Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “explorer”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,369 records · Page 76

NPD Classification Tools – User Guide NPD Explorer and NPDamCAT Apps

The existing infrastructure at non-powered dams (NPDs) presents a variety of opportunities from generating electricity and economic value to the myriad services they provide. However, it also presents a significant challenge because aging structures must be maintained, and changes to the ecosystems and river systems by NPDs must be managed. The various stakeholders interested in these opportunities and challenges require varying information about NPDs; in many cases, interest in NPDs can extend across the entire population of dams. Even when interest is more narrowly focused on an individual dam or a small subset of dams, understanding how these dams relate to the broader context of NPD infrastructure can be important. As noted in TM 2021/2155, “Each NPD has unique characteristics describing its design, operation, environmental impacts, social impacts, and economic potential. The large number of dams, the diversity of interests related to dams, the variety of dam characteristics, and the types of data required to describe dams all pose major challenges to an analysis of the entire dam population." This user guide describes two web-based tools that facilitate exploration of dams from a variety of perspectives: the NPD Explorer and the NPD Custom Analysis and Taxonomy (NPDamCAT). These tools facilitate access to information about dams and help users interact with the information, making small- to large-scale analyses more convenient for a broad set of stakeholders.

13 HYDRO ENERGY↗

RPD Explorer

The RPD Explorer is an interactive, spreadsheet-based tool for examining the data tables in the Requirements and Planning Document (RPD). This tool is based on the P&PD Explorer.

97 MATHEMATICS AND COMPUTING↗

Exploration of groundwater and geothermal characteristics of Tohatchi Hot Springs aquifer at local and regional scales

Objective: Aquifer sustainability for geothermal resources exploration of Tohatchi Hotsprings, New Mexico. Tasks: (1) Generate 3D numerical models using PFLOTRAN to explore the geothermal resources in the Tohatchi spring aquifer and its contiguous areas and (2) estimate the sustainability of the aquifer for future geothermal resource development.

54 ENVIRONMENTAL SCIENCES↗

Enabling Floating Solar Photovoltaic (FPV) Deployment: Exploring the Operational Benefits of Floating Solar-Hydropower Hybrids

The Southeast (SE) Asia region is undergoing rapid energy sector transitions and exploring the potential role of renewables - including solar photovoltaics (PV) - as it becomes increasingly competitive as a result of technological advances and falling capital costs. Low-cost solar PV provides countries in the region with an option to meet increasing energy demand and diversify generation portfolios, complementing hydropower and thermal-dominant systems and strengthening energy security throughout the region. Floating solar PV (FPV) has emerged as an attractive application of solar PV that allows for systems to be floated on water bodies. Pairing FPV in hybrid systems with hydropower may also provide significant value for power systems in the region, beyond oft-cited co-benefits of stand-alone FPV. Despite growing interest in FPV systems, few applications of hybrid FPV-hydropower systems exist in SE Asia, and limited information is available about the co-benefits these systems may provide for potential adopters. This work, funded by the U.S. Agency for International Development (USAID) through the Advanced Energy Partnership for Asia, explores the value that hybrid FPV-hydropower systems may provide to the power systems of SE Asian countries. This work on the value of hybrid FPV-hydropower systems is accompanied by a recent report, Creating an Enabling Policy and Regulatory Environment for Floating Solar Photovoltaics: Review of Barriers to FPV Deployment in Southeast Asia, also focused on SE Asia.

