Hypersonics at Sandia National Laboratories
Brief overview of Hypersonics with emphasis on fluid mechanics at Sandia
Wagnild, Ross Martin [Sandia National Laboratories↗
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Results for “FLUID MECHANICS”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Thermal field reconstruction and compressive sensing using proper orthogonal decomposition
Model order reduction allows critical information about sensor placement and experiment design to be distilled from raw fluid mechanics simulation data. In many cases, sensed information in conjunction with reduced order models can also be used to regenerate full field variables. In this paper, a proper orthogonal decomposition (POD) inferencing method is extended to the modeling and compressive sensing of temperature, a scalar field variable. The method is applied to a simulated, critically stable, incompressible flow over a heated cylinder (Re = 1000) with Prandtl number varying between 0.001 and 50. The model is trained on pressure and temperature data from simulations. Field reconstructions are then generated using data from selected sensors and the POD model. Finally, the reconstruction error is evaluated across all Prandtl numbers for different numbers of retained modes and sensors. The predicted trend of increasing reconstruction accuracy with decreasing Prandtl number is confirmed and a Prandtl number/sensor count error matrix is presented.
Matulis, John↗
A Novel CAE Method for Compression Molding Simulation of Carbon Fiber-Reinforced Thermoplastic Composite Sheet Materials
Its high-specific strength and stiffness with lower cost make discontinuous fiber-reinforced thermoplastic (FRT) materials an ideal choice for lightweight applications in the automotive industry. Compression molding is one of the preferred manufacturing processes for such materials as it offers the opportunity to maintain a longer fiber length and higher volume production. In the past, we have demonstrated that compression molding of FRT in bulk form can be simulated by treating melt flow as a continuum using the conservation of mass and momentum equations. However, the compression molding of such materials in sheet form using a similar approach does not work well. The assumption of melt flow as a continuum does not hold for such deformation processes. To address this challenge, we have developed a novel simulation approach. First, the draping of the sheet was simulated as a structural deformation using the explicit finite element approach. Next, the draped shape was compressed using fluid mechanics equations. The proposed method was verified by building a physical part and comparing the predicted fiber orientation and warpage measurements performed on the physical parts. The developed method and tools are expected to help in expediting the development of FRT parts, which will help achieve lightweight targets in the automotive industry.
36 MATERIALS SCIENCE↗
Gas Atomization of Molten Metal: Part I. Numerical Modeling Conception
This numerical analysis study entails creating and assessing a model that is capable of simulating molten metal droplets and the production of metal powder during the Gas Atomization (GA) method. The essential goal of this research aims to gather more information on simulating the process of creating metal powder. The model structure and perspective was built through the application of governing equations and aspects that utilized factors such as gas dynamics, droplet dynamics, energy balance, heat transfer, fluid mechanics and thermodynamics that were proposed from previous studies. The model is very simple and can be broken down into having a set of inputs to produce outputs. The inputs are the processing parameters such as the initial temperature of the metal alloy, the gas pressure and the size of the droplets. Additional inputs include the selection of the metal alloy and the atomization gas and factoring in their properties. The outputs can be designated by the velocity and thermal profiles of the droplet and gas. These profiles illustrate the speed of both as well as the rate of temperature change or cooling rate of the droplets. Here, the main focus is the temperature change and finding the right parameters to ensure that the metal powder is efficiently produced. Once the model was conceptualized and finalized, it was employed to verify the results of other previous studies.
