Mechanical Engineering - Research Publications
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ItemNo Preview AvailableData-driven turbulence modelling of inherently unsteady flow in stratified water storage tanks(PERGAMON-ELSEVIER SCIENCE LTD, 2024-02)
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ItemNo Preview AvailableDirect Numerical Simulation of Transitional and Turbulent Flows Over Multi-Scale Surface Roughness-Part II: The Effect of Roughness on the Performance of a High-Pressure Turbine Blade(ASME, 2024-03-01)Abstract Turbine blades generally present surface roughness introduced in the manufacturing process or caused by in-service degradation, which can have a significant impact on aero-thermal performance. A better understanding of the fundamental physical mechanisms arising from the interaction between the roughness and the turbine flow at engine-relevant conditions can provide insights for the design of blades with improved efficiency and longer operational life. To this end, a high-fidelity numerical framework combining a well-validated solver for direct numerical simulation and a second-order accurate immersed boundary method is employed to predict roughness-induced aero-thermal effects on an LS89 high-pressure turbine (HPT) blade at engine-relevant conditions. Different amplitudes and distributions of surface roughness are investigated and a reference smooth-blade simulation under the same flow conditions is conducted for comparison. Roughness of increasing amplitude progressively shifts the blade suction side boundary layer transition upstream, producing larger values of the turbulent kinetic energy and higher total wake losses. The on-surface data-capturing capabilities of the numerical framework provide direct measurements of the heat flux and the skin friction coefficient, hence offering quantitative information between the surface topology and engineering-relevant performance parameters. This work may provide a benchmark for future numerical studies of turbomachinery flows with roughness.
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ItemNo Preview AvailableDirect Numerical Simulation of Transitional and Turbulent Flows Over Multi-Scale Surface Roughness-Part I: Methodology and Challenges(ASME, 2024-03-01)Abstract High-fidelity simulation of transitional and turbulent flows over multi-scale surface roughness presents several challenges. For instance, the complex and irregular geometrical nature of surface roughness makes it impractical to employ conforming structured grids, commonly adopted in large-scale numerical simulations due to their high computational efficiency. One possible solution to overcome this problem is offered by immersed boundary methods, which allow wall boundary conditions to be enforced on grids that do not conform to the geometry of the solid boundary. To this end, a three-dimensional, second-order accurate boundary data immersion method (BDIM) is adopted. A novel mapping algorithm that can be applied to general three-dimensional surfaces is presented, together with a newly developed data-capturing methodology to extract and analyze on-surface flow quantities of interest. A rigorous procedure to compute gradient quantities such as the wall shear stress and the heat flux on complex non-conforming geometries is also introduced. The new framework is validated by performing a direct numerical simulation (DNS) of fully developed turbulent channel flow over sinusoidal egg-carton roughness in a minimal-span domain. For this canonical case, the averaged streamwise velocity profiles are compared against results from the literature obtained with a body-fitted grid. General guidelines on the BDIM resolution requirements for multi-scale roughness simulation are given. Momentum and energy balance methods are used to validate the calculation of the overall skin friction and heat transfer at the wall. The BDIM is then employed to investigate the effect of irregular homogeneous surface roughness on the performance of an LS-89 high-pressure turbine blade at engine-relevant conditions using DNS. This is the first application of the BDIM to realize multi-scale roughness for transitional flow in transonic conditions in the context of high-pressure turbines. The methodology adopted to generate the desired roughness distribution and to apply it to the reference blade geometry is introduced. The results are compared to the case of an equivalent smooth blade.
