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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Radiative Flux Analysis (RADFLUXANAL) Value-Added Product: Retrieval of Clear-Sky Broadband Radiative Fluxes and Other Derived Values

The Radiative Flux Analysis (RADFLUX) is a technique for using surface broadband radiation measurements for detecting periods of clear (i.e., cloudless) skies, and using the detected clear-sky data to fit functions that are then used to produce continuous clear-sky estimates. The clear-sky estimates and measurements are then used in various ways to infer cloud macrophysical properties. This value-added product (VAP) is based on methodologies developed by Dr. Charles N. Long as referenced in the papers below. It is an updated version of an earlier value-added data product called the Shortwave (SW) Clear-Sky Detection and Fitting Algorithm (SWCLRID). Two major improvements were made over the SWCLRID data product: 1) input data were first run through the Data Quality Assessment for Atmospheric Radiation Measurement (ARM) Radiation Data (QCRAD) VAP to better screen for data quality, and 2) additional processing was implemented to also include longwave (LW) clear sky estimates and derived values.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Distribution Function Instead of Steady-State Assumption in Time-Series Simulation

The quasi-steady-state assumption in time-series simulation is inadequate to model phenomena of interest to energy system integration such as inverter clipping, sell-back of excess electricity to a utility and utility hosting capacity, and battery throughput. Researchers are working on stochastic modeling, higher-resolution time series data, and machine learning approaches to address this need. This poster describes a distribution function that allows a maximum value, minimum value, and shape to the curve that can vary within each time-step based only on data inputs at the resolution of that time step (eg. Hourly). The distribution function is not used to synthesize high-resolution data, rather scalar integrals are used to calculate the quantities of interest within each time step. The form of the distribution function shows significant reduction in error when compared to 1 minute data and commercial software employing the distribution function (HOMER Pro version 14.3 and higher) shows a much improved estimate of inverter clipping in an example.

battery↗
DOE OSTI2017

Further Development of an ISOCS - based Advanced In Situ Gamma Spectrometry Services Tool for Waste Measurements - 17452

Canberra's In Situ Object Counting System is an established tool used for gamma spectrometry allowing a physical representation of complex geometries and mathematical calculation of the calibration function while avoiding the need for radioisotope standards. The ISOCS Uncertainty Estimator tool can be used to calculate defensible systematic calibration uncertainties. However the uncertainties depend on knowledge of the properties of the item being measured and for poorly characterized materials these can be large, often leading to large costs for waste sentencing. An ISOCS-based advanced in-situ gamma spectrometry services tool has been developed to reduce those uncertainties. This system is based on generating and comparing a range of candidate geometry models that yield figures of merit indicative of improved consistency between modelled data and available diverse measurement data. The approach and results of initial performance testing have previously been published, demonstrating an analysis procedure and enhanced accuracy for measurement of a low density 200 litre waste drum, based on measurements with known sources placed at different positions. It was shown how the accuracy of assay of Am-241 in a light matrix can be significantly improved. Further analysis has now been performed, with reference to measurements of a second drum, containing a standard matrix of higher density, and with a multiple radionuclide line source (Ba-133, Cs-137, Eu-152 and Am-241). These measurements represent a more challenging waste assay scenario, corresponding to potentially much larger assay uncertainties. Our results show how the assay uncertainty can be reduced, by careful application of AIGS, from relative values of the order of 100% to a few 10's of %. Furthermore, we demonstrate, through extended analysis of the test drum data, how an AIGS measurement program can be optimized to reduce the number of required measurement positions substantially. This paper describes these new results with comment on their importance and potential application for real waste assay projects. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Reduced Order Modeling conditioned on monitored features for response and error bounds estimation in engineered systems

