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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Estimating building simulation parameters via Bayesian structure learning

Many key building design policies are made using sophisticated computer simulations such as EnergyPlus (E+), the DOE flagship whole-building energy simulation engine. E+ and other sophisticated computer simulations have several major problems. The two main issues are 1) gaps between the simulation model and the actual structure, and 2) limitations of the modeling engine's capabilities. Currently, these problems are addressed by having an engineer manually calibrate simulation parameters to real world data or using algorithmic optimization methods to adjust the building parameters. However, some simulations engines, like E+, are computationally expensive, which makes repeatedly evaluating the simulation engine costly. This work explores addressing this issue by automatically discovering the simulation's internal input and output dependencies from ~20 Gigabytes of E+ simulation data, future extensions will use ~200 Terabytes of E+ simulation data. The model is validated by inferring building parameters for E+ simulations with ground truth building parameters. Our results indicate that the model accurately represents parameter means with some deviation from the means, but does not support inferring parameter values that exist on the distribution's tail.

Edwards, Richard E.↗
DOE OSTI2013

Estimating Building Simulation Parameters via Bayesian Structure Learning

Many key building design policies are made using sophisticated computer simulations such as EnergyPlus (E+), the DOE flagship whole-building energy simulation engine. E+ and other sophisticated computer simulations have several major problems. The two main issues are 1) gaps between the simulation model and the actual structure, and 2) limitations of the modeling engine's capabilities. Currently, these problems are addressed by having an engineer manually calibrate simulation parameters to real world data or using algorithmic optimization methods to adjust the building parameters. However, some simulations engines, like E+, are computationally expensive, which makes repeatedly evaluating the simulation engine costly. This work explores addressing this issue by automatically discovering the simulation's internal input and output dependencies from 20 Gigabytes of E+ simulation data, future extensions will use 200 Terabytes of E+ simulation data. The model is validated by inferring building parameters for E+ simulations with ground truth building parameters. Our results indicate that the model accurately represents parameter means with some deviation from the means, but does not support inferring parameter values that exist on the distribution's tail.

Energy Modeling↗
DOE OSTI2013

Resilient Plant Monitoring System: Design, Analysis, and Performance Evaluation

Resilient monitoring systems are sensor networks that degrade gracefully under malicious attacks on their sensors, causing them to project misleading information. The goal of this paper is to design, analyze, and evaluate the performance of a resilient monitoring system intended to monitor plant conditions (normal or anomalous). The architecture developed consists of four layers: data quality assessment, process variable assessment, plant condition assessment, and sensor network adaptation. Each of these layers is analyzed by either analytical or numerical tools, and the performance of the overall system is evaluated using simulations. The measure of resiliency of the resulting system is evaluated using Kullback Leibler divergence, and is shown to be sufficiently high in all scenarios considered.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Integrated Transmission and Distribution Co-Simulation Platform for Demonstration of Bulk Grid Services Using Distributed Energy Resources

In September 2020, the Federal Energy Regulatory Commission (FERC) released Order 2222, which opens wholesale markets to small-capacity distributed energy resources (DERs), recognizing their potential in improving operational efficiency by providing bulk grid services. Therefore, a co-simulation capability that can connect transmission and distribution (T&D) simulations and evaluate the impacts of DER provision of bulk grid services is needed. In this paper, we present a new integrated T&D co-simulation platform that incorporates T&D system simulators, DER aggregator/group strategies, and a co-simulation coordinator. Industry-standard communication protocols are employed to mimic real-world conditions. Secondary frequency regulation is selected as the representative bulk grid service, and we simulate the responses of DERs to the frequency regulation signals. The simulation results for a solar-rich distribution feeder in Colorado, USA, demonstrate how the T&D co-simulation setup is used to evaluate the contributions of DERs to minimize the bulk grid frequency deviation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Rancor-HUNTER: A Virtual Plant and Operator Environment for Predicting Human Performance

