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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 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Modeling thin layers of analytes on substrates for spectral analysis: use of solid/liquid n and k values to model reflectance spectra

Since solids are only sometimes seen en masse in a pure bulk form, and for liquids other than water almost never, a capability to model reflectance spectra from analytes deposited on various substrates would be highly advantageous. If available, the real, n ( ν ) , and imaginary, k ( ν ) , components of the complex refractive index, n n + i k , can be used to simulate infrared spectra, accounting for reflection, refraction, and absorption phenomena as a function of wavelength. We focus on using the Pacific Northwest National Laboratory (PNNL) derived n / k vectors for solid and liquid analytes deposited as thin layers on different types of substrates including conductors, such as aluminum, and inorganic dielectrics, such as glass. The model is an adaptation of the Monte Carlo ray trace modeling program, TracePro, extended through the use of its macrolanguage. The model is tested using thin films of organic liquids including silicone oil and no. 2 diesel fuel, as well as organic solids such as caffeine and acetaminophen on aluminum and glass. The predicted spectra for the solid films were compared to experimental hemispherical reflectance data measured using a Fourier transform spectrometer with an integrating sphere. The thickness of the calculated layer is a parameter for predicting the (transflectance) spectra and is obtained using the areal density measured from gravimetric methods to generate the thin-layer samples. Comparison of the calculated spectra with experimental hemispherical reflectance data shows excellent agreement, indicating promise for the use of measured n / k data to synthesize reference spectral data. In particular, accounting for the inhomogeneity of the deposits greatly improved the match with experimental data. Finally, the theoretical modeling shows that for thicker layers (ca. 20 to 100 μm) of typical organics possessing moderately strong k values, the longwave infrared features are often saturated and better spectral contrast is obtained from the overtone/combination bands in the shortwave infrared.

42 ENGINEERING↗
DOE OSTI2017

Quantum groups as generalized gauge symmetries in WZNW models. Part II. The quantized model

This is the second part of a paper dealing with the “internal” (gauge) symmetry of the Wess-Zumino-Novikov-Witten (WZNW) model on a compact Lie group G. It contains a systematic exposition, for G = SU(n), of the canonical quantization based on the study of the classical model (performed in the first part) following the quantum group symmetric approach first advocated by L.D. Faddeev and collaborators. The internal symmetry of the quantized model is carried by the chiral WZNW zero modes satisfying quadratic exchange relations and an n-linear determinant condition. For generic values of the deformation parameter the Fock representation of the zero modes’ algebra gives rise to a model space of U{sub q}(sl(n)). The relevant root of unity case is studied in detail for n = 2 when a “restricted” (finite dimensional) quotient quantum group is shown to appear in a natural way. The module structure of the zero modes’ Fock space provides a specific duality with the solutions of the Knizhnik-Zamolodchikov equation for the four point functions of primary fields suggesting the existence of an extended state space of logarithmic CFT type. Combining left and right zero modes (i.e., returning to the 2D model), the rational CFT structure shows up in a setting reminiscent to covariant quantization of gauge theories in which the restricted quantum group plays the role of a generalized gauge symmetry.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Comparative analysis of model-free and model-based HVAC control for residential demand response

In this paper, we present a comparative analysis of model-free reinforcement learning (RL) and model predictive control (MPC) approaches for intelligent control of heating, ventilation, and air-conditioning (HVAC). Deep-Q-network (DQN) is used as a candidate for model-free RL algorithm. The two control strategies were developed for residential demand-response (DR) HVAC system. We considered MPC as our golden standard to compare DQN's performance. The question we tried to answer through this work was, What % of MPC's performance can be achieved by model-free RL approach for intelligent HVAC control?. Based on our test result, RL achieved an average of ≈ 62% daily cost saving of MPC. Considering the pure optimization and model-based nature of MPC methods, the RL showed very promising performance. We believe that the interpretations derived from this comparative analysis provide useful insights to choose from various DR approaches and further enhance the performance of the RL-based methods for building energy managements.

