Fossil Fuels to Green Mines: Understanding Hydrogen-Shale Interactions for Secure Underground Storage

Hydrogen-powered mining trucks are rapidly gaining traction as a key driver of decarbonization in the mining industry. This surge necessitates a decisive shift towards renewable energy sources, primarily for hydrogen production. However, the inherent intermittency of renewables poses a challenge for continuous operations, demanding efficient storage solutions for hydrogen fuel. Hydrogen, derived from renewables, requires large-scale storage, with underground hydrogen storage (UHS) in depleted oil and gas reservoirs projected to provide this capacity. An impermeable seal (caprock) overlying depleted reservoirs is crucial for preventing leakage and ensuring secure storage. Shale, a potential caprock, has been recognized for its effectiveness in containing natural gas for geological time-periods. This study investigates the impact of hydrogen exposure on the matrix permeability of Marcellus shale, a key factor influencing its sealing capacity. A novel time-resolved approach was employed, measuring matrix permeability after each exposure to understand the dynamic interactions between hydrogen and the shale matrix. Samples were exposed to hydrogen in pressure reactions at realistic reservoir conditions at varying time durations. Preliminary results reveal an initial increase in permeability, while subsequent exposures show a decrease, indicating potential microstructural changes.

08 HYDROGEN↗
DOE OSTI2023

Understanding the Capabilities and Limitations of the Controls and Operations of High Voltage Direct Current (HVdc) Converters in Interconnected Electric Power Systems

This project will seek to build a fundamental understanding, and capability, to model and simulate the controls and operations of high voltage direct current (HVdc) converter stations in an electromagnetic simulation environment. While HVdc stations have been operated in the United States for over 50 years, these are typically simple two terminal point-to-point systems. Recently multi-terminal systems have begun to be deployed. The challenge with these new multi-terminal systems is that they often use different control schemes on the different terminals. The interactions of existing and new controls, and the fact that HVdc systems are rates in the 1,000’s of MWs means that small control instabilities can have dramatic impacts to bulk power systems. Despite these challenges, the operational capabilities of HVdc make them an attractive option for the transfer of the large amounts of renewable electricity that will be necessary for decarbonization of the nation’s electrical infrastructure and other sectors.

42 ENGINEERING↗
DOE OSTI2021

Understanding Spin Coherence in Polyoxometalate-Based Molecular Qubits

This research advances the understanding of spin decoherence mechanisms and addresses the grand challenges in quantum information science of generating and stabilizing quantum states that may be manipulated with single-atom precision. It is accomplished using unique capabilities developed at PNNL for ion soft landing and spatially resolved vibrational spectroscopy of well-defined supported molecular qubit (MQ) arrays. It addresses knowledge gaps impeding the development of MQ-based quantum devices by answering two scientific questions: 1) Can we minimize spin-lattice relaxation rates by tuning the substrate-MQ interface? 2) What is the optimum number of spin centers that enables sufficient coherent signal generation prior to decoherence through inter-MQ and MQ-support interactions? The objective is to develop predictive design principles for prolonging spin coherence lifetimes in arrays of optically-addressable MQs for quantum computing applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Microscopic Understanding of the Effects of Impurities in Low RRR SRF Cavities

The SRF community has shown that introducing certain impurities into high-purity niobium can improve quality factors and accelerating gradients. We question why some impurities improve RF performance while others hinder it. The purpose of this study is to characterize the impurities of niobium coupons with a low residual resistance ratio (RRR) and correlate these impurities with the RF performance of low RRR cavities so that the mechanism of impurity-based improvements can be better understood and improved upon. The combination of RF testing, temperature mapping, frequency vs temperature analysis, and materials studies reveals a microscopic picture of why low RRR cavities experience low BCS resistance behavior more prominently than their high RRR counterparts. We evaluate how differences in the mean free path, grain structure, and impurity profile affect RF performance. The results of this study have the potential to unlock a new understanding on SRF materials and enable the next generation of high Q/high gradient surface treatments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Understanding Sextupole

In this study, we reassess the dynamics within a simple accelerator lattice featuring a single degree of freedom and incorporating a sextupole magnet. In the initial segment, we revisit the H\'enon quadratic map, a representation of a general transformation with quadratic nonlinearity. In the subsequent section, we unveil that a conventional sextupole is essentially a composite structure, comprising an integrable McMillan sextupole and octupole, along with non-integrable corrections of higher orders. This fresh perspective sheds light on the fundamental nature of the sextupole magnet, providing a more nuanced understanding of its far-from-trivial chaotic dynamics. Importantly, it enables the description of driving terms of the second and third orders and introduces associated nonlinear Courant-Snyder invariant.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Advancing our understanding of instabilities in high-energy-density systems through the study of benchmark datasets with advanced modeling tools

