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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Artificial ground reflector size and position effects on energy yield and economics of single‐axis‐tracked bifacial photovoltaics

Abstract Artificial ground reflectors improve bifacial energy yield by increasing both front and rear‐incident irradiance. Studies have demonstrated an increase in energy yield due to the addition of artificial reflectors; however, they have not addressed the effect of varying reflector dimensions and placement on system performance and the impact of these parameters on the reflectors' financial viability. We studied the effect of high albedo (70% reflective) artificial reflectors on single‐axis‐tracked bifacial photovoltaic systems through ray‐trace modeling and field measurements. In the field, we tested a range of reflector configurations by varying reflector size and placement and demonstrated that reflectors increased daily energy yield up to 6.2% relative to natural albedo for PERC modules. To confirm the accuracy of our model, we compared modeled and measured power and found a root mean square error (RMSE) of 5.4% on an hourly basis. We modeled a typical meteorological year in Golden, Colorado, to demonstrate the effects of artificial reflectors under a wide range of operating conditions. Seventy percent reflective material can increase total incident irradiance by 1.9%–8.6% and total energy yield by 0.9%–4.5% annually after clipping is considered with a DC–AC ratio of 1.2. Clipping has a significant effect on reflector impact and must be included when assessing reflector viability because it reduces reflector energy gain. We calculated a maximum viable cost for these improvements of up to $2.50–4.60/m 2 , including both material and installation, in Golden. We expanded our analysis to cover a latitude range of 32–48°N and demonstrated that higher‐latitude installations with lower energy yield and higher diffuse irradiance content can support higher reflector costs. In both modeling and field tests, and for all locations, the ideal placement of the reflectors was found to be directly underneath the module due to the optimized rear irradiance increase.

14 SOLAR ENERGY↗
DOE OSTI2020

Deterministic incident-wave elevation prediction in intermediate water depth

Potential performance gains from optimal (non-causal) impedance-matching control of wave energy devices in irregular ocean waves are dependent on deterministic wave elevation prediction techniques that work well in practical applications. Although a number of devices are designed for operation in intermediate water depths, little work has been reported on deterministic wave prediction in such depths. Here, we investigated a deterministic wave-prediction technique based on an approximate propagation model that leads to an analytical formulation, which may be convenient to implement in practice. To improve accuracy, an approach to combine predictions based on multiple up-wave measurement points is evaluated. The overall method is tested using experimental time-series measurements recorded in the U.S. Navy MASK basin in Carderock, MD, USA. For comparison, an alternative prediction approach based on Fourier coefficients is also tested with the same data. Comparison of prediction approaches with direct measurements suggest room for improvement. Possible sources of error including tank reflections are estimated, and potential mitigation approaches are discussed.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Effects of micrometer-scale surface roughness on thermal infrared emittance spectra of silica glass

Surface roughness is known to decrease thermal infrared (TIR) absorption band intensity, but studies of the effect on geologically relevant samples are relatively limited. To determine the effect of surface roughness (with features smaller than ~2/3 of the wavelength) on TIR spectra, we investigated two glass compositions with prepared roughened surfaces: (1) high purity fused silica and (2) soda-lime glass (73 wt% SiO$_2$). We roughened the surfaces of the glasses by sandblasting and polishing with grit paper. The surfaces were characterized with scanning electron microscopy and stylus profilometry. We then analyzed the roughened glasses with TIR emittance spectroscopy. Micrometer-scale roughness causes a decrease in TIR absorption band intensity, relative to a specular surface. No significant changes in band shape or shifts in wavelength were detected. As roughness increases, empirical results show a logarithmic decrease in TIR absorption band intensity. The logarithmic trends of the two glass compositions are different; empirical roughness calibrations do not translate across different compositions. A linear, least-squares spectral deconvolution using two endmembers, specular and blackbody, predicts model spectra of roughened glass surfaces with relatively low error. This is of consequence to orbital TIR measurements of poorly constrained targets, such as the martian surface, because micrometer-scale roughness is adequately modeled by the addition of a blackbody spectrum to the deconvolution endmember matrix.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Modeling injection-induced fault slip using long short-term memory networks

