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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Exploration Systems Exterior Lighting Design Guidance

Humans are returning to the Moon — this time, to stay. NASA has selected a location that maximizes line-of-sight communication with Earth, solar visibility, and access to water ice: the Lunar South Pole (LSP). While the Sun is more consistently in the lunar sky at the poles, it never rises more than 7° above the horizon in the target landing regions. This harsh lighting environment--never experienced during the Apollo missions or in human spaceflight--presents an engineering challenge: Support and protect functional vision. The human vision system, which despite having a high-dynamic range, cannot see well into bright light and cannot adapt quickly from bright to dark or vice versa. The design of helmets, windows, and lighting solutions must work in a complementary fashion to achieve a system of lighting and functional vision support that enables crews to see into darkness while their eyes are light-adapted and see in bright light while still dark-adapted that protects their eyes from injury. This report brings together information and identifies gaps related to LSP Natural environment (topology, regolith, temperature, lighting, and so forth), NASA historical experience exploring the Moon, human vision capabilities and needs, exploration operations, simulation capabilities and needs (for design verification, training, mission planning, and so forth) and existing engineering, safety, medical and performance requirements related to support human exploration.

Simulation↗
DOE OSTI2017

Future Scenario Development from Disruptive Exploration Technologies and Business Models in the U.S. Geothermal Industry

With recent trends toward intermittent renewable energy sources in the U.S., the geothermal industry in its current form faces a crossroad: adapt, disrupt, or be left behind. Strategic planning with scenario analysis offers a framework to characterize plausible views of the future given current trends - as well as disruptions to the status quo. To inform strategic planning in the Department of Energy's (DOE) Geothermal Technology Office (GTO), the Geothermal Vision Study is tasked with offering data-driven pathways for future geothermal development. Scenario analysis is a commonly used tool in private industry corporate strategic planning as a way to prioritize and manage large investments in light of uncertainty and risk. Since much of the uncertainty and risk in a geothermal project is believed to occur within early stage exploration and drilling, this paper focuses on the levers (technical and financial) within the exploration process that can be pulled to affect change. Given these potential changes, this work first qualitatively explores potential shifts to the geothermal industry. Future work within the Geothermal Vision Study will incorporate these qualitative scenarios quantitatively, in competition with other renewable and conventional energy industries.

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

Technical Potential of Solar in Peru Using the Renewable Energy Data Explorer

Fact sheet details the Renewable Energy Data Explorer (RE Data Explorer) tool created for the Peruvian Ministry Energy and Mines (MINEM). The Peruvian RE Data Explorer is used to perform an initial technical potential analysis to calculate the available land area and technical potential for PV and CSP technologies in Peru.

14 SOLAR ENERGY↗
DOE OSTI2023

Exploring for Superhot Geothermal Targets in Magmatic Settings: 2022 Field Campaign at Newberry Volcano

This paper presents preliminary results from a subset of work carried out as part of a multinational research project entitled DErisking Exploration for multiple geothermal Plays in magmatic ENvironments (DEEPEN), supported by the U.S. Department of Energy (DOE) and Geothermica, a joint effort by EU member states and associated countries. The DEEPEN project will develop a customized approach to exploration for supercritical and superhot geothermal plays in magmatic systems, which will be applied to two demonstration sites. This paper summarizes field activities carried out at the U.S. demonstration site, Newberry Volcano in central Oregon. The objective of this work effort is to refine the subsurface model of Newberry Volcano, with special focus on deeper zones including the magmatic plumbing system and other key geologic elements. New data collection included gravity and wideband magnetotelluric (MT) surveys, as well as reinstallation of a seismic network. The National Renewable Energy Laboratory (NREL) and Enthalpion Energy LLC (Enthalpion) worked with the Deschutes National Forest Fort Rock District to use a low ground disturbance method of MT deployment to collect MT data inside the caldera and other restricted areas inside the National Volcanic Monument. This opened these areas to geophysical exploration for the first time in decades. Sites along and adjacent to the south rim of the volcano constituted the primary survey objectives. A team from Lawrence Berkeley National Laboratory (LBNL), the U.S. Geological Survey (USGS), and AltaRock also began the process of reinstalling the seismic network from the AltaRock enhanced geothermal system (EGS) demonstration in anticipation of further development activities at the site. The data ingestion, reduction, and analysis phase of the project is ongoing. We are currently processing the MT and gravity data and are developing a new, highly GPU-accelerated, 3D joint MT and gravity inversion to better localize the south rim/south flank conductive target and better understand its relationship to deep heat, fluid sources, and surface extrusive features. Joint inversions, which have not yet been undertaken at Newberry, will allow us to obtain constraints on the geologic model that cannot be determined from each method in isolation, improving our ability to image key geologic features at depth.

