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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 757 records · Page 42

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NASA NTRS1990

Near-wall turbulence model and its application to fully developed turbulent channel and pipe flows

A near-wall turbulence model and its incorporation into a multiple-timescale turbulence model are presented. The near-wall turbulence model is obtained from a k-equation turbulence model and a near-wall analysis. In the method, the equations for the conservation of mass, momentum, and turbulent kinetic energy are integrated up to the wall, and the energy transfer and the dissipation rates inside the near-wall layer are obtained from algebraic equations. Fully developed turbulent channel and pipe flows are solved using a finite element method. The computational results compare favorably with experimental data. It is also shown that the turbulence model can resolve the overshoot phenomena of the turbulent kinetic energy and the dissipation rate in the region very close to the wall.

Kim, S.-W.↗

DOE OSTI2022

Reinforcement learning for online adaptation of model predictive controllers: Application to a selective catalytic reduction unit

Here we present a novel application of reinforcement learning (RL) for online dynamic tuning of model predictive controllers (MPC). Applying a state-action-reward-state-action (SARSA) algorithm for temporal difference learning with a control-specific reward function improves the error tracking performance of a standard MPC formulation. The proposed RL approach is also readily adaptable to other MPCs, or entirely different control approaches. Practical details for the implementation of the RL-MPC algorithm are also presented. The proposed algorithm is applied to a case study of controlling nitrogen oxide (NO x ) emissions in an industrial selective catalytic reduction (SCR) unit, a control problem characterized by significant nonlinearity and time delay. Along with an RL-MPC formulation for NOx control, another MPC is proposed to mitigate ammonia slip and decrease ammonia consumption in the SCR. Results showing the efficacy of the RL-MPC for NO x control through learning and implementation on the nonlinear SCR dynamic model are presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Storm Surge Modeling as an Application of Local Time-Stepping in MPAS-Ocean

This paper presents the first practical application of local time-stepping (LTS) schemes in the Model for Prediction Across Scales-Ocean (MPAS-O). We use LTS schemes in a single-layer, global ocean model that predicts the storm surge around the eastern coast of the United States during Hurricane Sandy. The variable-resolution meshes used are of unprecedentedly high resolution in MPAS-O, containing cells as small as 125 m wide in Delaware Bay. It is shown that a particular, third-order LTS scheme (LTS3) produces sea-surface height solutions that are of comparable quality to solutions produced by the classical four-stage, fourth-order Runge-Kutta method (RK4) with a uniform time step on the same meshes. Furthermore, LTS3 is up to 35% faster in the best cases considered, where the number of cells using the coarse time-step relative to those using the fine time-step is as low as 1:1. This shows that LTS schemes are viable for use in MPAS-O with the added benefit of substantially less computational cost. The results of these performance experiments inform us of the requirements for efficient mesh design and configuration of LTS regions for LTS schemes. In particular, we see that for LTS to be efficient on a given mesh, it is important to have enough cells using the coarse time-step relative to those using the fine time-step, typically at least 1:5 to see an increase in performance.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1987

Finite element implementation of Robinson's unified viscoplastic model and its application to some uniaxial and multiaxial problems

A description of the finite element implementation of Robinson's unified viscoplastic model into the General Purpose Finite Element Program (MARC) is presented. To demonstrate its application, the implementation is applied to some uniaxial and multiaxial problems. A comparison of the results for the multiaxial problem of a thick internally pressurized cylinder, obtained using the finite element implementation and an analytical solution, is also presented. The excellent agreement obtained confirms the correct finite element implementation of Robinson's model.

Arya, V. K.↗

NASA NTRS1989

Finite element implementation of Robinson's unified viscoplastic model and its application to some uniaxial and multiaxial problems

Arya, V. K.↗

NASA NTRS1990

An assessment and application of turbulence models for hypersonic flows

The current approach to the Accurate Computation of Complex high-speed flows is to solve the Reynolds averaged Navier-Stokes equations using finite difference methods. An integral part of this approach consists of development and applications of mathematical turbulence models which are necessary in predicting the aerothermodynamic loads on the vehicle and the performance of the propulsion plant. Computations of several high speed turbulent flows using various turbulence models are described and the models are evaluated by comparing computations with the results of experimental measurements. The cases investigated include flows over insulated and cooled flat plates with Mach numbers ranging from 2 to 8 and wall temperature ratios ranging from 0.2 to 1.0. The turbulence models investigated include zero-equation, two-equation, and Reynolds-stress transport models.

