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At least 775 records · Page 43

CyBORG: An ORIGEN-Based Reactor Analysis Capability for Cyclus

One of the key weaknesses of many current nuclear fuel cycle simulation tools is in the inability to treat reactor-based materials feedbacks within fuel cycle systems. Rather, many of these tools rely on user-provided 'recipes' to describe the fission and transmutation of materials within a reactor. While sufficient for steady-state simulations (such as fuel cycle options at equilibrium), recipe-based models fall short when attempting to evaluate fuel cycle systems under transition. For example, within the context of the Fuel Cycle Options Evaluation and Screening Study, fuel cycle options such as EG29 (fast critical systems with a conversion ratio greater than unity which would drive thermal critical systems with recovered U and Pu) require physics-based treatments of materials within reactors in order to capture the full dynamics of material transformations within such actinide-based recycle scenarios. Similarly, other physics-based questions include system perturbations such as changing average fleet discharge burnup as well as accurate evaluations of available fuel materials to support fuel cycle transitions. In order to provide fuel cycle analysis the ability to evaluate these types of scenarios, a new ORIGEN-based reactor module for the Cyclus nuclear fuel cycle simulator is being developed known as CyBORG (Cyclus-Based ORiGen). CyBORG leverages recent modernization efforts in the Origen API to allow users to directly employ ORIGEN's validated depletion capabilities and extensive nuclear fuel data libraries in order to perform dynamic, physics-based reactor transformations to fuel materials within a fuel cycle simulation context. This paper will provide a summary of recent developments in this effort, including its present and proposed capabilities and overall design strategy. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Vehicle energy consumption estimation using large scale simulations and machine learning methods

Vehicle energy consumption and powertrain operations for future vehicle powertrain technologies are predicted through full-vehicle simulations using Autonomie, a simulation tool developed at Argonne National Laboratory. Over 1 million vehicles, with different powertrain types (conventional and numerous electrified powertrains) and component technologies (advanced engines, batteries, electrical machines, light weighting) are simulated for outputs including vehicle fuel economy and cost. Despite the ability of Autonomic to predict fuel economy given various combination of vehicle inputs, the full-vehicle simulation is very time-consuming. It takes approximately 84 h to simulate for 33,060 vehicles even using distributed computing on a cluster of 128 worker nodes. Moreover, Autonomic is unable to populate a continuous output space through simulation since it only yields outputs with discrete values instead of an input-output relation. This paper proposes a novel large-scale learning and prediction process (LSLPP) via machine learning approaches to answer the need for a continuous space of vehicle fuel economy and a more efficient simulation process. By learning in a supervised fashion to discover structures in data, the machine learning approaches seek to train a model that can explain the data with which we can perform prediction over unseen data. As such, we are able to accomplish analytic continuation on the current discrete space of simulation results. In addition, we present a random sampling -based numerosity reduction algorithm incorporated in LSLPP that reduces simulation runs and improves efficiency of data procurement. We analytically derive a theoretical bound in order to guarantee the effectiveness of our algorithm. We also compare random sampling to stratified sampling and suggest sampling strategies. A user-friendly tool is developed to support the process. Our experimental results confirm that the proposed LSLPP is able to greatly accelerate prediction and analysis of vehicle fuel economy. The output of this study is used by the US government to evaluate the impact of its R&D funding on energy security and CO 2 emission as well as for the setting of Corporate Average Fuel Economy (CAFE) standards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Machine learning for surrogate process models of bioproduction pathways

Technoeconomic analysis and life-cycle assessment are critical to guiding and prioritizing bench-scale experiments and to evaluating economic and environmental performance of biofuel or biochemical production processes at scale. Traditionally, commercial process simulation tools have been used to develop detailed models for these purposes. However, developing and running such models can be costly and computationally intensive, which limits the degree to which they can be shared and reproduced in the broader research community. This study evaluates the potential of an automated machine learning approach to develop surrogate models based on conventional process simulation models. The analysis focuses on several high-value biofuels and bioproducts for which pathways of production from biomass feedstocks have been well-established. The results demonstrate that surrogate models can be an accurate and effective tool for approximating the cost, mass and energy balance outputs of more complex process simulations at a fraction of the computational expense.

