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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Characterization of Collection Efficiency of the Common Research Model Midspan Wing Section in the IRT

This paper presents a preliminary study for the characterization of collection efficiency from icing tests conducted in the Icing Research Tunnel at NASA Glenn Research Center. A test method previously developed for measuring the attachment line maximum collection efficiency of a swept NACA 0012 airfoil model at zero angle of attack was applied to the leading-edge region of a 65%-scale version of the Common Research Model midspan wing section. A correlation for the stagnation line maximum collection efficiency as a function of the modified inertia parameter was obtained with LEWICE3D simulations utilizing a discrete number of drop diameters. It was then compared with the collection efficiency measurement data obtained in the IRT. For the experimental collection efficiency, two ice shape digitization procedures were utilized to extract 2-D chord-wise ice shape profiles, i.e., the Maximum Combined Cross Section or MCCS, and the Minimum Combined Cross Section or Min CCS, at selected span-wise locations from the 3-D scanned ice shapes. The preliminary result showed that the rime ice thickness method can be used to characterize the collection efficiency distribution, for conditions free of ice erosion, in the main ice shape region. However, a high-order statistical processing of the ice scan is needed for estimating the mean ice thickness in areas where feathers are prevalent. From the limited comparison of the experimental and LEWICE3D collection efficiency data in the CRM65 MS model leading edge area, it was shown that the attachment line maximum collection efficiency is reasonably estimated by the best curve-fit correlation in the range of modified inertia parameter tested. A tighter alignment control of the iced and cold clean model scans is needed to improve the comparison. Further evaluation of this correlation is recommended to assess its applicability for Common Research Model type swept wing icing scaling analysis.

Ice Scailing↗
NASA NTRSDate not supplied

Effect of Cross-Correlation of Orbital Error on Probability of Collision Determination

This paper discusses the effect of global model error on probability of collision (Pc) determination. Modifications to the Pc formulation for cross-correlation of orbital error in prediction are developed and assessed for recent conjunctions. While specific geometries can be identified or constructed to produce significant change in Pc for the modified formulation, it is of operational interest to quanti- fy the relative occurrence of such cases for satellite conjunction risk assessment. Large-scale analysis is feasible per data collections in place over the past year.

Steve Casali↗
NASA NTRSDate not supplied

The Additive Manufacturing Moment Measure (AM3) Approach to Predictions of Solid Cooling Rate and Time Above Melt

Qualification of a laser powder bed fusion additive manufacturing (LPBF-AM) process requires knowledge of the multi-scale material physics during the process, per part. As the LPBF-AM build occurs, each moment is influenced by the process history. Knowledge of the build sequence can be used to generate a discretized time-space-condition point field that when coupled with a nearest neighbors’ calculation results in a generalized and fully parallel process model computation. This GPU accelerated approach was developed for part-scale analysis of build files along with in-situ process monitoring sensor data and is termed the “Additive Manufacturing Moment Measure” (AM3). The AM3 approach will be presented and then used to evaluate an AM Bench relevant geometry with synchronized in-situ process data, ex-situ nondestructive evaluation, and optical microscopy observations. These comparisons permit a better understanding of how the process actions can affect the LPBF-AM build quality and the signals generated during in-situ process monitoring.

Additive Manufacturing↗
NASA NTRS2024

Platte River Water Resources: Assessing Urban Flood Vulnerability to Select Restoration Sites for Urban Woods and Prairies in the Great Plains

