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Today, the design process of high‐lift configurations in industry mainly relies on experts' knowledge, and lacks a simple exploration of the design space. Therefore, the introduction of high‐fidelity tools in an optimization chain is now envisaged. The purpose of this paper is to define and solve a realistic high‐lift design problem by the use of a constrained evolutionary algorithm, coupled to a Navier‐Stokes (RANS) solver. The complete optimization (shape and settings) of a 3‐element configuration has been carried out for landing and take‐off configurations using a sequential approach.

In a first step, the elements' shapes and settings of the landing configuration have been optimized simultaneously. Then, shapes have been frozen and settings have been optimized for take‐off conditions. The flow evaluation during the optimization process is made through 2.5D Navier‐Stokes computations on chimera grids. The optimization technique used is an evolutionary algorithm, with a dynamic adaptation of the covariance matrix (CMA‐ES). Geometric and aerodynamic constraints have been considered through a dynamic penalization technique of the cost function.

Solutions obtained have been analyzed and compared to the reference initial configuration. In term of cost functions improvement, 5.71 per cent drag reduction has been obtained for landing, and 2.89 per cent improvement on climb index at take‐off.

Compared to the global optimization process, the use of a sequential approach can be quite efficient.

This paper presents a first step for the introduction of recent advanced methods into a design process of high‐lift configurations in an industrial environment.

The paper aims to reduce the aerodynamic drag of a rotorcraft stabilizer in forward flight by taking into account downwash effects from the main rotor wake (power-on conditions).

A shape design methodology based on numerical optimization, CAD-in-the-loop (CAD: computer-aided design) approach and high-fidelity Computational Fluid Dynamics (CFD) tools was set-up and applied to modify the horizontal empennage of a rotorcraft configuration. This included the integration of both commercial and in-house computer-aided engineering tools for parametric geometry handling, adaptive mesh generation, CFD solution and evolutionary optimization within a robust evaluation chain for the aerodynamic simulation of the different design candidates generated during the automatic design loop. Geometrical modifications addressed both the stabilizer planform and sections, together with its setting angle in cruise configuration, accounting for impacts on the equilibrium, stability and control characteristics of the empennage.

An overall improvement of 11.1 per cent over the rotorcraft drag was estimated at the design condition (cruise flight; power-on) for the stabilizer configuration with optimized planform shape, which is increased to 11.4 per cent when combined with the redesigned airfoil to generate the stabilizer surface.

Critical design considerations are introduced with regard to structural and systems integration issues, and a design candidate alternative is identified and proposed as a compromise solution, achieving 8.3 per cent reduction of the rotorcraft configuration drag in cruise conditions with limited increase in the empennage aspect ratio and leading edge sweep angle when compared to the pure aerodynamic optimal design obtained from genetic algorithm evolution.

The proposed methodology faces the empennage design problem by explicitly taking into account the effects of main rotor wake impinging the stabilizer surface in forward flight conditions and using an automated optimization approach which directly incorporates professional CAD tools in the design loop.

This paper aims to present the design optimisation using genetic algorithm (GA) to achieve the highest strength to weight (S/W) ratio, for cold-formed steel residential roof truss.

The GA developed in this research simultaneously optimises roof pitch, truss configurations, joint coordinates and applied loading of typical dual-pitched symmetrical residential roof truss. The residential roof truss was considered with incremental uniform distributed loading, in both gravitational and uplift directions. The structural analyses of trusses were executed in this GA using finite element toolbox. The ultimate strength and serviceability of trusses were checked through the design formulation implemented in GA, according to the Australian standard, AS/NZS 4600 Cold-formed Steel Structures.

An optimum double-Fink roof truss which possess highest S/W ratio using GA was determined, with optimum roof pitch of 15°. The optimised roof truss is suitable for industrial application with its higher S/W ratio and cost-effectiveness. The combined methodology of multi-level optimisation and simultaneous optimisation developed in this research could determine optimum roof truss with consistent S/W ratio, although with huge GA search space.

The sizing of roof truss member is not optimised in this paper. Only single type of cold-formed steel section is used throughout the whole optimisation. The design of truss connection is not considered in this paper. The corresponding connection costs are not included in the proposed optimisation.

The optimum roof truss presented in this paper is suitable for industrial application with higher S/W ratio and lower cost, in either gravitational or uplift loading configurations.

