M. Sergio Campobasso
Bio: M. Sergio Campobasso is an academic researcher from Lancaster University. The author has contributed to research in topics: Aerodynamics & Turbine. The author has an hindex of 12, co-authored 29 publications receiving 438 citations. Previous affiliations of M. Sergio Campobasso include University of Glasgow & University of Oxford.
TL;DR: In this article, a reduced quadrature technique was used in gradient-based robust design optimization of aerodynamic shapes under probabilistic uncertainty, and it was shown that the solutions obtained through the proposed method can outperform those obtained through linearization without any significant increase in computational cost.
Abstract: Starting from a comparative study of various methods for uncertainty propagation, this paper presents a novel reduced quadrature technique to be used in gradient-based robust design optimization of aerodynamic shapes. The accuracy and computational efficiency of the method are investigated by means of mathematical analyses and numerical examples. The method is then applied to the robust design of airfoils under probabilistic uncertainty. It is shown that the solutions obtained through the proposed method can outperform those obtained through linearization, without any significant increase in computational cost.
TL;DR: In this paper, the authors present a linear analysis of turbomachinery aeroelasticity based on the linearization of the unsteady flow equations around the mean flow field, which can be determined by a nonlinear steady solver.
Abstract: The linear analysis of turbomachinery aeroelasticity is based on the linearization of the unsteady flow equations around the mean flow field, which can be determined by a nonlinear steady solver. The unsteady periodic flow can be decomposed into a sum of harmonics, each of which can be computed independently by solving a set of linearized equations. The analysis considers just one particular frequency of unsteadiness at a time, and the objective is to compute a complex flow solution that represents the amplitude and phase of the unsteady flow. The solution procedure of both the nonlinear steady and the linear harmonic Euler/Navier-Stokes solvers of the HYDRA suite of codes consists of a preconditioned fixed-point iteration. The numerical instabilities encountered while solving the linear harmonic equations for some turbomachinery test cases are documented, their physical origin highlighted, and the implementation of a GMRES algorithm aiming at the stabilization of the linear code summarized. Presented results include the flutter analysis of a two-dimensional turbine section and a civil engine fan.
TL;DR: Results highlight that the harmonic balance solver can compute these periodic flows more than 10 times faster than its time-domain counterpart, and with an accuracy comparable to that of the time- domain solver.
Abstract: This paper presents the numerical models underlying the implementation of a novel harmonic balance compressible Navier-Stokes solver with low-speed preconditioning for wind turbine unsteady aerodynamics. The numerical integration of the harmonic balance equations is based on a multigrid iteration, and, for the first time, a numerical instability associated with the use of such an explicit approach in this context is discussed and resolved. The harmonic balance solver with low-speed preconditioning is well suited for the analyses of several unsteady periodic low-speed flows, such as those encountered in horizontal axis wind turbines. The computational performance and the accuracy of the technology being developed are assessed by computing the flow field past two sections of a wind turbine blade in yawed wind with both the time-and frequency-domain solvers. Results highlight that the harmonic balance solver can compute these periodic flows more than 10 times faster than its time-domain counterpart, and with an accuracy comparable to that of the time-domain solver.
TL;DR: The steady and harmonic adjoint methods for turbomachinery design using the discrete Euler/Navier-Stokes equations are presented in this paper, where the linear sensitivity of steady state functionals such as mass and average exit angle to arbitrary changes in the geometry of the blades, and this linear sensitivity information can then be used as part of a nonlinear optimization procedure.
Abstract: An overview is presented of the steady and harmonic adjoint methods for turbomachinery design using the discrete approachin which the discretized nonlinearEuler/Navier–Stokes equationsare linearized and the resulting matrix is then transposed. Steady adjoint solvers give the linear sensitivity of steady-state functionals such asmass � ow and average exit � ow angle to arbitrary changes in the geometry of the blades, and this linear sensitivity information can then be used as part of a nonlinear optimization procedure. The harmonic adjoint method is based on a single frequency of unsteadiness and allows one to determine the generalized force acting on the blades due to arbitrary incoming time-periodic gusts. When the forcing is due to the wakes of the upstream blades, the adjointapproach can be used to tailor the shape of the incomingwakes to reduce greatly the level of forced vibration they induce. The presented suite of test cases includes the inlet guide vane and the rotor of a high-pressure turbine.
TL;DR: In this paper, the performance of a wing that is simultaneously heaving and pitching may be investigated by means of time-dependent turbulent flow simulations performed with a compressible Reynolds-averaged Navier-Stokes research solver using the K − ω shear stress transport model of Menter for the turbulence closure.
TL;DR: An overview of the state-of-the-art investigations on the recently developed oscillating foil energy converters is presented in this article, where a summary of available knowledge and up-to-date progress in the application of such bio-inspired systems for renewable energy devices is provided.
TL;DR: In this paper, the role of a number of parameters, including foil kinematics (modes, frequencies, amplitudes and time histories of motion), foil and system geometry (shape, configuration and structural flexibility), and flow physics effects (Reynolds number and turbulence, shear flows and ground effect), were investigated.
TL;DR: The historical development of these approaches are examined, the theoretical background of each major method and the associated numerical techniques required to make them practical in an engineering setting are described, and what is considered to be the state-of-the-art in these methods are described.
01 Jan 2008
TL;DR: A few illustrative examples of CFD-based optimization can be found in this article, where a complete industrial process: papermaking is described. But these examples are restricted to a single process.
Abstract: Generalities and methods.- A Few Illustrative Examples of CFD-based Optimization.- Mathematical Aspects of CFD-based Optimization.- Adjoint Methods for Shape Optimization.- Specific Applications of CFD-based Optimization to Engineering Problems.- Efficient Deterministic Approaches for Aerodynamic Shape Optimization.- Numerical Optimization for Advanced Turbomachinery Design.- CFD-based Optimization for Automotive Aerodynamics.- Multi-objective Optimization for Problems Involving Convective Heat Transfer.- CFD-based Optimization for a Complete Industrial Process: Papermaking.
TL;DR: In this article, a general formulation of the continuous adjoint method for incompressible flows, under the commonly used assumption of frozen turbulence, is presented, and necessary addenda are presented in order to deal with the differentiation of both low and high-Reynolds (with wall functions) number turbulence models; the latter requires the introduction of the so-called adjoint wall functions.
Abstract: This article focuses on the formulation, validation and application of the continuous adjoint method for turbulent flows in aero/hydrodynamic optimization. Though discrete adjoint has been extensively used in the past to compute objective function gradients with respect to (w.r.t.) the design variables under turbulent flow conditions, the development of the continuous adjoint variant for these flows is not widespread in the literature, hindering, to an extend, the computation of exact sensitivity derivatives. The article initially presents a general formulation of the continuous adjoint method for incompressible flows, under the commonly used assumption of “frozen turbulence”. Then, the necessary addenda are presented in order to deal with the differentiation of both low- and high-Reynolds (with wall functions) number turbulence models; the latter requires the introduction of the so-called “adjoint wall functions”. An approach to dealing with distance variations is also presented. The developed methods are initially validated in $$2D$$ cases and then applied to industrial shape and topology optimization problems, originating from the automotive and hydraulic turbomachinery industries.