Granular materials: Parameter identification and modelling of localisation problems

The prediction of landsliding requires an exact knowledge of the mechanical behaviour of granular materials. This kind of materials, e. g., sand, have a very complex deformation behaviour, which depend on the stress state and on the loading history. In this work, the deformation behaviour of the solid skeleton is characterised via homogeneous triaxial tests on dry sand specimens. Additionally, an appropriate elasto-plastic material law to describe the solid skeleton in the frame of Theory of Porous Media (TPM) is used, which is implemented in the FE tool PANDAS. Furthermore, a single-surface yield criterion with isotropic hardening, which limits the elastic domain, and a non-associated plastic flow are employed. The determination of the material parameters of the linear elasticity law as well as the single-surface yield criterion are based on test data of triaxial experiments. The material parameters are identified using a derivative-based optimisation method (donlp2), which is coupled with PANDAS. Finally, a simulation of a benchmark test is presented to show shear band localisation effects, where the material behaviour is described by a triphasic porous media model based on the TPM, where the constituents are a deformable solid skeleton and two pore fluids, water and air. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Parameter identification for rubber materials with artificial higher dimensional data

In general, laboratory test render only a limited number of experimental data. Consequently, the prediction of material behaviour becomes a difficult task and, moreover, a statistical analysis with a statistically based approach is almost impossible. As a remedy to increase the number of data, artificial data are generated by stochastic simulation. As a consequence an arbitrary number of data is available and the process of parameter identification can be analysed statistically. Here, the special challenge is the consideration of spatial and inhomogeneous problems. In this work artificial data are generated for a elastomer strip with hole under tension. The inhomogeneous stress/strain fields are optically measured with an Aramis/GOM system and have to be fitted to a stochastic model in order to generate artificial data. B-Splines are applied to fit the geometry of the test specimen and the measured data in space as well as in time. Parameter identifications applied and the resulting material parameters are statistically analysed. In the example, a statistical analysis of an Ogden model is performed. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

An extended covering model for flexible discrete and equity location problems

To model flexible objectives for discrete location problems, ordered median functions can be applied. These functions multiply a weight to the cost of fulfilling the demand of a customer which depends on the position of that cost relative to the costs of fulfilling the demand of the other customers. In this paper a reformulated and more compact version of a covering model for the discrete ordered median problem (DOMP) is considered. It is shown that by using this reformulation better solution times can be obtained. This is especially true for some objectives that are often employed in location theory. In addition, the covering model is extended so that ordered median functions with negative weights are feasible as well. This type of modeling weights has not been treated in the literature on the DOMP before. We show that several discrete location problems with equity objectives are particular cases of this model. As a result, a mixed-integer linear model for this type of problems is obtained for the first time.     

An extended multi-anticipative delay model of traffic flow

An extended multi-anticipative delay model is proposed by introducing multiple velocity differences and incorporating the reaction-time delay of drivers. The stability condition of the new model is obtained by applying the linear stability theory, and the modified Korteweg–de Vries (mKdV) equation is derived by the use of the nonlinear analysis method. The analytical and numerical results show that both the reaction-time delay of drivers and the information of multiple velocity differences have an important influence on the stability of the model, and that the stabilization of traffic flow is enhanced by appending the velocity difference information of multiple vehicles ahead or by decreasing the delay time.     

An extended CEV model and the Legendre transform-dual-asymptotic solutions for annuity contracts

This paper develops an extended constant elasticity of variance (E-CEV) model to overcome the shortcomings of the general CEV model. Under the E-CEV model, we study the optimal investment strategy before and after retirement in a defined contribution pension plan where benefits are paid by annuity. By applying the Legendre transform, dual theory and an asymptotic expansion approach, we respectively derive two asymptotic strategies for a CRRA and CARA utility functions in two different periods. Furthermore, we find that each asymptotic strategy can be decomposed into an optimal zero-order strategy and a perturbation strategy. The optimal zero-order strategy denotes an investment strategy where the current volatility is just equal to the mean level of the volatility, whereas the perturbation strategy provides an approximation solution to hedge the slow varying nature of the current volatility deviating from mean level. Finally, we find that the optimal zero-order strategy under given conditions will reduce to the results of Devolder et al. (2003), Xiao et al. (2007) and Gao (2009), respectively.     

An extended cost estimation model for a multi-material topology optimization approach

The manufacturing costs of hybrid parts comprise several different proportions depending on the manufacturing process and the materials used. A simplified cost model based on the material weights is therefore no longer sufficient. In this paper, an approach for the weight and costs optimization of hybrid parts is presented. An extended costs calculation function regarding additional manufacturing costs and the integration of a new cost objective in the optimization process is investigated. The effects of the consideration of costs on the optimization results will be qualitatively shown on a simple example structure. (© 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

An extended slacks-based measure model for data envelopment analysis with negative data

Data envelopment analysis (DEA) is a non-parametric approach based on linear programming that has been widely applied for evaluating the relative efficiency of a set of homogeneous decision-making units (DMUs) with multiple inputs and outputs. The original DEA models use positive input and output variables that are measured on a ratio scale, but these models do not apply to the variables in which negative data can appear. However, with the widespread use of interval scale data and undesirable data, the emphasis has been directed towards the simultaneous consideration of the positive and negative data in DEA models. In this paper, using the slacks-based measure, we propose an extended model to evaluate the efficiency of DMUs, even if some variables are measured on an interval scale and some on a ratio scale. Moreover, the extended model allows for the presence of all interval-scale variables, which are capable of taking both negative and positive values.     

