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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Spatial and Temporal Analysis of the Total Cost of Ownership for Class 8 Tractors and Class 4 Parcel Delivery Trucks

The medium- and heavy-duty transportation sector is experiencing rapid changes in powertrain technology innovation, with recent announcements of battery electric and fuel cell electric trucks being offered. The economics of these alternative powertrain vehicles are uncertain and difficult to compare directly. This analysis seeks to provide a rigorous, techno-economic analysis of all of these alternative powertrain vehicles within the same analytic framework. Specifically, this report evaluates the total cost of ownership (TCO) of six different truck powertrain technologies (diesel, diesel hybrid electric, plug-in hybrid electric, compressed natural gas, battery electric, and fuel cell electric) for three different truck vocations (Class 8 long haul [750-mile range and 500-mile range], Class 8 short haul [300-mile range], and Class 4 parcel delivery [120-mile range]), for three different time frames (2018, 2025, and Ultimate).

08 HYDROGEN↗
DOE OSTI2020

Integration of Total-Sky Imager Data with a Physics-Based Smart Persistence Model for Intra-Hour Forecasting of Solar Radiation

Short-term solar forecasting models based solely on global horizontal irradiance (GHI) measurements are often unable to discriminate the forecasting of the factors affecting GHI from those that can be precisely computed by atmospheric models. Our previous study introduced a Physics-based Smart Persistence model for Intra-hour forecasting of solar radiation (PSPI) that decomposed the forecasting of GHI into the computation of extraterrestrial solar radiation and solar zenith angle and the forecasting of cloud albedo and cloud fraction. The extraterrestrial solar radiation and solar zenith angle were accurately computed by the Solar Position Algorithm (SPA) developed at the National Renewable Energy Laboratory (NREL). A cloud retrieval technique was used to estimate cloud albedo and cloud fraction from surface-based observations of GHI. With the assumption of persistent cloud structures, the cloud albedo and cloud fraction were predicted for future time steps using a two-stream approximation and a 5-minute exponential weighted moving average, respectively. The model evaluation indicated the estimation and forecast of cloud fraction mostly contributed to the uncertainty of the PSPI though it overcame the persistence and smart persistence models in all forecast time horizons between 5 and 60 minutes. This study aims to enhance the PSPI by ingesting surface-based observations of cloud fraction from a total sky imager (TSI). The estimation and forecast of cloud albedo is correspondingly improved by utilizing the cloud fraction observations and thus leads to more accurate GHI forecast. Various time-series analysis methods are also investigated on the forecasting of cloud fraction and cloud albedo for further improving the GHI forecast. These improvements are valuable for many applications, such as forecasting energy use for buildings, grid operations, and ultimately bringing down the cost of solar energy.

14 SOLAR ENERGY↗
DOE OSTI2020

Total variation vs L1 regularization: a comparison of compressive sensing optimization methods for chemical detection

One of the fundamental assumptions of compressive sensing (CS) is that a signal can be reconstructed from a small number of samples by solving an optimization problem with the appropriate regularization term. Two standard regularization terms are the L1 norm and the total variation (TV) norm. We present a comparison of CS reconstruction results based on these two approaches in the context of chemical detection, and we demonstrate that optimization based on the L1 norm outperforms optimization based on the TV norm. Our comparison is driven by CS sampling, reconstruction, and chemical detection in two real-world datasets: the Physical Sciences Inc. Fabry-Perot interferometer sensor multispectral dataset and the Johns Hopkins Applied Physics Lab FTIR-based longwave infrared sensor hyperspectral dataset. Both datasets contain the release of a chemical simulant such as glacial acetic acid, triethyl phosphate, and sulfur hexafluoride. For chemical detection we use the adaptive coherence estimator (ACE) and bulk coherence, and we propose algorithmic ACE thresholds to define the presence or absence of a chemical of interest in both un-compressed data cubes and reconstructed data cubes. The un-compressed data cubes provide an approximate ground truth. We demonstrate that optimization based on either the L1 norm or TV norm results in successful chemical detection at a compression rate of 90%, but we show that L1 optimization is preferable. We present quantitative comparisons of chemical detection on reconstructions from the two methods, with an emphasis on the number of pixels with an ACE value above the threshold.