Stress changes due to changes in fluid pressure and temperature in a faulted formation may lead to the opening/shearing of the fault. This can be due to subsurface (geo)engineering activities such as fluid injections and geologic disposal of nuclear waste. Such activities are expected to rise in the future making it necessary to assess their short- and long-term safety. Here, a new machine learning (ML) approach to model pore pressure and fault displacements in response to high-pressure fluid injection cycles is developed. The focus is on fault behavior near the injection borehole. To capture the temporal dependencies in the data, long short-term memory (LSTM) networks are utilized. To prevent error accumulation within the forecast window, four critical measures to train a robust LSTM model for predicting fault response are highlighted: (i) setting an appropriate value of LSTM lag, (ii) calibrating the LSTM cell dimension, (iii) learning rate reduction during weight optimization, and (iv) not adopting an independent injection cycle as a validation set. Several numerical experiments were conducted, which demonstrated that the ML model can capture peaks in pressure and associated fault displacement that accompany an increase in fluid injection. The model also captured the decay in pressure and displacement during the injection shut-in period. Further, the ability of an ML model to highlight key changes in fault hydromechanical activation processes was investigated, which shows that ML can be used to monitor risk of fault activation and leakage during high pressure fluid injections.

58 GEOSCIENCES↗
DOE OSTI2021

Numerical simulation of NSLS-II fast orbit feedback system

We discuss recent work on the construction of a numerical simulation of the fast orbit feedback system at NSLS-II. The simulation operates in the time domain and also includes the spatial domain, i.e. all beam position monitors (BPMs) and correctors. It can accept inputs of the real beam orbit and the measured orbit response matrix. It can also add errors to every stage of the calculation. We present methods to verify the simulation results by comparing the simulation results with experimental data collected at NSLS-II. The results are in very good agreement. The effects of errors from BPMs and correctors, as well as the amplitude of excitation, on the feedback performance, are also explored. This simulation can be used to predict the behavior and performance of the system for a future upgrade.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Evaluation of Monin‐Obukhov Similarity Theory Wind Profiles in Convective Storm Environments and Cold Pools at the ARM Southern Great Plains Atmospheric Observatory

Monin-Obukhov similarity theory (MOST) is widely used in numerical weather prediction to model surface fluxes of momentum, heat, and water vapor. However, MOST is based on assumptions of steady state and horizontally homogeneous turbulence that can lead to prediction errors in and around convective storms. To understand the nature of these errors, we used wind and eddy covariance flux measurements from the Atmospheric Radiation Measurement Southern Great Plains Atmospheric Observatory to evaluate MOST wind profiles in fair-weather and convective storm environments, specifically those of mesoscale convective systems and ordinary thunderstorms. MOST wind profiles agreed well with observations in fair-weather cases, while in convective storm cases the theory systematically overestimated shear in cold pools after gust front passage. Surface layer stability was found to be important in assessing MOST within convective storm environments. The overestimation of wind shear in cold pools suggests the role of non-local fluxes in transferring momentum downward. We discuss reasons for differences and agreement with past studies, and conclude with recommendations to improve prediction of surface winds and fluxes in convective storm simulations.

58 GEOSCIENCES↗
DOE OSTI2024

Real space iterative reconstruction for vector tomography (RESIRE-V)

Tomography has had an important impact on the physical, biological, and medical sciences. To date, most tomographic applications have been focused on 3D scalar reconstructions. However, in some crucial applications, vector tomography is required to reconstruct 3D vector fields such as the electric and magnetic fields. Over the years, several vector tomography methods have been developed. Here, we present the mathematical foundation and algorithmic implementation of REal Space Iterative REconstruction for Vector tomography, termed RESIRE-V. RESIRE-V uses multiple tilt series of projections and iterates between the projections and a 3D reconstruction. Each iteration consists of a forward step using the Radon transform and a backward step using its transpose, then updates the object via gradient descent. Incorporating with a 3D support constraint, the algorithm iteratively minimizes an error metric, defined as the difference between the measured and calculated projections. The algorithm can also be used to refine the tilt angles and further improve the 3D reconstruction. To validate RESIRE-V, we first apply it to a simulated data set of the 3D magnetization vector field, consisting of two orthogonal tilt series, each with a missing wedge. Our quantitative analysis shows that the three components of the reconstructed magnetization vector field agree well with the ground-truth counterparts. We then use RESIRE-V to reconstruct the 3D magnetization vector field of a ferromagnetic meta-lattice consisting of three tilt series. Our 3D vector reconstruction reveals the existence of topological magnetic defects with positive and negative charges. We expect that RESIRE-V can be incorporated into different imaging modalities as a general vector tomography method. To make the algorithm accessible to a broad user community, we have made our RESIRE-V MATLAB source codes and the data freely available at https://github.com/minhpham0309/RESIRE-V.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Predissociation-based measurements of bond dissociation energies: US 2 , OUS, and USe

