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In this work, the design problem of hydrodynamic plain journal bearings is formulated as a multi-objective optimization problem to improve bearing performance under different operating conditions.

The problem is solved using a hybrid approach combining genetic algorithm and sequential quadratic programming. The selected state variables are oil leakage flow rate, power loss and minimum oil film thickness. The selected design variables are the radial clearance, length-to-diameter ratio, oil viscosity, oil supply pressure and oil supply groove angular position. A validated empirical model is adopted to provide relatively accurate estimation of the bearing state variables with reduced computations. Pareto optimal solution sets are obtained for different operating conditions, and secondary selection criteria are proposed to choose a final optimum design.

The adopted hybrid optimization approach is a random search algorithm that generates a different solution set for each run, thus a different bearing design. For a number of runs, it is found that the key design variables that significantly affect the optimum state variables are the bearing radial clearance, oil viscosity and oil supply pressure. Additionally, oil viscosity is found to represent the significant factor that distinguishes the optimum designs obtained using the implemented secondary selection criteria. Finally, the results of the proposed optimum design framework at different operating conditions are presented and compared.

The proposed multi-objective formulation of the bearing design problem can provide engineers with a systematic approach and an important degree of flexibility to choose the optimum design that best fits the application requirements.

This paper presents a versatile and economical knowledge‐based assembly design of blade and shell assemblies by employing behavioral modeling concepts. Behavioral modeling is a new generation CAD concept aimed at achieving ultimately optimum results with the efforts made in the early stage of the product development cycle. As a result, the assembly process of any odd‐configured parts such as torque converter blades, can be accurately planned, and made adaptable to all potential in‐process alterations due to either changes of components design or that of the assembly kinematics. Optimum assembly design is achieved when the volumetric interference meets a desired value based on an expert's determination. Experimental verification of the proposed optimum assembly design conducted in Luk, Inc. with two different blades' assemblies demonstrates satisfactory results.

This paper evaluates a Successive Response Surface Method (SRSM) specifically developed for simulation‐based design optimization, e.g. that of explicit nonlinear dynamics in crashworthiness design. Linear response surfaces are constructed in a subregion of the design space using a design of experiments approach with a D‐optimal experimental design. To converge to an optimum, a domain reduction scheme is utilized. The scheme requires only one user‐defined parameter, namely the size of the initial subregion. During optimization, the size of this region is adapted using a move reversal criterion to counter oscillation and a move distance criterion to gauge accuracy. To test its robustness, the results using the method are compared to SQP results of a selection of the well‐known Hock and Schittkowski problems. Although convergence to a small tolerance is slow when compared to SQP, the SRSM method does remarkably well for these sometimes pathological analytical problems. The second test concerns three engineering problems sampled from the nonlinear structural dynamics field to investigate the method's handling of numerical noise and non‐linearity. It is shown that, despite its simplicity, the SRSM method converges stably and is relatively insensitive to its only user‐required input parameter.

The purpose of this paper is to present a way to determine the optimum values of design parameters in a cylindrical heat sink with branched fins. Investigations into the effect of design parameters, such as the number of fins, length of fin, height of fin and outer diameter of the heat sink on heat transfer are reported here. In this analysis, branch angle (α = 10°) is considered.

The Taguchi method, a powerful tool to design optimization, is applied for the tests and standard L9 orthogonal array with three factors, and three levels for each factor are selected. Nine test samples are analyzed in which the total heat transfer rate for each test sample is found. Contribution ratios for each parameter are also found. The results obtained from this analysis are used to find the optimum design parameter values relating to the heat sink performance.

The optimum design parameters are analyzed in this paper. The reliability of the optimum test samples is verified. Also, the variation of the average heat transfer rate of optimum sample is reported when it is compared with the reference sample.

Effective design of a cylindrical heat sink has been reported for cooling light-emitting diode (LED) lights, which have recently attracted the attention of the illumination industry. In this analysis, the contribution ratios have an important role to set out the performance characteristics of a heat sink.

The reliability of the optimum test samples is verified. Also, the variation of the average heat transfer rate of optimum sample is reported when it is compared with the reference sample.

The structural design problem can be viewed as an iterative design loop with each iteration involving two stages for topology and shape designs with genetic algorithm (GA) as the optimization tool for both.

The topology optimization problem, which is ill posed, is regularized using a constraint on perimeter and solved using GA. The problem is formulated as one of compliance minimization subject to volume constraint for the single loading case. A dual formulation of this has been used for the multiple loading cases resulting in as many behavioral constraints as there are loading cases. The tentative topology given by the topology optimization module is taken and the domain boundary is approximated using straight lines, B‐splines and cubic spline curves and design variables are selected among the boundary defining points. Optimum boundary shape of the problem has been obtained using GA in two different ways: without stress constraints; and with stress constraints.

