SEARCH · Search NASA

Results for “COMPUTATIONAL FLUID DYNAMICS”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Computational fluid dynamics investigations of flow, heat transfer, and oxidation in heat recovery steam generator

Modern heat recovery steam generators (HRSGs) operate at elevated temperatures, leading to the formation of oxides inside the tubes of heat exchangers (HXs). This oxide growth reduces the heat recovery efficiency. Moreover, after reaching a certain critical thickness, some oxide scales detach from the tube surface (exfoliation), causing erosion damage to the components downstream. Predicting the metal temperature distribution and associated oxide thickness in the HXs of an HRSG can aid in mitigating these problems. Here, a computational fluid dynamics (CFD) model was developed within the commercial code STAR-CCM+ for the prediction of fluid flow, conjugate heat transfer, and associated oxidation in HRSGs. Moreover, a new Porous Media Model (PMM) method was developed to model the fin effect on the heat transfer in HX, which can substantially reduce the prohibitive computational costs of fin meshes. The developed CFD model was used to conduct a high-fidelity simulation of a real-scale HRSG to investigate flow, heat transfer, and oxide growth. The calculated oxide thickness on different tubes can be used to identify HX regions that require oxide-resistant coatings to prevent exfoliation and ensuing damages. Furthermore, this CFD framework can serve as a reference for future studies that intend to model and investigate high-temperature oxidation in HXs used for any applications.

42 ENGINEERING↗

DOE OSTI2021

Analysis of Hydrocyclone Geometry via Rapid Optimization Based on Computational Fluid Dynamics

Abstract Hydrocyclones exploit density gradients for the centrifugal separation of dispersions in a continuous liquid. Selection of the geometrics for optimal separation is case specific, like the media characteristics. The existing optimization method based on computational fluid dynamics (CFD) provides a powerful analytical tool but requires long computational times. The most common praxis for CFD optimization is via the single‐factor optimization method (SFOM). In this study, a novel approach is presented as an improved rapid optimization method that implements a dynamic‐mesh and user‐defined function optimization method (DUOM). The DUOM adapts the dynamic‐mesh approach from other applications to the optimization analysis of hydrocyclones. The DUOM reduced the computational time by 31.1 %, compared to the SFOM.

Liu, Lin↗

DOE OSTI2026

Scientific Data Compression for Large Scale Computational Fluid Dynamics (CFD) Simulations

This Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and General Electric (GE) investigated methods for reducing the size of large computational fluid dynamics (CFD) simulation datasets using scientific data compression techniques. The work focused on adapting the MultiGrid Adaptive Reduction of Data (MGARD) compression framework and integrating it with high-performance I/O and visualization tools used in CFD workflows. MGARD uses hierarchical multilevel decomposition to enable error-controlled compression of floating-point scientific data while preserving quantities of interest. During the project, MGARD compression was integrated with the ADIOS I/O framework and visualization tools such as ParaView to enable efficient storage, transfer, and analysis of simulation data. The collaboration also explored approaches for improving compression performance for CFD data defined on unstructured meshes. Results demonstrate that scientific data compression can significantly reduce storage requirements and improve data management for large-scale CFD simulations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Development of an Ultra-Low Head Siphon Hydro Turbine Using Computational Fluid Dynamics

Structural simplification and efficient hydraulic performance are key to effectively utilizing ultra-low head water power resources and reducing hydroelectric unit costs. In this study, a computational fluid dynamics (CFD) method was used to predict hydraulic performance of an axial turbine at the Gaoliangjian power station. CFD results agreed well with field test data. Using the same numerical method, a new siphon turbine was then designed based on the original distributor and turbine runner equipment. This study investigated the effect of different siphon outlet passage geometry parameters, runner blade shapes, and distributors on the hydraulic performance of the siphon turbine. The maximum hydraulic efficiency increased to 87.9% under a head of 2.87 m. Finally, the hydraulic performance of the turbine was compared for four different distributor designs after adding an intake sump at the turbine entrance. The bell-shaped distributor with four guide vanes resulted in the highest power output at the lowest head. Therefore, the siphon turbine is a good option for energy conversion in ultra-low water head settings.

