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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Thermodynamic Modeling of Heat Engines Including Heat Transfer and Compression–Expansion Irreversibilities

In this paper, a thermodynamic model based on an endoreversible engine approach is developed to analyze the performance of heat engines operating under different thermodynamic cycles. The model considers finite heat transfer rate, variable heat source and sink temperatures, and irreversibilities associated with the expansion and compression. Expressions for the maximum power and efficiency at maximum power output are obtained as a function of hot and cold reservoir temperatures, the equivalent isentropic efficiency of compression and expansion components, and the effective conductance ratio between heat exchangers. In all cases, the Curzon–Ahlborn efficiency is retrieved at constant reservoir temperatures and neglected compression–expansion irreversibilities. The proposed model allows assessing the effect of isentropic efficiencies and heat exchanger design and operation characteristics for different thermodynamic cycles.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Quantification of Uncertainty in Extreme Scale Computations (QUEST)

QUEST was a SciDAC Institute comprising Sandia National Laboratories, Los Alamos National Laboratory, the University of Southern California, the Massachusetts Institute of Technology, the University of Texas at Austin, and Duke University. The mission of QUEST is to: (1) develop a broad class of uncertainty quantification (UQ) methods/tools, and (2) provide UQ expertise and software to other SciDAC projects, thereby enabling/guiding their UQ activities. The USC effort centered on the development of reduced models and efficient algorithms for implementing various components of the UQ pipeline. USC personnel were responsible for the development of adaptive bases, adaptive quadrature, and reduced models to be used in estimation and inference.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Hybrid Cyber-attack Detection in Photovoltaic Farms

Here, to address the cyber-physical security in PV farms, a hybrid cyber-attack detection is proposed in this manuscript. To secure PV farms, the proposed method integrates model-based and data-driven methods by fusing the detection score at the device and system levels. First, a model-based cyber-attack detection method is developed for each PV inverter. A residual between the estimation of the Kalman filter and measurement is calculated. By leveraging the calculated residual from all inverters, a squared Mahalanobis distance is developed for device detection score generation. At the system level, a convolutional neural network (CNN) is proposed to detect cyber-attack using the waveform data at the point of common coupling (PCC) in PV farms. To improve the CNN detection accuracy, a set of well-designed features are extracted from the raw waveform data. Finally, a weighted detection score fusion method is proposed to combine device and system detection scores by using their complementary strength. The feasibility and robustness of the proposed method are validated by testing cases and a comparative experiment.

14 SOLAR ENERGY↗
DOE OSTI2018

Model-Based Air Flow Path Optimization of Heat Pump Clothes Dryer

A heat pump clothes dryer (HPCD) uses a vapor compression system to dry clothes. The condenser heats air, which passes through the drum to evaporate moisture out of the clothes, and the evaporator condenses water out of the air stream. As a result, the HPCD can achieve 50% energy savings compared to a conventional electric resistance dryer. In this work we developed a physics-based, quasi-steady-state HPCD system model with detailed heat exchanger and compressor models. The system model can simulate the inherently transient HPCD drying process, to size components, and to reveal trends in key variables (e.g. compressor discharge temperature, power consumption, required drying time, etc.) The system model was calibrated using experimental data from a prototype HPCD. Air leakages, in and out, along the closed air circulation path of HPCD cause varied effects on the performance. Understanding the location, magnitude, and direction of air leakage of the heat pump clothes dryer is critical for accurately characterizing the performance and developing a high-performance design. The system model was used to reveal the impacts. In addition, model-based parametric optimizations were conducted to design the HPCD charge inventory, flow rate, air path and leak points for optimum performance.

Shen, Bo↗
DOE OSTI2021

The interpenetration polymer network in a cement paste–waterborne epoxy system

The formation of the interpenetrating polymer network (IPN) structure within the cement-polymer system has been revealed by experiments from 2 dimensional to 3-dimensional scales. However, the microstructure design and performance prediction of IPN as a function of specific C-S-H/polymer components or ingredients' parameters e.g. water to cement ratios (w/c), polymer to cement ratios (p/c), monomer components, degree of polymerization (DP), etc. is by far not available. Here we developed a mesoscale model for IPN visualization based on the Flory-Huggins interaction theory which was applied to cement science for the first time. All the ingredients in the micro-structure were considered as soluble beads with rational sizes based on their properties obtained by molecular dynamic methods. The interaction parameters of each bead were then determined based on their element ratios and chemical backbones. The model was validated with the waterborne epoxy-cement material (WECM) in which a novel waterborne epoxy resin (WEP) was prepared and impregnated. The verification results on the 2D-3D scale show that the developed model predicts the WECM's IPN structures by rule and line concerning DP, w/c, and p/c in the mixture. The C-S-H beads were progressively scaled in size which alters the C-S-H texture to have completely different dissolution characteristics. Beads of diameter ~6 Å are more unstable and soluble which enable them to form a continuous phase in water or a composite structure with WEP. In contrast, beads with diameters larger than 10 Å have different properties with stronger nucleation effects. The results also suggest the impregnation content of WEP in cement-based material should be limited to 10% vol. to prevent the polymer IPN from decomposing into discrete clusters. The application of Flory-Huggins theory in cement-based composites demonstrates great potential in performance prediction and microstructure design.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Prediction of softening kinetics and recrystallization texture in non-isothermally annealed bulged tubes using CPFEM and CA models

