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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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At least 397 records · Page 22

Separation and Transition on the ROTEX-T Cone-Flare

As part of NATO STO AVT-346 “Predicting Hypersonic Boundary-Layer Transition on Complex Geometries,” coordinated experimental and computational studies were conducted on the ROTEX-T, a cone-flare geometry used in a successful flight-test experiment. At the as-flown conditions, a separation bubble existed at the compression corner. Separation, reattachment, and the multifaceted linear instability paths leading this bubble to transition to turbulence are challenging to predict, but have significant impact on surface pressure and heat flux. High-resolution background-oriented schlieren and infrared thermography measurements were made in the AFOSR–Notre Dame Large Mach-6 Quiet Tunnel at freestream unit Reynolds numbers from 5.8×10(exp 6) to 12.2×10(exp 6) m-1and nominally zero angle of attack. High-speed self-aligned focusing schlieren, infrared thermography, and focused laser differential interferometry measurements were made in the AFRL Mach-6 Ludwieg Tube from 2.2×10(exp 6) to 24.7×10(exp 6) m-1and nominally zero degrees angle of attack. The surface heat-flux and Stanton number distributions were computed. Separation and reattachment locations, as well as the flow state at each, were determined from the combination of surface and off-wall measurements. The convective and global boundary-layer instabilities of the axisymmetric laminar flow at the experimental conditions were investigated computationally. Amplification of Mack’s first and second modes were observed to have logarithmic amplification factors between 5 to 7.5 at the separation location, depending on conditions. The flow was found to be globally unstable to stationary three-dimensional disturbances concentrated in the reattachment region. Previous analysis of the ROTEX-T flight data had not assessed reattachment location or the flow state upon reattachment. Thanks to the insights gained from the coordinated, on- and off-wall ground-test measurements, these evaluations have now been made. The separation location indicated by laminar simulations is consistently numerically predicted to be upstream of the experimentally observed location for a transitional separation bubble. The cause of this difference is understood to lie in the steady-state and axisymmetric assumptions made by both solvers employed to compute the basic states analyzed, as flow topology considerations assert that unsteady two-dimensional or axisymmetric separation bubbles are structurally unstable and will become three-dimensional. Computed laminar heating rates prior to separation agreed well with experiment; transitional heating rates after reattachment were between laminar and turbulent computations.

CFD Validation↗

CFD modeling of turbulent air flow in self-heated gyroid TPMS structures: Thermal-hydraulic performance and validation

The application of mathematically derived geometries, such as triply periodic minimal surface (TPMS) lattices, has garnered significant interest across various fields, including the nuclear sector, due to their superior thermal-hydraulic characteristics for heat transfer compared to traditional plain or finned tubes. Here, this study validates a computational fluid dynamics (CFD) model, evaluates different turbulence models and CFD model settings, and performs uncertainty quantification to provide a comprehensive analysis. Despite extensive research on CFD modeling of TPMS lattices, such as gyroid and diamond geometries, there is a notable lack of publicly available literature providing comprehensive details on numerical analysis aspects, including convergence and methodological best practices. This study embarks on a benchmark analysis of a gyroid geometry to evaluate its thermal-hydraulic performance under turbulent flow conditions and scrutinize various CFD model configurations. The main contributions of this work include validating the CFD model, assessing and comparing different turbulence models, and enhancing pressure drop and temperature prediction capabilities. The results aim to support the development of methodologies needed to benchmark and enhance numerical analysis techniques for TPMS lattices. This work seeks to complement the existing body of knowledge, support the development of TPMS reactor concepts, and improve best practices for CFD modeling of TPMS lattices, ultimately advancing methodologies to support future applications in this domain.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Verification, Validation, and Solution Quality in Computational Physics: CFD Methods Applied to Ice Sheet Physics

Procedures and methods for veri.cation of coding algebra and for validations of models and calculations used in the aerospace computational fluid dynamics (CFD) community would be ef.cacious if used by the glacier dynamics modeling community. This paper presents some of those methods, and how they might be applied to uncertainty management supporting code veri.cation and model validation for glacier dynamics. The similarities and differences between their use in CFD analysis and the proposed application of these methods to glacier modeling are discussed. After establishing sources of uncertainty and methods for code veri.cation, the paper looks at a representative sampling of veri.cation and validation efforts that are underway in the glacier modeling community, and establishes a context for these within an overall solution quality assessment. Finally, a vision of a new information architecture and interactive scienti.c interface is introduced and advocated.

