Evaluation of transverse cracks detection depth in MFL rail NDT

The limiting detection depth of subsurface defects is considered as an important efficiency factor of Magnetic Flux Leakage (MFL) method of railway nondestructive testing. This issue is particularly topical since magnetizing systems of new type with increased interpole distance are implementing. The speculative limit of detection depth is investigated by numerical simulation. Test data of NDT facilities equipped with new magnetizing system are presented.     

Design optimization of slender elastic beam with initial twist using genetic algorithms and finite element analysis

This paper aims to obtain the optimal composite slender beam design for a rotor blade. The cross-sectional dimensions are considered as design variables. The objective is to optimize the box beam to attain a target matrix of stiffness values and maximum elastic coupling. The optimization process is performed using a genetic algorithm (GA), associated with a variational asymptotic method for the structural analysis. The stiffness control of arbitrary, complex section under some design condition is performed in composite beam where the geometrically nonlinear characteristic of the structure is considered. The objective function is defined as the weight, strength and fatigue life. The laminate thicknesses are to be determined optimally by defining a design index comprising a weighted average of the objective functions and determining the minimum.     

Behavior of a lug with through and non-through cracks under the action of an arbitrary load

The stress-intensity factor in lugs with one-sided and two-sided cracks and corner cracks at holes is determined. The stress-intensity factor, residual stress, and growth time of fatigue cracks are determined for lugs with an arbitrarily positioned crack under the action of an arbitrary load.     

Part-machine family formation using genetic algorithms in a fuzzy environment

In traditional cell-formation problems, it is assumed that each part is developed on a single machine. However, in many realistic situations, the suitability of alternative machines for developing the same part feature is frequently vague. Therefore, the fuzzy relation is ideally suited to represent this vague and uncertain cell-formation problem. Furthermore, part-machine family formation problems are usually NP-complete. In this study, a genetic algorithm (GA) is used to deal with the problem. The aim of this study is to design a GA-based algorithm to solve the part-machine family formation problem in a fuzzy environment. The results of computational tests presented are very promising.     

Minimizing flow-time variance in a single-machine system using genetic algorithms

A tandem automated guided vehicle (AGV) system deals with grouping workstations into some non-overlapping areas and assigning to each area exactly one AGV. This paper presents a new non-linear integer mathematical model to group n machines into N loops to minimize both inter-loop and intra-loop flow simultaneously based on balanced-loops strategy and inter-machine flows taken from ideas of cellular manufacturing systems. Due to computational difficulties of exact methods in solving the proposed model, a simulated annealing (SA) algorithm is proposed. A number of test problems are generated at random and solved by the proposed SA in order to show the efficiency of the algorithm. Finally, the results are reported by both the Lingo software and the proposed SA algorithm.     

Nonlinear predictive control of a drying process using genetic algorithms

A nonlinear predictive control technique is developed to determine the optimal drying profile for a drying process. A complete nonlinear model of the baker's yeast drying process is used for predicting the future control actions. To minimize the difference between the model predictions and the desired trajectory throughout finite horizon, an objective function is described. The optimization problem is solved using a genetic algorithm due to the successful overconventional optimization techniques in the applications of the complex optimization problems. The control scheme comprises a drying process, a nonlinear prediction model, an optimizer, and a genetic search block. The nonlinear predictive control method proposed in this paper is applied to the baker's yeast drying process. The results show significant enhancement of the manufacturing quality, considerable decrease of the energy consumption and drying time, obtained by the proposed nonlinear predictive control.     

Scanning with parallel transfer of an electron beam for a transverse profile monitor of an intense ion bunch

A method for fast parallel scanning of a low-energy electron beam (scan amplitude, ± 4 cm; scan time, 10 ns; beam energy, 60 keV) is described. Results of application of this method to nondestructive diagnostics of the proton bunch are presented.     

