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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Embedded Model Error Representation for Bayesian Model Calibration

Model error estimation remains one of the key challenges in uncertainty quantification and predictive science. For computational models of complex physical systems, model error, also known as structural error or model inadequacy, is often the largest contributor to the overall predictive uncertainty. This work builds on a recently developed framework of embedded, internal model correction, in order to represent and quantify structural errors, together with model parameters,within a Bayesian inference context. We focus specifically on a Polynomial Chaos representation with additive modification of existing model parameters, enabling a non-intrusive procedure for efficient approximate likelihood construction, model error estimation, and disambiguation of model and data errors’ contributions to predictive uncertainty. The framework is demonstrated on several synthetic examples, as well as on a chemical ignition problem.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Embedded Model Error Representation for Bayesian Model Calibration

Model error estimation remains one of the key challenges in uncertainty quantification and predictive science. For computational models of complex physical systems, model error, also known as structural error or model inadequacy,is often the largest contributor to the overall predictive uncertainty. This work builds on a recently developed framework of embedded, internal model correction, in order to represent and quantify structural errors, together with model parameters, within a Bayesian inference context. We focus specifically on a Polynomial Chaos representation with additive modification of existing model parameters, enabling a non-intrusive procedure for efficient approximate likelihood construction, model error estimation, and disambiguation of model and data errors' contributions to predictive uncertainty. As a result, the framework is demonstrated on several synthetic examples, as well as on a chemical ignition problem

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Spread Spectrum Digital Communications Modeling in Electronic Warfare Modeling and Simulation Software

This artifact is an intern project poster. The subject matter is modeling spread spectrum digital communications in electronic warfare modeling and simulation software produced by National and Homeland Security. It contains images of communications coverage analysis from the software, link budget terms, and image depicting the Wireless Spectrum Communications (WSComm) underlay control channel (UCC), and an image of a filter bank multicarrier spread spectrum (FBMCSS) signal. INL National and Homeland Security Electronic Warfare Modeling and Simulation software (EWMSS) is capable of modeling several digital and analog signal types, but it does not currently support spread spectrum techniques such as filter bank multicarrier spread spectrum (FBMCSS). FBMCSS modeling requires "processing gain," which is not present in EWMSS' link budget. Wireless Spectrum Communications (WSComm) Underlay Control Channel (UCC), a product of INL, employs FBMCSS and is modeled in EWMSS for this project. This research shows that by manually accounting for FBMCSS processing gain, EWMSS calculates a link margin that is within 0.023 dB of a link margin in an existing WSComm link budget. These link margins were based on free space path loss, an ideal propagation model. EWMSS has the capability to include terrain and other sophisticated propagation models in its calculations, giving it the potential to provide realistic, location-specific models of WSComm UCC if processing gain is accounted for.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

One System, Many Models: Designing a Surrogate Model for Sulfur Thermal Energy Storage: Preprint

Industrial process heating (IPH) relies primarily on thermal energy generated by fossil fuel combustion to produce, treat, and alter manufactured goods. Thermal energy storage (TES) helps reduce the carbon footprint of IPH systems by facilitating the utilization of renewable and waste heat sources. A promising new TES technology uses elemental sulfur as the heat-storage medium. The design of sulfur TES systems can be evaluated with the aid of computational fluid dynamics (CFD). However, the computational cost of such CFD efforts is prohibitive to comprehensive optimizations over design parameters. To reduce this computational cost, machine learning (ML) models can be developed to act as surrogates for CFD. In this paper, we describe the process of building and evaluating surrogate ML models for facilitating optimization of sulfur TES systems for IPH. To enforce the thermodynamic relationship between the two modeled quantities, we develop a hybrid model for sulfur temperature using both direct predictions of temperature and calculations of temperature from predictions of the heat transfer coefficient. The hybrid model enforces this constraint at the expense of the slightly reduced accuracy compared to two disjoint models. The overall high accuracy observed in our model evaluation demonstrates the usefulness of such surrogate modeling for studying TES systems. This work contributes to the field of TES surrogate modeling by offering a novel accurate hybrid approach to predicting simultaneously the heat transfer coefficient and temperature of the heat storage medium.

