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At least 127 records · Page 7

Two–Dimensional Idealized Hadley Circulation Simulation for Global High Resolution Model Development

A new framework for the development of global high resolution models using a vertical- meridional, two-dimensional pole-to-pole domain is proposed. Compared with the three-dimensional global model, the two-dimensional framework can simulate cloud-scale convection at significantly reduced computational cost, data volume, and turn-around time, and accelerate the development phase. Although idealized, it allows for simulation of various clouds and scale interactions under a wide range of environmental conditions, even though zonal waves such as mid latitude storms cannot be simulated. Physics schemes can be tested and assessed over a full array of simultaneously occurring cloud regimes. The framework can serve as an intermediate step between a one-dimensional simulation and a full three-dimensional global model. Using this framework, we analyze the resolution dependencies of simulated clouds and the Hadley circulation in a range of global high resolution models by performing multiple 1000-day simulations; for some resolutions tested, for example, 2 km horizontal resolution, three-dimensional simulation is not feasible at the present time. Analysis shows that both horizontal and vertical resolution determine the properties of the Hadley circulation and clouds, and that the differences among the simulated Hadley circulations are understood as differences in scale interactions influenced by resolution.

54 ENVIRONMENTAL SCIENCES↗

Reference Model Development

Presentation from the 2011 Water Peer Review in which principal investigator discusses project progress to develop a representative set of Reference Models (RM) for the MHK industry to develop baseline cost of energy (COE) and evaluate key cost component/system reduction pathways.

cost↗

Source characterization and modeling development for monoenergetic-proton radiography experiments on OMEGA

A monoenergetic proton source has been characterized and a modeling tool developed for proton radiography experiments at the OMEGA [T. R. Boehly et al., Opt. Comm. 133, 495 (1997)] laser facility. Multiple diagnostics were fielded to measure global isotropy levels in proton fluence and images of the proton source itself provided information on local uniformity relevant to proton radiography experiments. Global fluence uniformity was assessed by multiple yield diagnostics and deviations were calculated to be {approx}16% and {approx}26% of the mean for DD and D{sup 3}He fusion protons, respectively. From individual fluence images, it was found that the angular frequencies of Greater-Than-Or-Equivalent-To 50 rad{sup -1} contributed less than a few percent to local nonuniformity levels. A model was constructed using the Geant4 [S. Agostinelli et al., Nuc. Inst. Meth. A 506, 250 (2003)] framework to simulate proton radiography experiments. The simulation implements realistic source parameters and various target geometries. The model was benchmarked with the radiographs of cold-matter targets to within experimental accuracy. To validate the use of this code, the cold-matter approximation for the scattering of fusion protons in plasma is discussed using a typical laser-foil experiment as an example case. It is shown that an analytic cold-matter approximation is accurate to within Less-Than-Or-Equivalent-To 10% of the analytic plasma model in the example scenario.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Status Report on the Component Models Developed in the Modelica Framework: Reverse Osmosis Desalination Plant & Thermal Energy Storage

This report has been prepared as part of an effort to design and build a Modeling and Simulation (M&S) framework to assess the economic viability of a Nuclear-Renewable Hybrid Energy System (N-R HES). In order to facilitate dynamic M&S of such an integrated system, research groups in multiple national laboratories and universities have been developing various subsystems as dynamic physics-based components using the Modelica programming language. In Fiscal Years (FYs) 2015, Idaho National Laboratory (INL) performed a dynamic analysis of two region-specific N-R HES configurations, including the gas-to-liquid (natural gas to Fischer-Tropsch synthetic fuel) and brackish water Reverse Osmosis (RO) desalination plants as industrial processes. In FYs 2016–2017, INL developed two additional subsystems in the Modelica framework: (1) a high-temperature steam electrolysis plant as a high priority industrial plant to be integrated with a light water reactor within an N-R HES and (2) a gas turbine power plant as a secondary energy supply. In FY 2018, the RO desalination system model developed in FY 2015 has been updated such that the model is compatible with the most recent version of the ThermoPower library. Special attention has been given to the controller settings based on process models, aiming to improve process dynamics and controllability. A dynamic performance analysis of the updated RO desalination plant was carried out to evaluate the technical feasibility (load-following capability) of such a system operating under highly variable conditions requiring flexible output. Simulation results involving several case studies show that the suggested control scheme could maintain the controlled variables (including the variable electrical load and RO feed pressure) within desired limits under various plant operating conditions. The results also indicate that the proposed RO plant could provide operational flexibility to participate in energy management at the utility scale by dynamically optimizing the use of excess plant capacity within an N-R HES. For a small-scale energy storage system, a sensible Thermal Energy Storage (TES) model has been developed in the Modelica Framework in FY 2018.

