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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Utilizing In Situ Directional Hyperspectral Measurements to Validate Bio-Indicator Simulations for a Corn Crop Canopy

Two radiative transfer canopy models, SAIL and the two-layer Markov-Chain Canopy Reflectance Model (MCRM), were coupled with in situ leaf optical properties to simulate canopy-level spectral band ratio vegetation indices with the focus on the photochemical reflectance index in a cornfield. In situ hyperspectral measurements were made at both leaf and canopy levels. Leaf optical properties were obtained from both sunlit and shaded leaves. Canopy reflectance was acquired for eight different relative azimuth angles (psi) at three different view zenith angles (Theta (sub v)), and later used to validate model outputs. Field observations of photochemical reflectance index (PRI) for sunlit leaves exhibited lower values than shaded leaves, indicating higher light stress. Canopy PRI expressed obvious sensitivity to viewing geometry, as a function of both Theta (sub v) and psi . Overall, simulations from MCRM exhibited better agreements with in situ values than SAIL. When using only sunlit leaves as input, the MCRM-simulated PRI values showed satisfactory correlation and RMSE, as compared to in situ values. However, the performance of the MCRM model was significantly improved after defining a lower canopy layer comprised of shaded leaves beneath the upper sunlit leaf layer. Four other widely used band ratio vegetation indices were also studied and compared with the PRI results. MCRM simulations were able to generate satisfactory simulations for these other four indices when using only sunlit leaves as input; but unlike PRI, adding shaded leaves did not improve the performance of MCRM. These results support the hypothesis that the PRI is sensitive to physiological dynamics while the others detect static factors related to canopy structure. Sensitivity analysis was performed on MCRM in order to better understand the effects of structure related parameters on the PRI simulations. Leaf area index (LAI) showed the most significant impact on MCRM-simulated PRI among the parameters studied. This research shows the importance of hyperspectral and narrow band sensor studies, and especially the necessity of including the green wavelengths (e.g., 531 nm) on satellites proposing to monitor carbon dynamics of terrestrial ecosystems.

Cheng, Yen-Ben↗
NASA NTRSDate not supplied

Estimation of 3D Woven Design Sensitivities Using a Rapid Multiscale Analysis Technique

Highly-refined finite element models of three-dimension (3D) woven composite systems currently require excessive computational demands that limit their use in sensitivity analysis, uncertainty quantification, and optimization. An alternative analysis methodology was developed using the NASA Multiscale Analysis Tool (NASMAT) where multiscale models of a 3D woven composite (including inter-tow matrix voids and constituent failure) can be completed on a single central processing unit(CPU)on the order of ~30 s. To develop inputs and validation data for the NASMAT model, coupon and acid-digesting testing and x-ray computed tomography were performed. The NASMAT inputs were parameterized using a set of 25 input variables and distributions. These inputs were randomly sampled to generate a total of 100,000 NASMAT analyses that could be used to understand the influence of different material and geometric properties on the warp and weft-direction stiffness and strength. These analyses (including pre/post-processing) were performed in less than eight hours on a 120 CPU cluster. The computational efficiency of the NASMAT model enabled a sensitivity analysis to be performed, and dominant input variables were able to be identified. Key results were consistent with theoretical and experimental observations for the specific 3D woven system studied in this work.

NASMAT↗
DOE OSTI2024

A Fresh Take: Seasonal Changes in Terrestrial Freshwater Inputs Impact Salt Marsh Hydrology and Vegetation Dynamics

Abstract Salt marshes exist at the terrestrial-marine interface, providing important ecosystem services such as nutrient cycling and carbon sequestration. Tidal inputs play a dominant role in salt marsh porewater mixing, and terrestrially derived freshwater inputs are increasingly recognized as important sources of water and solutes to intertidal wetlands. However, there remains a critical gap in understanding the role of freshwater inputs on salt marsh hydrology, and how this may impact marsh subsurface salinity and plant productivity. Here, we address this knowledge gap by examining the hydrologic behavior, porewater salinity, and pickleweed ( Sarcocornia pacifica also known as Salicornia pacifica) plant productivity along a salt marsh transect in an estuary along the central coast of California. Through the installation of a suite of hydrometric sensors and routine porewater sampling and vegetation surveys, we sought to understand how seasonal changes in terrestrial freshwater inputs impact salt marsh ecohydrologic processes. We found that salt marsh porewater salinity, shallow subsurface saturation, and pickleweed productivity are closely coupled with elevated upland water level during the winter and spring, and more influenced by tidal inputs during the summer and fall. This seasonal response indicates a switch in salt marsh hydrologic connectivity with the terrestrial upland that impacts ecosystem functioning. Through elucidating the interannual impacts of drought on salt marsh hydrology, we found that the severity of drought and historical precipitation can impact contemporary hydrologic behavior and the duration and timing of the upland-marsh hydrologic connectivity. This implies that the sensitivity of salt marshes to climate change involves a complex interaction between sea level rise and freshwater inputs that vary at seasonal to interannual timescales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

