Issues in optimal parameter estimation for the nonlinear Muskingum flood routing model

This study answers two questions raised in the parameter estimation optimization for the nonlinear Muskingum flood routing model. The first question is whether a new global optimum was still found after the existing global optimum had already been found. In order to fairly verify this question, a standard routing procedure for the nonlinear Muskingum model, which has not been clearly described previously, is proposed. Because the routing procedure was coded in a spreadsheet, any researcher can easily test it after downloading it. The second question is the reason why various approaches, such as Lagrange multiplier, Broyden–Fletcher–Goldfarb–Shanno (BFGS), genetic algorithm, harmony search and particle swarm optimization, have tackled only Wilson's data set as the parameter estimation optimization for the nonlinear Muskingum model, because Wilson's data have a unique structure which is differentiated from other data sets. This study also provides various data sets to compare.     

Active control of FGM plates subjected to a temperature gradient: Modelling via finite element method based on FSDT

An efficient finite element formulation based on a first‐order shear deformation theory (FSDT) is presented for the active control of functionally gradient material (FGM) plates with integrated piezoelectric sensor/actuator layers subjected to a thermal gradient; this is accomplished using both static and dynamic piezothermoelastic analyses. The formulation based on FSDT can be applied to a range of relatively thin‐to‐moderately thick plates. A constant displacement‐cum‐velocity feedback control algorithm coupling the direct and inverse piezoelectric effects is applied to provide active feedback control of the integrated FGM plate in a self‐monitoring and self‐controlling system. Numerical results for the control of bending and torsional deflections and/or vibrations are presented for a FGM plate comprising zirconia and aluminium. The effects of constituent volume fraction and the influence of feedback control gain on the static and dynamic responses of the FGM plates are examined in detail. Copyright © 2001 John Wiley & Sons, Ltd.     

Identification and control of multi-evaporator air-conditioning systems

Modern multi-evaporator air-conditioners (MEACs) incorporate variable-speed compressors and variable-opening expansion valves as the actuators for improving cooling performance and energy efficiency. These actuators have to be properly feedback-controlled; otherwise the systems may exhibit even poorer performance than the conventional machines which use fixed-speed compressors and conventional expansion valves. In this paper, feedback controller design for the MEAC system is first addressed through experimental identification. The identification produces a low-order, linear model suitable for controller design. The feedback controller employed is multi-input–multi-output-based and possesses a cascade structure for dealing with the fast and slow dynamics in the system. To determine appropriate control parameters, conditions that establish the stability for the cascade design are given. Due to the deficiency in control inputs, the proposed control structure exhibits steady-state errors in the superheat responses which in turn can produce unacceptable steady-state superheats. To resolve this issue, the reference superheat settings are determined via an optimization procedure so that the resultant steady-state superheats become acceptable. The control experiments indicate that the proposed controller can successfully regulate the indoor temperatures and maintain the steady-state superheat temperatures at acceptable levels.     

Finite element piezothermoelasticity analysis and the active control of FGM plates with integrated piezoelectric sensors and actuators

 An efficient finite element model is presented for the static and dynamic piezothermoelastic analysis and control of FGM plates under temperature gradient environments using integrated piezoelectric sensor/actuator layers. The properties of an FGM plate are functionally graded in the thickness direction according to a volume fraction power law distribution. A constant displacement-cum-velocity feedback control algorithm that couples the direct and inverse piezoelectric effects is applied to provide active feedback control of the integrated FGM plate in a closed loop system. Numerical results for the static and dynamic control are presented for the FGM plate, which consists of zirconia and aluminum. The effects of the constituent volume fractions and the influence of feedback control gain on the static and dynamic responses of the FGM plates are examined. Received: 13 March 2002 / Accepted: 5 March 2003 The work described in this paper was supported by a grant awarded by the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. CityU 1024/01E).     

A Useful Method for Model - Building II: Synthesizing Response Functions From Individual Components

In model-building investigations the response of interest y is often a function of two or more components. The usual procedure in such situations is to use this function to compute the values of y for each run and then obtain the fitted equation ? = F(x ₁, x ₂, …, x _k ) relating ? to relevant process variables. In this article we suggest a different method that will sometimes be preferable: first fit equations to the component responses (either individually or in subsets) and then combine these equations to obtain the desired function F. The proposed method is especially useful when the usual procedure fails to produce a satisfactory model. A chemical example illustrates how, by using this method, a second-order model can be obtained from a first-order design (a two-level factorial design).     

