Results for “CFD Validation” — Page 23

NASA NTRSDate not supplied

Modeling Self-Pressurization and Spray Bar Pressure Control of A Cryogenic Storage Tank in Normal Gravity

This paper presents computational fluid dynamics (CFD) models for simulating self-pressurization and spray-bar pressure control processes in a large-scale liquid hydrogen storage tank under normal gravity conditions. For self-pressurization, the model employs the kinetics-based Schrage equation alongside the volume-of-fluid (VOF) method to account for interfacial mass transfer. The CFD predictions of pressure and temperature are compared with experimental data from the Multipurpose Hydrogen Test Bed (MHTB) experiment, and the predicted interfacial mass transfer rates are also presented. A CFD model simulating pressure control using a spray bar has also been developed. An Eulerian-Lagrangian approach models the interactions between discrete droplets and the continuous ullage (vapor) phase. The spray model is coupled with the VOF method by tracking droplets in the ullage and removing them when they reach the liquid interface. The T-sat model calculates droplet-ullage heat and mass transfer, where droplets warm up to the saturation temperature corresponding to the ullage vapor pressure before evaporating while remaining at the saturation temperature. The evolution of tank pressure, vapor temperature, and liquid temperature predicted by the CFD model is validated against data from the MHTB spray-bar mixing experiment. Overall, the CFD models agree with experimental data, demonstrating their capability to simulate self-pressurization and pressure control processes in large-scale cryogenic storage tanks. These models can be valuable tools for designing and optimizing cryogenic fluid management systems in future applications.

Computational Fluid Dynamics↗

NASA NTRSDate not supplied

Modeling Self-Pressurization and Spray Bar Pressure Control of A Cryogenic Storage Tank in Normal Gravity

This paper presents computational fluid dynamics (CFD) models for simulating self-pressurization and spray-bar pressure control processes in a large-scale liquid hydrogen storage tank under normal gravity conditions. For self-pressurization, the model employs the kinetics-based Schrage equation alongside the volume-of-fluid (VOF) method to account for interfacial mass transfer. The CFD predictions of pressure and temperature are compared with experimental data from the Multipurpose Hydrogen Test Bed (MHTB) experiment, and the predicted interfacial mass transfer rates are also presented. A CFD model simulating pressure control using a spray bar has also been developed. An Eulerian-Lagrangian approach models the interactions between discrete droplets and the continuous ullage (vapor) phase. The spray model is coupled with the VOF method by tracking droplets in the ullage and removing them when they reach the liquid interface. The T-sat model calculates droplet-ullage heat and mass transfer, wherein droplets warm up to the saturation temperature corresponding to the ullage vapor pressure before evaporating while remaining at the saturation temperature. The evolution of tank pressure, vapor temperature, and liquid temperature predicted by the CFD model is validated against data from the MHTB spray-bar mixing experiment. Overall, the CFD models agree with experimental data, demonstrating their capability to simulate self-pressurization and pressure control processes in large-scale cryogenic storage tanks. These models can be valuable tools for designing and optimizing cryogenic fluid management systems in future applications.

Self-Pressurization↗

DOE OSTI2020

Deep learning interfacial momentum closures in coarse-mesh CFD two-phase flow simulation using validation data

Multiphase flow phenomena have been widely observed in the industrial applications while it remains a challenging yet unsolved problems. Three-dimensional computational fluid dynamics (CFD) approaches resolve the flow fields on a finer special and temporal scales which can complement the dedicated experimental study. However, closures have to be introduced to reflect the underlying physics in multiphase flow. Among them, the interfacial forces, including drag, lift, turbulent dispersion and wall lubrication forces, play in important role on the bubble’s distribution and migration in liquid-vapor two-phase flow. Development of those closures traditionally rely on the experimental data and analytical derivation with simplified assumptions which usually cannot deliver a universal solution across wide range of flow conditions. In this paper, a data-driven approach, named as Feature Similarity Measurement (FSM), is developed and applied to improve the simulation capability of two-phase flow with coarse-mesh CFD approach. Interfacial momentum transfer in adiabatic bubbly flow serves as the focus of the present study. Both a mature and a simplified set of interfacial closures are taken as the low fidelity data. Experimental data and fine mesh CFD simulations results are adopted as high-fidelity data. Qualitative and quantitative analysis are performed in this paper which reveals that FSM can substantially improve the prediction of coarse mesh CFD model regardless of the choice of interfacial closures and it provides scalability and consistency across discontinuous flow regimes. Furthermore, it demonstrates that data-driven method can aid the multiphase flow modeling by exploring the connections between local physical features and simulation errors.