09 BIOMASS FUELS↗

Modeling and Analysis of the Reverse Water Gas Shift Process for In-Situ Propellant Production

This report focuses on the development of mathematical models and simulation tools developed for the Reverse Water Gas Shift (RWGS) process. This process is a candidate technology for oxygen production on Mars under the In-Situ Propellant Production (ISPP) project. An analysis of the RWGS process was performed using a material balance for the system. The material balance is very complex due to the downstream separations and subsequent recycle inherent with the process. A numerical simulation was developed for the RWGS process to provide a tool for analysis and optimization of experimental hardware, which will be constructed later this year at Kennedy Space Center (KSC). Attempts to solve the material balance for the system, which can be defined by 27 nonlinear equations, initially failed. A convergence scheme was developed which led to successful solution of the material balance, however the simplified equations used for the gas separation membrane were found insufficient. Additional more rigorous models were successfully developed and solved for the membrane separation. Sample results from these models are included in this report, with recommendations for experimental work needed for model validation.

Whitlow, Jonathan E.↗

Accelerating Lipidomic Method Development through in Silico Simulation

Judicious selection of mass spectrometry (MS) acquisition parameters is essential for effectively profiling the broad diversity and dynamic range of biomolecules. Typically, acquisition parameters are individually optimized to maximally characterize analytes from each new sample matrix. This time-consuming process often ignores the synergistic relationship between MS method parameters, producing suboptimal results. Here in this paper, we detail the creation of an algorithm which accurately simulates LC-MS/MS lipidomic data acquisition performance for a benchtop quadrupole-Orbitrap MS system. By coupling this simulation tool with a genetic algorithm for constrained parameter optimization, we demonstrate the efficient identification of LC-MS/MS method parameter sets individually suited for specific sample matrices. Finally, we utilize the in silico simulation to examine how continued developments in MS acquisition speed and sensitivity will further increase the power of MS lipidomics as a vital tool for impactful biochemical analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sockeye: A One-Dimensional, Two-Phase, Compressible Flow Heat Pipe Application

Sockeye is a heat pipe analysis application based on the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element framework. The primary purpose of Sockeye is to provide a transient heat pipe simulation tool to be used in the analysis of nuclear microreactor designs. Sockeye provides the capability to perform one-dimensional, two-phase, compressible flow simulation of a heat pipe working fluid and two-dimensional, axisymmetric heat conduction for the heat pipe cladding and its surroundings. Sockeye is demonstrated against analytical solutions and experimental data from the SAFE-30 heat pipe module test.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

BDEM (Discrete-element-simulator for high-solids granular flows) [SWR-22-72]

BDEM is a discrete element method based simulation tool developed specifically for modeling high-solids granular flows that include polydispersity, heat-transfer, moving boundaries and chemistry. Our solver provides facilities for simulating spherical/non-spherical particles with modified contact and friction models in complex dynamic geometries defined using level-sets or triangulated files. The solver is developed on top of NREL's open-source performance portable library, AMReX, providing parallel execution capabilities on current and upcoming high-performance-computing (HPC) architectures. Simulations at the scale of several millions to billion particles have been performed using this software on large scale computing resources. This software can be applied to non-reacting solids dominant flows in silos, hoppers and screw conveyors as well as in high temperature reacting systems such as screw kilns and auger reactors.

Sitaraman, Hariswaran↗

CoCoMANS Ocean App [Slides]

Thermohaline circulation is that part of ocean circulation which is driven by density gradients. It is widely believed that changes in the ocean thermohaline circulation on the 10 to 100 year time scale can instigate rapid climate change. Scientists world wide are currently using simulation tools based on semi-implicit and split methods that are first-order in time. From a numerical error perspective, the quality of such simulations is suspect. As a result of numerical stability issues resulting from semi-implicit and split methods they are forced to use low resolution grids; ie high resolution grids will require prohibitive numbers of timesteps. Having the ability to perform such simulation with reduced splitting errors, using high resolution grids, and using second-order accurate time integration methods will be a quantum leap forward in predictive ocean simulation.

