Model validation for structural dynamic analysis: An approach to the Sandia Structural Dynamics Challenge

The validation of mathematical models constructed for the dynamic analysis of critical structures is a very important, but complex, process. The essential requirement is to provide confirmation, using independent and more reliable data than that presented by the model in question, that the subject model is capable of describing the essential physics of the structure’s behaviour within the required accuracy. In this paper, the procedures of model validation using experimental data on a structure are summarised and applied to a structural dynamics validation problem developed by Sandia National Laboratories. One of the essential issues is to separate out any non-linear features of the system and to construct an appropriate linear model that is as accurate as possible to cope with variability of the subsystem structures. The linear model, which is constructed using simulated test data from an assembly of sample subsystems, is expressed as a mean model with a standard deviation. It is further used in the system response prediction for system accreditation and target application under specified excitation loads. The influence of the weak non-linearity features are neglected in the system response prediction because the experimental method used to derive the test data obscured the non-linear effects and precluded their identification. Further consideration of identification and modelling of the non-linear element for the Sandia 3DOF calibration system is discussed to evaluate its influence on the accuracy of the spatial model.     

基于网络的计算机等级考试系统的UML建模

文中通过统一建模语言(UML)描述网络考试系统的建模过程,并对其进行需求分析、总体设计和详细设计。以题库制作模块为例建立了系统用户模型、静态模型和动态模型的各种视图和规范化文档,描述了系统的功能需求、功能流程、类的结构与关系、对象之间的交互。最终采用面向对象语言实现计算机等级考试系统。使用这种方法对系统进行建模,优化了开发过程,并有利于提高系统的稳定性、可维护性和可重用性。     

A technique to circumvent SSL/TLS validations on iOS devices

SSL/TLS validations such as certificate and public key pinning can reinforce the security of encrypted communications between Internet-of-Things devices and remote servers, and ensure the privacy of users. However, such implementations complicate forensic analysis and detection of information disclosure; say, when a mobile app breaches user’s privacy by sending sensitive information to third parties. Therefore, it is crucial to develop the capacity to vet mobile apps augmenting the security of SSL/TLS traffic. In this paper, we propose a technique to bypass the system’s default certificate validation as well as built-in SSL/TLS validations performed in iOS apps. We then demonstrate its utility by analysing 40 popular iOS social networking, electronic payment, banking, and cloud computing apps.     

Probabilistic model identification of uncertainties in computational models for dynamical systems and experimental validation

We present a methodology to perform the identification and validation of complex uncertain dynamical systems using experimental data, for which uncertainties are taken into account by using the nonparametric probabilistic approach. Such a probabilistic model of uncertainties allows both model uncertainties and parameter uncertainties to be addressed by using only a small number of unknown identification parameters. Consequently, the optimization problem which has to be solved in order to identify the unknown identification parameters from experiments is feasible. Two formulations are proposed. The first one is the mean-square method for which a usual differentiable objective function and an unusual non-differentiable objective function are proposed. The second one is the maximum likelihood method coupling with a statistical reduction which leads us to a considerable improvement of the method. Three applications with experimental validations are presented in the area of structural vibrations and vibroacoustics.     

面向自动测试的集成电路制造装备测试模型

对于典型的集成电路制造装备,提出了一种面向自动测试系统的多层次测试模型;使用层次化建模方法进行建模,将典型集成电路制造装备的测试模型按层次划分为装备级、子系统级和仪器级;利用XML建立了模块化的测试模型的描述,并使用引用的方式实现测试模型的重用;提出了使用时间信息和GUID确定被引用测试模型可用性的算法;该模型被用于具有工艺腔室的典型集成电路制造装备中,提高了测试模型的重用性,并拓展了对不同层次被测对象的测试能力。     

Distributed control for energy-efficient and fast consensus in wireless sensor networks

The paper proposes a distributed control of nodes transmission radii in energy-harvesting wireless sensor networks for simultaneously coping with energy consumption and consensus responsiveness requirement. The stability of the closed-loop network under the proposed control law is proved. Simulation validations show the effectiveness of the proposed approach in nominal scenario as well as in the presence of uncertain node power requirements and harvesting system supply.     

