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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Asymmetric dark matter and CP violating scatterings in a UV complete model

We explore possible asymmetric dark matter models using CP violating scatterings to generate an asymmetry. In particular, we introduce a new model, based on DM fields coupling to the SM Higgs and lepton doublets, a neutrino portal, and explore its UV completions. We study the CP violation and asymmetry formation of this model, to demonstrate that it is capable of producing the correct abundance of dark matter and the observed matter-antimatter asymmetry. Crucial to achieving this is the introduction of interactions which violate CP with a T{sup 2} dependence.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Analysis of Irradiance Models for Bifacial PV Modules

We describe and compare two methods for modeling irradiance on the back surface of rack-mounted bifacial PV modules: view factor models and ray-tracing simulations. For each method we formulate one or more models and compare each model with irradiance measurements and short circuit current for a bifacial module mounted a fixed tilt rack with three other similarly sized modules. Our analysis illustrates the computational requirements of the different methods and provides insight into their practical applications. We find a level of consistency among the models which indicates that consistent models may be obtained by parameter calibrations.

14 SOLAR ENERGY↗
DOE OSTI2021

TEAMER - AquaHarmonics High Fidelity WEC Sim PTO and Control Model Validation, Sim Model

Collaborative effort between AquaHarmonics, Sandia National Laboratories (SNL), and the National Renewable Energy Laboratory (NREL) to revise and validate Aquaharmonics' full wave to wire model, allowing for reduced uncertainty and increased understanding of design requirements of a utility scale wave energy converter (WEC). SNL and NREL in collaboration with AquaHarmonics, will set up and run WEC Simulator (WEC-Sim) models of the AquaHarmonics WEC, building off past model developments for inclusion of custom PTO (power take-off) dynamics. The intent is to review, update, and verify or validate a new WEC-Sim model against wave tank experimental data. Furthermore, the WEC-Sim model will be coupled to an energy storage system model to better understand the wave-to-wire functionality. Project is part of the TEAMER (Testing & Expertise for Marine Energy) RFTS (request for technical support) system of WEC research projects. Testing data can be found in the associated MHKDR link below.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Nuclear Energy in Long-Term System Models: A Multi-Model Perspective

Long-term energy system models–including electric sector capacity expansion models–are widely used tools for informing planning, technology assessment, and policy analysis. Recent decarbonization goals and rapid technological change have increased the need to appropriately represent economic characteristics and technical details of energy system resources, including variable renewable energy, energy storage technologies, carbon-capture-equipped capacity, and nuclear energy. Nuclear power represents about 20% of electricity generation and 50% of carbon-free electricity in the United States as of 2021. However, there are many perspectives on the role of existing and new nuclear in the future U.S. energy system, which is reflected in the broad range of potential contributions reported in the literature. This project aims to understand how issues central to nuclear energy are represented in long-term energy models. Building on earlier collaborations that focused on variable renewable energy and energy storage, this project convenes four modeling teams that use national-scale long-term energy system models from the Electric Power Research Institute, the National Renewable Energy Laboratory, the U.S. Energy Information Administration, and the U.S. Environmental Protection Agency to share methods and data, update models, run coordinated scenarios, and identify research needs. Improving tools can provide more insightful analyses and ensure that methods are more transparent.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2020

GISS Model E2.2: A Climate Model Optimized for the Middle Atmosphere. Part 2: Validation of Large-Scale Transport and Evaluation of Climate Response

Here we examine the large‐scale transport characteristics of the new ``Middle Atmosphere" NASA Goddard Institute for Space Studies climate model (E2.2). First we evaluate the stratospheric transport circulation in historical atmosphere‐only simulations integrated with interactive trace gas and aerosol chemistry. Compared to lower vertical resolution model versions, E2.2 exhibits improved tropical ascent and older stratospheric mean ages that are more consistent with observed values. In the troposphere, poleward transport to the Arctic and interhemispheric mean ages in E2.2 are comparable to models participating in the Chemistry Climate Modeling Initiative. In addition to validating E2.2 we also assess its ``transport sensitivity" using the coupled atmosphere‐ocean abrupt 4xCO2 and transient 1%CO2 simulations submitted to the Coupled Model Intercomparison Project, Phase 6, along with a 2xCO2 simulation used to evaluate the linearity of the transport circulation's response to increased CO2. We show that decreases (increases) in a stratospheric mean age (idealized surface loss) tracer scale linearly with increased lower stratospheric upwelling, which also increases linearly with warming tropical sea surface temperatures (SSTs). Abrupt 2xCO2 and 4xCO2 experiments constrained with (fixed) pre‐industrial SSTs are also used to quantify the relative importance of rapid adjustments versus SST feedbacks to the transport circulation responses in the model. Finally, sensitivity experiments are presented to illustrate the impact of changes in the convective parameterization on stratospheric transport.

