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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Machine learning for analysis of atomic spectral data

Physics based forward models are the basis on which many experimental diagnostics are interpreted. For some diagnostics, models can be computationally expensive which precludes their use in real time analysis. Reduced models have the potential to capture sufficient physics thereby enabling the desired real time analysis. Using statistical inference and machine learning techniques the application of reduced models for inversion of atomic spectral data used to diagnose magnetic fields in a plasma will be examined. Two approaches are considered, (a) a reduction of the forward model where traditional inversion can be performed on the proxy model, and (b) a reduction of the direct inverse where parameters are a function of measured signal. The resulting inversion is sufficiently fast to be utilized in an online context for digital twinning, and ultimately real-time prediction, design, and control of plasma systems, such as tokamaks. Furthermore, these methods will be demonstrated on both simulated and experimentally measured data.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Electrochemical aptamer-based sensors: leveraging the sensing platform for minimally-invasive microneedle measurements and fundamental exploration of sensor biofouling dynamics

The ability to track the concentrations of specific molecules in the body in real time would significantly improve our ability to study, monitor, and respond to diseases. To achieve this, we require sensors that can withstand the complex environment inside the body. Electrochemical aptamer-based sensors are particularly promising for in vivo sensing, as they are among the only generalizable sensing technologies that can achieve real-time molecular monitoring directly in blood and the living body. In this project, we first focused on extending the application space of aptamer sensors to support minimally-invasive wearable measurements. To achieve this, we developed individually-addressable sensors with commercial off-the-shelf microneedles. We demonstrated sensor function in buffer, blood, and porcine skin (a common proxy for human skin). In addition to the applied sensing project, we also worked to improve fundamental understanding of the aptamer sensing platform and how it responds to biomolecular interferents. Specifically, we explored the interfacial dynamics of biofouling – a process impacting sensors placed in complex fluids, such as blood.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Experimental design applications for modeling and assessing carbon dioxide sequestration in saline aquifers

This project was a computer modeling effort to couple reservoir simulation and ED/RSM using Sensitivity Analysis, Uncertainty Analysis, and Optimization Methods, to assess geologic, geochemical, geomechanical, and rock-fluid effects and factors on CO 2 injectivity, capacity, and plume migration. The project objective was to develop proxy models to simplify the highly complex coupled geochemical and geomechanical models in the utilization and storage of CO 2 in the subsurface. The goals were to investigate and prove the feasibility of the ED/RSM processes and engineering development, and bridge the gaps regarding the uncertainty and unknowns of the many geochemical and geomechanical interacting parameters in the development and operation of anthropogenic CO 2 sequestration and storage sites. The bottleneck in this workflow is the high computational effort of reactive transport simulation models and large number of input variables to optimize with ED/RSM techniques. The project was not to develop the reactive transport, geomechanical, or ED/RSM software, but was to use what was commercially and/or publically available as a proof of concept to generate proxy or surrogate models. A detailed geologic and petrographic mineral assemblage and geologic structure of the doubly plunging anticline was defined using the USDOE RMOTC formations of interest data (e.g., Lower Sundance, Crow Mountain, Alcova Limestone, and Red Peak). The assemblage of 23 minerals was primarily developed from literature data and petrophysical (well log) analysis. The assemblage and structure was input into a commercial reactive transport simulator to predict the effects of CO 2 injection and complex reactions with the reservoir rock. Significant impediments were encountered during the execution phase of the project. The only known commercial reactive transport simulator was incapable of simulating complex geochemistry modeled in this project. Significant effort and project funding was expended to determine the limitations of both the commercial simulator and the Lawrence Berkeley National Laboratory (LBNL) R&D simulator, TOUGHREACT available to the project. A simplified layer cake model approximating the volume of the RMOTC targeted reservoirs was defined with 1-3 minerals eventually modeled with limited success. Modeling reactive transport in porous media requires significant computational power. In this project, up to 24 processors were used to model a limited mineral set of 1-3 minerals. In addition, geomechanical aspects of injecting CO 2 into closed, semi-open, and open systems in various well completion methods was simulated. Enhanced Oil Recovery (EOR) as a storage method was not modeled. A robust and stable simulation dataset or base case was developed and used to create a master dataset with embedded instructions for input to the ED/RSM software. Little success was achieved toward the objective of the project using the commercial simulator or the LBNL simulator versions available during the time of this project. Several hundred realizations were run with the commercial simulator and ED/RSM software, most having convergence problems and terminating prematurely. A proxy model for full field CO 2 injection sequestration utilization and storage was not capable of being developed with software available for this project. Though the chemistry is reasonably known and understood, based on the amount of effort and huge computational time required, predicting CO 2 sequestration storage capacity in geologic formations to within the program goals of ±30% proved unsuccessful.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Evaluating Proxy Apps with FPGAs

