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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

CondiDiag1.0: a flexible online diagnostic tool for conditional sampling and budget analysis in the E3SM atmosphere model (EAM)

Abstract. Numerical models used in weather and climate prediction take into account a comprehensive set of atmospheric processes (i.e., phenomena) such as the resolved and unresolved fluid dynamics, radiative transfer, cloud and aerosol life cycles, and mass or energy exchanges with the Earth's surface. In order to identify model deficiencies and improve predictive skills, it is important to obtain process-level understanding of the interactions between different processes. Conditional sampling and budget analysis are powerful tools for process-oriented model evaluation, but they often require tedious ad hoc coding and large amounts of instantaneous model output, resulting in inefficient use of human and computing resources. This paper presents an online diagnostic tool that addresses this challenge by monitoring model variables in a generic manner as they evolve within the time integration cycle. The tool is convenient to use. It allows users to select sampling conditions and specify monitored variables at run time. Both the evolving values of the model variables and their increments caused by different atmospheric processes can be monitored and archived. Online calculation of vertical integrals is also supported. Multiple sampling conditions can be monitored in a single simulation in combination with unconditional sampling. The paper explains in detail the design and implementation of the tool in the Energy Exascale Earth System Model (E3SM) version 1. The usage is demonstrated through three examples: a global budget analysis of dust aerosol mass concentration, a composite analysis of sea salt emission and its dependency on surface wind speed, and a conditionally sampled relative humidity budget. The tool is expected to be easily portable to closely related atmospheric models that use the same or similar data structures and time integration methods.

58 GEOSCIENCES↗
NASA NTRS1974

On conditional sampling for turbulent flow studies

The conditional sampling technique is analyzed as a weighted time average for turbulent flow. The various conditional averages are obtained by using different types of weighting functions. A second averaging relation is obtained between the conventional averages and the conditional averages. A few examples are given in which simplified expressions are used.

Wang, F. C.↗
DOE OSTI2020

A Particle-Based Conditional Sampling Scheme for the Simulation of Transport in Fractured Rock With Diffusion Into Stagnant Water and Rock Matrix

In situ experiments and field-scale characterization studies have pointed out that, in fractured crystalline media, groundwater flow is highly channelized. This implies that, at the scale of a single fracture, only part of the fracture surface area is in contact with flowing water, while the rest of in-plane water is essentially stagnant and can be accessed by solutes via molecular diffusion. Despite their importance for contaminant retention, to date, there are no numerical or analytical approaches that could be used to assess the implication of stagnant water zones on solute transport in realistic large-scale Discrete Fracture Network-based models. In this study, we present an efficient and flexible algorithm for the simulation of transport in fractured rock with diffusion into stagnant water and rock matrix. The algorithm is a generalization of a previously developed numerical framework for time domain particle tracking in sparsely fractured rock. The key of the generalization is that total time in fracture (τ f ) is first evaluated using a Monte Carlo sampling and then a second sampling is performed conditioned on τ f . The algorithm has been successfully validated against existing independent solutions and the implication of diffusion into stagnant water and secondary diffusion into the matrix has been assessed for a realistic modeling scenario. The results show that, due to diffusion into stagnant water, contaminants are more strongly retarded. This increased retention is more significant for sorbing species, as a larger number of sorption sites is accessible. A high sensitivity to the flowing channel/stagnant water zone geometry has also been observed.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1986

Influence of large-scale motion on turbulent transport for confined coaxial jets. Volume 1: Analytical analysis of the experimental data using conditional sampling

The existence of large scale coherent structures in turbulent shear flows has been well documented. Discrepancies between experimental and computational data suggest a necessity to understand the roles they play in mass and momentum transport. Using conditional sampling and averaging on coincident two component velocity and concentration velocity experimental data for swirling and nonswirling coaxial jets, triggers for identifying the structures were examined. Concentration fluctuation was found to be an adequate trigger or indicator for the concentration-velocity data, but no suitable detector was located for the two component velocity data. The large scale structures are found in the region where the largest discrepancies exist between model and experiment. The traditional gradient transport model does not fit in this region as a result of these structures. The large scale motion was found to be responsible for a large percentage downstream at approximately the mean velocity of the overall flow in the axial direction. The radial mean velocity of the structures was found to be substantially greater than that of the overall flow.

Brondum, D. C.↗
NASA NTRS2008

Approximation of Failure Probability Using Conditional Sampling

In analyzing systems which depend on uncertain parameters, one technique is to partition the uncertain parameter domain into a failure set and its complement, and judge the quality of the system by estimating the probability of failure. If this is done by a sampling technique such as Monte Carlo and the probability of failure is small, accurate approximation can require so many sample points that the computational expense is prohibitive. Previous work of the authors has shown how to bound the failure event by sets of such simple geometry that their probabilities can be calculated analytically. In this paper, it is shown how to make use of these failure bounding sets and conditional sampling within them to substantially reduce the computational burden of approximating failure probability. It is also shown how the use of these sampling techniques improves the confidence intervals for the failure probability estimate for a given number of sample points and how they reduce the number of sample point analyses needed to achieve a given level of confidence.