geophysics↗
DOE OSTI2017

Web-based visual data exploration for improved radiological source detection

Radiation detection can provide a reliable means of detecting radiological material. Such capabilities can help to prevent nuclear and/or radiological attacks, but reliable detection in uncontrolled surroundings requires algorithms that account for environmental background radiation. The Berkeley Data Cloud (BDC) facilitates the development of such methods by providing a framework to capture, store, analyze, and share data sets. In the era of big data, both the size and variety of data make it difficult to explore and find data sets of interest and manage the data. Thus, in the context of big data, visualization is critical for checking data consistency and validity, identifying gaps in data coverage, searching for data relevant to an analyst's use cases, and choosing input parameters for analysis. Downloading the data and exploring it on an analyst's desktop using traditional tools are no longer feasible due to the size of the data. This study describes the design and implementation of a visualization system that addresses the problems associated with data exploration within the context of the BDC. Finally, the visualization system is based on a JavaScript front end communicating via REST with a back end web server.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2018

Exploring Effective Best Management Practices in the Miyun Reservoir Watershed, China

Miyun reservoir watershed is a major source of drinking water for China’s capital, Beijing, which has a population of 21.75 million. Recently, the capacity of the Miyun reservoir to supply clean drinking water is threatened by increasing eutrophication (or algae bloom), mainly due to the discharge of wastewater and excessive fertilization application in the upstream watershed. Therefore, there is an urgent need to design effective best management practices (BMPs) to reduce upstream nutrient load and improve water quality in the Miyun reservoir. In this study, we built a watershed model (i.e. the Soil and Water Assessment Tool) in the Miyun Reservoir Watershed (MRW), and calibrated and validated it using long term sediment, nitrogen (N) and phosphorus (P) data. Further, we developed a Markov Chain based multi-objective optimization program to explore optimal BMPs with tradeoffs between economic costs and water quality responses. With the watershed model and the multi-objective optimization algorithms, we explored potential effectiveness of BMPs under two scenarios that are currently being considered: scenario 1 assumes funding of BMP implementation is from national grants and targets high water quality standard, while scenario 2 assumes funding is from farmers and targets water quality that barely meet the drinking water standard. We found substantial discrepancy between these two scenarios with respect to type and spatial configuration of BMPs and associated economic costs, highlighting the need of reconciling concerns from different stakeholders in order to arrive at a BMP plan that all parties will agree upon. In addition, we found that cross-subwatershed coordination and targeting flood season instead of year-round water quality standards could pronouncedly reduce economic cost of BMP implementation while not substantially degrade water quality. The watershed scale optimization method developed here hold the promise serve as an effective tool to explore tradeoffs between economic costs, water quality improvements, and decisions makers and stakeholders’ concerns in BMPs design, thereby informing sustainable watershed scale water resources management.

Qiu, Jiali↗
DOE OSTI2023

Exploring the Complex Chemistry of Uranium within Molten Chloride Salts

Harsh environments represent a unique opportunity to explore new frontiers in chemistry while developing novel tools to meet global needs. Exploring the chemistry of uranium within molten salts is a key example. Actinide chemistry within the highly ionic environment of a molten salt is poorly understood, particularly in the presence of common salt impurities or without active oxidation state control. Delving into this chemistry can provide new insight into actinide and f-electron interactions. Furthermore, expanding our chemical knowledge can also enable advances in and deployment of molten salt reactors or molten salt recycle schemes. Both molten salt applications aim towards providing green, reliable, and equitable energy as well as critical materials for the world. Here the utilization of visible absorbance and Raman spectroscopies to understand and quantify U within chloride-based salt eutectics is discussed. Furthermore, machine learning techniques in the form of chemometric modelling are developed and described, providing advanced analytical tools to quantify and characterize the U present. In conclusion, these tools are then leveraged to monitor and explore the dynamic fundamental chemistry of U within chloride-based salt melts.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

