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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Development of a Heavy-Duty Electric Vehicle Integration and Implementation (HEVII) Tool

As demand for consumer electric vehicles (EVs) has drastically increased in recent years, manufacturers have been working to bring heavy-duty EVs to market to compete with Class 6-8 diesel-powered trucks. Many high-profile companies have committed to begin electrifying their fleet operations, but have yet to implement EVs at scale due to their limited range, long charging times, sparse charging infrastructure, and lack of data from in-use operation. Thus far, EVs have been disproportionately implemented by larger fleets with more resources. To aid fleet operators, it is imperative to develop tools to evaluate the electrification potential of heavy-duty fleets. However, commercially available tools, designed mostly for light-duty vehicles, are inadequate for making electrification recommendations tailored to a fleet of heavy-duty vehicles. The main challenge is that light-duty tools do not estimate real-time vehicle mass, a factor that has a disproportionate impact on the energy consumption of large commercial vehicles. The Heavy-Duty Electric Vehicle Integration and Implementation (HEVII) tool advances the state of the art in evaluating electrification potential and infrastructure requirements for fleets of commercial vehicles. In this work, the HEVII tool is demonstrated with non-uniformly sampled telematics data from an existing fleet to assess the suitability for electrification of each individual vehicle, determine optimal locations for charging infrastructure to support a fleet of EVs and analyze associated costs. Payload mass is predicted using sparse ground-truth data for all input drive cycles and an initial data analysis is conducted to assess the characteristics driving behaviors and energy consumption of the fleet using an adaptable vehicle model. Battery size requirements are determined by applying a novel charger placement algorithm to maximize routes that are viable for EVs and balance time delays with infrastructure development costs. This work details and demonstrates the different aspects of the HEVII tool, presenting preliminary results from an example use case.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Ultrafast Laser Welding and Terahertz Time-domain Spectroscopy of Soda Lime Silicate Glass

Joining and welding techniques of similar and dissimilar materials have reached their limits due to the inflexibility of adapting dielectric materials, e.g., glasses and ceramics, reproducibility for transparent materials, and cycle process time. The ability to join pieces of glasses using laser irradiation allows rapid processing of vacuum insulating glass (VIG) for a widening range of commercial energy-efficient applications. We have used a 1064-nm laser wavelength with 15 picoseconds pulse width and a 155-kHz repetition rate to weld commercial plate glass pieces. The welded samples were characterized via x-ray fluorescence (XRF), time-of-flight secondary ion mass spectrometry (TOF–SIMS), polarimetry, and terahertz time-domain spectroscopy (THz-TDS) to determine the integrity of the weld and chemical changes in the welded areas. Our data shows no significant changes in glass chemistry and structure on average over nano- to micro-scales occurred from the welding process within the limits of the characterization tools. Our results demonstrate successful welding of glass plates without significant changes in the glass chemistry, structure, or properties in the laser-modified region or strains in the bulk glass.

Matthies, Kathleen [ORNL] (ORCID:0009000213135441)↗
DOE OSTI2017

A Lagrangian particle method with remeshing for tracer transport on the sphere

A Lagrangian particle method (called LPM) based on the flow map is presented for tracer transport on the sphere. The particles carry tracer values and are located at the centers and vertices of triangular Lagrangian panels. Remeshing is applied to control particle disorder and two schemes are compared, one using direct tracer interpolation and another using inverse flow map interpolation with sampling of the initial tracer density. Test cases include a moving-vortices flow and reversing-deformational flow with both zero and nonzero divergence, as well as smooth and discontinuous tracers. We examine the accuracy of the computed tracer density and tracer integral, and preservation of nonlinear correlation in a pair of tracers. Here, we compare results obtained using LPM and the Lin–Rood finite-volume scheme. An adaptive particle/panel refinement scheme is demonstrated.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Autonomous phototaxis of hydrogel swimmers

The design of synthetic soft matter capable of emulating the complex behaviors of living organisms, such as sensing and adapting to their environment, remains an important challenge in developing biomimetic materials. Functionalized hydrogels are ideal candidates for such materials since they are highly responsive to their environment and can be operated in water. In this work, we investigate a hybrid bonding hydrogel composed of peptide amphiphile supramolecular nanofibers covalently attached to a photoresponsive network, in which high-aspect-ratio ferromagnetic nanowires are aligned along the length of the sample, designed to swim under oscillating magnetic fields. This hybrid hydrogel swimmer can autonomously swim toward a light source by utilizing photoinduced interactions between supramolecular and covalent networks reminiscent of phototactic swimming in living systems. Using a combination of experimental techniques and a continuum model incorporating photochemistry, magnetoelasticity, and hydrodynamics, we explain the swimming mechanism and predict phototactic behavior. Our work highlights the potential role of hybrid bonding polymers, which leverage the interplay between supramolecular assemblies and covalent networks. We demonstrate how these polymers can be tailored to react dynamically to their environment, paving the way for developing intelligent and autonomous robotic systems.

