Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Resource Characterization”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Development of A High-Resolution Dataset for Solar Resource Adequacy Studies

High-resolution, long-term solar dataset is essential for characterizing the variability of solar energy resources and for informing strategies that ensure grid reliability and resilience in grid systems with high levels of solar energy integration. We present the development of a new 4-km, hourly Earth system dataset for the contiguous United States (CONUS), using a statistical downscaling approach that integrates the National Solar Radiation Database (NSRDB) with regional Earth system model projections. The new high-resolution Earth system dataset includes key variables - GHI, DNI, DHI, surface air temperature, and wind speed - under two future scenarios. Preliminary results show a reasonable agreement with NSRDB observations, with nBias less than 1% for GHI across CONUS. The dataset is expected to support in-depth analyses of extreme weather impacts and provide input to resource adequacy for future energy systems with diverse generation sources.

14 SOLAR ENERGY↗
NASA NTRSDate not supplied

UV Laser Development for In Situ Planetary Lander Instruments

Mass and Raman spectrometers represent progressive analytical platforms for future in situ lander missions to explore the surface chemistry of planetary bodies across the Solar System. Europa, the Moon, and Mars are some of the primary targets for future NASA missions to search for extraterrestrial life and potentially habitable environments beyond Earth, further our understanding of the timing and formation of the Solar System and identify potentially viable economic resources such as water and/or valuable metal assets. The CORALS (Characterization of Ocean Residues And Life Signatures) and CRATER (Characterization of Regolith And Trace Economic Resources) instruments are UV laser-enabled OrbitrapTM mass spectrometers currently under development for prospective lander missions to Europa and the Moon, respectively. The Raman Mass Spectrometer (RAMS) is a dual wavelength (UV and visible) laser enabled hybrid instrument that incorporates laser desorption/ ionization mass spectrometry (LDMS) and micro-Raman microspectroscopy imaging (μRS) into a compact instrument package for multiple planetary missions to the inner and outer Solar System. The Pulse Laser Ablation Sampling and Mass Analysis (PLASMA) instrument combines a multi-wavelength laser (deep-UV to near-IR), plasma source, and collision cell with a heritage quadrupole mass spectrometer (QMS) to enable high precision trace element analyses for a future Lunar lander instrument. We report on the advancement of four compact, robust, and high technology readiness level (TRL) solid state lasers operating at wavelengths 213 nm, 266 nm, 515 nm, 532 nm and 1064 nm that serve as the sampling and ionization sources, for the CRATER, CORALS, RAMS and PLASMA investigations.

Molly Fahey↗
DOE OSTI2024

When do different scenarios of projected electricity demand start to meaningfully diverge?

Resource adequacy studies look at balancing electricity supply and demand on 10- to 15-year time horizons while asset investment planning typically evaluates returns on 20- to 40-year time horizons. Projections of electricity demand are factored into the decision-making in both cases. Climate, energy policy, and socioeconomic changes are key uncertainties known to influence electricity demands, but their relative importance for demands over the next 10-40 years is unclear. The power sector would benefit from a better understanding of the need to characterize these uncertainties for resource adequacy and investment planning. In this study, we quantify when projected United States (U.S.) electricity demands start to meaningfully diverge in response to a range of climate, energy policy, and socioeconomic drivers. Here we use a wide yet plausible range of 21st century scenarios for the U.S. The projections span two population/economic growth scenarios (Shared Socioeconomic Pathways 3 and 5) and two climate/energy policy scenarios, one including climate mitigation policies and one without (Representative Concentration Pathways 4.5 and 8.5). Each climate/energy policy scenario has two warming levels to reflect a range of climate model uncertainty. We show that the socioeconomic scenario matters almost immediately – within the next 10 years, the climate/policy scenario matters within 25-30 years, and the climate model uncertainty matters only after 50+ years. This work can inform the power sector working to integrate climate change uncertainties into their decision-making.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Implications of increased spatial and trophic overlap between juvenile Pacific salmon and Sablefish in the northern California Current