Hyperspectral imagery, L1-norm, total variation, A↗
DOE OSTI2024

Conceptual range estimation for total cost of ownership of modular process‐intensified chemical plants

Abstract Chemical companies have used modularization to reduce capital costs and project timelines, putting capital to work faster and lowering the risk of entering new markets. Nevertheless, the impacts of using modularization along with advanced technologies, such as process intensification, have not yet been fully realized, often due to the uncertain business risks associated with their implementation. Therefore, new methods are needed for quantifying the impact of modular chemical process intensification (MCPI) on the capital and operating costs of chemical plants to help build a business case for this novel approach. This article presents a new conceptual range estimation technique for total cost of ownership that addresses the deficiencies of existing methods for quantifying MCPI impacts. The incorporation of percentage range estimates was employed to allow for adaptability across various cost and size scales. This work also begins to elucidate how chemical engineering and construction firms can benefit from MCPI and identifies barriers that inhibit MCPI applications in the chemical industry.

Alhamouri, Khaled I.↗
DOE OSTI2020

Extrinsic Absorption Pathways in Vanadium-Doped SiC Measured Using a Total Internal Reflection Geometry

Vanadium-doped SiC is under study for high-power photoconductive switches and is receiving increased attention as a potential material system for quantum computing, as the V can act as a quantum emitter at telecom wavelengths. Knowledge of the defect-mediated electronic transition pathways from sub-bandgap illumination in this material with low absorption and multi-photon and multi-path transition probability is important in optimizing quantum efficiency. Herein, the optical transitions of vanadium-doped SiC for two polytypes as a function of dopant concentration using a total internal reflection (TIR) geometry are examined. Furthermore, normalized quantum efficiency is reported and correlated with both dopant concentrations (V, N, B, and Al) measured by secondary ion mass spectroscopy (SIMS) and absorption measurements. Although both polytypes respond well to 532 nm light, efficiency at longer wavelengths does not correlate 1:1 with absorption coefficient and strongly depends on the polytype and net background co-dopant concentration. This has important implications for efficient excitation of both carriers for optoelectronics and for the use of V as a quantum emitter.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Enhancing Mechanical Properties of Carbon–Silicon Steel through Two–Stage Quenching and Partitioning with Bainitic Transformation: Ultimate Tensile Strength of 1875 MPa and Total Elongation of 8.03%

To achieve the desired microstructural properties, the ongoing development and innovation in new structural steels require novel thermal processing. This study aims to improve the mechanical properties of a commercial spring carbon–silicon steel by tailoring its microstructure through a process involving quenching and partitioning (Q&P) followed by bainitic transformation. A two–stage Q&P process is proposed to generate a nanoscale dispersion of stable retained austenite and carbides within the tempered martensite and bainite microstructure. The resulting tensile properties demonstrate a yield strength of 1280 MPa, an ultimate tensile strength of 1875 MPa, and a total elongation of 8.03%. These values surpass those of conventional spring 9254 steel, highlighting the effectiveness of the thermal treatment design. Microstructure analysis reveals the presence of tempered martensite, bainite sheaves, nanoscale carbides, and aggregates of retained austenite. Moreover, the resulting body–centered cubic matrix exhibits minimal lattice tetragonality of ≈1.0051, coupled with stable retained austenite featuring a carbon concentration of ≈3.42 ± 0.5 wt%, resulting in outstanding strength–ductility properties. In conclusion, these findings indicate that the proposed two–stage Q&P process, followed by bainitic transformation, significantly enhances the mechanical properties of carbon–silicon steels, making it a promising candidate for high–performance spring applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Quantifying the influence of natural climate variability on in situ measurements of seasonal total and extreme daily precipitation

