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Purpose: Novel aircraft propulsion configurations require a greater integration of the propulsive system with the airframe. As a consequence of the closer integration of the propulsive system, higher levels of flow distortion at the fan face are expected. This distortion will propagate through the fan and penalize the system performance. This will also modify the exhaust design requirements. This paper aims to propose a methodology for the aerodynamic optimization of the exhaust for novel embedded propulsive systems. To model the distortion transfer, a low order throughflow fan model is included. Design/methodology/approach: As the case study a 2D axisymmetric aft-mounted annular boundary layer ingestion (BLI) propulsor is used. An automated computational fluid dynamics approach is applied with a parametric definition of the design space. A throughflow body force model for the fan is implemented and validated for 2D axisymmetric and 3D flows. A multi-objective optimization based on evolutionary algorithms is used for the exhaust design. Findings: By the application of the optimization methodology, a maximum benefit of approximately 0.32% of the total aircraft required thrust was observed by the application of compact exhaust designs. Furthermore, for the embedded system, it is observed that the design of the compact exhaust and the nacelle afterbody have a considerable impact on the aerodynamic performance. Originality/value: This paper presents a novel approach for the exhaust design of embedded propulsive systems in novel aircraft configurations. To the best of the authors' knowledge, this is the first detailed optimization of the exhaust system on an annular aft-mounted BLI propulsor. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to discuss inverse problems that arise in a variety of practical thermal processes and systems. It presents some of the approaches that may be used to obtain results that lie within a small region of uncertainty. Therefore, the non-uniqueness of the solution is reduced so that the final design and boundary conditions may be determined. Optimization methods that may be used to reduce the uncertainty and to select locations for experimental data and for minimizing the error are presented. A few examples of thermal systems are given to illustrate the applicability of these methods and the challenges that must be addressed in solving inverse problems. Design/methodology/approach: In most analytical and numerical solutions, the basic equations that describe the process, as well as the relevant and appropriate boundary conditions, are known. The interest lies in obtaining a unique solution that satisfies the equations and boundary conditions. This may be termed as a direct or forward solution. However, there are many problems, particularly in practical systems, where the desired result is known but the conditions needed for achieving it are not known. These are generally known as inverse problems. In manufacturing, for instance, the temperature variation to which a component must be subjected to obtain desired characteristics is prescribed, but the means to achieve this variation are not known. An example of this circumstance is the annealing, tempering or hardening of steel. In such cases, the boundary and initial conditions are not known and must be determined by solving the inverse problem to obtain the desired temperature variation in the component. The solutions, thus, obtained are generally not unique. This is a review paper, which discusses inverse problems that arise in a variety of practical thermal processes and systems. It presents some of the approaches or strategies that may be used to obtain results that lie within a small region of uncertainty. It is important to realize that the solution is not unique, and this non-uniqueness must be reduced so that the final design and boundary conditions may be determined with acceptable accuracy and repeatability. Optimization techniques are often used for minimizing the error. This review presents several methods that may be applied to reduce the uncertainty and to select locations for experimental data for the best results. A few examples of thermal systems are given to illustrate the applicability of these methods and the challenges that must be addressed in solving inverse problems. By considering a variety of systems, the paper also shows the importance of solving inverse problems to obtain results that may be used to model and design thermal processes and systems. Findings: The solution of inverse problems, which frequently arise in thermal processes, is discussed. Different strategies to obtain the conditions that lead to the desired result are given. The goal of these approaches is to reduce uncertainty and obtain essentially unique solutions for different circumstances. The error of the method can be checked against known conditions to see if it is acceptable for the given problem. Several examples are given to illustrate the use of these methods. Originality/value: The basic strategies presented here for solving inverse problems that arise in thermal processes and systems, as well as the optimization techniques used to reduce the domain of uncertainty, are fairly original. They are used for certain challenging problems that have not been considered in detail earlier. Several methods are outlined for considering different types of problems. [ABSTRACT FROM AUTHOR]