GISS Model E2.2↗
DOE OSTI2014

Economic model predictive control of nonlinear process systems using empirical models

Economic model predictive control (EMPC) is a feedback control technique that attempts to tightly integrate economic optimization and feedback control since it is a predictive control scheme that is formulated with an objective function representing the process economics. As its name implies, EMPC requires the availability of a dynamic model to compute its control actions and such a model may be obtained either through application of first principles or through system identification techniques. In industrial practice, it may be difficult in general to obtain an accurate first‐principles model of the process. Motivated by this, in the present work, Lyapunov‐based EMPC (LEMPC) is designed with a linear empirical model that allows for closed‐loop stability guarantees in the context of nonlinear chemical processes. Specifically, when the linear model provides a sufficient degree of accuracy in the region where time varying economically optimal operation is considered, conditions for closed‐loop stability under the LEMPC scheme based on the empirical model are derived. The LEMPC scheme is applied to a chemical process example to demonstrate its closed‐loop stability and performance properties as well as significant computational advantages. © 2014 American Institute of Chemical Engineers AIChE J , 61: 816–830, 2015

Alanqar, Anas↗
DOE OSTI2018

Coupling methods between finite element-based Boussinesq-type wave and particle-based free-surface flow models [Coupling methods between finite element-based Boussinesq-typewave and particle-based free-surface flow models]

We develop one-way coupling methods between a Boussinesq-type wave model based on the discontinuous Galerkin finite element method and a free-surface flow model based on a mesh-free particle method to strike a balance between accuracy and computational cost. In our proposed model, computation of the wave model in the global domain is conducted first, and the nonconstant velocity profiles in the vertical direction are reproduced by using its results. Computation of the free-surface flow is performed in a local domain included within the global domain with interface boundaries that move along the reproduced velocity field in a Lagrangian fashion. To represent the moving interfaces, we used a polygon wall boundary model for mesh-free particle methods. Verification and validation tests of our proposed model are performed, and results obtained by the model are compared with theoretical values and experimental results to show its accuracy and applicability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

North American extreme precipitation events and related large-scale meteorological patterns: a review of statistical methods, dynamics, modeling, and trends

This paper surveys the current state of knowledge regarding large-scale meteorological patterns (LSMPs) associated with short-duration (less than 1 week) extreme precipitation events over North America. In contrast to teleconnections, which are typically defned based on the characteristic spatial variations of a meteorological feld or on the remote circulation response to a known forcing, LSMPs are defned relative to the occurrence of a specifc phenomenon—here, extreme precipitation—and with an emphasis on the synoptic scales that have a primary infuence in individual events, have medium-range weather predictability, and are well-resolved in both weather and climate models. For the LSMP relationship with extreme precipitation, we consider the previous literature with respect to defnitions and data, dynamical mechanisms, model representation, and climate change trends. There is considerable uncertainty in identifying extremes based on existing observational precipitation data and some limitations in analyzing the associated LSMPs in reanalysis data. Many diferent defnitions of “extreme” are in use, making it difcult to directly compare diferent studies. Dynamically, several types of meteorological systems—extratropical cyclones, tropical cyclones, mesoscale convective systems, and mesohighs—and several mechanisms—fronts, atmospheric rivers, and orographic ascent—have been shown to be important aspects of extreme precipitation LSMPs. The extreme precipitation is often realized through mesoscale processes organized, enhanced, or triggered by the LSMP. Understanding of model representation, trends, and projections for LSMPs is at an early stage, although some promising analysis techniques have been identifed and the LSMP perspective is useful for evaluating the model dynamics associated with extremes.

Barlow, Mathew↗
DOE OSTI2019

Investigation of goodness of model data fit using PLSR and PCR regression models to determine informative wavelength band in NIR region for non-invasive blood glucose prediction

Diabetes mellitus is a metabolic disorder characterized by the deficiency in insulin secretion or insulin action on target tissues. Diabetes being diagnosed, requires frequent monitoring. Current measurement techniques are invasive in nature, which is painful. Non-invasive measurement methods for the prediction of blood glucose is a big challenge. Hence this paper focuses on a comparative study to analyze the performance of the two regression models: partial least square regression (PLSR) and principal component regression (PCR) models to arrive at the best regression model for the prediction of blood glucose non-invasively based on NIR diffuse reflectance spectroscopy. The regression model developed involves spectral data collected from 32 subjects from a diabetic center using diffuse reflectance spectrometer (DRS). The spectroscopic data were acquired from the subjects both invasively using clinical method and non-invasively using DRS setup in the NIR spectral range whose wavelength ranges from 750 to 1040 nm. Multivariate analysis using PLSR is found to be a better regression model in terms of the fitted response and estimated mean square prediction error. It is observed that the mean square error value is 0.04 mg/dl for the tenth component in the PLSR model. The developed regression model also proves to be a useful tool in identifying the informative wavelength bands for blood glucose measurement.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Improving the Modeling of Slag and Steel Bath Chemistry in an Electric Arc Furnace Process Model

