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The effects of rotor blade design variables and their mutual interactions on aerodynamic efficiency of helicopters are investigated. The aerodynamic efficiency is defined based on figure of merit (FM) and lift-to-drag responses developed for hover and forward flight, respectively.

The approach is to couple a general flight dynamic simulation code, previously validated in the time domain, with design of experiment (DOE) required for the response surface development. DOE includes I-optimality criteria to preselect the data and improve data acquisition process. Desirability approach is also implemented for a better understanding of the optimum rotor blade planform in both hover and forward flight.

The resulting system provides a systematic manner to examine the rotor blade design variables and their interactions, thus reducing the time and cost of designing rotor blades. The obtained results show that the blade taper ratio of 0.3, the point of taper initiation of about 0.64 R within a SC1095R8 airfoil satisfy the maximum FM of 0.73 and the maximum lift-to-drag ratio of about 5.5 in hover and forward flight.

The work shows the practical possibility to implement the proposed optimization process that can be used for the advanced rotor blade design.

The work presents the rapid and reliable optimization process efficiently used for designing advanced rotor blades in hover and forward flight.

The purpose of this paper is to tackle a satellite module layout design problem (SMLDP). As a complex engineering layout and combinatorial optimization problem, SMLDP cannot be solved effectively by traditional exact methods. Although evolutionary algorithms (EAs) have shown some promise of tackling SMLDP in previous work, the solution quality and computational efficiency still pose a challenge. This paper aims to address these two issues.

Scatter search (SS) and a cooperative co‐evolutionary architecture are integrated to form a new approach called a cooperative co‐evolutionary scatter search (CCSS). The cooperative co‐evolutionary architecture is characterized by the decomposition and cooperation for dealing with complex engineering problems. SS is a flexible meta‐heuristic method that can effectively solve the combinatorial optimization problems. Designing the elements of SS is context‐dependent. Considering the characteristics of SMLDP, our work focuses on two folds: the diversification method, and the reference set update method. The diversification method is built on the method of coordinate transformation and the controlled randomness. The reference set is updated by the static method on the basis of two dissimilarities. Two test problems for circles packing illustrated the capacity of SS. However, when solving SMLDP, SS shows some limitations in the computational time and quality. This study adopts divide‐conquer‐coordination strategy to decompose SMLDP into several layout sub‐problems. Then CCSS is applied to cooperatively solve these sub‐problems. The experimental results illustrate the capability of the proposed approach in tackling the complex problem with less computational effort.

Applying CCSS to SMLDP can obtain satisfying solutions in terms of quality and computational efficiency. This contrasts with the limiting experimental results of SMLDP with some approaches (including modified SS).

A new CCSS is proposed to provide an effective and efficient way of solving SMLDP. Some elements of SS are improved to address the layout problem. SMLDP is decomposed into several sub‐problems that can be solved cooperatively by CCSS after its characteristics are taken into consideration.

The paper aims to introduce an efficient contact detection algorithm for smooth convex particles.

The contact points of adjacent particles are defined according to the common‐normal concept. The problem of contact detection is formulated as 2D unconstrained optimization problem that is solved by a combination of Newton's method and a Levenberg‐Marquardt method.

The contact detection algorithm is efficient in terms of the number of iterations required to reach a high accuracy. In the case of non‐penetrating particles, a penetration can be ruled out in the course of the iterative solution before convergence is reached.

The algorithm is only applicable to smooth convex particles, where a bijective relation between the surface points and the surface normals exists.

By a new kind of formulation, the problem of contact detection between 3D particles can be reduced to a 2D unconstrained optimization problem. This formulation enables fast contact exclusions in the case of non‐penetrating particles.

The purpose of this paper is to propose a progressive inverse identification algorithm to characterize flow stress of tubular materials from the material response, independent of choosing an a priori hardening constitutive model.

In contrast to the conventional forward flow stress identification methods, the flow stress is characterized by a multi-linear curve rather than a limited number of hardening model parameters. The proposed algorithm optimizes the slopes and lengths of the curve increments simultaneously. The objective of the optimization is that the finite element (FE) simulation response of the test estimates the material response within a predefined accuracy.

The authors employ the algorithm to identify flow stress of a 304 stainless steel tube in a tube bulge test as an example to illustrate application of the algorithm. Comparing response of the FE simulation using the obtained flow stress with the material response shows that the method can accurately determine the flow stress of the tube.

The obtained flow stress can be employed for more accurate FE simulation of the metal forming processes as the material behaviour can be characterized in a similar state of stress as the target metal forming process. Moreover, since there is no need for a priori choosing the hardening model, there is no risk for choosing an improper hardening model, which in turn facilitates solving the inverse problem.

The proposed algorithm is more efficient than the conventional inverse flow stress identification methods. In the latter, each attempt to select a more accurate hardening model, if it is available, result in constructing an entirely new inverse problem. However, this problem is avoided in the proposed algorithm.