97 MATHEMATICS AND COMPUTING↗

NASA NTRSDate not supplied

Validation and Development of a Fast-Running CFD Model for the No-Vent Fill of Liquid Propellant Tank

Cryogenic fluids, while offering higher energy density than storable propellants, present several handling challenges, including gradual boil-off and tank self-pressurization. Transferring these propellants between tanks can be problematic, as the receiving tank's temperature and pressure often lead to flashing and rapid boil-off upon injection. The No-Vent Fill (NVF) technique mitigates these risks by preventing liquid fuel from being expelled overboard. By controlling tank pressure and ensuring appropriate condensation in the ullage region, the NVF process avoids exceeding vent pressure limits. In this study, Loci/STREAM-VOF simulations were compared with data from NASA K-site test runs on a 2.1 cubic meter tank with a bottom orifice under various no-vent fill conditions, including different wall temperatures, flow rates, and inlet liquid temperatures. The effort demonstrated that Loci/STREAM-VOF is capable of quantitatively capturing the important physics of NVF with submerged jets: (1) validation of the liquid-vapor interface turbulence velocity using previous experimental data showed good agreement at different fill levels; (2) validation of the CFD Stanton number for mass transfer provided an adequate mass transfer coefficient range; (3) consistent pressure agreements were found in the pressure history for both cold and warm conditions; and (4) the variations of final pressure with flow rate and inlet liquid temperature were well predicted by the CFD simulation. The application of NVF for low-gravity conditions will be studied in future work.

CFD↗

NASA NTRSDate not supplied

Validation and Development of a Fast-Running CFD Model for the No-Vent Fill of Liquid Propellant Tank

Cryogenic fluids, while offering higher energy density than storable propellants, present several handling challenges, including gradual boil-off and tank self-pressurization. Transferring these propellants between tanks can be problematic, as the receiving tank's temperature and pressure often lead to flashing and rapid boil-off upon injection. The No-Vent Fill (NVF) technique mitigates these risks by preventing liquid fuel from being expelled overboard. By controlling tank pressure and ensuring appropriate condensation in the ullage region, the NVF process avoids exceeding vent pressure limits. In this study, Loci/STREAM-VOF simulations were compared with data from NASA K-site test runs on a 2.1 cubic meter tank with a bottom orifice under various no-vent fill conditions, including different wall temperatures, flow rates, and inlet liquid temperatures. The effort demonstrated that Loci/STREAM-VOF is capable of quantitatively capturing the important physics of NVF with submerged jets: (1) validation of the liquid-vapor interface turbulence velocity using previous experimental data showed good agreement at different fill levels; (2) validation of the CFD Stanton number for mass transfer provided an adequate mass transfer coefficient range; (3) consistent pressure agreements were found in the pressure history for both cold and warm conditions; and (4) the variations of final pressure with flow rate and inlet liquid temperature were well predicted by the CFD simulation. The application of NVF for low-gravity conditions will be studied in future work.