A Sensitivity-informed, Process Model Abstraction Implementation in GoldSim - 19276

System-level Performance Assessment (PA) models rely on specific process-level models for some inputs, such as infiltration. For probabilistic PA, the value of the process model output depends on the values of input parameters that also vary in the PA model. The simplest conceptual solution is to draw values of the input parameters from their distributions, run the process level model at these values, and then use the output where it is needed in the PA model. However, this solution is unsatisfactory for multiple reasons: (1) the PA Model should be set up such that new runs can be made and distributions can change without having to go back and run the process-level model; (2) calling the process model from the system model is possible, but technical difficulties remain in coupling the two; and (3) there is no uncertainty in the process-level model results incorporated into the PA model. Therefore, it is desirable to develop a method that maps the values of PA Model inputs to process level model outputs, in real time within the PA Model set up and using as simple of a map as possible without losing key features of the relationship. This has been termed 'model abstraction' because information about process model runs is 'abstracted' to be used with the PA model. A simple 'nearest neighbor' abstraction approach is presented to overcome these problems, in which a sensitivity-informed distance metric is used to map a system-level model realization to the most appropriate process-level model realization. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Machine learning-assisted early ignition prediction in a complex flow

Machine learning methods are used to improve the efficiency by which turbulence-resolved simulations predict whether a hydrogen jet in air crossflow will successfully ignite. The flush-mounted jet issues perpendicularly from the wall of a low-speed wind tunnel into a turbulent boundary layer wherein a laser-induced optical breakdown (LIB) hotspot is deposited. A detailed hydrogen chemical mechanism is used to model the radicals and any subsequent chemical reactions. A dielectric-barrier discharge actuator generates body forces and hydrogen radicals near the jet orifice. Here we focus on the success or not of the ignition based on LIB location. A challenge is that definitive determination of this requires long simulations, up to 440 µs after the LIB deposition. This is particularly expensive since multiple simulations are required to find the threshold. To reduce the computational effort, three short-time (91 µs) criteria are proposed, evaluated, and compared: a constructed criterion based on detailed observations of radicals near the stoichiometric surface and two machine learning approaches, each trained on 38 realizations. The constructed criterion provides a low-cost estimate of the ignition boundary that is unambiguous in 45 of the 50 training and test trials, so only 10% of them would need to be simulated longer. The trained neural networks correctly predict outcomes in all cases evaluated, with the more automated procedure—a convolutional neural network (CNN) trained on two-dimensional images—providing the most definitive outcome prediction. From the CNN, a sensitivity analysis is used to determine which kernel features from the two-dimensional input data, as defined by intermediate-layer network weights, are important for identifying ignition.

42 ENGINEERING↗
DOE OSTI2018

Sediment Characteristics and Methane Ebullition in Three Subarctic Lakes

Ebullition (bubbling) from climate-sensitive northern lakes remains an unconstrained source of atmospheric methane (CH 4 ). Although the focus of many recent studies, ebullition is rarely linked to the physical characteristics of lakes. In this study we analyze the sediments of subarctic postglacial lakes and investigate how sediment properties relate to the large spatial variation in CH 4 bubble flux, quantified over multiple years using bubble traps. The results show that the sediments from our lakes are rich in total organic carbon, containing 37 kg/m 3 on average. This number is roughly 40% higher than the average for yedoma deposits, which have been identified as high CH 4 emitters. However, the quantity of total organic carbon is not a useful indicator of high emissions from the study lakes. Neither is the amount of CH 4 in the sediment a reliable measure of ebullition potential. Instead, our data point to coarse detritus, partly from buried submerged aquatic vegetation and redeposited peat as spatial controls on fluxes, often in combination with previously established effects of incoming solar radiation and water depth. The results once again highlight the climate sensitivity of northern lakes, indicating that biological responses to warmer waters and increased energy input and heating of organic sediments during longer ice-free seasons can substantially alter future CH 4 emissions.

