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The purpose of this paper is to improve the framework of classical collaborative optimization (CCO) so as to solve the multi-disciplinary optimization problems with parametric and parameter-free variables, and therefore an improved collaborative optimization (ICO) is proposed.

To clarify the relation of design variables, the optimization problem is classified into three general case. For each case, the respective treatment is suggested for coupled or uncoupled variables in the framework of the ICO.

The decoupling treatment suggested in the ICO framework not only avoids the iteration divergence and thus optimization failure, but increases the optimal design space to some extent. The method is validated by optimizing an aircraft assembly and a high-speed train assembly.

The two practical examples proves that the present ICO succeeds in solving the problem that the CCO failed to, also gives the optimal results better than those from the sequential optimization method.

The Semiloof shell element stiffness and mass matrices are analysed. Various integration rules for the stiffness matrix are used, and the influence of these rules on the existence of mechanisms and on the element spectra is studied. Some methods for lumping the mass matrix are attempted with special reference to a method imposing a given behaviour of the spectra of eigenvalues.

Addresses problems in mechanics and physics involving two or more coupled variables of different nature, or a number of distinct domains which interact. For these kinds of problems, considers numerical solution by the coupling of operators appertaining to the individual participating phenomena, or defined in the domains. Reviews the co‐operation of distinct discretized operators in connection with the integration of temporal evolution processes, and the iterative treatment of stationary equations of state. The specification of subtasks complies with the demand for an independent treatment on different processing units arising in parallel computation. Physical subtasks refer to problems of different field variables interacting on the continuum level; their number is usually small. Fine granularity may be achieved by separating the problem region into subdomains which communicate via the boundaries. In multiphysics simulations operators are preferably combined such that subdomains are processed in parallel on different units, while physical phenomena are processed sequentially in the subdomain.

In this paper, a first‐order approximation coupling (FOAC) model is investigated to analyze the dynamics of the hub‐beam system, which is based on the Hamilton theory and the finite element discretization method. The FOAC model for the hub‐beam system considers the second‐order coupling quantity of the axial displacement caused by the transverse displacement of the beam. The dynamic characteristics of the system are studied through numerical simulations under twos cases: the rotary inertia of the hub is much larger than, and is close to, that of the flexible beam. Simulation and comparison studies using both the traditional zeroth‐order approximation coupling (ZOAC) model and the FOAC model shows that when large motion of the system is unknown, possible failure exists by using the ZOAC model, whereas the FOAC model is valid. When the rotary inertia of the hub is much larger than that of the beam, the result using the ZOAC model is similar to that using the FOAC model. But when the rotary inertia of the hub is close to that of the beam, the ZOAC model may lead to a large error, while the FOAC model can still accurately describe the dynamic hub‐beam system.

The purpose of this paper is to investigate changes in the commercial real estate market dynamics as a function of and conditional to the shifts in market state-space environment that can influence agent responses.

The analytical design uses a comparative computational experiment to address the performance of property assets in the current market based on comparison with prior structural patterns. The latent variables developed across market sectors are used to test agent behavior contingent on the perspectives of capital asset pricing conditionals (CAPM) and a behavioral momentum/herd construct. The state-space momentum analysis can assist the comparative analysis of current levels and shifts in property asset performance given the issues that have arisen with the financial crisis of 2007-2009.

An analytic approach is employed framed by a situation-dependent model. This frame considers risk profiles characterizing the perspectives and preferences guiding a delineated market state. This perspective is concerned with the possibility of shifts in market momentum and representativeness conditioning investor expectations. It is observed that the current market (post-crisis) has changed significantly from the prior operations (despite the diversity observed in prior market states). The dynamics of initial findings required an additional test anchored to the performance of the general capital market and the real economy across time. This context supports the use of a modified CAPM model allowing the consideration of opportunity cost in a space-time dynamic anchored with the consideration of equity, debt, riskless asset and liquidity options as they varied for the representative agents operating per market state.

This paper integrates neoclassical and behavioral economic constructs. Combines asset pricing with prospect theory and allows the calculation of endogenous time-preferences, risk attitudes and formulation and testing of hyperbolic discounting functions.

The research shows that market structure and agent behavior since the financial crisis has changed from the investment and valuation perspectives operating as observed and measured from 1970 up to 2007. In contradiction to the long-term findings of Reinhart and Rogoff (2008), but in compliance with common perspectives and decision heuristics often employed by investors, this time things have changed! Discounting and expected rates of return are dynamic and are hyperbolic and not constant. Returns and investment for property assets are situational (market state-space specific) and offer a distinct asset class, not appropriately estimated by many of the traditional financial models.

Assist in supporting insights to measure in errors and equations that result in inefficient resource allocation and beta discounting that supports the financial crisis created by assets subject to long-term decision needs (delta function).