25 ENERGY STORAGE↗

Impacts of contaminant storage on indoor air quality: Model development

A first-order, lumped capacitance model is used to describe the buffering of airborne chemical species by building materials and furnishings in the indoor environment. The model is applied to describe the interaction between formaldehyde in building materials and the concentration of the species in the indoor air. Storage buffering can decrease the effect of ventilation on the indoor concentration, compared to the inverse dependence of indoor concentration on the air exchange rate that is consistent with a constant emission rate source. If the exposure time of an occupant is long relative to the time scale of depletion of the compound from the storage medium, however, the total exposure will depend inversely on the air exchange rate. This lumped capacitance model is also applied to moisture buffering in the indoor environment, which occurs over much shorter depletion timescales of the order of days. This model provides a framework to interpret the impact of storage buffering on time-varying concentrations of chemical species and resulting occupant exposure. Pseudo-steady state behavior is validated using field measurements. Model behavior over longer times is consistent with formaldehyde and moisture concentration measurements in previous studies.

54 ENVIRONMENTAL SCIENCES↗

Benchmarking FFTF LOFWOS Test# 13 using SAM code: Baseline model development and uncertainty quantification

The development and deployment of advanced reactors, such as the sodium-cooled fast reactor (SFR), relies on sophisticated modeling tools to ensure the safety of the design under various transients. The predictive capability of these advanced modeling tools requires validation to garner trust in supporting the licensing of the advanced reactors. For this reason, the International Atomic Energy Agency (IAEA) initiated a coordinated research project (CRP) in 2018 for the analysis of the Fast Flux Test Facility (FFTF) Loss of Flow Without Scram (LOFWOS) Test #13.In this study, we present and discuss the benchmarking efforts of the modern system code SAM on the FFTF LOFWOS Test #13. Further, the SAM baseline model was developed according to the benchmark specification, which included a detailed core model with reactivity feedback. Generally, good agreement was observed between the baseline results and benchmark measurements; however, discrepancies persisted, particularly in predicted fuel assembly coolant outlet temperatures. Utilizing the baseline model, uncertainty quantification (UQ) and sensitivity analysis (SA) were conducted with the assistance of various statistical learning and machine learning methods, including kernel density estimation, Gaussian processes, and Sobol indices. Following the baseline model prediction and UQ and SA results, we discuss the reasons for the simulation discrepancies and propose further improvements to the model. This benchmarking effort adheres to the best-estimate plus uncertainty approach and can serve as a valuable example for supporting risk-informed licensing of advanced reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Coarse woody debris decomposition assessment tool: Model development and sensitivity analysis

Coarse woody debris (CWD) is an important component in forests, hosting a variety of organisms that have critical roles in nutrient cycling and carbon (C) storage. We developed a process-based model using literature, field observations, and expert knowledge to assess woody debris decomposition in forests and the movement of wood C into the soil and atmosphere. The sensitivity analysis was conducted against the primary ecological drivers (wood properties and ambient conditions) used as model inputs. The analysis used eighty-nine climate datasets from North America, from tropical (14.2° N) to boreal (65.0° N) zones, with large ranges in annual mean temperature (26.5°C in tropical to -11.8°C in boreal), annual precipitation (6,143 to 181 mm), annual snowfall (0 to 612 kg m -2 ), and altitude (3 to 2,824 m above mean see level). The sensitivity analysis showed that CWD decomposition was strongly affected by climate, geographical location and altitude, which together regulate the activity of both microbial and invertebrate wood-decomposers. CWD decomposition rate increased with increments in temperature and precipitation, but decreased with increases in latitude and altitude. CWD decomposition was also sensitive to wood size, density, position (standing vs downed), and tree species. The sensitivity analysis showed that fungi are the most important decomposers of woody debris, accounting for over 50% mass loss in nearly all climatic zones in North America. The model includes invertebrate decomposers, focusing mostly on termites, which can have an important role in CWD decomposition in tropical and some subtropical regions. The role of termites in woody debris decomposition varied widely, between 0 and 40%, from temperate areas to tropical regions. Woody debris decomposition rates simulated for eighty-nine locations in North America were within the published range of woody debris decomposition rates for regions in northern hemisphere from 1.6° N to 68.3° N and in Australia.

