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At least 73 records · Page 4

Status Report on FY2022 Model Development within the Integrated Energy Systems HYBRID Repository

This publication details newly created energy storage models developed within the HYBRID Modelica repository as part of the Department of Energy Office of Nuclear Energy (DOE-NE) Integrated Energy Systems (IES) program, led by Idaho National Laboratory (INL). Model development to-date includes creation of dynamic systems-level models of a pebble bed high temperature gas reactor (HTGR), liquid air energy storage (LAES), and compressed air energy storage (CAES) in the IES-based HYBRID repository. Models are developed using the latest publicly available data and incorporate the possibility of control strategy inclusion for use with the existing IES modeling, analysis, and optimization toolset. Simulations showcase the abilities of each technology to flexibly operate in ways consistent with IES operation expectations. When these models are available, they can be utilized within different integrated energy park concepts to understand optimal system operation, control, and dispatching. Moreover, given the generic nature of the models, industrial partner technologies can be quickly added to the repository using the existing models as a basis. Additional dynamic models for thermal energy storage concepts can be developed and added to the HYBRID repository as needed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Average-passage flow model development

A 3-D model was developed for simulating multistage turbomachinery flows using supercomputers. This average passage flow model described the time averaged flow field within a typical passage of a bladed wheel within a multistage configuration. To date, a number of inviscid simulations were executed to assess the resolution capabilities of the model. Recently, the viscous terms associated with the average passage model were incorporated into the inviscid computer code along with an algebraic turbulence model. A simulation of a stage-and-one-half, low speed turbine was executed. The results of this simulation, including a comparison with experimental data, is discussed.

Adamczyk, John J.↗

Radiation Environment Modeling for Spacecraft Design: New Model Developments

A viewgraph presentation on various new space radiation environment models for spacecraft design is described. The topics include: 1) The Space Radiatio Environment; 2) Effects of Space Environments on Systems; 3) Space Radiatio Environment Model Use During Space Mission Development and Operations; 4) Space Radiation Hazards for Humans; 5) "Standard" Space Radiation Environment Models; 6) Concerns about Standard Models; 7) Inadequacies of Current Models; 8) Development of New Models; 9) New Model Developments: Proton Belt Models; 10) Coverage of New Proton Models; 11) Comparison of TPM-1, PSB97, AP-8; 12) New Model Developments: Electron Belt Models; 13) Coverage of New Electron Models; 14) Comparison of "Worst Case" POLE, CRESELE, and FLUMIC Models with the AE-8 Model; 15) New Model Developments: Galactic Cosmic Ray Model; 16) Comparison of NASA, MSU, CIT Models with ACE Instrument Data; 17) New Model Developmemts: Solar Proton Model; 18) Comparison of ESP, JPL91, KIng/Stassinopoulos, and PSYCHIC Models; 19) New Model Developments: Solar Heavy Ion Model; 20) Comparison of CREME96 to CREDO Measurements During 2000 and 2002; 21) PSYCHIC Heavy ion Model; 22) Model Standardization; 23) Working Group Meeting on New Standard Radiation Belt and Space Plasma Models; and 24) Summary.

Barth, Janet↗

A Deterministic Interfacial Cyclic Oxidation Spalling Model: Model Development and Parametric Response - Part 1

An equation has been developed to model the iterative scale growth and spalling process that occurs during cyclic oxidation of high temperature materials. Parabolic scale growth and spalling of a constant surface area fraction have been assumed. Interfacial spallation of the only the thickest segments was also postulated. This simplicity allowed for representation by a simple deterministic summation series. Inputs are the parabolic growth rate constant, the spall area fraction, oxide stoichiometry, and cycle duration. Outputs include the net weight change behavior, as well as the total amount of oxygen and metal consumed, the total amount of oxide spalled, and the mass fraction of oxide spalled. The outputs all follow typical well-behaved trends with the inputs and are in good agreement with previous interfacial models.

Smialek, James L.↗

Thermal Effects Modeling Developed for Smart Structures

Applying smart materials in aeropropulsion systems may improve the performance of aircraft engines through a variety of vibration, noise, and shape-control applications. To facilitate the experimental characterization of these smart structures, researchers have been focusing on developing analytical models to account for the coupled mechanical, electrical, and thermal response of these materials. One focus of current research efforts has been directed toward incorporating a comprehensive thermal analysis modeling capability. Typically, temperature affects the behavior of smart materials by three distinct mechanisms: Induction of thermal strains because of coefficient of thermal expansion mismatch 1. Pyroelectric effects on the piezoelectric elements; 2. Temperature-dependent changes in material properties; and 3. Previous analytical models only investigated the first two thermal effects mechanisms. However, since the material properties of piezoelectric materials generally vary greatly with temperature (see the graph), incorporating temperature-dependent material properties will significantly affect the structural deflections, sensory voltages, and stresses. Thus, the current analytical model captures thermal effects arising from all three mechanisms through thermopiezoelectric constitutive equations. These constitutive equations were incorporated into a layerwise laminate theory with the inherent capability to model both the active and sensory response of smart structures in thermal environments. Corresponding finite element equations were formulated and implemented for both the beam and plate elements to provide a comprehensive thermal effects modeling capability.