Zhou, Daqing↗

DOE OSTI2017

Computational Fluid Dynamics Modeling of the Fuel Reactor in NETL's 50 kW th Chemical Looping Facility

The National Energy Technology Laboratory (NETL) has explored chemical looping in its 50 kW th facility using a number of oxygen carriers. In this work, the results for methane conversion in the fuel reactor with a hematite iron ore as the oxygen carrier are analyzed. The experimental results are compared to predictions using CPFD's barracuda computational fluid dynamics (CFD) code with kinetics derived from the analysis of fixed bed data. It has been found through analytical techniques from thermal gravimetric analysis data as well as the same fixed bed data that the kinetics for the methane–hematite reaction follows a nucleation and growth or Johnson–Mehl–Avrami (JMA) reaction mechanism. barracuda does not accept nucleation and growth kinetics; however, there is enough sufficient variability of the solids dependence within the software such that the nucleation and growth behavior can be mimicked. This paper presents the method to develop the pseudo-JMA kinetics for barracuda extracted from the fixed bed data and then applies these values to the fuel reactor data to compare the computational results to experimental data obtained from 50 kW th unit for validation. Lastly, a fuel reactor design for near complete conversion is proposed.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Experiment and computational fluid dynamics investigation of biochar elutriation in fluidized bed

Here, in fluidized bed biomass fast pyrolysis, the biomass is converted to biochar and elutriated. The elutriation rate is a key parameter in reactor designs and operations. This research presents a video-based continuous measurement of biochar elutriation rate in a fluidized bed with sands and biomass as bed materials. The fluidized bed is simulated with the Computational Fluid Dynamics - Coarse-Grained Discrete Element Method (CFD-CGDEM) in MFiX. The fluidization behavior of non-spherical sands can be more accurately captured when a rolling friction model is used. The predicted elutriation rate is close to the experimental measurement when the particle size distributions are considered and the filtered drag with a shape correction is used. These results validated the accuracy of the MFiX based CFD framework for the prediction of biochar elutriations in the fluidized bed biomass fast pyrolysis reactor.

09 BIOMASS FUELS↗

DOE OSTI2019

Using Computational Fluid Dynamics of Wind Simulations Coupled With Weather Data to Calculate Dynamic Line Ratings

Dynamic line rating is a technology that allows for the rating of electrical conductors to be calculated based on local weather conditions rather than using ”worst-case” assumptions of weather conditions. The static ratings are typically based on weather conditions that are conservative in nature, and thus dynamic line rating may provide room to increase the current capacity. The local weather conditions may estimate conditions more accurately near the transmission lines accounting for terrain such as nearby hills. One way to estimate the local weather conditions is through the use of computational fluid dynamics. The results of a wind field simulation can be coupled with sparsely located weather stations to provide an accurate assessment of the wind speeds along the path of the conductor. Here, the wind field simulations are calculated using a steady state Reynolds-averaged Navier-Stokes model. These results along with local solar radiance measurements can be used to provide estimates of the steady state ampacity with the standard IEEE equations. An advanced test case for this process involves performing these simulations in a complex terrain, Hells Canyon, the deepest river gorge in North America. The results show that by using weather-based sensors without considering localized wind conditions, the available ampacity may be over-predicted significantly.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Accelerating computational fluid dynamics simulation of post-combustion carbon capture modeling with MeshGraphNets