Numerous types of pulsed power driven inertial confinement fusion (ICF) and high energy density (HED) systems rely on implosion stability to achieve desired temperatures, pressures, and densities. Sandia National Laboratories Pulsed Power Sciences Center’s main ICF platform, Magnetized Liner Inertial Fusion (MagLIF), suffers from implosion instabilities which limit attainable fuel conditions and can compromise fuel confinement. This Truman Fellowship research primarily focused on computationally exploring (a) methods for improving our understanding of hydrodynamic and magnetohydrodynamic instabilities that form during cylindrical liner implosions, (b) methods for mitigating implosion instabilities, particularly those that degrade performance of MagLIF targets, and (c) novel MagLIF target designs intended to improve target performance primarily via enhanced implosion stability. Several multi-dimensional computational tools were used, including the magnetohydrodynamics code ALEGRA, the radiation-magnetohydrodynamics code HYDRA, and the magnetohydrodynamics code KRAKEN. This research succeeded in executing and analyzing simulations of automagnetizing liner implosions, shockless MagLIF implosions, dynamic screw pinch driven cylindrical liner implosions, and cylindrically convergent HED instability studies. The methods and tools explored and developed in this Truman Fellowship research have been published in several peer-reviewed journal articles and will serve as useful contributions to the fields of pulsed power science and engineering, particularly pertaining to pulsed power ICF and HED science.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Dislocation line tension model to improve understanding of the effects of hydrogen on the deformation of structural materials

Decarbonization efforts highlight hydrogen as an attractive alternative to fossil fuels, but its tendency to embrittle structural metals demands careful consideration when designing hydrogen infrastructure. Moreover, the mechanisms by which hydrogen degrades these materials are still being elucidated. The current work develops new computational tools to quantify the different contributions of hydrogen to the energy barrier of cross-slip, a key deformation mechanism. Novel features are implemented to a line tension model, which include the use of non-singular dislocation interactions, character-dependent dislocation energies and simulations of the constriction configurations. A new molecular dynamics technique is developed to calculate the interaction energy between the partials of a dissociated dislocation via fixing the centers of mass of the regions below and above the Shockley partials and performing time-averaged calculations. Hydrogen is found to impact the stacking fault width of dislocations in different ways depending on their characters: it decreases for dislocations with a character θ > 30°, remains unchanged for θ = 30° and increases for θ < 30°. The latter regime is a newly identified mechanism by which hydrogen inhibits cross-slip. Moreover, formation of nano-hydrides is predicted to occur around screw dislocations for high hydrogen concentrations, a phenomenon previously identified only in dislocations with an edge component. If nano-hydrides develop, their influence extending the equilibrium stacking fault width and increasing both the constriction and cross-slip energy barriers dominate over all other hydrogen contributions. The theory and tools developed will pave the way towards a comprehensive understanding of hydrogen-dislocation interactions in structural metals.

08 HYDROGEN↗
DOE OSTI2020

Mesoscale simulations of High Burnup Fuel Fragmentation: Applying phase-field modeling to understand high burnup fuel fragmentation during loss of coolant accident conditions

During a loss-of-coolant accident (LOCA) in a nuclear power plant, a rapid increase in temperature is experienced in the fuel. In commercial light water reactors (LWRs), the high burnup structure (HBS) forms in regions of the UO 2 fuel where local burnup is high, characterized by smaller grain sizes and large, overpressurized bubbles. During a LOCA transient, fuel in the HBS region is susceptible to fine fragmentation, where the fuel breaks up into micron-size fragments (sometimes referred to as pulverization). To better understand the mechanisms behind this phenomenon, mesoscale computational modeling using the Idaho National Laboratory code Marmot has been employed to simulate the process of HBS formation and response to a LOCA transient. The process of complete and partial HBS formation was demonstrated in prototypical LWR conditions. The simulated HBS microstructures from these simulations were passed to a phase-field model of fracture. To provide a more direct comparison with experiments, a set of experiments conducted by Studsvik on fine fragmentation/pulverization during LOCA conditions was simulated using the BISON fuel performance code. The temperature profiles from the BISON simulations were passed to a phase-field model to determine the gas bubble pressure as a function of time. These pressure histories were used in a phase-field model of fracture to determine under what conditions and in which types of bubbles fine fragmentation was likely to occur.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

An ML-based terrestrial data fusion and augmentation framework to enable advanced understanding of the terrestrial carbon and water interactions

