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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Willingness to Consider Pooled Rideshare?: An Exploratory Study on Influential Factors

Rideshare use has grown significantly, beginning with solo riders and evolving to pooled rideshare. Pooled rideshare involves sharing a ride with stranger(s). Despite the growth in rideshare services worldwide, the use of pooled rideshare in the U.S. is relatively low within all rideshare trips and compared to other forms of transportation, e.g., driving one's personal vehicle. A national survey of 5,385 individuals was conducted to identify factors influencing riders' willingness to consider pooled rideshare. Exploratory and confirmatory factor analyses were performed. The survey results indicated five factors: service experience, time/cost, traffic/environment, privacy, and safety. Understanding these factors is crucial for the future of dynamic ridesharing services in the U.S.

Su, Haotian↗
NASA NTRS1981

AgRISTARS: Foreign commodity production forecasting. The 1980 US corn and soybeans exploratory experiment

The U.S. corn and soybeans exploratory experiment is described which consisted of evaluations of two technology components of a production forecasting system: classification procedures (crop labeling and proportion estimation at the level of a sampling unit) and sampling and aggregation procedures. The results from the labeling evaluations indicate that the corn and soybeans labeling procedure works very well in the U.S. corn belt with full season (after tasseling) LANDSAT data. The procedure should be readily adaptable to corn and soybeans labeling required for subsequent exploratory experiments or pilot tests. The machine classification procedures evaluated in this experiment were not effective in improving the proportion estimates. The corn proportions produced by the machine procedures had a large bias when the bias correction was not performed. This bias was caused by the manner in which the machine procedures handled spectrally impure pixels. The simulation test indicated that the weighted aggregation procedure performed quite well. Although further work can be done to improve both the simulation tests and the aggregation procedure, the results of this test show that the procedure should serve as a useful baseline procedure in future exploratory experiments and pilot tests.

Malin, J. T.↗
NASA NTRS2003

HUMEX, a study on the survivability and adaptation of humans to long-duration exploratory missions, part I: lunar missions

The European Space Agency has recently initiated a study of the human responses, limits and needs with regard to the stress environments of interplanetary and planetary missions. Emphasis has been laid on human health and performance care as well as advanced life support developments including bioregenerative life support systems and environmental monitoring. The overall study goals were as follows: (i) to define reference scenarios for a European participation in human exploration and to estimate their influence on the life sciences and life support requirements; (ii) for selected mission scenarios, to critically assess the limiting factors for human health, wellbeing, and performance and to recommend relevant countermeasures; (iii) for selected mission scenarios, to critically assess the potential of advanced life support developments and to propose a European strategy including terrestrial applications; (iv) to critically assess the feasibility of existing facilities and technologies on ground and in space as testbeds in preparation for human exploratory missions and to develop a test plan for ground and space campaigns; (v) to develop a roadmap for a future European strategy towards human exploratory missions, including preparatory activities and terrestrial applications and benefits. This paper covers the part of the HUMEX study dealing with lunar missions. A lunar base at the south pole where long-time sunlight and potential water ice deposits could be assumed was selected as the Moon reference scenario. The impact on human health, performance and well being has been investigated from the view point of the effects of microgravity (during space travel), reduced gravity (on the Moon) and abrupt gravity changes (during launch and landing), of the effects of cosmic radiation including solar particle events, of psychological issues as well as general health care. Countermeasures as well as necessary research using ground-based test beds and/or the International Space Station have been defined. Likewise advanced life support systems with a high degree of autonomy and regenerative capacity and synergy effects were considered where bioregenerative life support systems and biodiagnostic systems become essential. Finally, a European strategy leading to a potential European participation in future human exploratory missions has been recommended. c2003 COSPAR. Published by Elsevier Ltd. All rights reserved.

Moon↗
NASA NTRS2012

Exploratory Climate Data Visualization and Analysis Using DV3D and UVCDAT

Earth system scientists are being inundated by an explosion of data generated by ever-increasing resolution in both global models and remote sensors. Advanced tools for accessing, analyzing, and visualizing very large and complex climate data are required to maintain rapid progress in Earth system research. To meet this need, NASA, in collaboration with the Ultra-scale Visualization Climate Data Analysis Tools (UVCOAT) consortium, is developing exploratory climate data analysis and visualization tools which provide data analysis capabilities for the Earth System Grid (ESG). This paper describes DV3D, a UV-COAT package that enables exploratory analysis of climate simulation and observation datasets. OV3D provides user-friendly interfaces for visualization and analysis of climate data at a level appropriate for scientists. It features workflow inte rfaces, interactive 40 data exploration, hyperwall and stereo visualization, automated provenance generation, and parallel task execution. DV30's integration with CDAT's climate data management system (COMS) and other climate data analysis tools provides a wide range of high performance climate data analysis operations. DV3D expands the scientists' toolbox by incorporating a suite of rich new exploratory visualization and analysis methods for addressing the complexity of climate datasets.