CFD↗

NASA NTRS2015

Results of Microgravity Fluid Dynamics Captured With the Spheres-Slosh Experiment

This paper provides an overview of the SPHERES-Slosh Experiment (SSE) aboard the International Space Station (ISS) and presents on-orbit results with data analysis. In order to predict the location of the liquid propellant during all times of a spacecraft mission, engineers and mission analysts utilize Computational Fluid Dynamics (CFD). These state-of-the-art computer programs numerically solve the fluid flow equations to predict the location of the fluid at any point in time during different spacecraft maneuvers. The models and equations used by these programs have been extensively validated on the ground, but long duration data has never been acquired in a microgravity environment. The SSE aboard the ISS is designed to acquire this type of data, used by engineers on earth to validate and improve the CFD prediction models, improving the design of the next generation of space vehicles as well as the safety of current missions. The experiment makes use of two Synchronized Position Hold, Engage, Reorient Experimental Satellites (SPHERES) connected by a frame. In the center of the frame there is a plastic, pill shaped tank that is partially filled with green-colored water. A pair of high resolution cameras records the movement of the liquid inside the tank as the experiment maneuvers within the Japanese Experimental Module test volume. Inertial measurement units record the accelerations and rotations of the tank, making the combination of stereo imaging and inertial data the inputs for CFD model validation.

slosh↗

NASA NTRS2015

Results of Microgravity Fluid Dynamics Captured with the Spheres-Slosh Experiment

This paper provides an overview of the SPHERES-Slosh Experiment (SSE) aboard the International Space Station (ISS) and presents on-orbit results with data analysis. In order to predict the location of the liquid propellant during all times of a spacecraft mission, engineers and mission analysts utilize Computational Fluid Dynamics (CFD). These state-of-the-art computer programs numerically solve the fluid flow equations to predict the location of the fluid at any point in time during different spacecraft maneuvers. The models and equations used by these programs have been extensively validated on the ground, but long duration data has never been acquired in a microgravity environment. The SSE aboard the ISS is designed to acquire this type of data, used by engineers on earth to validate and improve the CFD prediction models, improving the design of the next generation of space vehicles as well as the safety of current missions. The experiment makes use of two Synchronized Position Hold, Engage, Reorient Experimental Satellites (SPHERES) connected by a frame. In the center of the frame there is a plastic, pill shaped tank that is partially filled with green-colored water. A pair of high resolution cameras records the movement of the liquid inside the tank as the experiment maneuvers within the Japanese Experimental Module test volume. Inertial measurement units record the accelerations and rotations of the tank, making the combination of stereo imaging and inertial data the inputs for CFD model validation.

slosh↗

NASA NTRS2015

Result of Microgravity Fluid Dynamics Captured with the SPHERES-Slosh Experiment

This paper provides an overview of the SPHERES-Slosh Experiment (SSE) aboard the International Space Station (ISS) and presents on-orbit results with data analysis. In order to predict the location of the liquid propellant during all times of a spacecraft mission, engineers and mission analysts utilize Computational Fluid Dynamics (CFD). These state-of-the-art computer programs numerically solve the fluid flow equations to predict the location of the fluid at any point in time during different spacecraft maneuvers. The models and equations used by these programs have been extensively validated on the ground, but long duration data has never been acquired in a microgravity environment. The SSE aboard the ISS is designed to acquire this type of data, used by engineers on earth to validate and improve the CFD prediction models, improving the design of the next generation of space vehicles as well as the safety of current missions. The experiment makes use of two Synchronized Position Hold, Engage, Reorient Experimental Satellites (SPHERES) connected by a frame. In the center of the frame there is a plastic, pill shaped tank that is partially filled with green-colored water. A pair of high resolution cameras records the movement of the liquid inside the tank as the experiment maneuvers within the Japanese Experimental Module test volume. Inertial measurement units record the accelerations and rotations of the tank, making the combination of stereo imaging and inertial data the inputs for CFD model validation.

slosh↗

DOE OSTI2021

Three-Dimensional CFD Investigation of Pre-Spark Heat Release in a Boosted SI Engine