Challenges to Informed Peer Review Matching Algorithms

Background Peer review is a beneficial pedagogical tool. Despite the abundance of data instructors often have about their students, most peer review matching is by simple random assignment. In fall 2008, a study was conducted to investigate the impact of an informed algorithmic assignment method, called Un‐weighted Overall Need (UON), in a course involving Model‐Eliciting Activities (MEAs). The algorithm showed no statistically significant impact on the MEA Final Response scores. A study was then conducted to examine the assumptions underlying the algorithm. Purpose (Hypothesis ) This research addressed the question: To what extent do the assumptions used in making informed peer review matches (using the Un‐weighted Overall Need algorithim) for the peer review of solutions to Model‐Eliciting Activities decay? Design /method An expert rater evaluated the solutions of 147 teams' responses to a particular implementation of MEAs in a first‐year engineering course at a large mid‐west research university. The evaluation was then used to analyze the UON algorithm's assumptions when compared to a randomly assigned control group. Results Weak correlation was found in the five UON algorithm's assumptions: students complete assigned work, teaching assistants can grade MEAs accurately, accurate feedback in peer review is perceived by the reviewed team as being more helpful than inaccurate feedback, teaching assistant scores on the first draft of an MEA can be used to accurately predict where teams will need assistance on their second draft, and the error a peer review has in evaluating a sample MEA solution is an accurate indicator of the error they will have while subsequently evaluating a real team's MEA solution. Conclusions Conducting informed peer review matching requires significant alignment between evaluators and experts to minimize deviations from the algorithm's designed purpose.     

Handling “Dont Know” Survey Responses: The Case of Japanese Voters on Party Support

The problem of false negatives, people who really have attitudes but refrain from expressing them, could seriously bias the analysis, but has largely been neglected. Using a survey data including a number of “Don’t know” responses, this paper examined whether “Don’t know” respondents had underlying attitudes. We treated these nonresponses as nonignorably missing, in the sense that “Don’t know” responses are related to the answer of the question in some partially unknown way. We proposed a method to estimate parameters in a logit model when the covariates are nonignorably missing. The method simultaneously employed two generalized linear models: the proportional odds model for the response variable “Party-Support”, and the multinomial logit model for the nonresponse. We found that “Don’t know” responses to the Cabinet support question depended on whether the respondents supported the Cabinet, indicating the existence of false negatives. We also found that determining which party to support was based on voters’ ideology, city size and stance toward the Cabinet, even with the false negatives.

     

A scheduling method for Berth and Quay cranes

This paper discusses a method for scheduling Berth and Quay cranes, which are critical resources in port container terminals. An integer programming model is formulated by considering various practical constraints. A two-phase solution procedure is suggested for solving the mathematical model. The first phase determines the Berthing position and time of each vessel as well as the number of cranes assigned to each vessel at each time segment. The subgradient optimization technique is applied to obtain a near-optimal solution of the first phase. In the second phase, a detailed schedule for each Quay crane is constructed based on the solution found from the first phase. The dynamic programming technique is applied to solve the problem of the second phase. A numerical experiment was conducted to test the performance of the suggested algorithms. RID="*" ID="*" This research has been supported in part by Brain Korea 21 Program (1999–2002). Correspondence to: Y.-M. Park     

Structural parameters identification of uncertain multi-storey shear buildings using fuzzy neural network modelling

Present paper proposes a fuzzy neural network (FNN)-based modelling for the identification of structural parameters of uncertain multi-storey shear buildings. Here, the method is developed to identify uncertain structural mass, stiffness and damping matrices from the dynamic responses of the structure without any optimization processes that are generally used to solve inverse vibration problems. Uncertainty has been taken in term of fuzzy numbers. The governing equations of motion are first solved by the classical method to get responses of the consecutive stories. Further the governing equations of motion are modified based on relative responses of consecutive stories in such a way that the new set of equations can be implemented in a cluster of FNNs. As such the model starts solving the nth floor by FNN modelling to estimate the structural parameters. Subsequently, series of FNN models are used to estimate the parameters for (n ? 1)th storey to the first storey. One may note that single layer FNNs have been used for training for each cluster of the FNN such that the converged weights give the uncertain structural parameters. The initial weights in the FNN architecture are taken as the design parameters in uncertain (fuzzy) form. In order to validate the present model, various example problems of different multi-storey shear structures have been considered. Related results are incorporated in term of tables and graphs. Comparisons between theoretical and identified results are carried out and are found to be in good agreement.     