Maxwell, Thomas↗
NASA NTRS2014

CLEANing the Reward: Counterfactual Actions to Remove Exploratory Action Noise in Multiagent Learning

Learning in multiagent systems can be slow because agents must learn both how to behave in a complex environment and how to account for the actions of other agents. The inability of an agent to distinguish between the true environmental dynamics and those caused by the stochastic exploratory actions of other agents creates noise in each agent's reward signal. This learning noise can have unforeseen and often undesirable effects on the resultant system performance. We define such noise as exploratory action noise, demonstrate the critical impact it can have on the learning process in multiagent settings, and introduce a reward structure to effectively remove such noise from each agent's reward signal. In particular, we introduce Coordinated Learning without Exploratory Action Noise (CLEAN) rewards and empirically demonstrate their benefits

Reinforcement Learning↗
DOE OSTI2025

Ground-Truthing: Exploratory Borehole Characterization and Modeling to Verify and Expand Techno-Economic Evaluation of Earth Source Heat at Cornell U

This report documents the successful completion of DOE award DE-EE0009255: Ground- Truthing: Exploratory Borehole Characterization and Modeling to Verify and Expand Techno- Economic Evaluation of Earth Source Heat at Cornell University . Cornell University is evaluating the technical and economic feasibility of using deep direct-use (DDU) geothermal energy, referred to locally as Earth Source Heat (ESH), to serve as a renewable energy source for campus heating. To meet this objective, Cornell drilled an approximately 3-kilometer-deep exploratory borehole: the Cornell University Borehole Observatory (CUBO), or ESH-1. The team conducted an extensive suite of geophysical, hydrologic, thermal, mechanical, and geochemical measurements to evaluate subsurface conditions and geothermal development potential. This report summarizes the well drilling and testing tasks, findings, and conclusions.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Using feature importance as an exploratory data analysis tool on Earth system models

Abstract. Machine learning (ML) models are commonly used to generate predictions, but these models can also support the discovery of new science. Generating accurate predictions necessitates that a model captures the structure of the underlying data. If the structure is properly extracted, ML could be a useful exploratory and evidential tool. In this paper, we present a case study that demonstrates the use of ML for exploratory data analysis (EDA) in the climate space. We apply the ML explainability method of spatiotemporal zeroed feature importance (stZFI) to understand how climate-variable associations evolve over space and time. Our analyses focus on data from ensembles of Earth system models (ESMs) which provide data on different climate states and conditions. We elect to work with ESM ensembles since they allow us to compare feature importance across alternative scenarios not available with observed data. The ensembles also account for natural variability so that we can distinguish between signal and noise due to natural climate variability when computing feature importance. The use of perturbed initial condition ensembles introduces variability mimicking the natural variability in the atmosphere; thus the signals emerging using feature importance (FI) can be evaluated against the natural variability in the climate system. For our analyses, we consider the 1991 volcanic eruption of Mount Pinatubo, which was a large stratospheric aerosol injection. We explore the climate pathway associated with the eruption from aerosols to radiation to temperature at both the near-surface and stratospheric levels. In addition to applying the method to data generated from two different ESMs, we apply stZFI to reanalysis data to compare the associations identified by stZFI. We show how stZFI tracks the importance of aerosol optical depth over time on forecasting temperatures. This case study illustrates usefulness of an ML tool (stZFI) for EDA on a well-studied climate exemplar.