Kurte, Kuldeep↗
DOE OSTI2020

Modeling Plant Metabolism: From Network Reconstruction to Mechanistic Models

Mathematical modeling of plant metabolism allows the plant science community to understand the organization of plant metabolism, obtain quantitative insights into metabolic functions, and derive engineering strategies for manipulation of metabolism. Among the various modeling approaches, metabolic pathway analysis can dissect the basic functional modes of subsections of core metabolism, such as photorespiration, and reveal how classical definitions of metabolic pathways have overlapping functionality. In current research using constraint-based modeling in plants, numerous computational tools are currently available to analyze large-scale and genome-scale metabolic networks. For 13 C-metabolic flux analysis, principles of isotopic steady state have been used to study heterotrophic plant tissues, while nonstationary isotope labeling approaches are amenable to the study of photoautotrophic and secondary metabolism. Enzyme kinetic models explore pathways in mechanistic detail, and we discuss different approaches to determine or estimate kinetic parameters. In this review, we describe recent advances and challenges in modeling plant metabolism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Efficient Band-to-Trap Tunneling Model Including Heterojunction Band Offset

In this paper, we present an efficient band-to-trap tunneling model based on the Schenk approach, in which an analytic density-of-states (DOS) model is developed based on the open boundary scattering method. The new model explicitly includes the effect of heterojunction band offset, in addition to the well-known field effect. Its analytic form enables straightforward implementation into TCAD device simulators. It is applicable to all one-dimensional potentials, which can be approximated to a good degree such that the approximated potentials lead to piecewise analytic wave functions with open boundary conditions. The model allows for simulating both the electric-field-enhanced and band-offset-enhanced carrier recombination due to the band-to-trap tunneling near the heterojunction in a heterojunction bipolar transistor (HBT). Simulation results of an InGaP/GaAs/GaAs NPN HBT show that the proposed model predicts significantly increased base currents, due to the hole-to-trap tunneling enhanced by the emitter-base junction band offset. Finally, the results compare favorably with experimental observation.

42 ENGINEERING↗
DOE OSTI2016

Impacts of Model Bias on the Climate Change Signal and Effects of Weighted Ensembles of Regional Climate Model Simulations: A Case Study over Southern Québec, Canada

This study examined the impact of model biases on climate change signals for daily precipitation and for minimum and maximum temperatures. Through the use of multiple climate scenarios from 12 regional climate model simulations, the ensemble mean, and three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal climate change signals between current and future periods, for both median and extreme precipitation/temperature values. A significant dependence of seasonal climate change signals on the model biases over southern Québec in Canada was detected for temperatures, but not for precipitation. This suggests that the regional temperature change signal is affected by local processes. Seasonally, model bias affects future mean and extreme values in winter and summer. In addition, potentially large increases in future extremes of temperature and precipitation values were projected. For three synthetic scenarios, systematically less bias and a narrow range of mean change for all variables were projected compared to those of climate model simulations. In addition, synthetic scenarios were found to better capture the spatial variability of extreme cold temperatures than the ensemble mean scenario. Finally, these results indicate that the synthetic scenarios have greater potential to reduce the uncertainty of future climate projections and capture the spatial variability of extreme climate events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Model-Data for Joint Estimation of Biogeochemical Model Parameters from Multiple Experiments: A Bayesian Approach Applied to Mercury Methylation

This modeling archive supports the manuscript submitted for publication in the Environmental Modeling and Software. This study is supported by ORNL-SFA and IDEAS-Watershed. This study aims to improve calibration of complex biogeochemical models using datasets from multiple experiments targeting specific subprocesses. The proposed Bayesian joint-fitting scheme calibrates the entire biogeochemical model in one go using all the available datasets and estimate parameter uncertainties using Markov Chain Monte Carlo (MCMC). This allows for complete propagation of uncertainties and utilization of the information shared between different datasets. Mapping joint distribution of parameters guides model improvement by identifying null spaces in the parameter space. This archive contains files used to perform MCMC, post-process outputs and visualize results.