36 MATERIALS SCIENCE↗
Gas Atomization of Molten Metal: Part II. Applications
A numerical model was derived to obtain results for two alloys during the Gas Atomization (GA) method. The model equations and governing equations were implemented through the application of part I data. Aspects such as heat transfer, fluid mechanics, thermodynamics and law of motions were taken into account for the formulation of equations that take gas dynamics, droplet dynamics and energy balance or conservation into consideration. The inputs of the model include: Processing parameters such as the size of the droplets, characteristics of the metal alloy, initial temperature of the molten metal, properties and fractions of the atomization gas and the gas pressure. The outputs include velocity and thermal profiles of the droplet and gas. Velocity profiles illustrate the velocity of both droplet and gas, while thermal profiles illustrate cooling rate and the rate of temperature change of the droplets. The alloys are gamma-Titanium Aluminide (γ-TiAl) and Al-3003-O. These alloys were selected due to the vast amount of applications both can have in several industries. Certain processing parameters were held constant, while others were altered. Furthermore, the main focus of this study was to gain insight into which optimal parameters should be utilized within the GA method for these alloys and to provide insight into the behavior of these alloys
36 MATERIALS SCIENCE↗
STATISTICAL DECOUPLING OF A LAGRANGIAN FLUID PARCEL IN NEWTONIAN COSMOLOGY
The Lagrangian dynamics of a single fluid element within a self-gravitational matter field is intrinsically non-local due to the presence of the tidal force. This complicates the theoretical investigation of the nonlinear evolution of various cosmic objects, e.g., dark matter halos, in the context of Lagrangian fluid dynamics, since fluid parcels with given initial density and shape may evolve differently depending on their environments. In this paper, we provide a statistical solution that could decouple this environmental dependence. After deriving the evolution equation for the probability distribution of the matter field, our method produces a set of closed ordinary differential equations whose solution is uniquely determined by the initial condition of the fluid element. Mathematically, it corresponds to the projected characteristic curve of the transport equation of the density-weighted probability density function (ρPDF). Consequently it is guaranteed that the one-point ρPDF would be preserved by evolving these local, yet nonlinear, curves with the same set of initial data as the real system. Physically, these trajectories describe the mean evolution averaged over all environments by substituting the tidal tensor with its conditional average. For Gaussian distributed dynamical variables, this mean tidal tensor is simply proportional to the velocity shear tensor, and the dynamical system would recover the prediction of the Zel’dovich approximation (ZA) with the further assumption of the linearized continuity equation. For a weakly non-Gaussian field, the averaged tidal tensor could be expanded perturbatively as a function of all relevant dynamical variables whose coefficients are determined by the statistics of the field.
79 ASTRONOMY AND ASTROPHYSICS↗
Developing extensible lattice-Boltzmann simulators for general-purpose graphics-processing units
Lattice-Boltzmann methods are versatile numerical modeling techniques capable of reproducing a wide variety of fluid-mechanical behavior. These methods are well suited to parallel implementation, particularly on the single-instruction multiple data (SIMD) parallel processing environments found in computer graphics processing units (GPUs). Although more recent programming tools dramatically improve the ease with which GPU programs can be written, the programming environment still lacks the flexibility available to more traditional CPU programs. In particular, it may be difficult to develop modular and extensible programs that require variable on-device functionality with current GPU architectures. This paper describes a process of automatic code generation that overcomes these difficulties for lattice-Boltzmann simulations. It details the development of GPU-based modules for an extensible lattice-Boltzmann simulation package - LBHydra. The performance of the automatically generated code is compared to equivalent purpose written codes for both single-phase, multiple-phase, and multiple-component flows. The flexibility of the new method is demonstrated by simulating a rising, dissolving droplet in a porous medium with user generated lattice-Boltzmann models and subroutines.
97 MATHEMATICS AND COMPUTING↗
Strategies for Assessment of the Biological Performance and Design of Hydroturbines
The biological response of fish to turbine passage has been of concern for several decades and emphasized recently by consideration of hydro as a 'green' power source. The current state-of-the-art of hydro-turbine biological performance assessment, while still inadequate, has advanced considerably the past 10 years. For example, the importance of assessment of exposure to pressure changes during turbine passage has been emphasized by findings of laboratory studies of rapid decompression. It is now very clear that hydroturbine biological assessment must consider the physiological state and behavior of fish at turbine entry and changes in physiological state that drive aspects of behavior during tailrace passage. Such considerations are in addition to concerns about exposure of fish to mechanical and pressure sources of injury during turbine passage. Experimental designs and assessment tools have evolved for acclimation of test fish, observation of test fish behavior at approach and upon exit from the turbine environment, and precise estimation of turbine passage mortality. Fish condition assessment continues to improve permitting better classification of observed injuries to injury mechanisms. Computational fluid dynamics (CFD) models and other computer models permit detailed investigation of the turbine passage environment and development of hypotheses that can be tested in field studies using live fish. Risk assessment techniques permit synthesis of laboratory and in-field study findings and estimation of population level effects over a wide range of turbine operation scenarios. Risk assessment is also evolving to provide input to turbine runner design. These developments, and others, have resulted in more productive biological performance assessment studies and will continue to evolve and improve the quantity and quality of information obtained from costly live fish hydroturbine passage studies. This paper reviews the history of hydro-turbine biological assessment, presents the current state-of-the-art, and identify areas needing improvement.