Reduced Order Models (ROMs) form essential tools across engineering domains by virtue of their function as surrogates for computationally intensive digital twinning simulators. Although purely data-driven methods are available for ROM construction, schemes that allow to retain a portion of the physics tend to enhance the interpretability and generalization of ROMs. However, physics-based techniques can adversely scale when dealing with nonlinear systems that feature parametric dependencies. This study introduces a generative physics-based ROM that is suited for nonlinear systems with parametric dependencies and is additionally able to provide numerical error bounds associated with the respective estimates. A main contribution of this work is the conditioning of these parametric ROMs to features that can be derived from monitoring measurements, feasibly in an online fashion. This is contrary to most existing ROM schemes, which remain restricted to the prescription of the physics-based, and usually a priori unknown, system parameters. Our work utilizes conditional Variational Autoencoders to continuously map the required reduction bases to a feature vector extracted from limited output measurements, while additionally allowing for a probabilistic assessment of the ROM-estimated Quantities of Interest. An auxiliary task using a neural network-based parametrization of suitable probability distributions is introduced to re-establish the link with physical model parameters. We verify the proposed scheme on a series of simulated case studies incorporating effects of geometric and material nonlinearity under parametric dependencies related to system properties and input load characteristics.

Conditional VAEs↗
DOE OSTI2022

Transit Time Estimation in Catchments: Recent Developments and Future Directions

Abstract Water transit time is now a standard measure in catchment hydrological and ecohydrological research. The last comprehensive review of transit time modeling approaches was published 15+ years ago. But since then the field has largely expanded with new data, theory and applications. Here, we review these new developments with focus on water‐age‐balance approaches and data‐based approaches. We discuss and compare methods including StorAge‐Selection functions, well/partially mixed compartments, water age tracking through spatially distributed models, direct transit time estimates from controlled experiments, young water fractions, and ensemble hydrograph separation. We unify some of the heterogeneity in the literature that has crept in with these many new approaches, in an attempt to clarify the key differences and similarities among them. Finally, we point to open questions in transit time research, including what we still need from theory, models, field work, and community practice.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Angular systematics-free cosmological analysis of galaxy clustering in configuration space

ABSTRACT Galaxy redshift surveys are subject to incompleteness and inhomogeneous sampling due to the various constraints inherent to spectroscopic observations. This can introduce systematic errors on the summary statistics of interest, which need to be mitigated in cosmological analysis to achieve high accuracy. Standard practices involve applying weighting schemes based on completeness estimates across the survey footprint, possibly supplemented with additional weighting schemes accounting for density-dependent effects. In this work, we concentrate on pure angular systematics and describe an alternative approach consisting in analysing the galaxy two-point correlation function where angular modes are nulled. By construction, this procedure removes all possible known and unknown sources of angular observational systematics, but also part of the cosmological signal. We use a modified Landy–Szalay estimator for the two-point correlation function that relies on an additional random catalogue where angular positions are randomly drawn from the galaxy catalogue, and provide an analytical model to describe this modified statistic. We test the model by performing an analysis of the full anisotropic clustering in mock catalogues of luminous red and emission-line galaxies at 0.43 < z < 1.1. We find that the model fully accounts for the modified correlation function in redshift space, without introducing new nuisance parameters. The derived cosmological parameters from the analysis of baryon acoustic oscillations and redshift-space distortions display slightly larger statistical uncertainties, mostly for the growth rate of structure parameter fσ8 that exhibits a $50{{\ \rm per\ cent}}$ statistical error increase, but free from angular systematic error.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

LTAU-FF: Loss Trajectory Analysis for Uncertainty in atomistic Force Fields

LTAU (Loss Trajectory Analysis for Uncertainty) is a technique for estimating the uncertainty in a model's predictions for any regression task by approximating the cumulative distribution function (CDF) of the model's errors over the course of training. The approximated CDF, combined with a similarity search algorithm in the model's descriptor space, can then be used to estimate the likelihood that the model's predictions on any given test point will fall below a chosen threshold. LTAU-FF (LTAU in atomistic Force Fields) is the application of LTAU specifically for use with atomistic force fields.

Vita, JoshuaA↗
DOE OSTI2025

Bayesian Inference for the Seismic Moment Tensor Using Regional Waveforms and Teleseismic- P Polarities with a Data-Derived Distribution of Velocity Models and Source Locations

The largest source of uncertainty in any source inversion is the velocity model used in the transfer function that relates observed ground motion to the seismic moment tensor. However, standard inverse procedure often does not quantify uncertainty in the seismic moment tensor due to error in the Green’s functions from uncertain event location and Earth structure. Here, we incorporate this uncertainty into an estimation of the seismic moment tensor using a data-derived distribution of velocity models based on complementary geophysical data sets, including thickness constraints, velocity profiles, gravity data, surface-wave group velocities, and regional body-wave travel times. The data-derived distribution of velocity models is then used as a prior distribution of Green’s functions for use in Bayesian inference of an unknown seismic moment tensor using regional and teleseismic-P waveforms. The use of multiple data sets is important for gaining resolution to different components of the moment tensor. The combined likelihood is estimated using data-specific error models and the posterior of the seismic moment tensor is estimated and interpreted in terms of the most probable source type.