A hierarchically coupled cellular automata (CA) model, crystal plasticity finite element method (CPFEM), and thermal finite element (FE) model is developed to predict the softening kinetics of the bulged steel tube during non-isothermal annealing. Through the developed model, the kinetics of softening mechanisms including static recovery (SRV) and static recrystallization (SRX), as well as the recrystallization texture are predicted. Later, the Johnson-Mehl-Avrami-Kohnogorov (JMAK) model based on the predicted SRX data is developed to interpret the recrystallization behavior of the material. To perform this study, diverse experimental tests including tube hydroforming (THF), annealing, uniaxial tensile test, hardness test, as well as microstructure observations through optical microscopy and Electron Backscatter Diffraction (EBSD) tests on steel tube are performed. The obtained experimental data are utilized to calibrate and verify the implemented CPFEM model for simulation of THF process, thermal FE model for prediction of the local temperature over annealing time, and CA algorithm for modeling of the softening kinetics and texture evolution throughout the annealing process. The study shows that the predicted deformation characteristics, softening kinetics, recrystallization texture and temperature profile during non-isothermal annealing are in good agreement with experimental data. During the annealing process, a total of four stages for the kinetics of softening mechanisms is observed: No softening; SRV only; SRV dominant; and SRX dominant. During the progress of SRX, the behavior of recrystallization is abruptly changed, confirming that two different mechanisms are controlling the kinetics of transformation.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Prediction of Solar Radiation on Building Rooftops: A Data-Mining Approach

Solar energy technologies offer a clean, renewable, and domestic energy source, and are essential components of a sustainable energy future. The accurate measurement of solar radiation data is essential for optimum site selection of future distributed solar power plants as well as sizing photovoltaic systems. However, solar radiation data are not readily available because measured sequences of radiation values are obtained for a few locations in a country. When the data are available, they are usually at different time periods and spatial scale. The availability of solar radiation data at hourly or daily time scale will enhance the integration of solar energy into electricity generation and promote a sustainable energy future. The ability to generate approximate solar radiation values is often the only practical way to obtain radiation data at hourly or daily time scale. As a result, several models have been developed for estimating solar radiation values based on analytical, numerical simulation, and statistical approaches. However, these models have inherent challenges. We will discuss some of those challenges in this paper. To enhance the prediction of solar radiation values, a novel approach is presented for estimating solar radiation values using support vector machine technique. The approach accounts for unique characteristics that influence solar radiation values. The preliminary results obtained offer useful insights for model enhancements.

machine learning↗
DOE OSTI2017

Simulation and control of a passively cooled small modular reactor Samet - 142

This work regulates a small modular reactor (SMR) with traditional control methodologies and analyzes its response to typical disturbances. An analytical model for the passively cooled NuScale SMR is developed to represent the essential dynamics. The MATLAB/Simulink based model consists of reactor core, steam generator, pressurizer, hot leg riser and downcomer, and turbine representations. The point kinetics equations with a single combined neutron precursor group and the lumped parameter representations with single-phase natural circulation account for the neutronics and thermohydraulics in the reactor core. A lumped parameter, moving-boundary approach forms the basis of the nonlinear model adopted for the once-through helical-coil heat exchangers in which boundaries between regions of different fluid states (i.e., subcooled, boiling, and superheated) vary over time. A proportional-integral-derivative controller employing a sliding-average temperature strategy commonly used for pressurized water reactors is implemented. The responses of the SMR to two different disturbances are analyzed and discussed in detail. For the first scenario, a 5% step increase in the load is applied to the system, which results in a change in the steam valve opening. For comparison, two different simulations under this same disturbance are run: one including and one excluding the control systems. The second scenario tests the effectiveness of the control system to increase (or decrease) the reactor thermal power to a certain level within a desired time period. The simulation results show that important system variables are kept at the desired values by the proposed control strategy. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Thermal Overloading Risk Mitigation With a Semi-Analytical Probabilistic Model on Branch Current