Lee, Ho-Jun↗

Achievements and Ongoing Challenges for advanced CFD Boiling Closure Model Development using Physical Insights from Validation-Oriented High-Fidelity Boiling Experiment

The fundamental understanding of the boiling-associated heat transfer, including sliding bubble effect, is still challenging despite the intensive research for decades in both experimental and computational boiling research communities. One of the main difficulties of boiling experiment come from the fact that direct observation of the underlying principle through experiment is very difficult due to the high complexity of the boiling phenomenon. Also, since the heat transfer characteristics associated with boiling is the result of non-linear interaction of various physical parameters coupled to each other, it is challenging to find the relationship between the parameters for modeling. This paper discusses the authors’ past and ongoing boiling research under CASL (Consortium for Advanced Simulation of Light Water Reactors) program, including the efforts to overcome the difficulties of boiling measurement and model development. In particular, we focus on describing the major achievements, lessons learnt, and ongoing challenges for the CFD boiling closure model development based on the high-fidelity subcooled flow boiling experiment at Texas A&M University (TAMU). The major research achievements discussed through this paper include (i) novel boiling measurement strategy and high-fidelity validation data production, (ii) dedicated effort to identify the critical measurement issues in boiling experiment, (iii) new physical insight into sliding bubble heat transfer mechanisms, and (iv) new boiling closure model development. Discussion is also made on the ongoing challenges for the boiling closure model development and the future research plan based on the lessons learnt.

42 ENGINEERING↗

Next-generation concurrent engineering: developing models to complement point designs

Concurrent Engineering Design teams have made routine the rapid development of point designs for space missions. The Jet Propulsion Laboratory's Team X is now evolving into a next generation CED; nin addition to a point design, the team develops a model of the local trade space. The process is a balance between the power of model-developing tools and the creativity of human experts, enabling the development of a variety of trade models for any space mission.

trade space exploration↗

Argonne Bubble Experiment Thermal Model Development III

This report describes the continuation of the work reported in “Argonne Bubble Experiment Thermal Model Development” and “Argonne Bubble Experiment Thermal Model Development II”. The experiment was performed at Argonne National Laboratory (ANL) in 2014. A rastered 35 MeV electron beam deposited power in a solution of uranyl sulfate, generating heat and radiolytic gas bubbles. Irradiations were performed at beam power levels between 6 and 15 kW. Solution temperatures were measured by thermocouples, and gas bubble behavior was recorded. The previous report2 described the Monte-Carlo N-Particle (MCNP) calculations and Computational Fluid Dynamics (CFD) analysis performed on the as-built solution vessel geometry. The CFD simulations in the current analysis were performed using Ansys Fluent, Ver. 17.2. The same power profiles determined from MCNP calculations in earlier work were used for the 12 and 15 kW simulations. The primary goal of the current work is to calculate the temperature profiles for the 12 and 15 kW cases using reasonable estimates for the gas generation rate, based on images of the bubbles recorded during the irradiations. Temperature profiles resulting from the CFD calculations are compared to experimental measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Next-generation concurrent engineering: developing models to complement point designs

Concurrent Engineering Design (CED) teams have made routine the rapid development of point designs for space missions. The Jet Propulsion Laboratory's Team X is now evolving into a 'next-generation CED; in addition to a point design, the Team develops a model of the local trade space. The process is a balance between the power of a model developing tools and the creativity of humal experts, enabling the development of a variety of trade models for any space mission. This paper reviews the modeling method and its practical implementation in the ED environment. Example results illustrate the benefit of this approach.

concurrent engineering↗

Collaborative Project: The problem of bias in defining uncertainty in computationally enabled strategies for data-driven climate model development