54 ENVIRONMENTAL SCIENCES↗
Developing extensible lattice-Boltzmann simulationsfor general-purpose graphics-programming units
Lattice-Boltzmann methods are versatile numerical modeling techniques capable of reproducing a wide variety of fluid-mechanical behavior. These methods are well suited to parallel implementation, particularly on the single-instruction multiple data (SIMD) parallel processing environments found in computer graphics processing units (GPUs). Although more recent programming tools dramatically improve the ease with which GPU programs can be written, the programming environment still lacks the flexibility available to more traditional CPU programs. In particular, it may be difficult to develop modular and extensible programs that require variable on-device functionality with current GPU architectures. This paper describes a process of automatic code generation that overcomes these difficulties for lattice-Boltzmann simulations. It details the development of GPU-based modules for an extensible lattice-Boltzmann simulation package - LBHydra. The performance of the automatically generated code is compared to equivalent purpose written codes for both single-phase, multiple-phase, and multiple-component flows. The flexibility of the new method is demonstrated by simulating a rising, dissolving droplet in a porous medium with user generated lattice-Boltzmann models and subroutines.
97 MATHEMATICS AND COMPUTING↗
Multiphysics analysis of liquid metal annular linear induction pumps: A project overview
Liquid metal-cooled fission reactors are both moderated and cooled by a liquid metal solution. These reactors are typically very compact and they can be used in regular electric power production, for naval and space propulsion systems or in fission surface power systems for planetary exploration. The coupling between the electromagnetics and thermo-fluid mechanical phenomena observed in liquid metal thermo-magnetic systems for nuclear and space applications gives rise to complex engineering magnetohydrodynamics and numerical problems. It is known that electromagnetic pumps have a number of advantages over rotating mechanisms: absence of moving parts, low noise and vibration level, simplicity of flow rate regulation, easy maintenance and so on. However, while developing annular linear induction pumps, we are faced with a significant problem of magnetohydrodynamic instability arising in the device. The complex flow behavior in this type of devices includes a time-varying Lorentz force and pressure pulsation due to the time-varying electromagnetic fields and the induced convective currents that originates from the liquid metal flow, leading to instability problems along the device geometry. The determinations of the geometry and electrical configuration of liquid metal thermo-magnetic devices give rise to a complex inverse magnetohydrodynamic field problem were techniques for global optimization should be used, magnetohydrodynamics instabilities understood –or quantified- and multiphysics models developed and analyzed. Lastly, we present a project overview as well as a few computational models developed to study liquid metal annular linear induction pumps using first principles and the a few results of our multi-physics analysis.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Fundamental Advancements in Pre-Chamber Spark Ignition and Emissions Control for Natural Gas Engines
Argonne National Laboratory, the National Renewable Energy Laboratory, Oak Ridge National Laboratory, and Sandia National Laboratories collaborated on research to address barriers for natural gas engine efficiency. This research project focuses on early stage research focusing on pre-chamber spark-ignition (PCSI) to achieve diesel-like efficiency in medium- and heavy-duty natural gas engines by extending the lean dilution limit and/or exhaust gas recirculation (EGR) dilution limit, as well as shortening burn duration, with integrated aftertreatment. This project integrates experimental and simulation based tasks to address four key barriers to market penetration of PCSI for medium- and heavy-duty natural gas engines. These include Inadequate science base and simulation tools to describe/predict the fluid-mechanical and chemical-kinetic processes governing PCSI to enable engineers in industry to optimize designs for efficiency, noise, reliability, pollutant formation, emissions control integration, and drivability; limited ability to extend EGR and/or lean dilution limits at higher loads; increased propensity for PCSI hot-spot pre-ignition at high loads relative to spark ignition; and ineffective methane catalysts for the high engine-out unburned fuel concentrations coupled with low exhaust temperatures (<<400 degrees C) of high efficiency engines.