Ries, Daniel (ORCID:0000000250294647)↗
NASA NTRS1999

Measurements of Acidic Gases and Aerosol Species Aboard the NASA DC-8 Aircraft During the Pacific Exploratory Mission in the Tropics (PEM-Tropics A)

We received funding to provide measurements of nitric acid (HNO3), formic acid (HCOOH), acetic acid (CH3COOH), and the chemical composition of aerosols aboard the NASA Ames DC-8 research aircraft during the PEM-Tropics A mission. These measurements were successfully completed and the final data resides in the electronic archive (ftp-gte.larc.nasa.gov) at NASA Langley Research Center. For the PEM-Tropics A mission the University of New Hampshire group was first author of four different manuscripts. Three of these have now appeared in the Journal of Geophysical Research-Atmospheres, included in the two section sections on PEM-Tropics A. The fourth manuscript has just recently been submitted to this same journal as a stand alone paper. All four of these papers are included in this report. The first paper (Influence of biomass combustion emissions on the distribution of acidic trace gases over the Southern Pacific basin during austral springtime) describes the large-scale distributions of HNO3, HCOOH, and CH3COOH. Arguments were presented to show, particularly in the middle tropospheric region, that biomass burning emissions from South America and Africa were a major source of acidic gases over the South Pacific basin. The second paper (Aerosol chemical composition and distribution during the Pacific Exploratory Mission (PEM) Tropics) covers the aerosol aspects of our measurement package. Compared to acidic gases, O3, and selected hydrocarbons, the aerosol chemistry showed little influence from biomass burning emissions. The data collected in the marine boundary layer showed a possible marine source of NH3 to the troposphere in equatorial areas. This source had been speculated on previously, but our data was the first collected from an airborne platform to show its large-scale features. The third paper (Constraints on the age and dilution of Pacific Exploratory Mission-Tropics biomass burning plumes from the natural radionuclide tracer Pb-210) utilized the unexpectedly high concentrations of Pb-210 in the combustion plumes to estimate their ages and mixing along the transport route to the South Pacific basin. The final paper in the group (Tropospheric reactive-odd nitrogen over the South Pacific in austral springtime). This paper provides a summary of reactive nitrogen during PEM-Tropics A, with HNO3 and PAM showing the most impact from combustion emission.

Talbot, Robert W.↗
DOE OSTI2023

Wind turbine main bearing rating lives as determined by IEC 61400‐1 and ISO 281: A critical review and exploratory case study

Abstract This paper studies the rating lives of wind turbine main bearings, as determined by the IEC 61400‐1 and ISO 281 standards. A critical review of relevant bearing life theory and turbine design requirements is provided, including discussion on possible shortcomings such as the existence (or not) of the bearing fatigue load limit and the validity of assuming linear damage accumulation. A detailed exploratory case study is then undertaken to determine rating lives for two models of main bearing in a 1.5 MW wind turbine. Rating life assessment is carried out under different conditions, including various combinations of main bearing temperature, wind field characteristics, lubricant viscosity, and contamination levels. Rating lives are found to be sufficiently above the desired 20‐year design life for both bearing models under expected operating conditions. For the larger bearing, operational loads are shown to be below or close to the bearing fatigue load limit a vast majority of the time. Key sensitivities for rating life values are temperature and contamination. Overall, the results of this study suggest that an ISO 281 rating life assessment does not account for reported rates of main bearing failures in 1 to 3 MW wind turbines. It is recommended that a similar analysis be undertaken for ISO/TS 16281 rating lives, along with further efforts to identify principal root causes of main bearing failures in future work, possibly leading to a new application standard specific to this component. It is also recommended that the impacts of partial wake impingement on main bearing rating lives are investigated.

17 WIND ENERGY↗
DOE OSTI2023

Exploratory analysis of machine learning techniques in the Nevada geothermal play fairway analysis

Play fairway analysis (PFA) is commonly used to generate geothermal potential maps and guide exploration studies, with a particular focus on locating and characterizing blind geothermal systems. This study evaluates the application of machine learning techniques to PFA in the Great Basin region of Nevada. Following the evaluation of various techniques, we identified two approaches to PFA that produced promising results, 1) supervised Bayesian probabilistic neural networks to generate geothermal potential maps with confidence intervals, and 2) unsupervised principal component analysis paired with k-means clustering to generate both cluster maps to help identify spatial patterns, as well as new combined feature inputs. We applied these techniques to perform a comparative analysis between two principal sets of geological and geophysical features related to permeability and heat and a set of positive (known geothermal resources) and negative training sites (known drill sites with unsuitable geothermal conditions). We found that these methods constrain previously unrecognized feature controls on geothermal favorability, many of which are spatially organized within the extent of cluster groups and the major structural-hydrologic domains of the study area. Furthermore, we utilized exploratory unsupervised modeling to highlight spatial relationships between input data and predictive output results of our supervised modeling. As a result, we demonstrate how our models compare to the previous Nevada PFA and how the rapid insights these machine learning techniques offer may support future assessments of both known and undiscovered blind geothermal systems in the Great Basin region of Nevada and beyond.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Exploratory calculation of 𝐾 L → 𝜇 + ⁢𝜇 − decay from lattice QCD at physical pion mass