In the Platte River Basin, wetlands provide ecosystem services such as flood mitigation and wildlife habitat. However, increasing urban development in the area has impacted natural floodplain processes, leading to a decline in wildlife habitat and an elevated flood risk for nearby communities. To address this issue, Audubon Great Plains’ Urban Woods and Prairies (UWP) Initiative focuses on restoring vital habitats within urban areas to protect bird species and reduce flood hazards. Our project used remotely sensed data, including Landsat 8 Operational Land Imagery (OLI), Sentinel-2 Multispectral Instrument (MSI), and Sentinel-1 Synthetic Aperture Radar (SAR), to assess land use and land cover from 2013 to 2023, as well as flood extent. Broad-scale analysis of the LULC showed some changes in land use patterns across the Central Platte River Basin, with the most notable being a decrease in Agricultural land coverage and an increase in Vegetation and Grassland coverage. Land use changes varied across 13 focal cities across the entire basin. In particular, developed land in Grand Island, NE, nearly tripled from 2019 to 2023, making it a good possible candidate for restoration efforts. We overlaid a flood extent map with the LULC classifications in Grand Island to identify possible restoration sites under UWP. This data will inform Audubon Great Plains in identifying potential restoration sites in key cities.

Jennifer Mathis↗
NASA NTRSDate not supplied

Impact of Anthropogenic Activity, Climate Change, and Urbanization on Wetland Habitat in the Platte River Basin​

The Platte River Basin (PRB) is a dynamic ecosystem where wetlands play a pivotal role as essential habitats for various flora and fauna, including local and migratory birds. It provides many crucial ecosystem services that benefit humans directly and indirectly. However, anthropogenic activity, climate change, and urbanization have resulted in decline in wildlife habitat, elevated flood risk, and wetland loss. To address this issue, NASA DEVELOP partnered with Audubon Great Plains (AGP) to address the vital habitats within urban areas to protect bird species, reduce flood hazards, and analyze the potential impact of future development on wetlands. We utilized remotely sensed data from Landsat 8 Operational Land Imager (OLI), Sentinel-2 Multispectral Instrument (MSI), and Sentinel-1 Synthetic Aperture Radar (SAR) to assess land use and land cover (LULC) change. Nighttime lights data from Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) as well as NASA Socioeconomic Data and Applications Center (SEDAC) population data were also used as inputs to simulate urban growth potential up to 2050 using the open-source FUTure Urban-Regional Environment Simulation (FUTURES) model. A broad scale analysis across 13 focal cities showed varied changes in land use patterns across the PRB, with the most notable being a decrease in agricultural land coverage and an increase in vegetation and grassland coverage. We overlaid a flood extent map with the LULC classifications in Grand Island to identify possible restoration sites under AGP’s Urban Woods and Prairies Initiative. The results for two proposed scenarios showed that at least 51 counties out of 81 in the PRB would experience growth by year 2050. The first scenario (all wetlands are protected) showed that there will be no loss of wetlands by 2050. However, the second scenario (no wetlands are protected) showed a decrease in wetland area and loss of habitat for bird conservation. The results will help AGP to lead awareness workshops for communities about wetland protection and to form impactful conservation strategies in the future.​

Nancee Uniyal↗
DOE OSTI2014

MULTI-SCALE MODELING AND APPROXIMATION ASSISTED OPTIMIZATION OF BARE TUBE HEAT EXCHANGERS

Air-to-refrigerant heat exchangers are very common in air-conditioning, heat pump and refrigeration applications. In these heat exchangers, there is a great benefit in terms of size, weight, refrigerant charge and heat transfer coefficient, by moving from conventional channel sizes (~ 9mm) to smaller channel sizes (< 5mm). This work investigates new designs for air-to-refrigerant heat exchangers with tube outer diameter ranging from 0.5 to 2.0mm. The goal of this research is to develop and optimize the design of these heat exchangers and compare their performance with existing state of the art designs. The air-side performance of various tube bundle configurations are analyzed using a Parallel Parameterized CFD (PPCFD) technique. PPCFD allows for fast-parametric CFD analyses of various geometries with topology change. Approximation techniques drastically reduce the number of CFD evaluations required during optimization. Maximum Entropy Design method is used for sampling and Kriging method is used for metamodeling. Metamodels are developed for the air-side heat transfer coefficients and pressure drop as a function of tube-bundle dimensions and air velocity. The metamodels are then integrated with an air-to-refrigerant heat exchanger design code. This integration allows a multi-scale analysis of air-side performance heat exchangers including air-to-refrigerant heat transfer and phase change. Overall optimization is carried out using a multi-objective genetic algorithm. The optimal designs found can exhibit 50 percent size reduction, 75 percent decrease in air side pressure drop and doubled air heat transfer coefficients compared to a high performance compact micro channel heat exchanger with same capacity and flow rates.