36 MATERIALS SCIENCE↗

5G-TSN Architecture Capable of Providing Real-time Situational Awareness to Fossil-Energy (FE) Generation Systems (Final Technical Report)

This final report highlights the comprehensive achievements of the project focused on developing and validating a 5G-Time Sensitive Networking (TSN) architecture tailored for real-time operational awareness in fossil energy systems. The initiative successfully advanced through a series of technical milestones, including the integration of EMI-aware network models, deployment of advanced simulation frameworks, and real-world performance characterization at key sites such as UTEP and Fabens. Through the strategic use of NetSim® software, the team created and validated network configurations for wired and wireless environments, tested under varying congestion conditions, and verified network slicing implementations for URLLC-specific applications. Major accomplishments include the migration of simulation tools to the latest NetSim® version to support accurate modeling of TSN and network slicing, extensive EMI measurement campaigns, and the development of a robust simulation model for end-to-end SCADA system integration. Simulations compared both TDD and FDD duplexing modes, revealing insights into their performance under congested conditions. The wireless network was benchmarked for throughput, jitter, and delay metrics, aligning with 3GPP Release 15/16 and IEEE 802.1-TSN standards. A peer-reviewed conference paper was accepted and published, contributing to the broader academic and industrial discourse on 5G-TSN integration in energy systems, in addition to a journal article. Despite minor delays due to software limitations, the project achieved its objectives and delivered validated architecture ready for deployment in advanced energy network environments.

01 COAL, LIGNITE, AND PEAT↗

Development of a VOR/DME model for an advanced concepts simulator

The report presents a definition of a VOR/DME, airborne and ground systems simulation model. This description was drafted in response to a need in the creation of an advanced concepts simulation in which flight station design for the 1980 era can be postulated and examined. The simulation model described herein provides a reasonable representation of VOR/DME station in the continental United States including area coverage by type and noise errors. The detail in which the model has been cast provides the interested researcher with a moderate fidelity level simulator tool for conducting research and evaluation of navigator algorithms. Assumptions made within the development are listed and place certain responsibilities (data bases, communication with other simulation modules, uniform round earth, etc.) upon the researcher.

Steinmetz, G. G.↗

Simulation of Inviscid Compressible Multi-Phase Flow with Condensation

Condensation of vapours in rapid expansions of compressible gases is investigated. In the case of high temperature gradients the condensation will start at conditions well away from thermodynamic equilibrium of the fluid. In those cases homogeneous condensation is dominant over heterogeneous condensation. The present work is concerned with development of a simulation tool for computation of high speed compressible flows with homogeneous condensation. The resulting ow solver should preferably be accurate and robust to be used for simulation of industrial flows in general geometries.