Field-programmable gate arrays (FPGAs) are becoming more promising for high performance computing (HPC). Unlike fixed hardware specialization, reconfigurability allows FPGAs to be customized for a wide variety of HPC workloads. Our ultimate goal is to understand the viability of FPGAs as accelerators for some of the key HPC codes at LLNL and identify application characteristics that can benefit from the reconfigurability of FPGAs. More specifically, this LDRD project conducted a detailed performance study of FPGAs using sparse matrix computations and identified key optimization techniques to effectively use FPGA hardware resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Climate reconstruction for the Entre‐Douro‐e‐Minho region ( NW Portugal) between AD 1626 and AD 1820: synthesis of viticulture data and foraminiferal evidence

This work presents two novel climate‐related time series for the northwest of Portugal. The first is an AD 1626–1820 triennial‐resolved wine production series, based on the Benedictine accounts from six monasteries of the Entre‐Douro‐e‐Minho ( EDM ) region. The second, an AD 1654–2010 benthic foraminiferal record from the Caminha salt marsh, located in the lower estuary of the Minho River. The series were analysed together for the common period to outline how both palaeoclimatic proxies respond to the most likely natural environmental drivers of temporal variability, solar forcing included. Singular spectral analysis revealed a common significant multidecadal periodicity agreeing with recognized long‐term changes in solar activity, i.e. the Lower Gleissberg cycle (50–80 years). The application of wavelet analysis allowed the detection of high coherence at this time scale (centred at c . 64 years) between marsh foraminifera and both total solar irradiance and the North Atlantic Oscillation index. This relationship persists throughout the c . AD 1730–1875 period. The continuous wavelet transform results for wine production were inconclusive. As the time‐span analysed is recognized as one of high socio‐economic and political distress, the main human‐driven impacts on wine production, particularly in the two periods of greatly reduced solar activity – the Maunder and Dalton Minima – are reviewed in the light of the available historical records. In addition to a documented climate‐related agricultural crisis in Portugal, damage and losses to wine production may have been triggered by several local and international conflicts in which the country was involved. But to what extent the two influences contributed to the wine production variations observed in the EDM region during both periods remains an open question.

Moreno, João↗
DOE OSTI2021

Datasets for DOE 2021 Communities LEAP Pilot

This submission offers data aligned to each of the four eligibility criteria outlined in the United States Department of Energy (DOE) 2021 Communities LEAP (Local Energy Action Program) Pilot. Please visit the LEAP website (https://www.energy.gov/communitiesLEAP/communities-leap) to learn more about LEAP and gain additional contextual information for how these data may be used. The data provided in the file approximates how the eligibility criteria apply at the census tract level across the United States (U.S.). The excel file available for download provides information pertaining to each of the four criteria outlined (average energy burden, percent low income, historic fossil energy communities) for all census tracts within the 50 U.S. States, the District of Columbia (D.C.), and Puerto Rico. The tabs within the excel file provide a file description, a summary data table (a simplified, easy to use presentation of the four eligibilities criteria), metadata (description, source, and other pertinent details for all variables provided), and a full, detailed data table. Please note that while these data are provided at the census tract level, census tracts do not necessarily have the same physical boundaries as a community but were used as they provide the closest proxy based on publicly available information collected using an empirically robust method. U.S. territories are not listed but are eligible to apply to Communities LEAP. As stated in the Opportunity Announcement, applying communities should describe how they meet the eligibility criteria in their application even if these data do not specifically show that they are eligible.

Communities↗
DOE OSTI2018

Methodology to Calculate the ACE and HPQ Metrics Used in the Wave Energy Prize

The U.S. Department of Energy's Wave Energy Prize Competition encouraged the development of innovative deep-water wave energy conversion technologies that at least doubled device performance above the 2014 state of the art. Because levelized cost of energy (LCOE) metrics are challenging to apply equitably to new technologies where significant uncertainty exists in design and operation, the prize technical team developed a reduced metric as proxy for LCOE, which provides an equitable comparison of low technology readiness level wave energy converter (WEC) concepts. The metric is called 'ACE' which is short for the ratio of the average climate capture width to the characteristic capital expenditure. The methodology and application of the ACE metric used to evaluate the performance of the technologies that competed in the Wave Energy Prize are explained in this report.

