Electrical elements as implementation of active reduction of vibrations

The major aim of this study is to show how to carry out the process of structural and parametrical synthesis that is understood as a design method of the system with active suppression of vibrations. Active components are implemented as electric components. The other objective is to analyze how the active subsystem interacts with the overall investigated structure. (© 2013 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

An alternate implementation of Goldfarb's minimization algorithm

Goldfarb's algorithm, which is one of the most successful methods for minimizing a function of several variables subject to linear constraints, uses a single matrix to keep second derivative information and to ensure that search directions satisfy any active constraints. In the original version of the algorithm this matrix is full, but by making a change of variables so that the active constraints become bounds on vector components, this matrix is transformed so that the dimension of its non-zero part is only the number of variablesless the number of active constraints. It is shown how this transformation may be used to give a version of the algorithm that usually provides a good saving in the amount of computation over the original version. Also it allows the use of sparse matrix techniques to take advantage of zeros in the matrix of linear constraints. Thus the method described can be regarded as an extension of linear programming to allow a non-linear objective function.     

Multiobjective duality for convex ratios

In this paper we present a duality approach for a multiobjective fractional programming problem. The components of the vector objective function are particular ratios involving the square of a convex function and a positive concave function. Applying the Fenchel-Rockafellar duality theory for a scalar optimization problem associated to the multiobjective primal, a dual problem is derived. This scalar dual problem is formulated in terms of conjugate functions and its structure gives an idea about how to construct a multiobjective dual problem in a natural way. Weak and strong duality assertions are presented.     

Epsilon Dominance and Constraint Partitioning in Multiple Objective Problems

In this paper we consider efficient sets of multiple objective problems, in which the feasible action set is the intersection of two other sets, and where one of these sets has a special structure, such as an assignment or transportation structure. The objective is to find the efficient set of the special structure set, and its intersection with the other set, and to examine how good an approximation this set is to the desired efficient set. The approximation set is called an -efficient solution set. Some theoretical partition results are given for a special constraint structure with upper bounds on the objective function levels. For the case of 0-efficient solution sets, and finite explicit sets, a computational cost analysis of two computational sequences is given. We also consider two other 0-efficient solution set cases. Then -efficiency is considered for linear problems. Finally, the approach is illustrated by a special multiple objective transportation problem.     

From the Logical Square to Blanché’s Hexagon: Formalization, Applicability and the Idea of the Normative Structure of Thought

The square of opposition and many other geometrical logical figures have increasingly proven to be applicable to different fields of knowledge. This paper seeks to show how Blanché generalizes the classical theory of oppositions of propositions and extends it to the structure of opposition of concepts. Furthermore, it considers how Blanché restructures the Apuleian square by transforming it into a hexagon. After presenting G. Kalinowski??s formalization of Blanché??s hexagonal theory, an illustration of its applicability to mathematics, to modal logic, and to the logic of norms is depicted. The paper concludes by criticizing Blanché??s claim according to which, his logical hexagon can be considered as the objective basis of the structure of the organisation of concepts, and as the formal structure of thought in general. It is maintained that within the frame of diagrammatic reasoning Blanché??s hexagon keeps its privileged place as a ??nice?? and useful tool, but not necessarily as a norm of thought.     

Shape optimization for the Helmholtz equation

The aim of our work is to develop optimal dielectric composite structures with specific qualities. The task is to design interfaces of given material components such that the originated structure attains certain optical properties. Propagation of the electromagnetic waves in the composite is described by the Helmholtz equation. Success of the structure is enumerated by the objective function which is to be minimized. Interfaces of the given materials are parametrized by the cubic B–spline curves. The design variables are afterwards the positions of B–spline control points. For objective function evaluation one forward computation of the Helmholtz equation is needed. To get the sensitivity of the objective function we solve the backward (adjoint) equation. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Mechanism by which tension on the fibrous filler affects the structure and the strength of wound glass-plastics

Conclusions 1. We have studied how the structure of glass-plastics wound with twisted threads is affected by tension on the fibrous filler. The trend of changes in fiber content and porosity, as well as an increasingly nonuniform distribution of the reinforcing filler over the thickness, has been established.2. The effect of a nonuniform filler distribution over the thickness on the tensile strength has been evaluated. The calculated and the experimental curve of strength as a function of the tension have been compared, the former taking into account variable porosity, fiber content, and nonuniformity of fiber distribution over the thickness.3. It has been demonstrated that the change in the strength characteristics of a wound glass-plastic as a function of the tension on the reinforcing filler during winding is due to a combined complex effect of such factors as the overall fiber content and porosity, a nonuniform fiber distribution over the thickness, the fiber orientation, and the degree of mechanical damage in threads due to their interaction with the active components of the winding machine.Report presented at the Third All-Union Conference on Polymer Mechanics. Riga, November 10–12, 1976.Translated from Mekhanika Polimerov, No. 3, pp. 439–444, May–June, 1977.     