58 GEOSCIENCES↗
DOE OSTI2018

Impacts of anthropogenic aerosols on fog in North China Plain

Fog poses a sever environmental problem in the North China Plain (NCP), China, which has been witnessing increases anthropogenic emission since the early 1980s. Here, this work first uses the WRF/Chem model coupled with the local anthropogenic emissions to simulate and evaluate a severe fog event occurring in NCP. Comparison of the simulations against observations shows that WRF/Chem well reproduces the general features of temporal evolution of PM 2.5 mass concentration, fog spatial distribution, visibility, and vertical profiles of temperature, water vapor content and relative humidity in the planetary boundary layer throughout the whole period of the fog event. Sensitivity studies are then performed with five different levels of anthropogenic emission as model inputs to systematically examine the comprehensive impacts of aerosols on fog microphysical, macrophysical, radiative, and dynamical properties. The results show that as aerosol concentration increases, fog droplet number concentration and liquid water content all increase nonlinearly; but effective radius decreases. Macrophysical properties (fog fraction, fog duration, fog height, and liquid water path) also increase nonlinearly with increasing aerosol concentration, with rates of changes smaller than microphysical properties. Further analysis reveals distinct aerosol effects on thermodynamic and dynamical conditions during different stages of fog evolution: increasing aerosols invigorate fog formation and development by enhancing longwave-induced instability, fog droplet condensation accompanying latent heat release, and thus turbulence, but delay fog dissipation by reducing surface solar radiation, surface sensible and latent heat fluxes, and thus suppressing turbulence during the dissipation stage.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Distribution–Based Global Sensitivity Analysis in Hydrology

Global sensitivity analysis (GSA) is routinely used in academic setting to quantify the influence of input variability and uncertainty on predictions of a quantity of interest. Practical applications of GSA are hampered by its high computational cost, which arises from the need to run large (e.g., groundwater) models multiple times, and by its reliance on the analysis of variance, which formally requires input parameters to be uncorrelated. The former difficulty can be alleviated by replacing expensive models with inexpensive (e.g., polynomial) surrogates, while adoption of distribution-based (rather than variance-based) metrics can, in principle, overcome the latter but at significantly increased computational cost. To make use of distribution-based GSA feasible for regional-scale models with a large number of degrees of freedom, we supplement it with a surrogate model built with polynomial chaos expansions with analytically updated coefficients. Here, we demonstrate the computational efficiency of our algorithm on a case study dealing with evaluation of the effects of temperature variability on annual evapotranspiration at the regional scale.

42 ENGINEERING↗
DOE OSTI2018

Uncertainty Quantification Study of CTF for the OECD/NEA LWR Uncertainty Analysis in Modeling Benchmark

This work describes the results of a quantitative uncertainty analysis of the thermal-hydraulic subchannel code for nuclear engineering applications, Coolant Boiling in Rod Arrays-Three Field (COBRA-TF). CTF is used, which is a version of COBRA-TF developed in cooperation between the Consortium for Advanced Simulation of Light Water Reactors and North Carolina State University. Four steady-state cases from Phase II Exercise 3 of the Organisation for Economic Co-operation and Development/Nuclear Energy Agency Light Water Reactor Uncertainty Analysis in Modeling (UAM) Benchmark are analyzed using the statistical analysis tool, Design Analysis Kit for Optimization and Terascale Applications (Dakota). The input parameters include boundary condition, geometry, and modeling uncertainties, which are selected using a sensitivity study and then defined based on expert judgment. Here, a forward uncertainty quantification method with Latin hypercube sampling (LHS) is used, where the sample size is based on available computational resources.