Abstract Objective The study was designed to assess long-term variability in the distribution of juvenile Pacific salmon Oncorhynchus spp. and Sablefish Anoplopoma fimbria. The study also evaluated whether Sablefish and Pacific salmon shared food resources and looked to characterize Sablefish during an understudied period of their life cycle. Methods To meet the objectives, the study used data from 26 years of surface trawls conducted in Oregon and Washington coastal waters (1998–2023). Spatial–temporal models were used to measure changes in abundance and distribution of Pacific salmon and Sablefish along with covariates of ocean temperature. The study evaluated trophic characteristics of Pacific salmon and Sablefish from 2020 for differences. The temporal variation in size and diets of Sablefish were also analyzed, along with energy density of fish caught in 2020. Result The spatial–temporal model demonstrated that there has been a nearshore expansion of juvenile Sablefish over the past 26 years that was correlated with increased ocean temperature. The nearshore expansion of Sablefish resulted in increased spatial and trophic overlap with juvenile Pacific salmon. While feeding in nearshore waters, juvenile Sablefish demonstrated competitive feeding advantages over juvenile Pacific salmon during a critical phase of salmonid early marine life history. Juvenile Sablefish exhibited significant ontogenetic diet and energetic shifts, and even the smallest (68–80 mm fork length) were piscivorous. Conclusions If juvenile Sablefish numbers continue to increase relative to Pacific salmon, they could exert more competitive pressure, especially if food resources become limited. Pacific salmon may experience adverse effects from competition, regardless of whether or not juvenile Sablefish, which have recently expanded into nearshore waters, successfully recruit to the adult population.

Daly, Elizabeth A. (ORCID:0000000195334457)↗
DOE OSTI2024

Automated Gold Nanorod Spectral Morphology Analysis Pipeline

The development of a colloidal synthesis procedure to produce nanomaterials with high shape and size purity is often a time-consuming, iterative process. This is often due to quantitative uncertainties in the required reaction conditions and the time, resources, and expertise intensive characterization methods required for quantitative determination of nanomaterial size and shape. Absorption spectroscopy is often the easiest method for colloidal nanomaterial characterization. However, due to the lack of a reliable method to extract nanoparticle shapes from absorption spectroscopy, it is generally treated as a more qualitative measure for metal nanoparticles. This work demonstrates a gold nanorod (AuNR) spectral morphology analysis tool, called AuNR-SMA, which is a fast and accurate method to extract quantitative structural information from colloidal AuNR absorption spectra. To demonstrate the practical utility of this model, we apply it to three distinct applications. First, we demonstrate this model's utility as an automated analysis tool in a high-throughput AuNR synthesis procedure by generating quantitative size information from optical spectra. Second, we use the predictions generated by this model to train a machine learning model to predict the resulting AuNR size distributions under specified reaction conditions. Third, we apply this model to spectra extracted from the literature where no size distributions are reported and impute unreported quantitative information on AuNR synthesis. This approach can potentially be extended to any other nanocrystal system where absorption spectra are size dependent, and accurate numerical simulation of absorption spectra is possible. In addition, this pipeline could be integrated into automated synthesis apparatuses to provide interpretable data from simple measurements, help explore the synthesis science of nanoparticles in a rational manner, or facilitate closed-loop workflows.

36 MATERIALS SCIENCE↗
DOE OSTI2025

ALS-ENABLE: creating synergy and opportunity at the Advanced Light Source synchrotron structural biology beamlines

ALS-ENABLE is an integrated NIH P30 resource at the Advanced Light Source synchrotron at Lawrence Berkeley National Laboratory in Berkeley, California, USA. The resource provides a single portal to the combined mature structural biology technologies of macromolecular crystallography, small-angle X-ray scattering and X-ray footprinting mass spectrometry, and includes beamlines 2.0.1, 3.3.1, 4.2.2, 5.0.1, 5.0.2, 5.0.3, 8.2.1, 8.2.2, 8.3.1 and 12.3.1. This paper describes the organizational structure and the technologies of ALS-ENABLE. A case study showcasing the main technologies of the resource applied to the characterization of the SpyCatcher-SpyTag protein system is presented.