58 GEOSCIENCES↗
DOE OSTI2016

STATISTICALLY DETERMINED DISPERSION RELATIONS OF MAGNETIC FIELD FLUCTUATIONS IN THE TERRESTRIAL FORESHOCK

We obtain dispersion relations of magnetic field fluctuations for two crossings of the terrestrial foreshock by Cluster spacecraft. These crossings cover plasma conditions that differ significantly in their plasma β and in the density of the reflected ion beam, but not in the properties of the encountered ion population, both showing shell-like distribution function. Dispersion relations are reconstructed using two-point instantaneous wave number estimations from pairs of Cluster spacecraft. The accessible range of wave vectors, limited by the available spacecraft separations, extends to ≈2 × 10{sup 4} km. Results show multiple branches of dispersion relations, associated with different powers of magnetic field fluctuations. We find that sunward propagating fast magnetosonic waves and beam resonant modes are dominant for the high plasma β interval with a dense beam, while the dispersions of the interval with low beam density include Alfvén and fast magnetosonic modes propagating sunward and anti-sunward.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Mechanism of astatine and bismuth sorption on extraction chromatography resins from nitric acid media

Systematic study of astatine (At) sorption on extraction chromatography resins from nitric acid media has been performed at Texas A&M University. This work covers commercially available resins such as LN, TK400, SR, TRU, and UTEVA. Acquiring an understanding of At behavior in up to 4 M HNO 3 solutions is a key step to develop a rapid and reliable system for At separation and purification. The determined distribution coefficients are greater than 20 for all the resins studied, reaching 400 for TRU and UTEVA resins. The sorption uptake decreases in the order: TRU ≳ UTEVA >TK400 ≳ SR >LN. For each resin a thermodynamic model has been developed to suggest a possible mechanism of At sorption and corresponding sorption constants have been estimated. Literature data along with new results on bismuth (Bi) sorption by studied resins in nitric acid media have been reviewed and a mathematical model to describe its behavior has been suggested. A ratio of corresponding fit functions of At and Bi assigned to the same resin and acidity has been used to estimate separation factors of these elements. Furthermore, only the TRU resin is not suitable for efficient At isolation from Bi, while the other four resins demonstrate promising results.

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

Fault diagnosis and fault tolerant control for T-S fuzzy stochastic distribution systems subject to sensor and actuator faults

The problem of fault diagnosis (FD) and fault tolerant control (FTC) for a class of Takagi-Sugeno (T-S) fuzzy stochastic distribution control (SDC) systems subject to sensor and actuator faults is discussed in this paper. First, fuzzy logic models are used to approximate the output probability density function (PDF). Next, an adaptive augmented state/fault diagnosis observer is proposed to estimate the system state, sensor and the actuator faults simultaneously. New expected weights based on the sensor fault estimation information and a PI-type fuzzy feedback fault tolerant (FT) controller are designed to compensate the effect of sensor fault and actuator fault simultaneously. When the sensor fault occurs, the expected objective is redesigned to compensate the sensor fault. Meanwhile, the PI controller can compensate the effect of actuator fault, and the output PDF of the system can still track the desired PDF after the fault occurs. Finally, an example of quality distribution control in chemical reaction process is given to confirm the effectiveness of the algorithm.

