Application of Swarm Intelligence and Evolutionary Computation Algorithms for Optimal Reservoir Operation

Water Resources Management - Real-world problems often contain complex structures and various variables, and classical optimization techniques may face difficulties finding optimal solutions....     

Deployment optimization of software objects by design-level delay estimation

The quantitative performance evaluation of different deployments of distributed software objects over computational nodes is one of the main activities during the early stages of the design phase and should be supported by automated tools. The important design decision is to finding the optimal placement of objects, from the performance viewpoint, for different input workloads. Each deployment of objects may impose two kinds of delay on the overall performance of the software: first, the communicational delay due to the remote invocations among distributed objects and second, the computational delay due to the resource sharing by two or more concurrently executing object invocations. The object deployment problem can be formulated as an optimization problem to find the optimal deployment for which the total delay is minimal. In this paper an analytical model for delay prediction of object deployments considering the input workload of the software is presented. This model applies the object-oriented load metrics such as object population and object utilization to estimate the total amount of delay corresponding to a given object deployment. To achieve this, a novel method, called delay propagation, is proposed to compute the amount of delay corresponding to each method invocation which affects the overall response time of the software. In order to verify the proposed analytical delay predictor model, a statistical regression-based method is used. Moreover, by comparing the proposed method with the existing deployment optimization methods, which apply the Layered Queueing Networks to evaluate the performance of each deployment in the search space, a significant improvement in efficiency is observed due to the fast evaluation of each deployment instance in the search space.     

Reliability assessment of a stand-alone wind-hydrogen energy conversion system based on thermal analysis

Due to the stochastic behavior of the wind speed, accessing the wind energy would be problematic in some critical moments. One feasible solution lies in the use of wind turbines to produce hydrogen through an electrolyzer and by using wind-hydrogen hybrid systems. However, many of the issues related to these systems should be investigated to make landmark decisions about their performance. For instance, there is a lack of study on the reliability assessment of the wind-hydrogen systems; for this purpose, the main objective of this study is to evaluate the reliability of a stand-alone wind-hydrogen energy conversion system unconnected to the grid. The proposed system consists of two major parts: the rectifier and the buck converter. The primary task of the rectifier is to rectify the wind turbine output voltage to a constant DC voltage. Additionally, the buck converter is responsible to reduce the voltage level to a 48 V voltage, which meets the voltage requirement of the 3.6 kW electrolyzer. The results of the performed simulations showed that the rectifier is under more thermal stresses than the buck converter. The predicted mean time to failure (MTTF) of the hybrid system is approximately 7.6 years, and this estimation can affect the maintenance and refurbishment costs.     

The Enhanced Honey-Bee Mating Optimization Algorithm for Water Resources Optimization

Evolutionary and meta-heuristic algorithms are widely used to solve water resources optimization problems. In this context, the honey bee mating optimization (HBMO) algorithm, inspired by the mating ritual of honey bees, is a reliable and efficient algorithm. The HBMO algorithm is modified in this work leading to the Enhanced HBMO (EHBMO) algorithm. The EHBMO is then applied to solve several unconstrained/constrained mathematical benchmark functions and a multi-reservoir problem. The performance of the EHBMO is compared with those of the elitist genetic algorithm (EGA) and the HBMO algorithm. The results show that the EHBMO achieves a better solution in a smaller number of functional evaluations and with less variance of results about global optima in comparison with the EGA and the HBMO algorithm.     

The effect of TiO2 additive on sinterability and properties of SiC-Al2O3-Y2O3 composite system

In the current research, the effects of TiO₂ additive on mechanical and physical properties of SiC bodies, sintered by liquid phase methods were investigated. Al₂O₃ and Y₂O₃ were used as sintering-aids (10?wt% in total) with an Al₂O₃/Y₂O₃ ratio of 43/57 to provide liquid phase during Sintering. TiO₂ was also used as the oxide additive with an amount ranging from 0 to 10?wt%. After scaling and mixing the starting materials by a planetary mill, the obtained slurry was dried at 100?℃ for four hours. The derived powders were finally pressed under a pressure of 90?MPa. The samples were then pyrolyzed and sintered at 600?℃ and 1900?℃, respectively under argon atmosphere for 1.5?h. Phase analysis showed no trace of TiO₂ after the sintering process, demonstrating the complete TiO₂ to TiC transformation. The results showed that an increase in TiO₂ content up to 5?wt%, led an improvement in all the measured properties including the relative density, hardness, Young's modulus, bending strength, indentation fracture resistance and the brittleness factor, reaching to 96.2%, 24.4?GPa, 395.8?GPa, 521?MPa, 5.8?MPa?m^1/2 and 286.5?×?10^?6 m^?1, respectively. However more than 5?wt% additive resulted in a decrease in all the above-mentioned properties. Microstructural studies demonstrated that crack deflection and crack bridging were the major mechanisms responsible for an increase in the indentation fracture resistance.     