33 ADVANCED PROPULSION SYSTEMS↗
Constructing and proving the ground state of a generalized Ising model by the cluster tree optimization algorithm
Generalized Ising models, also known as cluster expansions, are an important tool in many areas of condensed-matter physics and materials science, as they are often used in the study of lattice thermodynamics, solid-solid phase transitions, magnetic and thermal properties of solids, and fluid mechanics. However, the problem of finding the global ground state of generalized Ising model has remained unresolved, with only a limited number of results for simple systems known. We propose a method to efficiently find the periodic ground state of a generalized Ising model of arbitrary complexity by a new algorithm which we term cluster tree optimization. Importantly, we are able to show that even in the case of an aperiodic ground state, our algorithm produces a sequence of states with energy converging to the true ground state energy, with a provable bound on error. Compared to the current state-of-the-art polytope method, this algorithm eliminates the necessity of introducing an exponential number of variables to counter frustration, and thus significantly improves tractability. We believe that the cluster tree algorithm offers an intuitive and efficient approach to finding and proving ground states of generalized Ising Hamiltonians of arbitrary complexity, which will help validate assumptions regarding local vs. global optimality in lattice models, as well as offer insights into the low-energy behavior of highly frustrated systems.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Multi-physics nuclear reactor simulator for advanced nuclear engineering education
Multi-physics nuclear reactor simulator, which aims to utilize for advanced nuclear engineering education, is being introduced to Nagoya Univ.. The simulator consists of the 'macroscopic' physics simulator and the 'microscopic' physics simulator. The former performs real time simulation of a whole nuclear power plant. The latter is responsible to more detail numerical simulations based on the sophisticated and precise numerical models, while taking into account the plant conditions obtained in the macroscopic physics simulator. Steady-state and kinetics core analyses, fuel mechanical analysis, fluid dynamics analysis, and sub-channel analysis can be carried out in the microscopic physics simulator. Simulation calculations are carried out through dedicated graphical user interface and the simulation results, i.e., spatial and temporal behaviors of major plant parameters are graphically shown. The simulator will provide a bridge between the 'theories' studied with textbooks and the 'physical behaviors' of actual nuclear power plants. (authors)
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Turbulence Model Study for Pressure and Velocity Distributions for Molten Salts in a Crossflow Tube Bundle
Empirical pressure drop correlations for various compositions of molten salts in crossflow across tube bundles/banks are limited due to the scarcity of experimental data for these fluids. This lack of experimental data presents a limitation when designing heat exchangers for Molten Salt Reactors (MSRs) that utilize cross-flow configurations with turbulent molten salts flowing in the shell side. In an effort to provide a starting point for future design and experimental work, a computational fluid dynamics (CFD) campaign is being conducted to estimate pressure drops over a range of Reynolds numbers, pitch to diameter ratios, and for both staggered and in-line tube banks. In an effort to continue this work, the study of various turbulence models were conducted to determine the applicability for steady RANS simulations. An in-line tube bank with FLiBe (LiF-BeF{sub 2}), a frequently selected molten salt in MSRs, was selected for these simulations. The estimated pressure drops and pressure and velocity distributions for each turbulence model was compared to determine the applicability. The k-ε turbulence model family was found to be the most appropriate model for steady Reynolds averaged Navier Stokes within this type of domain. Difference turbulence models were investigated for simulation of molten salt experiencing crossflow within an in-line tube bundle. The flow was simulated using a steady RANS formulation with different families of turbulence models. The different turbulence models provide a view of this specific flow behavior potential requirements and applicable for steady RANS. Of particular note, the k-ε models were able to converge easily within this domain. The predicted behavior for both models were observed to be mostly similar for both velocity and pressure distributions. Whereas, k-ω SST and SA models did not converge well and had observable differences for the predictions of pressure and velocity distributions. The global behaviors were generally similar, but the variations occurring suggest k-ω SST and SA turbulence models are not useful in the steady RANS formulation of this domain. When comparing to the empirical pressure drop, each turbulence model resulted in overpredictions ranging from 8.7% and 19.75% difference. The standard low-Re k-ε model having the lowest difference is likely the better model for simplified predictions for pressure drops. Further investigations will be conducted to determine the convergence issues for the k-ω SST and SA turbulence models. These might be due to the flow geometry or potentially a revision of the meshing is needed. The flow behavior may not be resolved using these models in a steady formulation due to inherent unsteadiness of the flow. (authors)
42 ENGINEERING↗