54 ENVIRONMENTAL SCIENCES↗

Transient Efficiency Flexibility and Reliability Optimization of Coal-Fired Power Plants (Reduced Order Model Development Report)

This document pertains to the reporting requirements of DOE contract FE-0031767. The document covers the development of a reduced order model library that can be used to represent coal-fired power plants. The models are transient and physics-based. Model classes in the library that correspond to different components in CFPPs are presented with physical explanations and representative results. Also, the use of the library to build an overall model for a representative CFPP is presented along with simulation results.

20 FOSSIL-FUELED POWER PLANTS↗

Nuclide inventory validation: radiochemical assay data quality and modeling challenges in benchmark models development

Oak Ridge National Laboratory is conducting radiochemical assay experiments, using high-precision analytical protocols validated with a comprehensive quality assurance plan, to expand the nuclide inventory validation basis for high burnup spent nuclear fuel. Preliminary measurement data for key actinides and fission products in two pressurized water reactor spent fuel samples are being used to investigate the impact of measurement data uncertainty on the sample burnup estimation. These measurement data are also being used to examine the impact of assumptions applied when developing best-estimate computational models to simulate fuel irradiation history. The simulations are being performed using depletion capabilities in the SCALE code system. Comparison of calculated and measured nuclide concentrations shows good agreement for the considered nuclides. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NRAP-Open-IAM Analytical Reservoir Model: Development and Testing

Geological carbon sequestration (GCS) is a key technology for reducing global carbon dioxide (CO 2 ) emissions. Over the last decade, the U.S. Department of Energy has invested in understanding the science base, developing practical implementation methods, and demonstrating secure GCS technologies to mitigate the environmental impacts associated with the atmospheric release of CO 2 . As part of the National Risk Assessment Partnership, a systems-level risk assessment tool, called the NRAP-Open-IAM, has been developed to conduct risk assessment and enable safe operations at a GCS site. The current NRAP-Open-IAM contains a simple reservoir model component that calculates the evolution of CO 2 saturation and fluid pressure in a storage reservoir during CO 2 injection operations. This report presents the development and testing of a new analytical reservoir reduced-order model (ROM), which is extended from an existing semi-analytical model for estimation of CO 2 and brine leakage along legacy wells, and enhances the capability of the NRAP-Open-IAM to simulate more types of reservoir conditions. The developed model is validated against three reference studies, and the results indicate that the new ROM predicts the behavior of the two-phase fluids (brine and injected CO 2 ) well and is applicable to different reservoir simulation boundary conditions (i.e., constant pressure boundary and infinite-acting boundary) without a priori user specification of the boundary type. Sensitivity analysis for a set of model parameters is performed using 4,000 synthetic cases prepared via a fully automated process and using machine-learning-based feature selection. The stochastic analysis identifies gravitational number (i.e., ratio of gravitational forces to viscous force) and distance between the injection well and observation location as the most impactful parameters for matching the pressure and CO 2 saturation, respectively, between the numerical simulations and the ROM. This report details the possible ROM uncertainties and serves as a guide for users to understand the use and limitations of this ROM. The code implementation of the model will be released as a module within the NRAP-Open-IAM.