Ralston, Corie Y↗
DOE OSTI2026

INL CRMO XRF Special Report No. 3: INL CRMO XRF Calibration Methods for the Analysis of Ceramics and Brick

This report details the analytical methods used by the Idaho National Laboratory Cultural Resource Management Office to characterize ceramic and brick artifacts using X-ray fluorescence spectrometry. More specifically, this report provides details on instrumentation, analysis times, and matrix-specific calibration protocols for ceramic materials. Calibration curves were developed to adjust raw instrumental output for 13 elements using a suite of reference standards made from historic brick borrowed from the Yale Peabody Museum. Calibration curves were validated by plotting predicted values against published reference values for the calibration set as well as a certified soil reference standard (SRM 2711a).

36 MATERIALS SCIENCE↗
NASA NTRS1991

Near-Earth asteroids: Observer alert network and database analysis

The Planetary Science Institute (PSI) was funded by SERCulpr to develop a communication network to alert observers of newly discovered near-earth asteroids (NEA's). This network is intended to encourage observers to obtain physical observations of NEA's, which are needed in order to characterize and assess the resource potential of these bodies. This network was declared operational in October 1990 via an announcement to the asteroid observing community. The PSI is also supported to develop the Near-Earth Asteroid Database (NEAD), a comprehensive database of physical and dynamical data on NEA's. In the past year, the database was updated on newly discovered NEA's during 1990, and new data on radar observations and dynamical classifications were added.

Davis, Donald R.↗
NASA NTRS2017

Equilibrium Temperatures and Albedos of Habitable Earth-Like Planets in a Coupled Atmosphere-Ocean GCM

The potential habitability of detected exoplanets is typically assessed using the concept of equilibrium temperature (T[subscript] e) based on cloud-free 1-D models with assumed albedo equal to Earth's (0.3) to determine whether a planet lies in the habitable zone. Incident stellar flux appears to be a better metric for stars unlike the Sun. These estimates, however, ignore the effect of clouds on planetary albedo and the fact that the climates of synchronously rotating planets are not well predicted by 1-D models. Given that most planet candidates that will be detected in the next few years will be tidally locked and orbiting M stars, how might the habitable zone e tailored to better in-form characterization with scarce observing resources?

Del Genio, Anthony↗
NASA NTRSDate not supplied

Numerical Modelling of Sublimation Losses During Sample Handling Within the Light WAVE Lunar Water Prospecting Instrument

NASA’s focus of exploring the Moon’s south pole under the Artemis program has placed new emphasis on characterizing the quantity and distribution of water ice and other volatiles present within the Moon’s permanently shadowed regions (PSRs), first measured during the 2009 LCROSS mission. NASA’s VIPER rover is the first of a series of prospecting missions to characterize this water ice resource. NASA’s Johnson Space Center (JSC) has developed the Light Water Analysis and Volatiles Extraction (Light WAVE) instrument shown in Figure 1 for a follow-on prospecting mission, designed to be a rover payload for water ice prospecting at various depths and locations within PSRs. A key source of error for lunar water prospecting instruments, including Light WAVE, is the loss of water in an icy regolith sample to the lunar vacuum via sublimation due to heating above its ice-stable temperature. This abstract and conference presentation discuss a sublimation model for Light WAVE’s sample crucible using COMSOL Multiphysics to assess the sublimation losses that would occur between sample collection from an external drill and sealing the sample within Light WAVE’s boiler.

