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At least 1,243 records · Page 69

Terry Turbopump Expanded Operating Band Modeling and Simulation Efforts in Fiscal Year 2020 - Progress Report

The Terry Turbine Expanded Operating Band Project is currently conducting testing at Texas A&M University as part of a revised experimental program meant to supplant previous full-scale testing plans under the headings of Milestone 5 and Milestone 6. In consultation with Sandia National Laboratories technical staff and with modeling and simulation support from the same, the hybrid Milestone 5&6 plan is moving forward with experiments aimed at addressing knowledge gaps regarding scale, working fluid, and turbopump self-regulation. Modeling and simulation efforts at Sandia National Laboratories in FY20 fell under the broad umbrella of Milestone 7 and consisted exclusively of MELCOR-related tasks aimed at: 1) Constructing/improving input models of Texas A&M University experiments, 2) Constructing a generic boiling water reactor input model according to best practices with systems-level Teny turbine capabilities, and 3) Adding code capability in order to leverage experimental data/findings, address bugs, and improve general code robustness Project impacts of the Covid-19 pandemic have fortunately been minimal thus far but are mentioned as necessary when discussing the hybrid Milestone 5&6 progress as well as the corresponding Milestone 7 modeling and simulation progress.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Simulation and model reduction for the AFW program

The simulation methodology used in the Active Flexible Wing wind-tunnel test program is described. An overview of the aeroservoelastic modeling used in building the required batch and hot-bench simulations is presented. Successful hot-bench implementation required that the full mathematical model be significantly reduced while assuring that accuracy be maintained for all combinations of 10 inputs and 56 outputs. The reduction was accomplished by using a method based on internally balanced realizations and focussing on the linear, aeroelastic portion of the full mathematical model. The error-bound properties of the internally balanced realization significantly contribute to its utility in the model reduction process. The reduction method and the results achieved are described.

Buttrill, Carey↗

Multiple-relaxation-time color-gradient lattice Boltzmann model for simulating two-phase flows with high density ratio

In this paper, we propose a color-gradient lattice Boltzmann (LB) model for simulating two-phase flows with high density ratio and high Reynolds number. The model applies a multi-relaxation-time (MRT) collision operator to enhance the stability of the simulation. A source term, which is derived by the Chapman-Enskog analysis, is added into the MRT LB equation so that the Navier-Stokes equations can be exactly recovered. Also, a new form of the equilibrium density distribution function is used to simplify the source term. To validate the proposed model, steady flows of a static droplet and the layered channel flow are first simulated with density ratios up to 1000. Small values of spurious velocities and interfacial tension errors are found in the static droplet test, and improved profiles of velocity are obtained by the present model in simulating channel flows. Then, two cases of unsteady flows, Rayleigh-Taylor instability and droplet splashing on a thin film, are simulated. In the former case, the density ratio of 3 and Reynolds numbers of 256 and 2048 are considered. The interface shapes and spike/bubble positions are in good agreement with the results of previous studies. In the latter case, the droplet spreading radius is found to obey the power law proposed in previous studies for the density ratio of 100 and Reynolds number up to 500.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Enhancing Modeling and Simulation for Effective Protection Strategies

This report was created by Sandia National Laboratories (SNL) to document the principles and methodology of performance data collection and integration with modeling and simulation tools to better facilitate the performance evaluation of physical protection systems (PPS). Results and conclusions from the use of modeling and simulation tools are only as good as the data employed by the tools when conducting analysis. Acquiring the performance testing data necessary to ensure effective evaluation can be a complex and sometimes daunting process. It is the desire of the organization to provide guidance that eases the burdens associated with pursuit of these objectives. This document draws heavily upon longstanding principles of systems engineering that have been developed and employed by SNL in the discipline of security since the 1970s. The scope of this document is constrained to the testing of system components and integration of data that is applicable within the context of PPS performance analysis using two tools that have been developed by SNL, PathTrace© and Scribe3D©. For guidance related to testing and evaluation more broadly, the manuals and reports referenced by this document can be consulted.