The objective of the project is to develop strategies for better representing scientific sensibilities within statistical measures of model skill that then can be used within a Bayesian statistical framework for data-driven climate model development and improved measures of model scientific uncertainty. One of the thorny issues in model evaluation is quantifying the effect of biases on climate projections. While any bias is not desirable, only those biases that affect feedbacks affect scatter in climate projections. The effort at the University of Texas is to analyze previously calculated ensembles of CAM3.1 with perturbed parameters to discover how biases affect projections of global warming. The hypothesis is that compensating errors in the control model can be identified by their effect on a combination of processes and that developing metrics that are sensitive to dependencies among state variables would provide a way to select version of climate models that may reduce scatter in climate projections. Gabriel Huerta was responsible for leading the effort to develop statistical methods for evaluating these field dependencies. The UT effort will incorporate these developments into MECS, which is a set of python scripts being developed at the University of Texas for managing the workflow associated with data-driven climate model development over HPC resources. We regularly consult with Peter Gleckler (LLNL), Mark Taylor (SNL), and Rich Neale (NCAR) to provide additional insight into issues concerning CAM5 model development and multi-model evaluation of the AR5 archive. This grant was originally assigned to Indiana University where both the PI (Huerta) and the Postdoc (Nosedal) worked on the project from March 1, 2012-March 31, 2013.

97 MATHEMATICS AND COMPUTING↗

Supo Thermal Model Development IV

This report describes the continuation of the Computational Fluid Dynamics (CFD) model of the Supo cooling system described in the reports, Supo Thermal Model Development, II, and III. In the previous reports, the solution natural convection of Supo was simulated using a 2D, axisymmetric model that altered the actual geometry. A 3D geometry of Supo will more accurately estimate the natural convection heat transfer coefficient (HTC) of the system since Supo contains several non-symmetric internal components that can only be modeled in 3D. This, in turn, will improve the natural convection HTC results for comparison purposes with past operational data and previous 2D CFD results. Unfortunately, the complexities of performing multiphase 3D CFD simulations has proven too large of a task for our current capabilities. Instead, this report will focus on the 3D model development for the 2.39 kW/L (31.3 kW) case and limitations and challenges associated with the 3D simulations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Challenge Problem 1: Preliminary Model Development and Assessment of Flexible Heat Transfer Modeling Approaches

This report presents the modeling progress of a university consortium studying flexible modeling for turbulent heat transfer. In the context of advanced nuclear reactor design, where challenges include non-unity Prandtl fluids, free and mixed convection, and transitional flow, computational fluid dynamics methods are underutilized due to low confidence in modeling approaches and high computational cost. This report evaluates the performance of engineering CFD models in diabatic, buoyant turbulent flow. It finds that all turbulence models including several variants of the k-ε and k-ω models struggle to predict accurate turbulent momentum and heat transfer in such flows. The Nusselt numbers have been compared between the models and the DNS data, where calculations have been performed for each case and trends have shown a good agreement between DNS estimated Nusselt numbers and available correlations as well as experimental data. A novel DNS correlation for high Pr cases as they are transitioning from mixed convection to natural convection has been proposed. While Nusselt number errors relative to DNS range from 20% to 50%, the models capture similar trends to DNS with respect to Nusselt suppression and amplification under varying levels of buoyancy effect. This report also highlights model form error as a significant contributor to CFD predictions and proposes a framework for quantifying model error and improving confidence in CFD calculations. To improve the predictive capability of engineering CFD models, data-driven approaches for turbulence models are investigated. Theoretical frameworks based on the invariant tensor / vector basis neural networks for prediction of Reynolds stresses and turbulent heat fluxes are employed. The models are developed using direct numerical simulations data for forced convection flows of different fluids in vertical planar channel domain. The framework is implemented in spectral element solvers Nek5000 / nekRS and has shown a potential for future development and consideration of mixed convection flows.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Loads Model Development and Analysis for the F/A-18 Active Aeroelastic Wing Airplane

The Active Aeroelastic Wing airplane was successfully flight-tested in March 2005. During phase 1 of the two-phase program, an onboard excitation system provided independent control surface movements that were used to develop a loads model for the wing structure and wing control surfaces. The resulting loads model, which was used to develop the control laws for phase 2, is described. The loads model was developed from flight data through the use of a multiple linear regression technique. The loads model input consisted of aircraft states and control surface positions, in addition to nonlinear inputs that were calculated from flight-measured parameters. The loads model output for each wing consisted of wing-root bending moment and torque, wing-fold bending moment and torque, inboard and outboard leading-edge flap hinge moment, trailing-edge flap hinge moment, and aileron hinge moment. The development of the Active Aeroelastic Wing loads model is described, and the ability of the model to predict loads during phase 2 research maneuvers is demonstrated. Results show a good match to phase 2 flight data for all loads except inboard and outboard leading-edge flap hinge moments at certain flight conditions. The average load prediction errors for all loads at all flight conditions are 9.1 percent for maximum stick-deflection rolls, 4.4 percent for 5-g windup turns, and 7.7 percent for 4-g rolling pullouts.