computational fluid dynamics↗
DOE OSTI2017

Development of a Regional Groundwater Flow Model for the U.S. Department of Energy Oak Ridge Reservation: EarthVision{sup R} Conceptual Site Model - 17367

A regional scale groundwater flow model (GFM) has been developed for the U.S. Department of Energy (DOE) Oak Ridge Reservation (ORR). Development of the model implements a key recommendation of the ORR Groundwater Strategy. The model will be used as the calibrated flow model for the ORR and as the framework for future, smaller scale, modeling efforts to support cleanup actions and decisions under the Comprehensive Environmental Response, Compensation, and Liability Act of 1980 (CERCLA). The Oak Ridge site is located in a geologically complex region and encompasses three large government facilities, including the Y-12 National Security Complex (Y-12), Oak Ridge National Laboratory (ORNL), and the East Tennessee Technology Park (ETTP). An interagency approach for addressing legacy groundwater contamination from past operations at these facilities has been developed, resulting in an ORR Groundwater Strategy that was agreed to by DOE, the U.S. Environmental Protection Agency (EPA), and Tennessee Department of Environment and Conservation (TDEC) in fiscal year (FY) 2014. The ORR Groundwater Strategy provides a comprehensive approach to addressing and prioritizing groundwater issues across the DOE reservation. Implementation of key recommendations from the strategy began in FY 2014, including the recommendation to 'develop and maintain an ORR-wide regional groundwater flow model to ensure a single, regional, calibrated model to support groundwater characterization, decision-making, and remediation.' As part of the cleanup plans for the Oak Ridge site under CERCLA and the Federal Facility Agreement (FFA), there are six final watershed-scale groundwater Records of Decision (RODs) currently planned. In preparation for future projects, the regional GFM has been constructed to serve as the single, calibrated regional flow model to be used as the hydrologic base for the groundwater plume-specific modeling developed for the RODs. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Development of a Regional Groundwater Flow Model for the U.S. Department of Energy Oak Ridge Reservation: Numerical Model using MODFLOW-USG - 17368

A regional scale groundwater flow model (GFM) has been developed for the U.S. Department of Energy (DOE) Oak Ridge Reservation (ORR). Development of the model implements a key recommendation of the ORR Groundwater Strategy. The model will be used as the single calibrated flow model for the ORR and as the framework for future, smaller scale, modeling efforts to support cleanup actions and decisions under the Comprehensive Environmental Response, Compensation, and Liability Act of 1980 (CERCLA). The Oak Ridge site is located in a geologically complex region and encompasses three large government facilities, including the Y-12 National Security Complex (Y-12), Oak Ridge National Laboratory (ORNL), and the East Tennessee Technology Park (ETTP). An interagency approach for addressing legacy groundwater contamination from past operations at these facilities has been developed, resulting in an ORR Groundwater Strategy that was agreed to by DOE, the U.S. Environmental Protection Agency (EPA), and Tennessee Department of Environment and Conservation (TDEC). The ORR Groundwater Strategy provides a comprehensive approach to addressing and prioritizing groundwater issues across the DOE reservation. One component of the strategy is to 'develop and maintain an ORR-wide regional groundwater flow model to ensure a single, regional, calibrated model to support groundwater characterization, decision-making, and remediation.' As part of the cleanup plans for the Oak Ridge site under CERCLA and the Federal Facility Agreement (FFA), there are six final watershed-scale groundwater Records of Decision (RODs) currently planned. In preparation for future projects, the regional GFM has been constructed to serve as the single, calibrated regional flow model to be used as the hydrologic base for the groundwater plume-specific modeling developed for the RODs. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Can artificial intelligence and data-driven machine learning models match or even replace process-driven hydrologic models for streamflow simulation?: A case study of four watersheds with different hydro-climatic regions across the CONUS