Science & Technology - Other Topics↗
DOE OSTI2023

Evaluating the Interplay between Trajectory Segmentation and Mode Inference Error

Travel behavior changes are essential to transportation decarbonization. Travel diaries, consisting of sequences of trips between places, are typically used to instrument human travel behavior. However, these diaries are only as accurate as the underlying methods used to construct them. Travel diary algorithms have been a popular research topic since the advent of Global Positioning System tracking surveys. These algorithms have typically been validated using prompted recall of presegmented trips, thus disregarding the continuity of mode inference. Phone operating systems have adopted battery-conserving techniques, but the resulting data collection errors have not been studied extensively. We introduce a framework to evaluate the accuracy of trip length computations and mode inference by analyzing continuous mode-segmented trajectories for groups of trips. We then use the framework to identify the input data quality and the impact of postprocessing. Our primary inputs to this evaluation are MobilityNet, a public dataset containing information from three artificial timelines covering 15 different travel modes, and sample open-source travel diary creation algorithms from the OpenPATH project. Our framework concretely shows that the variance of the distance error drops from (0.217, 0.0848) to (o.011, 0.0407) (Android, iOS) after postprocessing. Similarly, the weighted F-scores for mode inference increase from (0.25, 0.29) to (0.60, 0.74) (iOS, Android) between random forest and geographic information system-based models. We hope that this standardized method will be adapted to evaluate other, potentially proprietary, travel diary algorithms. Finally, the results can be used to understand and improve the state of the art in the travel diary creation field.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Towards long-term standardised carbon and greenhouse gas observations for monitoring Europe’s terrestrial ecosystems: A review

Research infrastructures play a key role in launching a new generation of integrated long-term, geographically distributed observation programmes designed to monitor climate change, better understand its impacts on global ecosystems, and evaluate possible mitigation and adaptation strategies. The pan-European Integrated Carbon Observation System combines carbon and greenhouse gas (GHG; CO 2 , CH 4 , N 2 O, H 2 O) observations within the atmosphere, terrestrial ecosystems and oceans. High-precision measurements are obtained using standardised methodologies, are centrally processed and openly available in a traceable and verifiable fashion in combination with detailed metadata. The Integrated Carbon Observation System ecosystem station network aims to sample climate and land-cover variability across Europe. In addition to GHG flux measurements, a large set of complementary data (including management practices, vegetation and soil characteristics) is collected to support the interpretation, spatial upscaling and modelling of observed ecosystem carbon and GHG dynamics. The applied sampling design was developed and formulated in protocols by the scientific community, representing a trade-off between an ideal dataset and practical feasibility. Finally, the use of open-access, high-quality and multi-level data products by different user communities is crucial for the Integrated Carbon Observation System in order to achieve its scientific potential and societal value.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Defining the Direction of Nuclear-Plasma Interaction Research at the National Ignition Facility

Electron-mediated nuclear-plasma interactions (NPIs) have the potential to change nuclear reaction rates in high energy density plasma (HEDP) environments, such as those found in experiments at the National Ignition Facility (NIF), in astrophysical phenomenon, or in nuclear detonations, relative to conventional laboratory measurements on room-temperature targets. Two Discovery Science shots to detect these interactions at the NIF were conducted in January and September 2017 at the conclusion of a campaign to develop the indirect-drive exploding pusher experimental platform and diagnostics. These shots were designed to measure the differential population of a high-spin isomer of 133 Xe of an inplasma versus a control sample, where a non-zero differential would indicate a measurable influence of the plasma on 134 Xe(n,2n) reactions. Preliminary observations from these shots were consistent with a small NPI effect, but improved theoretical understanding coupled with refined data analysis were needed to definitively establish the discovery or lack thereof. Achieving both of these, a statistically-credible NPI was indeed observed at a level predicted by an adapted Monte Carlo gamma-cascade model, a significant lowering by of the isomerto- ground state activity ratio in 133 Xe.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Ab Initio Many Body Quantum Embedding and Local Correlation in Crystalline Materials using Interpolative Separable Density Fitting

We present an efficient implementation of ab initio many-body quantum embedding and local correlation methods for infinite periodic systems through translational symmetry adapted interpolative separable density fitting, an approach which reduces the scaling of the calculations to only linear with the number of k-points. Employing this methodology, we compute correlated ground-state coupled cluster energies within density matrix embedding and local natural orbital correlation frameworks for both weakly and strongly correlated solids, using up to 1000 k-points. By extrapolating the local correlation domains and k-point sampling we further obtain estimates of the full coupled cluster with singles, doubles, and perturbative triples ground-state energies in the thermodynamic limit.

