Residual stresses in porcelain tiles. Measurement and process variables assessment

This research addresses the residual stresses phenomenon taking place during the manufacture of porcelain tiles. Residual stresses were quantified by the strain relaxation slotting method. The method is based on the fact that stresses are released when a slot is made leading to a curvature change.Once the method was validated, the impact of process variables such as starting body composition, temperature and cooling rate of firing cycle was investigated. Findings showed that cooling rate was the most influencing variable whereas Young’s modulus of fired specimens also play a significant role. Symmetry of the parabolic residual stress profile denoted homogenous cooling on upper and lower tile surfaces during the cooling step. In addition, it was observed that polishing of a stressed tile gives rise to a decreasing of deformation as a consequence of stress release by mechanical grinding.     

Adaptive neuro-fuzzy algorithm applied to predict and control multi-phase flow rates through wellhead chokes

A Takagi-Sugeno adaptive neuro-fuzzy inference system (TSFIS) model is developed and applied to a dataset of wellhead flow-test data for the Resalat oil field located offshore southern Iran, the objective is to assist in the prediction and control of multi-phase flow rates of oil and gas through the wellhead chokes. For this purpose, 182 test data points (Appendix 1) related to the Resalat field are evaluated. In order to predict production flow rate (Q_L) expressed as stock-tank barrels per day (STB/D), this dataset includes four selected input variables: upstream pressure (Pwh); wellhead choke sizes (D64); gas to liquid ratio (GLR); and, base solids and water including some water-soluble oil emulsion (BS&W). The test data points evaluated include a wide range of oil flow rate conditions and values for the four input variables recorded. The TSFIS algorithm applied involves five data processing steps: a) pre-processing, b) fuzzification, c) rules base and adaptive neuro-fuzzy inference engine, d) defuzzification, and e) post-processing of the fuzzy model. The developed TSFIS model for the Resalat oil field database predicted oil flow rate to a high degree of accuracy (root mean square error = 247 STB/D, correlation coefficient = 0.9987), which improves substantially on the commonly used empirical algorithms used for such predictions. TSFIS can potentially be applied in wellhead choke fuzzy controllers to stabilize flow in specific wells based on real-time input data records.     

岩层与地表移动变形量的时空关系及描述方法

矿山开采沉陷是指地下开采引起的岩层与地表移动现象和过程，移动变形的描述方法是开采沉陷研究的基础。本文较为全面地阐述了岩层与地表移动变形量的时空关系，指出开采沉陷的岩层、地表、松散层等3个主体，9个移动变形量。按照移动盆地、主断面、任意点3种描述模式，给出了各移动变形量之间的数学关系;论述地表动态移动变形与开采影响的传播过程的时空关系，提出了开采推进时间、影响传播时间双变量的动态移动变形描述方法;给出了直线型、折线型、网状观测站地表移动变形的关系式。可为开采沉陷观测分析、预计模型研究提供数学依据。     

An engineering method for complex structural optimization involving both size and topology design variables

This work presents an engineering method for optimizing structures made of bars, beams, plates, or a combination of those components. Corresponding problems involve both continuous (size) and discrete (topology) variables. Using a branched multipoint approximate function, which involves such mixed variables, a series of sequential approximate problems are constructed to make the primal problem explicit. To solve the approximate problems, genetic algorithm (GA) is utilized to optimize discrete variables, and when calculating individual fitness values in GA, a second-level approximate problem only involving retained continuous variables is built to optimize continuous variables. The solution to the second-level approximate problem can be easily obtained with dual methods. Structural analyses are only needed before improving the branched approximate functions in the iteration cycles. The method aims at optimal design of discrete structures consisting of bars, beams, plates, or other components. Numerical examples are given to illustrate its effectiveness, including frame topology optimization, layout optimization of stiffeners modeled with beams or shells, concurrent layout optimization of beam and shell components, and an application in a microsatellite structure. Optimization results show that the number of structural analyses is dramatically decreased when compared with pure GA while even comparable to pure sizing optimization.     

Sensor network design based on system-wide reliability criteria. Part I: Objectives

Reliability based criteria are quite popular for optimal sensor network design. We present a modified definition of system reliability for sensor network design for two applications: reliable estimation of variables in a steady state linear flow process, and reliable fault detection and diagnosis for any process. Unlike the weakest-link based definition of system reliability in the literature, the proposed definition considers the entire system and is consistent with the reliability concept used in classical reliability literature. For each application, dual approaches for defining system reliability are proposed, and their analogy with the reliability problem in the classical reliability literature is established. Using examples and stochastic simulations, the advantage of using the proposed system reliability in contrast to the existing definition is illustrated. Part II of this series of articles presents methods for efficient generation of the system reliability function and its use in optimization-based approaches for designing optimal sensor networks.     