CFD↗
DOE OSTI2015

Fleet DNA Phase 1 Refinement & Phase 2 Implementation; NREL (National Renewable Energy Laboratory)

Fleet DNA acts as a secure data warehouse for medium- and heavy-duty vehicle data. It demonstrates that vehicle drive cycle data can be collected and stored for large-scale analysis and modeling applications. The data serve as a real-world data source for model development and validation. Storage of the results of past/present/future data collection efforts improves analysis efficiency through pooling of shared data and provides the opportunity for 'big data' type analyses. Fleet DNA shows it is possible to develop a common database structure that can store/analyze/report on data sourced from multiple parties, each with unique data formats/types. Data filtration and normalization algorithms developed for the project allow for a wide range of data types and inputs, expanding the project’s potential. Fleet DNA demonstrates the power of integrating Big Data with existing and future tools and analyses: it provides an enhanced understanding and education of users, users can explore greenhouse gases and economic opportunities via AFLEET and ADOPT modeling, drive cycles can be characterized and visualized using DRIVE, high-level vehicle modeling can be performed using real-world drive cycles via FASTSim, and data reporting through Fleet DNA Phase 1 and 2 websites provides external users access to analysis results and gives the opportunity to explore on their own.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2014

IMG-ABC: An Atlas of Biosynthetic Gene Clusters to Fuel the Discovery of Novel Secondary Metabolites

In the discovery of secondary metabolites (SMs), large-scale analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of relevant computational resources. We present IMG-ABC (https://img.jgi.doe.gov/abc/) -- An Atlas of Biosynthetic gene Clusters within the Integrated Microbial Genomes (IMG) system1. IMG-ABC is a rich repository of both validated and predicted biosynthetic clusters (BCs) in cultured isolates, single-cells and metagenomes linked with the SM chemicals they produce and enhanced with focused analysis tools within IMG. The underlying scalable framework enables traversal of phylogenetic dark matter and chemical structure space -- serving as a doorway to a new era in the discovery of novel molecules.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

OpenStudio: A Platform for Ex Ante Incentive Programs

Many utilities operate programs that provide ex ante (up front) incentives for building energy conservation measures (ECMs). A typical incentive program covers two kinds of ECMs. ECMs that deliver similar savings in different contexts are associated with pre-calculated 'deemed' savings values. ECMs that deliver different savings in different contexts are evaluated on a 'custom' per-project basis. Incentive programs often operate at less than peak efficiency because both deemed ECMs and custom projects have lengthy and effort-intensive review processes--deemed ECMs to gain confidence that they are sufficiently context insensitive, custom projects to ensure that savings are claimed appropriately. DOE's OpenStudio platform can be used to automate ex ante processes and help utilities operate programs more efficiently, consistently, and transparently, resulting in greater project throughput and energy savings. A key concept of the platform is the OpenStudio Measure, a script that queries and transforms building energy models. Measures can be simple or surgical, e.g., applying different transformations based on space-type, orientation, etc. Measures represent ECMs explicitly and are easier to review than ECMs that are represented implicitly as the difference between a with-ECM and without-ECM models. Measures can be automatically applied to large numbers of prototype models--and instantiated from uncertainty distributions--facilitating the large scale analysis required to develop deemed savings values. For custom projects, Measures can also be used to calibrate existing building models, to automatically create code baseline models, and to perform quality assurance screening.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

SMR Re-Scaling and Modeling for Load Following Studies

This study investigates the creation of a new set of scaling parameters for the Oregon State University Multi-Application Small Light Water Reactor (MASLWR) scaled thermal hydraulic test facility. As part of a study being undertaken by Idaho National Lab involving nuclear reactor load following characteristics, full power operations need to be simulated, and therefore properly scaled. Presented here is the scaling analysis and plans for RELAP5-3D simulation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Cities Topology - Curbs and Parking