Coakley, T. J.↗

NASA NTRS1991

Recent improvements in atmospheric environment models for Space Station applications

The capability of empirical models of the earth's thermosphere must continually be updated if they are to keep pace with their many applications in the aerospace industry. This paper briefly summarizes the progress of several such efforts in support of the Space Station Program. The efforts consists of the development of data bases, analytical studies of the data, and evaluation and intercomparison of thermosphere models. A geomagnetic storm model of Slowey does not compare as well to the MSIS-86 model as does the Marshall Engineering Thermosphere (MET). LDEF orbit decay data is used to evaluate the performance of the MET and MSIS-86 during a period of high solar activity; equal to or exceeding the highest levels that existed during the time of the original data sets upon which these models are based.

Anderson, B. Jeffrey↗

DOE OSTI2021

Coarse Woody Debris Decomposition Assessment Tool: Model validation and application

Coarse woody debris (CWD) is a significant component of the forest biomass pool; hence a model is warranted to predict CWD decomposition and its role in forest carbon (C) and nutrient cycling under varying management and climatic conditions. A process-based model, CWDDAT (Coarse Woody Debris Decomposition Assessment Tool) was calibrated and validated using data from the FACE (Free Air Carbon Dioxide Enrichment) Wood Decomposition Experiment utilizing pine ( Pinus taeda ), aspen ( Populous tremuloides ) and birch ( Betula papyrifera ) on nine Experimental Forests (EF) covering a range of climate, hydrology, and soil conditions across the continental USA. The model predictions were evaluated against measured FACE log mass loss over 6 years. Four widely applied metrics of model performance demonstrated that the CWDDAT model can accurately predict CWD decomposition. The R 2 (squared Pearson’s correlation coefficient) between the simulation and measurement was 0.80 for the model calibration and 0.82 for the model validation ( P <0.01). The predicted mean mass loss from all logs was 5.4% lower than the measured mass loss and 1.4% lower than the calculated loss. The model was also used to assess the decomposition of mixed pine-hardwood CWD produced by Hurricane Hugo in 1989 on the Santee Experimental Forest in South Carolina, USA. The simulation reflected rapid CWD decomposition of the forest in this subtropical setting. The predicted dissolved organic carbon (DOC) derived from the CWD decomposition and incorporated into the mineral soil averaged 1.01 g C m -2 y -1 over the 30 years. The main agents for CWD mass loss were fungi (72.0%) and termites (24.5%), the remainder was attributed to a mix of other wood decomposers. These findings demonstrate the applicability of CWDDAT for large-scale assessments of CWD dynamics, and fine-scale considerations regarding the fate of CWD carbon.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1989

Application of photometric models to asteroids

The way an asteroid or other atmosphereless solar system body varies in brightness in response to changing illumination and viewing geometry depends in a very complicated way on the physical and optical properties of its surface and on its overall shape. This paper summarizes the formulation and application of recent photometric models by Hapke (1981, 1984, 1986) and by Lumme and Bowell (1981). In both models, the brightness of a rough and porous surface is parameterized in terms of the optical properties of individual particles, by shadowing between particles, and by the way in which light is scattered among collections of particles. Both models succeed in their goal of fitting the observed photometric behavior of a wide variety of bodies, but neither has led to a very complete understanding of the properties of asteroid regoliths, primarily because, in most cases, the parameters in the present models cannot be adequately constrained by observations of integral brightness alone over a restricted range of phase angles.

Bowell, Edward↗

NASA NTRS2013

Kuang's Semi-Classical Formalism for Calculating Electron Capture Cross Sections and Sample Application for ENA Modeling

Accurate estimates of electron-capture cross sections at energies relevant to ENA modeling (approx. few MeV per nucleon) and for multi-electron ions must rely on detailed, but computationally expensive, quantummechanical description of the collision process. Kuang's semi-classical approach is an elegant and efficient way to arrive at these estimates. Motivated by ENA modeling efforts, we shall briefly present this approach along with sample applications and report on current progress.