With recent developments in computational techniques, Data-driven Machine Learning Models (DMLs) have shown great potential in simulating streamflow and capturing the rainfall-runoff relationship in given watersheds, which are traditionally fulfilled by Process-based Hydrologic Models (PHMs). There are debates on whether the DMLs can outperform and possibly replace the classical PHMs for streamflow simulation and river forecasting, but no clear conclusions have been made. This study aims to investigate whether the newer DMLs have any potential in further improving the simulation accuracy of classical PHMs, and vice versa. To do this, we compared a few popular PHMs and DMLs over four watersheds across the Continental US (CONUS) that are associated with different input, climate, and regional conditions. A total of five hydrologic models were chosen, including (1) two classical lumped models, i.e., the Sacramento Soil Moisture Accounting (SAC-SMA) and Xinanjiang (XAJ); (2) one modern distributed model, termed Coupled Routing and Excess Storage (CREST); (3) and two DMLs including an Artificial Neural Networks (ANN) and a deep learning model, termed Long Short Term Memory (LSTM). Our results demonstrated that the DMLs still significantly biased when using the baseline input scenario with the PHMs. However, the DMLs fed with delayed input scenarios had great potential and can reach high simulation accuracy. The DMLs, especially the ANN, outperformed other employed models under the rainfall-runoff relationship in which rainfall dominantly drives. Furthermore, the DMLs also showed better performance in the high-flow regime, while the PHMs had a better performance for the low-flow regime, implying both PHMs and DMLs have their own merits and are worthy of joint development. In general, our study indicated a great potential of using DMLs to simulate streamflow, but further studies are still needed to verify the transferability and scalability of DMLs in large-scale experiments, such as the Distributed Model Intercomparison Projects 1&2 conducted by National Weather Services but to compare modern DMLs and PHMs.

58 GEOSCIENCES↗
DOE OSTI2015

A model for dark matter, naturalness and a complete gauge unification

We consider dark matter in a minimal extension of the Standard Model (SM) which breaks electroweak symmetry dynamically and leads to a complete unification of the SM and technicolor coupling constants. The unification scale is determined to be M{sub U}≈2.2×10{sup 15} GeV and the unified coupling α{sub U}≈0.0304. Moreover, unification strongly suggest that the technicolor sector of the model must become strong at the scale of O(TeV). The model also contains a tightly constrained sector of mixing neutral fields stabilized by a discrete symmetry. We find the lightest of these states can be DM with a mass in the range m{sub DM}≈30–800 GeV. We find a large set of parameters that satisfy all available constraints from colliders and from dark matter search experiments. However, most of the available parameter space is within the reach of the next generation of DM search experiments. The model is also sensitive to a modest improvement in the measurement of the precision electroweak parameters.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

From deep TLS validation to ensembles of atomic models built from elemental motions

Procedures are described for extracting the vibration and libration parameters corresponding to a given set of TLS matrices and their simultaneous validation. Knowledge of these parameters allows the generation of structural ensembles corresponding to these matrices. The translation–libration–screw model first introduced by Cruickshank, Schomaker and Trueblood describes the concerted motions of atomic groups. Using TLS models can improve the agreement between calculated and experimental diffraction data. Because the T, L and S matrices describe a combination of atomic vibrations and librations, TLS models can also potentially shed light on molecular mechanisms involving correlated motions. However, this use of TLS models in mechanistic studies is hampered by the difficulties in translating the results of refinement into molecular movement or a structural ensemble. To convert the matrices into a constituent molecular movement, the matrix elements must satisfy several conditions. Refining the T, L and S matrix elements as independent parameters without taking these conditions into account may result in matrices that do not represent concerted molecular movements. Here, a mathematical framework and the computational tools to analyze TLS matrices, resulting in either explicit decomposition into descriptions of the underlying motions or a report of broken conditions, are described. The description of valid underlying motions can then be output as a structural ensemble. All methods are implemented as part of the PHENIX project.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Most theoretical approaches used in nuclear astrophysics to model the nucleosynthesis of heavy elements incorporate the so-called statistical model in order to describe the excitation and decay properties of atomic nuclei. One of the basic assumptions of this model is the validity of the Brink–Axel hypothesis and the related concept of so-called photon strength functions to describe γ-ray transition probabilities. We present a novel experimental approach that allows for the first time to experimentally determine the photon strength function simultaneously in two independent ways by a unique combination of quasi-monochromatic photon beams and a newly implemented γ–γ coincidence setup. This technique does not assume a priori the validity of the Brink–Axel hypothesis and sets a benchmark in terms of the detection sensitivity for measuring decay properties of photo-excited states below the neutron separation energy. The data for the spherical off-shell nucleus 128 Te were obtained for γ-ray beam-energy settings between 3 MeV and 9 MeV in steps of 130 keV for the lower beam energies and in steps of up to 280 keV for the highest beam settings. We present a quantitative analysis on the consistency of the derived photon strength function with the Brink–Axel hypothesis. The data clearly demonstrate a discrepancy of up to a factor of two between the photon strength functions extracted from the photoabsorption and photon emission process, respectively. In addition, we observe that the photon strength functions are not independent of the excitation energy, as usually assumed. Thus, we conclude, that the Brink–Axel hypothesis is not strictly fulfilled in the excitation-energy region below the neutron separation threshold (S n = 8.78 MeV) for the studied case of 128 Te.