Lunar Polar Water↗
NASA NTRS2012

Characterizing Orbital Debris and Spacecrafts Through a Multi-Analytical Approach

Defining the risks present to both crewed and robotic spacecrafts is part of NASA s mission, and is critical to keep these resources out of harms way. Characterizing orbital debris is an essential part of this mission. We present a proof-of-concept study that employs multiple techniques to demonstrate the efficacy of each approach. The targets of this study are IDCSPs (Initial Defense Communications Satellite Program). 35 of these satellites were launched by the US in the mid-1960s and were the first US communications satellites in the GEO regime. They were emplaced in slightly sub-synchronous orbits. These targets were chosen for this proof-of-concept study for the simplicity of their observable exterior surfaces. The satellites are 26-sided polygons (86cm in diameter), initially spin-stabilized and covered on all sides in solar panels. Data presented here include: (a) visible broadband photometry (Johnson B and Cousins R bands) taken with the University of Michigan s 0.6-m aperture Curtis-Schmidt telescope MODEST (for Michigan Orbital DEbris Survey Telescope) in Chile in November, 2011, (b) laboratory broadband photometry (Johnson BV Cousins RI) of solar cells, obtained using the Optical Measurements Center (OMC) at NASA/JSC (see Cowardin et al., this meeting for more details), (c) visible-band spectra taken using the Magellan 6.5m Baade Telescope at Las Campanas Observatory in Chile in March, 2012 (see also Seitzer et al., this meeting), and (d) visible-band laboratory spectra of solar cells using a Field Spectrometer. Color-color plots using broadband photometry (e.g. B-R vs. R-I) demonstrate that different material types fall into distinct areas on the plots (Cowardin, AMOS 2010). Spectra will be binned in wavelength to compare with photometry results and plotted on the same graph for comparison. This allows us to compare lab data with telescopic data, and photometric results with spectroscopic results. In addition, the spectral response of solar cells in the visible wavelength regime varies from relatively flat (modern black solar cells with uniform albedo as a function of wavelength) to older solar cells whose reflectivity is sharply peaked in the blue (similar to the IDCSP solar cells). With a target like IDCSPs, the material type is known a priori. Therefore, this study will also be used to determine whether laboratory spectra of pre-launch (pristine) solar cells differ from the telescopic spectra of IDCSPs that have been exposed to the harsh environment of space for ~45 years to investigate whether space weathering effects are evident.

Lederer, S. M.↗
NASA NTRS1998

Workload Characterization of CFD Applications Using Partial Differential Equation Solvers

Workload characterization is used for modeling and evaluating of computing systems at different levels of detail. We present workload characterization for a class of Computational Fluid Dynamics (CFD) applications that solve Partial Differential Equations (PDEs). This workload characterization focuses on three high performance computing platforms: SGI Origin2000, EBM SP-2, a cluster of Intel Pentium Pro bases PCs. We execute extensive measurement-based experiments on these platforms to gather statistics of system resource usage, which results in workload characterization. Our workload characterization approach yields a coarse-grain resource utilization behavior that is being applied for performance modeling and evaluation of distributed high performance metacomputing systems. In addition, this study enhances our understanding of interactions between PDE solver workloads and high performance computing platforms and is useful for tuning these applications.

Waheed, Abdul↗
NASA NTRS2015

The Parameterization of Top-Hat Particle Sensors with Microchannel-Plate-Based Detection Systems and its Application to the Fast Plasma Investigation on NASA's Magnetospheric MultiScale Mission

The most common instrument for low energy plasmas consists of a top-hat electrostatic analyzer geometry coupled with a microchannel-plate (MCP)-based detection system. While the electrostatic optics for such sensors are readily simulated and parameterized during the laboratory calibration process, the detection system is often less well characterized. Furthermore, due to finite resources, for large sensor suites such as the Fast Plasma Investigation (FPI) on NASA's Magnetospheric Multiscale (MMS) mission, calibration data are increasingly sparse. Measurements must be interpolated and extrapolated to understand instrument behavior for untestable operating modes and yet sensor inter-calibration is critical to mission success. To characterize instruments from a minimal set of parameters we have developed the first comprehensive mathematical description of both sensor electrostatic optics and particle detection systems. We include effects of MCP efficiency, gain, scattering, capacitive crosstalk, and charge cloud spreading at the detector output. Our parameterization enables the interpolation and extrapolation of instrument response to all relevant particle energies, detector high voltage settings, and polar angles from a small set of calibration data. We apply this model to the 32 sensor heads in the Dual Electron Sensor (DES) and 32 sensor heads in the Dual Ion Sensor (DIS) instruments on the 4 MMS observatories and use least squares fitting of calibration data to extract all key instrument parameters. Parameters that will evolve in flight, namely MCP gain, will be determined daily through application of this model to specifically tailored in-flight calibration activities, providing a robust characterization of sensor suite performance throughout mission lifetime. Beyond FPI, our model provides a valuable framework for the simulation and evaluation of future detection system designs and can be used to maximize instrument understanding with minimal calibration resources.

