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The high probability of the occurrence of separation bubbles or shocks and early transition to turbulence on surfaces of airfoil makes it very difficult to design high-lift and high-speed Natural-Laminar-Flow (NLF) airfoil for high-altitude long-endurance unmanned air vehicles. To resolve this issue, a framework of uncertainty-based design optimization (UBDO) is developed based on an adjusted polynomial chaos expansion (PCE) method.

The γ ̄Re-θt transition model combined with the shear stress transport k-ω turbulence model is used to predict the laminar-turbulent transition. The particle swarm optimization algorithm and PCE are integrated to search for the optimal NLF airfoil. Using proposed UBDO framework, the aforementioned problem has been regularized to achieve the optimal airfoil with a tradeoff of aerodynamic performances under fully turbulent and free transition conditions. The tradeoff is to make sure its good performance when early transition to turbulence on surfaces of NLF airfoil happens.

The results indicate that UBDO of NLF airfoil considering Mach number and lift coefficient uncertainty under free transition condition shows a significant deterioration when complicated flight conditions lead to early transition to turbulence. Meanwhile, UBDO of NLF airfoil with a tradeoff of performances under both fully turbulent and free transition conditions holds robust and reliable aerodynamic performance under complicated flight conditions.

In this work, the authors build an effective uncertainty-based design framework based on an adjusted PCE method and apply the framework to design two high-performance NLF airfoils. One of the two NLF airfoils considers Mach number and lift coefficient uncertainty under free transition condition, and the other considers uncertainties both under fully turbulent and free transition conditions. The results show that robust design of NLF airfoil should simultaneously consider Mach number, lift coefficient (angle of attack) and transition location uncertainty.

The purpose of this paper is to propose the use of the continuous adjoint method as a tool to identify the appropriate location and “type” (suction or blowing) of steady jets used in active flow control systems.

The method is based on continuous adjoint and covers both internal and external aerodynamics. The adjoint equations, including the adjoint to the SpalartAllmaras turbulence model and their boundary conditions are formulated. At the cost of solving the flow and adjoint equations just once, the sensitivity derivatives of the objective function with respect to hypothetical (normal) jet velocities at all wall nodes are computed. Comparisons of the computed sensitivities with finite differences and parametric studies to assess the present method are included.

Though the sensitivities are computed for zero jet velocities, they adequately support decision making on: the recommended location of jet(s), at boundary nodes with high absolute valued sensitivities; and the selection between suction or blowing jets, based on the sign of the computed sensitivities. Regarding adjoint methods, two important findings of this work are: the role of the adjoint pressure which proves to be an excellent sensor in flow control problems; and the prediction accuracy of the proposed adjoint method compared to the commonly made assumption of “frozen turbulence”.

First use of the continuous adjoint method using full differentiation of the turbulence model, in flow control optimization. A low‐cost design tool for recommending some of the most important jet characteristics.

This paper aims to conduct the optimization of the multi-stage gas turbine with the effect of the cooling air injection based on the adjoint method.

Continuous adjoint method is combined with the S2 surface code.

The optimization of the stagger angles, stacking lines and the passage can improve the attack angles and restrain the development of the boundary, reducing the secondary flow loss caused by the cooling air injection.

The aerodynamic performance of the gas turbine can be improved via the optimization of blade and passage based on the adjoint method.

The results of the first study on the adjoint method applied to the S2 surface through flow calculation including the cooling air effect are presented.

This paper aims to present a dynamically adjusted deflated restarting procedure for the generalized conjugate residual method with an inner orthogonalization (GCRO) method.

The proposed method uses a GCR solver for the outer iteration and the generalized minimal residual (GMRES) with deflated restarting in the inner iteration. Approximate eigenpairs are evaluated at the end of each inner GMRES restart cycle. The approach determines the number of vectors to be deflated from the spectrum based on the number of negative Ritz values, k∗.

The authors show that the approach restores convergence to cases where GMRES with restart failed and compare the approach against standard GMRES with restarts and deflated restarting. Efficiency is demonstrated for a 2D NACA 0012 airfoil and a 3D common research model wing. In addition, numerical experiments confirm the scalability of the solver.