Kelleners, Philip↗

Analysis of Roll Steering for Solar Electric Propulsion Missions

Nothing is more vital to a spacecraft than power. Solar Electric Propulsion (SEP) uses that power to provide a safe, reliable, and, most importantly, fuel efficient means to propel a spacecraft to its destination. The power performance of an SEP vehicle s solar arrays and electrical power system (EPS) is largely influenced by the environment in which the spacecraft is operating. One of the most important factors that determines solar array power performance is how directly the arrays are pointed to the sun. To get the most power from the solar arrays, the obvious solution is to point them directly at the sun at all times. Doing so is not a problem in deep space, as the environment and pointing conditions that a spacecraft faces are fairly constant and are easy to accommodate, if necessary. However, large and sometimes rapid variations in environmental and pointing conditions are experienced by Earth orbiting spacecraft. SEP spacecraft also have the additional constraint of needing to keep the thrust vector aligned with the velocity vector. Thus, it is important to analyze solar array power performance for any vehicle that spends an extended amount of time orbiting the Earth, and to determine how much off-pointing can be tolerated to produce the required power for a given spacecraft. This paper documents the benefits and drawbacks of perfectly pointing the solar arrays of an SEP spacecraft spiraling from Earth orbit, and how this might be accomplished. Benefits and drawbacks are defined in terms of vehicle mass, power, volume, complexity, and cost. This paper will also look at the application of various solar array pointing methods to future missions. One such pointing method of interest is called roll steering . Roll steering involves rolling the entire vehicle twice each orbit. Roll steering, combined with solar array gimbal tracking, is used to point the solar arrays perfectly towards the sun at all points in the orbit, while keeping the vehicle thrusters aligned in the velocity direction. Roll steering is particularly attractive for a recently proposed mission that involves a spiral trajectory from low Earth orbit (LEO) to the Earth-Moon Lagrange Point 1 (E-M L1). During the spiral, the spacecraft will spend over 300 days experiencing the full spectrum of near-earth environments and solar array pointing conditions. An extensive study of the application of SEP (and roll steering) to this spiral mission is included, highlighting the ultimate goal of reduced vehicle cost and mass. Tools used for this analysis include the Systems Power Analysis for Capability Evaluation (Refs. 1 and 2) (SPACE) electrical power systems code, and SEP trajectory simulation tools developed at NASA Glenn Research Center.

Pederson, Dylan, M.↗

Optimization of Elastodynamic Finite Integration Technique on Intel Xeon Phi Knights Landing Processors

This work describes the development and optimization of an implementation of an isotropic elastodynamic finite integration technique (EFIT) code for parallelized computation on Intel Knights Landing (KNL) hardware. EFIT is a numerical approach resulting in standard staggered-grid finite difference equations for the elastodynamic equations of motion to simulate bulk waves is solids. The computationally efficient simulation of elastodynamic wave propagation and interactions in aerospace materials is of high-interest in the fields of nondestructive evaluation (NDE) and structural health monitoring (SHM). Ultrasonic inspection uses an ultrasonic signal, generated at the surface of the material/structure via use of a piezoelectric transducer, to propagate sound waves into the material where it interacts with any existing defects, as well as with structural boundaries and any material inhomogeneity. Reflections from defects and boundaries are then measured by a transducer. Realistic ultrasound simulation tools can significantly aid the development and optimization of inspection techniques and can assist in the interpretation of experimental data. The optimization of an elastodynamics simulation code for the KNL Many Integrated Core processor was performed. The optimization focused on data locality and vectorization. Results show that tiling of the data to exploit the cache behavior and allow for significant utilization of the KNL hardware. The MPI implementation allows for a scalable implementation enabling large problems to be simulated. The model results were validated against theoretical dispersion curves to within 2% of the group velocity, and within 0.5% of the phase velocity of the A0 mode. Aggressive use of tiling, threading, and vectorization techniques allowed for dramatically improved time to solution.

