• Smart Structures and Systems
• /
• v.20 no.6
• /
• pp.729-737
• /
• 2017

Piezoelectric composite laminates are a powerful material system that offers vast options to improve structural behavior. Successful design of piezoelectric adaptive structures and testing of control laws call for highly accurate, reliable and numerically efficient numerical tools. This paper puts focus onto linear and geometrically nonlinear static and dynamic analysis of smart structures made of such a material system. For this purpose, highly efficient linear 3-node and 4-node finite shell elements are proposed. Both elements employ the Mindlin-Reissner kinematics. The shear locking effect is treated by the discrete shear gap (DSG) technique with the 3-node element and by the assumed natural strain (ANS) approach with the 4-node element. Geometrically nonlinear effects are considered using the co-rotational approach. Static and dynamic examples involving actuator and sensor function of piezoelectric layers are considered.

• Asian-Australasian Journal of Animal Sciences
• /
• v.8 no.3
• /
• pp.295-300
• /
• 1995

Data from purebred and crossbred cattle involving Holstein and the Local breed in Bangladesh were used to estimate the genetic effects on average daily milk yield and birth weight A total of 877 records on average daily milk yield for 4 types of breed groups and a total of 418 records on birth weight for 5 breed groups were analyzed. Two different methods were applied in this study; the least squares analysis of variance approach and the linear regression approach. Breed group effects were highly significant for both average daily milk yield and birth weight. The result showed that straightbred Holstein produced the highest milk yield and the 7/8 crosses ranked highest in birth weight For the two traits, the additive breed effect was highly significant, whereas the individual heterosis effect was not significant. Furthermore, this study showed a negative maternal heterosis for average daily milk yields and a positive maternal heterosis for birth weight Comparing the breed least squares means obtained from the linear regression approach revealed that straightbred Holstein produced the highest average milk yield and the 3/4 crosses were predicted to have the largest birth weight. It is indicated that the linear regression approach can adequately separate the genetic component of performance, estimate unknown crossbreeding parameters and predict unknown performance of crosses which are not include in the original data.

• Journal of Power Electronics
• /
• v.13 no.5
• /
• pp.829-840
• /
• 2013

The modified sinusoidal pulse-width modulation (SPWM) is one of the PWM techniques used in three-phase AC-DC buck converters. The modified SPWM works without the current sensor (the converter is current sensorless), improves production of sinusoidal AC current, enables obtainment of near-unity power factor, and controls output voltage through modulation gain (ranging from 0 to 1). The main problem of the modified SPWM is the huge starting current and voltage (during transient) that results from a large step change from the reference voltage. When the load changes, the output voltage significantly drops (through switching losses and non-ideal converter elements). The single-input single-output (SISO) approach with minor-loop voltage feedback controller presented here overcomes this problem. This approach is created on a theoretical linear model and verified by discrete-model simulation on MATLAB/Simulink. The capability and effectiveness of the SISO approach in compensating start-up current/voltage and in achieving zero steady-state error were tested for transient cases with step-changed load and step-changed reference voltage for linear and non-linear loads. Tests were done to analyze the transient performance against various controller gains. An experiment prototype was also developed for verification.

• Journal of the Korean Society for Railway
• /
• v.19 no.4
• /
• pp.547-554
• /
• 2016

This study considered how to estimate the deterioration rate of the track quality index, which represents track geometric irregularity. Most existing studies have used a simple linear regression and regarded the slope of the regression equation as the progress rate. In this paper, we present a Bayesian approach to estimate the track irregularity progress. This Bayesian approach has many advantages, among which the biggest is that it can formally include the prior distribution of parameters which can be derived from historic data or from expert experiences; then, the rate can be expressed as a probability distribution. We investigated the possibility of applying the Bayesian method to the estimation of the deterioration rate by comparing our bayesian approach to the conventional linear regression approach.

• International journal of steel structures
• /
• v.18 no.5
• /
• pp.1654-1665
• /
• 2018

In an irregular prism tensegrity, the number of force equilibrium equations is less than the number of unknown parameters of nodal coordinates and member force ratios. As a result, the form-finding process normally becomes nonlinear with additional conditions or needs to be carried out with the use of iterative procedures. For cases of irregular prism tensegrity which involves large number of members, it was found that previously proposed methods of form-finding are not practical. Moreover, there is a need for a form-finding approach which is able to cater to different requirements on final configuration. In this paper, the length relation condition is introduced to be used in combination with the force equilibrium equation. With the combined use of length relation and equilibrium conditions, a linear form-finding approach for irregular prism tensegrity was successfully formulated and developed. An easy-to-use interactive form-finding tool has been developed which can be used for form-finding of irregular prism tensegrities with large number of elements as well as under diverse specific requirements on their configurations.