42 ENGINEERING↗
DOE OSTI2016

The past, present and future of microbiome analyses

Microbes evolved on Earth approximately 3.5 billion years ago and eventually occupied every habitable environment in its biosphere. While microorganisms are responsible for key functions on Earth including carbon and nutrient cycling and determining the health and disease of its inhabitants (i.e. plants and animals), >99% of the estimated trillions of microbes have yet to be discovered.1 In addition, high microbial diversity has made it difficult to study specific functions carried out by complex microbial communities within "microbiomes", such as those inhabiting the soil and human gut.2,3 Fortunately, technological advances over the last few decades have greatly facilitated studies of complex microbiomes and their functions. Here we will specifically discuss advances related to nucleic acid sequencing and mass spectrometry analyses that have enabled exploration and understanding of complex microbiomes in a range of environments and our own bodies.4,5,6,7

Next Generation sequencing and Mass Spec↗
DOE OSTI2018

Model selection and parameter estimation in tumor growth models using approximate Bayesian computation-ABC

Cancer is one of the most fatal diseases in the world. Governments and researchers from various areas have continuously concentrated efforts to better understand the disease and propose diagnostic and treatment techniques. The use of mathematical models of tumor growth is of great importance for the development of such techniques. Due to the variety of models nowadays available in the literature, the problems of model selection and parameter estimation come into picture, aiming at suitably predicting the patient’s status of the disease. As the available data on dependent variables of existing models might not justify the use of common likelihood functions, approximate Bayesian computation (ABC) becomes a very attractive tool for model selection and model calibration (parameter estimation) in tumor growth models. In the present study, a Monte Carlo approximate Bayesian computation (ABC) algorithm is applied to select among competing models of tumor growth, with and without chemotherapy treatment. Simulated measurements are used in this work. The results obtained show that the algorithm correctly selects the model and estimates the parameters used to generate the simulated measurements.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Fluid temperature predictions of geothermal borefields using load estimations via state observers

Fluid temperature predictions of geothermal borefields usually involves temporal superposition of its characteristic g-function, using load aggregation schemes to reduce computational times. Assuming that the ground has linear properties, it can be modeled as a linear state space system where the states are the aggregated loads. However, the application and accuracy of these models is compromised when the borefield is already operating and its load history is not registered or there are gaps in the data. This paper assesses the performance of state observers to estimate the borefield load history and obtain accurate fluid predictions. Results show that both Time-Varying Kalman Filter (TVKF) and Moving Horizon Estimator (MHE) provide predictions with average and maximum errors below 0.1 $^\circ C$ and 1 $^\circ C$ respectively. MHE outperforms TVKF in terms of n-step ahead output predictions and load history profile at the expenses of about 5 times more computational time.

Figueroa, Iago C.↗
DOE OSTI2017

Nucleotide Dependence of Subunit Rearrangements in Short-Form Rubisco Activase from Spinach

Higher-plant Rubisco activase (Rca) plays a critical role in regulating the activity of ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco). In vitro, Rca is known to undergo dynamic assembly–disassembly processes, with several oligomer stoichiometries coexisting over a broad concentration range. Although the hexamer appears to be the active form, changes in quaternary structure could play a role in Rubisco regulation. Therefore, in this work, fluorescent labels were attached to the C-termini of spinach β-Rca, and the rate of subunit mixing was monitored by measuring energy transfer as a function of nucleotide and divalent cation. Only dimeric units appeared to exchange. Poorly hydrolyzable substrate analogues provided locked complexes with high thermal stabilities (apparent T m = 60 °C) and an estimated t 1/2 of at least 7 h, whereas ATP-Mg provided tight assemblies with t 1/2 values of 30–40 min and ADP-Mg loose assemblies with t 1/2 values of <15 min. Accumulation of ADP to 20% of the total level of adenine nucleotide substantially accelerated equilibration. An initial lag period was observed with ATP·Mg, indicating inhibition of subunit exchange at low ADP concentrations. The ADP K i value was estimated to exceed the K m for ATP (0.772 ± 96 mM), suggesting that the equilibration rate is a function of the relative contributions of high- and low-affinity states. C-Terminal cross-linking generated covalent dimers, required the N-terminal extension to the AAA+ domain, and provided evidence of different classes of sites. We propose that oligomer reorganization may be stalled during periods of high Rubisco reactivation activity, whereas changes in quaternary structure are stimulated by the accumulation of ADP at low light levels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