Optimizing Worked‐Example Instruction in Electrical Engineering: The Role of Fading and Feedback during Problem‐Solving Practice

How can we help college students develop problem‐solving skills in engineering? To answer this question, we asked a group of engineering freshmen to learn about electrical circuit analysis with an instructional program that presented different problem‐solving practice and feedback methods. Three findings are of interest. First, students who practiced by solving all problem steps and those who practiced by solving a gradually increasing number of steps starting with the first step first (forward‐fading practice) produced higher near‐transfer scores than those who were asked to solve a gradually increasing number of steps but starting with the last step first (backward‐fading practice). Second, students who received feedback immediately after attempting each problem‐solving step outperformed those who received total feedback on near transfer. Finally, students who learned with backward‐fading practice produced higher near‐ and far‐transfer scores when feedback included the solution of a similar worked‐out problem. The theoretical and practical implications for engineering education are discussed.     

The superconvergent patch recovery and a posteriori error estimates. Part 1: The recovery technique

This is the first of two papers concerning superconvergent recovery techniques and a posteriori error estimation. In this paper, a general recovery technique is developed for determining the derivatives (stresses) of the finite element solutions at nodes. The implementation of the recovery technique is simple and cost effective. The technique has been tested for a group of widely used linear, quadratic and cubic elements for both one and two dimensional problems. Numerical experiments demonstrate that the recovered nodal values of the derivatives with linear and cubic elements are superconvergent. One order higher accuracy is achieved by the procedure with linear and cubic elements but two order higher accuracy is achieved for the derivatives with quadratic elements. In particular, an O(h⁴) convergence of the nodal values of the derivatives for a quadratic triangular element is reported for the first time. The performance of the proposed technique is compared with the widely used smoothing procedure of global L₂ projection and other methods. It is found that the derivatives recovered at interelement nodes, by using L₂ projection, are also superconvergent for linear elements but not for quadratic elements. Numerical experiments on the convergence of the recovered solutions in the energy norm are also presented. Higher rates of convergence are again observed. The results presented in this part of the paper indicate clearly that a new, powerful and economical process is now available which should supersede the currently used post-processing procedures applied in most codes.     

Efficient uncertainty quantification of dynamical systems with local nonlinearities and uncertainties

Idealized modeling of most engineering structures yields linear mathematical models, i.e., linear ordinary or partial differential equations. However, features like nonlinear dampers and/or springs can render nonlinear an otherwise linear model. Often, the connectivity of these nonlinear elements is confined to only a few degrees-of-freedom (DOFs) of the structure. In such cases, treating the entire structure as nonlinear results in very computationally expensive solutions. Moreover, if system parameters are uncertain, their stochastic nature can render the analysis even more computationally costly. This paper presents an approach for computing the response of such systems in a very efficient manner. The proposed solution procedure first segregates the DOFs appearing in the nonlinear and/or stochastic terms from those DOFs that involve only linear deterministic operations. Second, the responses of nonlinear/stochastic terms are determined using a non-standard form of a nonlinear Volterra integral equation (NVIE). Finally, the responses of the remaining DOFs are computed through a convolution approach using the fast Fourier transform to further increase the computational efficiency. Three examples are presented to demonstrate the efficacy and accuracy of the proposed method. It is shown that, even for moderately sized systems (∼1000 DOFs), the proposed method is about three orders of magnitude faster than a conventional Monte Carlo sampling method (i.e., solving the system of ODEs repeatedly).     

Modeling of latent structure of indomethacin solid dispersion tablet using Bayesian networks

Background: When designing pharmaceutical products, the relationships between causal factors and pharmaceutical responses are intricate. A Bayesian network (BN) was used to clarify the latent structure underlying the causal factors and pharmaceutical responses of a tablet containing solid dispersion (SD) of indomethacin (IMC).

