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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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Nonequilibrium Solvent Effects during Photodissociation in Liquids: Dynamical Energy Surfaces, Caging and Chemical Identity

In the gas phase, potential energy surfaces can be used to provide insight into the details of photochemical reaction dynamics. In solution, however, it is unclear what potential energy surfaces, if any, can be used to describe even simple chemical reactions such as the photodissociation of a diatomic solute. In this paper, we use mixed quantum/classical (MQC) molecular dynamics (MD) to study the photodissociation of $Na$ $^+_2$ in both liquid Ar and liquid tetrahydrofuran (THF). We examine both the gas-phase potential surfaces and potentials of mean force (PMF), which assume that the solvent remains at equilibrium with the solute throughout the photodissociation process and show that neither resemble a nonequilibrium dynamical energy surface that is generated by taking the time integral of work. For the photodissociation of $Na$ $^+_2$ in liquid Ar, the dynamical energy surface shows clear signatures of solvent caging, and the degree of caging is directly related to the mass of the solvent atoms. For $Na$ $^+_2$ in liquid THF, local specific interactions between the solute and solvent lead to changes in chemical identity that create a kinetic trap that effectively prevents the molecule from dissociating. Here, the results show that nonequilibrium effects play an important role even in simple solution-phase reactions, requiring the use of dynamical energy surface to understand such chemical events.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Radioshielding Properties of Nickel-Containing Activated Carbon

The possibility of metal-carbon nanocomposites synthesis by chemical deposition of nickel particles on powdered activated carbon has shown. The regularities of electromagnetic radiation interaction in the frequency range of 8–12 GHz with these nanocomposites have investigated depending on the composition of water solutions used in the process of their synthesis. Based on the results of such a study, the prospect of metal-carbon nanocomposites using for making of effective electromagnetic radiation shields and radio-absorbing materials has proved.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

Precipitation Risk when Diluting DFLAW Feed Saturated in Aluminum Hydroxide

The technical bases to support the One System River Protection Project Integrated Flowsheet assumption for diluting staged Direct Feed Low-Activity Waste (DFLAW) from the Hanford waste tanks with raw river water must be assessed in light of the risk of aluminum hydroxide (gibbsite) precipitation prior to the subsequent transfer of tank contents into the Low-Activity Waste Pretreatment System (LAWPS) from days to months after dilution. The operational and mission impacts of using other dilution fluids such as inhibited water, demineralized water, or a 2 M sodium hydroxide solution also must be assessed. As a first step to help inform this investigation, a survey was conducted of Hanford waste-related tests documenting the processing of tank waste materials (solutions, salt cakes, sludges) or their simulants for instances of gibbsite dissolution and precipitation. Experience from the aluminum industry, particularly the Bayer process, also was surveyed to gain insight into the precipitation and dissolution of gibbsite in sodium hydroxide solutions. The dependence of aluminum concentration on hydroxide concentration in analyses of actual tank waste solutions also was surveyed for tanks that have a long-term static inventory and tanks suspected of containing or known to contain substantial gibbsite solid phase in their sludge solids. Finally, an experimental program is outlined to aid prediction of the outcomes of DFLAW staged feed dilution with respect to significant variables that influence gibbsite dissolution and precipitation. The results of these investigations are summarized in this report.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1977

Crystal growth from solutions in low gravity

An experiment performed during the Apollo-Soyuz flight investigated a novel process for growing single crystals from solutions. In zero gravity, reactant solutions were allowed to diffuse slowly toward each other through a region of pure solvent in which they underwent a chemical reaction to form crystals of an insoluble material. The process is analogous to the growth of crystals in gels in normal gravity. The experiment was successful and yielded crystals of about the expected size, number, and quality. The results indicate that with further refinement the process should yield large, high quality crystals of a variety of materials.

