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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 937 records · Page 52

AEDGE: Atomic Experiment for Dark Matter and Gravity Exploration in Space

We propose in this White Paper a concept for a space experiment using cold atoms to search for ultra-light dark matter, and to detect gravitational waves in the frequency range between the most sensitive ranges of LISA and the terrestrial LIGO/Virgo/KAGRA/INDIGO experiments. This interdisciplinary experiment, called Atomic Experiment for Dark Matter and Gravity Exploration (AEDGE), will also complement other planned searches for dark matter, and exploit synergies with other gravitational wave detectors. We give examples of the extended range of sensitivity to ultra-light dark matter offered by AEDGE, and how its gravitational-wave measurements could explore the assembly of super-massive black holes, first-order phase transitions in the early universe and cosmic strings. AEDGE will be based upon technologies now being developed for terrestrial experiments using cold atoms, and will benefit from the space experience obtained with, e.g., LISA and cold atom experiments in microgravity. This paper is based on a submission (v1) in response to the Call for White Papers for the Voyage 2050 long-term plan in the ESA Science Programme. ESA limited the number of White Paper authors to 30. However, in this version (v2) we have welcomed as supporting authors participants in the Workshop on Atomic Experiments for Dark Matter and Gravity Exploration held at CERN: ({\tt https://indico.cern.ch/event/830432/}), as well as other interested scientists, and have incorporated additional material.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

From Gargamelle to MINERvA: exploring the structure of the nucleon with neutrinos

Neutrino scattering experiments have been exploring the structure of the nucleon with Deep-Inelastic Scattering for over 50 years. Although hints of nucleon structure were available using CERN’s first neutrino beam in the 1960s, the study actually started quantitatively in the early 1970s with the Gargamelle heavy liquid bubble chamber that produced first neutrino confirmation of scaling. This study of nucleon structure continued with both bubble chambers and more massive electronic detectors that, with higher energy neutrino beams and $Q^2$ reach, examined the breaking of this scaling while testing Quantum Chromodynamics. Here, a significant factor when including neutrino explorations of nucleon structure in the overall picture is that to gather significant statistics, neutrino experiments have had to use heavier nuclear targets. It has been experimentally demonstrated that the structure of the nucleon in the nuclear environment is indeed different than the free nucleon structure. Understanding this modified structure has played an important part in the experimental and theoretical exploration of nucleon structure by neutrinos and is one of the important goals of the on-going MINERvA experiment at Fermilab.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

(Invited) Modeling Electrolyzers: Exploring the Applied Voltage Breakdown

To commercialize successfully polymer-electrolyte electrolyzers and optimize their performance, one requires a detailed understanding of the underlying physics and phenomena. Mathematical modeling is ideally suited to explore such intricacies. In this Tutorial, the modeling equations and approaches towards both proton- and hydroxide-conducting polymer electrolyzers will be detailed. This includes the introduction of the applied voltage breakdown that separates the overall polarization curve into its constitutive parts such that the limiting mechanisms can be ascertained. Throughout, different case studies will be explored including impacts of bubble generation, liquid versus vapor feed, and pH changes due to carbonate and hydroxide solution feeds. A key focus of the Tutorial will be in exploring and describing the various transport and competing phenomena within the electrolyzer cell.

42 ENGINEERING↗

The MG-RAST API explorer: an on-ramp for RESTful query composition

Background The MG-RAST API provides search capabilities and delivers organism and function data as well as raw or annotated sequence data via the web interface and its RESTful API. For casual users, however, RESTful APIs are hard to learn and work with. Results We created the graphical MG-RAST API explorer to help researchers more easily build and export API queries; understand the data abstractions and indices available in MG-RAST; and use the results presented in-browser for exploration, development, and debugging. Conclusions The API explorer lowers the barrier to entry for occasional or first-time MG-RAST API users.

59 BASIC BIOLOGICAL SCIENCES↗

Innovative Exploration Techniques for Geothermal Assessment at Jemez Pueblo, New Mexico

Surface exploration methods like geological mapping, mineralogical analysis, hydrogeochemistry, magnetotelluric as well as seismic, have been used to analyze the study area and identify a location for a production size exploration well. After that location has been identified in a blind resource scenario, a 5,657 feet deep deviated production size exploration well has been drilled. The surface casing is 13 3/8 inch with open hole starting at 4,136 feet. The well has been designed to be deepened up to 8,000 feet if needed. The first 4,180 feet have been sufficiently analyzed and were considered only of direct use interest prior to drilling. That has been confirmed. The remaining depth couldn't be logged by the time the report has been submitted because the well had an obstruction at 4,180 feet. Currently the power production potential for the drilling location cannot be determined without additional work-over of the well. The seismic conducted prior to drilling was a 100% success, providing a clear image of the subsurface and allowing for geosteering to be fact based and on target. Once the obstruction has been removed, work can continue to determine the power generation potential at that location.