Method: IMC, a poorly water-soluble drug, was tested with polyvinylpyrrolidone as the carrier polymer. Tablets containing a SD or a physical mixture of IMC, different quantities of magnesium stearate, microcrystalline cellulose, and low-substituted hydroxypropyl cellulose, and subjected to different compression force were selected as the causal factors. The pharmaceutical responses were the dissolution properties and tensile strength before and after the accelerated test and a similarity factor, which was used as an index of the storage stability.

Result: BN models were constructed based on three measurement criteria for the appropriateness of the graph structure. Of these, the BN model based on Akaike’s information criterion was similar to the results for the analysis of variance. To quantitatively estimate the causal relationships underlying the latent structure in this system, conditional probability distributions were inferred from the BN model. The responses were accurately predicted using the BN model, as reflected in the high correlation coefficients in a leave-one-out cross-validation procedure.

Conclusion: The BN technique provides a better understanding of the latent structure underlying causal factors and responses.     

A robust approach to model densification and crack formation in powder compaction processes

This paper deals with the question of how to efficiently integrate a constitutive model that describes the densification of powders and the potential formation of cracks in Powder Metallurgy (P/M) cold compaction processes. The analyzed model is a large strain, elastoplastic model of the Drucker–Prager/Cap type, refined to cover also the prediction of crack formation, and featuring non‐conventional elements such as a density‐dependent Von Mises yield surface; a parabolic plastic potential function for the Drucker–Prager envelope; and a softening law whose softening modulus is dependent on the level of densification. The employed integration procedure is a non‐conventional hybrid or IMPLicit–EXplicit (IMPL‐EX) scheme, whose essence is to solve explicitly for some variables and implicitly for others, with the peculiarity of the ‘explicit’ variables being but extrapolated values of the same quantities computed, at previous time steps, by means of a fully implicit scheme. The return‐mapping equations stemming from this implicit scheme are solved using an unconditionally convergent, fractional step method‐based iterative procedure. The performance of the IMPL‐EX integration algorithm is critically assessed in two different situations: the densification of a cylindrical specimen, and the fracture process in a diametral compression test. Results obtained show conclusively that the proposed hybrid integration strategy offers an efficient solution to the trade‐off between robustness and computational time requirements. Copyright © 2011 John Wiley & Sons, Ltd.     

A time‐integration method for the viscoelastic–viscoplastic analyses of polymers and finite element implementation

The present study introduces a time‐integration algorithm for solving a non‐linear viscoelastic–viscoplastic (VE–VP) constitutive equation of isotropic polymers. The material parameters in the constitutive models are stress dependent. The algorithm is derived based on an implicit time‐integration method (Computational Inelasticity. Springer: New York, 1998) within a general displacement‐based finite element (FE) analysis and suitable for small deformation gradient problems. Schapery's integral model is used for the VE responses, while the VP component follows the Perzyna model having an overstress function. A recursive‐iterative method (Int. J. Numer. Meth. Engng 2004; 59 :25–45) is employed and modified to solve the VE–VP constitutive equation. An iterative procedure with predictor–corrector steps is added to the recursive integration method. A residual vector is defined for the incremental total strain and the magnitude of the incremental VP strain. A consistent tangent stiffness matrix, as previously discussed in Ju (J. Eng. Mech. 1990; 116 :1764–1779) and Simo and Hughes (Computational Inelasticity. Springer: New York, 1998), is also formulated to improve convergence and avoid divergence. Available experimental data on time‐dependent and inelastic responses of high‐density polyethylene are used to verify the current numerical algorithm. The time‐integration scheme is examined in terms of its computational efficiency and accuracy. Numerical FE analyses of microstructural responses of polyethylene reinforced with elastic particle are also presented. Copyright © 2009 John Wiley & Sons, Ltd.     