Lind, M. D.↗
DOE OSTI2020

Today's Energy Challenges, Tomorrow's Solutions: Electrons to Molecules: Building a New Foundation for Industrial Processes

The vast majority of global goods and materials we use on a daily basis are manufactured from fossil fuel precursors - chemical building blocks strung together using combinations of heat, pressure, and chemical catalysis. NREL, along with energy industry partners, is exploring the use of renewable, affordable electricity as the driving force for the conversion of low-energy molecules - such as water and carbon dioxide (CO2) - to generate other molecules that could be used as chemicals, materials, fuels, or energy storage.Through this research, NREL and its partners are working together to determine the most efficient and cost-effective solutions for energy storage as well as safer ways to create chemicals and plastics that do not rely solely on fossil fuels.

affordable electricity↗
DOE OSTI2026

SEED: Semantic Energy Exploration and Discovery

The Bioenergy Knowledge Discovery Framework (KDF) hosts a vast repository of specialized data, yet traditional keyword-based search methods often struggle to provide direct answers, requiring significant domain expertise and manual effort to filter through raw documents. To overcome these barriers, this software introduces a semantic search engine that enables both specialists and non-specialists to query the KDF using natural language. By shifting from rigid keyword matching to intent-based retrieval, the tool automatically identifies and ranks the most relevant sources within the database. The system functions by processing natural language queries to extract the most pertinent information, delivering an AI-generated plain-language summary alongside exact supporting quotes from retrieved documents. This integrated approach provides users with immediate, evidence-based answers while eliminating the need for exhaustive manual review. By surfacing direct insights and contextual evidence, the software enhances the usability of existing KDF resources and democratizes access to complex bioenergy data. Ultimately, this semantic search solution accelerates the discovery process and supports faster, more informed decision-making across the bioenergy sector.

Pan, Meiyu (Melrose) [Oak Ridge National Laborator↗
DOE OSTI2019

PaKman: Scalable Assembly of Large Genomes on Distributed Memory Machines

De novo genome assembly is a fundamental problem in the field of bioinformatics, that aims to assemble the DNA sequence of an unknown genome from numerous short DNA fragments (aka reads) obtained from it. With the advent of high-throughput sequencing technologies, billions of reads can be generated in a matter of hours, necessitating efficient parallelization of the assembly process. While multiple parallel solutions have been proposed in the past, conducting a large- scale assembly at scale remains a challenging problem because of the inherent complexities associated with data movement, and irregular access footprints of memory and I/O operations. In this paper, we present a novel algorithm, called PaKman, to address the problem of performing large-scale genome assemblies on a distributed memory parallel computer. Our approach focuses on improving performance through a combination of novel data structures and algorithmic strategies for reducing the communication and I/O footprint during the assembly process. A key aspect of our algorithm is its graph data structure, which comprises fat nodes (or what we call "macro-nodes") that reduce the communication burden during contig generation. We present an extensive performance and qualitative evaluation of our algorithm, including comparisons to other state-of-the-art parallel assemblers. Our results demonstrate the ability to achieve near-linear speedups on up to 8K cores (tested); outperform state-of-the-art distributed memory and shared memory tools in performance while delivering comparable (if not better) quality; and reduce time to solution significantly. For instance, PaKman is able to complete an assembly of the full human genome in just over a minute on 8K cores.

Ghosh, Priyanka↗
NASA NTRS2011

Developer Tools for Evaluating Multi-Objective Algorithms

Multi-objective algorithms for scheduling offer many advantages over the more conventional single objective approach. By keeping user objectives separate instead of combined, more information is available to the end user to make trade-offs between competing objectives. Unlike single objective algorithms, which produce a single solution, multi-objective algorithms produce a set of solutions, called a Pareto surface, where no solution is strictly dominated by another solution for all objectives. From the end-user perspective a Pareto-surface provides a tool for reasoning about trade-offs between competing objectives. From the perspective of a software developer multi-objective algorithms provide an additional challenge. How can you tell if one multi-objective algorithm is better than another? This paper presents formal and visual tools for evaluating multi-objective algorithms and shows how the developer process of selecting an algorithm parallels the end-user process of selecting a solution for execution out of the Pareto-Surface.

