An adaptive region segmentation combining surrogate model applied to correlate design variables and performance parameters in a transonic axial compressor

Surrogate models have been widely applied to correlate design variables and performance parameters in turbomachinery optimization applications. With more design variables and uncertain factors taken into account in an optimization design problem, the mathematical relations between the design variables and the performance parameters might present linear, low-order nonlinear or even high-order nonlinear characteristics, and are usually analytically unknown. Therefore, it is required that surrogate models have high adaptability and prediction accuracy for both the linear and nonlinear characteristics. The paper mainly investigates the effectiveness of an adaptive region segmentation combining surrogate model based on support vector regression and kriging model applied to a transonic axial compressor to approximate the complicated relationships between geometrical variables and objective performance outputs with different sampling methods and sizes. The purpose is to explore the prediction accuracy and computational efficiency of this adaptive surrogate model in real turbomachinery applications. Three different sampling techniques are studied: (1) uniform design; (2) Latin hypercube sampling method; (3) Sobol quasi-random design. For the low dimensional case with five variables, the adaptive region segmentation combining surrogate model performs better (not worse) than the single component surrogate in terms of prediction accuracy and computational efficiency. In the meanwhile, it is also noted that the uniform design applied to the adaptive surrogate model has more advantages over the Latin hypercube sampling method especially for the small sample size cases, both performing better than the Sobol quasi-random design. Moreover, a high dimensional case with 12 variables is also utilized to further validate the prediction advantage of the adaptive region segmentation combining surrogate model over the single component surrogate, and the computational results favor it. Overall, the adaptive region segmentation combining surrogate model has produced acceptable to high prediction accuracy in presenting complex relationships between the geometrical variables and the objective performance outputs and performed robustly for a transonic axial compressor problem.

     

Different Estimation Methods for Constant Stress Accelerated Life Test under the Family of the Exponentiated Distributions

The Accelerated Life Testing (ALT) has been used for a long time in several fields to obtain information on the reliability of product components and materials under operating conditions in a much shorter time. One of the main purposes of applying ALT is to estimate the failure time functions and reliability performance under normal conditions. This paper concentrates on the estimation procedures under ALT and how to select the best estimation method that gives accurate estimates for the reliability function. For this purpose, different estimation methods are used, such as maximum likelihood, least squares (LS), weighted LS, and probability weighted moment. Moreover, the reliability function under usual conditions is predicted. The estimation procedures are applied under the family of the exponentiated distributions in general, and for the exponentiated inverted Weibull (EIW) as a special case. Numerical analysis including simulated data and a real life data set is conducted to compare the performances between these four methods. It is found that the ML method gives the best results among other estimation methods. Finally, a comparison between the EIW and the Inverted Weibull (IW) distributions based on a real life data set is made using a likelihood ratio test. It is observed that the EIW distribution can provide better fitting than the IW in case of ALT. Copyright © 2015 John Wiley & Sons, Ltd.     

Online scheduling with rejection and withdrawal

We study an online scheduling problem with rejection, in which some rearrangement of the solution is allowed. This problem is called scheduling with rejection and withdrawal. Each arriving job has a processing time and a rejection cost associated with it, and it needs to be either assigned to a machine or rejected upon arrival. At termination, it is possible to choose at most a fixed number of scheduled jobs and withdraw them (i.e., decide to reject them). We study the minimization version, where the goal is to minimize the sum of the makespan and the total rejection cost (which corresponds to the penalty), and the maximization problem, where the goal is to maximize the sum of the minimum load and the total rejection cost (which corresponds to profit). We study environments of machines, which are the case of m identical machines and the case of two uniformly related machines, and show a strong relation between these problems and the related classic online scheduling problems which they generalize, in contrast to standard scheduling with rejection, which typically makes the scheduling problems harder.     

Configuration Maintenance for Distributed Applications Management

The MANDAS project has defined a layered architecture for the management of distributed applications. In this paper we examine a vertical slice of this architecture, namely the management applications and services related to configuration management. We introduce an information model which captures the configuration information for distributed applications and discuss a repository service based on the model. We define a set of services and management applications to support maintenance of configuration information, and describe how the different types of configuration information are collected. Finally, we present two management applications that use configuration information.     

