Swallow swarm optimization algorithm: a new method to optimization

This paper presents an exposition of a new method of swarm intelligence–based algorithm for optimization. Modeling swallow swarm movement and their other behavior, this optimization method represents a new optimization method. There are three kinds of particles in this method: explorer particles, aimless particles, and leader particles. Each particle has a personal feature but all of them have a central colony of flying. Each particle exhibits an intelligent behavior and, perpetually, explores its surroundings with an adaptive radius. The situations of neighbor particles, local leader, and public leader are considered, and a move is made then. Swallow swarm optimization algorithm has proved high efficiency, such as fast move in flat areas (areas that there is no hope to find food and, derivation is equal to zero), not getting stuck in local extremum points, high convergence speed, and intelligent participation in the different groups of particles. SSO algorithm has been tested by 19 benchmark functions. It achieved good results in multimodal, rotated and shifted functions. Results of this method have been compared to standard PSO, FSO algorithm, and ten different kinds of PSO.     

Predication of concrete mix design using adaptive neural fuzzy inference systems and fuzzy inference systems

The aim of this study is to design adaptive neural-fuzzy inference system (ANFIS) model and fuzzy expert system for determination of concrete mix designs and finally compare their results. Idea of these systems based on two surveys: first, ACI structures and principles, second a concrete mix designs dataset that collected via Prof. I-Cheng Yeh. Datasets that loaded in to ANFIS has 552 mix designs and based on ACI mix designs. Moreover, in this study, we have designed fuzzy expert system. Input fields of fuzzy expert system are Slump, Maximum Size of Aggregate (D _max), Concrete Compressive Strength (CCS), and Fineness Modulus. Output fields are quantities of water, cement, fine aggregate (F.A.) and coarse aggregate (C.A.). In the ANFIS model, we have four layers (four ANFIS models): the first layer takes values of D _max and Slump and then determines the quantity of Water, the second layer takes values of Water (computed in the past layer) and CCS then measures the value of Cement, the third layer takes values of D _max and Slump to compute C.A. and the fourth layer takes values of Water, Cement, and C.A. (determined in past layers) and then measures the value of F.A. When these systems were designed and tested, comparison between two systems (FIS and ANFIS) results showed that results of ANFIS model are better than fuzzy expert system’s results. In the ANFIS model, for Water output field, training and average testing errors are 0.86 and 0.8. For cement field, training error and average testing error are in the orders of 0.21 and 0.22. Training and average testing error of C.A. are in the orders of 0.0001 and 0.0004 and finally, training and average testing errors of F.A. are in the orders of 0.0049 and 0.0063. Results of fuzzy expert system in comparison to ACI results follow average errors: average error of Water, Cement, C.A., and F.A. are in the orders of 9.5%, 27.6%, 96.5%, and 49%.     

Volume Expansion of Compacted Graphite Iron Induced by Pearlite Decomposition and the Effect of Oxidation at Elevated Temperature

Engine cylinder blocks and heads, made of compacted graphite iron, are subjected to prolonged periods of cyclic heating and cooling. These conditions may give rise to the decomposition of the pearlite matrix accompanied by the formation of lower-density graphite and oxides, which will lead to an increase of material volume. The microstructural instability deteriorates the physical and mechanical properties of CGI and accordingly the thermal fatigue properties. In the present work it was shown that the extent and mechanism of volume change are drastically affected by the presence of an oxide atmosphere. It was found that after annealing under atmospheric conditions internal oxidation largely inhibited the progress of pearlite decomposition and therefore much smaller growth rates were obtained as compared to those observed under vacuum conditions in the dilatometer. After 16 h of annealing time at 700 °C in vacuum, the CGI samples exhibited 6 times faster growth kinetics as compared to annealing in open atmosphere.     

Modeling and fuzzy control of the engine coolant conditioning system in an IC engine test bed

Mechanical and thermodynamical performance of internal combustion engines is significantly affected by the engine working temperature. In an engine test bed, the internal combustion engines are tested in different operating conditions using a dynamometer. It is required that the engine temperature be controlled precisely, particularly in transient states. This precise control can be achieved by an engine coolant conditioning system mainly consisting of a heat exchanger, a control valve, and a controller. In this study, constitutive equations of the system are derived first. These differential equations show the second-order nonlinear time-varying dynamics of the system. The model is validated with the experimental data providing satisfactory results. After presenting the dynamic equations of the system, a fuzzy controller is designed based on our prior knowledge of the system. The fuzzy rules and the membership functions are derived by a trial and error and heuristic method. Because of the nonlinear nature of the system the fuzzy rules are set to satisfy the requirements of the temperature control for different operating conditions of the engine. The performance of the fuzzy controller is compared with a PI one for different transient conditions. The results of the simulation show the better performance of the fuzzy controller. The main advantages of the fuzzy controller are the shorter settling time, smaller overshoot, and improved performance especially in the transient states of the system.     