Thompson, David E.↗

Infrared imaging - A validation technique for computational fluid dynamics codes used in STOVL applications

The need for a validation technique for computational fluid dynamics (CFD) codes in STOVL applications has led to research efforts to apply infrared thermal imaging techniques to visualize gaseous flow fields. Specifically, a heated, free-jet test facility was constructed. The gaseous flow field of the jet exhaust was characterized using an infrared imaging technique in the 2 to 5.6 micron wavelength band as well as conventional pitot tube and thermocouple methods. These infrared images are compared to computer-generated images using the equations of radiative exchange based on the temperature distribution in the jet exhaust measured with the thermocouple traverses. Temperature and velocity measurement techniques, infrared imaging, and the computer model of the infrared imaging technique are presented and discussed. From the study, it is concluded that infrared imaging techniques coupled with the radiative exchange equations applied to CFD models are a valid method to qualitatively verify CFD codes used in STOVL applications.

Hardman, R. R.↗

Development and Validation of a Two-Phase Thermal-Hydraulic CFD Code NEK-2P

A project is underway to develop, verify and validate an advanced two-phase flow modeling capability for the highly-scalable, high-performance Computational Fluid Dynamics (CFD) code NEK5000. The goal of this work is to verify and validate the two-phase version of the NEK5000 code, named NEK-2P, to simulate the two-phase flow and heat transfer phenomena that occur in a Boiling Water Reactor (BWR) fuel bundle under various operating conditions. The NEK-2P two-phase flow models follow the approach used for the Extended Boiling Framework (EBF) previously developed at Argonne but include more fundamental physical models of boiling phenomena and advanced numerical algorithms for improved computational accuracy, robustness, and computational speed. The development of the NEK-2P two-phase solver and the implementation of the Extended Boiling Framework two-phase models were initially supported by Argonne National Laboratory (Argonne) through a Laboratory Directed Research and Development (LDRD) project during FY2014-2016. The development and validation of the two-phase models through analyses of selected two-phase boiling flow experiments was supported by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program in FY2017-2020. This report focuses on verification and validation of the water-steam boiling model NEK-2P Two-Phase, CFD code. The NEK-2P was validated with Nuclear Power Engineering Corporation (NUPEC) Pressurized Water Reactor (PWR) Sub-channel and Bundle Test (PSBT) void distribution benchmark. Three different simulations were performed and analyzed for various operating conditions such as wall-heat flux and sub-cooled inlet temperatures. Reasonably good agreement with measured data was obtained in predicting the measured void distributions. Simulations were performed for Virginia Tech. (VT) 3x3 rod bundle geometry with and without spacers. The preliminary results were presented for Simplified Spacer Grid (SSG). In addition, the implementation of interface reconstruction model was tested with one of the Becker benchmark Critical Heat Flux (CHF) experiments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Validation of a Two-Phase CFD Model for Autogenous Pressurization and Expulsion