14 SOLAR ENERGY↗

Exploring New Ways to Classify Industries for Energy Analysis and Modeling

As the US moves closer to embracing a net zero greenhouse gas emissions position, combustion processes outside the power sector are becoming urgent concerns. Industry is an important end user of energy and relies on fossil fuels used directly for process heating and as feedstocks for a diverse range of applications. Fuel and energy use by industry is heterogeneous, meaning that even a single product group can vary broadly in its production routes and associated energy usage. In the US, the North American Industry Classification System (NAICS) serves as the basis for data collection and reporting. In turn, data based on NAICS is the foundation of most US energy modeling. Thus, the effectiveness of NAICS at representing energy use is a limiting condition for plans to improve energy efficiency and alternatives to fossil fuels in industry. Facility-level data to build more detail into heterogeneous sectors is scarce. This work explores alternative classification schemes for industry based on energy use characteristics, and provides a validation of an approach to make facility-level energy use estimates based on publicly available data from the greenhouse gas reporting program. First, several approaches to industrial taxonomies and their usefulness for industrial energy modeling are summarized. Data from Industrial Assessment Centers is analyzed using unsupervised machine learning techniques to detect clusters. Cladistics, an approach from biology, is adapted to energy and process characteristics of industries. A cladogram is presented for evolutionary directions in the iron and steel sector. Cladograms are a promising tool for constructing scenarios and summarizing directions of sectoral innovation. Finally, validation is performed for facility-level energy estimates from the US EPA Greenhouse Gas Reporting Program. This validation assists in making this data source available for use in energy modeling. Together, this work explores alternative approaches for categorizing industries in a way that aids understanding energy use, and presenting pathways for the future.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Kilopower - Powering the Future of Space Exploration [Poster]

The Kilopower Project was initiated by NASA’s Space Technology Mission Directorate to demonstrate subsystem-level technology readiness of small space fission power in a relevant environment (TRL 5) for space science and human exploration power needs. The Kilopower Project centerpiece is the Kilowatt Reactor Using Stirling Technology (KRUSTY) test, which consists of the development and testing of a ground technology demonstrator of a 1 kWe class fission power system. The technologies to be developed and validated by KRUSTY are extensible to space fission power systems from 1 to 10 kWe, which can enable modular surface fission power systems for human exploration, as well as higher power future potential deep space science missions.

42 ENGINEERING↗

ALP Experiment Sensitivity Exploration (Preliminary Findings)

This report presents an exploration of sensitivity estimates for multiple prominent proposed techniques to search for axion-like particles (ALPs). The sensitivities are plotted over particle mass ($m_a$) and coupling ($g_{aγγ}$) parameter space. Explorations include variation over detector type, integration time, background cosmology, and size of the apparatus.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Innovative Subsurface Learning and Hawaiian Exploration using Advanced Tomography (ISLAND HEAT) Phase 1 (Final Report)

The Innovative Subsurface Learning and Hawaiian Exploration using Advanced Tomography (ISLAND HEAT) project aims to leverage and enhance existing Hawai'i geothermal play fairway analysis (PFA) results and validate a conceptual model-driven, optimized, least-cost exploration and geophysical suite at a proven geothermal field with known permeability, the Puna Geothermal Venture, located in the Lower East Rift Zone. The abundance of geophysical scrutinization before, during, and after the 2018 Kilauea eruption at and around the broader Puna system offers a rare opportunity to elucidate geophysical expressions within a dynamic magmatic rift setting. Development of the methodology continues with its application at a second prospective site identified by the PFA, Mauna Kea, which serves as confirmation of the integrated approach.

15 GEOTHERMAL ENERGY↗

Nonperturbative Exploration of Near-Conformal Dynamics

This project had three major goals: Explore qheories of composite dark matter and composite Higgs bosons through the work of the Lattice Strong Dynamics (LSD) collaboration.; Extend lattice gauge theories to curved manifolds through the work of the Quantum Finite Elements (QFE) collaboration.; Explore normalizing flow neural networks for producing ensembles of lattice gauge theory configurations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

CubeSat Interplanetary Exploration: A Deep Dive into Nuclear Propulsion and Astrodynamics for Small Satellites

CubeSats are small satellites most commonly used by universities, however, nowadays places like NASA are looking to CubeSats for interplanetary missions. Because of their universal form fit it makes them cost effective, economical, and therefor desirable for deep space. To achieve deep space exploration, we must explore the applications of propulsion and astrodynamics on small satellites. This paper will touch on one scaling Ion and chemical propulsion as well as nuclear kilo reactors. Two choreographing a flight path for these small satellites and lastly designing an efficient cost-effective platform for CubeSats to get to deep space territory.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Exploring the process-structure-property relationship of Aerosol Deposition to phosphor coatings for non-contact thermometry