42 ENGINEERING↗

Efficient Optimization of Energy Recovery From Geothermal Reservoirs With Recurrent Neural Network Predictive Models

Improving the long-term energy production performance of geothermal reservoirs can be accomplished by optimizing field development and management plans. Reliable prediction models, however, are needed to evaluate and optimize the performance of the underlying reservoirs under various operation and development strategies. In traditional frameworks, physics-based simulation models are used to predict the energy production performance of geothermal reservoirs. However, detailed simulation models are not trivial to construct, require a reliable description of the reservoir conditions and properties, and entail high computational complexity. Data-driven predictive models can offer an efficient alternative for use in optimization workflows. This paper presents an optimization framework for net power generation in geothermal reservoirs using a variant of the recurrent neural network (RNN) as a data-driven predictive model. The RNN architecture is developed and trained to replace the simulation model for computationally efficient prediction of the objective function and its gradients with respect to the well control variables. The net power generation performance of the field is optimized by automatically adjusting the mass flow rate of production and injection wells over 12 years, using a gradient-based local search algorithm. Two field-scale examples are presented to investigate the performance of the developed data-driven prediction and optimization framework. Furthermore, the prediction and optimization results from the RNN model are evaluated through comparison with the results obtained by using a numerical simulation model of a real geothermal reservoir.

15 GEOTHERMAL ENERGY↗

Additive Manufacturing Modeling and Simulation A Literature Review for Electron Beam Free Form Fabrication

Additive manufacturing is coming into industrial use and has several desirable attributes. Control of the deposition remains a complex challenge, and so this literature review was initiated to capture current modeling efforts in the field of additive manufacturing. This paper summarizes about 10 years of modeling and simulation related to both welding and additive manufacturing. The goals were to learn who is doing what in modeling and simulation, to summarize various approaches taken to create models, and to identify research gaps. Later sections in the report summarize implications for closed-loop-control of the process, implications for local research efforts, and implications for local modeling efforts.

Seufzer, William J.↗

Modeling and Simulation to Support Current and Advanced Reactors : Thermal Hydraulics

Presentation on thermohydraulic modeling and simulation capabilities in support of current and advanced reactors. The presentation includes information on the capabilities of RELAP5-3D, MOOSE and the experimental testbed for this purpose. This presentation is intended for a Taiwan delegation that will be visiting INL in August 2024.

42 ENGINEERING↗

Reduction of a detailed soot model for simulations of pyrolysing solid fuels

Here, we introduce a computationally inexpensive soot formation model for use in simulating large solid-complex fuel systems. The proposed model evaluates three variables: number density of tars, bulk mass density of soot particles, and particle number density. Each of these variables are influenced by soot formation phenomena, and this model evaluates the most common of these phenomena: soot nucleation, surface reactions, and coagulation. Two separate simulations were carried out using this model and results were compared against simulations using a more detailed and computationally expensive model. Findings are promising and show a meaningful reduction in model complexity and computational cost while still giving comparable results.

58 GEOSCIENCES↗

Integrating O/S models during conceptual design, part 1

The University of Dayton is pleased to submit this report to the National Aeronautics and Space Administration (NASA), Langley Research Center, which integrates a set of models for determining operational capabilities and support requirements during the conceptual design of proposed space systems. This research provides for the integration of the reliability and maintainability (R&M) model, both new and existing simulation models, and existing operations and support (O&S) costing equations in arriving at a complete analysis methodology. Details concerning the R&M model and the O&S costing model may be found in previous reports accomplished under this grant (NASA Research Grant NAG1-1327). In the process of developing this comprehensive analysis approach, significant enhancements were made to the R&M model, updates to the O&S costing model were accomplished, and a new simulation model developed. This is the 1st part of a 3 part technical report.

Ebeling, Charles E.↗

Dynamic Simulation of a Periodic 10 K Sorption Cryocooler

A transient thermal simulation model has been developed to simulate the dynamic performance of a multiple-stage 10 K sorption cryocooler for spacecraft sensor cooling applications that require periodic quick-cooldown (under 2 minutes) , negligible vibration, low power consumption, and long life (5 to 10 years). The model was specifically designed to represent the Brilliant Eyes Ten-Kelvin Sorption Cryocooler Experiment (BETSCE), but it can be adapted to represent other sorption cryocooler systems as well. The model simulates the heat transfer, mass transfer, and thermodynamic processes in the cryostat and the sorbent beds for the entire refrigeration cycle, and includes the transient effects of variable hydrogen supply pressures due to expansion and overflow of hydrogen during the cooldown operation. The paper describes model limitations and simplifying assumptions, with estimates of errors induced by them, and presents comparisons of performance predictions with ground experiments. An important benefit of the model is its ability to predict performance sensitivities to variations of key design and operational parameters. The insights thus obtained are expected to lead to higher efficiencies and lower weights for future designs.