17 WIND ENERGY↗
DOE OSTI2026

Spectrally accurate, reverse-mode differentiable bounce-averaging algorithm and its applications

We present a fast, spectrally (exponentially) accurate, automatically differentiable bounce-averaging algorithm that is used to simplify kinetic models. Using this algorithm, implemented in the DESC stellarator optimisation suite, we can perform efficient optimisation of many objectives to improve stellarator performance, such as the effective ripple 𝜖 eff metric for the neoclassical transport coefficient in the low collisionality regime and proxies for energetic particle confinement. For the first time, we optimise a finite-beta stellarator to directly reduce neoclassical ripple transport using reverse-mode differentiation. This ensures the computational cost of differentiation is independent of the number of controllable parameters.

fusion plasma↗
DOE OSTI2020

Materials loss measurements using superconducting microwave resonators

The performance of superconducting circuits for quantum computing is limited by materials losses. In particular, coherence times are typically bounded by two-level system (TLS) losses at single photon powers and millikelvin temperatures. The identification of low loss fabrication techniques, materials, and thin film dielectrics is critical to achieving scalable architectures for superconducting quantum computing. Superconducting microwave resonators provide a convenient qubit proxy for assessing performance and studying TLS loss and other mechanisms relevant to superconducting circuits such as non-equilibrium quasiparticles and magnetic flux vortices. In this review article, we provide an overview of considerations for designing accurate resonator experiments to characterize loss, including applicable types of losses, cryogenic setup, device design, and methods for extracting material and interface losses, summarizing techniques that have been evolving for over two decades. Results from measurements of a wide variety of materials and processes are also summarized. Finally, we present recommendations for the reporting of loss data from superconducting microwave resonators to facilitate materials comparisons across the field.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

From Waste-Heat Recovery to Refrigeration: Compositional Tuning of Magnetocaloric Mn 1+ x Sb

Magnetic refrigeration, as well as waste-heat recovery, can be accomplished through the magnetocaloric effect, where temperature changes the magnetic state of a material or vice versa. Promising magnetocaloric materials display large changes in magnetic entropy (ΔS M ) upon application of a moderate magnetic field and are often associated with magnetic materials possessing some degree of magnetostructural coupling. In such compounds, the magnetic transition is coupled to some structural transition at the ordering temperature, and indicators for these are readily calculated by the magnetic deformation proxy Σ M . MnSb, with a Curie temperature T C = 577 K, has a calculated magnetic deformation of Σ M = 5.9% and is a promising candidate material for waste-heat recovery. The temperature dependence of structural, magnetic, and magnetocaloric properties of Mn 1+ x Sb, where $x$ is a tunable amount of interstitial Mn, is studied here. specifically, excess Mn is incorporated as an interstitial whose magnetic moment is antialigned with the stoichiometric Mn, and the excess Mn has the effect of lowering T C , such that the Curie temperature can be tuned from 577 K to nearly room temperature at 318 K for $x$ = 0.2. For $x$ = 0.0, 0.1, and 0.2, values of ΔS M under a maximum magnetic field $H$ = 5 T are found to be 3.65, 3.00, and 2.83 J K -1 kg -1 , respectively. While the maximum ΔS M decreases with $x$, the high refrigerant capacity a more holistic measure of performance-is retained in this highly tunable system.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Challenges in constraining anthropogenic aerosol effects on cloud radiative forcing using present-day spatiotemporal variability

A large number of processes are involved in the chain from emissions of aerosol precursor gases and primary particles to impacts on cloud radiative forcing. Those processes are manifest in a number of relationships that can be expressed as factors dlnX/dlnY driving aerosol effects on cloud radiative forcing. These factors include the relationships between cloud condensation nuclei (CCN) concentration and emissions, droplet number and CCN concentration, cloud fraction and droplet number, cloud optical depth and droplet number, and cloud radiative forcing and cloud optical depth. The relationship between cloud optical depth and droplet number can be further decomposed into the sum of two terms involving the relationship of droplet effective radius and cloud liquid water path with droplet number. These relationships can be constrained using observations of recent spatial and temporal variability of these quantities. However, we are most interested in the radiative forcing since the preindustrial era. Because few relevant measurements are available from that era, relationships from recent variability have been assumed to be applicable to the preindustrial to present-day change. Our analysis of Aerosol Comparisons between Observations and Models (AeroCom) model simulations suggests that estimates of relationships from recent variability are poor constraints on relationships from anthropogenic change for some terms, with even the sign of some relationships differing in many regions. Proxies connecting recent spatial/temporal variability to anthropogenic change, or sustained measurements in regions where emissions have changed, are needed to constrain estimates of anthropogenic aerosol impacts on cloud radiative forcing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