Full-field, multi-measurand diagnostics provide rich validation data necessary to improve the product life cycle time of nuclear safety components. Thermophosphor digital image correlation (TP+DIC) is a method of simultaneously measuring strain and temperature fields using patterned phosphor coatings deposited with aerosol deposition (AD). While TP+DIC produces a functional diagnostic, the coating’s reproducibility and the effect of the patterned features on the inferred temperature remains uncharacterized. This NSR&D project provided the opportunity to study two areas: 1) the tunability and repeatability of aerosol deposition and 2) the robustness of aerosol deposition phosphor on deforming substrates. The first area explores the process-property relationship of parameters elucidating the significance of each on the coating. The second area explores the relationship between the features’ characteristics (namely thickness) and the phosphor emission and inferred temperature. Together, the results will lead to the improved accuracy and functionality of TP+DIC for qualification testing of nuclear safety components.

36 MATERIALS SCIENCE↗

Climate adaptation and sustainability in switchgrass: exploring plant-microbe-soil interactions across continental scale environmental gradients

Less carbon-intensive energy sources are needed to reduce greenhouse gas emissions and their predicted role in climate change. There is growing interest in the potential of biofuels for meeting this need. A critical question is whether large-scale biofuel production can be sustainable over the time scales needed to mitigate our carbon debt from fossil fuel consumption. The carbon balance and ultimately the sustainability of biofuel feedstock production is the result of complex climate-coupled interactions between carbon fixation, sequestration, and release through combustion. Similarly, the long-term productivity of biofuels depends on the environmental factors limiting plant growth. These factors are often related to soil resources which involve complex interactions at the plant-microbe-soil interface impacting their availability and cycling. Our collaborative project addressed sustainable switchgrass (Panicum virgatum) production by exploring Plant Systems, Plant-Microbiome Interactions, and Ecosystem Processes through the integrating lens of Multi-Scale Modeling. Our research was based on detailed characterization of genetically diverse switchgrass genotypes planted in common gardens across a continental latitudinal gradient. The underlying theme of our Plant Systems research was the use of locally adapted plant material to explore plant function, to understand the mechanistic basis of environmental interactions, and to discover the plant genes important for adaptation and sustainability in the face of climate change. Our Plant-Microbiome Interaction project characterized the microbial communities associated with switchgrass using genomic tools. Our Ecosystem Processes research focused on carbon cycle responses at the ecosystem level using stand level plantings. Finally, our Multi-Scale Modeling helped to define conditions of a sustainable biofuel system and identify key tradeoffs between genetic diversity, productivity, and ecosystem services. Genome-wide association analyses were used to identify alleles that contribute to successful establishment and biomass production across North America. Together, our work provided a baseline analyses of the potential of switchgrass as a biofuel feedstock. Our project resulted in a number of successful outcomes. First, we were successful in collecting switchgrass germplasm across the species range, propagating the material, and establishing common garden experiments across the species range. In collaboration with DOE JGI, we successfully assembled the first tetraploid switchgrass genome and published this resource with an analyses of the genetic basis local adaptation from our gardens (Lowry et al. 2019, Lovell et al. 2021). The gardens were used to characterize the genetic architecture for a number of important plant phenotypes. Our project also conducted extensive sampling and sequencing to characterize the bacterial and fungal associates of switchgrass roots and leaves. We showed that host genotype, location, and harvesting practices can play a role in microbiome assembly (Singer et al. 2019 & 2022, Van Wallendael et al. 2020 & 2022, Edwards et al. 2023). Our ecosystem processes work created baseline dataset of carbon and nutrient cycling in realistic stand plantings of switchgrass. Data from this experiment provided new insight into the role of plant traits, phenology, and local environments in ecosystem processes like soil respiration, net-ecosystem exchange, and dynamics of soil and plant nutrients (Ricketts et al. 2023). Finally, our crop modelling experiments help to characterize the sensitivity of common modeling frameworks to parameters, identify key limiters of productivity across large geographic scales, and leverage patterns of local adaptation in prediction. Ultimately, these studies help to identify critical plant-microbe-soil traits that may be manipulated, through breeding or agronomic management, to improve the sustainability of biofuel feedstocks.

