Sensitivity analysis of differential-algebraic equations and partial differential equations

Sensitivity analysis generates essential information for model development, design optimization, parameter estimation, optimal control, model reduction and experimental design. In this paper we describe the forward and adjoint methods for sensitivity analysis, and outline some of our recent work on theory, algorithms and software for sensitivity analysis of differential-algebraic equation (DAE) and time-dependent partial differential equation (PDE) systems.     

基于Simulink超短波电台的故障仿真研究

本文以某型航空超短波电台通信距离近故障为切入点,依据电台工作的直扩模式通信机理,采用Simulink搭建了直扩通信系统的仿真模型,并设置了接近电台工作参数的仿真条件.研究了在脉冲调制干扰情况下对电台接收机灵敏度指标的直接影响和对通信距离间接影响的程度,通过仿真运算和结果分析,可复现电台的故障产生过程,为查找故障部位分析原因并进行科学处理提供了依据.     

Blast-induced ground vibration prediction in granite quarries: An application of gene expression programming,ANFIS, and sine cosine algorithm optimized ANN

Blasting of rocks has intrinsic environmental impacts such as ground vibration, which can interfere with the safety of lives and property. Hence, accurate prediction of the environmental impacts of blasting is imperative as the empirical models are not accurate as evident in the literature. Therefore, there is need to consider some robust predictive models for accurate prediction results. Gene expression programming(GEP), adaptive neuro-fuzzy inference system(ANFIS), and sine cosine algorithm optimized artificial neural network(SCA-ANN) models are proposed for predicting the blast-initiated ground vibration in five granite quarries. The input parameters into the models are the distance from the point of blasting to the point of measurement(D), the weight of charge per delay(W), rock density(q), and the Schmidt rebound hardness(SRH) value while peak particle velocity(PPV) is the targeted output. 100 datasets were used in developing the proposed models. The performance of the proposed models was examined using the coefficient of determination(R2) and error analysis. The R2 values obtained for the GEP, ANFIS,and SCA-ANN models are 0.989, 0.997, and 0.999, respectively, while their errors are close to zero. The proposed models are compared with an empirical model and are found to outperform the empirical model.     

三峡左岸电站发电机-变压器组继电保护的配置

三峡左岸电站发电机变压器组的继电保护技术设计方案,自１９９４年３月以来,由三峡开发总公司多次组织国内著名专家教授对其进行审查,并委托长江水利委员会会同清华大学、华中理工大学对其主保护进行灵敏度模拟计算,于１９９７年８月形成了向国外招标的最终方案,得到了国外投标商的积极响应和配合,并在第一次设计联络会上得到了外商的确认。简要介绍了三峡左岸电站发电机变压器组主保护的选取和其他后备保护的配置方案。     

GIS空间操作灵敏度分析

本文论述了用数学模型表示地理适应性分析原理的方法以及计算过程和地理适应性分析的数学变换方法;研究了地理信息系统（GIS）空间操作的灵敏度分析;并且在此基础上,进行了算例分析。     

Study of differential search algorithm based automatic generation control of an interconnected thermal-thermal system with governor dead-band

An attempt has been made to the effective application of a recently introduced, powerful optimization technique called differential search algorithm (DSA), for the first time to solve load frequency control (LFC) problem in power system. In this paper, initially, DSA optimized classical PI/PIDF controller is implemented to an identical two-area thermal-thermal power system and then the study is extended to two more realistic power systems which are widely used in the literature. To assess the usefulness of DSA, three enhanced competitive algorithms namely comprehensive learning particle swarm optimization (CLPSO), ensemble of mutation and crossover strategies and parameters in differential evolution (EPSDE), and success history based DE (SHADE) are studied in this paper. Moreover, the superiority of proposed DSA optimized PI/PID/PIDF controller is validated by an extensive comparative analysis with some recently published meta-heuristic algorithms such as firefly algorithm (FA), bacteria foraging optimization algorithm (BFOA), genetic algorithm (GA), craziness based particle swarm optimization (CRPSO), differential evolution (DE), teaching-learning based optimization (TLBO), particle swarm optimization (PSO), and quasi-oppositional harmony search algorithm (QOHSA). A case of robustness and sensitivity analysis has been performed for the concerned test system under parametric uncertainty and random load perturbation. Furthermore, to demonstrate the efficacy of proposed DSA, the system nonlinearities like reheater of the steam turbine and governor dead band are included in the system modeling. The extensive results presented in this article demonstrate that proposed DSA can effectively improve system dynamics and may be applied to real-time LFC problem.     