Giesy. Daniel P.↗
DOE OSTI2018

Sampling Conditions for Conforming Voronoi Meshing by the VoroCrust Algorithm

We study the problem of decomposing a volume with a smooth boundary into a collection of Voronoi cells. Unlike the dual problem of conforming Delaunay meshing, a principled solution to this problem for generic smooth surfaces remained elusive. VoroCrust leverages ideas from weighted α-shapes and the power crust algorithm to produce unweighted Voronoi cells conforming to the surface, yielding the first provably-correct algorithm for this problem. Given a κ-sparse ε-sample, we work with the balls of radius δ times the local feature size centered at each sample. The corners of the union of these balls on both sides of the surface are the Voronoi sites and the interface of their cells is a watertight surface reconstruction embedded in the dual shape of the union of balls. With the surface protected, the enclosed volume can be further decomposed by generating more sites inside it. Compared to clipping-based algorithms, VoroCrust cells are full Voronoi cells, with convexity and fatness guarantees. Compared to the power crust algorithm, VoroCrust cells are not filtered, are unweighted, and offer greater flexibility in meshing the enclosed volume by either structured or randomly genenerated samples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Turbulence kinetic energy budget and conditional sampling of momentum, scalar, and intermittency fluxes in thermally stratified wind farms

A description of the turbulence kinetic energy budget is investigated to understand the dynamics and turbulence energy transfer between the atmospheric boundary layer and large wind farms. The turbulence kinetic energy budget terms are a dominant factor in explaining the energy supply process in wind farms. Large eddy simulations are used to generate the thermally stratified wind turbine array boundary layer, where stable and unstable conditions are considered. The wakes represent a sink of mean kinetic energy, and turbulence transport redistributes energy in the wake region. The energy balance between the budget terms is dependent on the physical location in the wind farm. During the unstable scenario, turbulence is driven by the production, transport, and buoyancy terms. Further, the contribution of the turbulence kinetic energy budget terms is reduced with increasing atmospheric stability, especially above the shear layer, where the mechanical production is the dominant term. Pressure diffusion redistributes the turbulent energy from the streamwise direction into the other components of the normal Reynolds stresses. This distinctive feature of the changing thermal stratification is presented through the quadrant analysis. The momentum ejection and sweep frequencies are both comparable and dominant. The scalar flux shows an increase in the contribution of the negative correlation in the quadrants. The quadrant analysis is extended to account for intermittency based on the pointwise Holder exponents. As a result, positive correlations are dominant in the wake and in higher layers of the domain for both considered cases.

17 WIND ENERGY↗
NASA NTRS1977

Conditional sampling analysis for turbulent flows

Previous techniques used for design of subsonic wind tunnels have been improved and combined in computer program. Program is applicable to compressible flow through, most closed-, or open throated, single-, double-, or non-return wind tunnels or ducts. Program is selfchecking and selfprotecting, thus minimizing undetected and wasteful user errors.

Wang, F. C.↗
NASA NTRS1980

Conditional sampling technique to test the applicability of the Taylor hypothesis for the large-scale coherent structures

Comparisons of the distributions of large scale structures in turbulent flow with distributions based on time dependent signals from stationary probes and the Taylor hypothesis are presented. The study investigated an area in the near field of a 7.62 cm circular air jet at a Re of 32,000, specifically having coherent structures through small-amplitude controlled excitation and stable vortex pairing in the jet column mode. Hot-wire and X-wire anemometry were employed to establish phase averaged spatial distributions of longitudinal and lateral velocities, coherent Reynolds stress and vorticity, background turbulent intensities, streamlines and pseudo-stream functions. The Taylor hypothesis was used to calculate spatial distributions of the phase-averaged properties, with results indicating that the usage of the local time-average velocity or streamwise velocity produces large distortions.

Hussain, A. K. M. F.↗
NASA NTRS1989

Bivariate conditional sampling of buoyancy flux during an intense cold-air outbreak

The joint frequency distribution technique was used to analyze buoyancy fluxes in the marine atmospheric boundary layer (MABL) for the cloud street regime noted during the Genesis of Atlantic Lows Experiment. It is found that for the lower half of the MABL, the buoyancy flux is mainly generated by the rising thermals and the sinking compensating ambient air, and is mainly consumed by the entrainment and detrainment of thermals, penetrative convection, and the entrainment from the MABL top. If the buoyancy flux is primarily driven by the temperature flux, these buoyancy-flux generating processes should be the same for the lower boundary layers over land and ocean. The results of the scale analysis of the buoyancy flux agree well with those obtained for mesoscale cellular convection during the Air-Mass Transformation Experiment.

