Determination of fracture energy,process zone longth and brittleness number from size effect,with application to rock and conerete

The dependence of the fracture energy and the effective process zone length on the specimen size as well as the craek extension from the notch is analyzed on the basis of BaN at failure is reformulated in a manner in which the parameters are the fracture energy and the effective (elastically equivalent) process zone length. A method to determine these material properties from _N-data by linear and nonlinear regressions is shown. This method permits these properties to be evaluated solely on the basis of the measured maximum loads of specimens of various sizes and possibly also of different shapes. Variation of both the fracture energy and the effective process zone length as a function of the specimen size is determined. The theoretical results agree with previous fracture tests of rock as well as concrete and describe them adequately in relation to the inevitable random scatter of the tests.

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Résumé En se reposant sur la loi des effets dimensionnels approximatifs développée par Ba     

An evolutionary‐based adaptive neuro‐fuzzy inference system for intelligent short‐term load forecasting

The continuing growth in size and complexity of electric power systems requires the development of applicable load forecasting models to estimate the future electrical energy demands accurately. This paper presents a novel load forecasting approach called genetic‐based adaptive neuro‐fuzzy inference system (GBANFIS) to construct short‐term load forecasting expert systems and controllers. At the first stage, all records of data are searched by a novel genetic algorithm (GA) to find the most suitable feature of inputs to construct the model. Then, determined inputs are fed into the adaptive neuro‐fuzzy inference system to evolve the initial knowledge‐base of the expert system. Finally, the initial knowledge‐base is searched by another robust GA to induce a better cooperation among the rules by rule weight derivation and rule selection mechanisms. We show the superiority and applicability of our approach by applying it to the Iranian monthly electrical energy demand problem and comparing it with the most frequently adopted approaches in this field. Results indicate that GBANFIS outperforms its rival approaches and is a promising tool for dealing with short‐term load forecasting problems.     

Structural characterization and strengthening mechanism of forsterite nanostructured scaffolds synthesized by multistep sintering method

In this study, highly porous forsterite scaffolds with interconnected porosities were synthesized using multi-step sintering (MSS) method. The starting powder was nanosized forsterite, which was synthesized from talc and magnesium carbonate powders. The phase composition, average particle size and morphology of the produced forsterite powder were characterized by X-ray diffraction technique (XRD) and transition electron microscopy (TEM). Forsterite scaffolds were produced by foamy method using polymeric sponges. MSS process including three steps was used to efficiently sinter the forsterite nanopowders without destroying the initial porous structure of polymeric sponges. The results showed that MSS technique is an efficient and appropriate procedure to produce highly porous forsterite scaffolds with pore size in the range of 100–300?μm. The compressive strength, compressive modulus and porosity of C12 specimen (sintered at 1650?°C for 1?h with subsequent annealing at 1000?°C for 1000?min) was 1.88?MPa, 29.2?MPa, and 72.4%, respectively, which is very close to that of cancellous bone. The approach studied in this research can be developed for other nanostructure ceramics to produce highly porous scaffolds with interconnected porosities for load bearing applications.     

Additive-free photosynthesis of acrylamide hydrogels initiated with CdS and TiO<Subscript>2</Subscript> as light visible nano-photocatalysts

Hydrogels are three-dimensional polymer networks which can be synthesized by different techniques, such as free-radical addition reaction which is the most well-known technique in functional vinyl monomer polymerization. Photopolymerization, as an attractive technique, has been used in radical polymerization of monomers and has revitalized interest in the idea that it congregates a wide range of economic and ecological expectations. Due to the spatial–temporal control and a mild curing process of polymerization, photoinitiator semiconductor nano-particles offer great advantages, such as effective and quantitative reaction. Cadmium sulfide nanowire, titanium dioxide (TiO₂) nanotube, and TiO₂ nanowire were used as visible photocatalysts for photopolymerization of acrylamide hydrogel without using any additive under the sunlight and purple LED irradiations. The effects of different synthetic parameters, including initiator type and concentration and type of light sources, were investigated to achieve hydrogels with maximum swelling capacity. The results showed that the swelling of hydrogel reached 80 g water/g hydrogel when the TiO₂ nanowire was used as the photoinitiator. The synthesized semiconductors and hydrogels were characterized by X-ray diffractometry, adsorption isotherm, infrared spectroscopy, thermogravimetric analysis, and transmission electron microscopy. According to the results, the new initiators led to semiconductor-based hydrogels, achieved with high swelling property through a high-speed high-efficient photopolymerization reaction in a safe manner.     