This paper presents a two-phase computational fluid dynamics (CFD) model for simulating autogenous pressurization and expulsion in a cryogenic liquid hydrogen storage tank, utilizing a volume-of-fluid (VOF) approach combined with the kinetics-based Schrage equation to accurately capture the phase boundary and interfacial heat, mass, and momentum transfer between liquid and vapor phases. The model is validated against experimental data from NASA's K-site tank facility, specifically experimental case 225, which involved pressurization and controlled expulsion of liquid hydrogen. Various turbulence models are evaluated to assess their influence on model accuracy. The CFD simulations successfully replicate key thermodynamic behaviors observed during the experiments, including pressure evolution, temperature profiles, and phase-change dynamics at the vapor-liquid interface. The predicted tank pressures, temperatures, and pressurant requirements agree with experimental data, with pressurant mass predictions within 16\% of observed values. This study highlights the importance of selecting appropriate turbulence models to accurately simulate complex flow and heat transfer phenomena during tank pressurization and expulsion. By enhancing the accuracy and reliability of CFD models for liquid hydrogen under cryogenic conditions, this research contributes to developing efficient cryogenic propellant management strategies for future space missions.

Computational Fluid Dynamics↗

Validation of a Two-Phase CFD Model for Autogenous Pressurization and Expulsion

This paper presents a two-phase computational fluid dynamics (CFD) model for simulating autogenous pressurization and expulsion in a cryogenic liquid hydrogen storage tank, utilizing a volume-of-fluid (VOF) approach combined with the kinetics-based Schrage equation to accurately capture the phase boundary and interfacial heat, mass, and momentum transfer between vapor and liquid phases. The model is validated against experimental data from NASA's K-site tank facility, specifically experimental case 225, which involved autogenous pressurization and controlled expulsion of liquid hydrogen. Various turbulence models are evaluated to assess their influence on model accuracy. The CFD simulations successfully replicate key thermodynamic behaviors observed during the experiments, including pressure evolution, temperature profiles, and phase-change dynamics at the vapor-liquid interface. The predicted tank pressures and temperatures agree well with experimental data, whereas the pressurant mass predictions are within 16% of observed values. This study emphasizes the importance of selecting appropriate turbulence models to accurately simulate the complex flow and heat transfer phenomena during tank autogenous pressurization and expulsion. By improving the accuracy and reliability of CFD models for these processes, this research contributes to developing efficient cryogenic propellant management strategies for future space missions.

Computational Fluid Dynamics↗

Development of an Axisymmetric Afterbody Test Case for Turbulent Flow Separation Validation

As identified in the CFD Vision 2030 Study commissioned by NASA, validation of advanced RANS models and scale-resolving methods for computing turbulent flows must be supported by improvements in high-quality experiments designed specifically for CFD implementation. A new test platform referred to as the Axisymmetric Afterbody allows for a range of flow behaviors to be studied on interchangeable afterbodies while facilitating access to higher Reynolds number facilities. A priori RANS computations are reported for a risk-reduction configuration to demonstrate critical variation among turbulence model results for a given afterbody, ranging from barely-attached to mild separated flow. The effects of body nose geometry and tunnel-wall boundary condition on the computed afterbody flow are explored to inform the design of an experimental test program.

Disotell, Kevin J.↗

Flow visualization and pressure distributions for an all-body hypersonic aircraft

A CFD code-validation effort has been conducted at the NASA-Ames 3.5-ft hypersonic wind tunnel, using a generic, 'all-body' hypersonic aircraft configuration model. The CFD methods to be validated encompass approximate inviscid ones and the upwind parabolized Navier-Stokes solver code. Flow visualizations and pressure distributions are obtained for the cases of zero and 15 deg angles of attack. A complex leeward flow is observed at angle-of-attack with crossflow separation and vortices, and significant changes are noted in the transition from the forebody's conical to the afterbody's nonconical flows.

Lockman, William K.↗

Design and validation of advanced transonic wings using CFD and very high Reynolds number wind tunnel testing

A study is presented that opens the possibility for further wing aerodynamic technology advances when the test and design environment is at a significantly higher Reynolds number than that used for previous generations of commercial transports. Early generation wings were based primarily on NACA airfoil sections integrated simply into three-dimensional designs. Recently, designs have been developed with a major influence from CFD and have depended less on iterative wind tunnel testing. It is shown that, coupled with improvements in CFD wing modeling and advances in test techniques, additional improvements in wing technology can be realized at significantly higher Reynolds numbers.