The uranium-containing molecules US 2 , OUS, and USe have been investigated using a pulsed laser ablation supersonic beam molecular source with time-of-flight mass spectrometric detection. Spectra have been recorded using the resonant two-photon ionization method over the spectroscopic range from 277 to 238 nm. These species have a myriad of excited electronic states in this spectroscopic region, leading to spectra that are highly congested and appear quasicontinuous. Sharp predissociation thresholds are observed, allowing precise bond dissociation energies to be measured. In the case of the triatomic molecules, it was necessary to use one laser for excitation and a delayed laser for ionization in order to observe a sharp predissociation threshold that allowed a precise bond dissociation energy to be measured. The resulting thermochemical values are D 0 (SU-S) = 4.910 ± 0.003 eV, D 0 (OU-S) = 5.035 ± 0.004 eV, and D 0 (USe) = 4.609 ± 0.009 eV. These results provide the first measurement of D 0 (USe) and reduce the error limits in the previous values of D 0 (SU-S) and D 0 (OU-S) by a factor of more than 70.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Fast and stable deep-learning predictions of material properties for solid solution alloys

We present a novel deep learning (DL) approach to produce highly accurate predictions of macroscopic physical properties of solid solution binary alloys and magnetic systems. The major idea is to make use of the correlations between different physical properties in alloy systems to improve the prediction accuracy of neural network (NN) models. We use multitasking NN models to simultaneously predict the total energy, charge density and magnetic moment. These physical properties mutually serve as constraints during the training of the multitasking NN, resulting in more reliable DL models because multiple physics properties are correctly learned by a single model. Two binary alloys, copper–gold (CuAu) and iron–platinum (FePt), were studied. Our results show that once the multitasking NN's are trained, they can estimate the material properties for a specific configuration hundreds of times faster than first-principles density functional theory calculations while retaining comparable accuracy. We used a simple measure based on the root-mean-squared errors to quantify the quality of the NN models, and found that the inclusion of charge density and magnetic moment as physical constraints leads to more stable models that exhibit improved accuracy and reduced uncertainty for the energy predictions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Synthetic spectra for Lyman- α forest analysis in the Dark Energy Spectroscopic Instrument

Synthetic data sets are used in cosmology to test analysis procedures, to verify that systematic errors are well understood and to demonstrate that measurements are unbiased. In this work we describe the methods used to generate synthetic datasets of Lyman-α quasar spectra aimed for studies with the Dark Energy Spectroscopic Instrument (DESI). In particular, we focus on demonstrating that our simulations reproduces important features of real samples, making them suitable to test the analysis methods to be used in DESI and to place limits on systematic effects on measurements of Baryon Acoustic Oscillations (BAO). We present a set of mocks that reproduce the statistical properties of the DESI early data set with good agreement. Additionally, we use a synthetic dataset to forecast the BAO scale constraining power of the completed DESI survey through the Lyman-α forest.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Primordial non-Gaussianity from the completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey – I: Catalogue preparation and systematic mitigation

ABSTRACT We investigate the large-scale clustering of the final spectroscopic sample of quasars from the recently completed extended Baryon Oscillation Spectroscopic Survey (eBOSS). The sample contains 343 708 objects in the redshift range 0.8 < z < 2.2 and 72 667 objects with redshifts 2.2 < z < 3.5, covering an effective area of $4699\, {\rm deg}^{2}$. We develop a neural network-based approach to mitigate spurious fluctuations in the density field caused by spatial variations in the quality of the imaging data used to select targets for follow-up spectroscopy. Simulations are used with the same angular and radial distributions as the real data to estimate covariance matrices, perform error analyses, and assess residual systematic uncertainties. We measure the mean density contrast and cross-correlations of the eBOSS quasars against maps of potential sources of imaging systematics to address algorithm effectiveness, finding that the neural network-based approach outperforms standard linear regression. Stellar density is one of the most important sources of spurious fluctuations, and a new template constructed using data from the Gaia spacecraft provides the best match to the observed quasar clustering. The end-product from this work is a new value-added quasar catalogue with the improved weights to correct for non-linear imaging systematic effects, which will be made public. Our quasar catalogue is used to measure the local-type primordial non-Gaussianity in a companion paper.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Large scale structure reconstruction with short-wavelength modes