Chemical Physics (physics.chem-ph)↗
DOE OSTI2023

Field-scale dynamics of planting dates in the US Corn Belt from 2000 to 2020

Crop planting dates are a dynamic feature of agricultural systems that respond to short- and long-term climate signals, crop and cultivar selection, and technology changes. Planting date records are essential for yield gap analyses, accurate crop modeling, and tracking farmer adaptations to weather and climate change. Although planting dates have high variation at local scales due to heterogeneity in farm resources and decision-making, available long-term data on planting dates is largely restricted to aggregated regional statistics or, at best, satellite-derived datasets with limited spatiotemporal extent and at resolutions unable to distinguish individual fields (> 250 m). Here, we generated retrospective annual field-scale (30 m) planting date maps for both maize and soybeans spanning 2000-2020 across a 12 state region in the United States Corn Belt based on Landsat satellite data and a large ground sample of over 28,000 maize and soybean fields. Using training data from 2015-2020 for model selection, we found that planting date predictions improved with harmonic regression of Landsat data and additional annual weather covariates. The preferred random forests model approximately doubled performance compared to a null model based on state median planting dates, capturing 47% of field-level variation for maize (mean absolute error, MAE = 7.4 days) and 44% for soybeans (MAE = 7.5 days) against held-out ground truth test data for 2008-2014. We also evaluated the full 2000-2020 dataset with state agricultural statistics, finding strong agreement with median planting dates for maize (R 2 = 0.76, MAE = 4.4 days) and slightly lower agreement for soybeans (R 2 = 0.65, MAE = 5.4 days) when aggregated to the state level. We then used this new dataset to analyze environmental determinants of planting dates at a finer-scale than previously possible, controlling for unobserved variation at the sub-state district level. We found that during 2000-2020, each standard deviation increase in rainfall delayed planting by ~ 2.5 days, and fields with higher soil productivity ratings tended to be planted earlier. We did not find meaningful trends over the last two decades in planting dates for maize or soybeans, in contrast to trends towards earlier planting dates late last century and predicted for this period in climate adaptation studies. We hypothesize increases in early season rainfall may have inhibited these shifts towards earlier planting. Remotely sensed planting dates will be a useful tool for yield gap analyses, crop simulation modeling, and ongoing assessment of climate adaptation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Persistent Octrees for Parallel Mesh Refinement Through Non-Volatile Byte-Addressable Memory

We report that octree-based mesh adaptation has enabled simulations of complex physical phenomena. Existing meshing algorithms were proposed with the assumption that computer memory is volatile. Consequently, for failure recovery, the in-core algorithms need to save memory states as snapshots with slow file I/Os. The out-of-core algorithms store octants on disks for persistence. However, neither of them was designed to leverage unique characteristics of non-volatile byte-addressable memory (NVBM). In this paper, we propose a novel data structure Distributed Persistent Merged octree (DPM-octree) for both meshing and in-memory storage of persistent octrees using NVBM. It is a multi-version data structure and can recover from failures using its earlier persistent version stored in NVBM. In addition, we design a feature-directed sampling approach to help dynamically transform the DPM-octree layout for reducing NVBM-induced memory write latency. DPM-octree uses parity trees which are created using erasure coding and stored in NVBM to support low-latency in-memory octant recovery after data loss. DPM-octree has been successfully integrated with Gerris software for simulation of fluid dynamics. Finally, our experimental results with real-world scientific workloads show that DPM-octree scales up to 1.1 billion mesh elements with 1000 processors on the Titan supercomputer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A spatiotemporally explicit and scalable indicator of intact lands across the conterminous United States, 1986–2023