Not Available

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Evaluation of convection‐permitting model simulations of cloud populations associated with the Madden‐Julian Oscillation using data collected during the AMIE/DYNAMO field campaign

Abstract Regional convection‐permitting model simulations of cloud populations observed during the 2011 Atmospheric Radiation Measurement (ARM) Madden‐Julian Oscillation Investigation Experiment/Dynamics of the Madden‐Julian Oscillation Experiment (AMIE/DYNAMO) field campaign are evaluated against ground‐based radar and ship‐based observations. Sensitivity of model simulated reflectivity, surface rain rate, and cold pool statistics to variations of raindrop breakup/self‐collection parameters in four state‐of‐the‐art two‐moment bulk microphysics schemes in the Weather Research and Forecasting (WRF) model is examined. The model simulations generally overestimate reflectivity from large and deep convective cells, and underestimate stratiform rain and the frequency of cold pools. In the sensitivity experiments, introduction of more aggressive raindrop breakup or decreasing the self‐collection efficiency increases the cold pool occurrence frequency in all of the simulations, and slightly reduces the reflectivity and precipitation statistics bias in some schemes but has little effect on the overall mean surface precipitation. Both the radar observations and model simulations of cloud populations show an approximate power law relationship between convective echo‐top height and equivalent convective cell radius.

Hagos, Samson↗
DOE OSTI2017

A climate model projection weighting scheme accounting for performance and interdependence: Model Projection Weighting Scheme

Uncertainties of climate projections are routinely assessed by considering simulations from different models. Observations are used to evaluate models, yet there is a debate about whether and how to explicitly weight model projections by agreement with observations. Here we present a straightforward weighting scheme that accounts both for the large differences in model performance and for model interdependencies, and we test reliability in a perfect model setup. We provide weighted multimodel projections of Arctic sea ice and temperature as a case study to demonstrate that, for some questions at least, it is meaningless to treat all models equally. The constrained ensemble shows reduced spread and a more rapid sea ice decline than the unweighted ensemble. We argue that the growing number of models with different characteristics and considerable interdependence finally justifies abandoning strict model democracy, and we provide guidance on when and how this can be achieved robustly.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

A Taylor Expansion-Based Adaptive Design Strategy for Global Surrogate Modeling With Applications in Groundwater Modeling

Global sensitivity analysis (GSA) and uncertainty quantification (UQ) for groundwater modeling are challenging because of the model complexity and significant computational requirements. To reduce the massive computational cost, a cheap-to-evaluate surrogate model is usually constructed to approximate and replace the expensive groundwater models in the GSA and UQ. Constructing an accurate surrogate requires actual model simulations on a number of parameter samples. Thus, a robust experimental design strategy is desired to locate informative samples so as to reduce the computational cost in surrogate construction and consequently to improve the efficiency in the GSA and UQ. In this study, we develop a Taylor expansion-based adaptive design (TEAD) that aims to build an accurate global surrogate model with a small training sample size. TEAD defines a novel hybrid score function to search informative samples, and a robust stopping criterion to terminate the sample search that guarantees the resulted approximation errors satisfy the desired accuracy. The good performance of TEAD in building global surrogate models is demonstrated in seven analytical functions with different dimensionality and complexity in comparison to two widely used experimental design methods. The application of the TEAD-based surrogate method in two groundwater models shows that the TEAD design can effectively improve the computational efficiency of GSA and UQ for groundwater modeling.