Chou, Shu-Hsien↗
DOE OSTI2015

Fast temperature spectrometer for samples under extreme conditions

We have developed a multi-wavelength Fast Temperature Readout (FasTeR) spectrometer to capture a sample’s transient temperature fluctuations, and reduce uncertainties in melting temperature determination. Without sacrificing accuracy, FasTeR features a fast readout rate (about 100 Hz), high sensitivity, large dynamic range, and a well-constrained focus. Complimenting a charge-coupled device spectrometer, FasTeR consists of an array of photomultiplier tubes and optical dichroic filters. The temperatures determined by FasTeR outside of the vicinity of melting are, generally, in good agreement with results from the charge-coupled device spectrometer. Near melting, FasTeR is capable of capturing transient temperature fluctuations, at least on the order of 300 K/s. A software tool, SIMFaster, is described and has been developed to simulate FasTeR and assess design configurations. FasTeR is especially suitable for temperature determinations that utilize ultra-fast techniques under extreme conditions. Working in parallel with the laser-heated diamond-anvil cell, synchrotron Mössbauer spectroscopy, and X-ray diffraction, we have applied the FasTeR spectrometer to measure the melting temperature of {sup 57}Fe{sub 0.9}Ni{sub 0.1} at high pressure.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Hydrophysical Evaluation of Wells TW-B, TW-7, UE-6d, U-2gg PSE 3A, U-10L 1, and UE-6e in Yucca Flat

This study evaluated six wells in Yucca Flat in support of the Underground Test Area (UGTA) Activity conducted by the U.S. Department of Energy (DOE) at the Nevada National Security Site (NNSS). Accessibility and groundwater sampling conditions were assessed and if conditions permitted, samples were collected for tritium analysis. Four of the wells, TW-B, UE-6d, UE-6e, and TW-7 were sampled in support of UGTA responses to recommendations made by the Yucca Flat/Climax Mine External Peer Review Committee (Navarro, 2016). In addition to its role in support of these responses, TW-7 was included because it is listed in the NNSS Integrated Groundwater Sampling Plan (DOE, 2014) as a required sampling location, although it had not been sampled since 1994. U-2gg PSE 3A and U-10L 1 were evaluated to determine whether deteriorating well conditions can be addressed so that these wells can be used as additional sampling points in Yucca Flat.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Efficient Neural Network Approaches for Conditional Optimal Transport with Applications in Bayesian Inference

In this work, we present two neural network approaches that approximate the solutions of static and dynamic conditional optimal transport (COT) problems. Both approaches enable conditional sampling and conditional density estimation, which are core tasks in Bayesian inference—particularly in the simulation-based (“likelihood-free”) setting. Our methods represent the target conditional distribution as a transformation of a tractable reference distribution. Obtaining such a transformation, chosen here to be an approximation of the COT map, is computationally challenging even in moderate dimensions. To improve scalability, our numerical algorithms use neural networks to parameterize candidate maps and further exploit the structure of the COT problem. Our static approach approximates the map as the gradient of a partially input convex neural network. It uses a novel numerical implementation to increase computational efficiency compared to state-of-the-art alternatives. Our dynamic approach approximates the conditional optimal transport via the flow map of a regularized neural ODE; compared to the static approach, it is slower to train but offers more modeling choices and can lead to faster sampling. We demonstrate both algorithms numerically, comparing them with competing state-of-the-art approaches, using benchmark datasets and simulation-based Bayesian inverse problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Tests of a High Temperature Sample Conditioner for the Waste Treatment Plant LV-S2, LV-S3, HV-S3A and HV-S3B Exhaust Systems

Tests were performed to evaluate a sample conditioning unit for stack monitoring at Hanford Tank Waste Treatment and Immobilization Plant (WTP) exhaust stacks with elevated air temperatures. The LV-S2, LV-S3, HV-S3A and HV-S3B exhaust stacks are expected to have elevated air temperature and dew point. At these emission points, exhaust temperatures are too high to deliver the air sample directly to the required stack monitoring equipment. As a result, a sample conditioning system is considered to cool and dry the air prior to its delivery to the stack monitoring system. The method proposed for the sample conditioning is a dilution system that will introduce cooler, dry air to the air sample stream. This method of sample conditioning is meant to reduce the sample temperature while avoiding condensation of moisture in the sample stream. An additional constraint is that the ANSI/HPS N13.1-1999 standard states that at least 50% of the 10 μm aerodynamic diameter (AD) particles present in the stack free stream must be delivered to the sample collector. In other words, depositional loss of particles should be limited to 50% in the sampling, transport, and conditioning systems. Based on estimates of particle penetration through the LV-S3 sampling system, the diluter should perform with about 80% penetration or better to ensure that the total sampling system passes the 50% or greater penetration criterion.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