Optimal allocation of redundancies in series systems

It is of great interest for the problem of how to allocate redundancies in a system so as to optimize the system performance in reliability engineering and system security. In this paper, we consider the problems of optimal allocation of both active and standby redundancies in series systems in the sense of various stochastic orderings. For the case of allocating one redundancy to a series system with two exponential components, we establish two likelihood ratio order results for active redundancy case and standby redundancy case, respectively. We also discuss the case of allocating K active redundancies to a series system and establish some new results. The results developed here strengthen and generalize some of the existing results in the literature. Specifically, we give an answer to an open problem mentioned in Hu and Wang [T. Hu, Y. Wang, Optimal allocation of active redundancies in r-out-of-n systems, Journal of Statistical Planning and Inference 139 (2009) 3733–3737]. Numerical examples are provided to illustrate the theoretic results established here.     

Parallel structural optimization applied to bone remodeling on distributed memory machines

In this paper, we investigate parallel structural optimization methods on distributed memory MIMD machines. We have restricted ourselves to the case of minimizing a multivariate non-linear function subject to bounds on the independent variables, when the objective function is expensive to evaluate as compared to the linear algebra portion of the optimization. This is the case in structural applications, when a large three-dimensional finite element mesh is used to model the structure.This paper demonstrates how parallelism can be exploited during the function and gradient computation as well as the optimization iterations. For the finite element analysis, a torus wrap skyline solver is used. The reflective Newton method, which attempts to reduce the number of iterations at the expense of more linear algebra per iteration, is compared with the more conventional active set method. All code is developed for an Intel iPSC/860, but can be ported to other distributed memory machines.The methods developed are applied to problems in bone remodeling. In the area of biomechanics, optimization models can be used to predict changes in the distribution of material properties in bone due to the presence of an artificial implant. The model we have used minimizes a linear combination of the mass and strain energy in the entire domain subject to bounds on the densities in each finite element.Early results show that the reflective Newton method can outperform active set methods when few variables are active at the minimum.     

Random Block Coordinate Descent Methods for Linearly Constrained Optimization over Networks

In this paper we develop random block coordinate descent methods for minimizing large-scale linearly constrained convex problems over networks. Since coupled constraints appear in the problem, we devise an algorithm that updates in parallel at each iteration at least two random components of the solution, chosen according to a given probability distribution. Those computations can be performed in a distributed fashion according to the structure of the network. Complexity per iteration of the proposed methods is usually cheaper than that of the full gradient method when the number of nodes in the network is much larger than the number of updated components. On smooth convex problems, we prove that these methods exhibit a sublinear worst-case convergence rate in the expected value of the objective function. Moreover, this convergence rate depends linearly on the number of components to be updated. On smooth strongly convex problems we prove that our methods converge linearly. We also focus on how to choose the probabilities to make our randomized algorithms converge as fast as possible, which leads us to solving a sparse semidefinite program. We then describe several applications that fit in our framework, in particular the convex feasibility problem. Finally, numerical experiments illustrate the behaviour of our methods, showing in particular that updating more than two components in parallel accelerates the method.     

Mode hunting through active information

We propose a new method to find modes based on active information. We develop an algorithm called active information mode hunting (AIMH) that, when applied to the whole space, will say whether there are any modes present and where they are. We show AIMH is consistent and, given that information increases where probability decreases, it helps to overcome issues with the curse of dimensionality. The AIMH also reduces the dimensionality with no resource to principal components. We illustrate the method in three ways: with a theoretical example (showing how it performs better than other mode hunting strategies), a real dataset business application, and a simulation.     

Optimization over the efficient set using an active constraint approach

In this work the problem of maximizing a nonlinear objective over the set of efficient solutions of a multicriteria linear program is considered. This is a nonlinear program with nonconvex constraints. The approach is to develop an active constraint algorithm which utilizes the fact that the efficient structure in decision space can be associated in a natural way with hyperplanes in the space of objective values. Examples and numerical experience are included.     