An improvement to the thermochemical module of the electric arc furnace (EAF) process model developed by Meier based on the work of Logar, Dovžan, and Škrjanc is presented. Different models for the calculation of activities in melt and slag are implemented, and separate reaction zones are defined for the interaction of slag and melt, the injection of oxygen, and the injection of carbon. For each zone, equilibrium compositions and reaction rates are calculated. Furthermore, diffusion of species is considered as a rate-limiting factor in reactions between slag and melt, and diffusion rates are calculated from the bulk melt to the reaction zone where reactions with the slag take place. Oxygen and sulfur dissolved in the melt and CaS in the slag are added as new species not previously considered in the EAF model. The treatment of carbon is revised to reduce model complexity and improve accuracy. The improved model is validated using extensive data from an industrial EAF, and results are compared to measured data as well as results obtained with the unmodified model. The different models for the determination of thermodynamic activities and their impacts on the duration of the simulation as well as its results are evaluated.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A heuristic model inversion for coupled thermo-hydro-mechanical modelling of triaxial experiments

As multiphysics geomechanical models get developed, their increasing complexity and number of parameters make it particularly difficult to calibrate against experimental data. In this contribution, we present a heuristic workflow to invert for parameters of a coupled Thermo-Hydro-Mechanical (THM) model in a way that helps the theoretical modellers refine their definition of the underlying elasto-visco-plastic model itself. We apply this workflow to the calibration of deviatoric and volumetric data for two sets of triaxial experiments on mudstone and sandstone. Here, we show that beyond the calibration of well-defined parameters of the THM model, one or two scaling factors of the experimentally obtained yield surface and two more factors to capture the confinement and pore pressure dependency of the flow law lead to the satisfactory matching of series of experiments at varying confinements for two different rock types. Using this physical model, we also show that tracking the volumetric component of the mechanical power in the numerical simulations might allow reducing the number of experiments required to calibrate the model.

58 GEOSCIENCES↗
DOE OSTI2016

Modeling of inertial deposition in scaled models of rat and human nasal airways: Towards in vitro regional dosimetry in small animals

Rodents are routinely used in inhalation toxicology tests as human surrogates. However, in vitro dosimetry tests in rodent casts are still scarce due to small rodent airways and in vitro tests to quantify sub-regional dosimetry are still impractical. We hypothesized that for inertial particles whose deposition is dominated by airflow convection (Reynolds number) and particle inertia (Stokes number), the deposition should be similar among airway replicas of different scales if their Reynolds and Stokes numbers are kept the same. In this study, we aimed to (1) numerically test the hypothesis in three airway geometries: a USP induction port, a human nose model, and a Sprague-Dawley rat nose model, and (2) find the range of applicability of this hypothesis. Five variants of the USP and human nose models and three variants of the rat nose model were tested. Inhalation rates and particle sizes were scaled to match the Reynolds number and Stokes numbers. A low-Reynolds-number k–ω model was used to resolve the airflow and a Lagrangian tracking algorithm was used to simulate the particle transport and deposition. Statistical analysis of predicted doses was conducted using ANOVA. For normal inhalation rates and particle dia- meters ranging from 0.5 to 24 mm, the deposition differences between the life-size and scaled models are insignificant for all airway geometries considered (i.e., human nose, USP, and rat nose). Furthermore, the deposition patterns and exit particle profiles also look similar among scaled models. However, deposition rates and patterns start to deviate if inhalation rates are too low, or particle sizes are too large. For the rat nose, the threshold velocity was found to be 0.71 m/s and the threshold Froude number to be 50. Results of this study provide a theoretical foundation for sub-regional in vitro dosimetry tests in small animals and for interpretation of data from inter-species or intra-species with varying body sizes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Non-local model for surface tension in fluid-fluid simulations