East Fork Poplar Creek↗
DOE OSTI2022

Parallel simulated annealing with embedded machine learning and multifidelity models for reactor core design

This paper presents extensions to a penalty-free, parallel simulated annealing (SA) algorithm for multi-constrained combinatorial optimization with the aim of embedding multi-fidelity physics models into the annealing procedure. The method uses a low-fidelity, quickly executing model for rapid design space exploration and a high-fidelity model for detailed constraint resolution and on-the-fly bias correction. Machine learning models updated within the annealing procedure were used to bridge the gap between the multi-fidelity models, which led to accurate rapid exploration and efficient detailed constraint resolution. A software implementation of the new multi-fidelity optimization methods, called ML-PSA, was demonstrated on a continuous multi-fidelity optimization problem and a constrained combinatorial PWR lattice design problem. These problems demonstrate some of the features, parallel performance characteristics, and extensible nature of the multi-fidelity SA methods. This paper shows that the developed software and procedure are a general optimization tool that can be applied to a wide variety of scientific and engineering design optimization applications. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

The Variable Saturation Hydraulic Conductivity Method for Improving Soil Water Content Simulation in EPIC and APEX Models

Core Ideas We propose VSHC for calculating soil water percolation in continuous models. VSHC relates permeability to daily hydraulic properties to estimate hydraulic conductivity. VSHC performed well at field scale and improved estimates of peak streamflows. Soil water percolation is a key process in the life cycle of water in fields, watersheds, and river basins. The Environmental Policy Integrated Climate (EPIC) and the Agricultural Policy/Environmental eXtender (APEX) are continuous models developed for evaluating the environmental effects of agricultural management. Traditionally, these models have simulated soil water percolation processes using a tipping‐bucket approach, with the rate of flow limited by the saturated hydraulic conductivity. This simple approach often leads to inaccuracy in simulating elevated soil water conditions where soil water content (SWC) levels may remain above field capacity under prolonged wet weather periods or limited drainage. To overcome this deficiency, a new submodel, the variable saturation hydraulic conductivity (VSHC) method, was developed for simulating soil water percolation processes using a nonlinear equation to estimate the effective hydraulic conductivity as a function of the SWC and soil properties. The VSHC method was evaluated at three sites in the United States and two sites in Europe. In addition, a numerical solution of the Richards equation was used as a benchmark for SWC comparison. Results show that the VSHC method substantially improves the accuracy of the SWC simulation in long‐term simulations, particularly during wet periods. At the watershed scale, results on the Riesel Y2 watershed indicate that the VSHC method enhances model performance in the high‐flow regime of channel peak flows because of the improved estimation of SWC, which implies that the improved SWC simulation at the field scale is beneficial to hydrologic modeling at the watershed scale.

Doro, Luca↗
DOE OSTI2016

Dynamic Metabolic Model Building Based on the Ensemble Modeling Approach

Ensemble modeling of kinetic systems addresses the challenges of kinetic model construction, with respect to parameter value selection, and still allows for the rich insights possible from kinetic models. This project aimed to show that constructing, implementing, and analyzing such models is a useful tool for the metabolic engineering toolkit, and that they can result in actionable insights from models. Key concepts are developed and deliverable publications and results are presented.

09 BIOMASS FUELS↗
DOE OSTI2016

Model complexity and choice of model approaches for practical simulations of CO 2 injection, migration, leakage and long-term fate

This report documents the accomplishments achieved during the project titled “Model complexity and choice of model approaches for practical simulations of CO 2 injection,migration, leakage and long-term fate” funded by the US Department of Energy, Office of Fossil Energy. The objective of the project was to investigate modeling approaches of various levels of complexity relevant to geologic carbon storage (GCS) modeling with the goal to establish guidelines on choice of modeling approach.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Nuclear Energy Advanced Modeling and Simulation (NEAMS) Accident Tolerant Fuels High Impact Problem: Coordinate Multiscale U 3 Si 2 Modeling

Since the events at the Fukushima-Daiichi nuclear power plant in March 2011 significant research has unfolded at national laboratories, universities and other institutions into alternative materials that have potential enhanced accident tolerance when compared to traditional \uo~fuel zircaloy clad fuel rods. One of the potential replacement fuels is uranium silicide (\usi) for its higher thermal conductivity and uranium density. The lower melting temperature is of potential concern during postulated accident conditions. Another disadvantage for \usi~ is the lack of experimental data under power reactor conditions. Due to the aggressive development schedule for inserting some of the potential materials into lead test assemblies or rods by 2022~\cite{bragg-sitton_2014} multiscale multiphysics modeling approaches have been used to provide insight into these materials. \\ \noindent The purpose of this letter report is to highlight the multiscale modeling effort for \usi~fuel as part of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Accident Tolerant Fuel (ATF) High Impact Problem (HIP). This fiscal year two new models for \usi~fuel have been incorporated into the BISON fuel performance code~\cite{Williamson2012} based upon lower length scale simulations using the GRASS-SST rate theory code. The models are briefly described in the following sections.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Model comparisons of the reactive burn model SURF in three ASC codes