Low-temperature heat release (LTHR) in spark-ignited internal combustion engines is a critical step toward the occurrence of auto-ignition, which can lead to an undesirable phenomenon known as engine knock. As such, correct predictions of LTHR are of utmost importance to improve the understanding of knock and enable techniques aimed at controlling it. While LTHR is typically obscured by the deflagration following the spark ignition, extremely late ignition timings can lead to LTHR occurrence prior to the spark, i.e., pre-spark heat release (PSHR). In this research, PSHR in a boosted direct-injection SI engine was numerically investigated using three-dimensional computational fluid dynamics (CFD). A hybrid approach was used, based on the G-equation model for representing the turbulent flame front and the multi-zone well-stirred reactor model for tracking the chemical reactions within the unburnt region. A recently developed best practice was also employed which keeps the well-stirred reactor model active throughout the entire simulation. This allowed for correct predictions of the previous cycle trapped residuals which have a considerable effect on the onset of LTHR. Multi-cycle simulations were conducted using Co-Optima alkylate and E30 fuels. The predicted in-cylinder pressure and heat release rate agreed well with the experimental data and served as validation for the CFD model. Following the initial validation, the dynamics of PSHR was discussed and a series of parameters of interest were assessed. First, the effect of exhaust valve temperature was investigated, qualitatively highlighting the importance of boundary conditions uncertainty. Further analyses were carried out on the effects of fuel properties, including laminar flame speed (LFS) and heat of vaporization (HOV). The results indicate that PSHR phasing is slightly advanced with lower LFS as more trapped unburnt fuel is made available for the next cycle. A similar trend was observed with lower HOV as less intense spray cooling led to higher mixture temperatures, i.e., higher mixture reactivity. Finally, a comparison of Co-Optima alkylate and E30 fuels was made using the pressure-temperature trajectory framework. It was shown that the differences between Co-Optima alkylate and E30 in PSHR tendency are correlated with both HOV and chemical effects.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2026

Machine learning based prediction of airflow maldistribution in air-to-refrigerant heat exchangers

Flow maldistribution is a common challenge in heat exchanger (HX) design and particularly important for air-to-refrigerant geometries where capacity losses can approach 65%. This has a major impact on central air conditioning systems, as compact duct design motivates the use of A-type HXs which are known to be affected by airflow maldistribution. Because velocity profiles are difficult to predict, components are often oversized leading to increased material cost, system footprint, and refrigerant charge. Several studies detail airflow maldistribution for individual HXs and packages, but findings cannot always be extrapolated to new designs. In this work, a machine learning (ML) based flow profile prediction framework is developed and applied to two common package configurations: (i) A-type and (ii) U-type HXs, across a broad range of HX geometries and flow rates. Porous media CFD simulations are validated against independent data for both package types as well as comprehensive in house measurements for a finless geometry with shape optimized non-round tubes, which validates the framework for new heat transfer surfaces. The ML models are trained on the porous media CFD simulations, predicting volumetric flow rate (VFR) within 1.1% and 1.9% with maximum relative L 2 norm errors of 0.48 and 0.65, respectively, while also delivering 10 5 speed up factor compared to full porous media CFD. HX level simulations show an up to 9% reduction in heat transfer from flow maldistribution, with greater losses occurring at smaller half apex angles. This framework enables rapid and highly accurate prediction of airflow maldistribution induced capacity degradation.