Supervised clustering of variables

In predictive modelling, highly correlated predictors lead to unstable models that are often difficult to interpret. The selection of features, or the use of latent components that reduce the complexity among correlated observed variables, are common strategies. Our objective with the new procedure that we advocate here is to achieve both purposes: to highlight the group structure among the variables and to identify the most relevant groups of variables for prediction. The proposed procedure is an iterative adaptation of a method developed for the clustering of variables around latent variables (CLV). Modification of the standard CLV algorithm leads to a supervised procedure, in the sense that the variable to be predicted plays an active role in the clustering. The latent variables associated with the groups of variables, selected for their “proximity” to the variable to be predicted and their “internal homogeneity”, are progressively added in a predictive model. The features of the methodology are illustrated based on a simulation study and a real-world application.     

Study on ride comfort of tractor with tandem suspension based on multi-body system dynamics

The aim of the paper is to report a systematic methodology which is used to evaluate and improve the ride comfort. An accurate model is necessary for further investigation and optimization. The vehicle dynamics model of tractor with tandem suspension is modeled and simulated in dynamics software ADAMS, which is redeveloped to add a function of automatic parametric modeling and simulation. The modeling methods of nonlinear characteristic components and various road excitation inputs, which can be simply seen as the implementation means for the model solution, are introduced. A new index called annoyance rate is presented to indicate the quantitative correlation between objective method and subjective comment. The quantitative correlation between them, which is quite different from the qualitative “comfortable” or “uncomfortable” results attained by objective evaluation, can be defined by function and regarded as a basis to scientifically evaluate and improve the ride comfort. According to the request of performance-based design, the parameter sensitive analysis and structure optimization have been carried out to find the trade-off among ride comfort, maneuverability and safety. The approach has proved to be very effective for predicting and improving the ride comfort by experiment results. The methodology can be also used for any other specific category of vehicle.     

Über den Einfluss eines mit der Höhe veränderlichen Windes auf die Flugbahn einer Rakete

Summary The present investigation deals with the influence on the trajectory of an artillery rocket of a wind variable in height. Under certain simplified conditions the effect is computed for the active and passive trajectory and it is shown how the two components can be combined into a single ballistic wind by means of suitable weight factors, into a wind, however, which must be defined differently for the longitudinal and the transverse directions.      

Imperfect debugging in software reliability: A Bayesian approach

The objective of studying software reliability is to assist software engineers in understanding more of the probabilistic nature of software failures during the debugging stages and to construct reliability models. In this paper, we consider modeling of a multiplicative failure rate whose components are evolving stochastically over testing stages and discuss its Bayesian estimation. In doing so, we focus on the modeling of parameters such as the fault detection rate per fault and the number of faults. We discuss how the proposed model can account for “imperfect debugging” under certain conditions. We use actual inter-failure data to carry out inference on model parameters via Markov chain Monte Carlo methods and present additional insights from Bayesian analysis.     

Maintainability of a Grade Structure as a Transportation Problem

A new approach to the maintainability of a grade structure in a deterministic environment, using promotion control, is sought. Our main objective is to show how this manpower planning issue can be viewed in the context of transportation problems. By the same token, a condition for the maintainability of a structure will be proved to be sufficient.     

基于车身装配结构优化的改进图分解算法

在考虑车身制造和装配成本的前提下对车身装配结构优化方法进行了研究,提出一种改进的图分解算法将车身装配结构最优地分解为一组部件.以白车身侧围的装配模型为例,将结构的几何图形转化为与之对应的关系拓扑图,再分割该关系拓扑图为一组工程约束下的单连通不交叉子图集,结合遗传算法中的算子操作,利用有限单元法分析并计算得到产品几何图形的最优分割,采用NSGA-Ⅱ算法并实现该装配体综合性能最优的目标.     

Modelling of Type I fracture network: Objective function formulation by fuzzy sensitivity analysis

This paper advances the fundamental understanding in mathematical and computational modelling of discrete fracture networks (Type I). It presents a systematic procedure to solve the most important problem in modelling by global optimization — objective function formulation, which negates guesswork in objective function formulation by automatic selection of highly ranked components and their corresponding weighting factors. The procedure starts from real data to identify potential components of the objective function. The components are then ranked by fuzzy sensitivity analysis, based on their effects on the final objective function value and simulation convergence. The final fracture network inversion is subsequently realized and validated. Results of the study provide an explanation why previous methods such as stochastic simulations are not sufficiently reliable, compared to global optimization methods.