Abstract While various studies explore the relationship between individual sources of climate variability and extreme precipitation, there is a need for improved understanding of how these physical phenomena simultaneously influence precipitation in the observational record across the contiguous United States. In this work, we introduce a single framework for characterizing the historical signal (anthropogenic forcing) and noise (natural variability) in seasonal mean and extreme precipitation. An important aspect of our analysis is that we simultaneously isolate the individual effects of seven modes of variability while explicitly controlling for joint inter-mode relationships. Our method utilizes a spatial statistical component that uses in situ measurements to resolve relationships to their native scales; furthermore, we use a data-driven procedure to robustly determine statistical significance. In Part I of this work we focus on natural climate variability: detection is mostly limited to DJF and SON for the modes of variability considered, with the El Niño/Southern Oscillation, the Pacific–North American pattern, and the North Atlantic Oscillation exhibiting the largest influence. Across all climate indices considered, the signals are larger and can be detected more clearly for seasonal total versus extreme precipitation. We are able to detect at least some significant relationships in all seasons in spite of extremely large (> 95%) background variability in both mean and extreme precipitation. Furthermore, we specifically quantify how the spatial aspect of our analysis reduces uncertainty and increases detection of statistical significance while also discovering results that quantify the complex interconnected relationships between climate drivers and seasonal precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Viscoelastic-Mapping of Cellulose Nanofibrils Using Low-Total-Force Contact Resonance Force Microscopy (LTF-CRFM)

Low-total-force contact resonance force microscopy (LTF-CRFM), an atomic force microscopy method, is introduced as a non-destructive means to quantify the local viscoelastic loss tangent (tan..delta..) of supported cellulose nanofibrils (CNFs). The method limits static and dynamic forces during measurement to minimize substrate and geometry effects and to reduce the potential for stress-induced CNF damage. LTF-CRFM uses Brownian motion to achieve the thermally-limited lowest dynamic force, while approaching adhesive pull-off to achieve the low static force. LTF-CRFM measurements were shown to generate analyzable data without evidence of nonlinear artifacts and without damage to the CNF over static forces ranging from 11.6 to 84.6 nN. The measured tan..delta.. of CNFs was 0.015 +/- 0.0094, which is the first reported tan..delta.. measurement of an isolated CNF. Finally, LTF-CRFM successfully mapped tan..delta.. along the length of CNFs to determine that kink defects along the CNF do not impart a local viscoelastic property change at the spatial resolution of the measurement.

BIOMASS FUELS↗
DOE OSTI2024

Quantification of uranium metal and total uranium in U-UO 2 mixtures using H 3 PO 4 -HCl

Here, the selective dissolution of uranium metal from its mixtures with UO 2 was studied to establish a simple and rapid quantitative method. Uranium metal was found to selectively dissolve as U(IV) into a solution of phosphoric and hydrochloric acids, with quantitative dissolution occurring within 1 h. Total dissolution of uranium as U(VI) could then be obtained by nitric acid addition and heating for 0.5–1 h. Analysis of the resulting U(IV) and U(VI) solutions by ICP-OES or UV–Vis spectroscopy yielded uranium metal-to-UO 2 ratios with an accuracy of ± 10% or better. Accuracy of the ICP-OES method was slightly better than UV–Vis, but the simplicity of the latter makes it an attractive option for some applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Uncertainty improvement of 22 Na based radioactive tracer dilution for determining total mass of pyroprocessing molten salt systems by 154 Eu removal

To determine the total salt mass of the molten salt systems for pyroprocessing spent nuclear fuels, a 22 Na based radioactive tracer dilution was studied in Idaho National Laboratory in recent years. This 22 Na based RTD technique was deemed feasible, but due to the gamma energy peak of 22 Na coinciding with one of the energy peaks of 154 Eu radioisotope in the molten salt, the uncertainty of the 22 Na radioactivity in the 22 Na-spiked salt samples was quite high. To improve the uncertainty of the 22 Na based RTD technique, we proposed to chemically remove the 154 Eu of the salt samples by DGA resin for gamma spectroscopy. The effectiveness of removing 154 Eu on uncertainty improvement was evaluated. Furthermore, it was found that (1) the 154 Eu fission product effect on the uncertainty and detection limit can be effectively eliminated by chemically removing the 154 Eu during the salt sample preparation and (2) the uncertainty of 22 Na radioactivity in the salt samples for electrorefining was significantly improved from 13% to 2%, showing the potential of practical engineering application of 22 Na based RTD as a safeguards technique for molten salt systems for pyroprocessing spent nuclear fuels.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Total Blood Mercury Predicts Methylmercury Exposure in Fish and Shellfish Consumers