The pharmaceutical industry is one of the most essential areas of health in any country. It is defined as a system of processes, operations and organizations involved in discovering, developing and producing drugs. The supply chain in the pharmaceutical field is one of the most important strategic issues in the pharmaceutical and health-care industries. The purpose of this study is to reduce the total cost of the supply chain network and reduce the amount of distribution scheduling.

In this study, the authors designed a drug supply chain network with uncertainty-related corruption. The optimal number and location of potential facilities, the optimal allocation of flow between facilities, the optimal routing of vehicles and the optimal amount of inventory in production and distribution center warehouses were determined to achieve these two objective functions.

In evaluating the small sample size problem, it was found that the comprehensive benchmarking method was more efficient than the other methods in obtaining the mean index of the first objective function. The utility function method has also proved its efficiency in obtaining the mean of the second objective function indices, the spacing index and the computational time. Because of the inefficiency of GAMS software in resolving size issues, the modified NSGA II and MOPSO algorithms with modified priority-based encryption have been used. First, using the Taguchi method, the initial parameters of the metaheuristic algorithms are adjusted, and then, 15 sample problems are designed in larger sizes. To avoid generating random data, five problems were equally designed, and the averages of objective functions and metrics of met heuristic algorithms (number of efficient solutions, maximum expansion index, spacing index and computational time) were analyzed as the basis of evaluation and comparison. Therefore, using all the indicators and results of the NSGA II algorithm is recommended.

In this research, a biobjective modeling approach is proposed to minimize the total costs of the supply chain network (construction costs, storage costs and product transportation costs between centers) and advertising costs and to minimize distribution and transportation scheduling across each level of the supply chain network.

This paper presents an efficient lossless compression method to reduce the storage requirement and transmission time for radiographic non‐destructive testing images of aircraft components. The method is based on a combination of predictive coding and the integer wavelet transform. By using the component CAD model to divide the radiographic image of aircraft components into different regions with each region having the same material structure, the parameters of the predictors and the choice of the integer wavelet transform are optimised according to the specific image features contained in each region. Using a real radiographic image of a practical aircraft component as an example, the proposed method is presented and shown to offer a significantly higher compression ratio than other lossless compression schemes currently available.

This paper analyses the link between educational qualification structure and information technology (IT) in the service production process. The analysis is based on 1996 cross‐sectional data for approximately 1,000 West German firms. The empirical evidence indicates that IT capital and high‐skilled labor are complements in the production process: firms with higher IT investment output ratios employ a larger fraction of high‐skilled workers at the expense of unskilled workers. To a lesser extent, the positive IT effect carries through for workers with vocational degrees including masters and technicians. Furthermore, we find that firms’ expectations of the future size of their high‐skilled workforce are positively related to their initial IT investment output ratio. To account for censoring in the employment variables, the empirical analysis uses Powell’s Censored Least Absolute Deviations estimators as well as standard Tobit estimators.

The passive source localization (PSL) problem using angles of arrival (AOA), time differences of arrival (TDOA) or gain ratios of arrival (GROA) is generally nonlinear and nontrival. In this research, the purpose of this paper is to design an accurate hybrid source localization approach to solve the PSL problem. The inspiration is drawn from the fact that the bearings, TDOAs and GROAs are complementary in terms of their geometry properties.

The maximum-likelihood (ML) method is reexamined by using hybrid measurements. Being assisted by the bearings, a new hybrid weighted least-squares (WLS) method is then proposed by jointly utilizing the bearing, TDOA and GROA measurements.

Theoretical performance analysis illustrates that the mean-square error of the ML or WLS method can attain the Cramér-Rao lower bound for Gaussian noise over small error region. However, the WLS method has much lower computational complexity than the ML algorithm. Compared with the AOA-only, TDOA-only, AOA-TDOA, TDOA-GROA methods, the localization accuracy can be greatly improved by combining the AOAs, TDOAs and GROAs, especially for some specific geometries.

A novel bearing-assisted TDOA-GROA method is proposed for source localization, and a new hybrid WLS estimator is presented inspired from the fact that the bearings, TDOAs and GROAs are complementary in terms of their geometry properties.

The purpose of this paper is to present an overview of the aircraft design problems which can be efficiently solved using a special solid finite‐element model of variable density.

Optimization algorithms based on fully‐stressed design philosophy, sensitivity coefficients, and employing material density as a design variable provide means to generate optimal topology layouts, subject to a wide range of design constraints. A novel non‐dimensional criterion is used for assessment of load‐carrying efficiency of structures and knowledge accumulation.

Variable density model, together with non‐dimensional criterion of structural efficiency, yields a new versatile approach to a structural weight estimation at early design stages. New weight equations are used. The approach is a powerful tool for addressing complex multidisciplinary design optimization (MDO) problems such as aerodynamic load prediction taking aeroelastic deformations into account and aerodynamic‐structural design optimization of unconventional aircraft configurations.

For accurate estimation of wing weight and deflections, the method should be tuned by regression analysis of existing aircraft to properly account for secondary structural weight.

The developed software tools for aeroelastic behaviour prediction and coupled aerodynamic‐structural design optimization are ready for integration into the complex MDO framework.

The variable density model is shown to have broad predictive opportunities for design problems at early stages of a product development.