SU-E-T-752: Three-Dimensional Carcinogenic Maps Induced by Photons and Protons

Purpose: Evaluate the excess relative risk (ERR) induced by photons and protons in each voxel of the lung, and display it as a three-dimensional map, known as the ERRM (i.e. excess relative risk map) along with the dose distribution map. In addition, we also study the effect of variations in the linear energy transfer (LET) distribution on ERRM for a given proton plan. Methods: The excess relative risk due to radiation is estimated using the initiation-inactivation-proliferation formalism. This framework accounts for three biological phenomenon: mutation induction, cell kill and proliferation. Cell kill and mutation induction are taken as a function of LET using experimental data. LET distributions are calculated using a Monte Carlo algorithm. ERR is then estimated for each voxel in the organ, and displayed as a three dimensional carcinogenic map. Results: The differences in the ERR’s between photons and protons is seen from the three-dimensional ERR map. In addition, we also varied the LET of a proton plan and observed the differences in the corresponding ERR maps demonstrating variations in the ERR maps depend on features of a proton plan. Additionally, our results suggest that any two proton plans that have the same integral dose does not necessarily imply identical ERR maps, and these changes are due to the variations in the LET distribution map. Conclusion: Clinically, it is important to have a three dimensional display of biological end points. This study is an effort to introduce 3D ERR maps into the treatment planning workflow for certain sites such as pediatric head and neck tumors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

A microbial functional group-based module for simulating methane production and consumption: Application to an incubated permafrost soil

In this study, accurately estimating methane (CH 4 ) flux is critically important for investigating and predicting the biogeochemistry-climate feedback. Better simulating CH 4 flux requires explicit representations of microbial processes on CH 4 dynamics because all processes for CH 4 production and consumption are actually carried out by microbes. A microbial functional group based module was developed and tested against an incubation experiment. The module considers four key mechanisms for CH 4 production and consumption: methanogenesis from acetate or single-carbon compounds and CH 4 oxidation using molecular oxygen or other inorganic electron acceptors. These four processes were carried out by four microbial functional groups: acetoclastic methanogens, hydrogenotrophic methanogens, aerobic methanotrophs, and anaerobic methanotrophs. This module was then linked with the decomposition subroutine of the Community Land Model , and was further used to simulate dynamics of carbon dioxide (CO 2 ) and CH 4 concentrations from an incubation experiment with permafrost soils. The results show that the model could capture the dynamics of CO 2 and CH 4 concentrations in microcosms with top soils, mineral layer soils and permafrost soils under natural and saturated moisture conditions and a temperature gradient of -2°C, 3°C, and 5°C. Sensitivity analysis confirmed the importance of acetic acid's direct contribution as substrate and indirect effects through pH feedback on CO 2 and CH 4 production and consumption. This study suggests that representing the microbial mechanisms is critical for modeling CH 4 production and consumption; it is urgent to incorporate microbial mechanisms into Earth system models for better predicting the behavior of the climate system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Atomic and Molecular Adsorption on Cu(111)

Here, due to the wide use of copper-based catalysts in industrial chemical processes, fundamental understanding of the interactions between copper surfaces and various reaction intermediates is highly desired. Here, we performed periodic, self-consistent density functional theory (DFT-GGA) calculations to study the adsorption of five atomic species (H, C, N, O, and S), seven molecular species (NH 3 , CH 4 , N 2 , CO, HCN, NO, and HCOOH), and 13 molecular fragments (CH, CH 2 , CH 3 , NH, NH 2 , OH, CN, COH, HCO, COOH, HCOO, NOH, and HNO) on the Cu(111) surface at a coverage of 0.25 monolayer. The preferred binding site, binding energy, and the corresponding surface deformation energy of each species were determined, as well as the estimated diffusion barrier and diffusion pathway. The binding strengths calculated using the PW91 functional decreased in the following order: CH > C > O > S > CN > NH > N > CH 2 > OH > HCOO > COH > H > NH 2 > NOH > COOH > HNO > HCO > CH 3 > NO > CO > NH 3 > HCOOH. No stable binding structures were observed for N 2 , HCN, and CH 4 . The adsorbate–surface and intramolecular vibrational modes of all the adsorbates at their preferred binding sites were deternined. Using the calculated adsorption energetics, potential energy surfaces were constructed for the direct decomposition of CO, CO 2 , NO, N 2 , NH 3 , and CH 4 and the hydrogen-assisted decomposition of CO, CO 2 , and NO.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