Free transverse vibration of an axially loaded non-uniform spinning twisted Timoshenko beam using differential transform

This study investigates the vibration problems of an axially loaded non-uniform spinning twisted Timoshenko beam. First, using the Timoshenko beam theory and Hamilton's principle, we derive the governing equations and boundary conditions of the beam. Secondly, the differential transform method is used to solve these equations with appropriate boundary conditions. Finally, the effects of the twist angle, spinning speed, and axial force on the natural frequencies of a non-uniform Timoshenko beam are investigated and discussed.     

The extensible elastica of a prestressed beam with arbitrary boundary conditions

An axially prestressed elastic beam with arbitrary boundary conditions is considered. The solution of the problem is sought within the non-linear bending theory derived under the assumptions of finite deflections and small strains. The extensibility of the beam axis is taken into account, while the influence of shear force is neglected. A set of transcendental equations with incomplete elliptic integrals is obtained as the general solution. For small deflections, a linear solution of the problem is given too. Several numerical results for the case of prestressed bolt in a joint are discussed and presented in the form of appropriate diagrams.     

Selection of an optimal parametric combination for achieving a better surface finish in dry milling using genetic algorithms

In machining, coolants improve machinability, increase productivity by reducing tool wear and extend tool life. However, due to ecological and human health problems, manufacturing industries are now being forced to implement strategies to reduce the amount of cutting fluids used in their production lines. A trend that has emerged to solve these problems is machining without fluid – a method called dry machining – which has been made possible due to technological innovations. This paper presents an experimental investigation of the influence of tool geometry (radial rake angle and nose radius) and cutting conditions (cutting speed and feed rate) on machining performance in dry milling with four fluted solid TiAlN-coated carbide end mill cutters based on Taguchi’s experimental design method. The mathematical model, in terms of machining parameters, was developed for surface roughness prediction using response surface methodology. The optimization is then carried out with genetic algorithms using the surface roughness model developed and validated in this work. This methodology helps to determine the best possible tool geometry and cutting conditions for dry milling.     

Nonlinear finite element analysis of a laminated cylindrical shell with transverse matrix cracks

A clamped laminated cylindrical shell is presented to investigate nonlinear structural behavior involving geometrically nonlinear deformation. In the investigation, transverse matrix cracks are considered in the stiffness of the laminated cylindrical shell. Stiffness degradation is examined for several laminated angles and transverse crack density. Micro-mechanics theory on the composite material was used to derive the degraded stiffness of the laminated cylindrical shell due to the crack density. Iterative numerical scheme was developed to calculate the degraded composite stiffness which is a complicated relation with the crack density. A nonlinear finite element program was developed using 3-D degenerated shell element and the fist order shear deformation theory to consider the large deformation of the clamped laminated cylindrical shell. The updated Lagrangian method is used for nonlinear finite element analysis. Nonlinear structural responses of the laminated cylindrical shell were examined for various stacking sequences and crack density under transversely loaded pressure. Also, the effect of crack opening/closed was considered in the examination. Through this study, it is realized that the transverse matrix crack causes moderate stiffness reduction and affects the responses of the composite shell.     

Design of PID-type controllers using multiobjective genetic algorithms

The design of a PID controller is a multiobjective problem. A plant and a set of specifications to be satisfied are given. The designer has to adjust the parameters of the PID controller such that the feedback interconnection of the plant and the controller satisfies the specifications. These specifications are usually competitive and any acceptable solution requires a tradeoff among them. An approach for adjusting the parameters of a PID controller based on multiobjective optimization and genetic algorithms is presented in this paper. The MRCD (multiobjective robust control design) genetic algorithm has been employed. The approach can be easily generalized to design multivariable coupled and decentralized PID loops and has been successfully validated for a large number of experimental cases.     

Scheduling a single machine with multiple preventive maintenance activities and position-based deteriorations using genetic algorithms

In this paper, we study a single machine scheduling problem with deteriorating processing time of jobs and multiple preventive maintenances which reset deteriorated processing time to the original processing time. In this situation, we consider three kinds of problems whose performance measures are makespan, total completion time, and total weighted completion time. First, we formulate integer programming formulations, and using the formulations, one can find optimal solutions for small problems. Since these problems are known to be NP-hard and the size of real problem is very large, we propose a number of heuristics and design genetic algorithms for the problems. Finally, we conduct some computational experiments to evaluate the performance of the proposed algorithms.     