A semi-analytical formulation is presented in this paper for the probability computation of branch current in multiphase systems. The developed formula is derived based on the linear power flow model in rectangular coordinates. The system uncertainty injections can be renewable energy resources or loads and are modeled using a Gaussian mixture model (GMM). The developed formula can be used to compute the line current violation probability as well as integrate into optimal power flow problem as chance-constraint relaxation. Here, the proposed formula is first compared with the Matlab embedded numerical integration function to show its performance. Besides, the semi-analytical formula is validated and compared with the Monte Carlo simulation method using the IEEE 123-bus system, EPRI Ckt5, and Ckt7 systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Model based co-simulation platform for integrated building system control and design optimization

Both steady-state and dynamic simulations have been widely used by HVAC&R industry to support product/equipment development for decades. Steady-state simulation focuses on the system mass, energy and momentum balance of an equilibrium state. It is based on high-fidelity components models, and thus is suitable for system and component design optimization. Dynamic simulation studies the system transient response and is generally used for controls development and verification. It usually does not require rigorous component models of high accuracy because 1) the commonly used PID control is feedback control whose control performance evaluation doesn’t require high fidelity system/plant model; 2) high-fidelity dynamic model significantly increases the number of equations and variables and creates tremendous challenge for math solver. For supervisory control, transactive control or optimization of an integrated building system, the HVAC&R equipment is often one of the sub-components to be controlled. High-fidelity equipment models are required for accurately evaluating control strategies. In addition, building equipment manufacturers have developed a lot of high-fidelity steady-state equipment/component models per their expertise. Thus, a platform that can integrate OEM high-fidelity steady-state model with dynamic building simulation and/or electric power system & grid simulation to support the development and verification of supervisory control for integrated building systems is necessary. In this study, ORNL’s heat pump design tool (HPDM) is utilized to develop a co-simulation platform for supervisory control and optimization in integrated building systems. It is based on a model that integrates high-fidelity steady-state simulation equipment models with dynamic building simulation. A practical case of using the proposed co-simulation platform to develop and evaluate the supervisory control and optimization is presented and discussed.

Sun, Jian↗
DOE OSTI2010

Initial Report on Reservoir Modeling (SECARB Phase III Work Product 4.2.4.b)

The SECARB Partnership Anthropogenic Test, located in the Southeast Unit of the Citronelle oilfield will inject CO 2 into the saline waters of the Cretaceous Paluxy sandstone formation for three to four years. In order to accurately model the injection, migration, and long-term fate of carbon dioxide (CO 2 ) in the subsurface, GEM-GHG, a Computer Modeling Group software program for reservoir simulation and transport modeling was selected for the simulation. GEM-GHG is a very robust compositional reservoir simulator, with all the necessary options available for modeling CO 2 trapping mechanisms (including solubility, residual gas and mineralization). This simulation tool is widely known and used in the petroleum and sequestration industries. A reservoir model was built, based on a previously developed comprehensive picture of the subsurface geology at the site (Work Product 4.2.1.d - Report on Subsurface Characterization for the Anthropogenic Test Project Site). This report describes in details the different inputs that were used to create the model as well as the results of the injection scenario in terms of achievable injection rates, plume extension and pressure response.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2014

Final Report on Reservoir Modeling (SECARB Phase III Work Product 4.2.4.c)

The SECARB Partnership Anthropogenic Test, located in the Southeast Unit of the Citronelle oilfield will inject CO 2 into the saline waters of the Cretaceous Paluxy sandstone formation for three years. In order to accurately model the injection, migration, and long-term fate of CO 2 in the subsurface, GEM, a Computer Modeling Group software program for transport and geochemical modeling, was selected for the simulation. GEM is a very robust compositional reservoir simulator, with all the necessary options available for modeling CO 2 trapping mechanisms (including solubility, residual gas and mineralization). This simulation tool is widely known and used in the petroleum and sequestration industries. A reservoir model was built, based on a previously developed comprehensive picture of the subsurface geology at the site (Work Product 4.2.1.d - Report on Subsurface Characterization for the Anthropogenic Test Project Site). This report describes in details the different inputs that were used to create the model as well as the results of the injection scenario in terms of achievable injection rates, plume extent and pressure response.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2016

CAMPUS: Fully Coupled Multiphysics Modeling and Simulation of LWR and FBR Nuclear Fuel Behavior