A robust calibration of the clumped isotopes to temperature relationship for foraminifers

The clumped isotope (Δ 47 ) proxy is a promising geochemical tool to reconstruct past ocean temperatures far back in time and in unknown settings, due to its unique thermodynamic basis that renders it independent from other environmental factors like seawater composition. Although previously hampered by large sample-size requirements, recent methodological advances have made the paleoceanographic application of Δ 47 on small (<5 mg) foraminifer samples possible. Previous studies show a reasonable match between Δ 47 calibrations based on synthetic carbonate and various species of planktonic foraminifers. However, studies performed before recent methodological advances were based on relatively few species and data treatment that is now outdated. To overcome these limitations and elucidate species-specific effects, we analyzed 14 species of planktonic foraminifers in sediment surface samples from 13 sites, covering a growth temperature range of ~0-28 °C. We selected mixed layer-dwelling and deep-dwelling species from a wide range of ocean settings to evaluate the feasibility of temperature reconstructions for different water depths. Various techniques to estimate foraminifer calcification temperatures were tested in order to assess their effects on the calibration and to find the most suitable approach. Results from this study generally confirm previous findings that there are no species-specific effects on the Δ 47 -temperature relationship in planktonic foraminifers, with one possible exception. Various morphotypes of Globigerinoides ruber were found to often deviate from the general trend determined for planktonic foraminifers. Our data are in excellent agreement with a recent foraminifer calibration study that was performed with a different analytical setup, as well as with a calibration based exclusively on benthic foraminifers. A combined, methodologically homogenized dataset also reveals very good agreement with an inorganic calibration based on travertines. Our findings highlight the potential of the Δ 47 paleothermometer to be applied to recent and extinct species alike to study surface ocean temperatures as well as thermocline variability for a multitude of settings and time scales.

58 GEOSCIENCES↗
DOE OSTI2025

Towards combination of charge and light readout at O(10) MeV energies in DUNE

The Deep Underground Neutrino Experiment (DUNE) is an experiment under construction that will employ 10-kt scale liquid-argon-TPC technology to do precision measurements of neutrino oscillations. Apart from the determination of CP violation in neutrino interactions, one of the main scientific goals of DUNE is the detection of neutrinos from a supernova burst. It is imperative to maximise the potential of the detector for extracting information for these rare events. The use of light signals to aid the calorimetry of neutrino interactions provides such potential. We will present current efforts to demonstrate the application of combined calorimetry in one of the DUNE prototype detectors at CERN. The ground-level placement of the detector allows collection of large samples of cosmic-ray muons stopping within its volume. Michel electrons from muon decay can be identified in both the ionization charge and scintillation light, serving as a proxy for supernova neutrino interactions at O(10) MeV energies. The method for demonstrating combined calorimetry and its associated challenges will be introduced. We will also summarise the current analysis status and future prospects.

Pěč, Viktor [Prague, Inst. Phys.] (ORCID:000000034↗
DOE OSTI2025

Forty-year hydropower generation reanalysis for Conterminous United States

First published in 2022, the RectifHyd dataset provides hydrologically consistent estimates of monthly net generation for approximately 1,500 hydropower plants in the United States, addressing a gap in industrial surveys that have collected monthly generation data from only ~10% of plants post-2003. Here we present RectifHydPlus—an extended and enhanced dataset that improves on both the proxy information and temporal downscaling methodology adopted in RectifHyd. In addition to providing updated estimates of historical monthly generation for 590 plants with >10 MW nameplate capacity from 1980 through 2019, RectifHydPlus adds a hydrological control dataset that isolates the influence of historical water availability on generation. The new hydrological control dataset is suited to applications seeking to represent the capabilities of the contemporary fleet subject to historical interannual variability in climate. RectifHydPlus also includes a forty-year, daily-resolution, spill-adjusted water release time series for each dam, allowing users to aggregate generation estimates to the desired temporal resolution.

