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作者： Vrh, M. Halilovič, M. Štok, B. Laboratory for Numerical Modelling and Simulation Faculty of Mechanical Engineering University of Ljubljana Aškerčeva 6 SI-1000 Ljubljana Slovenia Kovinoplastika Lož Stari trg pri Ložu Slovenia

In accordance with the great importance given to the subject of stiffness degradation, in particular with regard to metal forming, this work experimentally investigates the anisotropic elastic properties of plastically prestrained cold-rolled sheet metal (stainless steel EN 1.4301, also AISI 304). From the experiments performed, two main conclusions regarding stiffness degradation can be extracted. First, since under specific stretching the intensity of the normalized Young's moduli degradation in both directions remains approximately similar, it may be concluded that the potential initial elastic anisotropy tends to be preserved during loading. Second, as the evidenced stiffness degradation has proved to be strongly correlated with the stretching direction of the sheet metal, it can be concluded that the stiffness evolution in the cold rolled sheet steel is path dependent. These interesting discoveries also provide some answers for modelling the kinetic damage evolution laws in damage mechanics. © Society for Experimental Mechanics 2010.

关键词： Anisotropy

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Green's function and Bloch theory for the analysis of the dynamic response of a periodically supported beam to a moving load

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Journal of Physics: Conference Series 2012年第1期382卷

作者： R Lassoued M Lecheheb G Bonnet Laboratory of Materials Durability of Construction Department of Civil Engineering Faculty of Engineering sciences University Mentouri Constantine Algeria University Paris East Marne la Vallée Laboratory of modelling and simulation Multi Echelle CNRS UMR 8208 5 boulevard Descartes 77454 Marne la Vallée Cedex France

This paper describes an analytical method for the wave field induced by a moving load on a periodically supported beam. The Green's function for an Euler beam without support is evaluated by using the direct integration. Afterwards, it introduces the supports into the model established by using the superposition principle which states that the response from all the sleeper points and from the external point force add up linearly to give a total response. The periodicity of the supports is described by Bloch's theorem. The homogeneous system thus obtained represents a linear differential equation which governs rail response. It is initially solved in the homogeneous case, and it admits a no null solution if its determinant is null, this permits the establishment the dispersion equation to Bloch waves and wave bands. The Bloch waves and dispersion curves contain all the physics of the dynamic problem and the wave field induced by a dynamic load applied to the system is finally obtained by decomposition into Bloch waves, similarly to the usual decomposition into dynamic modes on a finite structure. The method is applied to obtain the field induced by a load moving at constant velocity on a thin beam supported by periodic elastic supports.

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Energy efficient clustering algorithm in wireless sensor networks using fuzzy logic control

Energy efficient clustering algorithm in wireless sensor net...

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IEEE Colloquium on Humanities, Science and engineering (CHUSER)

作者： Z.W. Siew A. Kiring H.T. Yew P. Neelakantan K.T.K. Teo Modelling Simulation and Computing Laboratory School of Engineering and Information Technology Universiti Malaysia Sabah Kota Kinabalu Malaysia

In general, environment monitoring cluster based hierarchical routing protocol is among the most common protocol being opted due to the load balancing among each other sensor. Sensors are randomly deployed in a specific area to collect useful information periodically for a few months or even a few years. Therefore, battery power limitation becomes a challenging issue. It is also impractical to maintain the network lifetime by changing the battery frequently. Low energy adaptive cluster hierarchical (LEACH) is one of the common clustering protocols that will elect the cluster head based on the probability model which will possibly lead to a reduce in network lifetime due to election of cluster head with a least desired location in the network. For wireless sensor networks, the distribution of cluster head selection directly influences the network's lifetime. This paper presents factors which will affect the network lifetime and apply fuzzy logic based cluster head selection conducted in base station. The base station considers two selection criteria from sensor nodes which are energy level and distance to the base station to select the suitable cluster head that will prolong the first node die (FND) time, data stream guaranteed for every round and also increase the throughput received by the base station before FND.

关键词： Base stations Protocols Peer to peer computing Mathematical model Clustering algorithms Fuzzy logic Wireless sensor networks

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Genetic algorithm based PID optimization in batch process control

Genetic algorithm based PID optimization in batch process co...