CFD-Informed Spacer Grid Models in the Subchannel Code CTF
Data from computational fluid dynamics (CFD) simulations can be utilized to improve the predictive capabilities of the subchannel code CTF. Past work incorporating CFD results into CTF has included accounting for directed crossflow and turbulent mixing between adjacent subchannels. Spacer grids impact fluid flow in various ways, and this work focuses on four spacer grid effects, namely: 1. Directed crossflow; 2. Turbulent mixing; 3. Enhanced downstream heat transfer; 4. Pressure drop correlation. Heat transfer augmentation occurs partially due to the disturbances in the developed flow and from the additional turbulence generated by the presence of obstructions in the fluid flow's path. The boundary layer disruption is caused in part by the newly-directed flow just downstream of the spacer grid vanes. This effect lessens as the distance from the grid increases and the flow returns to its developed state, closer to what would be expected in a bare subchannel. Current plans of this work are to develop a method for incorporating the effects of spacer grids on the heat transfer calculation within CTF. Proposed techniques include the addition of an enhancement factor to the local heat transfer coefficient. The inclusion of CFD data from properly-designed simulations will allow CTF to better predict parameters such as fluid temperatures near spacer grids. Improved pressure loss coefficients for each grid can also be generated using CFD simulations. The heat transfer modification has been studied, with other authors noting correlations which are dependent on grid properties such as the blockage ratio. Parameters considered in this study are the turbulent kinetic energy (TKE) and vorticity. There are currently no models to calculate or store either of these parameters within CTF. When accounting for spacer grid effects in CTF, it is important to not double-count the effects towards two different CTF models. This requires carefully designing CFD simulations around capturing specific phenomena from the grids and being able to apply these CFD results to all appropriate flow conditions. (authors)
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Distributed Temperature Sensing within a 19-pin Wire-Wrapped Fuel Bundle Model
It has always been difficult to measure local temperature and flow velocity within fuel bundle geometries because of their complex and compact layouts. High-resolution mapping of the flow field is especially challenging. High-resolution data is typically obtained using optical instruments but optical access to the interior regions of a bundle is severely limited. Velocity fields within fuel bundle models have been mapped with particle image velocimetry (PIV), an optical technique that employs lasers and cameras. Optical access to the bundle interior is obtained using transparent materials and matching the refractive index of the physical structures with that of the fluid. Testing is necessarily isothermal because refractive indices vary with temperature. However, the ultimate aim of such studies is understanding fluid dynamics and heat transfer within real reactors and so flow field mapping under nonisothermal conditions is of particular interest. Temperature fields can be mapped at high-resolution using laser-induced fluorescence (LIF). However, as an optical technique it is unsuitable for nonisothermal liquid flows. This is due to the same sort of optical distortion that restricts PIV. It is also unsuitable for opaque fluids and setups with restricted optical access. Fiber optic distributed temperature sensing (DTS) offers a high-resolution alternative that does not rely upon imaging. A single sensor can map temperature fields at resolutions far exceeding that achievable with conventional sensors such as thermocouples. Though fiber optic sensors cannot match the spatial resolution and bandwidth of LIF, they are suitable for nonisothermal and opaque flows. And though fibers are physical probes that perturb the flow, they can be strung across complex geometries to provide data in regions lacking the optical access necessary for techniques like LIF. Distributed temperature sensing has the potential to provide fuel bundle temperature data of a type that cannot be obtained with optical methods or conventional sensors. This paper reports on preliminary results of efforts to use fiber optic distributed temperature sensors in a fuel bundle model. We are conducting a feasibility study exploring implementation issues such as strain control in the mounting configuration and signal noise associated with flow-induced vibration. We describe here the setup and present preliminary data from our first phase testing with stagnant flow. (authors)
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Uncertainty Quantification by Monte Carlo Analysis using CFD Simulations for GEMIX Benchmark Activities