Large scale density modes are difficult to measure because they are sensitive to systematic observational errors in galaxy surveys, but we can study them indirectly by observing their impact on small scale perturbations. Cosmological perturbation theory predicts that second-order density inhomogeneities are a convolution of a short- and a long-wavelength mode. This arises physically because small scale structures grow at different rates depending on the large scale environment in which they reside. This induces an off-diagonal term in the two-point statistics in Fourier space that we use as the basis for a quadratic estimator for the large scale field. Here, we demonstrate that this quadratic estimator works well on an N-body simulation of size (2.5 h -1 Gpc) 3 . In particular, the quadratic estimator successfully reconstructs the long-wavelength modes using only small-scale information. This opens up novel opportunities to study structure on the largest observable scales.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

OptZConfig: Efficient Parallel Optimization of Lossy Compression Configuration

Lossless compressors have very low compression ratios that do not meet the needs of today's large-scale scientific applications that produce vast volumes of data. Error-bounded lossy compression (EBLC) is considered a critical technique for the success of scientific research. Although EBLC allows users to set an error bound for the compression, users have been unable to specify the requirements on the compression quality, limiting practical use. Our contributions are: (1) We formulate the problem of configuring EBLC to preserve a user-defined metric as an optimization problem. This allows many classes of new metrics to be preserved, which improves over current practices. (2) We present a framework, OptZConfig, that can adapt to improvements in the search algorithm, compressor, and metrics with minimal changes, enabling future advancements in this area. (3) We demonstrate the advantages of our approach against the leading methods to configure compressors to preserve specific metrics. Here, our approach improves compression ratios against a specialized compressor by up to 3 x, has a 56x speedup over FRaZ, 1000x speedup over MGARD-QOI post tuning, and 110x speedup over systematic approaches which had not been bounded by compressors before.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Investigation of potential causes of production limiting fouling within SWPF due to mercury solids formation during pH swings within the SWPF process

The Salt Waste Processing Facility (SWPF) goal to investigate the use a high sodium Salt Batch 5 Qualification sample as the radioactive salt solution for mixing tests meant to evaluate the propensity for solids formation between the 5.6 M sodium clarified salt solution (CSS) and scrub solutions (0.05 M HNO 3 and 0.025 M NaOH solutions) during pH changes has been completed at SRNL. The key results and conclusions from this investigation to evaluate the propensity for solids formation between CSS and scrub solutions because of pH fluctuations include the following: None of the 8 test matrices, involving the mixing/titrating of scrub solution with CSS and vice versa, showed any visible evidence for the formation of solids with pH changes. The average turbidity measurements for these 8 tests, excluding test 7, was 21.6 ± 0.4 NTU. This average turbidity value is within 2 sigma of the baseline turbidity value of 20.5 NTU for the CSS only without added scrub solutions. However, only in test 7, which involved the titrating of CSS into dilute nitric acid scrub solution (0.05 M HNO 3 solution), was a small measurable change in the turbidity of the mixture observed at 31.9 ºC. On the other hand, the equivalent test (instantaneous addition of CSS into 0.05 M HNO 3 ) gave an average turbidity measurement value of 21.6 ± 0.6 NTU at a temperature of 24.0 ºC. This difference in turbidity measurement has been attributed to either instrument performance errors or the effect of temperature. It is recommended that these CSS and scrub solution mixing tests be performed with corresponding simulant solutions in a non-radioactive environment. A simulant environment will aid in the full integration of a pH and turbidity meter equipment with the experimental set up. A new detection method, preferable a laser-based method, may be needed in detecting and confirming the precipitation of fine particulates at the right blending times and pH fluctuations in the solution mixtures. On the other hand, the differing free OH concentrations (~2 M in CSS), H + concentrations (0.05 M HNO 3 ) for the titrants and the bulk solutions, may make it almost impossible to observe a neutral pH or a pH in the range of 7-9, where the potential for solids formation is maximized and leads to possible precipitation of minerals like aluminum hydroxides.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Quantum Search Approaches to Sampling-Based Motion Planning