Instrument-model↗
DOE OSTI2025

A novel approach for large-scale wind energy potential assessment

Increasing wind energy generation is central to grid decarbonization, yet methods to estimate wind energy potential are not standardized, leading to inconsistencies and even skewed results. This study aims to improve the fidelity of wind energy potential estimates through an approach that integrates geospatial analysis and machine learning (i.e., Gaussian process regression). We demonstrate this approach to assess the spatial distribution of wind energy capacity potential in the Contiguous United States (CONUS). We find that the capacity-based power density ranges from 1.70 MW/km2 (25th percentile) to 3.88 MW/km2 (75th percentile) for existing wind farms in the CONUS. The value is lower in agricultural areas (2.73 ± 0.02 MW/km2, mean ± 95 % confidence interval) and higher in other land cover types (3.30 ± 0.03 MW/km2). Notably, advancements in turbine manufacturing could reduce power density in areas with lower wind speeds by adopting low specific-power turbines, but improve power density in areas with higher wind speeds (>8.35 m/s at 120m above the ground), highlighting opportunities for repowering existing wind farms. Wind energy potential is shaped by wind resource quality and is regionally characterized by land cover and physical conditions, revealing significant capacity potential in the Great Plains and Upper Texas. The results indicate that areas previously identified as hot spots using existing approaches (e.g., the west of the Rocky Mountains) may have a limited capacity potential due to low wind resource quality. Improvements in methodology and capacity potential estimates in this study could serve as a new basis for future energy systems analysis and planning.

Dai, Tao↗
NASA NTRSDate not supplied

Characterization of Fluorescence Signals in Synthetic Anorthite

In-situ resource utilization (ISRU) is a key capability to enable a long term presence on the Moon and other planetary bodies. For example, efforts have been underway to develop processes to utilize the lunar regolith to produce building materials and extract useful resources. In processes that utilize the regolith directly to produce construction materials, such as in various sintering methods, characterizing the composition of the regolith is important as the composition can affect the optimal process parame-ters. In processes that involve extracting resources such as iron, oxygen, hydrogen, etc., identifying areas with higher abundance of a particular resource will be critical since different regions of the Moon exhibit differing regolith composition. To this end, Ra-man is one technique that can rapidly characterize the mineralogy of rock samples. This technique has al-ready been deployed on Mars to detect various miner-als including olivine, carbonates, phosphates, etc. Besides characterizing the mineralogy, Raman spectra often contain unwanted fluorescence signals that can mask Raman peaks. In some cases, the fluorescence signals are narrow enough to aid in the identification of specific elements in soils. In this work, we explore fluorescence peaks in a synthetic anorthite sample, which are at the same position as Ruby fluorescence peaks attributed to chromium. These fluorescence peaks, as well as similar fluorescence peaks attributed to other elements, could have important implications for ISRU and the mining of critical resources as has been previously described.

Raman Spectroscopy↗
NASA NTRS2011

Global Assimilation of Multi-Sensor Snow Observations for Improved Characterization of Snow Processes