15 GEOTHERMAL ENERGY↗

Statistical Projections for Multi-resolution, Multi-dimensional Visual Data Exploration and Analysis

An ongoing challenge in visual exploration and analysis of large, multi-dimensional datasets is how to present useful, concise information to a user for some specific visualization tasks. Typical approaches to this problem have proposed either reduced-resolution versions of data, or projections of data, or both. These approaches still have some limitations such as consuming high computation or suffering from errors. In this work, we explore the use of a statistical metric as the basis for both projections and reduced-resolution versions of data, with a particular focus on preserving one key trait in data, namely variation. We use two different case studies to explore this idea, one that uses a synthetic dataset, and another that uses a large ensemble collection produced by an atmospheric modeling code to study long-term changes in global precipitation. The primary findings of our work are that in terms of preserving the variation signal inherent in data, that using a statistical measure more faithfully preserves this key characteristic across both multi-dimensional projections and multi-resolution representations than a methodology based upon averaging.

54 ENVIRONMENTAL SCIENCES↗

Renewable Energy Data Explorer User Guide

This publication provides a user guide for the Renewable Energy Data Explorer and technical potential tool within the Explorer. The Renewable Energy Data Explorer is a dynamic, web-based geospatial analysis tool that facilitates renewable energy decision-making, investment, and deployment. It brings together renewable energy resource data and other modeled or measured geographic information system (GIS) layers, including land use, weather, environmental, population density, administrative, and grid data.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Explore the Techno-Economic Viability of Using Large-Scale Additive Manufacturing (AM) For High-Performance Windows

Use of 3D printing, or additive manufacturing (AM) technology, in window design and construction is an under-explored area of research. Given the rapid advancements in AM technology and the potential for AM to address significant challenges associated with window design and manufacturing, there was a need to explore the feasibility of using AM technology. Alcoa’s Kawneer (Alcoa Building and Construction Systems) partnered with Oak Ridge National Laboratory’s (ORNL) Manufacturing Demonstration Facility (MDF) to explore the technical and commercial viability of large-scale 3D printing technologies with Kawneer’s AM window design. The project combined Alcoa/Kawneer’s design and expertise with ORNL’s equipment capability to create and study the world’s first 3D printed window using Big Area Additive Manufacturing (BAAM) technology. The results show that AM is useful for creating custom window shapes and sizes. With AM, more efficient windows can be made by sealing the glass pane into the printed frame during the printing process. In addition to energy savings, the use of AM reduces the manual labor required to produce custom windows.

36 MATERIALS SCIENCE↗

Exploring Electrocatalysis of Methane on Transition Metal Surfaces

Methane is a potent greenhouse gas because it has a heat-absorbing ability that is 20 times stronger than the better-known carbon dioxide. It is also the dominant component of nature gas (>70%). Its current greenhouse effect is only second to carbon dioxide largely because of its relatively low atmospheric concentration. Alarmingly, however, the latter has seen a 1.5-time increase since 1750, mainly due to anthropogenic livestock farming, coal and natural gas mining, and organic matter decomposing in waste landfills. Mitigating such a trend effectively and efficiently is therefore highly desirable and intensely sought for. This final technical report describes some exciting research progresses made over the last three years supported financially by the aforementioned award. The research conducted focused on exploring electrochemical direct methane to methanol (DMTM) conversion under mild conditions. The goal of research was to explore the possibility of developing potentially game-changing electrocatalysts and electrocatalysis that can convert methane directly to methanol in a most sustainable way for curbing its effect on global warming. Progress has been made in the following three directions. First, by adapting a hydrogen fuel-cell configuration that enables gaseous methane to be transported directly to the electrocatalyst surface, we have overcome the perennial difficulty in measuring activity of methane electro-oxidation at low temperature and ambient pressure that has prevented any meaningful studies of electrocatalysis of methane conversion thus far. Second, we have developed a novel and operational in situ electrochemical infrared (IR) spectral cell for studying electrocatalysis of direct methane to methanol conversion. This novel cell is also expected to alleviate the measuring difficulty caused by low solubility of methane in aqueous electrolyte and low sticking coefficient for methane adsorption onto transition metal surface. It will improve significantly the IR’s signal to noise ratio. Third, we have successfully synthesized nano-sizing copper (Cu) exchanged zeolite mordenite (Cu-ZMOR) and coated it with carbon that enabled electrochemical access to the encaged Cu ions. This opens a door to unravel the chemistry of Cu ions in catalyzing direct methane to methanol conversion under mild experimental conditions. Altogether, these progresses achieved have laid a solid foundation for further exploring electrocatalysis of direct methane to methanol conversion in general where there exists “a plenty of room” for new discoveries and developments.