Thermal Integration of Sulfuric Acid and Continuous Catalyst Regeneration of Naphtha Reforming Plants

An optimal reactor design is proposed that simultaneously improves the naphtha reforming reactor performance and increases sulfur trioxide production. In this new configuration, the naphtha reforming process as an endothermic reaction is coupled with the oxidation reaction of sulfur dioxide, which is an exothermic reaction. The differential evolution optimization technique is applied to maximize the produced amounts and yields of aromatics and hydrogen. The results obtained with the optimized thermally coupled reactor are compared with those of the conventional and thermally coupled reactors, proving the superiority of the proposed configuration.     

Multi Objective Optimization with a New Evolutionary Algorithm

Various objectives are mainly met through decision making in real world. Achieving desirable condition for all objectives simultaneously is a necessity for conflicting objectives. This concept is called multi objective optimization widely used nowadays. In this study, a new algorithm, comprehensive evolutionary algorithm (CEA), is developed based on general concepts of evolutionary algorithms that can be applied for single or multi objective problems with a fixed structure. CEA is validated through solving several mathematical multi objective problems and the obtained results are compared with the results of the non-dominated sorting genetic algorithm II (NSGA-II). Also, CEA is applied for solving a reservoir operation management problem. Comparisons show that CEA has a desirable performance in multi objective problems. The decision space is accurately assessed by CEA in considered problems and the obtained solutions’ set has a great extent in the objective space of each problem. Also, CEA obtains more number of solutions on the Pareto than NSGA-II for each considered problem. Although the total run time of CEA is longer than NSGA-II, solution set obtained by CEA is about 32, 4.4 and 1.6% closer to the optimum results in comparison with NSGA-II in the first, second and third mathematical problem, respectively. It shows the high reliability of CEA’s results in solving multi objective problems.     

The effect of oxide,carbide, nitride and boride additives on properties of pressureless sintered SiC: A review

Properties such as high hardness, low density, and high elastic modulus have made SiC ceramics proper choices for a variety of industrial applications. However, disadvantages such as low sinterability, and low fracture toughness have limited the fabrication of these ceramics. Past researches show that the use of Al₂O₃-Y₂O₃ additives play an important role in improving the sinterability and the properties of the composites. The use of oxide, carbide, nitride and boride additives results in improved sinterability, physical and mechanical properties. The investigations show that the microstructure, porosities, amount of additives, reaction of additives with the matrix, grain size and, finally, the sintering temperature are the most important factors affecting the properties of SiC ceramics. In this paper, the effect of using various additives, the sintering temperature and the annealing heat treatment on sinterability, microstructure and properties of the SiC matrix composites fabricated by pressureless sintering method have been investigated.     

Fluidization Behavior of Cohesive Ca(OH)2 Powders Mixed with Hydrophobic Silica Nanoparticles

Dry mixing with hydrophobic silica nanopowders was used to improve the fluidization quality of Ca(OH)₂ particles which belong to the Geldart C group and, thus, normally cannot be fluidized. Three parameters, i.e., sieved size of Ca(OH)₂ particles and sieved size and weight percentage of SiO₂ nanoparticles were selected for experiments. A direct proportionality was found between the coverage quality of materials over each other and the fluidization behavior of their corresponding adsorbents. Optimum SiO₂ size and concentration values were determined for the improvement of Ca(OH)₂ fluidizability. The sieved size of Ca(OH)₂ powder had no consequential effect on the coverage quality. The Richarson‐Zaki equation and fractal analysis combined with a modified Richardson‐Zaki approach were proposed for prediction of the fluidization quality and agglomerate size.