Abstract Many studies evaluating methylmercury (MeHg) toxicity rely on whole blood total mercury (THg) measurements to estimate MeHg exposure. However, whole blood THg includes other forms of mercury (Hg), such as inorganic Hg, which have different exposure sources and toxicological effects than MeHg. Therefore, estimating the whole blood MeHg/THg ratio is critical to predicting MeHg exposure and, subsequently, efforts to establish an exposure–response relationship for use in risk assessment. A large, representative dataset (National Health and Nutrition Examination Survey (NHANES) 2011–2016) was used to determine the whole blood MeHg/THg ratio among (a) self-reported fish and shellfish consumers, ≥ 15 years of age (the “full adult” population ( N = 5268 training dataset; N = 2336 test dataset)) and (b) female fish and shellfish consumers, 15–44 years of age (the “women of reproductive age” population ( N = 1285 training dataset; N = 560 test dataset)). Unadjusted and adjusted linear and spline models with direct measurements for both THg and MeHg were evaluated. The mean whole blood MeHg/THg ratio was 0.75 (95% confidence interval (CI): 0.74, 0.75). This ratio was significantly higher among those with higher THg concentrations. All models exhibited excellent fit (adjusted R 2 from 0.957 to 0.982). Performance was slightly improved in spline versus linear models. For the full adult population and women of reproductive age, the unadjusted spline model predicted whole blood MeHg concentrations of 5.65 µg/L and 5.55 µg/L, respectively, when the THg concentration was 5.80 µg/L. These results suggest that whole blood THg is a good predictor of whole blood MeHg among fish and shellfish consumers.

Wells, Ellen M.↗
DOE OSTI2020

Using yttrium as an indicator to estimate total rare earth element concentration: a case study of anthracite-associated clays from northeastern Pennsylvania

Abstract This study demonstrated using yttrium (Y) as an indicator to estimate the total rare earth element and Y contents (REY) in coal-associated samples and to facilitate selection of samples with high REY assays in a fast and inexpensive manner. More than 10 anthracite-associated samples were collected from each of three Pennsylvanian sites (sites B, J and C) based on Thorium gamma ray logging suggesting high REY content. Several samples from each site were analyzed by ICP-MS to determine the rare earth distribution patterns and to establish the site-specific linear equations of Y and REY. The Y contents of the remaining samples were measured by a portable X-ray fluorescence analyzer, and the REY values were estimated based on the site-specific linear equation developed earlier. R-squared values above 0.70 were obtained for all the estimation equations from all three sites on both a whole sample basis and an ash basis. Previously, ash content has been widely used as an indicator of high REY content. This may not be applicable for a specific site. Site B in this study is an example where ash contents could not be statistically correlated with REY, so using Y for estimation is more applicable. The demonstrated sample screening process is suitable for samples from sites that share more similar distribution patterns (either MREY or LREY or HREY) as well as for samples from sites that share multiple distribution patterns (LREY/MREY/HREY) depending on the desirable accuracy. The demonstrated process lowers the analytical cost from $70 to 80 dollars per sample to $10–15 per sample while significantly reducing the processing time and acid consumption for ICP digestion. This is particularly true when a relatively large sample size is involved, for example, 100 samples from one site analyzed by ICP-MS/OES.

Yang, Xiaojing↗
DOE OSTI2021

Local ordering in disordered Nd x Zr 1-x O 2-0.5x pyrochlore as observed using neutron total scattering

Pyrochlore complex oxides (A 2 B 2 O 7 ) are an important class of fluorite-derivative ceramics with exceptional chemical and structural versatility which make them ideal model systems for studying disordering mechanisms over a range of spatial scales. Here, neutron total scattering methods were used to analyze the structural behavior in the non-stoichiometric series Nd x Zr 1-x O 2-0.5x (0.5 ≤ x ≤ 0.23) as a function of Nd content, x. Characterization of the structure functions using Rietveld refinement and the pair distribution functions with small-box refinement reveal complex disordering pathways; the average, long-range phase changes over a very narrow compositional range from pyrochlore ($Fd\bar{3}m$) to defect fluorite ($Fm\bar{3}m$) through full randomization of the cation and anion sublattices at x ~ 0.31, while the local, short-range structure continuously adopts a weberite-type atomic arrangement (C222 1 ). Comparison to a previously studied Ho 2 Ti 2-x Zr x O 7 solid solution series reveals how changes in chemical composition and stoichiometry modify defect formation and determine how disordering progresses across different length scales in pyrochlore oxides.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Probing the D-region ionosphere globally with Earth Networks Total Lightning Network data