03 NATURAL GAS↗

Understanding of catalytic transformation of shale gas and development of catalysts with high activity and selectivity through experimental exploration and theoretical simulation

Catalysis on transition metal oxides is equivalently important in contrast to that on metal catalysts in chemical and energy transformations. Understanding of catalytic reactions on early transition metal oxide catalysts is fundamentally intriguing and of great practical interest in efficient production of chemical and fuel feedstocks. Fundamental understanding of catalysis on transition metal oxide-based catalysts has been lagged behind catalysis on metals due to the complexity of chemistry and structure of surface and bulk of oxide catalysts and their structural flexibility in reactive environment at high temperatures. The funded DOE project explored surface chemistry of a few reducible oxides including CeO 2 - based, Co 3 O 4 -based, and CoO-based which are significant for heterogeneous catalysis. Through in-situ studies using ambient pressure X-ray photoelectron spectroscopy and high pressure scanning tunneling microscopy, we revealed phase transformation, the accompanying changes of surface chemistry and structure, and uncovered their correlations with catalytic activity and selectivity in catalytic reactions including reduction of NO with CO, water-gas shift, and chemical transformations of methane to methanol and acetic acid under mild conditions. Driven by the following two facts, we propose to pursue fundamental understanding of oxidative dehydrogenation of ethane and oxidative coupling of methane on oxide catalysts through both in-situ studies of catalyst surfaces during catalysis and computational studies in the renewal proposal. One driving force is the significance of oxidative dehydrogenation of ethane and oxidative coupling of methane for utilization of earth-abundant, relatively inexpensive energy resource and the urgent needs of efficient chemical processes to generate ethylene from shale gas. The other is that exploration of surface chemistry of oxide catalysts during catalysis has remained challenging though it is critical in deeply understanding catalysis on oxide catalysts and developing oxide-based catalysts toward high selectivity and activity. Therefore, the overall objective of the renewal proposal is to mechanistically understand the oxidative dehydrogenation of ethane and oxidative coupling of methane at a molecular level through building correlations between surface chemistry of catalysts during catalysis and the corresponding catalytic performances, and thus design catalysts with high selectivity and activity for production of ethylene with the guidance achieved from these fundamental studies. Experiments were designed to explore the influences of electronic states of cations supported on substrate oxides, cations of surface of the substrate oxides, and surface lattice oxygen atoms of the substrate oxides on their catalytic selectivity and activity. Surface chemistry, including oxidation state of the surface monomers and cations of substrate oxides and density of oxygen vacancies during catalysis, will be tracked with AP-XPS during catalysis. A correlation between surface chemistry of these catalysts at different temperatures and their corresponding catalytic selectivity for production of ethylene and activity will be built. Computational studies will calculate adsorption energies of reactant molecules and their dissociated species and intermediates on the catalyst surface, search transition states, and simulate reaction pathway close to experimental studies. By integrating the computational studies into these correlations to be built from experimental studies, fundamental understanding of the catalytic mechanisms of oxidative dehydrogenation of ethane and oxidative coupling of methane at a molecular level will be achieved. With these insights, new catalysts with high selectivity and activity will be developed.

36 MATERIALS SCIENCE↗

Exploration of a Novel Technique for Waste Heat Recovery Through Molecular Dynamics: Influence of Wettability and Electric Field on Water and Water-Based Nanofluids