飞行管理系统AADL建模与分析

航空电子系统软件的建模与分析是保证军用和民用飞机高可靠、高性能的重要手段,也是模型驱动软件体系结构的重要组成部分。飞行管理系统作为航空电子系统的重要组成部分,传统上,对该系统的可调度性分析是在系统设计完成后,在实现与验证阶段进行的,这使得系统无法进行的准确地软硬件需求分析。采用先进的建模方法AADL对其进行建模,为飞行管理系统的可调度性分析、可靠性分析以及通信延迟等分析提供了可能,使得在系统需求分析阶段就可以准确确定系统的软硬件需求,并能大大降低系统的更改验证成本。首先论述了建模语言AADL的基本构成以及与航空电子应用接口规范ARING653的对应关系;然后描述了飞行管理系统的功能构成,并建立了飞行管理系统的AADL模型;最后详细论述了系统调度理论,AADL工具,飞管系统AADL模型的仿真分析。通过仿真分析为飞管系统的处理器选型、系统设计、软件设计与优化提供了依据。     

NASA Langley’s approach to the Sandia’s structural dynamics challenge problem

The objective of this challenge is to develop a data-based probabilistic model of uncertainty to predict the acceleration response of subsystems (payloads) by themselves and while coupled to a primary (target) system. Although deterministic analyses of this type are routinely performed and representative of issues faced in real-world system design and integration, there are still several key technical challenges that must be addressed when analyzing the uncertainties of interconnected systems. For example, one key technical challenge is related to the fact that there is limited data on the target configurations. Also, while multiple data sets from experiments conducted at the subsystem level are provided, samples sizes are not sufficient to compute high confidence statistics. Moreover, in this challenge problem, additional constraints, in the form of ground rules, have been added. One such constraint is that mathematical models of the subsystem are limited to linear approximations of the nonlinear physics of the problem at hand. Also, participants are constrained to use these subsystem models and the multiple data sets to make predictions about the target system response under completely different forcing functions.Initially, our approach involved the screening of several different methods to arrive at the three presented herein. The first one is based on a transformation of the structural dynamic data in the modal domain to an orthogonal space where the mean and covariance of the data are matched. The other two approaches worked solutions in physical space where the uncertain parameter set is made of masses, stiffnessess, and damping coefficients; one matches the confidence intervals of low order moments of the statistics via optimization while the second one uses a Kernel density estimation approach. The paper will touch on the approaches, lessons learned, validation metrics and their comparison, data quantity restriction, and assumptions/limitations of each approach.     

A new approach to vision-based unsupervised learning of unexplored indoor environment for autonomous land vehicle navigation

A vision-based approach to unsupervised learning of the indoor environment for autonomous land vehicle (ALV) navigation is proposed. The ALV may, without human's involvement, self-navigate systematically in an unexplored closed environment, collect the information of the environment features, and then build a top-view map of the environment for later planned navigation or other applications. The learning system consists of three subsystems: a feature location subsystem, a model management subsystem, and an environment exploration subsystem. The feature location subsystem processes input images, and calculates the locations of the local features and the ALV by model matching techniques. To facilitate feature collection, two laser markers are mounted on the vehicle which project laser light on the corridor walls to form easily detectable line and corner features. The model management subsystem attaches the local model into a global one by merging matched corner pairs as well as line segment pairs. The environment exploration subsystem guides the ALV to explore the entire navigation environment by using the information of the learned model and the current ALV location. The guidance scheme is based on the use of a pushdown transducer derived from automata theory. A prototype learning system was implemented on a real vehicle, and simulations and experimental results in real environments show the feasibility of the proposed approach.