This research demonstrates the approaches in combining multi-level optimisation and simultaneous optimisation to handle large number of variables and hence executed an efficient design optimisation. The GA designed in this research determines the optimum residential roof truss with highest S/W ratio, instead of lightest truss weight in previous studies.

This paper aims to optimize the mass of a tethered aerostat to achieve optimum hull volume, and fins to generate aerodynamic lift to reduce the blow-by.

The design code of aerostat involving structure, aerostatics, aerodynamics and stability has been developed using MATLAB®. The design code is used to obtain the baseline configuration for a tactical aerostat mission by using the statistical values of the hull fineness ratio and the fin parameters of in-service aerostats. The effect of the design variables that include the hull fineness ratio, fin area and fin position on the aerostat mass and blow-by is determined through sensitivity analysis. The aerostat is optimized with an objective function of minimization of mass for the bounded values of design variables and taking blow-by limit as a constraint.

This study reveals that the simultaneous optimization of the aerostat hull fineness ratio, fin area and fin position results in an improvement in the design. The aerostat design with optimum values of these parameters helps in a reduction in its size and mass without compromising the blow-by limits.

This study has been conducted by keeping the hull shape constant by selecting standard National Physics Laboratory envelope shape. The aerodynamic model used in the design code is based on empirical relationships that can be improved in future studies that can use high fidelity aerodynamic models using CFD based surrogate models.

The previous studies on optimization of aerostats are limited to hull envelope shape only, whereas this paper presents the optimization of the hull and fin together. The optimized configuration obtained has a reduced mass and can operate within the specified blow-by limits.

The purpose of this paper is to achieve stable grasping and dexterous in-hand manipulation, the control of the multi-fingered robotic hand is a difficult problem as the hand has many degrees of freedom with various grasp configurations.

To achieve this goal, a novel object-level impedance control framework with optimized grasp force and grasp quality is proposed for multi-fingered robotic hand grasping and in-hand manipulation. The minimal grasp force optimization aims to achieve stable grasping satisfying friction cone constraint while keeping appropriate contact forces without damage to the object. With the optimized grasp quality function, optimal grasp quality can be obtained by dynamically sliding on the object from initial grasp configuration to final grasp configuration. By the proposed controller, the in-hand manipulation of the grasped object can be achieved with compliance to the environment force. The control performance of the closed-loop robotic system is guaranteed by appropriately choosing the design parameters as proved by a Lyapunove function.

Simulations are conducted to validate the efficiency and performance of the proposed controller with a three-fingered robotic hand.

This paper presents a method for robotic optimal grasping and in-hand manipulation with a compliant controller. It may inspire other related researchers and has great potential for practical usage in a widespread of robot applications.

The purpose of this paper is to present a new concept of passive loop technique called “high magnetic coupling passive loop” (HMCPL) (suitable for buried power lines) along with optimised design parameters.

The optimal design (geometrical displacement and shielding current intensity and phase) for the mitigation of magnetic field produced by flat and trefoil configuration of the power line is carried out by means of genetic algorithm.

Different layouts for the source (flat and trefoil configuration) and the shield (introduction of the phase splitting technique) are designed. The optimization parameters are the coordinates of the shield conductors and the transformer ratio of the magnetic core that couple the source and the shield. Moreover, physical constraints as maximum depth of excavation and geometric interference between cables were introduced in the optimization procedure.

The paper deals with a very new technology for field mitigation called HMCPL. Actually, the base layout of the HMCPL does not need an optimal design. On the other hand, in some applications the base layout cannot be used, therefore, the introduction of an optimal design cannot be avoided. In this paper, the optimal design of several configurations is performed showing that the performances of the HMCPL are very interesting even if the base layout cannot be used.

The capability to predict and evaluate various configurations’ performance during the conceptual design phase using multidisciplinary design analysis and optimization can significantly increase the preliminary design process’s efficiency and reduce design and development costs. This research paper aims to perform multidisciplinary design and optimization for an expendable microsatellite launch vehicle (MSLV) comprising three solid-propellant stages, capable of delivering micro-payloads in the low earth orbit. The methodology’s primary purpose is to increase the conceptual and preliminary design process’s efficiency by reducing both the design and development costs.