Free vibration analysis of Euler-Bernoulli beam with double cracks

In this paper, the influence of two open cracks on the dynamic behavior of a double cracked simply supported beam is investigated both analytically and experimentally. The equation of motion is derived by using the Hamilton’s principle and analyzed by numerical method. The simply supported beam is modeled by the Euler-Bemoulli beam theory. The crack sections are represented by a local flexibility matrix connecting three undamaged beam segments. The influences of the crack depth and the position of each crack on the vibration mode and the natural frequencies of a simply supported beam are analytically clarified for the single and double cracked simply supported beam. The theoretical results are also validated by a comparison with experimental measurements.     

A metamodel using neural networks and genetic algorithms for an integrated optimal design of mechanisms

This work examines the possibility of using genetic algorithms and some neural networks to optimise mechanisms. A detailed example shows that using this stochastic method along with neural networks is very efficient. We can thus speak of a metamodel for optimisation in the context of integrated design .     

Optimization of manual fabric-cutting process in apparel manufacture using genetic algorithms

In apparel manufacturing, experience and subjective assessment of production planners are used quite often to plan the production schedules in their fabric-cutting departments. The quantities of cut-pieces produced by fabric-cutting departments based on these non-systematic schedules cannot fulfil the cut-piece requirements of the downstream sewing lines and minimize the makespan. This paper proposes a genetic algorithms (GAs) approach to optimize both the cut-piece requirements and the makespan of the conventional fabric-cutting departments using manual spreading and cutting methods. An optimization model for the manual fabric cutting process based on GAs was developed. Two sets of production data were collected to validate the performance of the model and the experimental results were obtained. From the results, it can be found that both the makespan and cut-piece fulfilment rates are improved in which the latter is improved significantly.     

Crack tip shielding and anti-shielding effects of parallel cracks for a superconductor slab under an electromagnetic force

In this letter, the shielding or anti-shielding effect is firstly applied to obtain the behavior of two parallel cracks in a two-dimensional type-II superconducting under electromagnetic force. Fracture analysis is performed by the finite element method and the magnetic behavior of superconductor is described by the critical state Bean model. The stress intensity factors at the crack tips can be obtained and discussed for decreasing field after zero-field cooling. The shielding or anti-shielding effect at the crack tips depend on the distance between two parallel cracks and the crack length. The results indicate that the shielding effects of the two parallel cracks increase when the distance between the two parallel cracks decreases. It can be also obtained that the superconductors with shorter cracks has more remarkable shielding effect than those with longer cracks.     

Optimisation of fed-batch culture of hybridoma cells using genetic algorithms

In this paper, a program describing a genetic algorithm is used for optimising fed-batch culture hybridoma cells to obtain the highest yield over certain time period. Optimal feed rate trajectories for a single feed stream containing both glucose and glutamine, and separate feed streams of glucose and glutamine are determined via the genetic algorithm. As compared to the optimal constant feed rate regime, optimal varying feed rate trajectories improve the final monoclonal antibodies concentration by 10% for the single feed rate case and by 39% for the multi feed rate case in this simulation. In comparsion with a dynamic programming, GA calculated feed trajectories yield a much higher level of monoclonal antibodies concentration.     

Crack identification in a cantilever beam under uncertain end conditions

Crack identification in structures by changes of their dynamic behavior has been studied in the past, and various methods were developed enabling the calculation of crack location along a beam, by using the variations in the natural frequencies between the initial undamaged state and a later, cracked beam. Application of this procedure to cantilever beams may result in unacceptably large errors, due to changes in clamp rigidity between measurements in the two states. The present research studies the problem of crack identification in a cantilever when clamp rigidity is unknown, and may change with time. An identification method is developed, which requires monitoring of three natural bending frequencies. Crack location may then be found by using a universal curve, i.e. independent of any beam property (geometry or material). The proposed method was verified by numerical simulation and experiment.