cryocooler design performance sorption simulation ↗

Modeling and Simulation of Trapping Mechanisms of Granular Media in Space

This paper describes the modeling and simulation of trapped granular media, within the context of the Granular Imager project. We describe the physics of trapped granular media in space, and the methodologies used to stably confine and shape such a medium using electromagnetic fields. The numerical models have also been validated with results in the literature, obtaining excellent agreement. The results of the numerical tests indicate that it is possible, with structural arrangements of rings and plates at different levels of electrostatic potential, to stably confine one or more charged particles, when driven by voltages that can be modulated in time and space.

Quadrelli, Marco B.↗

Modeling and Simulation of a Parallel Hybrid-Electric Propulsion System - Electrified Powertrain Flight Demonstration (EPFD) Program

Electrified aircraft propulsion concepts have been proposed to meet aggressive future performance and environmental goals for the next generation of aircraft. However, electrified aircraft present a unique modeling and simulation challenge as they introduce multiple energy sources to the propulsion system, providing various means to meet thrust requirements, compared to conventional gas turbine propulsion architectures where only fuel is available. Additionally, the introduction of an electric powertrain to the existing system enables multiple electrified flight modes to exist (i.e. eTaxi, climb boost, takeoff boost, etc.), further increasing the complexity of the modeling environment. As part of the Electrified Powertrain Flight Demonstration program, this paper presents a modeling and simulation framework for a parallel hybrid-electric propulsion concept using the Environmental Design Space simulation tool. Electrical components are modeled in NPSS, and an overall sizing methodology is introduced. Finally, various operational modes of the electric powertrain are modeled and tested and their impact on key performance parameters is evaluated.

hybrid electric propulsion↗

Status on the Development of a Modeling and Simulation Framework for the Economic Assessment of Nuclear Hybrid Energy

Continued effort to design and build a modeling and simulation framework to assess the economic viability of Nuclear Hybrid Energy Systems (NHES) was undertaken in fiscal year (FY) 2016. The purpose of this report is to document the various tasks associated with the development of such a framework and to provide a status of their progress. Several tasks have been accomplished. First, a synthetic time history generator has been developed in RAVEN, which consists of Fourier series and autoregressive moving average model. The former is used to capture the seasonal trend in historical data, while the latter is to characterize the autocorrelation in residue time series (e.g., measurements with seasonal trends subtracted). As demonstration, both synthetic wind speed and grid demand are generated, showing matching statistics with database. In order to build a design and operations optimizer in RAVEN, a new type of sampler has been developed with highly object-oriented design. In particular, simultaneous perturbation stochastic approximation algorithm is implemented. The optimizer is capable to drive the model to optimize a scalar objective function without constraint in the input space, while the constraints handling is a work in progress and will be implemented to improve the optimization capability. Furthermore, a simplified cash flow model of the performance of an NHES in the electric market has been developed in Python and used as external model in RAVEN to confirm expectations on the analysis capability of RAVEN to provide insight into system economics and to test the capability of RAVEN to identify limit surfaces. Finally, an example calculation is performed that shows the integration and proper data passing in RAVEN of the synthetic time history generator, the cash flow model and the optimizer. It has been shown that the developed Python models external to RAVEN are able to communicate with RAVEN and each other through the newly developed RAVEN capability called “EnsembleModel”.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Distributed Macroscopic Traffic Simulation with Open Traffic Models

This paper presents OTM-MPI, an extension of the Open Traffic Models platform (OTM) for running macroscopic traffic simulations in high-performance computing environments. OTM-MPI represents the first open-source, distributed-memory, macroscopic simulation model developed for modern high performance parallel machines and large networks. Macroscopic simulations are appropriate for studying regional traffic scenarios when aggregate trends are of interest, rather than individual vehicle traces. They are also appropriate for studying the routing behavior of classes of vehicles, such as app-informed vehicles. The network partitioning was performed with METIS. Inter-process communication was done with MPI (message-passing interface). Results are provided for two networks: one realistic network which was obtained from Open Street Maps for Chattanooga, TN, and another larger synthetic grid network. The software recorded a speedups of 198x using 256 cores for Chattanooga, and 475x with 1,024 cores for the synthetic network.

macro-scopic traffic simulation↗