William C. Schneck↗

Impact of Heaters on Molten Salt Reactors Dynamics

Recently, there has been renewed interest in the Molten Salt Reactor (MSR) concept. This interest is mainly due to its advantages over Light Water Reactors (LWRs). Among these advantages are the flexibility in the fuel choice and the possibility to burn actinides [1]. Currently, two molten research reactors are under development. A 2 MW molten salt experimental reactor has been constructed and is planned for operation in China. A 1 MW Molten Salt Research Reactor is under construction in the United States [2]. Thus, Research and Development (R&D) programs are needed for the MSR technology. Reactor dynamics studies are crucial safety evaluation studies. The development of reactor dynamics tools for MSRs started during the Molten Salt Reactor Program (MSRP) at ORNL, focusing on the Molten Salt Reactor Experiment (MSRE) [3]. Although various dynamic simulation tools are available, R&D efforts to develop specialized tools for MSRs are still ongoing [4]. The primary motivation for this interest is the goal of commercializing MSRs. Developing a dynamics tool for MSRs is crucial for analyzing their safety and supporting their demonstration efforts. A crucial safety issue in MSRs is ensuring that the fuel salt in the primary loop remains molten. This concern becomes particularly important when the reactor operates at lower power levels. Most chloride and fluoride salts used as fuel have a melting point of approximately 450 °C [5]. Therefore, maintaining fuel salt temperatures above this melting point is essential to prevent it from freezing. Freezing of the fuel salt can lead to volume expansion, potentially causing damage to reactor components [6]. Moreover, it can create local blockages within fuel salt channels, reducing cooling efficiency and resulting in hot spots [7]. Various methods can prevent fuel salt from freezing at low power levels. These include reducing the fuel mass flow rate in the primary loop, decreasing heat exchange between the primary and secondary loops in the reactor, and using electric fuel salt heaters. Reducing the mass flow rate of fuel salt in the primary loop can increase the fuel salt transit time in the core, enhancing heat production and increasing temperature. However, it can potentially lead to challenges. These include increasing the potential for fuel salt deposition on the reactor channel walls [8], affecting the overall heat transfer processes. Thus, alternative methods should be used [9]. This research investigates the effects of fuel salt heaters on the dynamics and stability during MSR operation. The investigation includes studying the reactor stability with the fuel salt heaters on and off. In addition, the reactor response to transients is compared with and without the operation of fuel salt heaters. These transients include reactivity insertion, primary and secondary pump failure, and heat sink temperature increase. The results of the reactivity insertion transient are presented in the summary.

73 - NUCLEAR PHYSICS AND RADIATION PHYSICS↗

SAM Code Enhancements for Modeling of Liquid Metal-Cooled Fast Reactor Concepts

The SAM code is under development and supported by DOE-NE’s Nuclear Energy Advanced Modeling and Simulation program as a modern system-level modeling and simulation tool for advanced non-light water reactor safety analyses. These advanced reactor concepts incorporate novel and improved approaches to achieve safety and economic feasibility. This report summarizes two major efforts in addressing the modeling gaps in SAM for liquid-metal-cooled fast reactor (LMFR) applications, i.e. thermal mixing and stratification phenomena in large pools and corrosion-oxidation of components in flowing lead. A new one-dimensional model for thermal mixing and stratification effects in large pools and enclosures is developed and implemented. Thermal mixing and stratification occur when fluid enters a pool at a temperature different than the bulk fluid itself, a scenario often encountered during transients in pool-type systems. These phenomena are critical for the safety of reactors, impacting phenomena like natural circulation, which is essential for passive cooling. The improved model in SAM addresses limitations of state-of-the-art approaches by combining one-dimensional (1D) channels, representing the coolant jet flow, with lumped-parameter zero-dimensional (0D) pools, representing the rest of coolant in the tank. Energy exchange between the 1D jet and the 0D pools is based on heat transfer correlations calibrated against 3D simulations. It is verified that this model can handle various flow configurations, including hot jets in colder pools, cold jets in hotter pools, and the presence of features like ceilings, free surfaces, and obstacles. Additionally, validation against experimental data demonstrates the ability of the model to capture mixing and stratification effects in a wide range of conditions. The flexibility and improved accuracy of the new model make it a valuable tool for reactor safety analysis, allowing for the simulation of different geometries encountered in advanced reactors. A system-level corrosion modeling capability is developed and implemented in SAM to support Lead Fast Reactor (LFR) development. Although the initial focus of this capability will be on LFR application, this can later be expanded to include other liquid metals such as Lead-Bismuth Eutectic (LBE) and PbLi. This report summarizes the common corrosion mitigation strategies and outlines the progress on implementing and validating a corrosion-oxidation model in SAM. Verification and validation of the corrosion-oxidation portion of the model was performed using analytical solution and measured data from samples tested in the non-isothermal pumped lead loop at IPPE Obninsk. The iron transport and corrosion/precipitation portion of the model was assessed using an analytical model and measured corrosion depths from a natural convection lead loop experiment performed at CEA. It is demonstrated that the model implemented in SAM performed well in these assessments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Microstructure Modeling of Third Generation Disk Alloys