Packed columns are commonly used in post-combustion processes to capture CO 2 emissions by providing enhanced contact area between a CO 2 -laden gas and CO 2 -absorbing solvent. To study and optimize solvent-based post-combustion carbon capture systems (CCSs), computational fluid dynamics (CFD) can be used to model the liquid–gas countercurrent flow hydrodynamics in these columns and derive key determinants of CO 2 -capture efficiency. However, the large design space of these systems hinders the application of CFD for design optimization due to its high computational cost. In contrast, data-driven modeling approaches can produce fast surrogates to study large-scale physics problems. We build our surrogates using MeshGraphNets (MGN), a graph neural network framework that efficiently learns and produces mesh-based simulations. We apply MGN to a random packed column modeled with over 160K graph nodes and a design space consisting of three key input parameters: solvent surface tension, inlet velocity, and contact angle. Our models can adapt to a wide range of these parameters and accurately predict the complex interactions within the system at rates over 1700 times faster than CFD, affirming its practicality in downstream design optimization tasks. This underscores the robustness and versatility of MGN in modeling complex fluid dynamics for large-scale CCS analyses.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

ECAR-7932 Rev 0 Large Eddy Simulation of MARVEL Reactor Core Subchannel to Evaluate Model Uncertainty of Reynolds-Averaged Navier-Stokes Equation Based Computational Fluid Dynamics Analysis

In the previous work (ECAR-7210), the peak cladding temperature of the MARVEL microreactor has been evaluated by steady-state Reynolds-Averaged Navier-Stokes (RANS) based computational fluid dynamics (CFD) simulations. Although numerical uncertainties of RANS-based CFD simulations has been assessed in ECAR-7210, the model uncertainty of RANS turbulence models must be investigated to resolve the issues related to inaccurate prediction of turbulent heat flux and flow pulsation in a tight lattice rod bundle using the steady-state RANS simulations. Consequently, this ECAR conducted a high-fidelity CFD analysis utilizing Large Eddy Simulation (LES) to generate reference data and investigated the model uncertainty of RANS-based CFD simulations.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

DOE OSTI2021

Computational fluid dynamics modeling and analysis of silica nanoparticle synthesis in a flame spray pyrolysis reactor

Flame Spray Pyrolysis (FSP) is a method for large-scale production of nanoparticles and nanoscale powders employed in a wide range of industrial applications. Particle size and morphology are complex functions of the physicochemical phenomena occurring in the FSP reactor. An extensive study of FSP-related phenomena can be utilized to develop effective strategies for achieving desired particle size/morphology and scaling up the overall yield of an FSP system. In this work, a computational fluid dynamics (CFD) model of an FSP reactor is developed to simulate the coupling of key phenomena involved in the particle synthesis process: liquid spray breakup and evaporation, mixing, combustion, and particle formation/growth of silica nanoparticles. Herein, the particle sizes and their distributions from the CFD simulations are validated against experimental data. Subsequently, the simulations are utilized to investigate the impact of process parameters on the resultant flame dynamics and particle growth. Firstly, the CFD results show that the particle sizes are strongly correlated with the precursor concentration in the solvent. At lower precursor concentrations, the spread of the distribution is relatively insensitive to the value of the concentration. At higher concentrations, the spread is higher as the collision probability between particles is higher. Secondly, increasing the pilot flow rate increases the length of the pilot flames impacting the local ignition location of the spray flame. Lastly, it is shown that the dispersion gas flow rate strongly influences the spray flame shape. This shape can be used for control of particle growth as it helps determine the regions of high temperature and the residence time of the particles in the high temperature region enabling the design and process optimization of the FSP reactor.