54 ENVIRONMENTAL SCIENCES↗

Modeling methane emissions from arctic lakes: Model development and site‐level study

Abstract To date, methane emissions from lakes in the pan‐arctic region are poorly quantified. In order to investigate the response of methane emissions from this region to global warming, a process‐based climate‐sensitive lake biogeochemical model was developed. The processes of methane production, oxidation, and transport were modeled within a one‐dimensional sediment and water column. The sizes of 14 C‐enriched and 14 C‐depleted carbon pools were explicitly parameterized. The model was validated using observational data from five lakes located in Siberia and Alaska, representing a large variety of environmental conditions in the arctic. The model simulations agreed well with the measured water temperature and dissolved CH 4 concentration (mean error less than 1°C and 0.2 μM, respectively). The modeled CH 4 fluxes were consistent with observations in these lakes. We found that bubbling‐rate‐controlling nitrogen (N 2 ) stripping was the most important factor in determining CH 4 fraction in bubbles. Lake depth and ice cover thickness in shallow waters were also controlling factors. This study demonstrated that the thawing of Pleistocene‐aged organic‐rich yedoma can fuel sediment methanogenesis by supplying a large quantity of labile organic carbon. Observations and modeling results both confirmed that methane emission rate at thermokarst margins of yedoma lakes was much larger (up to 538 mg CH 4 m −2 d −1 ) than that at nonthermokarst zones in the same lakes and a nonyedoma, nonthermokarst lake (less than 42 mg CH 4 m −2 d −1 ). The seasonal variability of methane emissions can be explained primarily by energy input and organic carbon availability.

Tan, Zeli↗

High Fidelity Forward Model Development for Nuclear Reactor Spent Fuel Technical Nuclear Forensics

The fidelity of the forward model within a spent fuel forensic analysis system was improved by using two unique methodologies. The first consisted of developing a system to create accurate one-group neutron cross-section libraries for any user specified reactor system. In such, a detailed model is developed using the depletion code MONTEBURNS. During MONTEBURNS execution, cross-section libraries are generated at every user specified burnup step in time. These libraries could be developed for many reactor systems, then housed in a database and used for analyzing unknown fuel samples. The forensic analysis system for spent fuel resulted in higher accuracy at predicting the initial uranium isotopic compositions and burnup from spent fuel samples. Using this method, the error in results was reduced from the order of 1-6% down to less than 1% when recovering a fuel sample's burnup and initial uranium isotopic composition. The second method consisted of implementing 2D/3D reactor depletion codes as the forward model within the system's framework. This method would allow the usage of potentially recoverable geometric information from an unknown sample. No predetermined cross-section library is required for the system using this method, therefore potentially reducing model error associated with the neutron flux spectrum. The accuracy of the recovered initial uranium isotopic compositions and burnup from spent fuel samples was also improved using this method, even more so than the first. For MTR reactors, the error using this method was significantly reduced and was driven to below 0.5%. However, additional research may be required to determine the ideal fission yield and recoverable energy per fission for cases where significant amounts of 239 PU are bred and burned throughout the life of the fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Experimental Determination of Constitutive Response of Alloy 800H in Support of Viscoplastic Constitutive Model Development for ASME Section III, Division 5, Class A Applications

In FY 2022, a development effort was initiated at the US Department of Energy’s Argonne National Laboratory (Argonne) and Oak Ridge National Laboratory (ORNL) to develop the Alloy 800H viscoplastic constitutive model so that inelastic analysis methods can support high-temperature gas-cooled reactor (HTGR) designs. The viscoplastic constitutive equations will be developed at Argonne. The ORNL effort focuses on generating test data from various high-temperature experiments with specially designed loading histories to probe Alloy 800H’s constitutive response.