The objective of this program was to model, validate, and predict the precipitation microstructure evolution, using PrecipiCalc (QuesTek Innovations LLC) software, for 3rd generation Ni-based gas turbine disc superalloys during processing and service, with a set of logical and consistent experiments and characterizations. Furthermore, within this program, the originally research-oriented microstructure simulation tool was to be further improved and implemented to be a useful and user-friendly engineering tool. In this report, the key accomplishments achieved during the third year (2009) of the program are summarized. The activities of this year included: Further development of multistep precipitation simulation framework for gamma prime microstructure evolution during heat treatment; Calibration and validation of gamma prime microstructure modeling with supersolvus heat treated LSHR; Modeling of the microstructure evolution of the minor phases, particularly carbides, during isothermal aging, representing the long term microstructure stability during thermal exposure; and the implementation of software tools. During the research and development efforts to extend the precipitation microstructure modeling and prediction capability in this 3-year program, we identified a hurdle, related to slow gamma prime coarsening rate, with no satisfactory scientific explanation currently available. It is desirable to raise this issue to the Ni-based superalloys research community, with hope that in future there will be a mechanistic understanding and physics-based treatment to overcome the hurdle. In the mean time, an empirical correction factor was developed in this modeling effort to capture the experimental observations.

Jou, Herng-Jeng↗

A labeled dataset for building HVAC systems operating in faulted and fault-free states

Abstract Open data is fueling innovation across many fields. In the domain of building science, datasets that can be used to inform the development of operational applications - for example new control algorithms and performance analysis methods - are extremely difficult to come by. This article summarizes the development and content of the largest known public dataset of building system operations in faulted and fault free states. It covers the most common HVAC systems and configurations in commercial buildings, across a range of climates, fault types, and fault severities. The time series points that are contained in the dataset include measurements that are commonly encountered in existing buildings as well as some that are less typical. Simulation tools, experimental test facilities, and in-situ field operation were used to generate the data. To inform more data-hungry algorithms, most of the simulated data cover a year of operation for each fault-severity combination. The data set is a significant expansion of that first published by the lead authors in 2020.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Development of an Optimized Gasoline Surrogate Formulation for PACE Experiments and Simulations

New powertrain solutions are needed to address societal challenges stemming in part from a transportation sector which relies heavily on combustion of conventional hydrocarbon fuels like gasoline. One way to advance new solutions is through predictive simulations. Predictive simulations can potentially limit the extent of experimental validations, reduce time spent in engineering design cycles, unlock new strategies for high efficiency combustion with power density, and minimize tailpipe emissions. However, the simulation tools currently available are either too computationally expensive, inadequate in their accuracy, or a combination of the two. A DOE-funded consortium of national laboratories called the Partnership to Advance Combustion Engines (PACE) seeks to address this gap by rapidly delivering new knowledge and tools which enable market-competitive powertrain solutions for light-duty vehicles. Approaches to modeling combustion in powertrain systems typically incorporate computational fluid dynamics (CFD) simulations with chemical kinetic models. These CFD simulations generally use surrogate fuels featuring a limited number of existing components in a reduced kinetic model to limit computational costs. Such surrogate fuels often sacrifice matching several or more combustion and physical properties of the target gasoline fuel. Validation of surrogate fuels is also often only pursued for a small subset of standard metrics such as research or motor octane number (RON, MON). The purpose of this project is to develop an optimal E10 gasoline surrogate fuel suitable for tasks across PACE to facilitate rapid common analysis and progression toward consortium goals. This project received contributions from tasks led by eight PACE principal investigators. The project funding here reflects all tasks under Pitz, whose tasks also contributed to additional PACE projects. Based on the optimal gasoline surrogate fuel composition, a reduced chemical kinetic model will be shared with PACE researchers, industry, and the broader combustion community.

33 ADVANCED PROPULSION SYSTEMS↗