Hydroelectricity↗
DOE OSTI2023

Practical Understanding of Cancer Model Identifiability in Clinical Applications

Mathematical models are a core component in the foundation of cancer theory and have been developed as clinical tools in precision medicine. Modeling studies for clinical applications often assume an individual’s characteristics can be represented as parameters in a model and are used to explain, predict, and optimize treatment outcomes. However, this approach relies on the identifiability of the underlying mathematical models. In this study, we build on the framework of an observing-system simulation experiment to study the identifiability of several models of cancer growth, focusing on the prognostic parameters of each model. Our results demonstrate that the frequency of data collection, the types of data, such as cancer proxy, and the accuracy of measurements all play crucial roles in determining the identifiability of the model. We also found that highly accurate data can allow for reasonably accurate estimates of some parameters, which may be the key to achieving model identifiability in practice. As more complex models required more data for identification, our results support the idea of using models with a clear mechanism that tracks disease progression in clinical settings. For such a model, the subset of model parameters associated with disease progression naturally minimizes the required data for model identifiability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Limitations of reanalysis data for wind power applications

Wind energy resource estimates commonly depend on simulated wind speed profiles generated by reanalysis or weather models due to the lack of long time series measurements with sufficient coverage at relevant heights (roughly 90 m above ground). However, modeled data, including reanalyses, can be noisy and display a wide range of biases and errors, variously attributed to terrain effects, poor coverage of assimilated inputs, and model resolution. Wind generation records, if available at high temporal and geographical resolution, can provide a proxy for wind measurements and allow for evaluation of reanalyses and weather model wind time series. We use a 7-year-long data set of hourly, plant-level generation records from over 100 wind plants across Texas to evaluate two commonly used reanalysis data sets (MERRA2 and ERA5). Additionally, we use 1-year of records (2019) to evaluate an operational, high-resolution regional weather modeling product (HRRR v3). We find that across the region, and across all modeling products, the modeled representation of wind generation (i.e., wind speeds at hub heights passed through a power curve) has relatively small mean errors when aggregated daily, but that accuracy and hourly correlation have a strong diurnal sensitivity. Accuracy and correlation systematically decline through the evening and markedly improve after sunrise. These diurnal patterns persist even in the highest resolution model tested (HRRR v3). We hypothesize the nighttime decline in accuracy is mostly due to poorly represented boundary layer conditions, perhaps related to model representation of stability, while other uncertainties (such as wake effects) play a secondary role.

17 WIND ENERGY↗
DOE OSTI2016

Application of distance correction to ChemCam laser-induced breakdown spectroscopy measurements

Laser-induced breakdown spectroscopy (LIBS) provides chemical information from atomic, ionic, and molecular emissions from which geochemical composition can be deciphered. Analysis of LIBS spectra in cases where targets are observed at different distances, as is the case for the ChemCam instrument on the Mars rover Curiosity, which performs analyses at distances between 2 and 7.4 m is not a simple task. Previously, we showed that spectral distance correction based on a proxy spectroscopic standard created from first-shot dust observations on Mars targets ameliorates the distance bias in multivariate-based elemental-composition predictions of laboratory data. In this work, we correct an expanded set of neutral and ionic spectral emissions for distance bias in the ChemCam data set. By using and testing different selection criteria to generate multiple proxy standards, we find a correction that minimizes the difference in spectral intensity measured at two different distances and increases spectral reproducibility. When the quantitative performance of distance correction is assessed, there is improvement for SiO 2 , Al 2 O 3 , CaO, FeOT, Na 2 O, K 2 O, that is, for most of the major rock forming elements, and for the total major-element weight percent predicted. But, for MgO the method does not provide improvements while for TiO 2 , it yields inconsistent results. Additionally, we observed that many emission lines do not behave consistently with distance, evidenced from laboratory analogue measurements and ChemCam data. This limits the effectiveness of the method.

36 MATERIALS SCIENCE↗
DOE OSTI2016

CoMD Implementation Suite in Emerging Programming Models

CoMD-Em is a software implementation suite of the CoMD [4] proxy app using different emerging programming models. It is intended to analyze the features and capabilities of novel programming models that could help ensure code and performance portability and scalability across heterogeneous platforms while improving programmer productivity. Another goal is to provide the authors and venders with some meaningful feedback regarding the capabilities and limitations of their models. The actual application is a classical molecular dynamics (MD) simulation using either the Lennard-Jones method (LJ) or the embedded atom method (EAM) for primary particle interaction. The code can be extended to support alternate interaction models. The code is expected ro run on a wide class of heterogeneous hardware configurations like shard/distributed/hybrid memory, GPU's and any other platform supported by the underlying programming model.

Haque, Riyaz↗