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ItemNo Preview AvailableHigh-Fidelity Computational Assessment of Aero-Thermal Performance and the Reynolds' Analogy for Additively Manufactured Anisotropic Surface Roughness(ASME, 2023-11-01)Abstract Direct numerical simulations of incompressible turbulent forced convection over irregular, anisotropic surface roughness in a pressure-driven plane channel flow have been performed. Heat transfer was simulated by solving the passive scalar transport equation with Prandtl number Pr = 0.7. The roughness topographies under investigation here are based on an X-ray computed tomography scan of an additively manufactured internal cooling passage, which had an irregular, multiscale and mildly non-Gaussian height distribution. Three different roughness topographies and three different friction Reynolds numbers (Reτ = 395, 590, 720) were considered, along with reference smooth-wall simulations at matched Reτ. By systematically varying the roughness topography and flow conditions, a direct computational assessment of aero-thermal performance (pressure losses and heat transfer) and the Reynolds analogy factor, i.e., 2Ch/Cf, where Ch is the heat-transfer coefficient (Stanton number) and Cf is the skin-friction coefficient, was conducted. The results highlight the profound impact that the roughness orientation (relative to the flow direction) has upon the aero-thermal performance of additively manufactured internal passages, with transverse-aligned roughness augmenting heat transfer by as much as 33%, relative to its streamwise-aligned counterpart. An interrogation of velocity and temperature statistics in the near-wall region was also performed, which underlined the growing dissimilarity between heat transfer and drag as fully rough conditions are approached.
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ItemNo Preview AvailablePhysics-Based Machine Learning Discovered Nanocircuitry for Nonlinear Ion Transport in Nanoporous Electrodes(AMER CHEMICAL SOC, 2023-07-11)
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ItemNo Preview AvailableStudying turbulent flows with physics-informed neural networks and sparse data(ELSEVIER SCIENCE INC, 2023-12)
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ItemDirect Numerical Simulation of Riblets Applied to Gas Turbine Compressor Blades at On- and Off- Design Incidences(ASME, 2023-06-26)Any realizable increase in gas turbine efficiency has significant potential to reduce fuel burn and environmental impact. Streamwise micro-groove surfaces (‘riblets’) are well-known as a passive surface treatment to reduce drag, which may be useful in the context of increasing overall gas turbine efficiency. This paper presents the first direct numerical simulation of potentially performance-enhancing riblets on an axial flow high pressure compressor blade, where the micro-geometry of the riblets is fully resolved. The midspan section of a NACA6510 profile is considered at an engine-relevant true chord Reynolds number of 700,000 and Mach number 0.5 based on inlet conditions. Fixed triangular (or sawtooth) riblets are considered in the present numerical campaign. The current high-fidelity computational method permits the extraction of data such as the wall shear stress directly from the riblet surface. At the design incidence, the riblets tend to promote earlier transition to a turbulent flow over the suction side, yet significantly reduce the skin friction over the entire downstream chord to the trailing edge. The riblets reduce the viscous force over the blade by up to 18% at this nominal inflow incidence. Thus the current dataset permits new insight into the action of the riblets, since most studies of riblets on turbomachinery blades have been conducted experimentally where direct measurements of skin friction are not possible. The riblets are also able to reduce the skin friction over the high pressure compressor blade at off-design incidences, a promising result given axial flow compressors must cope with variable operating conditions.
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ItemNo Preview AvailableToward More General Turbulence Models via Multicase Computational-Fluid-Dynamics-Driven Training(AMER INST AERONAUTICS ASTRONAUTICS, 2023-05)The accuracy of machine-learned turbulence models often diminishes when applied to flow cases outside the training data set. In an effort to improve the predictive accuracy of data-driven models for an expanded set of cases, an extension of a computational fluid dynamics (CFD)-driven training framework consisting of three key steps is proposed. Firstly, a list of candidate flow-related parameters is selected to supplement Pope’s general tensor basis hypothesis. Secondly, modeling an additional production term may benefit the overall predictions in certain situations. Finally, the Reynolds-averaged Navier–Stokes (RANS) evaluations of candidate models are performed on several different flows simultaneously during the model training iterations. Five free-shear and five wall-bounded flow cases are chosen to train or test data-driven turbulence models. It is shown that the machine-learned models from the present multicase CFD-driven framework can significantly improve the predictive accuracy for the test cases where the baseline RANS results showed significant error from the ground truth. Meanwhile, for cases in which the baseline produced good results, the new models do not perform worse. Further analysis shows that the new models can adapt to opposite trends of turbulent diffusion required for the different cases with a common correction. Moreover, the trained models can be simplified and still achieve similar improvement as the whole expressions.
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ItemNo Preview AvailableSurface pressure spectrum variation with Mach number on a CD airfoil(ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD, 2022-05-26)
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ItemNo Preview AvailablePulsed impinging jets: Momentum and heat-transfer(PERGAMON-ELSEVIER SCIENCE LTD, 2022-05-15)