This paper proposes an extension of dynamic deflated restarting into the traditional GCRO method to improve convergence performance with a significant reduction in the memory usage. The novel deflation strategy involves selecting the number of deflated vectors per restart cycle based on the number of negative harmonic Ritz eigenpairs and defaulting to standard restarted GMRES within the inner loop if none, and restricts the deflated vectors to the smallest eigenvalues present in the modified Hessenberg matrix.

The increase in international trade, the advances in technology, the growing importance of the emerging markets are the main factors that have contributed to the explosion of counterfeiting experienced in recent years, estimated to be valued at about 5-7 per cent of the world trade. The luxury industry in Italy has been particularly hard hit and most brands nowadays are urgently looking for demand-side and supply-side strategies to track and control the phenomenon. The aim of this paper is to provide a supply chain view of counterfeiting and illegitimate trade phenomena, in a supply chain risk management perspective, to define and illuminate the interaction of the legitimate and the illegitimate supply chains.

The paper introduces the LISC model to represent and include all the illegitimate trade phenomena under analysis such as pure counterfeiting, factory overruns, grey and parallel market, supply chain infiltrations, product diversion and sale of stolen goods

The interrelations between legitimate and illegitimate supply chains are crucial to approach counterfeiting issue and define which illegitimate trade paths are more harmful to companies and customers.

The first limitation of the work is that the illegitimate trade categories defined in this paper mainly rely on data and phenomena collected from secondary sources that have not yet been directly observed by the authors. The second one is that a specific focus on high-end fashion industry was employed throughout this work: further analysis for evaluating the applicability and the significance of the illegitimate trade in other industries is still pending. The final limitation stems from the fact that it will be necessary to investigate the implications and the applicability of the model to the illegitimate on-line trade.

During the course of the MI-FIDO project, the model and the selection rules identified for illegitimate trade family classification were used as a basis for defining the rules for anomalies detection to be included in a “track and trace” system developed the project team currently under with a major Italian fashion brand.

To the authors ' knowledge, this is the first work that attempts to present a concise and systematic approach to luxury illegitimate trade from a supply chain perspective. Understanding which legitimate-illegitimate supply chain interactions are the most damaging will help fashion luxury and other industries to battle the counterfeiting phenomenon more effectively

The aim of the study is to present the implications for the financing and sustainability of enterprises based on a ranking methodology for categorical financial data.

Taking advantage of the optimal scaling properties of correspondence analysis (CA), a ranking‐clustering procedure is proposed. The proposed method was applied to categorical financial variables (i.e family farm income, gross profit, gross income, labour income and profitability) collected from a stratified random sampling of 80 Greek pig farms using a structured questionnaire.

The cluster analysis revealed three distinct groups of pig farms. Several recommendations for managerial practices and financial development resulted from this study. For the farms belonging to cluster C₁, that present low rankings on both criteria, a development planning process must be applied that will focus on organizational and management issues. For the farms belonging to cluster C₂, that present low rankings on the “composite income” criterion, policy measures have to be undertaken, aiming at exploiting their own production coefficients, reducing fixed costs and increasing productivity. Finally, for the farms in cluster C₃, that present high scores on both ranking criteria, it is recommended to take actions that will improve their competitiveness.

The findings are limited to five selected financial variables. Therefore, future studies in the same or other business fields would benefit from incorporating a greater number of variables.

The proposed methodological scheme could be useful to practitioners and academics, due to the fact that limited studies have dealt with this ranking problem, particularly in relation to the Greek agricultural business environment.

Topology optimization is a method used for developing optimized geometric designs by distributing material pixels in a given design space that maximizes a chosen quantity of interest (QoI) subject to constraints. The purpose of this study is to develop a problem-agnostic automatic differentiation (AD) framework to compute sensitivities of the QoI required for density distribution-based topology optimization in an unstructured co-located cell-centered finite volume framework. Using this AD framework, the authors develop and demonstrate the topology optimization procedure for multi-dimensional steady-state heat conduction problems.

Topology optimization is performed using the well-established solid isotropic material with penalization approach. The method of moving asymptotes, a gradient-based optimization algorithm, is used to perform the optimization. The sensitivities of the QoI with respect to design variables, required for optimization algorithm, are computed using a discrete adjoint method with a novel AD library named residual automatic partial differentiator (Rapid).