We compute the complex, long-distance two-photon-exchange amplitude which contributes to the rare 𝐾 L → 𝜇 + ⁢𝜇 − decay from lattice QCD. We use a 24 3 × 64 physical-pion-mass gauge field ensemble at an inverse lattice spacing of 1.023 GeV and a QED ∞ -based formalism. Our implementation strategies for all five non-SU(3)-flavor-suppressed diagram topologies are given in detail. We achieve a 25% statistical precision on the dispersive part of this long-distance amplitude. This calculation is carried out with 2+1 quark flavors and therefore requires the addition of counterterms to compensate for the absence of the Glashow-Iliopoulos-Maiani mechanism. These counterterms are not included in the current calculation and will be the subject of a second paper. Although a direct comparison to experiment cannot yet be made because of those omitted counterterms, the present exploratory calculation allows one to identify principal sources of statistical uncertainty in this calculation. The precision of our results is limited by the reconstruction of the physical contribution of the 𝜂 intermediate state, for which various strategies are tested and compared.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Exploratory Precipitation Metrics: Spatiotemporal Characteristics, Process-Oriented, and Phenomena-Based

Abstract Precipitation sustains life and supports human activities, making its prediction one of the most societally relevant challenges in weather and climate modeling. Limitations in modeling precipitation underscore the need for diagnostics and metrics to evaluate precipitation in simulations and predictions. While routine use of basic metrics is important for documenting model skill, more sophisticated diagnostics and metrics aimed at connecting model biases to their sources and revealing precipitation characteristics relevant to how model precipitation is used are critical for improving models and their uses. This paper illustrates examples of exploratory diagnostics and metrics including 1) spatiotemporal characteristics metrics such as diurnal variability, probability of extremes, duration of dry spells, spectral characteristics, and spatiotemporal coherence of precipitation; 2) process-oriented metrics based on the rainfall–moisture coupling and temperature–water vapor environments of precipitation; and 3) phenomena-based metrics focusing on precipitation associated with weather phenomena including low pressure systems, mesoscale convective systems, frontal systems, and atmospheric rivers. Together, these diagnostics and metrics delineate the multifaceted and multiscale nature of precipitation, its relations with the environments, and its generation mechanisms. The metrics are applied to historical simulations from phases 5 and 6 of the Coupled Model Intercomparison Project. Models exhibit diverse skill as measured by the suite of metrics, with very few models consistently ranked as top or bottom performers compared to other models in multiple metrics. Analysis of model skill across metrics and models suggests possible relationships among subsets of metrics, motivating the need for more systematic analysis to understand model biases for informing model development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Exploratory Analysis of Offshore CO 2 Storage Pilot Project in the Gulf of Mexico: Geologic, Infrastructure, and Cost Considerations

This analysis employs a high-level exploratory analytical approach to quantify various considerations needed for a potential CCS pilot project in the GOM, most notably the cost magnitude to develop an offshore pilot project. The scope of this analysis focuses on CO 2 storage in saline formations presented in two specific scenarios: parts of GOM Outer Continental Shelf (OCS) federal waters and Texas state waters.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

An Exploratory Data Mining Investigation for Constructing a Publicly Sourced Dataset of Foreign Hypersonic Tests

This document details a data mining exercise that resulted in an exploratory dataset of publicly reported foreign (non-US) hypersonic vehicle test events. Using a combination of targeted English language searches and country-specific queries, the study aggregates information from digital news media, official press releases, and social media posts. The resulting list of events captures the publicly available accounts of foreign hypersonic tests, although it does not represent an exhaustive record. Limitations such as inconsistent reporting, translation challenges, and the inherently provisional nature of open-source data are acknowledged. This dataset serves as an initial reference point for further inquiries into high-speed atmospheric phenomena and may facilitate future efforts to correlate these events with geophysical measurements.

33 ADVANCED PROPULSION SYSTEMS↗