42 ENGINEERING↗

DOE OSTI2021

Non-invasive characterization of complex coronary lesions

Conventional invasive diagnostic imaging techniques do not adequately resolve complex Type B and C coronary lesions, which present unique challenges, require personalized treatment and result in worsened patient outcomes. These lesions are often excluded from large-scale non-invasive clinical trials and there does not exist a validated approach to characterize hemodynamic quantities and guide percutaneous intervention for such lesions. This work identifies key biomarkers that differentiate complex Type B and C lesions from simple Type A lesions by introducing and validating a coronary angiography-based computational fluid dynamic (CFD-CA) framework for intracoronary assessment in complex lesions at ultrahigh resolution. Among 14 patients selected in this study, 7 patients with Type B and C lesions were included in the complex lesion group including ostial, bifurcation, serial lesions and lesion where flow was supplied by collateral bed. Simple lesion group included 7 patients with lesions that were discrete, <10mm long and readily accessible. Intracoronary assessment was performed using CFD-CA framework and validated by comparing to clinically measured pressure-based index, such as FFR. Local pressure, endothelial shear stress (ESS) and velocity profiles were derived for all patients. We validates the accuracy of our CFD-CA framework and report excellent agreement with invasive measurements (n=14,R 2 =0.6,p=0.0013). Ultra-high resolution achieved by the model enable physiological assessment in complex lesions and quantify hemodynamic metrics in all vessels up to 1mm in diameter. Importantly, we demonstrate that in contrast to traditional pressure-based metrics, there is a significant difference in the intracoronary hemodynamic forces, such as ESS, in complex lesions compared to simple lesions at both resting and hyperemic physiological states [n = 14, p=0.03]. Higher ESS was observed in the complex lesion group (7.0±4.7 Pa) than in simple lesion group (4.8±3.6 Pa). Complex coronary lesions have higher ESS compared to simple lesions, such differential hemodynamic evaluation can provide much the needed insight into the increase in adverse outcomes for such patients and has incremental prognostic value over traditional pressure-based indices, such as FFR.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Quantifying transport and electrocatalytic reaction processes in a gastight rotating cylinder electrode reactor via integration of Computational Fluid Dynamics modeling and experiments

Understanding the complexity of the multiple processes of mass, momentum, charge, and heat transport, and how these affect reaction kinetics at the electrode/electrolyte interface is one of the major challenges in the field of energy and catalysis. The rapid and rational scale-up of electrocatalytic systems to industrial scales require a detailed understanding of nonlinear transport-reaction processes, accessible only through the building of multi-physics models that capture with high fidelity the complexity of real-world devices. The gastight rotating cylinder electrode (RCE) reactor is a promising lab-scale tool that can decouple transport from intrinsic kinetics to generate data for first-principle models useful in the design of industrial, electrochemical reactors. Computational Fluid Dynamics (CFD) studies have previously been used to investigate the bulk flow in RCE reactors for simple corrosion and electroplating processes. However, the quantification of changes in local concentration within the viscous layer where catalysis takes place requires capturing the correct flow conditions inside the hydrodynamic boundary layer near the surface of the electrode. Further, this requires simulations with spatial resolution in the nm and μm scale and temporal resolutions between ms and s scales that are similar to the timescales for reactions on the electrode surface. In this study, experimental electrocatalysis is combined with CFD modeling to elucidate and parameterize the hydrodynamics in a gastight RCE reactor. CFD simulations of the electrochemical ferricyanide reduction reaction under mass transport limited conditions are used to evaluate the validity of the CFD model parameters by comparing calculated dimensionless mass transport descriptors to dimensionless correlations obtained experimentally. Justifications for assumptions and details of the simulation methods used in this study are presented to provide a detailed understanding of the effect that each model parameter has on the ability to accurately simulate electrocatalysis in RCE systems. The simulation methodology reported here is a first step towards the development of multi-scale models for the study of transport dependent electrocatalytic processes, such as the electrochemical transformation of CO 2 to fuels and chemicals.

42 ENGINEERING↗

NASA NTRS2022

Multi-Fidelity CFD Simulation of the Multirotor Test Bed

The high-fidelity and reduced order CFD method's validation and analysis are presented for the Multirotor Test Bed. The reduced-order method uses a rotor-disk model in the OVERFLOW CFD code and is an important aspect of this study. A rotor-trim option loosely coupling the Comprehensive code CAMRAD II with the OVERFLOW CFD code is included in the simulation that captures rotor blade aerodynamics, blade and rotor performance, rotor-rotor, and rotor-body interactions. Detailed comparison and validation were performed for both higher-fidelity full rotor unsteady flows and reduced-order rotor-disk methods. The tunnel geometry is included in the detailed computational effort. Computations of the low-Reynolds number flows were performed for a different number of in-plane rotors as well as for a single rotor modeled inside the tunnel.