On the Formation and Stability of Fullerenes

Abstract

Fullerenes (especially the higher ones) degrade to an insoluble material on storage in air. The C _2v(II) isomer of [78]fullerene is completely degraded after storage for 5 months. The extreme instability may account for the variable yields of this isomer obtained by different research groups. Strong heating of KBr discs of these insoluble materials produces CO₂ showing that they are oxygen containing. Given this inherent instability of fullerenes, the question arises as to why they are formed in the first place. It is argued that the formation is not a unique consequence of the need to eliminate dangling bonds produced during carbon vaporisation by the arc-discharge procedure. Rather, fullerene formation is favoured by a higher intramolecular dangling-bond collision frequency (i.e. much higher Arrhenius A-factor) for cage closure compared to the intermolecular collisions that lead to the more stable graphitic sheets.     

Construction,Properties, and Analysis of Group-Orthogonal Supersaturated Designs

Abstract

In this article, we propose a new method for constructing supersaturated designs that is based on the Kronecker product of two carefully chosen matrices. The construction method leads to a partitioning of the factors of the design such that the factors within a group are correlated to the others within the same group, but are orthogonal to any factor in any other group. We refer to the resulting designs as group-orthogonal supersaturated designs. We leverage this group structure to obtain an unbiased estimate of the error variance, and to develop an effective, design-based model selection procedure. Simulation results show that the use of these designs, in conjunction with our model selection procedure enables the identification of larger numbers of active main effects than have previously been reported for supersaturated designs. The designs can also be used in group screening; however, unlike previous group-screening procedures, with our designs, main effects in a group are not confounded. Supplementary materials for this article are available online.     

Tracking control of a multilayer piezoelectric actuator using a fiber bragg grating displacement sensor system

This paper provides a fiber Bragg grating (FBG) sensor system which can measure the point-wise, out-of-plane displacement to examine the position-tracking control problem of a multilayer piezoelectric actuator (MPA). An FBG filter-based wavelength-optical intensity modulation technique is used in this study. A nominal system model is identified experimentally from the responses excited by random signals measured by an FBG displacement sensor that are simultaneously compared with those obtained from a laser Doppler vibrometer. To further investigate the sensing ability of the proposed system in a feedback control problem, control strategies including robust Hα control, proportional-integralderivative control, and pseudoderivative feedback control are implemented. The characteristics of the step responses for each controller are examined. The experimental results show that the proposed sensor system is capable of performing the system identification and can serve as a feedback control sensor which has a displacement sensitivity of 5 mV/nm.     

OPTIMAL STRUCTURAL DESIGN BY ANT COLONY OPTIMIZATION

Ant colony optimization (ACO) is a relatively new heuristic combinatorial optimization algorithm in which the search process is a stochastic procedure that incorporates positive feedback of accumulated information. The positive feedback (;i.e., autocatalysis) facility is a feature of ACO which gives an emergent search procedure such that the (common) problem of algorithm termination at local optima may be avoided and search for a global optimum is possible.

The ACO algorithm is motivated by analogy with natural phenomena, in particular, the ability of a colony of ants to ‘optimize’ their collective endeavours. In this paper the biological background for ACO is explained and its computational implementation is presented in a structural design context. The particular implementation of ACO makes use of a tabu search (TS) local improvement phase to give a computationally enhanced algorithm (ACOTS).

In this paper ACOTS is applied to the optimal structural design, in terms of weight minimization, of a 25-bar space truss. The design variables are the cross-sectional areas of the bars, which take discrete values. Numerical investigation of the 25-bar space truss gave the best (i.e., lowest to-date) minimum weight value. This example provides evidence that ACOTS is a useful and technically viable optimization technique for discrete-variable optimal structural design.     

First-passage failure of quasi linear systems subject to multi-time-delayed feedback control and wide-band random excitation

A procedure for studying the first-passage failure of quasi-linear systems subject to multi-time-delayed feedback control and wide-band random excitation is proposed. The stochastic averaging method for quasi-integrable Hamiltonian systems is first introduced. The backward Kolmogorov equation governing the conditional reliability function and a set of generalized Pontryagin equations governing the conditional moments of first-passage time are then established. The conditional reliability function, the conditional probability density and moments of first-passage time are obtained by solving the backward Kolmogorov equation and generalized Pontryagin equations with suitable initial and boundary conditions. An example is given to illustrate the proposed procedure and the results from digital simulation are obtained to verify the effectiveness of the proposed procedure. The effects of time delay in feedback control forces on the conditional reliability function, conditional probability density and moments of first-passage time are analyzed.