Personal vehicles, buses, freight, emerging services (e.g., ride-hailing), and other modes impose several combinations of competing demands for curb space. Therefore, research is needed to better understand impacts and prioritize space allocation - parking, pick-up/drops or PUDOs, commercial zones, bus stops, etc. - to optimize mobility and energy use. This study aims to develop an optimization model to allocate and manage curb space by interviewing experts, analyzing responses to understand curb space key requirements and priorities, link such curb-management practices to mobility and energy productivity, and provide methods suitable for micro-scale analysis.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Estimation of conductivity for nanoporous materials

Methods and systems for estimating conductivity of clay mineral systems, and for applying the estimates in larger-scale analysis. Conductivity of the clay may be estimated by constructing a molecular model of an anhydrous charge-neutral clay, and then assigning a charge density by substitution of ions in the model of the clay structure. Counterions are inserted for charge neutrality, and water molecules are added to the model to reflect a selected level of hydration. Following assignment of force-field coefficients, molecular dynamics simulation provides data from which diffusion coefficients can be estimated. Application of the Nernst-Einstein relationship to the diffusion coefficients of the counterions provides the ion conductivity of the clay system. This conductivity can be used to derive a formation factor, and can be applied in direct numerical simulation analysis.

58 GEOSCIENCES↗
DOE OSTI2020

Multimodal Mass Spectrometry Imaging (MSI) of Archean and Jurassic Geologic Samples

Current geochemical analytical techniques such as gas chromatography-mass spectrometry (GC-MS and $G\acute{C}GC-MS$) can effectively determine the composition and structure of the organic biosignatures within a sample but cannot resolve the spatial distribution of organic biosignatures within rocks or sediments. The spatial distribution can be used to determine the character of the organic biosignatures [1], which can be indigenous (deposited with host rocks), non-indigenous (incorporated after deposition via fluid migration), or contaminant. Determining the character of organic biosignatures is critical for ancient samples [2] and will be critical if organics are observed in samples returned from Mars [3].Fs-LDPI-MS has the ability to map organic compounds across the surface of samples at 2 - 10 μm lateral resolution. Furthermore, fs-LDPI-MS can be used to carry out multiple analyses in the same location for micron-scale analysis of previously buried material [4]. We used fs-LDPI-MS to examine a ~164 million year old organic-rich mudstone from SW England (14.2 wt. % total organic carbon) [5] and determined the spatial distribution of likely indigenous components buried below potentially contaminated surface layers.We then used ToF-SIMS to re-analyze the mudstone to directly compare ToF-SIMS to fs-LDPI-MS datasets, and to analyze a series of ~2.7 billion year old geologic samples from Timmins, ON, CA [6]. Ref. [6] previously analyzed the Archean samples and observed a series of archaeal biomarkers, as well as hopanes and steranes. Using ToF-SIMS analysis, we were able to detect hopanes and steranes in the mudstone samples, but not in the Archean samples indicating that the hopanes and steranes are most likely contaminants in the Archean samples. We also did not observe the archaeal biomarkers; however, this may be from the lack of molecular ion preservation during ToF-SIMS.

Pasterski, Michael↗
DOE OSTI2012

Anomalous Morphological Scaling in Epitaxial Nb Thin Films on MgO(001)

Surface and interface roughness are critical factors in determining the properties and technological viability of many systems. These considerations are of principle importance for the development of next-generation SRF cavities where the ultimate surface determines the cavity?s performance. The predominant SRF technology currently used in linear accelerators is based on bulk niobium cavities, but ongoing efforts to improve cavity?s performance have considered the possibility of multi-layered thin film coatings on SRF cavities. [1] Nucleation and growth kinetics influence epitaxial thin films grown onto different substrates. In addition, films differ from bulk systems mainly because of limited material supply as well as stress contributions due to lattice mismatch, which can induce significant surface roughness. Rough surfaces lead to undesirable effects for SRF applications, many of which can be minimized by suitable choice of thin film growth parameters. We have undertaken a systematic effort to understand the evolution of the surface under specific deposition conditions. We present our scaling analysis applied to the evolving surface during epitaxial Nb growth. Funding Agency ? Department of Energy: Development and Characterization of Thin Film SRF Surfaces for Accelerator Cavities: DE-PS02-09ER09-05 from DOE-OHEP ARRA.