Purpose: T-shaped cavities occur by design in many technical applications. An example of such a stator cavity is the side space between the guide vane carriers and the outer casing of a steam turbine. Thermal conditions inside it have a significant impact on the deformation of the turbine casing. In order to improve its prediction, the purpose of this paper is to provide a methodology to gain better knowledge of the local heat transfer at the cavity boundaries based on experimental results. Design/methodology/approach: To determine the heat transfer coefficient distribution inside a model cavity with the help of a scaled generic test rig, an inverse heat conduction problem is posed and a method for solving such type of problems in the form of linear combinations of Trefftz functions is presented. Findings: The results of the calculations are compared with another inverse method using first-order gradient optimization technique as well as with estimated values obtained with an analytic two-dimensional thermal network model, and they show an excellent agreement. The calculation procedure is proved to be numerically stable for different degrees of complexity of the sought boundary conditions. Originality/value: This paper provides a universal and robust methodology for the fast direct determination of an arbitrary distribution of heat transfer coefficients based on material temperature measurements spread over the confining wall. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to apply two optimization methods to the issue of sensible energy store design. Design/methodology/approach: This paper is a comparison of topology optimization and genetic algorithms. Findings: Genetic algorithms are prone to converge to local maxima while requiring significantly longer convergence times compared to topology optimization. Topology optimization resulted in structures representing parallel sheets, which are as thin as the grid allows. These configurations can maintain the maximum surface area between the low and high conductivity materials at high refinement, resulting in the best performance. Practical implications: Time required for 99 per cent store discharge is decreased by 70 per cent using a 50 × 50 optimization grid at a loading of 10 Vol.%. Originality/value: These approaches have not been compared nor applied to this specific problem before. Value is in the key finding that maximization of surface area is only possible with fins/sheets and not tree structures. This dictates the optimal solution for dynamic behaviour. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to investigate the optimal geometry parameters in a dimple/protrusion-pin finned channel with high thermal performance.Design/methodology/approach The BSL turbulence model is used to calculate the flow structure and heat transfer in a dimple/protrusion-pin finned channel. The optimization algorithm is set as Non-dominated Sorting Genetic Algorithm II (NSGA-II). The high Nusselt number and low friction factor are chosen as the optimization objectives. The pin fin diameter, dimple/protrusion diameter, dimple/protrusion location and dimple/protrusion depth are applied as the optimization variables. An in-house code is used to generate the geometry model and mesh. The commercial software Isight is used to perform the optimization process.Findings The results show that the Nusselt number and friction factor are sensitive to the geometry parameters. In a pin finned channel with a dimple, the Nusselt number is high at the rear part of the dimple, while it is low at the upstream of the dimple. A high dissipative function is found near the pin fin. In the protrusion channel, the Nusselt number is high at the leading edge of the protrusion. In addition, the protrusion induces a high pressure drop compared to the dimpled channel.Originality/value The originality of this paper is to optimize the geometry parameters in a pin finned channel with dimple/protrusion. This is good application for the heat transfer enhancement at the trailing side for the gas turbine. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to reduce the computational burden and improve the precision of the parameter optimization in the convection-diffusion equation, a new algorithm, the refined gray-encoded evolution algorithm (RGEA), is proposed. Design/methodology/approach – In the new algorithm, the differential evolution algorithm (DEA) is introduced to refine the solutions and to improve the search efficiency in the evolution process; the rapid cycle operation is also introduced to accelerate the convergence rate. The authors apply this algorithm to parameter optimization in convection-diffusion equations. Findings – Two cases for parameter optimization in convection-diffusion equations are studied by using the new algorithm. The results indicate that the sum of absolute errors by the RGEA decreases from 74.14 to 99.29 percent and from 99.32 to 99.98 percent, respectively, compared to those by the gray-encoded genetic algorithm (GGA) and the DEA. And the RGEA has a faster convergent speed than does the GGA or DEA. Research limitations/implications – A more complete convergence analysis of the method is under investigation. The authors will also explore the possibility of adapting the method to identify the initial condition and boundary condition in high-dimension convection-diffusion equations. Practical implications – This paper will have an important impact on the applications of the parameter optimization in the field of environmental flow analysis. Social implications – This paper will have an important significance for a sustainable social development. Originality/value – The authors establish a new RGEA algorithm for parameter optimization in solving convection-diffusion equations. The application results make a valuable contribution to the parameter optimization in the field of environmental flow analysis. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to present a reduced order computational strategy for a multi-physics simulation involving a fluid flow, electromagnetism and heat transfer in a hot-wall chemical vapour deposition reactor. The main goal is to produce a multi-parametric solution for fast exploration of the design space to perform numerical prototyping and process optimisation.Design/methodology/approach Different reduced order techniques are applied. In particular, proper generalized decomposition is used to solve the parameterised heat transfer equation in a five-dimensional space.Findings The solution of the state problem is provided in a compact separated-variable format allowing a fast evaluation of the process-specific quantities of interest that are involved in the optimisation algorithm. This is completely decoupled from the solution of the underlying state problem. Therefore, once the whole parameterised solution is known, the evaluation of the objective function is done on-the-fly.Originality/value Reduced order modelling is applied to solve a multi-parametric multi-physics problem and generate a fast estimator needed for preliminary process optimisation. Different order reduction techniques are combined to treat the flow, heat transfer and electromagnetism problems in the framework of separated-variable representations. [ABSTRACT FROM AUTHOR]