Advances in simulation capabilities to model physical systems have outpaced the development of simulations for humans using those physical systems. There is an argument that the infinite span of potential human behaviors inherently render human modeling more challenging than physical systems. Despite this challenge, the need for modeling humans interacting with these complex systems is paramount. As technologies have improved, many of the failure modes originating from the physical systems have been solved. This means the overall proportion of human errors has increased, such that it is not uncommon to be the primary driver of system failure in modern complex systems. Moreover, technologies such as automated systems may introduce emerging contexts that can cause new, unanticipated modes of human error. Therefore, it is now more important than ever to develop models of human behavior to realize overall system error reductions and achieve established safety margins. To support new and novel concepts of operations for the anticipated wave of advanced nuclear reactor deployments, human factors and human reliability analysis researchers need to develop advanced simulation-based approaches. This talk presents a simulation environment suitable to both collect data and then perform Monte Carlo simulations to evaluate human performance and develop better models of human behavior. Specifically, the Rancor Microworld Simulator models a complex energy production system in a simplified manner. Rancor includes computer-based procedures, which serve as a framework to automatically classify human behaviors without manual, subjective experimenter coding during scenarios. This method supports a detailed level of analysis at the task level. It is feasible for collecting large sample sizes required to develop quantitative modelling elements that have historically challenged traditional full-scope simulator study approaches. Additionally, the other portion of this experimental platform, the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER), is presented to show how the collected data can be used to evaluate novel scenarios based on the contextual factors, or performance shaping factors, derived from Rancor simulations. Rancor-HUNTER is being used to predict operator performance with new procedures, such as results from control room modernization or new-build situations. Rancor-HUNTER is also proving a useful surrogate platform to model human performance for other complex systems.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2018

A hydrological emulator for global applications – HE v1.0.0

Abstract. While global hydrological models (GHMs) are very useful in exploring water resources and interactions between the Earth and human systems, their use often requires numerous model inputs, complex model calibration, and high computation costs. To overcome these challenges, we construct an efficient open-source and ready-to-use hydrological emulator (HE) that can mimic complex GHMs at a range of spatial scales (e.g., basin, region, globe). More specifically, we construct both a lumped and a distributed scheme of the HE based on the monthly abcd model to explore the tradeoff between computational cost and model fidelity. Model predictability and computational efficiency are evaluated in simulating global runoff from 1971 to 2010 with both the lumped and distributed schemes. The results are compared against the runoff product from the widely used Variable Infiltration Capacity (VIC) model. Our evaluation indicates that the lumped and distributed schemes present comparable results regarding annual total quantity, spatial pattern, and temporal variation of the major water fluxes (e.g., total runoff, evapotranspiration) across the global 235 basins (e.g., correlation coefficient r between the annual total runoff from either of these two schemes and the VIC is >0.96), except for several cold (e.g., Arctic, interior Tibet), dry (e.g., North Africa) and mountainous (e.g., Argentina) regions. Compared against the monthly total runoff product from the VIC (aggregated from daily runoff), the global mean Kling–Gupta efficiencies are 0.75 and 0.79 for the lumped and distributed schemes, respectively, with the distributed scheme better capturing spatial heterogeneity. Notably, the computation efficiency of the lumped scheme is 2 orders of magnitude higher than the distributed one and 7 orders more efficient than the VIC model. A case study of uncertainty analysis for the world's 16 basins with top annual streamflow is conducted using 100 000 model simulations, and it demonstrates the lumped scheme's extraordinary advantage in computational efficiency. Our results suggest that the revised lumped abcd model can serve as an efficient and reasonable HE for complex GHMs and is suitable for broad practical use, and the distributed scheme is also an efficient alternative if spatial heterogeneity is of more interest.

Liu, Yaling↗
DOE OSTI2019

Evaluation of Combustion Models for CFD Simulation of Pre-Chamber Ignition in a Natural Gas Engine

Natural gas is considered an attractive alternative fossil fuel as it produces 25% less carbon dioxide and emits fewer amounts of toxic pollutants compared to gasoline and diesel. A pre-chamber type ignition device in a natural gas engine is capable of extending the lean operating limit, and hence improving thermal efficiency, by providing spatially distributed ignition with multiple turbulent flame-jets and accelerating the combustion rate. However, the process of ignition in the main chamber triggered by turbulent jets emanating from a pre-chamber is very sensitive to the pre-chamber geometry and fueling strategy, and any effort to optimize these parameters requires fundamental understanding of the underlying physical and thermodynamic phenomena, which can be studied by a multi-dimensional numerical simulation approach. In this study, three turbulent combustion models widely adopted in the multi-dimensional engine modeling community were preliminary evaluated to simulate the combustion process in a natural gas engine with a pre-chamber spark-ignition system. One multi-zone well-stirred reactor model, and two flamelet-based combustion models, G-equation and Extended Coherent Flamelet Model, were employed for this assessment. Under a fuel-lean condition, the three combustion models were used to match experimental data and analyze the differences in terms of in-cylinder pressure and heat release rate.

combustion model evaluation↗
DOE OSTI2018

Impacts of anthropogenic aerosols on fog in North China Plain

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

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A Theory for the Response of Tropical Moist Convection to Mechanical Orographic Forcing