Globally, ecologically intact areas are increasingly scarce. Agricultural expansion into previously uncultivated areas drives the loss of intact lands that might otherwise exhibit high levels of ecological integrity. Thus, the absence of cultivation can be an indicator of intact lands as measured from remote sensing data and thematic maps. Our objective for this study was to develop and compare tractable approaches based on remotely sensed satellite data to map spatial patterns of potentially intact lands across the conterminous U.S. (CONUS). Using annual cultivation probabilities derived from satellite observations, we classified and mapped potentially intact lands across CONUS from 1986 to 2023 at 30 m resolution. We created three maps, first by applying a constant cultivation probability threshold across CONUS, second by varying the threshold state-by-state to maximize state-level overall accuracies, and third by equalizing the state-level user's and producer's accuracies to minimize classification bias. Validation against 800,000+ independent ground samples resulted in CONUS-level overall accuracies ≥85% for the roughly 660 million ha of potentially intact land. Map accuracy varied with the proportion of potentially intact lands across regions, with the Pacific-Mountain and Great Plains regions exhibiting the highest accuracies, while Eastern CONUS exhibited a greater mix of potentially intact and non-intact lands and more moderate map accuracies. These novel maps and approaches can be adapted to different spatiotemporal extents to support conservation and production decisions ranging from species and ecosystems protection to reducing land conversion and climate mitigation.

agriculture↗
DOE OSTI2019

Super-resolution energy spectra from neutron direct-geometry spectrometers

Neutron direct-geometry time-of-flight chopper spectroscopy is instrumental in studying fundamental excitations of vibrational and/or magnetic origin. We report here that techniques in super-resolution optical imagery (which is in real-space) can be adapted to enhance resolution and reduce noise for a neutron spectroscopy (an instrument for mapping excitations in reciprocal space). The procedure to reconstruct super-resolution energy spectra of phonon density of states relies on a realization of multiframe registration, accurate determination of the energy-dependent point spread function, asymmetric nature of instrument resolution broadening, and iterative reconstructions. Applying these methods to phonon density of states data for a graphite sample demonstrates contrast enhancement, noise reduction, and ~5-fold improvement over nominal energy resolution. The data were collected at three different incident energies measured at the wide angular-range chopper spectrometer at the Spallation Neutron Source.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Dual microscopy to explore enhanced atmospheric ice nucleation on multi-component aerosols

Using an optical microscopy setup adapted to in-situ studies of ice formation at ambient pressure, we examined a specific multicomponent mineral, microcline, with the ultimate aim of gaining a more realistic understanding of ice nucleation in Earth’s atmosphere. We focused on a perthitic feldspar, microcline, to test the hypothesis that co-existence in some feldspars of K-rich and Na-rich phases are contributing to enhanced ice nucleation. On a sample deliberately chosen to contain lamella, a typical perthitic microstructure, and flat surface regions next to each other, we performed a series of ice formation experiments. We found microcline to promote ice formation, causing a large number of ice nucleation events at around - 27°C. The number of ice nuclei decreased from experimental run to experimental run, indicating surface aging upon repeated exposure to humidity. An analysis of 10 experimental runs of identical conditions did not reveal an obvious enhancement of ice formation at the lamellar microstructure. Instead, we find efficient nucleation at various surface sites that produce orientationally aligned ice crystallites with asymmetric shape. Based on this observation we propose that surface steps running along select directions produce microfacets of an orientation that is favorable to enhanced ice nucleation, similar to previously reported for K-rich feldspars.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

ULTRA-DEEP GEMINI NEAR-INFRARED OBSERVATIONS OF THE BULGE GLOBULAR CLUSTER NGC 6624

We used ultra-deep J and K {sub s} images secured with the near-infrared (NIR) GSAOI camera assisted by the multi-conjugate adaptive optics system GeMS at the GEMINI South Telescope in Chile, to obtain a ( K {sub s} , J - K {sub s} ) color–magnitude diagram (CMD) for the bulge globular cluster NGC 6624. We obtained the deepest and most accurate NIR CMD from the ground for this cluster, by reaching K {sub s} ∼ 21.5, approximately 8 mag below the horizontal branch level. The entire extension of the Main Sequence (MS) is nicely sampled and at K {sub s} ∼ 20 we detected the so-called MS “knee” in a purely NIR CMD. By taking advantage of the exquisite quality of the data, we estimated the absolute age of NGC 6624 ( t {sub age} = 12.0 ± 0.5 Gyr), which turns out to be in good agreement with previous studies in the literature. We also analyzed the luminosity and mass functions of MS stars down to M ∼ 0.45 M{sub ⊙}, finding evidence of a significant increase of low-mass stars at increasing distances from the cluster center. This is a clear signature of mass segregation, confirming that NGC 6624 is in an advanced stage of dynamical evolution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Synroc Waste-forms for Immobilization of Advanced Reprocessing Wastes - 16167