42 ENGINEERING↗
DOE OSTI2020

Effects of Photovoltaic Module Materials and Design on Module Deformation Under Load

Quasi-static structural finite-element models of an aluminum-framed crystalline silicon photovoltaic module and a glass-glass thin-film module were constructed and validated against experimental measurements of deflection under uniform pressure loading. Specific practices in the computational representation of module assembly were identified as influential to matching experimental deflection observations. Additionally, parametric analyses using Latin hypercube sampling were performed to propagate input uncertainties related to module materials, dimensions, and tolerances into uncertainties in simulated deflection. Sensitivity analyses were performed on the uncertainty quantification datasets using linear correlation coefficients and variance-based sensitivity indices to elucidate key parameters influencing module deformation. Results identified edge tape and adhesive material properties as being strongly correlated to module deflection, suggesting that optimization of these materials could yield module stiffness gains at par with the conventionally structural parameters, such as glass thickness. This exercise verifies the applicability of finite-element models for accurately predicting mechanical behavior of solar modules and demonstrates a workflow for model-based parametric uncertainty quantification and sensitivity analysis. Finally, applications of this capability include the assessment of field environment loads, derivation of representative loading conditions for reduced-scale testing, and module design optimization, among others.

42 ENGINEERING↗
DOE OSTI2020

Tapsolver: A Python Package For The Simulation And Analysis Of Tap Reactor Experiments

TAPsolver is a python package, which automates TAP simulation and analysis routines. TAPsolver is built around the python packages FEniCS and Dolfin-Adjoint, which help take advantage of model adjoints to provide automatic derivatives. TAPsolver is flexible, with reaction mechanisms and rate constants that can be set through input files that allow users to take advantage of the different functionalities, which include sensitivity analyses, parameter optimization and uncertainty quantification.

Yonge, Adam↗
DOE OSTI2018

System Advisor Model (SAM) General Description (Version 2017.9.5)

This document describes the capabilities of the System Advisor Model (SAM) developed and distributed by the U.S. Department of Energy's National Renewable Energy Laboratory. The document is for potential users and others wanting to learn about the model's capabilities. SAM is a techno-economic computer model that calculates performance and financial metrics of renewable energy projects. Project developers, policy makers, equipment manufacturers, and researchers use graphs and tables of SAM results in the process of evaluating financial, technology, and incentive options for renewable energy projects. SAM simulates the performance of photovoltaic, concentrating solar power, solar water heating, wind, geothermal, biomass, and conventional power systems. The financial models are for projects that either buy and sell electricity at retail rates (residential and commercial) or sell electricity at a price determined in a power purchase agreement (PPA). SAM's simulation tools facilitate parametric and sensitivity analyses, Monte Carlo simulation and weather variability (P50/P90) studies. SAM can also read input variables from Microsoft Excel worksheets. For software developers, the SAM software development kit (SDK) makes it possible to use SAM simulation modules in their applications written in C/C plus plus, C sharp, Java, Python, MATLAB, and other languages. NREL provides both SAM and the SDK as free downloads at https://sam.nrel.gov. SAM is an open source project, so its source code is available to the public. Researchers can study the code to understand the model algorithms, and software programmers can contribute their own models and enhancements to the project. Technical support and more information about the software are available on the website.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

HPE ultralit project (ARPA-E open program 2018) final report 15

The goal of the program was to build a fully integrated optical transceiver with >1 Tb/s and <1.5 pJ/bit operating at 50 ◦ C. Optical transceivers are critical components in high-performance-computers (HPC) and data centers, and the details of their implementation has a big impact on the total power consumption (energy efficiency) of an HPC system. Our proposed transceiver used three key enabling technologies. Firstly, SiGe avalanche photodetectors have record-low sensitivities, meaning that they can reach low bit error rates with very little light input. As a result, we can drive our lasers at a lower drive current, thus saving electrical power. Secondly, we use MOS-based capacitive tuning in our deinterleaver, modulator, and demultiplexer. Capacitive tuning allows for the tuning of photonic elements with zero static power consumption. Thirdly, we use quantum dots as the gain material in our light source. This allows us to efficiently use our light source at temperatures that are typically encountered in an HPCsystem. Our proposed optical transceiver consisted of a quantum dot comb laser as a light source, a booster SOA, MOS-based deinterleavers, MOS based ring modulators, MOS-based ring demultiplexers, and SiGe APDs.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

Phase Field Simulations of Microstructure Evolution in IN718 using a Surrogate Ni–Fe–Nb Alloy during Laser Powder Bed Fusion