The proposed two stage strategy has been tested on benchmark structural optimization problems and its performance is found to be extremely good.

The strategy appears to be eminently suitable for implementation in a general purpose FE software as an add‐on module for structural design optimization.

It has been observed that the integrated topology and shape design method is robust and easy to implement in comparison with other techniques. The computing time requirements for the GA does not appear daunting in the present scenario of high performance parallel computing and improved GA techniques.

This paper demonstrates the use of genetic algorithms (GAs) for size optimization of trusses. The concept of rebirthing is shown to be considerably effective for problems involving continuous design variables. Some benchmark examples are studied involving 4‐bar, 10‐bar, 64‐bar, 200‐bar and 940‐bar two‐dimensional trusses. Both continuous and discrete variables are considered.

The purpose of this paper is to efficiently use as few sample points as possible to get a sufficiently explored design space and an accurate optimum for adaptive metamodel-based design optimization (AMBDO).

A parameterized lower confidence bounding (PLCB) scheme is proposed in which a cooling strategy is introduced to guarantee the balance between exploitation and exploration by varying weights of the predicting error and optimum of a metamodel. The proposed scheme is investigated by a set of test functions and a structural optimization problem, in which PLCB with four kinds of cooling control functions are studied. Moreover, other infill criteria (such as expected improvement and its extension versions) are taken into comparison.

Results show that the proposed PLCB (especially PLCB with the first cooling control function) based AMBDO method can find the optimum with fewer evaluations and maintain good accuracy, which means the proposed PLCB contributes to the excellent efficiency and accuracy in finding global optimal solutions.

The parameterized version of the lower confidence bound metric is proposed for AMBDO, typically used in the context of adaptive sampling in efficient global optimization.

This paper deals with the optimum design of composite laminated plates. Both ply orientation angles and ply thicknesses of the composite plate are used as design variables. The optimum design process is divided into two sublevels. In the first sublevel, the strain energy of the plate is minimized by changing the ply orientation angles while the ply thickness distributions remain unmodified. In the second sublevel, with the angle values obtained in the first sublevel, the optimum thickness distribution of each ply is obtained by minimizing the structural weight while satisfying stiffness and gauge constraints. The final optimum design is achieved by iterating between these two sublevels. The stiffness analysis is performed by the finite element method in which a triangular element is used that is suitable for from thin to thick plates and includes the transverse shear effects. All the derivative analysis is performed analytically. The mathematical programming method called Constrained Variable Metric is used to solve the optimum problem. An example is provided for a rectangular laminated plate with good results to show the effectiveness of the method.

Grounded theory, supported by leading designers, argues for an integrated approach covering end users and designers. However, no substantial work on apparel design has been done so far where a balance is maintained by combining the opinions of consumers and the designers. The purpose of this paper is to provide an analytical framework for designing apparel considering both consumers’ opinions and fashion designers’ views.

An algorithm is proposed for reducing attributes and their levels to carry out conjoint analysis and assign utilities to different attributes and their levels. After selecting the best three design combinations based on their utilities, the authors have arrived at optimum design combinations. Through Delphi method, the opinions of a few fashion designers about these selected design combinations have been collected for matching with optimum design.

An optimum design is suggested for a formal office shirt, for North Indian women, by integrating opinions of designers and consumers.

Attribute and level reduction technique is an original contribution to the literature. Further, the authors’ approach to apparel design may provide a guideline to apparel manufacturers when designing their products. Knowledge of optimum design combinations gained through this approach may help apparel manufacturers and retailers in bringing efficiency in stock keeping unit management by keeping more stocks of apparel with optimum design combinations and thus ensuring a better return on investment made on their stocks.

Porous media can provide excellent performance in thermal energy transport applications. This study aims to optimise the square porous slabs (placed in the middle of the channel) parameters to enhance the cooling performance of the jet-impingement microchannel heat sink.

Three levels of each design parameters, i.e. porous slab side, porous slab height, type of material, permeability and quadratic drag factor, are studied; and an L₂₇ orthogonal array is adopted to generate the design points in the specified design space. Optimum designs of the porous media slabs are achieved to minimise the maximum-wall temperature, thermal resistance and pressure drop and maximise the average heat transfer coefficient and figure of merit (FOM).

Results exhibited that the porous media material and permeability are the most, whereas drag factor is the least significant factors with respect to the overall performance of the heat sink. The optimum value of FOM for the proposed hybrid heat sink model belongs to the set of design variables, i.e. 0.4 mm slab side, 0.6 mm slab height, 5 × 10⁻¹¹ m² permeability, 0.21 drag factor and copper as substrate material.

This study proposes a novel design and a hybrid approach to investigate and optimise the hydrothermal performance of jet impingements on porous slabs inserted in the microchannels.