Reece, Charles↗
DOE OSTI2020

Machine Learning in Nuclear Thermal Hydraulics, Part 2: Opportunities and Perspectives

This paper summarizes the issues in nuclear thermal hydraulics (NTH), mainly from the three named aspects, and illustrates potential opportunities of machine learning (ML) applications in dealing with these issues. These issues are problems in simultaneously realizing computational efficiency and accuracy of system thermal hydraulic (STH) modeling and simulation, uncertainty in the scaling analysis for the best-estimate calculations of transient and accident analysis, and difficulties in optimal data production and usage for the development and assessment of evaluation models. Due to ML uncertainty, data insufficiency, and lack of cognition about how to efficiently incorporate knowledge and data, challenges of adapting ML techniques still exist. Accordingly, several perspectives are proposed to provide insights for ML applications in solving these issues.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Surrogate materials options for single phase conjugate heat transfer scaled experiments of light water reactors at prototypical conditions

In light water reactors, the conjugate heat transfer between heating rods and cooling water is a problem of paramount importance that has been studied for decades. The design of nuclear reactors depends on correlations for the heat transfer coefficient between heat source and coolant, and experimental studies are needed to improve the existing correlations, develop new ones that are adapted to the new reactors designed and their components, and develop high fidelity turbulence models. No studies have been carried out yet at prototypical conditions where the liquid velocity and temperature fields are measured, because of the difficulty to find instruments that can resist the extreme operating conditions. Here, two surrogate gases, sulfur hexafluoride and cryogenic nitrogen, are proposed to conduct conjugate heat transfer experiments at prototypical conditions. Surrogate structural materials are also investigated to favorably reproduce conjugate heat transfer for steady and transient operations. The operating conditions are now less demanding than high-pressure, high-temperature water, which allows the deployment of many proven diagnostics. To demonstrate these surrogate materials, a sample scaling analysis is applied to one pressurized water reactor fuel rod under axial flow and vibrations, showing a very close matching between prototype and model for the conjugate heat transfer. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

SMR Re-Scaling and Modeling for Load Following Studies

This study investigates the creation of a new set of scaling parameters for the Oregon State University Multi-Application Small Light Water Reactor (MASLWR) scaled thermal hydraulic test facility which modeled the NuScale power SMR design. As part of a study being undertaken by Idaho National Lab involving nuclear reactor load following characteristics, full power operations need to be simulated, and therefore properly scaled. Presented here is the scaling analysis and plans for RELAP5-3D simulation. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Investigating SU(3) with Nf=8 fundamental fermions at strong renormalized coupling

Lattice simulations have observed a novel strong coupling symmetric mass generation (SMG) phase for the SU(3) gauge system with $N_f=8$ fundamental fermions (represented by two sets of staggered fields) at very large renormalized coupling ($g^2_{GF} \gtrsim 25$). The results of Phys.Rev.D 106 (2022) 014513 suggest that the SMG phase is separated from the weak coupling, conformal phase by a continuous phase transition, implying that the SMG phase exists in the continuum limit. To scrutinize these findings, we are generating a set of large volume zero temperature ensembles using nHYP improved staggered fermions with additional Pauli-Villars fields to tame gauge field fluctuations. We consider the low-lying meson spectrum and verify the existence of the SMG phase. Based on a finite size scaling analysis we predict that the phase transition between the strong and weak coupling phases is likely governed by a merged fixed point that is ultraviolet in the strong coupling but infrared in the weak coupling side. This finding suggests that the SU(3) 8-flavor system sits at the opening of the conformal window

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