Prediction of the onset of mode III delamination in carbon-epoxy laminates

The aim of this paper is to determine a method for accurately predicting the onset of mode III delamination in multi-layered structures. A software called DEILAM and a model of plates called M4-5N are used to evaluate the stresses in the laminate. This model has already been validated [Mechanics of Materials 34 (2002) 217]; it yields finite values and a delamination onset criterion involving the maximum value of the interfacial stresses can be thus considered. One single parameter appears in the criterion and is identified by means of tensile tests. The criterion obtained is able to reproduce thickness effects. Two application examples with two materials are considered and in both examples the theoretical predictions are very accurate.     

A new ship's auto pilot design through a stochastic model

A new type of ship's autopilot system is designed by a statistical approach. A ship's motion at sea is described by a multi-variable autoregressive model using minimum AIC (Akaike's Information Criterion) procedure. Through the fitted model, the ship's behavior is analyzed and an optimal control law for a ship under a newly introduced criterion function is derived. The feasibility of our control system is checked by both digital and hybrid simulations. The results of the simulation show that with our controller the yaw motion is depressed through smoother and less rudder motion than that of the conventional autopilot systems and the ill effect of rolling is avoided. It is expected that the controller has another merit: it is quite robust for possible changes of external environments. Finally, a successful result of an actual sea test is briefly discussed. Thus, the possibility of realizing an entirely new autopilot system by a stochastic model is demonstrated.     

余度结构故障概率计算的一种方法

在一个余度结构中,有多种破坏模式,要精确计算结构的故障概率是复杂的。本文则根据限界准则和被删出的故障模式对结构故障概率最大贡献的公式,求得结构故障概率的上下限,简单地求得结构故障概率。为说明此方法的有效性,提出了数值例子。     

A stable friction compensation scheme for motion control systems

In mechanical positioning control systems, friction phenomenon makes undersirable responses. Friction compensation scheme is frequently implemented to the control system together with the friction estimator in order to cancel the effect of the friction. However, the error in the estimation of the friction results in undercompensation or overcompensation, which also makes undesirable responses. In this paper, a new friction compensation scheme is proposed. The stability analysis is performed based on the circle criterion, which provides a sufficient condition for asymptotic stability of a system. For an application example, the scheme is implemented to a mechanical positioning system of a second-order plant with nonlinear friction. The effectiveness of this scheme is illustrated with the time responses obtained by computer simulation.     

Construction and validation of a psychometric scale to measure consumers’ fears of novel food technologies: The food technology neophobia scale

Consumers’ fears of novel food technologies are documented. The ability to identify population segments that have greater or lesser neophobia, thus enabling identification of early adopters of innovative products, would be useful. The Food Neophobia Scale [FNS; Pliner, P., & Hobden, K. (1992). Development of a scale to measure the trait of food neophobia in humans. Appetite, 19, 105–120] is a useful tool for assessing reactions to ethnic foods (and sensation seeking) but less suitable for assessing receptivity to foods produced by novel technologies. Therefore, there is a need to develop a new psychometric tool that identifies food technology neophobia.In a three stage validation exercise, 81 statements (items) were reduced to 31 (n = 193) and subsequently reduced to 13 items (n = 459) by factor analysis. After a face validity check, the new 13 item Food Technology Neophobia Scale was tested (n = 295) and found to have predictive (criterion) validity (willingness to consume foods produced by novel food technologies). Furthermore, convergent validity was found between the FTNS and Trust in Science scale [TISS; Bak, H. (2001). Education and public attitudes toward science: Implications for the ‘deficit model’ of education and support for science and technology. Social Science Quarterly, 82(4), 779–793] and FNS.     

Deterministic and probabilistic ship pitch prediction using a multi-predictor integration model based on hybrid data preprocessing,reinforcement learning and improved QRNN

The deterministic and probabilistic prediction of ship motion is important for safe navigation and stable real-time operational control of ships at sea. However, the volatility and randomness of ship motion, the non-adaptive nature of single predictors and the poor coverage of quantile regression pose serious challenges to uncertainty prediction, making research in this field limited. In this paper, a multi-predictor integration model based on hybrid data preprocessing, reinforcement learning and improved quantile regression neural network (QRNN) is proposed to explore the deterministic and probabilistic prediction of ship pitch motion. To validate the performance of the proposed multi-predictor integrated prediction model, an experimental study is conducted with three sets of actual ship longitudinal motions during sea trials in the South China Sea. The experimental results indicate that the root mean square errors (RMSEs) of the proposed model of deterministic prediction are 0.0254°, 0.0359°, and 0.0188°, respectively. Taking series #2 as an example, the prediction interval coverage probabilities (PICPs) of the proposed model of probability predictions at 90%, 95%, and 99% confidence levels (CLs) are 0.9400, 0.9800, and 1.0000, respectively. This study signifies that the proposed model can provide trusted deterministic predictions and can effectively quantify the uncertainty of ship pitch motion, which has the potential to provide practical support for ship early warning systems.     

An evaluation method of probability of elastic-plastic fracture by 2-parameter criterion

Many researchers have made a lot of progress in studying the evaluation of fracture probability of brittle materials. However, studies of fracture probability for elastic-plasticity have not been made yet. An evaluation method for fracture probability which is grafted onto a 2-parameter criterion and statistical probability analysis is not only introduced in this study, but also applied to the simple 2-dimensional model and carbon steel piping to vealuate the effect of statistical variables.     

A study on the initial crack curving angle of isotropic/orthotropic bimaterial

In this paper, when the initial propagation angle of a branched crack is calculated from the maximum tangential stress criterion (MTSC) and the minimum strain energy density criterion (MSEDC), it is essential that you use stress components in which higher order terms are considered and stress components at the position in a distance 0.005 mm from the crack tip ( =γ . When an interfacial crack propagates along the interface at a constant velocity, the initial propagation angles of the branched crack are similar to the mode mixities (phase angle) and the theoretical values obtained from MTSC and MSEDC. The initial propagation angle of the branched crack depends considerably on the stress intensity factor K{IN2}.     

一种灵敏度准则矩阵构成的新方法

针对变形监测网的特点,对准则矩阵加以研究,提出了一种构造灵敏度准则的新方法。用该方法通过典型模型下的实例进行二次优化,论证了该方法的可行性和合理性。     

融合深度学习与最大间距准则的人脸识别方法

当前,人脸识别技术遇到的突出问题是光照、姿态、遮挡和表情等因素所引起的识别精度的下降,这些问题是人脸识别系统不完美的主要原因,深度学习是一种新的方法,可有效解决这些问题。首先通过引入深度学习算法进行多层次的学习,然后提取高层特征进行人脸描述,最后应用最大间距准则减小最小二乘估计产生的重建误差,实现有效的面部识别分类。该算法在ORL、CAS-PEAL和扩展Yale-B人脸数据库中进行了不同光照、姿态、遮挡、表情和容貌特征变化条件下的仿真实验。结果表明,所提出的算法比传统线性分类算法具有更高的效率和准确度。