Snow conditions on the land surface are recognized to be key components of the global hydrological cycle as they play a critical role in the determination of local and regional climate. In many mid-latitude and high-latitude regions, the seasonal water storage and associated spring snowmelt dominate the local hydrology. The contribution to the runoff and moisture conditions from snow is vital in supporting agriculture and in determining water resources management practices. Consequently, accurate characterization of snow properties becomes important for both end-use applications and weather and climate research. Recently a joint effort between the u.S. Air Force and NASA has enabled a blended, multi-sensor snow product known as the AFWA NASA Snow Algorithm (ANSA). This global snow dataset has been generated by utilizing the Earth Observation System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer for EOS (AMSR-E) datasets. ANSA product includes estimates of snow cover extent, snow water equivalent (SWE) and SWE-derived snow depth fields. The MODIS-based products enable snow cover mappings under cloud-free conditions whereas the passive microwave data from AMSR-E provides measurements under cloudy conditions. These remotely-sensed snow observations are further augmented with the information from ground-based snow measurements through data fusion techniques. The resulting ANSA products are employed in the NASA Land Information System (LIS) data assimilation framework, which provides a comprehensive environment for integrating community land surface models, ground and satellite-based observations, and ensemble-based data assimilation tools. LIS incorporates the multisensor ANSA snow retrievals with the land surface model estimates to generate spatially and temporally continuous estimates of snow states, through data assimilation. A suite of experiments to assimilate ANSA snow cover, SWE and snow depth estimates with different land surface models in LIS are conducted and the resulting estimates of snow conditions are evaluated against a number of in-situ observational datasets, over several regions of the world. These evaluations are used to compare and contrast the advantages and disadvantages of these multi-sensor snow observations.

Kumar, Sujay↗
NASA NTRS1973

Microsampling techniques for infrared spectroscopic analysis of lunar and terrestrial minerals

Microsampling techniques have been developed for infrared analysis of single mineral grains from lunar rocks and dusts, allowing a detailed molecular structure characterization of these complex fine-grained samples. The methods include special devices for isolating single grains, preparing micropellets from the grains, and obtaining in situ microspecular reflectance spectra from grains in polished rock samples. Although specifically developed for the work on lunar samples, the special techniques for single grain infrared analysis were found to be equally useful in studies of complex terrestrial mineral samples. For example, infrared microanalysis has contributed substantially in solving problems concerned with our natural resources, such as the structural characterization of minerals from commercial iron ores, marine deposits, coal, and fly ash derived from coal.

Estep, P. A.↗
NASA NTRS2012

Preliminary Characterization of IDCSP Spacecrafts Through a Multi-Analytical Approach

Defining the risks present to both crewed and robotic spacecrafts is part of NASA s mission, and is critical to keep these resources out of harm s way. Characterizing orbital debris is an essential part of this mission. We present a proof-of-concept study that employs multiple techniques to demonstrate the efficacy of each approach. The targets of this study are IDCSPs (Initial Defense Communications Satellite Program). 35 of these satellites were launched by the US in the mid-1960s and were the first US military communications satellites in the GEO regime. They were emplaced in slightly sub-synchronous orbits. These targets were chosen for this proof-of-concept study for the simplicity of their observable exterior surfaces. The satellites are 26-sided polygons (86cm in diameter), initially spin-stabilized, and covered on all sides in solar panels. Data presented here include: (a) visible broadband photometry (Johnson/Kron-Cousins BVRI) taken with the 0.9m SMARTs telescope (Small and Medium Aperture Telescopes) at the Cerro Tololo Inter-American Observatory (CTIO) in Chile in April, 2012, (b) laboratory broadband photometry (Johnson/ Bessell BVRI) of solar cells, obtained using the Optical Measurements Center (OMC) at NASA/JSC [1], (c) visible-band spectra taken using the Magellan 6.5m Baade Telescope at Las Campanas Observatory in Chile in May, 2012 [2], and (d) visible-band laboratory spectra of solar cells using an ASD Field Spectrometer. Color-color plots using broadband photometry (e.g. B-R vs. B-V) demonstrate that different material types fall into distinct areas on the plots [1]. Spectra of the same material types as those plotted in the color-color plots each display their own signature as well. Here, we compare lab data with telescopic data, and photometric results with spectroscopic results. The spectral response of solar cells in the visible wavelength regime varies from relatively flat to somewhat older solar cells whose reflectivity can be gently or sharply peaked in the blue. With a target like IDCSPs, the material type is known a priori, aiding in understanding how material type affects one s observations.

Lederer, S. M.↗