Multidiscipline feasible architecture is applied for the multidisciplinary design and optimization of an expendable MSLV at the conceptual level to accommodate interdisciplinary interactions during the optimization process. The multidisciplinary design and optimization framework developed and implemented in this research effort encompasses coupled analysis disciplines of vehicle geometry, mass calculations, aerodynamics, propulsion and trajectory. Nineteen design variables were selected to optimize expendable MSLV to launch a 100 kg satellite at an altitude of 600 km in the low earth orbit. Modern heuristic optimization methods such as genetic algorithm (GA), particle swarm optimization (PSO) and SA are applied and compared to obtain the optimal configurations. The initial population is created by passing the upper and lower bounds of design variables to the optimizer. The optimizer then searches for the best possible combination of design variables to obtain the objective function while satisfying the constraints.

All of the applied heuristic methods were able to optimize the design problem. Optimized design variables from these methods lie within the lower and upper bounds. This research successfully achieves the desired altitude and final injection velocity while satisfying all the constraints. In this research effort, multiple runs of heuristic algorithms reduce the fundamental stochastic error.

The use of multiple heuristics optimization methods such as GA, PSO and SA in the conceptual design phase owing to the exclusivity of their search approach provides a unique opportunity for exploration of the feasible design space and helps in obtaining alternative configurations capable of meeting the mission objectives, which is not possible when using any of the single optimization algorithm.

The optimized configurations can be further used as baseline configurations in the microsatellite launch missions’ conceptual and preliminary design phases.

Satellite launch vehicle design and optimization is a complex multidisciplinary problem, and it is dealt with effectively in the multidisciplinary design and optimization domain. It integrates several interlinked disciplines and gives the optimum result that satisfies these disciplines’ requirements. This research effort provides the multidisciplinary design and optimization-based simulation framework to predict and evaluate various expendable satellite launch vehicle configurations’ performance. This framework significantly increases the conceptual and preliminary design process’s efficiency by reducing design and development costs.

The objective of this study is to highlight the questions arising in the design of district heating and cooling systems (DHCSs) in a distributed generation context and to present a model to help find cost‐effective solutions.

Literature on energy systems optimisation is reviewed and a mixed integer programming model for decentralized DHCSs design is developed and applied to two real case studies.

Distributed cooling generation partly coupled with distributed cogeneration and DH is the preferred solution in the examined areas. The optimal configurations, with special reference to network sizing and layout, significantly depend on heating demand profiles and energy prices.

Interdependencies between energy units sizing and network layout definition should be considered. Obtaining more robust and reliable network configurations should be the objective of future modelling efforts.

Despite the growth of distributed energy conversion, designers often rely on centralized concepts in order to reap economies of scale. The presented model helps in discovering less usual solutions representing the most profitable option.

Combining and comparing central and distributed production of heat and cooling under consideration of network costs.

This paper aims to optimize the configuration of assembly lines (ALs) considering the two long-term decision problems within the line balancing and part feeding (PF) contexts, when the supermarket concept is applied in PF.

To this purpose, a bi-level mathematical model is proposed to deal with the assembly line balancing problem (ALBP) and supermarket location problem (SLP) during the strategic decision-making phase of ALs’ configuration. The proposed model is applied on the known test problems taken from the ALBP literature to verify its performance.

The computational results verify that when the proposed structure is applied, the resulting AL configurations are optimized from both ALBP and SLP considerations in terms of the number of stations and line efficiency as well as supermarket transportation and installation costs.

No study has yet dealt with the long-term decision problem of configuring ALs considering both ALBP and SLP. Also, this study validates the effect of the ALBP on the SLP solutions as two long-term interrelated decision problems.

Reducing energy consumption in walking robots is an issue of great importance in field applications such as humanitarian demining so as to increase mission time for a given power supply. The purpose of this paper is to address the problem of improving energy efficiency in statically stable walking machines by comparing two leg, insect and mammal, configurations on the hexapod robotic platform SILO6.

Dynamic simulation of this hexapod is used to develop a set of rules that optimize energy expenditure in both configurations. Later, through a theoretical analysis of energy consumption and experimental measurements in the real platform SILO6, a configuration is chosen.

It is widely accepted that the mammal configuration in statically stable walking machines is better for supporting high loads, while the insect configuration is considered to be better for improving mobility. However, taking into account the leg dynamics and not only the body weight, different results are obtained. In a mammal configuration, supporting body weight accounts for 5 per cent of power consumption while leg dynamics accounts for 31 per cent.

As this paper demonstrates, the energy expended when the robot walks along a straight and horizontal line is the same for both insect and mammal configurations, while power consumption during crab walking in an insect configuration exceeds power consumption in the mammal configuration.