Abstract Spatial patterns of tropical rainfall are strongly influenced by mountains. Although theories for precipitation induced by convectively stable upslope ascent exist for the midlatitudes, these do not represent the interaction of moist convection with orographic forcing. Here, we present a theory for convective precipitation produced by the mechanical interaction of a tropical ridge with a basic-state horizontal wind. Deviations from this basic state are represented as the sum of a “dry” perturbation, due to the stationary orographic gravity wave, and a “moist” perturbation that carries the convective response. The moist component dynamics are subject to the weak temperature gradient approximation; they are forced by the dry mode’s influence on lower-tropospheric moisture and temperature. Analytical solutions provide estimates of the precipitation distribution, including peak precipitation, upstream extent, and rain shadow extent. The theory can be used with several degrees of complexity depending on the technique used to compute the dry mode, which can be drawn from linear mountain wave theory or full numerical simulations. To evaluate the theory, we use a set of convection-permitting simulations with a flow-perpendicular ridge in a long channel. The theory makes a good prediction for the cross-slope precipitation profile, indicating that the organization of convective rain by orography can be quantitatively understood by considering the effect of stationary orographic gravity waves on a lower-tropospheric convective quasi-equilibrium state.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Hawaiian Electric Companies Demand Response Tool

This document introduces the Hawaiian Electric Companies Demand Response Tool, which was developed at the Pacific Northwest National Laboratory. The battery storage evaluation tool by PNNL was modified to run one-year simulations that evaluate the benefits of behind-the-meter behind-the-meter photovoltaics and storage from the customer perspective, while optimizing use of these assets to minimize customer energy bills and improve reliability.

14 SOLAR ENERGY↗
DOE OSTI2014

Fracture Propagation, Fluid Flow, and Geomechanics of Water-Based Hydraulic Fracturing in Shale Gas Systems and Electromagnetic Geophysical Monitoring of Fluid Migration

We investigate fracture propagation induced by hydraulic fracturing with water injection, using numerical simulation. For rigorous, full 3D modeling, we employ a numerical method that can model failure resulting from tensile and shear stresses, dynamic nonlinear permeability, leak-off in all directions, and thermo-poro-mechanical effects with the double porosity approach. Our numerical results indicate that fracture propagation is not the same as propagation of the water front, because fracturing is governed by geomechanics, whereas water saturation is determined by fluid flow. At early times, the water saturation front is almost identical to the fracture tip, suggesting that the fracture is mostly filled with injected water. However, at late times, advance of the water front is retarded compared to fracture propagation, yielding a significant gap between the water front and the fracture top, which is filled with reservoir gas. We also find considerable leak-off of water to the reservoir. The inconsistency between the fracture volume and the volume of injected water cannot properly calculate the fracture length, when it is estimated based on the simple assumption that the fracture is fully saturated with injected water. As an example of flow-geomechanical responses, we identify pressure fluctuation under constant water injection, because hydraulic fracturing is itself a set of many failure processes, in which pressure consistently drops when failure occurs, but fluctuation decreases as the fracture length grows. We also study application of electromagnetic (EM) geophysical methods, because these methods are highly sensitive to changes in porosity and pore-fluid properties due to water injection into gas reservoirs. Employing a 3D finite-element EM geophysical simulator, we evaluate the sensitivity of the crosswell EM method for monitoring fluid movements in shaly reservoirs. For this sensitivity evaluation, reservoir models are generated through the coupled flow-geomechanical simulator and are transformed via a rock-physics model into electrical conductivity models. It is shown that anomalous conductivity distribution in the resulting models is closely related to injected water saturation, but not closely related to newly created unsaturated fractures. Our numerical modeling experiments demonstrate that the crosswell EM method can be highly sensitive to conductivity changes that directly indicate the migration pathways of the injected fluid. Accordingly, the EM method can serve as an effective monitoring tool for distribution of injected fluids (i.e., migration pathways) during hydraulic fracturing operations

02 PETROLEUM↗
DOE OSTI2024

Evaluation of RANS vs. LES simulation of fluid flow through 3 × 3 rod bundle with a simple spacer grid as a precursor to coupled fluid–structure interaction simulations