Beyond Optimization: Exploring Novelty Discovery in Autonomous Experiments

Autonomous experiments (AEs) are transforming how scientific research is conducted by integrating artificial intelligence with automated experimental platforms. Current AEs primarily focus on the optimization of a predefined target; while accelerating this goal, such an approach limits the discovery of unexpected or unknown physical phenomena. Here, we introduce a novel framework, INS 2 ANE (Integrated Novelty Score−Strategic Autonomous Non-Smooth Exploration), to enhance the discovery of novel phenomena in autonomous microscopy experimentation. Our method integrates two key components: (1) a novelty scoring system that evaluates the uniqueness of experimental results and (2) a strategic sampling mechanism that promotes exploration of under-sampled regions even if they appear less promising by conventional criteria. We validate this approach on a preacquired data set with a known ground truth comprising of image−spectral pairs. We further implement the process on autonomous scanning probe microscopy experiments. INS 2 ANE significantly increases the diversity of explored phenomena in comparison to conventional optimization routines, enhancing the likelihood of discovering previously unobserved phenomena. These results demonstrate the potential for autonomous microscopy experiments to enhance the scientific discovery by navigating complex experimental spaces to uncover novel phenomena.

Materials↗
DOE OSTI2013

Multiscale simulation of the ground and photo-induced charge-separated states of a molecular triad in polar organic solvent: Exploring the conformations, fluctuations, and free energy landscapes

Here, the approach of a multiscale simulation that combines quantum chemical calculations, classical molecular dynamics simulations, and statistical physics to integrate the information of the electronic states of a conformationally complex molecule into its structural distribution over an ensemble was performed to understand the influence of a polar organic solvent on the structural stability of carotene-porphyrin-fullerene molecular triad in both the ground and the photoinduced charge-separated excited states. The excited states of the triad were computed with the ab initio quantum chemical calculations using the algebraic diagrammatic construction through the second order correction (ADC(2)) method and the time-dependent density functional theory (TDDFT). The replica exchange molecular dynamics was used for the enhanced sampling of the ensemble in order to explore the phase space of the ground state and the photoinduced charge-separated excited state of triad in explicit tetrahydrofuran (THF) solvent. An importance sampling was strategically employed to bridge the gap between the two computational methods that aim to explore distinct realms of dynamics. We analyzed the free energy landscape, the structural fluctuations, the solvent arrangements, the static dielectric constant, and the interactions between the triad and the solvent molecules. The analysis of the free energy landscape of the triad indicates that the charge-separated excited state of the triad is thermodynamically stable in a linearly extended geometry, while the ground-state triad explores several extended and bent conformations that are populated in the local free energy minima separated by low free energy barriers at an order of thermal fluctuation (kBT). The stabilization of a linearly extended structure of the charge-separated excited state triad is predominantly due to the solvation interactions (van der Waals and electrostatic interactions) between the triad and the THF molecules as well as the interactions within the THF molecules. Differences in the charge distribution on a molecular triad induce slight changes in the dielectric property of THF near the triad. Our study suggests that by measuring the differences in a dielectric response of solvent near the triad, it is possible to provide insight into the population of the charge-separated electronic state of the triad relative to that of the ground state.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Deep reaction network exploration at a heterogeneous catalytic interface

Characterizing the reaction energies and barriers of reaction networks is central to catalyst development. However, heterogeneous catalytic surfaces pose several unique challenges to automatic reaction network characterization, including large sizes and open-ended reactant sets, that make ad hoc network construction the current state-of-the-art. Here, we show how automated network exploration algorithms can be adapted to the constraints of heterogeneous systems using ethylene oligomerization on silica-supported single-site Ga 3+ as a model system. Using only graph-based rules for exploring the network and elementary constraints based on activation energy and size for identifying network terminations, a comprehensive reaction network is generated and validated against standard methods. The algorithm (re)discovers the Ga-alkyl-centered Cossee-Arlman mechanism that is hypothesized to drive major product formation while also predicting several new pathways for producing alkanes and coke precursors. These results demonstrate that automated reaction exploration algorithms are rapidly maturing towards general purpose capability for exploratory catalytic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

SANE: strategic autonomous non-smooth exploration for multiple optima discovery in multi-modal and non-differentiable black-box functions

Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and multimodal parameter spaces, such as phase diagrams of Hamiltonians with multiple interactions, composition spaces of combinatorial libraries, material structure image spaces, and molecular embedding spaces. Often these systems are black-boxes and time-consuming to evaluate, which resulted in strong interest towards active learning methods such as Bayesian optimization (BO). However, these systems are often noisy which make the black box function severely multi-modal and non-differentiable, where a vanilla BO can get overly focused near a single or faux optimum, deviating from the broader goal of scientific discovery. To address these limitations, here we developed Strategic Autonomous Non-Smooth Exploration (SANE) to facilitate an intelligent Bayesian optimized navigation with a proposed cost-driven probabilistic acquisition function to find multiple global and local optimal regions, avoiding the tendency to becoming trapped in a single optimum. To distinguish between a true and false optimal region due to noisy experimental measurements, a human (domain) knowledge driven dynamic surrogate gate is integrated with SANE. We implemented the gate-SANE into pre-acquired piezoresponse spectroscopy data of a ferroelectric combinatorial library with high noise levels in specific regions, and piezoresponse force microscopy (PFM) hyperspectral data. SANE demonstrated better performance than classical BO to facilitate the exploration of multiple optimal regions and thereby prioritized learning with higher coverage of scientific values in autonomous experiments. Our work showcases the potential application of this method to real-world experiments, where such combined strategic and human intervening approaches can be critical to unlocking new discoveries in autonomous research.

Biswas, Arpan [University of Tennessee, Knoxville,↗
DOE OSTI2016

Exploring the free energy surface using ab initio molecular dynamics

Efficient exploration of the configuration space and identification of metastable structures are challenging from both computational as well as algorithmic perspectives. Here, we extend the recently proposed orderparameter aided temperature accelerated sampling schemes to efficiently and systematically explore free energy surfaces, and search for metastable states and reaction pathways within the framework of density functional theory based molecular dynamics. The sampling method is applied to explore the relevant parts of the configuration space in prototypical materials SiO 2 and Ti to identify the different metastable structures corresponding to different phases in these materials. In addition, we use the string method in collective variables to study the melting pathways in the high pressure cotunnite phase of SiO 2 and the hcp to fcc phase transition in Ti.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2012

MID-INFRARED SELECTION OF ACTIVE GALACTIC NUCLEI WITH THE WIDE-FIELD INFRARED SURVEY EXPLORER. I. CHARACTERIZING WISE-SELECTED ACTIVE GALACTIC NUCLEI IN COSMOS

The Wide-field Infrared Survey Explorer (WISE) is an extremely capable and efficient black hole finder. We present a simple mid-infrared color criterion, W1 - W2 {>=} 0.8 (i.e., [3.4]-[4.6] {>=}0.8, Vega), which identifies 61.9 {+-} 5.4 active galactic nucleus (AGN) candidates per deg{sup 2} to a depth of W2 {approx} 15.0. This implies a much larger census of luminous AGNs than found by typical wide-area surveys, attributable to the fact that mid-infrared selection identifies both unobscured (type 1) and obscured (type 2) AGNs. Optical and soft X-ray surveys alone are highly biased toward only unobscured AGNs, while this simple WISE selection likely identifies even heavily obscured, Compton-thick AGNs. Using deep, public data in the COSMOS field, we explore the properties of WISE-selected AGN candidates. At the mid-infrared depth considered, 160 {mu}Jy at 4.6 {mu}m, this simple criterion identifies 78% of Spitzer mid-infrared AGN candidates according to the criteria of Stern et al. and the reliability is 95%. We explore the demographics, multiwavelength properties and redshift distribution of WISE-selected AGN candidates in the COSMOS field.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

BGC Atlas: a web resource for exploring the global chemical diversity encoded in bacterial genomes

Secondary metabolites are compounds not essential for an organism’s development, but provide significant ecological and physiological benefits. These compounds have applications in medicine, biotechnology and agriculture. Their production is encoded in biosynthetic gene clusters (BGCs), groups of genes collectively directing their biosynthesis. The advent of metagenomics has allowed researchers to study BGCs directly from environmental samples, identifying numerous previously unknown BGCs encoding unprecedented chemistry. Here, we present the BGC Atlas (https://bgc-atlas.cs.uni-tuebingen.de), a web resource that facilitates the exploration and analysis of BGC diversity in metagenomes. The BGC Atlas identifies and clusters BGCs from publicly available datasets, offering a centralized database and a web interface for metadata-aware exploration of BGCs and gene cluster families (GCFs). We analyzed over 35 000 datasets from MGnify, identifying nearly 1.8 million BGCs, which were clustered into GCFs. The analysis showed that ribosomally synthesized and post-translationally modified peptides are the most abundant compound class, with most GCFs exhibiting high environmental specificity. We believe that our tool will enable researchers to easily explore and analyze the BGC diversity in environmental samples, significantly enhancing our understanding of bacterial secondary metabolites, and promote the identification of ecological and evolutionary factors shaping the biosynthetic potential of microbial communities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Exploring experimental conditions to reduce uncertainties in the optical potential