The solidification microstructure in IN718 during additive manufacturing was modeled using phase field simulations. The novelty of the research includes the use of a surrogate Ni–Fe–Nb alloy that has the same equilibrium solidification range as IN718 as the model system for phase field simulations, the integration of the model alloy thermodynamics with the phase field simulations, and the use of high-performance computing tools to perform the simulations with a high enough spatial resolution for realistically capturing the dendrite morphology and the level of microsegregation seen under additive manufacturing conditions. Heat transfer and fluid flow models were used to compute the steady state temperature gradient and an average value of the solid-liquid (s-l) interface velocity that were used as input for the phase field simulations. The simulations show that the solidification morphology is sensitive to the spacing between the columnar structures. Spacing narrower than a critical value results in continued growth of a columnar microstructure, while above a critical value the columnar structure evolves into a columnar dendritic structure through the formation of secondary arms. These results are discussed in terms of the existing columnar to dendritic transition (CDT) theories. The measured interdendritic Nb concentration, the primary and secondary arm spacing is in reasonable agreement with experimental measurements performed on the nickel-base superalloy IN718.

36 MATERIALS SCIENCE↗
NASA NTRS1975

Description of CASCOMP Comprehensive Airship Sizing and Performance Computer Program, Volume 2

The computer program CASCOMP, which may be used in comparative design studies of lighter than air vehicles by rapidly providing airship size and mission performance data, was prepared and documented. The program can be used to define design requirements such as weight breakdown, required propulsive power, and physical dimensions of airships which are designed to meet specified mission requirements. The program is also useful in sensitivity studies involving both design trade-offs and performance trade-offs. The input to the program primarily consists of a series of single point values such as hull overall fineness ratio, number of engines, airship hull and empennage drag coefficients, description of the mission profile, and weights of fixed equipment, fixed useful load and payload. In order to minimize computation time, the program makes ample use of optional computation paths.

Davis, J.↗
NASA NTRS1990

Space system operations and support cost analysis using Markov chains

This paper evaluates the use of Markov chain process in probabilistic life cycle cost analysis and suggests further uses of the process as a design aid tool. A methodology is developed for estimating operations and support cost and expected life for reusable space transportation systems. Application of the methodology is demonstrated for the case of a hypothetical space transportation vehicle. A sensitivity analysis is carried out to explore the effects of uncertainty in key model inputs.

Unal, Resit↗
NASA NTRS1992

Noncontact charge measurement

A method for noncontact charge measurements is presented, which uses a system based on the reciprocal motion principle of a grounded conductor near a point charge. The system exhibits extremely good linearity with respect to the input electric field and has a resolution of greater than 10 V/m. The high sensitivity of the apparatus makes the system feasible for use at a safe distance in various applications for monitoring static charge.

Lin, Kuan-Chan↗
NASA NTRS2003

Ocean Primary Production Estimates from Terra MODIS and Their Dependency on Satellite Chlorophyll Alpha Algorithms

Simplistic models relating global satellite ocean color, temperature, and light to ocean net primary production (ONPP) are sensitive to the accuracy and limitations of the satellite estimate of chlorophyll and other input fields, as well as the primary productivity model. The standard MODIS ONPP product uses the new semi-analytic chlorophyll algorithm as its input for two ONPP indexes. The three primary MODIS chlorophyll Q estimates from MODIS, as well as the SeaWiFS 4 chlorophyll product, were used to assess global and regional performance in estimating ONPP for the full mission, but concentrating on 2001. The two standard ONPP algorithms were examined with 8-day and 39 kilometer resolution to quantify chlorophyll algorithm dependency of ONPP. Ancillary data (MLD from FNMOC, MODIS SSTD1, and PAR from the GSFC DAO) were identical. The standard MODIS ONPP estimates for annual production in 2001 was 59 and 58 GT C for the two ONPP algorithms. Differences in ONPP using alternate chlorophylls were on the order of 10% for global annual ONPP, but ranged to 100% regionally. On all scales the differences in ONPP were smaller between MODIS and SeaWiFS than between ONPP models, or among chlorophyll algorithms within MODIS. Largest regional ONPP differences were found in the Southern Ocean (SO). In the SO, application of the semi-analytic chlorophyll resulted in not only a magnitude difference in ONPP (2x), but also a temporal shift in the time of maximum production compared to empirical algorithms when summed over standard oceanic areas. The resulting increase in global ONPP (6-7 GT) is supported by better performance of the semi-analytic chlorophyll in the SO and other high chlorophyll regions. The differences are significant in terms of understanding regional differences and dynamics of ocean carbon transformations.

Essias, Wayne E.↗