58 GEOSCIENCES↗
DOE OSTI2025

Enhancing occupant behavior representation for interoperability between building information modeling and building energy modeling

Building Performance Simulation (BPS) has been adopted as an essential tool for designing, operating, and retrofitting buildings to optimize energy efficiency throughout the building life cycle. The Green Building XML (gbXML) schema facilitates seamless data exchange between Building Information Modeling (BIM) and Building Energy Modeling (BEM) software tools. However, limited occupant behavior (OB) representation in BIM often leads to inconsistent and inaccurate energy simulation in BEM software. This paper presents 154 systematic enhancements to the existing occupant behavior XML (obXML) schema v1.3.4, initially developed for standardizing OB representation for BEM, to address existing limitations and improve interoperability with BIM models. The enhancements encompass improved integration with BIM models through extended building representations and system operations, expanded support for advanced OB models with additional environmental parameters and mathematical capabilities, and implementation of a standardized model documentation framework. To facilitate seamless data transformation between gbXML and obXML schemas, we developed a publicly available gb-obXML Schema Converter. Three case studies demonstrate the enhanced schema’s capabilities: representation of building information using a two-story office building model, documentation of a window operation behavior model, and validation of the schema converter’s functionality. The enhanced obXML schema v1.4 enables sophisticated modeling of occupant-building interactions while maintaining consistency with industry-standard BIM schemas. The standardized documentation framework facilitates reproducibility and knowledge sharing in the OB research community, while the schema converter automates the integration of building information into OB simulation workflows. These enhancements establish a foundation for more accurate building performance simulation by supporting sophisticated representation of occupant behavior within the BIM-to-BEM simulation workflows.

Chung, Jihoon↗
DOE OSTI2015

Knowledge brokering on emissions modelling in Strategic Environmental Assessment of Estonian energy policy with special reference to the LEAP model

Strategic Environmental Assessment (SEA) serves as a platform for bringing together researchers, policy developers and other stakeholders to evaluate and communicate significant environmental and socio-economic effects of policies, plans and programmes. Quantitative computer models can facilitate knowledge exchange between various parties that strive to use scientific findings to guide policy-making decisions. The process of facilitating knowledge generation and exchange, i.e. knowledge brokerage, has been increasingly explored, but there is not much evidence in the literature on how knowledge brokerage activities are used in full cycles of SEAs which employ quantitative models. We report on the SEA process of the national energy plan with reflections on where and how the Long-range Energy Alternatives Planning (LEAP) model was used for knowledge brokerage on emissions modelling between researchers and policy developers. Our main suggestion is that applying a quantitative model not only in ex ante, but also ex post scenario modelling and associated impact assessment can facilitate systematic and inspiring knowledge exchange process on a policy problem and capacity building of participating actors. - Highlights: • We examine the knowledge brokering on emissions modelling between researchers and policy developers in a full cycle of SEA. • Knowledge exchange process can evolve at any modelling stage within SEA. • Ex post scenario modelling enables systematic knowledge exchange and learning on a policy problem.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Enhancement of phase change material hysteresis model: A case study of modeling building envelope in EnergyPlus

Nowadays, buildings are expected to offer demand side services to the power grid to enhance the electrical load flexibility, which leads to the concepts of grid-interactive efficient buildings (GEBs). Phase change material (PCM)-based thermal energy storage has seen increasing attention in recent years for peak load shifting of grid-interactive efficient buildings (GEBs). Numerical models are critical tools for design and evaluation of PCM-integrated systems. Most industrial-grade PCMs are reported to melt/freeze over a temperature range instead of at a unique temperature. Such thermal hysteresis effect significantly affects the reliability of simulation results because not only the heat transfer process depends on melting and freezing temperatures, the PCM thermal properties change significantly during the phase change process as well. This study is aimed to develop a model for the PCMs used in the building envelope with the capability to accurately simulate hysteretic behaviors. Further, this model is based on a two-phase assumption and is implemented in a whole building energy performance simulation program (i.e., EnergyPlus). A comparison between numerical results and experimental data shows that during a complete phase transition, the two-phase model could achieve a good agreement with the experimental data. During a partial phase transition, the two-phase model could lead to significant improvements compared to other alternative PCM models, including the existing PCM model in EnergyPlus. Last, whole building simulations were performed to study this model's performance regarding heating/cooling loads and zone mean air temperature of a given building. The results show that the difference in hourly heating/cooling loads introduced by the models was less than 1% in design conditions, while significant changes were observed in both hourly heating/cooling loads and zone mean air temperature when the PCM envelope underwent partial phase transition processes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