Uncertainty quantification for nuclear theories has gained a more prominent role in the field, with more groups attempting to understand the uncertainties in their calculations. However, recent studies have shown that the uncertainties on the optical potentials are too large for the theory to be useful. The goal of this work is to explore possible experimental conditions that may reduce the uncertainties on elastic scattering and single-nucleon transfer cross sections that come from the fitting of the optical model parameters to experimental data. Using Bayesian methods, we explore the effect of the uncertainties of optical model parameters on the angular grid of the differential cross section, including cross-section data at nearby energies, and changes in the experimental error bars. We also study the effect on the resulting uncertainty when other observables are included in the fitting procedure, particularly the total (reaction) cross sections. We study proton and neutron elastic scattering on 48 Ca and 208 Pb. We explore the parameter space with the Markov-chain Monte Carlo method, produce posterior distributions for the optical model parameters, and construct the corresponding 95% confidence intervals on the elastic-scattering cross sections. We also propagate the uncertainties on the optical potentials to the 48 Ca(d,p) 49 Ca(g.s.) and 208 Pb(d,p) 209 Pb(g.s.) cross sections. We find little sensitivity to the angular grid and an improvement of up to a factor of 2 on the uncertainties by including data at a nearby energy. Although reducing the error bars on the data does reduce the uncertainty, the gain is often considerably smaller than one would naively expect. We also find that the inclusion of total reaction cross section can improve the uncertainty although the magnitude of the effect depends strongly on the cases considered.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

A Critical Exploration of the Efficiency Impacts of Demand Response From HVAC in Commercial Buildings

Increasing quantities of renewable energy generation has yielded a need for greater energy storage capacity in power systems. Thermal storage in variable air volume (VAV) heating, ventilation, and air conditioning (HVAC) in commercial buildings has been identified as an inexpensive source of grid storage, but the true costs are not known. Recent literature explores the inefficiency associated with providing grid services from these HVAC-based demand response (DR) resources by employing a battery analogy to calculate round-trip efficiency (RTE). Results vary significantly across studies and in some cases reported efficiencies are strikingly low. This article has three objectives to address these prior results. First, we synthesize and expand on insights into existing literature by systematically exploring the potential causes for the discrepancies in results. We reinforce previous work indicating baseline modeling may drive differences across studies and deduce that control accuracy plays a role in the major differences between experiments and simulation. Second, we discuss why the RTE metric is problematic for DR applications, discuss another proposed metric, additional energy consumption (AEC), and propose an extension, which we call uninstructed energy consumption (UEC), to evaluate DR performance. Finally, we explore the merits of different metrics using experimental data and highlight UEC's reduced sensitivity to the characteristics of the DR signal than previously proposed metrics.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

A Visual Analytics Paradigm Enabling Trillion-Edge Graph Exploration

We present a visual analytics paradigm and a system prototype for exploring web-scale graphs. A web-scale graph is described as a graph with ~one trillion edges and ~50 billion vertices. While there is an aggressive R&D effort in processing and exploring web-scale graphs among internet vendors such as Facebook and Google, visualizing a graph of that scale still remains an underexplored R&D area. The paper describes a nontraditional peek-and-filter strategy that facilitates the exploration of a graph database of unprecedented size for visualization and analytics. We demonstrate that our system prototype can 1) preprocess a graph with ~25 billion edges in less than two hours and 2) support database query and visualization on the processed graph database afterward. Based on our computational performance results, we argue that we most likely will achieve the one trillion edge mark (a computational performance improvement of 40 times) for graph visual analytics in the near future.

graph visualization↗
DOE OSTI2022

Information-Theoretic Exploration of Multivariate Time-Varying Image Databases

Modern scientific simulations produce very large datasets, making interactive exploration of such data computationally prohibitive. An increasingly common data reduction technique is to store visualizations and other data extracts in a database. The Cinema project is one such approach, storing visualizations in an image database for post hoc exploration and interactive image-based analysis. This work focuses on developing efficient algorithms that can quantify various types of multivariate dependencies existing within multi-variable datasets. It applies specific mutual information measures for the quantification of salient regions from multivariate image data. Here, using such information measures, the opacity of the images is modulated so that the salient regions are automatically highlighted and the domain scientists can interactively explore the most relevant regions for scientific discovery.

97 MATHEMATICS AND COMPUTING↗