Barghouty, A. F.↗

DOE OSTI2022

Modeling the AC Power Flow Equations with Optimally Compact Neural Networks: Application to Unit Commitment

Nonlinear power flow constraints render a variety of power system optimization problems computationally intractable. Emerging research shows, however, that the nonlinear AC power flow equations can be successfully modeled using neural networks. These neural networks can be exactly transformed into mixed integer linear programs and embedded inside challenging optimization problems, thus replacing nonlinearities that are intractable for many applications with tractable piecewise linear approximations. Such approaches, though, suffer from an explosion of the number of binary variables needed to represent the neural network. Accordingly, this paper develops a technique for training an "optimally compact'' neural network, i.e., one that can represent the power flow equations with a sufficiently high degree of accuracy while still maintaining a tractable number of binary variables. We demonstrate the use of this neural network as an approximator of the nonlinear power flow equations by embedding it in the AC unit commitment problem, transforming the problem from a mixed integer nonlinear program into a more manageable mixed integer linear program. We use the 14-, 57-, and 89-bus networks as test cases and compare the AC-feasibility of commitment decisions resulting from the neural network, DC, and linearized power flow approximations. Our results show that the neural network model outperforms both the DC and linearized power flow approximations when embedded in the unit commitment problem. The neural network formulation most often selects a feasible unit commitment schedule, and furthermore, it only s

AC power flow↗

DOE OSTI2026

SMR safety through HTTF modeling and benchmark efforts for code validation for gas-cooled reactor applications

Accurate modeling and simulation tools for thermal-hydraulics calculations are a key element needed to design and license new advanced reactors including Small Modular Reactors (SMR) and Microreactors. Uncertainties in modeling and simulation can have significant safety and economic implications. The High Temperature Test Facility (HTTF) at Oregon State University (OSU) is a scaled integral effects experiment designed to investigate transient behavior in high-temperature gas-cooled prismatic-block nuclear reactors. High-quality measurement data is available from the HTTF that is suitable for a thermal-hydraulics code validation benchmark for gas-cooled reactor simulations. Here, this paper summarizes individual HTTF modeling efforts to date for tool validation at Idaho National Laboratory (INL), Argonne National Laboratory (ANL), Oregon State University (OSU) and Canadian Nuclear Laboratories (CNL) using system thermal-hydraulics codes, Computational Fluid Dynamics (CFD) codes and system-CFD code couplings. Also, the paper introduces the ongoing OECD Nuclear Energy Agency (NEA) High Temperature Gas Reactor Thermal-Hydraulics (HTGR T/H) benchmark that allows for better comparisons of results between different international modeling teams. The benchmark provides well defined computational problems that include code-to-code comparisons and comparisons to measured data. These problems provide an avenue for quantifying accuracy and identifying sources of uncertainty in thermal-hydraulics calculations, including in measured thermophysical properties, as part of validation for gas-cooled reactor simulation tools.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

DOE OSTI2022

Cluster cosmology with anisotropic boosts: validation of a novel forward modelling analysis and application on SDSS redMaPPer clusters

We present a novel analysis for cluster cosmology that fully forward models the abundances, weak lensing, and the clustering of galaxy clusters. Our analysis notably includes an empirical model for the anisotropic boosts impacting the lensing and clustering signals of optical clusters. These boosts arise from a preferential selection of clusters surrounded by anisotropic large-scale structure, a consequence of the limited discrimination between line-of-sight interlopers and true cluster members offered by photometric surveys. We validate our analysis via a blind cosmology challenge on mocks, and find that we can obtain tight and unbiased cosmological constraints without informative priors or external calibrations on any of our model parameters. We then apply our analysis on the SDSS redMaPPer clusters, and find results favoring low Ωm and high σ8, combining to yield the lensing strength constraint $S_8 = 0.715_{-0.021}^{+0.024}$. We investigate potential drivers behind these results through a series of post-unblinding tests, noting that our results are consistent with existing cluster cosmology constraints but clearly inconsistent with other CMB/LSS based cosmology results. From these tests, we find hints that a suppression in the cluster lensing signal may be driving our results.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Yet Another Discriminant Analysis (YADA): A Probabilistic Model for Machine Learning Applications