We propose a non-local model for surface tension obtained in the form of an integral of a molecular-force-like function with support 3.5e added to the Navier-Stokes momentum conservation equation. We demonstrate analytically and numerically that with the non-local model interfaces with a radius of curvature larger than the support length behave macroscopically and microscopically, otherwise. For static droplets, the pressure difference Pe,in - Pe,out satisfies the Young-Laplace law for droplet radius greater than 3.5e and other- wise deviates from the Young-Laplace law. The latter indicates that the surface tension in the proposed model decreases with decreasing radius of curvature, which agrees with molecular dynamics and experimental studies of nanodroplets. Using the non-local model we perform numerical simulations of droplets under dynamic conditions, including a rising droplet, a droplet in shear flow, and two colliding droplets in shear flow, and compare results with a standard Navier-Stokes model subject to the Young-Laplace boundary condition at the fluid-fluid interface implemented via the Conservative Level Set (CLS) method. We find good agreement with existing numerical methods and analytical results for a rising macroscopic droplet and a droplet in a shear flow. For colliding droplets in shear flow, the non- local model converges (with respect to the grid size) to the correct behavior, including sliding, coalescence, and merging and breaking of two droplets depending on the capillary number. In contrast, we find that the results of the CLS model are highly grid-size dependent.

Howard, Amanda A.↗
DOE OSTI2021

Deep glassy state dynamic data challenge glass models: Configurational entropy models

This work was the result of the student's (Dongjie Chen) qualifying exam response. In it the experimental observation from our labs that the relaxation times of ultrastable glasses (a 20 million year old amber and a vapor deposited amorphous teflon) do not follow the expected Vogel-Fulcher or WLF types of divergence as the temperatures fall below the glass transition temperature. In the work we evaluated several theories by considering them in different ways. We used them as generally used and show that they do not capture the non-diverging behavior. Because the models were all entropy-based models, we also considered the possibility that the temperature dependence of the entropy used in the models is incorrect and chose two ways of estimating the entropy that do not follow the classical theoretical models. First we used the actually measured calorimetric response for the two ultrastable glasses, and we used the Milchev model, which does not go to zero above 0 Kelvin. Both of these approaches led to improved agreement between the theories and the experimental data. Finally, we also asked what the temperature dependence of the entropy would have to be so that the models agreed with the observed data. In some cases the entropy so-calculated was reasonable, while in others it was unphysical. In sum, the important point of the work is that the observation of non-diverging time-scales that suggest that there is no ideal glass transition can be reasonably captured by current theories if they take more realistic models of the entropy than is usually the case.

36 MATERIALS SCIENCE↗
DOE OSTI2018

An automatic performance model-based scheduling tool for coupled climate system models

The prediction of the climate system is highly depended on the efficient integration of observations and simulations of the Earth. This is regarded as a canonical example of the cyber-physical system. The climate system model, the simulation engine in this cyber-physical system, is one of most challenging applications in scientific computing. It utilizes the multi-physics simulation that couples multiple components, conducts decadal to millennium simulations, and has long been an important application on supercomputers. However, current climate system models suffer from the inefficient task scheduling methods resulting in an intolerable simulation time. Take the Community Earth System Model (CESM), the most widely used climate system model, as an example, one major reason that CESM suffers from bad performances is the huge overhead to rationally distribute processes among the coupled heterogeneous components. According to the report of NCAR, every percent improvement in CESM performance frees up to the equivalent of $250,000 in computing resources in their scientific experiments. To address such challenge, our paper firstly constructs a lightweight and accurate performance model for effectively capturing and predicting the heterogeneous time-to-solution performance of end-to-end CESM components with a given simulation configuration. Then, based on the performance model, we further propose an efficient scheduling strategy based on rectangular packing method to determine the best process layout among different components, and the process numbers assigned to each component. Our evaluations show that we can achieve 58% average run time reductions on CESM comparing to the widely used sequential process layout for a scale of 144 to 480 cores on typical CPU clusters. And we can save 4 million CPU hours when we conduct one standard scientific experiment (a 2870-year simulation), which equals to save $40,089 with a charge of $0.01 per CPU hour. Meanwhile, 26% extra performance improvements could also be gained in our methods comparing to the heuristic branch and bound algorithm with the guidance of the known curve-fitting performance model.

58 GEOSCIENCES↗
DOE OSTI2024

Modeling information flow in a computer processor with a multi-stage queuing model

In this paper, we introduce a nonlinear stochastic model to describe the propagation of information inside a computer processor. In this model, a computational task is divided into stages, and information can flow from one stage to another. The model is formulated as a spatially-extended, continuous-time Markov chain where space represents different stages. This model is equivalent to a spatially-extended version of the M/M/s queue. The main modeling feature is the throttling function which describes the processor slowdown when the amount of information falls below a certain threshold. We derive the stationary distribution for this stochastic model and develop a closure for a deterministic ODE system that approximates the evolution of the mean and variance of the stochastic model. In conclusion, we demonstrate the validity of the closure with numerical simulations.

97 MATHEMATICS AND COMPUTING↗