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International Conference on Computer Applications and Industrial Electronics (ICCAIE)

作者： M.K. Tan Y.K. Chin H.J. Tham K.T.K. Teo Modelling Simulation and Computing Laboratory School of Engineering and Information Technology Universiti Malaysia Sabah Kota Kinabalu Malaysia

The primary aim in batch process is to enhance the process operation in order to achieve high quality and purity product while minimising the production of undesired by-product. However, due to the difficulties to perform online measurement, batch process supervision is based on the direct measurable quantities, such as temperature. During the process, a large amount of exothermic heat is released when the reactants are mixed together. The exothermic behaviour causes the reaction to become unstable and consequently the quality and purity of the final product will be affected. Therefore, it is important to have a control scheme which is able to balance the needs of process safety with the product quality and purity. Since the chemical industries are still applying PI and PID to control the batch process, researchers are keen to optimize PID parameters using artificial intelligence (AI) techniques. However, most of these PID optimization techniques need online process model to predetermine the optimizer parameters. However in practice, the dynamic model of the batch process is poorly known. As a result, majority of the studies focused on acceptable performance instead of optimum performance of the batch process control. This paper proposes a new genetic algorithm (GA) optimizer which consists of additional information of the online estimated model parameters in addition to the PID parameters as the string of the GA. The simulation results show that the proposed GA auto-tuning method is a better candidate than the regular GA where the estimated model parameters in fitness function is capable to control the process temperature while avoiding model mismatch and disturbance condition.

关键词： Inductors Heating Batch production systems Genetic algorithms Coolants Optimization Process control

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Adaptive hybrid channel assignment in wireless mobile network via genetic algorithm

Adaptive hybrid channel assignment in wireless mobile networ...

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International Conference on Hybrid Intelligent Systems (HIS)

作者： Y. S. Chia Z. W. Siew A. Kiring S. S. Yang K. T. K. Teo Modelling Simulation and Computing Laboratory School of Engineering and Information Technology Universiti Malaysia Sabah Kota Kinabalu Malaysia

In wireless mobile network, the challenge is to assign appropriate frequency spectrum channels to requested calls while maintaining a desirable level of electromagnetic compatibility (EMC) constraint. An effective channel assignment technique is important to improve the system capacity and to reduce the effect of the interference. Most of the existing channel assignment approaches are based on deterministic methods. In this paper, an adaptive hybrid channel assignment (HCA) technique based on genetic algorithm (GA) is proposed. The proposed GA based optimization in HCA scheme is capable to adapt the population size to the number of eligible channels for a particular cell upon new call arrivals in order to achieve faster convergence speed. Besides, the proposed approach can handle both the reassignment of existing calls as well as the allocation of channel to a new call in an adaptive process to maximize the utility of the limited frequency spectrum. The simulation for both uniform and nonuniform traffic distributions on a 49-cells network model show that the average new incoming call blocking or call dropping probability for the proposed hybrid channel optimization method is lower than the deterministic HCA methods.

关键词： Genetic algorithms Vectors Interference Channel allocation Resource management Biological cells Optimization

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CUSUM-Variance Ratio based Markov Chain Monte Carlo algorithm in overlapped vehicle tracking

CUSUM-Variance Ratio based Markov Chain Monte Carlo algorith...

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International Conference on Computer Applications and Industrial Electronics (ICCAIE)

作者： W.Y. Kow W.L. Khong Y.K. Chin I. Saad K.T.K. Teo Modelling Simulation and Computing Laboratory School of Engineering and Information Technology Universiti Malaysia Sabah Kota Kinabalu Malaysia

Markov Chain Monte Carlo (MCMC) is one of the algorithms that have been widely implemented in tracking vehicle for traffic surveillance purposes. The sampling efficiency of the algorithm is essential to determine the vehicle position accurately. However, the sample size of the algorithm is still remaining an issue as non-optimal sample size will defect the tracking accuracy, especially when the moving vehicle is overlapped. Adaptive sample size of MCMC has been implemented using CUSUM Path Plot and Variance Ratio algorithms to perform vehicle tracking. CUSUM Path Plot determines the samples convergence rate by calculating the hairiness of the sample size whereas Variance Ratio method computes two sets of MCMC to determine the samples steady state. This paper proposes the fusion of CUSUM-Variance ratio algorithm to enhance the tracking efficiency. Experimental results shows that the CUSUM-Variance Ratio method have a better performance in tracking the overlapping vehicle with higher accuracy and more optimal sample size compared to the standalone CUSUM Path Plot and Variance Ratio approaches.

关键词： Vehicles Target tracking Convergence Indexes Accuracy Silicon Algorithm design and analysis

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Overlapping vehicle tracking via adaptive particle filter with multiple cues

Overlapping vehicle tracking via adaptive particle filter wi...