• Communications for Statistical Applications and Methods
• /
• v.8 no.2
• /
• pp.319-325
• /
• 2001

In this note, we propose a simple fuzzy linear regression model for fuzzy input-output data based on Tanaka's approach. Then an LP-based method to derived the satisfying solution of the decision making is developed.

• Steel and Composite Structures
• /
• v.4 no.6
• /
• pp.471-487
• /
• 2004

Modular steel scaffolds are commonly used as supporting scaffolds in building construction, and traditionally, the load carrying capacities of these scaffolds are obtained from limited full-scale tests with little rational design. Structural failure of these scaffolds occurs from time to time due to inadequate design, poor installation and over-loads on sites. In general, multi-storey modular steel scaffolds are very slender structures which exhibit significant non-linear behaviour. Hence, secondary moments due to both $P-{\delta}$ and $P-{\Delta}$ effects should be properly accounted for in the non-linear analyses. Moreover, while the structural behaviour of these scaffolds is known to be very sensitive to the types and the magnitudes of restraints provided from attached members and supports, yet it is always difficult to quantify these restraints in either test or practical conditions. The problem is further complicated due to the presence of initial geometrical imperfections in the scaffolds, including both member out-of-straightness and storey out-of-plumbness, and hence, initial geometrical imperfections should be carefully incorporated. This paper presents an extensive numerical study on three different approaches in analyzing and designing multi-storey modular steel scaffolds, namely, a) Eigenmode Imperfection Approach, b) Notional Load Approach, and c) Critical Load Approach. It should be noted that the three approaches adopt different ways to allow for the non-linear behaviour of the scaffolds in the presence of initial geometrical imperfections. Moreover, their suitability and accuracy in predicting the structural behaviour of modular steel scaffolds are discussed and compared thoroughly. The study aims to develop a simplified and yet reliable design approach for safe prediction on the load carrying capacities of multi-storey modular steel scaffolds, so that engineers can ensure safe and effective use of these scaffolds in building construction.

• International Journal of Reliability and Applications
• /
• v.6 no.2
• /
• pp.101-115
• /
• 2005

This article provides a new class of multivariate linear failure rate distributions where every component is a mixture of linear failure rate distribution. The new class includes several multivariate and bivariate models including Marslall and Olkin type. The approach in this paper is based on the introducing a linear failure rate distributed latent random variable. The distribution of minimum in a competing risk model is discussed.

• Proceedings of the KSRS Conference
• /
• v.2
• /
• pp.643-646
• /
• 2006

This paper addresses the approach to extract linear features from satellite imagery using an efficient segmentation method. The extraction of linear features from satellite images has been the main concern of many scientists. There is a need to develop a more capable and cost effective method for the Iranian map revision tasks. The conventional approaches for producing, maintaining, and updating GIS map are time consuming and costly process. Hence, this research is intended to investigate how to obtain linear features from SPOT satellite imagery. This was accomplished using a discontinuity-based segmentation technique that encompasses four stages: low level bottom-up, middle level bottom-up, edge thinning and accuracy assessment. The first step is geometric correction and noise removal using suitable operator. The second step includes choosing the appropriate edge detection method, finding its proper threshold and designing the built-up image. The next step is implementing edge thinning method using mathematical morphology technique. Lastly, the geometric accuracy assessment task for feature extraction as well as an assessment for the built-up result has been carried out. Overall, this approach has been applied successfully for linear feature extraction from SPOT image.

• Communications for Statistical Applications and Methods
• /
• v.10 no.2
• /
• pp.607-617
• /
• 2003

This paper offers a practical comparison of efficiency between local likelihood approach and conventional kernel approach in density estimation. The local likelihood estimation procedure maximizes a kernel smoothed log-likelihood function with respect to a polynomial approximation of the log likelihood function. We use two types of data driven bandwidths for each method and compare the mean integrated squares for several densities. Numerical results reveal that local log-linear approach with simple plug-in bandwidth shows better performance comparing to the standard kernel approach in heavy tailed distribution. For normal mixture density cases, standard kernel estimator with the bandwidth in Sheather and Jones(1991) dominates the others in moderately large sample size.