A study of the SURF reactive burn model was performed in FLAG, PAGOSA and XRAGE. In this study, three different shock-to-detonation transition experiments were modeled in each code. All three codes produced similar model results for all the experiments modeled and at all resolutions. Buildup-to-detonation time, particle velocities and resolution dependence of the models was notably similar between the codes. Given the current PBX 9502 equations of state and SURF calibrations, each code is equally capable of predicting the correct detonation time and distance when impacted by a 1D impactor at pressures ranging from 10-16 GPa, as long as the resolution of the mesh is not too coarse.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2018

Application of Bayesian Model Selection for Metal Yield Models using ALEGRA and Dakota

This report introduces the concepts of Bayesian model selection, which provides a systematic means of calibrating and selecting an optimal model to represent a phenomenon. This has many potential applications, including for comparing constitutive models. The ideas described herein are applied to a model selection problem between different yield models for hardened steel under extreme loading conditions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A modular biogeochemical modeling suite for next-generation ocean models (Final Report)

The Marine Biogeochemistry Library (MARBL) is a self-contained implementation of ocean biogeochemistry suitable for incorporation in Earth system models. The default configuration of MARBL represents multiple nutrient co-limitation (N, P, Si, and Fe), includes three explicit phytoplankton functional groups (diatoms, diazotrophs, and pico/nano phytoplankton), and one implicit group (calcifiers); there is one zooplankton group. MARBL includes fully prognostic carbonate chemistry and simulates sinking particulate organic matter implicitly, subject to ballasting by mineral dust, biogenic mineral carbonate and opal. MARBL represents subgrid-scale variations in light, variable C:P stoichiometry, semi-labile and refractory dissolved organic material pools, prognostic oceanic emission of ammonia, and an explicit ligand tracer that complexes iron. MARBL is fully runtime-configurable, and is flexible enough to accommodate a variable number of plankton functional types and ecosystem configurations. Critically, MARBL is implemented to be independent of any particular ocean general circulation model (OGCM); it is a standalone library that interfaces with an OGCM's via an explicit "driver" layer. MARBL can thus be coupled to multiple OGCM's, enabling efficient maintenance, development, and cross-model inter-comparison. MARBL is the ocean biogeochemistry component for the Community Earth System Model and the DOE’s Energy Exascale Earth System Model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

BISON BWR Fuel Modeling Capability: Material Models (FY2020)

Until this year the BISON fuel performance code has been developed primarily for pressurized water reactor (PWR), accident tolerant fuel (ATF), and advanced reactor (e.g., tri-structural isotropic (TRISO), metallic) analyses. The main focus of this work is to develop and document required material models that would aid predicting cladding failure with a specific hydride distribution to be investigated for boiling water reactor (BWR) applications in the next fiscal year. In terms of materials, the primary differences between a BWR and PWR is the use of gadolinia doping of the UO 2 fuel, the use of Zircaloy-2 for the cladding, and the addition of a liner on the inner surface of the cladding for improved pellet-clad mechanical interaction (PCMI)performance. The liner is typically made of pure zirconium or a lower tin content zirconium alloy (e.g. Zr-0.3%Sn). This work details the development and documentation of material and behavioral models for BWR analysis such as the addition of material and behavior models for gadolinia doped UO 2 , pure zirconium, Zr-0.3%Sn, and Zircaloy-2 as well as the ease-of-use additions to allow internal meshing capabilities to include liners. Another important aspect affecting cladding performance is hydrogen diffusion and hydride precipitation in the cladding. A model was added previously for non-lined, homogeneous claddings. In this work, instructions are provided on how to apply the model to BWR liner cladding. Representative experimental values are provided for the hydrogen diffusion parameters and precipitation-dissolution kinetics for typical liner materials of interest.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

FECM/NETL CO 2 Transport Cost Model (2022): Model Overview [Slides]

The FECM/NETL CO 2 Transport Cost Model (CO 2 _T_COM) is an Excel spreadsheet model that calculates the cost of transporting CO 2 from the beginning to the end of a pipeline. This document provides an overview of the model. This document is intended to provide a user with a briefer description of the model and how to use the model than the user’s manual.

42 ENGINEERING↗