Solvent-Induced Formation of Novel Ni(II) Complexes Derived from Bis-Thiosemicarbazone Ligand: An Insight from Experimental and Theoretical Investigations

In this work, we report solvent-induced complexation properties of a new N₂S₂ tetradentate bis-thiosemicarbazone ligand (H₂L^I), prepared by the condensation of 4-phenylthiosemicarbazide with bis-aldehyde, namely 2,2’-(ethane-1,2-diylbis(oxy)dibenzaldehyde, towards nickel(II). Using ethanol as a reaction medium allowed the isolation of a discrete mononuclear homoleptic complex [NiL^I] (1), for which its crystal structure contains three independent molecules, namely 1-I, 1-II, and 1-III, in the asymmetric unit. The doubly deprotonated ligand L^I in the structure of 1 is coordinated in a cis-manner through the azomethine nitrogen atoms and the thiocarbonyl sulfur atoms. The coordination geometry around metal centers in all the three crystallographically independent molecules of 1 is best described as the seesaw structure. Interestingly, using methanol as a reaction medium in the same synthesis allowed for the isolation of a discrete mononuclear homoleptic complex [Ni(L^II)₂] (2), where L^II is a monodeprotonated ligand 2-(2-(2-(2-(dimethoxymethyl)phenoxy)ethoxy)benzylidene)-N-phenylhydrazine-1-carbothioamide (HL^II). The ligand L^II was formed in situ from the reaction of L^I with methanol upon coordination to the metal center under synthetic conditions. In the structure of 2, two ligands L^II are coordinated in a trans-manner through the azomethine nitrogen atom and the thiocarbonyl sulfur atom, also yielding a seesaw coordination geometry around the metal center. The charge and energy decomposition scheme ETS-NOCV allows for the conclusion that both structures are stabilized by a bunch of London dispersion-driven intermolecular interactions, including predominantly N–H∙∙∙S and N–H∙∙∙O hydrogen bonds in 1 and 2, respectively; they are further augmented by less typical C–H∙∙∙X (where X = S, N, O, π), CH∙∙∙HC, π∙∙∙π stacking and the most striking, attractive long-range intermolecular C–H∙∙∙Ni preagostic interactions. The latter are found to be determined by both stabilizing Coulomb forces and an exchange-correlation contribution as revealed by the IQA energy decomposition scheme. Interestingly, the analogous long-range C–H∙∙∙S interactions are characterized by a repulsive Coulomb contribution and the prevailing attractive exchange-correlation constituent. The electron density of the delocalized bonds (EDDB) method shows that the nickel(II) atom shares only ~0.8|e| due to the σ-conjugation with the adjacent in-plane atoms, demonstrating a very weak σ-metalloaromatic character.     

EPB tunneling challenges in bouldery ground: a new experience on the Tabriz metro line 1, Iran

Underground construction of the Tabriz metro line 1 involved boring twin tunnels with two earth pressure balance machines in alluvial deposits. Although this type of machine is recommended for excavation in fine soils, its performance was evaluated in this project where part of the ground consists of alluvial deposits with particle size ranging from silt to boulder and even rock blocks. It was found that the tunnel boring machine (TBM) performance was highly reduced due to the variation in ground conditions. Many types of problem were observed during the excavation in coarse grained alluvial deposits including high cutter-head torque, excessive wear of tools, breaking of TBM parts and ground instabilities in the form of large settlement and ground collapse. A trial effort was implanted to stabilize the overburden ground by the injection of cement grout, but this proved to be unsuccessful. In both cases, the excavation operation was delayed. With the experience gained from the excavation of the first tunnel and use of foam with a high foam expansion ratio as a soil conditioner in closed mode, the performance of the TBM in the second tunnel improved.     

The Raw microprocessor: a computational fabric for software circuits and general-purpose programs

Wire delay is emerging as the natural limiter to microprocessor scalability. A new architectural approach could solve this problem, as well as deliver unprecedented performance, energy efficiency and cost effectiveness. The Raw microprocessor research prototype uses a scalable instruction set architecture to attack the emerging wire-delay problem by providing a parallel, software interface to the gate, wire and pin resources of the chip. An architecture that has direct, first-class analogs to all of these physical resources will ultimately let programmers achieve the maximum amount of performance and energy efficiency in the face of wire delay.     

Artificial fish swarm algorithm: a survey of the state-of-the-art,hybridization, combinatorial and indicative applications

AFSA (artificial fish-swarm algorithm) is one of the best methods of optimization among the swarm intelligence algorithms. This algorithm is inspired by the collective movement of the fish and their various social behaviors. Based on a series of instinctive behaviors, the fish always try to maintain their colonies and accordingly demonstrate intelligent behaviors. Searching for food, immigration and dealing with dangers all happen in a social form and interactions between all fish in a group will result in an intelligent social behavior.This algorithm has many advantages including high convergence speed, flexibility, fault tolerance and high accuracy. This paper is a review of AFSA algorithm and describes the evolution of this algorithm along with all improvements, its combination with various methods as well as its applications. There are many optimization methods which have a affinity with this method and the result of this combination will improve the performance of this method. Its disadvantages include high time complexity, lack of balance between global and local search, in addition to lack of benefiting from the experiences of group members for the next movements.