multi-objective optimization↗
DOE OSTI2026

Integrating Resilience Planning in Distribution System Planning

Electric utilities, regulators, and stakeholders face increasing risks of severe storms, freezes, floods, and heat waves damaging grid infrastructure and causing power outages—and increasing risks of utility equipment igniting wildfires. At the same time, customer electricity rates have risen substantially in recent years, due in part to replacing aging infrastructure and improving resilience to natural hazards and physical threats. To address these challenges, utilities are beginning to move beyond traditional, siloed planning processes to balance resilience with other fundamental grid objectives such as affordability, reliability, safety, and serving new loads. This study presents a framework for states and utilities that want to advance integration of resilience and distribution planning processes to improve planning efficiency, better prioritize cost-effective grid expenditures, and balance planning objectives. The framework includes 7 key integration points between these planning processes: -Strategy process -Data -Threat assessments -Solution identification and prioritization -Optimization opportunities -Consideration of other grid needs -Metrics Lawrence Berkeley National Laboratory reviewed utility distribution system plans and interviewed subject matter experts to identify emerging practices for each of the 7 integration points. This report presents these practices, which can be used as a guide toward more holistic planning and cohesive investment strategies. It also includes 3 case studies to provide practical examples of how utilities apply such integrated planning processes: two pole hardening programs and one microgrid planning effort. The report concludes by identifying opportunities for future research.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Time Dependent Analysis of Laser Heating of Metal Parts in Contact with HE

We consider the time dependent heat transfer of laser energy impinging on metal parts that are in contact with high explosives (HE). The predecessor to this calculation was TN-J4-17-2109, “Heat Transfer Analysis from Laser Energy on Metal Parts in Contact with HE”, which considered the time independent heat transfer and compared to experimental results. The intent here is to extend those results to the time dependent case. The steady-state results were developed because they were the “worst case” from a safety perspective: the steady state represents the highest possible temperature excursion. However, we found that the temperatures achieved were well above the safety limits established by the DOE High Explosives Safety Manual. Moreover, they were well above the safety limit published by the LANL / Weapons Facilities Operations (WFO) in WFO-OS-ES-48, which establishes an upper temperature limit of 70°C for metal in contact with High Explosive (HE). The J-4 response to the original results was to design, build, and deploy an interlock system for DARHT that would ensure no laser energy on the firing point when both personnel and HE were present. This system was tested and proved effective, refer TP-DARHT-1150, (12/19/2016). It was reviewed and approved by the LANL Explosives Instrumentation Review Committee, refer PRES-J4-16-2140, “DARHT Laser Diagnostics Interlock System: Presentation to the EIRC”, (2016). Although the interlock system prevented personnel from being on the firing point under conditions where the diagnostic lasers would heat metal above the WFO limit, the WFO limit was still exceeded during the Multiplexed Photonic Doppler Velocimetry (MPDV) tuning process. The only practical solution is to limit the amount of time that the MPDV lasers are engaged at full power. The diagnostics interlock system was implemented with laser shutters that can fully interrupt the beams, and these shutters can be used to limit the amount of time that the lasers will impinge on the hydrotest assembly. It is the purpose of this paper to provide quantitative guidance on what length of time can be permitted during this tuning process. Therefore, we will solve the time-dependent heat transfer equation to determine the temperature increase as a function of time. This function can be inverted to determine the maximum allowable time for energizing the lasers based on the maximum allowable temperature at the metal to HE interface.