09 BIOMASS FUELS↗

Exploring the Feasibility of INCONEL® ALLOY 740H® for Power Plant Headers: Integrating Machine Learning with Computational Fluid Dynamics (CFD)

This keynote presentation explores the behavior of headers—essential components of pipeline systems—using ANSYS simulation software and machine learning techniques. The study aims to predict the thermal and mechanical performance of headers under diverse conditions through both steady-state and transient simulations. We investigate critical parameters such as heat transfer coefficient, fluid velocity, and temperature to optimize header design. Conducted as part of a DOE project led by NCAT in collaboration with UNC Charlotte, this research encompasses multiple key topics. The initial section focuses on the behavior of header systems under steady-state conditions using ANSYS simulation. It underscores the importance of headers in industrial infrastructure, especially in the energy sector, and examines the implications of material selection and flow direction on heat transfer dynamics. Methodologically, we employ Computational Fluid Dynamics (CFD) analysis through ANSYS, detailing the development of models, material properties, geometry specifications, boundary conditions, and meshing strategies. Our simulations explore various operational parameters, including temperature and mass flow rates, crucial for predicting heat transfer coefficients and enhancing header design. Results from the study include parametric investigations into mesh sensitivity, viscosity model evaluations, and the effects of heat transfer locations, all validated against theoretical calculations. We conclude with insights on mesh optimization, the suitability of viscosity models, and recommendations for future research aimed at improving header system efficiency and sustainability in industrial applications.

20 FOSSIL-FUELED POWER PLANTS↗

Exploring Offshore Regional Atlantic Carbon Storage and Infrastructure for Eastern USA (Supporting Communities and Industry for Mid-Atlantic Offshore Carbon Storage Hub)

This final technical report presents a summary of work completed for the project Supporting Communities and Industry for Mid-Atlantic Offshore Carbon Storage Hub (FE0032407), which has been designated EXPLORE-ACS (Exploring Potential Long-Term Offshore Regional Atlantic Carbon Storage). The project is part of the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL) funding opportunity announcement 2799 for Regional Initiatives to Accelerate Carbon Capture, Utilization, and Storage (CCUS) Deployment. The objective of the DOE 2799 program is to identify and address the challenges facing commercial deployment of carbon capture, transport, and storage in specific regions of the United States.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Bayesian Exploration and Surrogate Emulation of Nonlinear Beam-Response Geometry in the LBNF Beamline

Next-generation long-baseline neutrino experiments aim to achieve multi-MW proton beam power while reducing accelerator-induced systematic uncertainties. At Fermilab, the LBNF beamline is designed for 1.2 MW operation with PIP-II and is upgradeable to 2.4 MW. DUNE will probe the three-flavor neutrino paradigm and search for CP violation, requiring precise neutrino-flux normalization and improved control of accelerator-related uncertainties. Within the LBNF beamline, the System for On-Axis Neutrino Detection (SAND) will constrain flux uncertainties using precision near-detector measurements, while the Muon Monitor System (MuMS) will provide beamline diagnostics sensitive to the proton beam, target, and horn configuration. However, the pion phase space relevant for DUNE depends simultaneously on many correlated parameters, including beam centroid, beam width, horn current and alignment, target position, optics shifts, and radiation-induced changes. Consequently, MuMS observables exhibit nonlinear and coupled responses that are difficult to characterize using traditional one-parameter scans. To address this challenge, we are developing a Bayesian Exploration framework coupled to physics-informed surrogate emulators trained on Geant4 beamline simulations. Gaussian-process emulators provide both fast predictions and uncertainty estimates, enabling adaptive selection of new simulation points in beam-parameter space. As an initial demonstration, we construct surrogate emulators for MuMS response observables using a verified simulation campaign spanning proton-beam steering conditions. The emulators reproduce the simulated dependence of MuMS centroid and gradient observables while providing predictive uncertainties, and serve as the foundation for future multidimensional exploration including beam width, horn current, and additional beamline parameters. This work establishes a framework for uncertainty-aware beam monitoring, adaptive simulation campaigns, and rapid beam-response inference for future DUNE operations.

