Mechanical Engineering - Research Publications
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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)
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ItemNo Preview AvailableMomentum boundary-layer characterisation from a pulsed impinging jet(ELSEVIER SCIENCE INC, 2022-04)
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ItemRiblet-generated flow mechanisms that lead to local breaking of Reynolds analogy(CAMBRIDGE UNIV PRESS, 2022-11-14)We investigate the Reynolds analogy over riblets, namely the analogy between the fractional increase in Stanton number Ch and the fractional increase in the skin-friction coefficient Cf, relative to a smooth surface. We investigate the direct numerical simulation data of Endrikat et al. (Flow Turbul. Combust., vol. 107, 2021, pp. 1–29). The riblet groove shapes are isosceles triangles with tip angles α = 30◦, 60◦, 90◦, a trapezoid, a rectangle and a right triangle. The viscous-scaled riblet spacing varies between s+ ≈ 10 to 60. The global Reynolds analogy is primarily influenced by Kelvin–Helmholtz rollers and secondary flows. Kelvin–Helmholtz rollers locally break the Reynolds analogy favourably, i.e., cause a locally larger fractional increase in Ch than in Cf. These rollers induce negative wall shear stress patches which have no analogue in wall heat fluxes. Secondary flows at the riblets’ crests are associated with local unfavourable breaking of the Reynolds analogy, i.e., locally larger fractional increase in Cf than in Ch. Only the triangular riblets with α = 30◦ trigger strong Kelvin–Helmholtz rollers without appreciable secondary flows. This riblet shape globally preserves the Reynolds analogy from s+ = 21 to 33. However, the other riblet shapes have weak or non-existent Kelvin–Helmholtz rollers, yet persistent secondary flows. These riblet shapes behave similarly to rough surfaces. They unfavourably break the global Reynolds analogy and do so to a greater extent as s+ increases.