Goldhammer, Mark I.↗

Turbulence Modeling Verification and Validation

Computational fluid dynamics (CFD) software that solves the Reynolds-averaged Navier-Stokes (RANS) equations has been in routine use for more than a quarter of a century. It is currently employed not only for basic research in fluid dynamics, but also for the analysis and design processes in many industries worldwide, including aerospace, automotive, power generation, chemical manufacturing, polymer processing, and petroleum exploration. A key feature of RANS CFD is the turbulence model. Because the RANS equations are unclosed, a model is necessary to describe the effects of the turbulence on the mean flow, through the Reynolds stress terms. The turbulence model is one of the largest sources of uncertainty in RANS CFD, and most models are known to be flawed in one way or another. Alternative methods such as direct numerical simulations (DNS) and large eddy simulations (LES) rely less on modeling and hence include more physics than RANS. In DNS all turbulent scales are resolved, and in LES the large scales are resolved and the effects of the smallest turbulence scales are modeled. However, both DNS and LES are too expensive for most routine industrial usage on today's computers. Hybrid RANS-LES, which blends RANS near walls with LES away from walls, helps to moderate the cost while still retaining some of the scale-resolving capability of LES, but for some applications it can still be too expensive. Even considering its associated uncertainties, RANS turbulence modeling has proved to be very useful for a wide variety of applications. For example, in the aerospace field, many RANS models are considered to be reliable for computing attached flows. However, existing turbulence models are known to be inaccurate for many flows involving separation. Research has been ongoing for decades in an attempt to improve turbulence models for separated and other nonequilibrium flows. When developing or improving turbulence models, both verification and validation are important steps in the process. Verification insures that the CFD code is solving the equations as intended (no errors in the implementation). This is typically done either through the method of manufactured solutions (MMS) or through careful step-by-step comparisons with other verified codes. After the verification step is concluded, validation is performed to document the ability of the turbulence model to represent different types of flow physics. Validation can involve a large number of test case comparisons with experiments, theory, or DNS. Organized workshops have proved to be valuable resources for the turbulence modeling community in its pursuit of turbulence modeling verification and validation. Workshop contributors using different CFD codes run the same cases, often according to strict guidelines, and compare results. Through these comparisons, it is often possible to (1) identify codes that have likely implementation errors, and (2) gain insight into the capabilities and shortcomings of different turbulence models to predict the flow physics associated with particular types of flows. These are valuable lessons because they help bring consistency to CFD codes by encouraging the correction of faulty programming and facilitating the adoption of better models. They also sometimes point to specific areas needed for improvement in the models. In this paper, several recent workshops are summarized primarily from the point of view of turbulence modeling verification and validation. Furthermore, the NASA Langley Turbulence Modeling Resource website is described. The purpose of this site is to provide a central location where RANS turbulence models are documented, and test cases, grids, and data are provided. The goal of this paper is to provide an abbreviated survey of turbulence modeling verification and validation efforts, summarize some of the outcomes, and give some ideas for future endeavors in this area.

Rumsey, Christopher L.↗

A status of the activities of the NASA. Marshall Space Flight Center Combustion Devices Technology Team

The Consortium for Computational Fluid Dynamics (CFD) Applications in Propulsion Technology was established to focus on computational fluid dynamics applications in propulsion. Specific areas of effort include developing the CFD technology required to address rocket propulsion issues, validating the technology, and applying the validated technology to design problems. The Combustion Devices Technology Team was formed to implement the above objectives in the broad area of combustion driven flows. In an effort to bring CFD to bear in the design environment, the team has focused its efforts on the Space Transportation Main Engine nozzle. The main emphasis has been on the film cooling scheme used to cool the nozzle wall. Benchmark problems have been chosen to validate CFD film cooling capabilities. CFD simulations of the subscale nozzle have been made. Also, CFD predictions of the base flow resulting from this type of nozzle have been made. The status of these calculations is presented along with future plans. Information is given in viewgraph form.