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IEEE International Conference on Control System, Computing and engineering (ICCSCE)

作者： W.L. Khong W.Y. Kow Y.K. Chin I. Saad K.T.K. Teo Modelling Simulation and Computing Laboratory School of Engineering and Information Technology Universiti Malaysia Sabah Kota Kinabalu Malaysia

Vehicle tracking is a vital approach to assist the on-road traffic surveillance system. Since the on-road vehicles is increasing, occlusion and overlapping of vehicles is often happen in the traffic surveillance scene. Therefore, segmentation and tracking of the occlusion or overlapped vehicle can be a challenging task in surveillance system via image processing. In this paper, a multiple cues overlapping vehicle tracking algorithm is proposed to continuously track the occluded vehicle effectively. The earlier vehicle tracking systems are normally based on colour feature which will leads to inaccurate results when the background colour is complex or too similar with the target vehicle. On the other hand, shape feature will increase the accuracy but consume more computation time in the resampling process during overlapping. The experimental results show that enhancement of the particle filter resampling process with multiple cues is capable to track the overlapped vehicle with higher accuracy and without compromising the processing time.

关键词： Vehicles Color Target tracking Shape Particle filters Histograms Accuracy

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Multiple intersections traffic signal timing optimization with genetic algorithm

Multiple intersections traffic signal timing optimization wi...

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IEEE International Conference on Control System, Computing and engineering (ICCSCE)

作者： Y.K. Chin K.C. Yong N. Bolong S.S. Yang K.T.K. Teo Modelling Simulation and Computing Laboratory School of Engineering and Information Technology Universiti Malaysia Sabah Kota Kinabalu Malaysia

Traffic congestion in the urban area occurs more frequent than the past due to rapidly increasing on road vehicle usage rates. It could seriously hinder the development of urban area if a well management system has not being established. These scenarios necessitate the development of advance traffic management systems to increase the performance of signalized intersection. Traffic signal timing management (TSTM) system which comprise of genetic algorithm based optimization is proposed. Using a proper TSTM system, network traffic flow can be improved with considerably less cost than other infrastructural improvements. The proposed genetic algorithm based optimization approach allows signal timing parameters such as offset, cycle time, green split and phase sequence to be optimized with objective of minimum delay and better traffic fluency. The proposed GATSTM system has the ability to handle and manage the dynamic changes of the traffic networks condition by calibrating the system parameters accordingly.

关键词： Timing Genetic algorithms Vehicles Biological cells Optimization Traffic control

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Kernel-based object tracking via particle filter and mean shift algorithm

Kernel-based object tracking via particle filter and mean sh...

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International Conference on Hybrid Intelligent Systems (HIS)

作者： Y. S. Chia W. Y. Kow W. L. Khong A. Kiring K. T. K. Teo Modelling Simulation and Computing Laboratory School of Engineering and Information Technology Universiti Malaysia Sabah Kota Kinabalu Malaysia

One of the critical tasks in object tracking is the tracking of fast-moving object in random motion, especially in the field of machine vision applications. An approach towards the hybrid of particle filter (PF) and mean shift (MS) algorithm in visual tracking is proposed. In this proposed system, complete occlusion and random movement of object can be handled due to its ability in predicting the object location with adaptive motion model. In addition, the PF is capable to maintain multiple hypotheses to handle clutters in background and temporary failure. However PF requires a large number of particles to approximate the true posterior of the target dynamics. Therefore, MS algorithm is applied to the sampling process of the PF to move these particles in gradient ascent direction. Consequently a small sample size will be sufficient to represent the system dynamics accurately. The proposed approach is aimed to track the moving object in random directions under varying conditions with acceptable computational time.

关键词： Target tracking Kernel Image color analysis Adaptation models Particle filters Histograms

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Shear test based identification of the hardening behaviour of stainless sheets after the onset of necking using cubic spline interpolation

Shear test based identification of the hardening behaviour o...

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10th International Conference on Computational Structures Technology, CST 2010

作者： Vrh, M. Halilovic, M. Štok, B. Laboratory for Numerical Modelling and Simulation Faculty of Mechanical Engineering University of Ljubljana Slovenia

ISBN: (纸本)9781905088386

The paper focuses on a reliable identification of the hardening curve of sheet metal after onset of necking with the developed shear test. The main comparative advantage of the test is its simple procedure for which no further development of experimental equipment regarding standard tensile test is needed. The only modification of the standard tensile test refers to a purposely designed symmetric shear specimen which enables achievement of large shear strains during stable loading condition. In addition the paper presents the hardening curve approximation based on the cubic spline techniques. Such approach is very convenient for use because splines are smooth and are able to approximate accurately local curvatures without global estimation being influenced. From a comparison between the analytically extrapolated and identified hardening curves it is shown that using analytical extrapolation at large strains is seriously flawed as a result of the considerable differences between the curves. © Civil-Comp Press, 2010.

关键词： Hardening

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