The research literature on Computational Fluid Dynamics (CFD) of coolant flow through rod bundles with spacer-grids and mixing vanes is replete, ranging from high fidelity Large Eddy Simulation (LES)/Direct Numerical Simulation (DNS) simulations to Reynolds-Averaged Navier–Stokes (RANS) modeled studies. The mixing of flow between subchannels and the pressure drop through the bundle are fundamental quantities useful for comparing and evaluating CFD methods. Less commonly observed and compared are the forces exerted onto the structure by the fluid. The present study seeks to evaluate the use of RANS simulations for predicting the structural response to fluid flow. Wall resolved RANS simulations are benchmarked against LES simulations of fluid flow at a Reynolds number of 15,000 through a 3 × 3 fuel rod bundle with a simple spacer grid. Velocity line-plots are compared showing good agreement between RANS and LES results, ascertaining that the former is capable of capturing the essential time-averaged velocity profile. Additionally, the distribution of forces on the spacer grid and fuel rods are collected as a function of time and space. The RANS methods are evaluated using the frequency and magnitude of the fluctuating forces on various portions of the structure as compared to LES. In conclusion, the power spectral density evaluation of the models reveal underprediction of force amplitude on the rod walls by RANS and also discrepancy in the prediction of high frequency spectra, especially in the immediate vicinity of spacer-grid structure, which may be attributed to the lack of random turbulence fluctuation or insufficient modeling of small-scale eddies in RANS simulation.

FIV↗
DOE OSTI2024

Evaluation of neutron dosimetry capabilities with the MC-15 portable multiplicity counter

This work proposes a preliminary neutron dose rate estimation method for a neutron multiplicity detector through measurement- and simulation-based analyses. Uncharacterized neutron-emitting sources may be encountered in situations such as nuclear emergency response, safeguards, and treaty verification. These circumstances may present irradiation risk to personnel conducting field assay, search, and characterization measurements. It is therefore of interest to provide a field neutron dosimetry capability with the existing neutron multiplicity counting (NMC) capabilities. To date, no commercially-available neutron detection systems are capable of both accurate NMC and real-time neutron dosimetry. This work will focus on estimating dose rate using input from a single fielded NMC called the MC-15. The energy-dependent neutron detection efficiency response of the MC-15 was quantified in monoenergetic neutron simulations and evaluated in response to two neutron-emitting sources and to a polyethylene-moderated source. The results were compared to existing neutron dosimeters and established the proof of concept for further investigation of the MC-15 for dose estimation. Measurement results were also replicated in simulations; additional simulations were then conducted to expand upon the limited empirical data. The initial empirical results provided a conversion factor appropriate for use when measuring 252 Cf neutrons that is independent of polyethylene shielding presence and thickness. The simulated data sets were then used to evaluate a fit equation allowing estimation of the neutron dose rate for less restricted geometric configurations and dependent only on the distance between the source and the detector. Additionally, the energy dependence of the efficiency response indicates that further empirical evaluations could provide energy-dependent conversion factors for broader neutron dosimetry capabilities with a wider range of neutron-emitting sources.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

The coastal streamflow flux in the Regional Arctic System Model

The coastal streamflow flux from the Arctic drainage basin is an important driver of dynamics in the coupled ice-ocean system. Comprising more than one third of the total freshwater flux into the Arctic Ocean, streamflow is a key component of the regional and global freshwater cycle. To better represent the coupling of the streamflow flux to the ocean, we have developed and applied the RVIC streamflow routing model within the Regional Arctic System Model (RASM). The RASM is a high-resolution regional Earth System Model whose domain includes all of the Arctic drainage basin. Here in this paper, we introduce the RVIC streamflow routing model, detailing its application within RASM and its advancements in terms of representing high-resolution streamflow processes. We evaluate model simulated streamflow relative to in situ observations and demonstrate a method for improving model performance using a simple optimization procedure. We also present a new, spatially and temporally consistent, high-resolution data set of coastal freshwater fluxes for the Arctic drainage basin and surrounding areas that is based on a fully coupled RASM simulation and intended for use in Arctic Ocean modeling applications. This data set is evaluated relative to other coastal streamflow data sets commonly used by the ocean modeling community. We demonstrate that the RASM-simulated streamflow flux better represents the annual cycle than existing data sets, especially in ungauged areas. Finally, we assess the impact that streamflow has on the coupled ice-ocean system, finding that the presence of streamflow leads to reduced sea surface salinity, increased sea surface temperatures, and decreased sea ice thickness.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Implementation of a generalized actuator disk wind turbine model into the weather research and forecasting model for large-eddy simulation applications