Most of the energy produced globally comes by way of a heat engine. The Carnot principle places a limit as to how thermodynamically efficient a heat engine can be. There is no heat engine that can be 100% thermodynamically efficient and as such a substantial proportion of all heat supplied to a heat engine is lost as waste heat. Waste heat therefore is a large energy source ready to be properly utilized. Herein, a novel approach for converting waste heat to electricity is discussed. It involves the use of the liquid to vapor phase change of a material dielectric (water) or electrolyte (nanofluid) in the embodiment of a capacitor for direct thermal to electrostatic energy conversion. While this method of waste heat recovery could potentially be added to the ever expanding portfolio of energy conversion techniques, a number of aspects must be addressed before it can be brought into practice. Water was seen as an ideal dielectric phase change material given its high relative permittivity ratio when in the liquid form as compared to its vapor form. However, given its short voltage holdoff time the phase change of water would need to occur rapidly. This brings up concerns of explosive boiling. Herein, molecular dynamics analysis into the explosive boiling behavior of thin water films gave more insight into how the interaction between the surface and liquid affected explosive boiling onset time. A Lennard-Jones potential with one interaction site and a Morse potential with three interaction sites between water and solid substrate were used. It was found generally that a stronger interaction between water film and substrate led to faster explosive boiling onset times but an increase in the number of interaction sites delayed explosive boiling, even at the same wettability (contact angle). Understanding changes in the density and enthalpy of vaporization of a liquid dielectric such as water in the presence of an electric field is of importance due to the electrostatic nature of the waste heat conversion method under consideration. Specifically, if both density and enthalpy of vaporization are increased, the thermodynamic efficiency of the waste heat conversion method under consideration is decreased. Electric field effects are explored herein via molecular dynamics using two water models, the TIP4P-Ew and SWM4-NDP. The SWM4-NDP model is polarizable while the TIP4P-Ew model is not, which allows for a determination of the importance of model polarizability (i.e. variation in water model dipole moment) on these two properties of water when subjected to an electric field. Herein it was found that both water models respond similarly in terms of density and vaporization enthalpy variance upon the introduction of an electric field. Comparison was also made to the pressure induced by the electric field (electrostriction pressure) by way of a density comparison and it was found that the predicted electrostriction pressure overestimates the pressure experienced by water. Water by itself has a high enthalpy of vaporization, which limits the efficiency of the newly proposed conversion method. Research both experimental and through simulation has shown that the vaporization enthalpy of nanofluids can be engineered via nanoparticle size and material selection. An avenue less explored is manipulating the enthalpy of vaporization by altering the interaction strength between the nanoparticles and the base fluid. In practice this could be achieved through the addition of coatings to the nanoparticles to alter their wettability to the base fluid. This was explored by using a Lennard-Jones potential and Morse potential to model the interaction between base fluid (water) and the nanoparticle. For nanoparticles 2nm in diameter and at weight percentages up to 6%, the change in vaporization enthalpy due to alterations of the interaction strength between nanoparticle and base fluid was not significant (less than a 1% difference) when compared to the effect of altering the weight percentage of nanoparticles in the nanofluid or introducing an electric field. However, the effect of wettability may still become important at other nanoparticle concentrations and sizes. In all, the studies presented here further the understanding of phase change and thermodynamic properties of water and water based nanofluids under an electrostatic field which will help inform the development of a novel approach to waste heat conversion. The reduction of waste heat will improve energy sustainability outlooks.

30 DIRECT ENERGY CONVERSION↗

GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The primary goals of this project are identifying hidden geothermal resources in the USA and designing profitable enhanced geothermal systems (EGS). Many non-obvious processes and parameters could characterize geothermal resources and could control the ultimate energy potential of geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize geothermal resources, but this data is sparse and multi-scale that has hindered attempts to leverage the datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) give promise to overcome these issues. Modern ML methods and tools can (1) analyze large datasets, (2) assimilate model ensembles that include a multitude of inputs and outputs, (3) process sparse datasets, (4) perform transfer learning between sites with different data quality, (5) extract hidden geothermal signatures from field and simulation data, (6) label geothermal resources and processes, (7) identify highvalue data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies.

58 GEOSCIENCES↗

Exploration with Scalable Gaussian Process Reinforcement Learning

Exploration is a challenging problem in reinforcement learning (RL), especially in environments with sparse rewards. Quantifying and utilizing the parametric uncertainty has been shown to be paramount for successful exploration [Osband et al., 2018]. Bayesian, or approximately Bayesian, methods present a principled means of estimating the parametric uncertainty in RL problems. Gaussian processes, nonparametric Bayesian models, are often impractical due to poor scalability and computational bottlenecks. We introduce a scalable Gaussian process RL (GPRL) method which directly induces sparsity in the covariance matrix to facilitate faster computation. This is a departure from previous GPRL methods which instead rely on data reduction and subsampling. We compare various covariance-based exploration techniques (Thompson sampling, upper confidence bound, and probabilistic maximum variance) which leverage our scalable GP framework in sparse reward environments. Finally, we show favorable comparison against the bootstrapped deep Q-Network.