Pareto–Koopmans efficiency in two‐stage network data envelopment analysis in the presence of undesirable intermediate products and nondiscretionary factors

Many studies have recently been conducted on the evaluation of system performance with a two‐stage network structure in data envelopment analysis (DEA) literature. One of the topics of interest to researchers has been the mitigation of undesirable products or nondiscretionary factors into their corresponding possible production set (PPS) and their impact on overall efficiency calculations. Determination of decision‐making units (DMUs) with Pareto–Koopmans efficiency status is decisive in identifying benchmark units. The calculated overall efficiency status is compromised when both undesirable products and nondiscretionary factors are present. This work utilizes an axiomatic approach. A novel PPS for a two‐stage network in presence of undesirable intermediate products and nondiscretionary exogenous inputs is introduced. Based on this PPS and by focusing on the principle of mathematical dominance, new models for evaluating overall and divisional efficiencies are presented. In addition, by proposing a two‐step network DEA approach, a necessary and sufficient condition for detection of DMUs with Pareto–Koopmans efficiency status is provided. And by introducing a two‐step algorithm, a novel technique for determining overall efficiency conditions is produced. Finally, the proposed technology is applied to a practical example, and outcomes are discussed.     

Development of novel method for prediction of gas density in operational conditions

The performance of gas industries is extensively function of gas properties such as gas density. Due to this importance in the present work, a novel grid partitioning based fuzzy inference system method applied to predict gas density base on pressure, temperature and molecular weight of gas. To this end, the required experimental data are collected from reliable sources. Different comparison scenarios are used to evaluate the ability of model. The coefficients of determination (R²) for training and testing phases are calculated as 0.9985 and 0.9980 respectively. The determined indexes and graphical evaluations show that predicting model can estimate gas density in high degree of accuracy. According to the obtained results, the predicting model can be used as a simple and powerful software in gas industries to predict different processes.     

A mathematical model for assessing the effects of a lot splitting feature on a dynamic cellular manufacturing system

Numerous studies have been carried out in the field of cellular manufacturing systems (CMS) by considering different types of production costs. In all the presented models, it has been assumed that either the production lot of a part type should be processed by only one machine or it can be split among several machines. To the best of our knowledge, there is no research considering the advantages and disadvantages of the lot splitting feature in designing a CMS under a dynamic environment. In this paper, a mixed-integer nonlinear programming model is formulated to design a dynamic CMS by considering the burdened costs of processing part operations, idleness of cells and machines, inter-cell movements, installation/uninstallation of machines, machine overhead, production lost, splitting production lots and dispersing machines among cells. Furthermore, the advantages and disadvantages of the lot splitting feature are investigated by regarding its effect on the burdened costs. After linearization, an illustrative numerical example is solved by GAMS software (CPLEX solver) to illustrate the model performance and analyze the effect of the lot splitting feature. Since the given problem is NP-hard, an efficient simulated annealing algorithm is developed and tested using several test problems.     

Deposition of palladium submonolayer on nanoporous gold film and investigation of its performance for the methanol electrooxidation reaction

The electrocatalytic activity of nanoporous gold film (NPGF) toward methanol oxidation reaction (MOR) upon Pd deposition is studied. Pd_θNPGFs (where, θ stands for the surface coverage of Pd on NPGF: 0.07, 0.19, 0.37 and 0.59) are prepared via surface engineering of NPGF using underpotential deposition (UPD) and galvanic replacement method.     

An immune algorithm for hybrid flow shop scheduling problem with time lags and sequence-dependent setup times

This paper deals with hybrid flow shop scheduling problems considering time lags and sequence-dependent setup times which have wide application in real-world problems. Most of the researches on operations scheduling problems have ignored time lags. A mathematical model is presented which is capable of solving the small size of the considered problem in a reasonable time. Since these problems are strongly NP-hard, a meta-heuristic algorithm based on the immune algorithm is developed. The optimization criterion considered in this paper is the minimization of the makespan. Numerical experiments are used to evaluate the performance and effectiveness of the proposed algorithm. The results of the proposed algorithm are compared with the presented mathematical programming model and a benchmark algorithm. Computational results indicate that the proposed algorithm can produce near-optimal solutions in a short computational time. Moreover, it can be applied easily in real factory conditions and for large-sized problems.     

ZnO Nanoparticles as Ethanol Gas Sensors and the Effective Parameters on Their Performance

<正>ZnO nanoparticles are synthesized and applied as ethanol gas sensors.In some cases,the sensitivity and response time of these particles are shown to be higher than that has been reported in the literature.It has been investigated that the most possible reason for this higher gas sensing performance can be attributed to the quantity of the activity coefficient of its initial components.However,other effects such as pH and thermal decomposition are of importance as well.Specific ion interaction(SIT) model is applied to derive the mean activity coefficient values of the additives used in synthesis of ZnO nanoparticles.