Uncertainty quantification (UQ) methods can be applied to computational fluid dynamics (CFD) simulations for determining the uncertainty bands of the simulations results. In order to determine the applicability of these different methods, simple benchmark activities have been conducted by various group for comparison. The GEMIX (Generic Mixing experiment) test facility was used to develop benchmark data for this purpose by the Paul Scherrer Institute (PSI). The facility involves the mixing of two fluids that are initially separated. One of the two fluids is water with sugar dissolved in it to create a fluid with similar fluid properties to water, except for density. The other fluid was distilled water to reduce the uncertainty in the fluid's properties. During the experiments, velocity fields and concentration measurements were acquired at several planes of interest. The velocity fields were acquired using particle image velocimetry (PIV) and concentrations of each fluid were acquired using laser induced fluorescence (LIF). The inlet velocity profiles were acquired using laser Doppler velocimetry (LDV). The activity provided the opportunity to vary turbulence models, meshing methodologies, and numerical schemes for creation of uncertainty estimates. The present study investigates the usage of a simple Monte Carlo (MC) technique for varying the inlet boundary conditions of each inlet. The velocity profiles and densities of each inlet were specifically varied based on experiment measurement uncertainty. The intent was to isolate the uncertainty due to inlet quantities and not related to meshing, numerical scheme, or turbulence models. The comparisons of experimental and simulation results were found to be reasonably accurate. Though deficiencies were identified in the modeling approach to be corrected in future works by the authors. (authors)
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Sensitivity Analysis of Passive Heat Removal Capability of FHR Based on Efficient Surrogate Model and GenFlow
Code Scaling, Applicability and Uncertainty Evaluation Methodology (CSAU) is used for quantifying reactor safety margins and works as an alternative method for licensing nuclear power plant. In the framework of CSAU, sensitivity and uncertainty analysis (SA and UA) should be performed. However, for large-scale complicated thermal hydraulics analysis simulated by code (e.g. RELAP5, CFD and subchannel analysis, the sensitivity and uncertainty analysis is really time-consuming. Furthermore, sometimes it is not feasible to perform SA and UA. Specifically, the computation time for Monte Carlo sampling or advanced LHS sampling can be neglected, but the computation time for thermal hydraulics code makes up main part of time during SA and UA process. In order to accelerate the speed of SA and UA, thermal hydraulics code can be improved based on advanced mathematic algorithm or using parallel method. However, the development for new mathematic method needs long time and strict verification and validation process is needed for a new code, which usually takes a couple of years or even longer time to have an approved code that can be used in nuclear industry. An alternative way to improve the speed of SA and UA is using surrogate model. The surrogate model is derived from the input as well as output data of the original code, assuming the code as a black box. The most common method is using response surface method (RSM) as a surrogate for the code, the input parameters are then sampled from their assumed distribution and the corresponding value of the response surface function is calculated. However, a couple of input parameters need hundreds or even thousands of original code calculations. The large number of runs is an obvious disadvantage of this method. Besides, the second disadvantage is an appropriate response surface function must be selected (e.g. quadratic, cubic, quartic, with or without cross product terms, or using a non-polynomial form) to avoid the overfit and underfit problem. This process is time consuming and expensive. Polynomial chaos expansion method is a reasonably fast and attractive alternative, stochastic model. The chaos expansion provides an efficient high-order method of including non-linear effects in stochastic analysis. Usually, the information about the model parameters and their probability distribution is limited and the dependence between them is not known. However, if arbitrary polynomial chaos is used, instead of assuming probability distribution for input parameters which may introduces additional subjectivity into the analysis, the available information can directly and most purely be used in stochastic analysis based on arbitrary data distribution. Thus, it is not necessary to know the exact probability density functions to perform SA and UA based on arbitrary polynomial chaos (aPC). The aPC has been applied for uncertainty quantification in many fields (e.g. in solid mechanics, fluid flows, thermal sciences), and become widely used in nuclear industry recently. Mk1 PB-FHR is a small modular fluoride-salt-cooled, high-temperature reactors (FHRs) that is a concept design by University of California, Berkeley (UCB). It has inherently safe features like natural-circulation-driven systems (e.g. direct reactor auxiliary cooling system (DRACS)) to passively remove decay heat from the reactor core during design basis and beyond design. It is necessary to perform SA and UA, since the licensing process of this new kind of reactor is under way and there are many design parameters that have not been fixed. Current nuclear commercial codes, such as RELAP5, have mainly been developed for light water reactors, which require the use of comprehensive two-phase flow models. This capability is not required to simulate single-phase flow phenomena in FHRs, whose baseline coolant, flibe, remains liquid up to 1430 deg. C at atmospheric pressure. The FHR advanced natural circulation analysis (FANCY) code has been developed specifically for FHR technology modeling and validation work has been performed by using CIET data in UCB. The code has been renamed General Flow (GenFlow) because it has been further developed to have the capability to model complicated pipework system based on object-oriented concept for user friendly purpose. Besides, it can be used to simulate both the force circulation as well as natural circulation. (authors)
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