42 ENGINEERING↗

DOE OSTI2016

Neutronics and computational fluid dynamics analyses for a natural circulation loop of molten fuel salt

A conceptual reactor system of molten fuel salt loop designed for Mo-99 production was analyzed by coupling TRITON neutronics and Fluent computational fluid dynamics (CFD) simulations. The loop system operated in 1 MW thermal power features natural circulation and potential extraction of non-soluble fission products (FP) in fuel salt. The behavior of natural circulation was studied and the power and temperature distributions in equilibrium were obtained. A long-term fuel depletion analysis of the system considering fuel circulation and reprocessing was then performed using an approximate stepwise sequence of simulations. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2016

HIGH-FIDELITY SIMULATION-DRIVEN MODEL DEVELOPMENT FOR COARSE-GRAINED COMPUTATIONAL FLUID DYNAMICS

Nuclear reactor safety analysis requires identifying various credible accident scenarios and determining their consequences. For a full-scale nuclear power plant system behavior, it is impossible to obtain sufficient experimental data for a broad range of risk-significant accident scenarios. In single-phase flow convective problems, Direct Numerical Simulation (DNS) and Large Eddy Simulation (LES) can provide us with high fidelity results when physical data are unavailable. However, these methods are computationally expensive and cannot be afforded for simulation of long transient scenarios in nuclear accidents despite extraordinary advances in high performance scientific computing over the past decades. The major issue is the inability to make the transient computation parallel, thus making number of time steps required in high-fidelity methods unaffordable for long transients. In this work, we propose to apply a high fidelity simulation-driven approach to model sub-grid scale (SGS) effect in Coarse Grained Computational Fluid Dynamics CG-CFD. This approach aims to develop a statistical surrogate model instead of the deterministic SGS model. We chose to start with a turbulent natural convection case with volumetric heating in a horizontal fluid layer with a rigid, insulated lower boundary and isothermal (cold) upper boundary. This scenario of unstable stratification is relevant to turbulent natural convection in a molten corium pool during a severe nuclear reactor accident, as well as in containment mixing and passive cooling. The presented approach demonstrates how to create a correction for the CG-CFD solution by modifying the energy balance equation. A global correction for the temperature equation proves to achieve a significant improvement to the prediction of steady state temperature distribution through the fluid layer.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2015

Computational Fluid Dynamics Prediction of a Modified Savonius Wind Turbine with Novel Blade Shapes

The Savonius wind turbine is a type of vertical axis wind turbine (VAWTs) that is simply composed of two or three arc-type blades which can generate power even under poor wind conditions. A modified Savonius wind turbine with novel blade shapes is introduced with the aim of increasing the power coefficient of the turbine. The effect of blade fullness, which is a main shape parameter of the blade, on the power production of a two-bladed Savonius wind turbine is investigated using transient computational fluid dynamics (CFD). Simulations are based on the Reynolds Averaged Navier-Stokes (RANS) equations with a renormalization group turbulent model. This numerical method is validated with existing experimental data and then utilized to quantify the performance of design variants. Results quantify the relationship between blade fullness and turbine performance with a blade fullness of 1 resulting in the highest coefficient of power, 0.2573. This power coefficient is 10.98% higher than a conventional Savonius turbine.

17 WIND ENERGY↗

DOE OSTI2014

Comparison of Hydrodynamic Load Predictions Between Engineering Models and Computational Fluid Dynamics for the OC4-DeepCwind Semi-Submersible: Preprint

Hydrodynamic loads on the platforms of floating offshore wind turbines are often predicted with computer-aided engineering tools that employ Morison's equation and/or potential-flow theory. This work compares results from one such tool, FAST, NREL's wind turbine computer-aided engineering tool, and the computational fluid dynamics package, OpenFOAM, for the OC4-DeepCwind semi-submersible analyzed in the International Energy Agency Wind Task 30 project. Load predictions from HydroDyn, the offshore hydrodynamics module of FAST, are compared with high-fidelity results from OpenFOAM. HydroDyn uses a combination of Morison's equations and potential flow to predict the hydrodynamic forces on the structure. The implications of the assumptions in HydroDyn are evaluated based on this code-to-code comparison.