Tucker, Kevin↗

Code Validation Study for Base Flows

New and old rocket launch concepts recommend the clustering of motors for improved lift capability. The flowfield of the base region of the rocket is very complex and can contain high temperature plume gases. These hot gases can cause catastrophic problems if not adequately designed for. To assess the base region characteristics, advanced computational fluid dynamics (CFD) is being used. As a precursor to these calculations the CFD code requires validation on base flows. The primary objective of this code validation study was to establish a high level of confidence in predicting base flows with the USA CFD code. USA has been extensively validated for fundamental flows and other applications. However, base heating flows have a number of unique characteristics so it was necessary to extend the existing validation for this class of problems. In preparation for the planned NLS 1.5 Stage base heating analysis, six case sets were studied to extend the USA code validation data base. This presentation gives a cursive review of three of these cases. The cases presented include a 2D axi-symmetric study, a 3D real nozzle study, and a 3D multi-species study. The results of all the studies show good general agreement with data with no adjustments to the base numerical algorithms or physical models in the code. The study proved the capability of the USA code for modeling base flows within the accuracy of available data.

Ascoli, Edward P.↗

Engine Combustion System Optimization Using Computational Fluid Dynamics and Machine Learning: A Methodological Approach

Gasoline compression ignition (GCI) engines are considered an attractive alternative to traditional spark-ignition and diesel engines. Here, a Machine Learning-Grid Gradient Ascent (ML-GGA) approach was developed to optimize the performance of internal combustion engines. ML offers a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. The developed ML-GGA model was compared with a recently developed Machine Learning-Genetic Algorithm (ML-GA). Detailed investigations of optimization solver parameters and variable limit extension were performed in the present ML-GGA model to improve the accuracy and robustness of the optimization process. Detailed descriptions of the different procedures, optimization tools, and criteria that must be followed for a successful output are provided here. The developed ML-GGA approach was used to optimize the operating conditions (case 1) and the piston bowl design (case 2) of a heavy-duty diesel engine running on a gasoline fuel with a research octane number (RON) of 80. The ML-GGA approach yielded >2% improvements in the merit function, compared with the optimum obtained from a thorough computational fluid dynamics (CFD) guided system optimization. The predictions from the ML-GGA approach were validated with engine CFD simulations. This study demonstrates the potential of ML-GGA to significantly reduce the time needed for optimization problems, without loss in accuracy compared with traditional approaches.

33 ADVANCED PROPULSION SYSTEMS↗

ENGINE COMBUSTION SYSTEM OPTIMIZATION USING CFD AND MACHINE LEARNING: A METHODOLOGICAL APPROACH

Gasoline compression ignition (GCI) engines are considered an attractive alternative to traditional spark-ignition and diesel engines. In this work, a Machine Learning-Grid Gradient Algorithm (ML-GGA) approach was developed to optimize the performance of internal combustion engines. Machine learning (ML) offers a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. The developed ML-GGA model was compared with a recently developed Machine learning Genetic Algorithm (ML-GA). Detailed investigations of optimization solver parameters and variables limits extension were performed in the present ML-GGA model to improve the accuracy and robustness of the optimization process. Detailed descriptions of the different procedures, optimization tools and criteria that must be followed for a successful output are provided here. The developed ML-GGA approach was used to optimize the operating conditions (case 1) and the piston bowl design (case 2) of a heavy-duty diesel engine running on a gasoline fuel with a Research Octane Number (RON) of 80. The ML-GGA approach yielded > 2% improvements in the merit function, compared to the optimum obtained from a thorough computational fluid dynamics (CFD) guided system optimization. The predictions from the ML-GGA approach were validated with engine CFD simulations. This study demonstrates the potential of ML-GGA to significantly reduce the time needed for optimization problems, without loss in accuracy compared to traditional approaches.

engine optimization↗