ARMD↗

NASA NTRS2013

Hypersonic Inflatable Aerodynamic Decelerator (HIAD) Technology Development Overview

The successful flight of the Inflatable Reentry Vehicle Experiment (IRVE)-3 has further demonstrated the potential value of Hypersonic Inflatable Aerodynamic Decelerator (HIAD) technology. This technology development effort is funded by NASA's Space Technology Mission Directorate (STMD) Game Changing Development Program (GCDP). This paper provides an overview of a multi-year HIAD technology development effort, detailing the projects completed to date and the additional testing planned for the future. The effort was divided into three areas: Flexible Systems Development (FSD), Mission Advanced Entry Concepts (AEC), and Flight Validation. FSD consists of a Flexible Thermal Protection Systems (FTPS) element, which is investigating high temperature materials, coatings, and additives for use in the bladder, insulator, and heat shield layers; and an Inflatable Structures (IS) element which includes manufacture and testing (laboratory and wind tunnel) of inflatable structures and their associated structural elements. AEC consists of the Mission Applications element developing concepts (including payload interfaces) for missions at multiple destinations for the purpose of demonstrating the benefits and need for the HIAD technology as well as the Next Generation Subsystems element. Ground test development has been pursued in parallel with the Flight Validation IRVE-3 flight test. A larger scale (6m diameter) HIAD inflatable structure was constructed and aerodynamically tested in the National Full-scale Aerodynamics Complex (NFAC) 40ft by 80ft test section along with a duplicate of the IRVE-3 3m article. Both the 6m and 3m articles were tested with instrumented aerodynamic covers which incorporated an array of pressure taps to capture surface pressure distribution to validate Computational Fluid Dynamics (CFD) model predictions of surface pressure distribution. The 3m article also had a duplicate IRVE-3 Thermal Protection System (TPS) to test in addition to testing with the Aerocover configuration. Both the Aerocovers and the TPS were populated with high contrast targets so that photogrammetric solutions of the loaded surface could be created. These solutions both refined the aerodynamic shape for CFD modeling and provided a deformed shape to validate structural Finite Element Analysis (FEA) models. Extensive aerothermal testing has been performed on the TPS candidates. This testing has been conducted in several facilities across the country. The majority of the testing has been conducted in the Boeing Large Core Arc Tunnel (LCAT). HIAD is continuing to mature testing methodology in this facility and is developing new test sample fixtures and control methodologies to improve understanding and quality of the environments to which the samples are subjected. Additional testing has been and continues to be performed in the NASA LaRC 8ft High Temperature Tunnel, where samples up to 2ft by 2ft are being tested over representative underlying structures incorporating construction features such as sewn seams and through-thickness quilting. With the successful completion to the IRVE-3 flight demonstration, mission planning efforts are ramping up on the development of the HIAD Earth Atmospheric Reenty Test (HEART) which will demonstrate a relevant scale vehicle in relevant environments via a large-scale aeroshell (approximately 8.5m) entering at orbital velocity (approximately 7km/sec) with an entry mass on the order of 4MT. Also, the Build to Print (BTP) hardware built as a risk mitigation for the IRVE-3 project to have a "spare" ready to go in the event of a launch vehicle delivery failure is now available for an additional sub-orbital flight experiment. Mission planning is underway to define a mission that can utilize this existing hardware and help the HIAD project further mature this technology.

Hughes, Stephen J.↗

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↗

NASA NTRS2011

The Crucial Role of Error Correlation for Uncertainty Modeling of CFD-Based Aerodynamics Increments