In this paper, we present a novel formulation of traditional sampling-based motion planners as database-oracle structures that can be solved via quantum search algorithms. We consider two complementary scenarios: for simpler sparse environments, we formulate the Quantum Full Path Search Algorithm (q-FPS), which creates a superposition of full random path solutions, manipulates probability amplitudes with Quantum Amplitude Amplification (QAA), and quantum measures a single obstacle free full path solution. For dense unstructured environments, we formulate the Quantum Rapidly Exploring Random Tree algorithm, q-RRT, that creates quantum superpositions of possible parent-child connections, manipulates probability amplitudes with QAA, and quantum measures a single reachable state, which is added to a tree. As performance depends on the number of oracle calls and the probability of measuring good quantum states, we quantify how these errors factor into the probabilistic completeness properties of the algorithm. We then numerically estimate the expected number of database solutions to provide an approximation of the optimal number of oracle calls in the algorithm. We compare the q-RRT algorithm with a classical implementation and verify quadratic run-time speedup in the largest connected component of a 2D dense random lattice. We conclude by evaluating a proposed approach to limit the expected number of database solutions and thus limit the optimal number of oracle calls to a given number.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Measurement of Local Impedance Characteristics of In-Plane PEM Electrolyzer Component Features via Segmented Cell

Segmented cells are a class of advanced diagnostic devices that enable the measurement of current distribution within the active area of an electrochemical cell, allowing for the evaluation of localized impacts from operating conditions, flow fields and component inhomogeneities. Segmented cell devices have been applied to support R&D efforts for the advancement of polymer electrolyte membrane fuel cell technologies and more recently proton exchange membrane water electrolysis (PEMWE). Beyond current density distributions, segmented cells have been successfully deployed to collect the distribution of other relevant parameters such as high frequency resistance and electrode potentials. Very recently, a promising impedance method has been reported for water electrolysis where a one-dimensional segmented cell is coupled to a multichannel potentiostat, to enable the measurement of local cell impedances, further expanding the diagnostic capabilities of the segmented cell. In this study, we will present recent efforts to accurately measure local impedance characteristics for a PEMWE cell using a two-dimensional segmented cell device coupled with a multichannel potentiostat. The distribution of local resistances, i.e. high frequency, charge transfer, mass transport and catalyst layer, and iR-free overpotentials were successfully measured after eliminating sources of random and systematic error. We will discuss the application of this diagnostic on a cell containing a 1 cm feature simulating an ionomer skin. The results from these tests give insights if such an irregularity needs to be classified as a defect, and highlight the usefulness of coupling impedance spectroscopy with segmented cells for holistic spatial diagnostics of electrochemical devices.

08 HYDROGEN↗
DOE OSTI2021

Impact of Intake and Exhaust Ducts on the Recovery Efficiency of Heat Recovery Ventilation Systems

The heat recovery efficiency of ventilation systems utilizing heat recovery ventilators (HRVs) depends not only on the heat recovery efficiency of the HRV units themselves but also on the intake and exhaust ducts that connect the HRV units to the outside environment. However, these ducts are often neglected in heat loss calculations, as their impact on the overall heat recovery efficiency of HRV systems is often not understood and, to the knowledge of the authors, a mathematical model for the overall heat recovery efficiency of HRV systems that accounts for these ducts has not been published. In this research, a mathematical model for the overall heat recovery efficiency of HRV systems that accounts for the intake and exhaust ducts was derived and validated using real-life data. The model-predicted decrease in heat recovery efficiency due to the ducts was in reasonable agreement (relative error within 20%) with the real-life measurements. The results suggest that utilizing this model allows for more correct ventilation heat loss calculations compared to using the heat recovery efficiency of the HRV unit alone, but more field studies are needed to verify the accuracy of this model in a wide range of applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