Soil moisture is essential to the terrestrial carbon and water cycles and land–atmosphere interactions. There are various types of soil moisture data, and each type has the distinct spatiotemporal strengths and limitations, depending on the diverse applications and retrieval methodologies of different data types (Li et al., in review; The PNNL-82151 FY23 Report). However, the limitations of different soil moisture data in terms of accuracy and spatiotemporal coverage hinder our ability to further understand the soil moisture dynamics across scales. To have a gap free soil moisture data product with a fine spatiotemporal coverage and vertical profiles, we train extreme gradient boosting (XGBoost) models by using (1) in-situ soil moisture measurements from the International Soil Moisture Network (ISMN), (2) soil moisture from the ECMWF reanalysis (ERA) at the 9 km and sub-daily spatiotemporal resolution, (3) the Daymet meteorological fields, and (4) data products that characterize surface conditions, including soil texture, organic content, topography, vegetation type, and rooting depth. We use the trained XGBoost models that have consistent performance across seven soil layers, i.e., 0–5 cm, 5–10 cm, 10–20 cm, 20–40 cm, 40–60 cm, 60–100 cm, and 100–200 cm, and the gridded model predictors to generate a soil moisture data at the 1 km and daily spatiotemporal resolution for the Continental United States (CONUS) from 2001–2020. This dataset can be broadly used for Earth system model benchmark, monitoring extreme weathers, making informed decisions regarding agriculture, water resource management, climate change mitigation, and ecosystem preservation.

58 GEOSCIENCES↗
DOE OSTI2024

Advancing the Understanding of Manufacturing Tools for Hardware Security

This project’s goal was to explore new methods and tools to evaluate the focused ion beam (FIB) effect on active electrical devices, which is becoming increasingly challenged by the continual decrease in transistor geometry. Novel hole transfer methods leveraging FIB patterning were demonstrated utilizing selective area atomic layer deposition (ALD) and metal assisted chemical etching. A FIB damage electrical tester device was fabricated, and the effects of FIB beams were characterized by examining change in performance of damaged transistors. Detailed characterization of end-of-range damage for common FIB ions were correlated to modeling methods. Finally, undamaged and damaged devices were simulated by Charon to begin understanding the FIB effects on active devices. This test platform along with modeling methods give a powerful way to assess FIB damage in materials and devices, and with more development can help establish methods to predict FIB damage effects on electrical devices.

42 ENGINEERING↗
DOE OSTI2024

Understanding Decision-Relevant Regional Data Products: Workshop Report

A broad community of climate adaptation practitioners, stakeholders and policymakers rely on historical reconstructions and future projections of local to regional climate. To be of value to these users, climate data must be credible, salient, and authoritative (Cash et al. 2002). Namely, data must be consistent with our physical understanding of the global Earth system, must be relevant for informing the decision-making process, and must be backed by expert judgment. As more and more data products have become available, multiple challenges have emerged around the production, evaluation, selection, and use of these data products. Consequently, to ensure crucial decisions leverage the best possible historical and future physical climate data, there is a pressing need to develop a coordinated national climate data strategy that is inclusive of all relevant communities of practice.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Understanding Twinning and Deformation in High Entropy Alloys

A combination of high strength and high ductility has been observed in multi-principal element alloys due to twin formation attributed to low stacking fault energy (SFE). In the pursuit of low SFE alloys, a key bottleneck is the lack of understanding of the composition–SFE cor- relations that would guide tailoring SFE via alloy composition. Using density functional theory (DFT), we show that dopant radius, which have been postulated as a key descriptor for SFE in dilute alloys, does not fully explain SFE trends across different host metals. Instead, charge density is a much more central descriptor. It allows us to (1) explain contrasting SFE trends in Ni and Cu host metals due to various dopants in dilute concentrations, (2) explain the large SFE variations observed in the literature even within a given alloy composition due to the nearest neighbor environments in “model” concentrated alloys, and (3) develop a machine learning model that can be used to predict SFEs in multi-elemental alloys. This model opens a possibility to use charge density as a descriptor for predicting SFE in alloys. Furthermore, a descriptor-less machine learning (ML) model based only on charge density images extracted from density functional theory (DFT) is developed to predict stacking fault energies (SFE) in concentrated alloys. The model is based on convolutional neural networks (CNNs) as one of the promising ML techniques for dealing with complex images and data. Identification of correct descriptors is a key bottleneck to develop ML models for predicting materials properties. Often, in most ML models, textbook physical descriptors such as atomic radius, valence charge and electronegativity are used as descriptors which have limitations because these properties change in concentrated alloys when multiple elements are mixed to form a solid solution. We illustrate that, within the scope of DFT, the search for descriptors can be circumvented by electronic charge density, which is the backbone of the Kohn-Sham DFT and describes the system completely. The performance of our model is demonstrated by predicting SFE of concentrated alloys with an RMSE and R2 of 6.18 mJ/m2 and 0.87, respectively, validating the accuracy of the proposed approach.

36 MATERIALS SCIENCE↗