• IE interfaces
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• v.16 no.4
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• pp.485-495
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• 2003

This paper reports on the application of the integration of mathematical programming model and database in a decision support system (DSS) for the planning of the multi-reservoir operating system. The DSS is based on a multi-objective, mixed-integer goal programming (MIGP) model, which can generate efficient solutions via the weighted-sums method (WSM). The major concern of this study is seamless, efficient integration between the mathematical model and the database, because there are significant differences in structure and content between the data for a mathematical model and the data for a conventional database application. In order to load the external optimization results on the database, we developed a systematic way of naming variable/constraint so that a rapid identification of variables/constraints is possible. An efficient database structure for planning of the multi-reservoir operating system is presented by taking advantage of the naming convention of the variable/constraint.

• Smart Structures and Systems
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• v.3 no.3
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• pp.245-261
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• 2007

Nonlinear time-domain system identification (SI) algorithm is proposed to assess damage in a shear building by synchronously estimating time-varying stiffness and damping parameters using measured acceleration data. Mass properties have been assumed as the a priori known information. Viscous damping was utilized for the current research. To chase possible nonlinear dynamic behavior under severe vibration, an incremental governing equation of vibrational motion has been utilized. Stiffness and damping parameters are estimated at each time step by minimizing the response error between measured and computed acceleration increments at the measured degrees-of-freedom. To solve a nonlinear constrained optimization problem for optimal structural parameters, sensitivities of acceleration increment were formulated with respect to stiffness and damping parameters, respectively. Incremental state vectors of vibrational motion were computed numerically by Newmark-${\beta}$ method. No model is pre-defined in the proposed algorithm for recovering the nonlinear response. A time-window scheme together with Monte Carlo iterations was utilized to estimate parameters with noise polluted sparse measured acceleration. A moving average scheme was applied to estimate the time-varying trend of structural parameters in all the examples. To examine the proposed SI algorithm, simulation studies were carried out intensively with sample shear buildings under earthquake excitations. In addition, the algorithm was applied to assess damage with laboratory test data obtained from free vibration on a three-story shear building model.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2891-2893
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• 2005

In this paper, we introduce a new category of Self-Organizing Fuzzy Polynomial Neural Networks (SOFPNN) that is based on a genetically optimized multi-layer perceptron with fuzzy polynomial neurons (FPNs) and discuss its comprehensive design methodology involving mechanisms of genetic optimization. The conventional SOFPNN algorithm leads to a tendency to produce overly complex networks as well as a repetitive computation load by the trial and error method and/or the a repetitive parameter adjustment by designer. In order to generate a structurally and parametrically optimized network, such parameters need to be optimal. In this study, in solving the problems with the conventional SOFPNN, we introduce a new design approach of evolutionary optimized SOFPNN. Optimal parameters design available within FPN (viz. the no. of input variables, the order of the polynomial, input variables, and the no. of membership function) lead to structurally and parametrically optimized network which is more flexible as well as simpler architecture than the conventional SOFPNN. In addition, we determine the initial apexes of membership functions by genetic algorithm.

• Journal of Advanced Marine Engineering and Technology
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• v.16 no.5
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• pp.60-66
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• 1992

In most cases a structure consists of the assembly of some substructures, we assemble them with various joints, and the structure is fixed to a foundation through mounts. In case of the structure with rigid joints like welding, the Finite Element Mothod could be easily used to analyize the structure's characteristics, but in case of the structure with elastic joints like bolts or rivets, it might be difficult to analyize it by taking account of joint's rigidities, with the conventional method. This paper proposes the method to identify the joint rigidities by the Sensitive Analysis Method and the Optimization Techniques. And the proposed method applied to identify the rigidities of 4 bolts to combine 2 plates(500mm long, 100mm wide, 3.15mm thich). The analized results were well coincident with the experimental results. To confirm the reliability 0 the rigidities identified, another trial was done for the stucture to combine other 2 plates with same joints. The results were good too. This paper is proposin the identifying method of the joint rigidity of a structure, and it could be used for the data base of the joint rigidity and for the guidance to select joint stiffness.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2821-2823
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• 2002

In this paper we propose the Multi-FNN (Fuzzy-Neural Networks) for optimal identification modeling of complex system. The proposed Multi-FNNs is based on a concept of FNNs and exploit linear inference being treated as generic inference mechanisms. In the networks learning, backpropagation(BP) algorithm of neural networks is used to updata the parameters of the network in order to control of nonlinear process with complexity and uncertainty of data, proposed model use a HCM(Hard C-Means)clustering algorithm which carry out the input-output dat a preprocessing function and Genetic Algorithm which carry out optimization of model The HCM clustering method is utilized to determine the structure of Multi-FNNs. The parameters of Multi-FNN model such as apexes of membership function, learning rates, and momentum coefficients are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization abilities of the model. NOx emission process data of gas turbine power plant is simulated in order to confirm the efficiency and feasibility of the proposed approach in this paper.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.10 s.253
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• pp.1209-1218
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• 2006