36 MATERIALS SCIENCE↗

Kinetic model development and Bayesian uncertainty quantification for the complete reduction of Fe-based oxygen carriers with CH 4 , CO, and H 2 for chemical looping combustion

In this work, three kinetic models are developed and calibrated for the complete multi-step reduction of an Fe-based oxygen carrier (OC) particle with CH 4 , CO, and H 2 , using data from thermogravimetric analysis. The complete reduction rate profiles exhibit complex dynamics whose trajectory is significantly different depending on the reducing gas. A Bayesian model building and parameter estimation framework is applied for simultaneous parameter and model structure uncertainty quantification. The final models show excellent agreement between model predictions and calibration data, as well as new data not used for calibration (for the reduction of the OC with CH 4 ). Parameter uncertainty is quantified by determining joint posterior distribution, and model structure uncertainty is addressed by incorporating Gaussian process stochastic functions (represented by Bayesian smoothing splines) into the kinetic models. The final kinetic models with discrepancy functions are readily employable in equation-oriented simulation and optimization platforms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Model Development in MARMOT for High Burn-up Structure Formation

A phase field model for the formation of High Burn-up Structure (HBS) was developed and implemented in MARMOT. The model takes into consideration the chemical energy of gas atoms, interfacial energies of grain boundaries and bubble surfaces, and strain energy associated with dislocations, which renders the model capable of simulating the concurrent formation and growth of both bubbles and sub-grains. Moreover, in contrast to existing phase-field models of recrystallization, the current model makes no ad hoc or a priori assumptions for the nucleation rate or recrystallized grain size and shape. All the model parameters were quantified in terms of thermodynamic and kinetic properties. The model predicts a strong effect of magnitude and distribution of dislocation density, grain boundary energy, and bubble surface energy on the formation of sub-grains. The model results were shown to agree well with theoretical predictions. For polycrystalline UO 2 at 1200K, the recrystallized average grain size was found to be on the order of of 0.6-1.3 microns at a burn-up in the range of 98-105 GWD/tU. These values lie well within the range of reported data in literature.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Fuel Matrix Degradation Model Development Update: Alloy Corrosion Rates and Hydrogen Generation

This work is being performed as part of the DOE NE Spent Fuel and Waste Science and Technology Campaign, Argillite and Crystalline Rock R&D work packages: SF-19AN01030101 and SF-19AN01030201. This document meets the milestone M4SF-19AN010301013 for Argillite R&D and the milestone M4SF-19AN010302013 for Crystalline R&D. The fuel matrix degradation (FMD) model calculates the degradation rate of spent UO2 fuel based on fundamental electrochemical theory and thermodynamics. The model provides the quantitative basis for radionuclide source term predictions in the generic disposal system analysis (GDSA) performance assessment (PA) model. The FMD model has been implemented in a manner that facilitates its integration with the GDSA-PA code and a preliminary, integrated FMD-GDSA model has been successfully tested (Jerden et al., 2017). The specific focus of on-going work is to accurately and quantitatively represent the generation of H2 in a breached waste package and its effect on the spent fuel degradation rate so that this key process can be accurately represented in PA models. It has been shown experimentally that millimolar concentrations of dissolved H2 in contact with spent fuel will inhibit oxidative dissolution and decrease the fuel degradation rates by as much as three orders of magnitude (e.g., Röllin et al., 2001, Ollila, 2008). This will lead to a significant decrease in the radionuclide source term values used in repository PA models. Sensitivity studies using the FMD model have shown that the dissolved H2 concentration is the dominant environmental variable affecting the UO2 spent fuel dissolution rate as long as a source of H2 persists in the breached waste package (Jerden et al., 2015). Therefore, on-going experimental and modeling efforts focus on H2 production, accumulation and interfacial reactions within a breached waste package. The anoxic corrosion of metallic engineering materials within a breached waste package will be the main source of H2 in crystalline and argillite rock repository systems. The most important H2-producing alloys present within a waste package include stainless steel, carbon steel, and aluminum alloys and the Zircaloy fuel cladding. A steel corrosion module was added to the FMD model to account for these H2 sources and couple the H2 generation rate with fuel degradation processes (Jerden et al., 2017). As discussed below, there is a need for experimental data from electrochemical corrosion tests to quantify the H2 generation rates due to the corrosion of these waste package alloys as a function of key environmental variables (Eh, pH, groundwater chemistry). This report presents results from series of electrochemical corrosion tests with materials present in waste packages that provide information needed to parameterize and validate the FMD model. The alloys tested include 316L stainless steel (316SS), AISI 4320 carbon steel (C-steel) and Zircaloy-4 fuel cladding (unirradiated). Potentiodynamic polarization and potentiostatic polarization tests were performed in buffer solutions at pH 4, 7 and 10 with NaCl concentrations of 0, 4 and 100 millimolar (mM). The potentiostatic tests were performed at voltages varying from 0.5 volts down to -0.66 volts, vs the standard hydrogen electrode (SHE), and all tests were performed at laboratory ambient temperatures (~22 °C). The corrosion rates measured during the electrochemical tests were used as direct input to a new FMD/in-package chemistry model that is being developed to provide accurate long-term spent fuel degradation rates as chemical conditions (Eh, pH, speciation) evolve within a breached waste package. This new model was developed by coupling the FMD model with the reactive transport code X1t, which is a module within the Geochemist’s Workbench (GWB) reaction path modeling code (Jerden et al., 2019). The reactive transport model consists of a 1D domain discretized with 21 reaction diffusion cells and includes a single waste packag