17 WIND ENERGY↗

DOE OSTI2023

Efficient GPU Implementation of Automatic Differentiation for Computational Fluid Dynamics

Many scientific and engineering applications require repeated calculations of derivatives of output functions with respect to input parameters. Automatic Differentiation (AD) is a method that automates derivative calculations and can significantly speed up code development. In Computational Fluid Dynamics (CFD), derivatives of flux functions with respect to state variables (Jacobian) are needed for efficient solutions of the nonlinear governing equations. AD of flux functions on graphics processing units (GPUs) is challenging as flux computations involve many intermediate variables that create high register pressure and require significant memory traffic because of the need to store the derivatives. This paper presents a forward-mode AD method based on multivariate dual numbers that addresses these challenges and simultaneously reduces the floating-point operation count. The dimension of the multivariate dual numbers is optimized for performance. The flux computations are restructured to minimize the number of temporary variables and reduce register pressure. For effective utilization of memory bandwidth, shared memory is used to store the local flux Jacobian. This AD implementation is compared with several other Jacobian implementations on an NVIDIA V100 GPU (V100). For three-dimensional perfect-gas compressible-flow equations implemented in a practical CFD code, the AD implementation of a flux Jacobian based on multivariate dual numbers of dimension 5 outperforms all other GPU AD implementations on V100. Its performance is comparable with the optimized hand-differentiated version. Finally, the implementation achieves 75% of the peak floating-point throughput and 61 % of the peak global device memory bandwidth usage.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

An Alternative Frictional Boundary Condition for Computational Fluid Dynamics Simulation of Friction Stir Welding

For better application of numerical simulation in optimization and design of friction stir welding (FSW), this paper presents a new frictional boundary condition at the tool/workpiece interface for computational fluid dynamics (CFD) modeling of FSW. The proposed boundary condition is based on an implementation of the Coulomb friction model. Using the new boundary condition, the CFD simulation yields non-uniform distribution of contact state over the tool/workpiece interface, as validated by the experimental weld macrostructure. It is found that interfacial sticking state is present over large area at the tool-workpiece interface, while significant interfacial sliding occurs at the shoulder periphery, the lower part of pin side, and the periphery of pin bottom. Due to the interfacial sticking, a rotating flow zone is found under the shoulder, in which fast circular motion occurs. The diameter of the rotating flow zone is smaller than the shoulder diameter, which is attributed to the presence of the interfacial sliding at the shoulder periphery. For the simulated welding condition, the heat generation due to friction and plastic deformation makes up 54.4 and 45.6% of the total heat generation rate, respectively. In conclusion, the simulated temperature field is validated by the good agreement to the experimental measurements.

36 MATERIALS SCIENCE↗

DOE OSTI2024

ECAR-8055 Rev 0 Verification and Validation of Star-CCM+ for Computational Fluid Dynamics Analyses for the MARVEL Microreactor

The objective of this Engineering Calculations and Analysis Report (ECAR) is to provide documentation and highlight relevant information regarding the verification and validation (V&V) of the commercial computational fluid dynamics (CFD) code STAR-CCM+ for the thermal and fluids analyses performed for the MARVEL microreactor.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

DOE OSTI2013

Wind Turbine Modeling for Computational Fluid Dynamics

With the shortage of fossil fuel and the increasing environmental awareness, wind energy is becoming more and more important. As the market for wind energy grows, wind turbines and wind farms are becoming larger. Current utility-scale turbines extend a significant distance into the atmospheric boundary layer. Therefore, the interaction between the atmospheric boundary layer and the turbines and their wakes needs to be better understood. The turbulent wakes of upstream turbines affect the flow field of the turbines behind them, decreasing power production and increasing mechanical loading. With a better understanding of this type of flow, wind farm developers could plan better-performing, less maintenance-intensive wind farms. Simulating this flow using computational fluid dynamics is one important way to gain a better understanding of wind farm flows. In this study, we compare the performance of actuator disc and actuator line models in producing wind turbine wakes and the wake-turbine interaction between multiple turbines. We also examine parameters that affect the performance of these models, such as grid resolution, the use of a tip-loss correction, and the way in which the turbine force is projected onto the flow field.

17 WIND ENERGY↗