Precision servomechanisms are widely used in machine tool, semiconductor and flat panel display industries. It is important to improve contouring accuracy in high-precision servomechanisms. In order to improve the contouring accuracy, cross-coupled control systems have been proposed. However, it is very difficult to select the controller parameters because cross-coupled control systems are multivariable, nonlinear and time-varying systems. In this paper, in order to improve contouring accuracy of a biaxial servomechanism, a cross-coupled controller is adopted and an optimal tuning procedure based on an integrated design concept is proposed. Strict mathematical modeling and identification process of a servomechanism are performed. An optimal tuning problem is formulated as a nonlinear constrained optimization problem including the relevant controller parameters of the servomechanism. The objective of the optimal tuning procedure is to minimize both the contour error and the settling time while satisfying constraints such as the relative stability and maximum overshoot conditions, etc. The effectiveness of the proposed optimal tuning procedure is verified through experiments.

• Structural Engineering and Mechanics
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• v.78 no.5
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• pp.519-528
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• 2021

One of the most efficient designs of solar trackers for photovoltaic panels is the single-axis tracker, which holds the panels along a torque tube that is driven by a motor at the central section. These trackers have evolved to become extremely slender structures due to mechanical optimization against static load and the need of cost reduction in a very competitive market. Owing to the corresponding decrease in mechanical resistance, some of these trackers have suffered aeroelastic instability even at moderate wind speeds, leading to catastrophic failures. In the present work, an analytical and experimental approach has been developed to study that phenomenon. The analytical study has led to identify the dimensionless parameters that govern the motion of the panel-tracker structure. Also, systematic wind tunnel experiments have been carried out on a 3D aeroelastic scale model. The tests have been successful in reproducing the aeroelastic phenomena arising in real-scale cases and have allowed the identification and a close characterization of the phenomenon. The main results have been the determination of the critical velocity for torsional galloping as a function of tilt angle and a calculation methodology for the optimal sizing of solar tracker shafts.

• Microbiology and Biotechnology Letters
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• v.19 no.2
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• pp.135-139
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• 1991

Tridecanedioic acid (DC-13), starting material of the valuable musk ethylene brassylate, was obtained from n-tridecane by the Candida tropicalis mutant. The mutants were first obtained from primary screening step using the selective medium and then solid phase extraction sampling method was used for the selective isolation of organic acids from the cultured media of mutants. The resulting acids were directly converted to volatile tert-butyldimethyl silyl delivatives, which were then analyzed by gas chromatography. The efficient GC profiling method was used for the rapid identification of the mutant producing DC-13 in large quantity, and for the optimization of the culture conditions of mutant. The optimal culture conditions were found as follows: pH 8.0, 30$^{\circ}C$, 250rpm, 48hour of culture and $(NH_4)_2HPO_4$ as nitrogen source.

• Mycobiology
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• v.37 no.3
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• pp.218-224
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• 2009

The principal objective of this study was to determine the optimal liquid culture conditions in shake flasks for maximal sporulation of Beauveria bassiana. The optimal initial pH for the spore production of B. bassiana using Potato Dextrose Broth was 5.2. The screening in shake flasks of carbon and nitrogen sources resulted in the identification of an optimal medium based on 3% sucrose and 1% casamino acid, with a C : N ratio of 22 : 4. Using this medium, a production level of $5.65{\times}10^7$ spores per ml was obtained after 5 days of culture. Using 3% corn meal, 2% corn steep powder, and 2% rice bran, the maximum spore concentration of $8.54{\times}10^8$/ml was achieved 8 days after inoculation at $25^{\circ}C$ in a rotary shaking incubator operated at 200 rpm. This represents a yield gain of approximately 2.89 times that of pre-optimization.

• Interaction and multiscale mechanics
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• v.5 no.3
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• pp.211-228
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• 2012

This paper reports the development of a generalized inverse analysis formulation for the parameter estimation of four-parameter Burger model. The analysis is carried out by formulating the problem as a mathematical programming formulation in terms of identification of the design vector, the objective function and the design constraints. Thereafter, the formulated constrained nonlinear multivariable problem is solved with the aid of fmincon: an in-built constrained optimization solver module available in MatLab. In order to gain experience, a synthetic case-study is considered wherein key issues such as the determination and setting up of variable bounds, global optimality of the solution and minimum number of data-points required for prediction of parameters is addressed. The results reveal that the developed technique is quite efficient in predicting the model parameters. The best result is obtained when the design variables are subjected to a lower bound without any upper bound. Global optimality of the solution is achieved using the developed technique. A minimum of 4-5 randomly selected data-points are required to achieve the optimal solution. The above technique has also been adopted for real-time settlement of four oil refineries with encouraging results.