An existing technique to use broadband lightning waveforms to probe the D-region ionosphere (60–90 km altitude) is shown to be extendable to a global scale using the Earth Networks Total Lightning Network (ENTLN). This paper demonstrates the technique in detail on a region of the Southeastern United States. This demonstration shows that diurnal D-region height variation and smaller time-scale variations on the order of tens of minutes to hours are evident in the measurement. The technique is then extended to three additional global regions on this same day: Northeastern U.S., India, and Japan. The diurnal behavior between these different regions is compared to a D-region model from the International Reference Ionosphere.

D-region ionosphere↗
DOE OSTI2020

Intra-annual variations of regional total column ozone, aerosol optical depth, and water vapor from ground-based, satellite-based and model-based observations

The Microtops II ozonometer has been deployed to continuously measure the total column ozone (TCO), pre-cipitable water content (PWC) and aerosol optical thickness (AOT) at Atigre village (16.74° N, 74.37° E, 604 m above sea level, masl) located on the southeastern slope of Indian western Ghats. The Microtops II ozonometer measurements during the period from September 2017 to June 2018 were analyzed along with the retrieved products of Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASA's Terra satellites and also the ERA-interim reanalysis model. We found that the TCO (or PWC) data from the OMI (or MODIS) and the ERA reanalysis model data products are in good agreement. The mea-surements showed strong seasonal variability such that TCO was lowest in the winter season but increased in the summer season, and both PWC and AOT were lowest in the post-monsoon season and increased in the summer season. In continuous ERA-interim reanalysis TCO observations, we found the three types of periodicities in the daily mean TCO as well as PWC (i) The weekly (7 days), (ii) quasi-biweekly (14 to 16 days), (iii) Madden Julian Oscillations (MJO) (30–60 days) oscillations. These oscillations depend on the periodic weather changes in the troposphere. We also observe that the average day to day variability in daily mean TCO observations in the observational period is about 1.4%, 1.1%, 2.62% in the Microtops II ozonometer, ERA-interim reanalysis, and OMI data respectively. We found the positive correlation between daily mean AOT and PWC in all seasons (except monsoon), which is maximum in the winter season, showing the hygroscopic nature of aerosols. The sources of water vapor and aerosol at our location are also studied using back-trajectory analysis.

Nade, Dada R.↗
DOE OSTI2022

Short-term solar radiation forecast using total sky imager via transfer learning

Ground-based sky cameras, which capture hemispherical images, have been extensively used for localized monitoring of clouds. This paper proposes a short-term forecasting approach based on transfer learning using Total Sky-Imager (TSI) images of the Southern Great Plains (SGP) site obtained from the Atmospheric Radiation Measurement (ARM) dataset. An accurate estimation of solar irradiance using TSI is key for short-term solar energy generation forecasting and optimal energy consumption planning. We make use of deep neural network architectures such as AlexNet and ResNet-101 to extract the underlying deep convolution features from TSI images and then train using an ensemble learning approach to model and forecast solar radiation. We demonstrate the performance of the proposed approach by showcasing the best and worst cases. Thus, the transfer learning approach significantly reduces the time and resources required for modeling solar radiation. We outperform with reference to another state-of-art technique for solar modeling using TSI images at different forecast lead times.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

First Multimodal, Three-Dimensional, Image-Guided Total Marrow Irradiation Model for Preclinical Bone Marrow Transplantation Studies

Total marrow irradiation (TMI) has significantly advanced radiation conditioning for hematopoietic cell transplantation in hematologic malignancies by reducing conditioning-induced toxicities and improving survival outcomes in relapsed/refractory patients. However, the relapse rate remains high, and the lack of a preclinical TMI model has hindered scientific advancements. To accelerate TMI translation to the clinic, we developed a TMI delivery system in preclinical models.

62 RADIOLOGY AND NUCLEAR MEDICINE↗