Topologies that maximize or minimize relevant quantities of interest in heat conduction applications are presented. The efficacy of the technique is demonstrated using a variety of realistic heat transfer applications in both two and three dimensions, in conjugate heat transfer problems with finite conductivity ratios and in non-rectangular/non-cuboidal domains.

In contrast to most published work which has either used finite element methods or Cartesian finite volume methods for transport applications, the topology optimization procedure is developed in a general unstructured finite volume framework. This permits topology optimization for flow and heat transfer applications in complex design domains such as those encountered in industry. In addition, the Rapid library is designed to provide a problem-agnostic pathway to automatically compute all required derivatives to machine accuracy. This obviates the necessity to write new code for finding sensitivities when new physics are added or new cost functions are considered and permits general-purpose implementations of topology optimization for complex industrial applications.

The purpose of this paper is to provide a design solution of an engine intake duct suitable for delivering air to the compressor of a gas turbine engine of a general aviation turboprop aircraft, where the initial duct shape suffers a problem of flow distortion due to flow separation at the compressor inlet.

Aerodynamic design uses a three-dimensional inverse-by-optimization approach where the deviation from a desirable target pressure distribution is minimized by means of the adjoint method.

By virtue of a minimization algorithm, the specified target pressure distribution does not necessarily have to be fully realizable to drive the initial pressure distribution towards one with a favourable pressure gradient. The resulting optimized engine intake duct features a deceleration region, in a diverging channel, followed by an acceleration region, in a contracting channel, inhibiting flow separation on the compressor inlet plane.

The flow separation at the compressor inlet has been eliminated allowing proper installation of the engine and flight testing of the aircraft.

Placement and shaping of the intake duct of a turboshaft and turboprop gas turbine engine is a common industrial problem which can be challenging when the available space is limited. The inverse-by-optimization approach based on a reduced flow model, i.e. inviscid flow based on the Euler equations, and a specification of a simple target pressure distribution constitutes an efficient method to overcome the challenge.

The purpose of this paper is to present a simple approach for calculation of the sensitivities in the free-form inverse design problems. The approach is based on the analogy with the similar tasks used in the signal-processing analysis. In the proposed case it is not required to solve an adjoint problem as in the most of the similar optimization tasks. The simulation engine used in the background is a Fast Boundary Element Method. The approach is validated on some known benchmark problems.

Inverse design is recognized nowadays as a crucial scientific grand challenge. Contrary to the conventional approach (“Given the structure, find the properties”) it purses a new paradigm (“Given the desired property, find the structure”). Inverse class of problems has a broad application area, from the material-, medical-, bio- to the engineering-class of problems. When dealing with the inverse design in free-form optimization of the engineering problems the typical approach is to calculate the adjoint problem. Calculation of the adjoint problem mostly requires the costly calculation of the gradients, which makes the whole optimization procedure rather expensive due to the high computational burden required for their solution.

In this paper it is proposed a novel Simple Sensitivity Approach to get in a fast way the response (sensitivity) function of the analyzed structure. The simulation engine used in the background is the Fast Boundary Element Method.

Novel approach for inverse design when performing the free-form optimization of engineering problems.

There is significant amount of literature tackling different issues related to the port industry. The present chapter focuses on a single business unit of seaports aiming at the documentation of works related to container terminals.

An effort to review, collect and present the majority of the works present in the last 30 years, between 1980 and 2010, has been made in order to picture the problems dealt and methods used by the authors in the specific research field. To facilitate the reader, studies have been grouped under five categories of addressed problems (productivity and competitiveness, yard and equipment utilization, equipment scheduling, berth planning, loading/unloading) and four modelling methodologies (mathematics and operations research, management and economics, simulation, stochastic modelling).

The analysis shows that most works focus on productivity and competitiveness issues followed by yard and equipment utilisation and equipment scheduling. In reference to the methodologies used managerial and economic approaches lead, followed by mathematics and operations research.

In reference to future research, two fields have been identified where there is scope of significant contribution by the academic community: container terminal security and container terminal supply chain integration.

The present chapter provides the framework for researchers in the field of port container terminals to picture the so far works in this research area and enables the identification of gaps at both research question and methodology level for further research.