Nuclear fuels operate in an environment that involves complex multiphysics phenomena, and the multiphysics behavior is often tightly coupled. The prediction of fuel behavior under irradiation involves very complex material behavior that is not seen in any other engineering discipline. Understanding and predicting the evolving material properties and phenomenal behaviors of nuclear fuels are major challenges for fuel design and behavior prediction. The multiphysics behavior is often a tightly coupled thermal, mechanical and chemical phenomenon associated with a large number of control parameters and uncertainties, which requires an advanced fuel performance modeling and simulation capability to improve the existing reactors performance, to address environmental and reactor safety concerns. Nuclear fuel performance modeling and simulation capability is necessary as a result of the high cost and difficulty in experimental measurements. So, a fuel performance code called CityU Advanced Multiphysics Nuclear Fuels Performance with User-defined Simulations (CAMPUS) was developed to predict both light water reactor and fast reactor fuel behavior. An effective approach was developed using self-defined multiphysics models based on the framework of COMSOL Multiphysics to manage the nonlinearities associated with light water reactor and fast reactor fuels performance analysis. The modelling and simulations approach is of particular importance since it demonstrates highly interrelated and nonlinear fuel performance models can be developed and implemented into a multiphysics platform, and thus more efforts can be put into physics model development and improvement. The modelling results can be used to identify the important phenomena and parameters, to direct and design experiments and to assist in post analysis of expensive nuclear experiments for light water reactor and fast reactor nuclear fuel performance analysis. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Thermo-Fluid Modeling Framework for Supercomputer Digital Twins: Part 1, Demonstration at Exascale

A thermo-fluid modeling framework is being developed for ExaDigiT---an open-source framework for developing comprehensive digital twins of liquid-cooled supercomputers. The work is being conducted in two parts, and discussion is divided into two companion papers. The work documented in this paper focuses on the development of a cooling system library in Dymola for the Frontier supercomputer at Oak Ridge National Laboratory. The second part, outlined in a companion paper, focuses on a templating structure called Auto-CSM for easily creating model-agnostic, physics-based thermo-fluid cooling system models for liquid-cooled supercomputers using a text-based schema. The cooling model is being developed using primarily the open-source Transient Simulation Framework of Reconfigurable Models (TRANSFORM) library. The library follows the templating architecture developed within the TRANSFORM library for modeling subsystems. A full-system validation was performed to validate a very simple model that is integrated with the system controls, and the results are presented herein.

Kumar, Vineet↗
DOE OSTI2024

Development and Validation of a Process Model and Open-Source Process Simulator for Microalgae-Based Tertiary Phosphorus Recovery

Microalgae-based tertiary wastewater treatment has the potential to meet stringent effluent phosphorus limits, with the added benefit of producing a marketable feedstock. However, the lack of validated mechanistic models and their implementation in process simulators have limited the adoption of this technology. In this study, an updated lumped pathway metabolic model (Phototrophic-Mixotrophic Process Model, PM 2 ), including both photoautotrophic and heterotrophic metabolisms of microalgae, was developed to predict effluent phosphorus concentration and biomass yield in response to dynamic influent and varying environmental conditions. The model was implemented in QSDsan – an open-source, Python-based design and simulation platform – for robust simulation under uncertainty. A global sensitivity analysis was performed to prioritize model parameters for calibration. The model was then calibrated and validated using batch experimental data and 45 days of continuous online monitoring data from a full-scale (568 m 3 ·d -1 ) microalgae-based tertiary wastewater treatment plant (EcoRecover process). In particular, along with dynamic influent composition, temperature and light intensity data with diel variation were provided as model inputs to reflect the microalgal behavior under day-night cycling. Overall, the QSDsan-based microalgae process simulator was able to predict effluent phosphorus within 0.02–0.04 mg-P·L -1 , while also capturing the general trends of state variables according to nutrient availability.

Lumped pathway metabolic model↗
DOE OSTI2014

A nucleotide-level coarse-grained model of RNA

We present a new, nucleotide-level model for RNA, oxRNA, based on the coarse-graining methodology recently developed for the oxDNA model of DNA. The model is designed to reproduce structural, mechanical, and thermodynamic properties of RNA, and the coarse-graining level aims to retain the relevant physics for RNA hybridization and the structure of single- and double-stranded RNA. In order to explore its strengths and weaknesses, we test the model in a range of nanotechnological and biological settings. Applications explored include the folding thermodynamics of a pseudoknot, the formation of a kissing loop complex, the structure of a hexagonal RNA nanoring, and the unzipping of a hairpin motif. We argue that the model can be used for efficient simulations of the structure of systems with thousands of base pairs, and for the assembly of systems of up to hundreds of base pairs. The source code implementing the model is released for public use.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