Purpose This paper aims to investigate the entropy generation due to magnetohydrodynamic natural convection flow and heat transfer in a porous enclosure filled with Cu-water nanofluid in the presence of viscous dissipation effect. The left and right walls of the cavity are thermally insulated. There are heated and cold parts, and these are placed on the bottom and top wall, respectively, whereas the remaining parts are thermally insulated.Design/methodology/approach The finite volume method is used to solve the dimensionless partial differential equations governing the problem. A comparison with previously published woks is presented and is found to be in an excellent agreement.Findings The minimization of entropy generation and local heat transfer according to different values of the governing parameters are presented in details. It is found that the presence of magnetic field has negative effects on the local entropy generation because of heat transfer and the local total entropy generation. Also, the increase in the heated part length leads to a decrease in the local Nusselt number.Originality/value This problem is original, as it has not been considered previously. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to report the result of a numerical investigation of film cooling performance on a flat plate for finding optimum blowing ratios.Design/methodology/approach Steady-state simulations have been performed, and the flow has been considered incompressible. Calculations have been performed with 3D finite-volume method and the k-e turbulence model.Findings The adiabatic film cooling effectiveness and the effects of density ratio (DR), blowing ratio (M) and main stream turbulence intensity (Tu), coolant penetration, hole incline and diameter are studied. The temperature and film cooling effectiveness contours, centerline and laterally film cooling effectiveness are presented for these cases. Results show that the cases with smaller Tu have better effectiveness. In the console, using the air coolant and in cylindrical hole cases, using CO2 coolant fluid has higher effectiveness. The results indicated that there is an optimum blowing ratio in the cylindrical hole cases to optimize the performance of new gas turbines.Research limitations/implications Investigation of optimum blowing ratio for the convex surfaces and turbine blades is a prospective topic for future studies.Practical implications The motivation of this study comes from several industrial applications such as film cooling of gas turbine components. This research gives the best blowing ratio for receiving maximum cooling effectiveness with minimum coolant velocity.Originality/value This study optimizes the blowing ratio for film cooling on a flat plate. [ABSTRACT FROM AUTHOR]

Purpose - The aim of this paper is to investigate performance improvements of a monolithic solid oxide fuel cell geometry through an entropy generation analysis. Design/methodology/approach - The analysis of entropy generation rates makes it possible to identify the phenomena that cause the main irreversibilities in the fuel cell, to understand their causes and to propose changes in the design and operation of the system. The various contributions to entropy generation are analyzed separately in order to identify which geometrical parameters should be considered as the independent variables in the optimization procedure. The local entropy generation rates are obtained through 3D numerical calculations, which account for the heat, mass, momentum, species and current transport. The system is then optimized in order to minimize the overall entropy generation and increase efficiency. Findings - In the optimized geometry, the power density is increased by about 10 per cent compared to typical designs. In addition, a 20 per cent reduction in the fuel cell volume can be achieved with less than a 1 per cent reduction in the power density with respect to the optimal design. Research limitations/implications - The physical model is based on a simple composition of the reactants, which also implies that no chemical reactions (water gas shift, methane steam reforming, etc.) take place in the fuel cell. Nevertheless, the entire procedure could be applied in the case of different gas compositions. Practical implications - Entropy generation analysis allows one to identify the geometrical parameters that are expected to play important roles in the optimization process and thus to reduce the free independent variables that have to be considered. This information may also be used for design improvement purposes. Originality/value - In this paper, entropy generation analysis is used for a multi-physics problem that involves various irreversible terms, with the double use of this physical quantity: as a guide to select the most relevant design geometrical quantities to be modified and as objective function to be minimized in the optimization process. [ABSTRACT FROM AUTHOR]

Purpose - The purpose of this paper is to present an approach capable of solving Burgers' equation. Diagonal Padé approximation with a factorization scheme is applied to find numerical solutions of the one-dimensional Burgers' equation by presenting explicit factoring the polynomials of the approximation. The numerical results obtained by this approach, for various values of viscosity, have been compared with the exact solution and are found to be in good agreement with each other. Design/methodology/approach - In this paper, factorized diagonal Padé approach is applied to solve Burgers' equation. In this method, Burgers' equation is reduced to a system of ordinary differential equations and is solved piecewise analytically to obtain the solution of the problem. Findings - The results of proposed approach show that when the obtained results are compared to similar methods, this approach gives better accuracy. Also, the graphs with small ? values satisfy the physical properties of the problem; therefore, the approach is promising for nonlinear problems. Research limitations/implications - The authors' experiments show that the applied method worked fine with Burgers' equation and they hope to extend it to some other nonlinear problems. Practical implications - The proposed method is easy to implement and the given algorithm is easy to use, even for non experts. The approach is flexible to use high order Padé approximants. Originality/value - In the approach described in the paper, Padé approximation is calculated in a different manner than the classical approach. [ABSTRACT FROM AUTHOR]