EURO-GANEX, an advanced reprocessing technology, aims to separate both major (U, Pu) and minor (Np, Am, and Cm) actinides together from fission products. As the final waste composition is free from actinides - as opposed to current process waste, e.g. from PUREX - adapted immobilization matrices need to be developed. Synroc is a potential wasteform that has proven itself to be efficient to immobilize high-level nuclear wastes (HLW). In this study, a new composition of Synroc, 'Synroc-Z', is designed and characterized. The primary modification is to reduce the amount of zirconolite phase, which acts as the main host for actinides. The optimum hot-press conditions for Synroc-Z samples with a waste loading of 20 wt% were determined to be: 1200 deg. C and 20 MPa for 3 h. The durability of Synroc-Z was examined via the MCC-1 test at 90 deg. C. It shows similar leach resistance to Synroc-C, which is much better than current glass waste-forms. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

A new μ -high energy resolution fluorescence detection microprobe imaging spectrometer at the Stanford Synchrotron Radiation Lightsource beamline 6-2

In this report we describe a new synchrotron X-ray Fluorescence (XRF) imaging instrument with an integrated High Energy Fluorescence Detection X-ray Absorption Spectroscopy (HERFD-XAS) spectrometer at the Stanford Synchrotron Radiation Lightsource at beamline 6-2. The X-ray beam size on the sample can be defined via a range of pinhole apertures or focusing optics. XRF imaging is performed using a continuous rapid scan system with sample stages covering a travel range of 250 × 200 mm 2 , allowing for multiple samples and/or large samples to be mounted. The HERFD spectrometer is a Johann-type with seven spherically bent 100 mm diameter crystals arranged on intersecting Rowland circles of 1 m diameter with a total solid angle of about 0.44% of 4π sr. A wide range of emission lines can be studied with the available Bragg angle range of ~64.5°–82.6°. With this instrument, elements in a sample can be rapidly mapped via XRF and then selected features targeted for HERFD-XAS analysis. Furthermore, utilizing the higher spectral resolution of HERFD for XRF imaging provides better separation of interfering emission lines, and it can be used to select a much narrower emission bandwidth, resulting in increased image contrast for imaging specific element species, i.e., sparse excitation energy XAS imaging. This combination of features and characteristics provides a highly adaptable and valuable tool in the study of a wide range of materials.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Multiclass Classification Using Bayesian Multivariate Adaptive Regression Splines

We present a new Bayesian model for the problem of multiclass classification. In this model, the probabilities of class membership of a given observation are determined by the mean of a latent Gaussian distribution. The mean functions of this latent distribution consist of combinations of highly flexible basis functions of the inputs: multivariate adaptive regression splines (MARS), first developed for multiple regression. We use reversible jump Markov chain Monte Carlo to make inference on the classification model, including the number of basis functions. We compare the probabilistic classification performance of our proposed approach to existing methods on simulated and benchmark data, and compare uncertainty estimates on simulated data. Our proposed method compares favorably with existing Bayesian and frequentist multiclass classification methods in out-of-sample probabilistic classification, and uncertainty estimation of these probabilistic classifications. We examine the fit of the proposed method to a data set of hurricane storm surge levels near Delaware Bay, US, and conclude that sea level rise is a key contributor to damage delivered by storm surge.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Comparative transcriptomics between Synechococcus PCC 7942 and Synechocystis PCC 6803 provide insights into mechanisms of adaptation to stress.

Background: Synechococcus sp. PCC 7942 and Synechocystis sp. PCC 6803 are model cyanobacteria from which the metabolism and adaptive responses of other cyanobacteria are inferred. Here we report the gene expression response of these two strains to a variety of nutrient and environmental stresses of varying duration, using transcriptomics. Our data comprise both stranded and 5' enriched libraries in order to elucidate many aspects of the transcriptome. Results: Both organisms were exposed to stress conditions due to nutrient deficiency (inorganic carbon) or change of environmental conditions (salinity, temperature, pH, light) sampled at 1 and 24 hours after the application of stress. The transcriptome profile of each strain revealed similarities and differences in gene expression for photosynthetic and respiratory electron transport chains and carbon fixation. Transcriptome profiles also helped us improve the structural annotation of the genome and identify possible missed genes (including anti-sense) and determine transcriptional units (operons). Finally, we predicted association of proteins of unknown function biochemical pathways by associating them to well-characterized ones based on their transcript levels correlation. Conclusions: Overall, this study results an informative annotation of those species and the comparative analysis of the response of the two organisms revealed similarities but also significant changes in the way they respond to external stress and the duration of the response

59 BASIC BIOLOGICAL SCIENCES↗