An extended stochastic failure model for a system subject to random shocks

In this article, a stochastic failure model for a system subject to a random shock process is studied. It is assumed that a fatal shock results in an immediate system failure, whereas a non-fatal shock may increase the susceptibility of the system to failure. The lifetime distribution of the system and its failure rate function are derived, and the effect of environmental factors on the failure process of the system is also investigated. Lifetimes of systems operated under different environmental conditions are stochastically compared.     

An extended grey forecasting model for omnidirectional forecasting considering data gap difference

To achieve effective and efficient decision making in a highly competitive business environment, an enterprise must have an appropriate forecasting technique that can meet the requirements of both timeliness and accuracy. Accordingly, in the early stages, building a forecasting model with incomplete information and limited samples is very important to a business. Grey system theory is one of the prediction methods that can be built with a small sample and yet has a strong ability to make short-term predictions. The purpose of this study is to come up with an improved forecasting model based on the concept of this theory to enlarge the applicability of the grey forecasting model in various situations. By extending the data transforming approach, this method generalizes a building procedure for the grey model to grasp the data outline and information trend. Specifically, a novel inverse accumulating generation operator is developed to enable omnidirectional forecasting. The research utilizes observations of the titanium alloy fatigue limit along with temperature changes as raw data to verify the performance of the proposed method. The experimental results show that not only can this method expand the application scope of the grey forecasting model, but also improve its forecasting accuracy.     

An extended optimal replacement model of systems subject to shocks

A system is subject to shocks that arrive according to a non-homogeneous Poisson process. As shocks occur a system has two types of failures: type I failure (minor failure) is rectified by a minimal repair, whereas type II failure (catastrophic failure) is removed by replacement. The probability of a type II failure is permitted to depend on the number of shocks since the last replacement. This paper proposes a generalized replacement policy where a system is replaced at the nth type I failure or first type II failure or at age T, whichever occurs first. The cost of the minimal repair of the system at age t depends on the random part C(t) and deterministic paper c(t). The expected cost rate is obtained. The optimal n¹ and optimal T¹ which would minimize the cost rate are derived and discussed. Various special cases are considered and detailed.     

An extended beam theory for smart materials applications part I: Extended beam models,duality theory,and finite element simulations

An extended theory for elastic and plastic beam problems is studied. By introducing new dependent and independent variables, the standard Timoshenko beam model is extended to take account of shear variation in the lateral direction. The dynamic governing equations are established via Hamilton's principle, and existence and uniqueness results for the solution of the static problem are proved. Using the theory of convex analysis, the duality theory for the extended beam model is developed. Moreover, the extended theory for rigid-perfectly plastic beams is also established. Based on the extended model, a finite-element method is proposed and numerical results are obtained indicating the usefulness of the extended theory in applications.The work of the first author was supported in part by National Science Foundation under Grant DMS9400565.     

Parameter identification for a class of nonlinear chaotic and hyperchaotic flows

Based on the stability theory, an accurate and fast parameter identification law of chaotic and hyperchaotic flows is created by selecting right initial values and suitable observers. The suitable observers are designed and used to identify any uncertain parameters of chaotic and hyperchaotic flows. Furthermore, the accuracy of parameter identification is very much improved by making use of wavelet de-noising. Theory analysis and numerical simulations of Lorenz and hyperchaotic Chen systems are implemented to verify the effectiveness and feasibility of the observers to identify the parameters.     

An extended queueing control model for facilities with front room and back room operations and mixed-skilled workers

Three related problems arising in retail facilities with front room and back room operations, and cross-trained workers, are considered. In the first problem, the goal is to determine an optimal policy for switching workers between the two rooms. In the second and third problems, the goal is to determine the minimum number of workers that should be hired by the facility such that a satisfactory switching policy exists. We analyze two questions arising from previous work on these problems. Firstly, we demonstrate that the previously proposed policy definition is sub-optimal and cannot represent a set of solutions that are reasonable in practice, and propose an alternative definition. Secondly, we examine the problem of finding the optimal combination of cross-trained and specialized workers under a complete set of assumptions regarding worker costs. This analysis shows that the structure of the optimal solution depends on the policy definition that is employed. Moreover, under some assumptions the cost of the ‘optimal’ solution with the original policy definition will be greater than the cost of the optimal solution with the new one.     

An extended mover—stayer model for diagnosing the dynamics of trial and repeat for a new brand

This paper proposes an approach that extends the mover—stayer model to examine the impact of a new brand on brand choice patterns in a mature, frequently purchased product category. The objective is to obtain insights into the dynamics of brand choice following trial and repeat purchase of the new brand. The analysis uses consumer panel data on brand choices over a limited number of consecutive purchase occasions spanning the new brand introduction. The estimated parameters of the model provide diagnostic information for possible managerial action. An illustrative empirical application of the model demonstrates some of the insights into consumer buying patterns following a new brand introduction and potential managerial implications.     

Parameter identification and synchronization of fractional-order chaotic systems

The knowledge about parameters and order is very important for synchronization of fractional-order chaotic systems. In this article, identification of parameters and order of fractional-order chaotic systems is converted to an optimization problem. Particle swarm optimization algorithm is used to solve this optimization problem. Based on the above parameter identification, synchronization of the fractional-order Lorenz, Chen and a novel system (commensurate or incommensurate order) is derived using active control method. The new fractional-order chaotic system has four-scroll chaotic attractors. The existence and uniqueness of solutions for the new fractional-order system are also investigated theoretically. Simulation results signify the performance of the work.