Allen, Michael J.↗

Loads Model Development and Analysis for the F/A-18 Active Aeroelastic Wing Airplane

The Active Aeroelastic Wing airplane was successfully flight-tested in March 2005. During phase 1 of the two-phase program, an onboard excitation system provided independent control surface movements that were used to develop a loads model for the wing structure and wing control surfaces. The resulting loads model, which was used to develop the control laws for phase 2, is described. The loads model was developed from flight data through the use of a multiple linear regression technique. The loads model input consisted of aircraft states and control surface positions, in addition to nonlinear inputs that were calculated from flight-measured parameters. The loads model output for each wing consisted of wing-root bending moment and torque, wing-fold bending moment and torque, inboard and outboard leading-edge flap hinge moment, trailing-edge flap hinge moment, and aileron hinge moment. The development of the Active Aeroelastic Wing loads model is described, and the ability of the model to predict loads during phase 2 research maneuvers is demonstrated. Results show a good match to phase 2 flight data for all loads except inboard and outboard leading-edge flap hinge moments at certain flight conditions. The average load prediction errors for all loads at all flight conditions are 9.1 percent for maximum stick-deflection rolls, 4.4 percent for 5-g windup turns, and 7.7 percent for 4-g rolling pullouts.

Allen, Michael J.↗

Atmospheric model development in support of SEASAT. Volume 4: Forecast model sensitivity study

Atmospheric analysis and prediction models of varying (grid) resolution were developed. The models were tested using real observational data for the purpose of assessing the impact of grid resolution on short range numerical weather prediction. The work statement was amended to include the performance of sensitivity tests using a coarse mesh (63 x 63 x 5 level) prediction model in order to identify and order factors which might mask or impair the utility of SEASAT data on short range weather prediction. Such factors included: initial conditions; topography; surface friction; latent heating; diffusion of momentum and temperature; and computational devices such as tendency truncators, pressure smoothers, and temporal filters.

Lewit, H. L.↗

ATF material model development and validation for priority fuel concepts

Development, implementation, and validation of material and behavior models for accident tolerant fuel (ATF) concepts in the Bison fuel performance code began in 2014 in response to the events that occurred at the Fukushima Daichii nuclear power plant in March 2011. Early on the focus was on U 3 Si 2 fuel and FeCrAl cladding as part of a high impact problem through the Nuclear Energy and Advanced Modeling Simulation (NEAMS) program. Then, developments for Cr 2 O 3 -doped UO 2 fuel, and SiC-SiC and Cr-coated zirconium-based claddings began based upon industry interests. In late fiscal year 2018 the Consortium for Advanced Simulation of Light Water Reactors (CASL) took over further ATF work in Bison in support of the Nuclear Regulatory Commission (NRC) engagement. Discussions with the NRC identified their list of priority fuel and cladding concepts, which included Cr 2 O 3 -doped UO 2 and U 3 Si 2 fuels, and Cr-coated zirconium-based and FeCrAl claddings. In particular, the NRC suggested that reports similar in form to NUREG/CR-7024 [1] that was developed for traditional LWR materials UO 2 and zirconium-based claddings (i.e., Zircaloy-4, M5®, ZIRLO) be created for the priority ATF concepts. The approach to ATF capability development in Bison since the beginning has been two-fold: (1) empirical correlations and (2) multiscale model development. Both approaches have uncertainty inherent to them. Uncertainty in empirical correlations is bounded by the experimental data upon which with the correlation was developed. Models developed through a multiscale approach have uncertainty associated with the lower length scale calculations and input parameters that must be propagated to the engineering scale model in Bison. In this report, the recommended models, their range of applicability (e.g., temperature, burnup), and associated uncertainty for the NRC priority fuel concepts Cr 2 O 3 -doped UO 2 and U 3 Si 2 are presented in a manner similar to the aforementioned NUREG. In addition, the Cr 2 O 3 -doped UO 2 models are validated to the Halden Reactor tess IFA-677.1 rods 1 and 5 and IFA-716.1 rod 1. For U 3 Si 2 the models are validated to the recent post-irradiation examination (PIE) data ATF-13 and ATF-15 rods that were irradiated in the Advanced Test Reactor (ATR) at Idaho National Laboratory. Finally, an uncertainty quantification (UQ) and sensitivity analysis (SA) is completed on a single rod for each fuel concept that takes into account the defined uncertainty in select models. The results of the UQ and SA analyses indicate that given the large uncertainty in some of the input ATF models that the uncertainty on the Bison predictions of fuel performance metrics of interest bound the available experimental data. Correlation coefficients are also reported that identified the uncertain inputs with the strongest correlation (positive or negative) with the outputs of interest. Fuel performance metrics investigated include fuel elongation, rod internal pressure, fuel centerline temperature, and fission gas release.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