Purpose - This paper aims to develop and describe an improved process for determining the rate of heat generation in living tissue. Design/methodology/approach - Previous work by the authors on solving the bioheat equation has been updated to include a new localized meshless method which will create a more robust and computationally efficient technique. Inclusion of this technique will allow for the solution of more complex and realistic geometries, which are typical of living tissue. Additionally, the unknown heat generation rates are found through genetic algorithm optimization. Findings - The localized technique showed superior accuracy and significant savings in memory and processor time. The computational efficiency of the newly proposed meshless solver allows the optimization process to be carried to a higher level, leading to more accurate solutions for the inverse technique. Several example cases are presented to demonstrate these conclusions. Research limitations/implications - This work includes only 2D development of the approach, while any realistic modeling for patient-specific cases would be inherently 3D. The extension to 3D, as well as studies to improve the technique by decreasing the sensitivity to measurement noise and to incorporate non-invasive measurement positioning, are under way. Practical implications - As medical imaging continuously improves, such techniques may prove useful in patient diagonosis, as heat generation can be correlated to the presence of tumors, infections, or other conditions. Originality/value - This paper describes a new application of meshless methods. Such methods are becoming attractive due to their decreased pre-processing requirements, especially for problems involving complex geometries (such as patient specific tissues), as well as optimization problems, where geometries may be constantly changing. [ABSTRACT FROM AUTHOR]

Purpose - The purpose of this paper is to show how, with a view to the shortcomings of traditional optimization methods, a multi-objective optimization concerning the structure sizes of micro-channel heat sink is performed by adaptive genetic algorithm. The optimized micro-channel heat sink is simulated by computational fluid dynamics (CFD) method, and the total thermal resistance is calculated to compare with that of thermal resistance network model. Design/methodology/approach - Taking the thermal resistance and the pressure drop as goal functions, a multi-objective optimization model was proposed for the micro-channel cooling heat sink based on the thermal resistance network model. The coupled solution of the flow and heat transfer is considered in the optimization process, and the aim of the procedure is to find the geometry most favorable to simultaneously maximize heat transfer while obtaining a minimum pressure drop. The optimized micro-channel heat sink was numerically simulated by CFD software. Findings - The results of optimization show that the base convection thermal resistance contributes to maximum the total thermal resistance, and base conduction thermal resistance contributes to least. The width of optimized micro-channel and fin are 197 and 50?µm, respectively, and the corresponding total thermal resistance of the whole micro-channel heat sink is 0.838?K/W, which agrees well with the analysis result of thermal resistance network model. Research limitations/implications - The convection heat transfer coefficient is calculated approximately here for convenience, and that may induce some errors. Originality/value - The maximum difference in temperature of the optimized micro-channel cooling heat sink is 84.706?K, which may satisfy the requirement for removal of high heat flux in new-generation chips. The numerical simulation results are also presented, and the results of numerical simulation show that the optimized micro-channel heat sink can enhance thermal transfer performance. [ABSTRACT FROM AUTHOR]

Purpose - This paper seeks to discuss a mechanistic modeling concept for local phenomena governing two- and multi-phase flows and heat transfer. Design/methodology/approach - An overview is given of selected issues concerning the formulation of multidimensional models of two-phase flow and heat transfer. A complete computational multiphase fluid dynamics (CMFD) model of two-phase flow is presented, including local constitutive models applicable to two-phase flows in heated channels. Results are shown of model testing and validation. Findings - It has been demonstrated that the overall model is capable of capturing various local flow and heat transfer phenomena in general, and the onset of temperature excursion (CHF) in low quality forced-convection boiling, in particular. Research limitations/implications - Whereas the multiphase model formulation is applicable to a large class of problems, geometries and operating conditions, the closure laws and results are focused on forced-convection boiling in heated channels. Practical implications - The proposed approach can be used to predict multidimensional velocity field and phase distribution in two-phase flow devices and components used in thermal power plants, nuclear power plants and chemical processing plants. Originality/value - A complete mechanistic multidimensional model of forced-convection boiling in heated channels is given. The potential of a CMFD approach is demonstrated to perform virtual experiments that can be used in system design and optimization, and in safety analysis. [ABSTRACT FROM AUTHOR]