The paper offers a combination and comparison of neoclassic asset pricing using a modified CAPM (two-pass) approach within the structural frame of Kahneman and Tversky’s (1979) prospect theory. This technique allows the consideration of the effects of present bias, beta-delta functions and the operation of the Allais Paradox in market states that are characterized by gains and losses and thus risk aversion and risk seeking behavior. This ability for differentiation allows for the development of endogenous time-preferences and hyperbolic discounting factors characteristic of commercial property investment.

Flying‐capacitor multilevel converters (FCC) need a passive or active regulation of the capacitor voltages. Recently the trend is towards active control, often implemented separately from the current control. The advantages of a true multi‐variable control sparked the interest to apply Model Based Predictive Control (MBPC) for FCC. In this paper an objective analysis method to evaluate the effects of several design choices is presented. The effects of the weight factor selection, model simplification, and prediction horizon expansion for MBPC of a 3‐level FCC are analyzed in a systematical way.

The analysis is mainly based on the mean square error (MSE) of current and capacitor voltage. The results are analysed for different lengths of the prediction horizon and for a wide range of weight factor values. Similarly the effect of a model simplification, neglecting the neutral point voltage, is studied when implementing MBPC for FCCs while considering the computational aspects. Validation of the simulation results is done by experiments on an FPGA‐based setup.

Including the effect of the neutral point voltage considerably increases the current control quality and a much wider range of good values for the weight factor exists. As this good range is not critically dependent on the current amplitude it is possible to select one weight factor value for all operating points. Furthermore, it is concluded that increasing the prediction horizon increases the computational load without improving the control quality.

The effects of increasing the prediction horizon when including other controlled variables is to be investigated, as well as the robustness to modeling errors. The MSE analysis methodology is very suitable for this further research.

For practitioners of MBPC in power electronics the paper proves that by means of simulations and the MSE one value for weight factor can be chosen for all operating points. The paper clearly shows that a practical implementation is feasible and demonstrates that neglecting the neutral point voltage is not good practice.

The MSE‐based analysis is shown to be a systematical and unbiased methodology to evaluate the effects of design choices. The results from this analysis can be directly applied in practical setups.

The purpose of the paper is to prepare the hygrothermal model with fraction order theory in a mathematical aspect.

In this study, linear hygrothermoelastic theory is adopted to analyze and discuss the memory effect in a finite length hollow cylinder subjected to hygrothermal loading.

Analytical solutions of temperature, moisture and stresses are obtained in this study by using the decoupling technique and the method of Integral transform.

The paper deals with the original work based on hygrothermal response in hollow cylinder by theory of uncoupled-coupled heat and moisture.

Outlines a general methodology for the solution of the system of algebraic equations arising from the discretization of the field equations governing coupled problems. Considers that this discrete problem is obtained from the finite element discretization in space and the finite difference discretization in time. Aims to preserve software modularity, to be able to use existing single field codes to solve more complex problems, and to exploit computer resources optimally, emulating parallel processing. To this end, deals with two well‐known coupled problems of computational mechanics – the fluid‐structure interaction problem and thermally‐driven flows of incompressible fluids. Demonstrates the possibility of coupling the block‐iterative loop with the nonlinearity of the problems through numerical experiments which suggest that even a mild nonlinearity drives the convergence rate of the complete iterative scheme, at least for the two problems considered here. Discusses the implementation of this alternative to the direct coupled solution, stating advantages and disadvantages. Explains also the need for online synchronized communication between the different codes used as is the description of the master code which will control the overall algorithm.

A computer program for the solution of the single carrier semiconductor equations in GaAs has been developed to simulate charge storage and transfer in GaAs charge‐coupled devices. An uncoupled Newton method is used to solve the steady state problem, and a stable, uncoupled method is used for the transient solution. Using transient simulation, the transfer of a charge packet from well to well can be simulated over time. By comparing the size of the charge packet before and after the transfer, information on the charge transfer inefficency can be derived.

The purpose of this paper is to report the implementation of an alternative time integration procedure for the dynamic non-linear analysis of structures.

The time integration algorithm discussed in this work corresponds to a spectral decomposition technique implemented in the time domain. As in the case of the modal decomposition in space, the numerical efficiency of the resulting integration scheme depends on the possibility of uncoupling the equations of motion. This is achieved by solving an eigenvalue problem in the time domain that only depends on the approximation basis being implemented. Complete sets of orthogonal Legendre polynomials are used to define the time approximation basis required by the model.

A classical example with known analytical solution is presented to validate the model, in linear and non-linear analysis. The efficiency of the numerical technique is assessed. Comparisons are made with the classical Newmark method applied to the solution of both linear and non-linear dynamics. The mixed time integration technique presents some interesting features making very attractive its application to the analysis of non-linear dynamic systems. It corresponds in essence to a modal decomposition technique implemented in the time domain. As in the case of the modal decomposition in space, the numerical efficiency of the resulting integration scheme depends on the possibility of uncoupling the equations of motion.

One of the main advantages of this technique is the possibility of considering relatively large time step increments which enhances the computational efficiency of the numerical procedure. Due to its characteristics, this method is well suited to parallel processing, one of the features that have to be conveniently explored in the near future.