Solving fuzzy capacitated location routing problem using hybrid variable neighborhood search and evolutionary local search

A fuzzy capacitated location routing problem (FCLRP) is solved by using a heuristic method that combines variable neighborhood search (VNS) and evolutionary local search (ELS). Demands of the customer and travel times between customers and depots are considered as fuzzy and deterministic variables, respectively in FCLRP. Heterogeneous and homogeneous fleet sizes are performed together to reach the least multi-objective cost in a case study. The multi-objective cost consists of transportation cost, additional cost, vehicle waiting cost and delay cost. A fuzzy chance constrained programming model is added by using credibility theory. The proposed method reaches the solution by performing four stages. In the first stage, initial solutions are obtained by using a greedy heuristic method, and then VNS heuristic, which consists of seven different neighborhood structures, is performed to improve the solution quality in the second stage. In the third stage, a perturbation procedure is applied to the improved solution using ELS algorithm, and then VNS heuristic is applied again in the last stage. The combination of VNS and ELS is called VNSxELS algorithm and applied to a case study, which has fifty-seven customers and five distributing points, effectively in a reasonable time.     

A coupled and interactive influence of operational parameters for optimizing power output of cleaner energy production systems under uncertain conditions

The mechanisms in proton‐exchange membrane fuel cells (PEMFCs) cannot be explicitly represented by a mathematical function because the PEMFC system is multi‐dimensional and complex and represents uncertainty in operation variables, which cannot be modeled by experiments or by trial‐and‐error approach. Therefore, this work proposes to study the coupled and interactive influence of stack current (SC), stack temperature (ST), oxygen excess ratio (OER), hydrogen excess ratio (HER), and inlet air humidity (IAH) for optimizing the power output of PEMFC. The data obtained from the experiments have been inserted into architecture of automated neural‐network search, which automates the selection of error function, activation function, uncertainties in inputs and number of hidden neurons in formulation of a robust and accurate model for power density as a function of five operational variables. Among the operational variables, the correlation coefficient between the SC and the output power is the highest, followed by OER, and the ST. However, for HER and IAH, the power output follows negative nonlinear relation. The optimization converged at 130^th iteration results in maximum power output of 3410 W for an optimum value of SC (51A), ST (59°C), OER (3:2), HER (1:10), and IAH (0.8).     

Stability boundary analysis of magnetohydrodynamic circulator for the intermediate heat transfer system of prototype gen IV sodium fast reactor

One of the most important parts in the development of generation IV nuclear reactors is safety. In the research on generation IV sodium‐cooled fast reactors, magnetohydrodynamic (MHD) circulators have received attention for the stable transport of coolants. In this study, the stability of an MHD circulator was evaluated using a mathematical approach to obtain the critical value of the developed pressure. The critical developed pressure equation is a function of the flow rate and dimensionless parameters, which were derived from the theoretical model of the MHD circulator with a dimensionless scaled velocity, flow rate, and pressure. The stability conditions expressed using the critical value of the developed pressure and dimensionless parameters were investigated according to the changes in the main design variables of the MHD circulator. The relationships between the dimensionless parameters, stability, and main design variables constituting the stability boundary of the MHD circulator were analysed. The stability of the MHD circulator is considered safe when the stability criterion ε is lower than 1. The geometrical variables such as the duct thickness or width of the flow gap and electrical variables such as the frequency were the main parameters affecting the flow stability in the MHD circulator.     

Seismic risk analysis for reinforced concrete structures with both random and parallelepiped convex variables

This article develops an improved seismic risk assessment formulation exhibiting both random and bounded uncertainties using a probability and parallelepiped convex set mixed model. Limit thresholds for different types of components are described via a probabilistic model. The distribution parameters of limit thresholds are originally treated by employing a multidimensional parallelepiped convex model, in which marginal intervals are utilised to represent scattering levels for the distribution parameters, while relevant angle are employed to express the correlation between uncertain distribution parameters. The structural responses, i.e., engineering demand parameters (EDPs), are considered as correlated random variables and are assumed to follow a multidimensional lognormal distribution. A performance limit state function, which allows considering the relationship between the EDPs and the corresponding limit thresholds, is employed to reflect the coexistence of both random and parallelepiped convex variables. The limit state function is mapped into the standard parameter space via a transformation technique. Then, the improved seismic risk formulation, characterised through a probability and parallelepiped convex mixed variables, can be derived with the combination of the seismic fragility function and the ground motion hazard curve. The main purpose is to illustrate that the performance limit states should be properly modeled as random and parallelepiped convex mixed variables rather than only random or deterministic quantities. A six-story reinforced concrete building designed according to Chinese codes are used to illustrate the proposed approach for constructing hazard curves. The interstory drift and the peak floor acceleration are the selected EDPs, calculated through incremental dynamic analysis. The results demonstrate that the calculated failure probabilities for different limit states in 50?years are found capable of meeting the requirements of Chinese seismic norms after the proposed seismic risk formulation is adopted.