This paper presents a probabilistic model for various machine learning (ML) applications. While deep learning (DL) has produced state-of-the-art results in many domains, DL models are complex and over-parameterized, which leads to high uncertainty about what the model has learned, as well as its decision process. Further, DL models are not probabilistic, making reasoning about their output challenging. In contrast, the proposed model, referred to as Yet Another Discriminate Analysis(YADA), is less complex than other methods, is based on a mathematically rigorous foundation, and can be utilized for a wide variety of ML tasks including classification, explainability, and uncertainty quantification. YADA is thus competitive in most cases with many state-of-the-art DL models. Ideally, a probabilistic model would represent the full joint probability distribution of its features, but doing so is often computationally expensive and intractable. Hence, many probabilistic models assume that the features are either normally distributed, mutually independent, or both, which can severely limit their performance. YADA is an intermediate model that (1) captures the marginal distributions of each variable and the pairwise correlations between variables and (2) explicitly maps features to the space of multivariate Gaussian variables. Numerous mathematical properties of the YADA model can be derived, thereby improving the theoretic underpinnings of ML. Validation of the model can be statistically verified on new or held-out data using native properties of YADA. However, there are some engineering and practical challenges that we enumerate to make YADA more useful.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Thermochemical characterization of intumescent materials and their application in FEM models using Aria

Intumescent materials are in wide use as protective coatings in fire protection or thermal management applications. These materials undergo chemical reactions occurring from approximately 300°C to 900°C, which outgas and expand the material, providing an appreciable increase in insulative performance. However, the complicated chemical mechanisms and large changes in materials properties complicate the incorporation of these materials into predictive thermal models. This document serves to outline the thermochemical characterization of select intumescent materials, the extraction of relevant parameters, and the incorporation of these parameters into the ChemEQ reaction model implemented in Aria. This work was performed in 2016 and documented in a draft SAND report in March 2017. In 2022, the draft SAND report was discovered and put through R&A.

36 MATERIALS SCIENCE↗

NASA NTRS1991

Reliability growth models for NASA applications

The objective of any reliability growth study is prediction of reliability at some future instant. Another objective is statistical inference, estimation of reliability for reliability demonstration. A cause of concern for the development engineer and management is that reliability demands an excessive number of tests for reliability demonstration. For example, the Space Transportation Main Engine (STME) program requirements call for .99 reliability at 90 pct. confidence for demonstration. This requires running 230 tests with zero failure if a classical binomial model is used. It is therefore also an objective to explore the reliability growth models for reliability demonstration and tracking and their applicability to NASA programs. A reliability growth model is an analytical tool used to monitor the reliability progress during the development program and to establish a test plan to demonstrate an acceptable system reliability.

Taneja, Vidya S.↗

NASA NTRS1982

A bivariate gamma probability distribution with application to gust modeling

A five-parameter gamma distribution (BGD) having two shape parameters, two location parameters, and a correlation parameter is investigated. This general BGD is expressed as a double series and as a single series of the modified Bessel function. It reduces to the known special case for equal shape parameters. Practical functions for computer evaluations for the general BGD and for special cases are presented. Applications to wind gust modeling for the ascent flight of the space shuttle are illustrated.

Smith, O. E.↗

DOE OSTI2020

An advanced membrane-based HMX model and its application in utilizing sensible and latent heat removed in space cooling

This paper presents a comprehensive simulation model for advanced membrane-based heat and mass exchanger (HMX) components which account for three separate fluid streams with complex flow patterns. The model was implemented with various liquid desiccants and their properties (including LiCl, CaCl and ionic liquid (IL)). Preliminary model validation is presented using data from a laboratory prototype absorber. The paper also presents implementation of the model into a sorption system modeling platform and analyzes potential benefit analysis of the HMX component in utilizing the sensible and latent heat removed in space cooling to heat water. The developed model and codes are expected to enable detailed optimization studies and identify novel configurations for the three-fluid HMX maximum performance and cost effectiveness.

Gao, Zhiming↗