42 ENGINEERING↗
DOE OSTI2024

Neural network methods for radiation detectors and imaging

Recent advances in image data proccesing through deep learning allow for new optimization and performance-enhancement schemes for radiation detectors and imaging hardware. This enables radiation experiments, which includes photon sciences in synchrotron and X-ray free electron lasers as a subclass, through data-endowed artificial intelligence. We give an overview of data generation at photon sources, deep learning-based methods for image processing tasks, and hardware solutions for deep learning acceleration. Most existing deep learning approaches are trained offline, typically using large amounts of computational resources. However, once trained, DNNs can achieve fast inference speeds and can be deployed to edge devices. A new trend is edge computing with less energy consumption (hundreds of watts or less) and real-time analysis potential. While popularly used for edge computing, electronic-based hardware accelerators ranging from general purpose processors such as central processing units (CPUs) to application-specific integrated circuits (ASICs) are constantly reaching performance limits in latency, energy consumption, and other physical constraints. These limits give rise to next-generation analog neuromorhpic hardware platforms, such as optical neural networks (ONNs), for high parallel, low latency, and low energy computing to boost deep learning acceleration (LA-UR-23-32395).

edge computing↗
NASA NTRS1975

UHMLE: Program description user guide

A program which computes maximum likelihood estimates for the general normal mixture is introduced. The program allows the user to fix any subsets of the mixture parameters; this fixed set may be redefined at various times in the iteration process. There is considerable time saved in computing the likelihoods if the diagonal form is specified. Hence, in the early iterations the diagonal assumption might be used, changing over to the full covariance mode later in the iteration process for a more refined solution. This flexibility allows the user to choose the sequence of parameter configurations in the iteration process which he feels will optimize the computation time required as well as possibly avoid convergence to suboptimal local maxima of the likelihood function.

Cobely, W. A.↗
NASA NTRS2015

Development of an Exploration-Class Cascade Distillation Subsystem: Performance Testing of the Generation 1.0 Prototype

The ability to recover and purify water is crucial for realizing long-term human space missions. The National Aeronautics and Space Admininstration and Honeywell co-developed a five-stage vacuum rotary distillation water recovery system referred to as the Cascade Distillation Subsystem (CDS). Over the past three years, NASA's Advanced Exploration Systems (AES) Water Recovery Project (WRP) has been working toward the development of a flight-forward CDS design. In 2012 the original CDS prototype underwent a series of incremental upgrades and tests intened to both demonstrate the feasibility of a on-orbit demonstration of the system and to collect operational and performance data to be used to inform a second generation design. The latest testing of the CDS Generation 1.0 prototype was conducted May 29 through July 2, 2014. Initial system performance was benchmarked by processing deionized water and sodium chloride. Following, the system was challenged with analogue urine waste stream solutions stabilized with an Oxone-based and the two International Space Station baseline and alternative pretreatment solutions. During testing, the system processed more than 160 kilograms of wastewater with targeted water recoveries between 75 and 85% depending on the specific waste stream tested. For all wastewater streams, contaminant removals from wastewater feed to product water distillate, were estimated at greater than 99%. The average specific energy of the system was less than 120 Watt-hours/kilogram. The following paper provides detailed information and data on the performance of the CDS as challenged per the WRP test objectives.

Callahan, Michael R.↗
DOE OSTI2018

Impact of Physics Parameterization Ordering in a Global Atmosphere Model

Abstract Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid‐scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effect of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k ‐means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Numerical and Analytical Modeling of Flow Partitioning in Partially Saturated Fracture Networks

Infiltration processes in fractured-porous media remain a crucial, yet not very well understood component of recharge and vulnerability assessment. Under partially-saturated conditions flows in fractures, percolating fracture networks, and fault zones contribute to the fastest spectrum of infiltration velocities via preferential pathways. Specifically, the partitioning dynamics at fracture intersections determine the magnitude of flow fragmentation into vertical and horizontal components and hence the bulk flow velocity and dispersion of fracture networks. In this work, we derive an approximate analytical solution for the partitioning process and validate it using smoothed particle hydrodynamics simulations. The developed transfer function is conceptually based on simulation results and laboratory experiments carried out in previous works. It allows to efficiently simulate flow through fracture networks with simple cubic structure and arbitrary number of fractures and aperture sizes via linear response theory and convolution of a given input signal. We derive a non-dimensional bulk flow velocity ($\widetilde{v}$) and dispersion coefficient ($\widetilde{D}$) to characterize fracture networks in terms of dimensionless horizontal and vertical time scales $\tau_m$ and $\tau_0$. The dispersion coefficient is shown to strongly depend on the horizontal time scale and converges towards a constant value of $0.08$ within reasonable fluid and geometrical parameter ranges, while the non-dimensional velocity exhibits a characteristic $\widetilde{v} \sim \tau_m^{-1/2}$ scaling. Given that hydraulic information is often only available at limited places within (fractured-porous) aquifer system, such as boreholes or springs, our study intends to provide a rudimentary analytical concept to potentially reconstruct internal fracture network geometries from external boundary information, e.g., the dispersive properties of discharge (groundwater level fluctuations).