The Ares I ascent aerodynamics database for Design Cycle 3 (DAC-3) was built from wind-tunnel test results and CFD solutions. The wind tunnel results were used to build the baseline response surfaces for wind-tunnel Reynolds numbers at power-off conditions. The CFD solutions were used to build increments to account for Reynolds number effects. We calculate the validation errors for the primary CFD code results at wind tunnel Reynolds number power-off conditions and would like to be able to use those errors to predict the validation errors for the CFD increments. However, the validation errors are large compared to the increments. We suggest a way forward that is consistent with common practice in wind tunnel testing which is to assume that systematic errors in the measurement process and/or the environment will subtract out when increments are calculated, thus making increments more reliable with smaller uncertainty than absolute values of the aerodynamic coefficients. A similar practice has arisen for the use of CFD to generate aerodynamic database increments. The basis of this practice is the assumption of strong correlation of the systematic errors inherent in each of the results used to generate an increment. The assumption of strong correlation is the inferential link between the observed validation uncertainties at wind-tunnel Reynolds numbers and the uncertainties to be predicted for flight. In this paper, we suggest a way to estimate the correlation coefficient and demonstrate the approach using code-to-code differences that were obtained for quality control purposes during the Ares I CFD campaign. Finally, since we can expect the increments to be relatively small compared to the baseline response surface and to be typically of the order of the baseline uncertainty, we find that it is necessary to be able to show that the correlation coefficients are close to unity to avoid overinflating the overall database uncertainty with the addition of the increments.

Hemsch, Michael J.↗

DOE OSTI2022

Computational Fluid Dynamics Simulations to Predict Oxidation in Heat Recovery Steam Generator Tubes

Heat Recovery Steam Generators (HRSGs) are widely used across United States in combined cycle power plants to recover waste heat from the gas turbine (GT). HRSGs are used either to generate electricity or to produce process steam for industrial applications. The primary components of HRSG consists of a duct and a heat exchanger (HX). It is known across the power industry that the high temperature oxidation and ensuing exfoliation problem is a major cause for the damage of HX materials of HRSG. Alloys and/or coatings that can prevent or mitigate oxidation are very expensive, therefore they must be used or applied on the select regions of the HX tubes where the tendency of oxide formation is the highest. The main goal of this project is to identify such regions through Computational Fluid Dynamics (CFD) simulations. Therefore, in this work, we developed a CFD framework using commercial code StarCCM+ for the prediction of the fluid flow and heat transfer in a HRSG and associated oxidation inside the tubes of the HX. The developed CFD framework was verified and validated with experimental data before deployment. We also developed an innovative method to model the effect of the fins on the heat transfer and the pressure drop using a porous media model (PMM) approach to keep the mesh size within reasonable limits. After validation, we performed high-fidelity CFD simulations of a real-scale HRSG using the PMM, with High Performance Computing (HPC) resources of ORNL. From the simulation results, we acquired oxide thickness maps for all the tubes of the select HX sections of HRSG prone to oxidation. These oxide maps can inform regions of the HX tubes that requires oxide-resistant coatings, thereby guiding engineers for cost-efficient manufacturing of the HX that can combat oxidation in HRSGs.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Photoionization of seeded combustion products as a method of enhancing the efficiency of magnetohydrodynamic power generators

Here, in this study, we performed an experimental and computational investigation into the feasibility of utilizing photoionization to enhance the electrical conductivity of seeded oxy-fuel combustion products and improve the performance of magnetohydrodynamic (MHD) power generators. We applied a variety of optical and microwave diagnostics to study the ionization and recombination processes of potassium excited by an excimer laser in a high-velocity oxy-fuel free jet. Computational fluid dynamic (CFD) simulations were performed to model the thermophysical properties and species densities of the free jet. The CFD results were validated with position-dependent potassium concentration measurements. Electron recombination exponential lifetimes were measured through time-resolved microwave transmission. The experimental electron lifetimes were compared with lifetimes calculated from CFD-predicted species densities and literature recombination rates. It was determined that K + or O 2 are the most likely recombination partners for photoionized electrons. Time-resolved fluorescence measurements provided evidence of an ionization pathway involving a two-photon ionization of KOH . Finally, a zero-dimensional chemical kinetic model was developed to assess the fundamental viability of inducing a non-equilibrium electron population to provide a net energy return in combustion-driven MHD power generators. We determined that a high energy return is feasible for targeting electrode boundary layers with ultraviolet photoionization. We also found that photoionization could potentially lower the required temperature of the bulk gas flow.

20 FOSSIL-FUELED POWER PLANTS↗