Mono-window Algorithm Applicability in Fujian Sea and Its Surrounding Areas Sea Surface Temperature Retrieval

On the basis of four quarters HJ\|1b thermal infrared remote sensing images during 2013~2014,each of the spring,summer,autumn and winter,mono\|window algorithm was adopted to retrieve Sea Surface Temperature(SST).To verify the feasibility and accuracy of this algorithm,the derived results were compared with the measured SST data,show that the average absolute error is 0.86 ℃ and the correlation coefficient R² is 0.971 5.The different levels influence on derived results caused by the uncertainty of water vapor and atmospheric temperature is analyzed,indicate that if the water vapor error ranges between -2~0 g/cm²and the temperature variation is between -2 ℃~2 ℃,the sea surface temperature error will be within 5%,the high retrieving accuracy can still be achieved;The sensitivity of the water vapor in winter shows higher than in summer,while the sensitivity of atmospheric temperature demonstrates lower than in summer.Therefore,mono\|window algorithm is good applicable in the SST retrieval in Fujian sea and its surrounding areas,which is of great significance to Fujian environmental monitoring.     

Human-oriented design of collaborative robots

Collaborative robotics is a possible solution to the problem of musculoskeletal disorders (MSDs) in industry, but efficiently designing such robots remains an issue because ergonomic assessment tools are ill-adapted to such devices. This paper presents a generic method for performing detailed ergonomic assessments of co-manipulation activities and its application to the optimal design of collaborative robots. Multiple ergonomic indicators are defined to estimate the different biomechanical demands which occur during manual activities. For any given activity, these indicators are measured through dynamic virtual human simulations, for varying human and robot features. Sensitivity indices are thereby computed to quantify the influence of each parameter of the robot and identify those which should mainly be modified to enhance the ergonomic performance. The sensitivity analysis also allows to extract the indicators which best summarize the overall ergonomic performance of the activity. An evolutionary algorithm is then used to optimize the influential parameters of the robot with respect to the most informative ergonomic indicators, in order to generate an efficient robot design. The whole method is applied to the optimization of a robot morphology for assisting a drilling activity. The performances of the resulting robots confirm the relevance of the proposed approach.     

A multi-objective reliability-based decision support system for incorporating decision maker utilities in the design of infrastructure

Infrastructure comprises the most fundamental facilities and systems serving society. Because infrastructure exists in economic, social, and environmental contexts, all lifecycle phases of such facilities should maximize utility for society, occupants, and designers. However, due to uncertainties associated with the nature of the built environment, the economic, social, and environmental (i.e., triple bottom line) impacts of infrastructure assets must be described as probabilistic. For this reason, optimization models should aim to maximize decision maker utilities with respect to multiple and potentially conflicting probabilistic decision criteria. Although stochastic optimization and multi-objective optimization are well developed in the field of operations research, their intersection (multi-objective optimization under uncertainty) is much less developed and computationally expensive. This article presents a computationally efficient, adaptable, multi-objective decision support system for finding optimal infrastructure design configurations with respect to multiple probabilistic decision criteria and decision maker requirements (utilities). The proposed model utilizes the First Order Reliability Method (FORM) in a systems reliability approach to assess the reliability of alternative infrastructure design configurations with regard to the probabilistic decision criteria and decision maker defined utilities, and prioritizes the decision criteria that require improvement. A pilot implementation is undertaken on a nine-story office building in Los Angeles, California to illustrate the capabilities of the framework. The results of the pilot implementation revealed that “high-performing” design configurations (with higher initial costs and lower failure costs) had a higher probability of meeting the decision maker’s preferences than more traditional, low initial cost configurations. The proposed framework can identify low-impact designs that also maximize decision maker utilities.     

配热电阻测温二次仪表不确定度评定

根据国家质量技术监督局发布实施JJF1059-《测量不确定度评定与表示》计量技术规范,我单位对配热电阻测温二次仪表的不确定度进行了新的评定,评定方法依据新标准进行,并已顺利通过省局复审。