97 MATHEMATICS AND COMPUTING↗

Using Homogenized Models to Explore the Effect of Fracture Densities on Weathering

Despite its importance, only a few researchers have incorporated the effects of fracturing into models of reactive transport for rock weathering. Here we explore 2D simulations that describe weathering under conditions of diffusive and advective transport within heterogeneous media consisting of rocky blocks and fractures. In our simulations, the Darcy velocities vary in space and time and depend on weathering processes within the rock matrix. We explore simulations with saturated and unsaturated flow for weathering bedrock that consists of blocks separated by inert or weathered material. The simulations show that a simplified homogenized model can approximate exact solutions for some of the simulated columns and hills and can allow exploration of coupling between flow and reaction in fractured rock. These hillslope simulations document that, even in the presence of 2D water flow, i) an increase in fracture density results in faster weathering advance rates; and ii) the water table locates deeper for a rock system that is weathered and fractured rather than weathered and unfractured. Some of these patterns have also been observed for natural systems. But these simulations also highlight how simplified models that do not use appropriate averaging of heterogeneities can be inaccurate in predicting weathering rate for natural systems. For example, if water flows both vertically and laterally through the vadose zone of a hill, then a prediction of the depth of regolith that is based on modeling strictly unidirectional downward infiltration will be unrealistically large. Likewise, if the fracture density observed near the land surface is used in a model to predict depth of weathering for a system where the fracture density decreases downward, the model will overestimate regolith depth. Learning how to develop accurately homogenized models could thus enable better conceptual models and predictions of weathering advance in natural systems.

58 GEOSCIENCES↗

Design-Space Exploration for Inverse-Design of Wind Turbine Blades Using Data-Driven Methods

The state-of-the-practice aerodynamic design methods for wind turbine blades is typically based on Blade-Element Momentum (BEM) theory using a pre-designed frozen family of airfoils. The airfoils are themselves typically designed using panel methods. The design of the next-generation of large flexible rotors will need to capture the non-linear aerodynamics and three-dimensional flow to reduce the levelized cost of wind energy. Data-driven methods for aerodynamic design using data generated by computational fluid dynamics offer an attractive alternative to BEM-based methods that captures the non-linear aerodynamics of the component airfoils as well as the root and tip sections. In this work, we develop and demonstrate a framework to "smartly" explore the relevant design space in combination with an appropriate automated CFD pipeline to evaluate the aerodynamics of each design. The design-space exploration framework uses appropriate perturbations to the airfoil shape and induction profile from a baseline shape in combination with the inverse-design using BEM. The resulting designs are evaluated using an automated CFD pipeline using the in-house CFD solver framework "Mercury". We perform verification and validation to establish the capability of the Mercury framework to predict the aerodynamic performance of wind turbines. The CFD simulation of the perturbed blade shapes are optimized to restart from the converged baseline simulation to reduce the computational time. Finally, we demonstrate the design-space exploration technique for the design of the outboard section and the full rotor using perturbations to the shape and operating conditions of the NREL 5-MW turbine.

aerodynamic design methods↗

Nuclear data for space exploration

Understanding the harmful effects of galactic cosmic rays (GCRs) on space exploration requires a substantial amount of nuclear data. Specifically, the interaction of energetic GCR charged particles with spacecraft materials generates secondary radiations that, through energy deposition, can harm astronauts and electronic systems. By identifying the gaps in our knowledge of the relevant nuclear data—such as interaction cross sections—and identifying ways to fill those gaps—with measurements, compilations, evaluations, dissemination, reaction modeling, sensitivity studies, and uncertainty quantification—the safety and viability of space exploration can be improved. This work surveys the state of the art in this interdisciplinary field and identifies promising collaborative research topics that have significant potential to advance our understanding of the effects of the space radiation environment on space exploration.

42 ENGINEERING↗

Methodology for Exploring Water and Hydropower Operating Criteria That Simultaneously Improve Economic and Environmental Considerations

Despite the reliability and flexibility of hydropower, the operation of hydroelectric power plants may have significant impacts on the downstream river system, including its water stage, sediment transport, and water temperature, ultimately affecting the ecology. To address these challenges, there is a need to identify water scheduling patterns that improve both hydropower economics and the environment relative to current operations. This paper presents a new methodology to explore promising operational criteria/rules that can achieve such improvements. Typical environmental impact statements and relicensing processes generally perform detailed site-specific analyses of a few alternatives that focus on reservoir water release operating rules and their associated environmental impacts. In contrast, the methodology presented in this article uses a widely applicable approach that explores a much larger solution space. This large set of potential alternatives can be represented in a multidimensional space for which one axis represents the economic value and the other axis quantify individual environmental impacts (e.g., sediment transport and fish growth), and they are explored via two approaches: a Monte Carlo simulation that identifies “win–win” alternatives and a multi-objective optimization problem that identifies Pareto-optimal alternatives.

13 HYDRO ENERGY↗