Ganguly, Sudeshna [Fermilab] (ORCID:00000003163482↗

A Full-Stack Exploration of Language-Based Parallelism in Fortran 2023

This poster explores native parallel features in Fortran 2023 through the lens of supporting applications with libraries, compilers, and parallel runtimes. The language revision informally named Fortran 2008 introduced parallelism in the form of Single Program Multiple Data (SPMD) execution with two broad feature sets: (1) loop-level parallelism via do concurrent and (2) a Partitioned Global Address Space (PGAS) comprised of distributed “coarray” data structures. Fortran’s native parallelism has demonstrated high performance [1] and reduced the burden of inserting what sometimes amounts to more directives than code. Several compilers support both feature sets, typically by translating do concurrent into serial do loops annotated by parallel directives and by translating SPMD/PGAS features into direct calls to a communication library. Our research focuses primarily on two questions: (1) can the compiler’s parallel runtime library be developed in the language being compiled (Fortran) and (2) can we define an interface to the runtime that liberates compilers from being hardwired to one runtime and vice versa. We are answering these questions by developing the Parallel Runtime Interface for Fortran (PRIF) [2] and the Co-Array Fortran Framework of Efficient Interfaces to Network Environments (Caffeine) [3]. Caffeine is initially targeting adoption by LLVM Flang, a new open-source Fortran compiler developed by a broad community in industry, academia, and government labs. We are also exploring the use of these features in Inference-Engine, a deep learning library designed to facilitate neural network training and inference for high-performance computing applications written in modern Fortran.

Rasmussen, Katherine↗

Editorial: Deep-sea observation equipment and exploration technology

The increasing interest in deep-sea exploration is a crucial catalyst for driving advancements in deep-sea observation technology research. Numerous sophisticated sensors have been developed to facilitate comprehensive studies in deep-sea physics, chemistry, and geology. For example, cutting-edge small and compact seabed samplers are now employed on various platforms, such as Autonomous Underwater Vehicles (AUVs), Remotely Operated Vehicles (ROVs), and Human-Operated Vehicles (HOVs), enabling observation of the hadal zone. Additionally, Micro-electromechanical systems (MEMS) sensors are routinely utilized for ocean wave observation. This Research Topic aims to foster new insights into ocean exploration and observation technology, including ocean sensor technology, ocean observation platforms, and ocean observation reliability technology.

47 OTHER INSTRUMENTATION↗

A Weighted Analysis to Improve the X-Ray Polarization Sensitivity of the Imaging X-ray Polarimetry Explorer

Imaging X-ray Polarimetry Explorer (IXPE) is a Small Explorer mission that was launched at the end of 2021 to measure the polarization of X-ray emission from tens of astronomical sources. Its focal-plane detectors are based on the Gas Pixel Detector, which measures the polarization by imaging photoelectron tracks in a gas mixture and reconstructing their initial directions. The quality of the single track, and then the capability of correctly determining the original direction of the photoelectron, depends on many factors, e.g., whether the photoelectron is emitted at low or high inclination with respect to the collection plane or the occurrence of a large Coulomb scattering close to the generation point. The reconstruction algorithm used by IXPE to obtain the photoelectron emission direction also calculates several properties of the shape of the tracks that characterize the process. In this paper we compare several such properties and identify the best one to weight each track on the basis of the reconstruction accuracy. We demonstrate that significant improvement in sensitivity can be achieved with this approach and for this reason it will be the baseline for IXPE data analysis.

79 ASTRONOMY AND ASTROPHYSICS↗