基于交叉耦合效应的车用内置式永磁电机转子位置估计

该文提出一种基于滑模观测器和基于凸极效应信号注入相结合的、考虑电机中电感交叉耦合效应的内置式永磁同步电机无速度传感器控制方法。系统在硬件在环平台中实验。直轴和交轴电感间的交叉耦合效应由有限元法算得。所提出的方法能使内置式永磁同步电机获得更好的运行性能。硬件在环平台验证了Matlab/Simulink的结果。样机实验得到的结果与Matlab仿真以及硬件在环实验的结果相吻合。实验结果表明,所提出的算法是有效的,硬件在环平台在一定程度上能模拟样机实验。     

Microstructure and elastic tensile behavior of polyethylene terephthalate-exfoliated graphene nanocomposites

Polyethylene terephthalate-exfoliated graphene nanocomposites were prepared by injection molding. Nanocomposites with graphene platelets of 2, 5, 10, and 15% weight fractions were molded and tested for mechanical characterization. Transmission electron microscopy imaging along with X-ray diffraction show that the graphene platelets remained intact and were dispersed into the matrix. An exponential increase in the Young’s modulus of the nanocomposites was observed, but with current limits on exfoliation they do not yet reach the potential suggested by idealized predictions.     

Synthesis and Biopharmaceutical Evaluation of Imatinib Analogues Featuring Unusual Structural Motifs

A convenient synthesis of imatinib, a potent inhibitor of ABL1 kinase and widely prescribed drug for the treatment of a variety of leukemias, was devised and applied to the construction of a series of novel imatinib analogues featuring a number of non‐aromatic structural motifs in place of the parent molecule's phenyl moiety. These analogues were subsequently evaluated for their biopharmaceutical properties (e.g., ABL1 kinase inhibitory activity, cytotoxicity). The bicyclo[1.1.1]pentane‐ and cubane‐containing analogues were found to possess higher themodynamic solubility, whereas cubane‐ and cyclohexyl‐containing analogues exhibited the highest inhibitory activity against ABL1 kinase and the most potent cytotoxicity values against cancer cell lines K562 and SUP‐B15. Molecular modeling was employed to rationalize the weak activity of the compounds against ABL1 kinase, and it is likely that the observed cytotoxicity of these agents arises through off‐target effects.     

Learning curve analysis of concentrated photovoltaic systems

Price declines and volume growth of concentrated photovoltaic (CPV) systems are analysed using the learning curve methodology and compared with other forms of solar electricity generation. Logarithmic regression analysis determines a learning rate of 18% for CPV systems with 90% confidence of that rate being between 14 and 22%, which is higher than the learning rates of other solar generation systems (11% for CSP and 12 to 14% for PV). Current CPV system prices are competitive with PV and CSP, which, when combined with the higher learning rate, indicates that CPV is likely to further improve its marketability. A target price of 1 $/W in 2020 could be achieved with a compound growth rate of 67% for the total deployed volume between 2014 and 2020, which would realize a cumulative deployed volume of 7900 MW. Other projections of deployment volumes from commercial sources are converted using the learning rate into future price scenarios, resulting in predicted prices in the range of 1.1 to 1.3 $/W in 2020. © 2014 The Authors. Progress in Photovoltaics: Research and Applications published by John Wiley & Sons Ltd.     

Movement abnormalities and the progression of prodromal symptomatology in adolescents at risk for psychotic disorders.

The link between movement abnormalities and psychotic disorders is presumed to reflect common neural mechanisms that influence both motor functions and vulnerability to psychosis. The prodromal period leading to psychotic disorders represents both a viable point for intervention and a developmental period that, if studied, could shed light on etiology; however, no published studies have examined the temporal progression of this link. A group with high levels of prodromal symptomatology (i.e., adolescents with schizotypal personality disorder [SPD]; n = 42) and both psychiatric controls (with other personality disorders or conduct disorder [OD]; n = 30) and nonpsychiatric controls ([NC]; n = 49) were recruited. Videotapes of structured psychiatric interviews were coded for movement abnormalities by raters blind to participants' diagnostic status, and follow-up assessments were conducted 1 year later. Controlling for psychotropic medications, the authors found that adolescents with SPD exhibited significantly more motor abnormalities in the face and upper body than did OD and NC controls. At baseline, movement abnormalities were positively correlated with the severity of positive, negative, and total prodromal symptoms. Within the SPD group, baseline movement abnormalities predicted symptom severity 1 year later. Movement abnormalities represent an early risk indicator that may be predictive of later symptom severity and potentially of psychosis onset. (PsycINFO Database Record (c) 2010 APA, all rights reserved)