A generalized actuator disk (GAD) wind turbine parameterization designed for large-eddy simulation (LES) applications was implemented into the Weather Research and Forecasting (WRF) model. WRF-LES with the GAD model enables numerical investigation of the effects of an operating wind turbine on and interactions with a broad range of atmospheric boundary layer phenomena. Numerical simulations using WRF-LES with the GAD model were compared with measurements obtained from the Turbine Wake and Inflow Characterization Study (TWICS-2011), the goal of which was to measure both the inflow to and wake from a 2.3-MW wind turbine. Data from a meteorological tower and two light-detection and ranging (lidar) systems, one vertically profiling and another operated over a variety of scanning modes, were utilized to obtain forcing for the simulations, and to evaluate characteristics of the simulated wakes. Simulations produced wakes with physically consistent rotation and velocity deficits. Two surface heat flux values of 20 W m –2 and 100 W m –2 were used to examine the sensitivity of the simulated wakes to convective instability. Simulations using the smaller heat flux values showed good agreement with wake deficits observed during TWICS-2011, whereas those using the larger value showed enhanced spreading and more-rapid attenuation. This study demonstrates the utility of actuator models implemented within atmospheric LES to address a range of atmospheric science and engineering applications. In conclusion, validated implementation of the GAD in a numerical weather prediction code such as WRF will enable a wide range of studies related to the interaction of wind turbines with the atmosphere and surface.

17 WIND ENERGY↗
DOE OSTI2016

Dakota Uncertainty Quantification Methods Applied to the CFD code Nek5000

This report presents the state of advancement of a Nuclear Energy Advanced Modeling and Simulation (NEAMS) project to characterize the uncertainty of the computational fluid dynamics (CFD) code Nek5000 using the Dakota package for flows encountered in the nuclear engineering industry. Nek5000 is a high-order spectral element CFD code developed at Argonne National Laboratory for high-resolution spectral-filtered large eddy simulations (LESs) and unsteady Reynolds-averaged Navier-Stokes (URANS) simulations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2013

Real-Time Prediction of Power System Frequency in FNET: A State Space Approach

This paper proposes a novel approach to predict power frequency by applying a state-space model to describe the time-varying nature of power systems. It introduces the Expectation maximization (EM) and prediction error minimization (PEM) algorithms to dynamically estimate the parameters of the model. This paper discusses how the proposed models can be used to ensure the efficiency and reliability of power systems in Frequency Monitoring Network (FNET), if serious frequency fluctuation or measurement failure occur at some nodes; this is achieved without requiring the exact model of complex power systems. Our approach leads to an easy online implementation with high precision and short response time that are key to effective frequency control. We randomly pick a set of frequency data for one power station in FNET and use it to estimate and predict the power frequency based on past measurements. Several computer simulations are provided to evaluate the method. Simulation results showed that the proposed technique could achieve good performance regarding the frequency monitoring with very limited measurement input information.

Djouadi, Seddik M↗
DOE OSTI2014

Assessing the CAM5 Physics Suite in the WRF-Chem Model: Implementation, Resolution Sensitivity, and a First Evaluation for a Regional Case Study

A suite of physical parameterizations (deep and shallow convection, turbulent boundary layer, aerosols, cloud microphysics, and cloud fraction) from the global climate model Community Atmosphere Model version 5.1 (CAM5) has been implemented in the regional model Weather Research and Forecasting with chemistry (WRF-Chem). A downscaling modeling framework with consistent physics has also been established in which both global and regional simulations use the same emissions and surface fluxes. The WRF-Chem model with the CAM5 physics suite is run at multiple horizontal resolutions over a domain encompassing the northern Pacific Ocean, northeast Asia, and northwest North America for April 2008 when the ARCTAS, ARCPAC, and ISDAC field campaigns took place. These simulations are evaluated against field campaign measurements, satellite retrievals, and ground-based observations, and are compared with simulations that use a set of common WRF-Chem Parameterizations. This manuscript describes the implementation of the CAM5 physics suite in WRF-Chem provides an overview of the modeling framework and an initial evaluation of the simulated meteorology, clouds, and aerosols, and quantifies the resolution dependence of the cloud and aerosol parameterizations. We demonstrate that some of the CAM5 biases, such as high estimates of cloud susceptibility to aerosols and the underestimation of aerosol concentrations in the Arctic, can be reduced simply by increasing horizontal resolution. We also show that the CAM5 physics suite performs similarly to a set of parameterizations commonly used in WRF-Chem, but produces higher ice and liquid water condensate amounts and near-surface black carbon concentration. Further evaluations that use other mesoscale model parameterizations and perform other case studies are needed to infer whether one parameterization consistently produces results more consistent with observations.

CAM5 physics suite↗