Jerden, James↗

Constitutive model development of aluminum alloy 1100 for elevated temperature forming process

Commercially pure aluminum alloy, AA1100, presents good electrical and thermal conductivity, high formability, and low cost. Those favorable characteristics have the potential to enable bipolar plates with improved economics and enhanced performance compared to current stainless steel bipolar plates for proton exchange membrane fuel cells. An accurate constitutive model is essential to develop and optimize processing parameters and effectively control the forming process. Here, the objective of this work is to develop a constitutive model of AA1100 that is able to simulate stress-strain relation, formed geometry, and predict the onset of fracture strain to avoid forming failure. Initially, a set of tensile tests at temperature between 300 and 500°C and strain rate between 0.005 and 1.0/s were conducted to examine the deformation behavior. Then, a set of damage-based unified visco-plastic constitutive equations is proposed and calibrated based on the results of stress-strain data. A genetic algorithm optimization method is applied to search for best fitting material constants in constitutive equations. The proposed model shows good predictability of both the stress-strain relation and fracture strain at low strain rate and high temperature conditions. The accuracy of proposed model is also evaluated statistically. A comparison of the proposed model with three popular models (Arrhenius-type mode, Johnson-Cook model and Zerilli-Armstrong model) was made. The proposed model shows the best experimental agreement with correlation coefficient of 0.96 in contrast to 0.25, 0.38 and 0.75 for the popular models, respectively. The proposed model can help to optimize the elevated temperature forming process and guide die design to enable optimal geometric features in the formed components.

08 HYDROGEN↗

Multi-objective Eco-Routing Model Development and Evaluation for Battery Electric Vehicles

This paper develops a multi-objective eco-routing algorithm (eco- and travel time-optimum routing) for battery electric vehicles (BEVs) and internal combustion engine vehicles (ICEVs) and investigates the network-wide impacts of the proposed multi-objective Nash optimum (user equilibrium) traffic assignment on a large-scale network. Unlike ICEVs, BEVs are more energy efficient on low-speed arterial trips compared with highway trips. Different energy consumption patterns require different eco-routing strategies for ICEVs and BEVs. This study found that single-objective eco-routing could significantly reduce the energy consumption of BEVs but also significantly increase their average travel time. Consequently, the study developed a multi-objective routing model (eco- and travel time-routing) to improve both energy and travel time measures. The model introduced a link cost function that uses the specification of the value of time and the cost of fuel/energy. The simulation study found that multi-objective routing could reduce BEV energy consumption by 13.5%, 14.2%, 12.9%, and 10.7%, as well as ICEV fuel consumption by 0.1%, 4.3%, 3.4%, and 10.6% for “not congested, “slightly congested,”“moderately congested,” and “highly congested” conditions, respectively. The study also found that multi-objective user equilibrium routing reduced the average vehicle travel time by up to 10.1% compared with the standard user equilibrium traffic assignment for highly congested conditions, producing a solution closer to the system optimum traffic assignment. The results indicate that the proposed multi-objective eco-routing strategy can reduce vehicle fuel/energy consumption effectively with minimum impacts on travel times for both BEVs and ICEVs.

Engineering↗