ATF material model development and validation for priority cladding concepts

Development, implementation, and validation of material and behavior models for accident tolerant fuel (ATF) concepts in the Bison fuel performance code began in 2014 in response to the events that occurred at the Fukushima Daichii nuclear power plant in March 2011. Early on the focus was on U 3 Si 2 fuel and FeCrAl cladding as part of a high impact problem through the Nuclear Energy and Advanced Modeling Simulation (NEAMS) program. Then, developments for Cr 2 O 3 -doped UO 2 fuel, and SiC-SiC and Cr-coated zirconium-based claddings began based upon industry interests. In late fiscal year 2018 the Consortium for Advanced Simulation of Light Water Reactors (CASL) took over further ATF work in Bison in support of the Nuclear Regulatory Commission (NRC) engagement. Discussions with the NRC identified their list of priority fuel and cladding concepts, which included Cr 2 O 3 -doped UO 2 and U 3 Si 2 fuels, and Cr-coated zirconium-based and FeCrAl claddings. In particular, the NRC suggested that reports similar in form to NUREG/CR-7024 that was developed for traditional LWR materials UO 2 and zirconium-based claddings (i.e., Zircaloy-4, M5 ® , ZIRLO TM ) be created for the priority ATF concepts. The approach to ATF capability development in Bison since the beginning has been two-fold: (1) empirical correlations and (2) multiscale model development. Both approaches have uncertainty inherent to them. Uncertainty in empirical correlations is bounded by the experimental data upon which with the correlation was developed. Models developed through a multiscale approach have uncertainty associated with the lower length scale calculations and input parameters that must be propagated to the engineering scale model in Bison. In this report, the recommended models, their range of applicability (e.g., temperature, fluence), and associated uncertainty for the NRC priority clad concepts Cr-coated zirconium based clad and FeCrAl are presented in a manner similar to the aforementioned NUREG. In addition, in the absence of experimental data for validation, demonstration cases are presented that investigate the ballooning and burst behavior of Cr-coated and FeCrAl clads as well as tritium permeation in FeCrAl. A portion of the study by Gamble et al. on FeCrAl failure is also revisited with the latest updated models. First, the nominal results are shown using the as implemented models. Then a sensitivity analysis and uncertainty quantification is performed to assess the impact of the uncertainties in the models on the parameters of interest. For the Cr-clad ballooning case the parameter of interest is the time to burst. For the revisited FeCrAl study, the parameter of interest is the pressure at burst.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Important ice processes are missed by the Community Earth System Model (CESM) in Southern Ocean mixed–phase clouds: Bridging SOCRATES observations to model developments

Global climate models (GCMs) are challenged by difficulties in simulating cloud phase and cloud radiative effect over the Southern Ocean (SO). Some of the new generation GCMs predict too much liquid and too little ice in mixed-phase clouds. This misrepresentation of cloud phase in GCMs results in weaker negative cloud feedback over the SO and a higher climate sensitivity. Based on a model comparison with observational data obtained during the Southern Ocean Cloud Radiation and Aerosol Transport Experimental Study (SOCRATES), this study addresses a key uncertainty in the Community Earth System Model version 2 (CESM2) related to cloud phase, namely ice formation in pristine remote SO clouds. It is found that sea spray organic aerosols (SSOA) are the most important type of ice nucleating particles (INPs) over the SO with concentrations one order of magnitude higher than those of dust INPs based on measurements and CESM2 simulations. Secondary ice production (SIP) which includes riming splintering, rain droplet shattering, and ice-ice collisional fragmentation as implemented in CESM2 is the dominant ice production process in moderately cold clouds with cloud temperatures greater than –20°C. SIP enhances the in-cloud ice number concentrations (Ni) by 1-3 orders of magnitude and predicts more mixed-phase (with percentage occurrence increased from 15% to 21%), in better agreement with the observations. Finally, this study highlights the importance of accurately representing cloud phase over the pristine remote SO by considering the ice nucleation of SSOA and SIP processes, which are currently missing in most GCM cloud microphysics parameterizations.

54 ENVIRONMENTAL SCIENCES↗