42 ENGINEERING↗
DOE OSTI2021

Recent Updates in ETOE-2 and MC 2 -3

The MC 2 -3 code is a multigroup cross section generation code for fast reactor applications, developed by Argonne National Laboratory (ANL) under the DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. In this work, first, the cross section libraries for ENDF/B-VII.1 and ENDF/B-VIII.0 data were generated using the updated ETOE-2 code. Preliminary verification and validation tests of the ENDF/B-VII.1 MC 2 -3 library were performed with the selected fast reactor benchmark problems. Processing and verifying the libraries suggested that significant efforts would be required for thoroughly verifying the ENDF/B-VII.1 MC 2 -3 library and successfully processing the ENDF/B-VIII.0 MC 2 -3 library. Secondly, the cross section generation capability of MC 2 -3 was updated with the intermediate group lattice calculation and the equivalent Dancoff-factor cell (EDC) method to significantly improve the performance of a twodimensional assembly calculation using the method of characteristics (MOC). This effort was made useful in implementing and verifying the EDC method in the Griffin cross section API. Finally, we analyzed a SFR problem, for which unusually large deviations in core eigenvalues from Monte Carlo solutions were reported, by generating multigroup cross sections with MC 2 -3, performing core calculations with DIF3D-VARIANT, and analyzing cross section and eigenvalue results against Monte Carlo solutions. The analysis confirmed that the MC 2 -3/DIF3D solutions were in good agreement with Monte Carlo solutions, providing the correct process of accurately generating broad-group cross sections with MC 2 -3

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Hyporheic Zone Microbiome Assembly Is Linked to Dynamic Water Mixing Patterns in Snowmelt-Dominated Headwater Catchments

We report that terrestrial and aquatic elemental cycles are tightly linked in upland fluvial networks. Biotic and abiotic mineral weathering, microbially mediated degradation of organic matter, and anthropogenic influences all result in the movement of solutes (e.g., carbon, metals, and nutrients) through these catchments, with implications for downstream water quality. Within the river channel, the region of hyporheic mixing represents a hot spot of microbial activity, exerting significant control over solute cycling. To investigate how snowmelt-driven seasonal changes in river discharge affect microbial community assembly and carbon biogeochemistry, depth-resolved pore water samples were recovered from multiple locations around a representative meander on the East River near Crested Butte, CO, USA. Vertical temperature sensor arrays were also installed in the streambed to enable seepage flux estimates. Snowmelt-driven high river discharge led to an expanding zone of vertical hyporheic mixing and introduced dissolved oxygen into the streambed that stimulated aerobic microbial respiration. These physicochemical processes contributed to microbial communities undergoing homogenizing selection, in contrast to other ecosystems where lower permeability may limit the extent of mixing. Conversely, lower river discharge conditions led to a greater influence of upwelling groundwater within the streambed and a decrease in microbial respiration rates. Finally, associated with these processes, microbial communities throughout the streambed exhibited increasing dissimilarity between each other, suggesting that the earlier onset of snowmelt and longer periods of base flow may lead to changes in the composition (and associated function) of streambed microbiomes, with consequent implications for the processing and export of solutes from upland catchments.

58 GEOSCIENCES↗