Reduction of stilling basin length with tall end sill

Experiments were conducted to characterize forced hydraulic jumps in stilling basins for enforced cases due to tail water level or dam site arrangement and construction.The case with a single tall sill was simulated in a horizontal flume downstream of a sluice gate.Results of experiments are compared with the classical hydraulic jump, and significant effect of tall sill on dissipation of energy in shorter distance was confirmed.Furthermore, the generated jumps were classified based on the ratio of sill height to basin length, and a simple design criterion was proposed to estimate the basin length for a desired jump and particular inflow.     

LADPSO: using fuzzy logic to conduct PSO algorithm

Optimization plays a critical role in human modern life. Nowadays, optimization is used in many aspects of human modern life including engineering, medicine, agriculture and economy. Due to the growing number of optimization problems and their growing complexity, we need to improve and develop theoretical and practical optimization methods. Stochastic population based optimization algorithms like genetic algorithms and particle swarm optimization are good candidates for solving complex problems efficiently. Particle swarm optimization (PSO) is an optimization algorithm that has received much attention in recent years. PSO is a simple and computationally inexpensive algorithm inspired by the social behavior of bird flocks and fish schools. However, PSO suffers from premature convergence, especially in high dimensional multi-modal functions. In this paper, a new method for improving PSO has been introduced. The Proposed method which has been named Light Adaptive Particle Swarm Optimization is a novel method that uses a fuzzy control system to conduct the standard algorithm. The suggested method uses two adjunct operators along with the fuzzy system in order to improve the base algorithm on global optimization problems. Our approach is validated using a number of common complex uni-modal/multi-modal benchmark functions and results have been compared with the results of Standard PSO (SPSO2011) and some other methods. The simulation results demonstrate that results of the proposed approach is promising for improving the standard PSO algorithm on global optimization problems and also improving performance of the algorithm.     

Exergy based performance analysis of a solid oxide fuel cell and steam injected gas turbine hybrid power system

This paper presents exergy analysis of a hybrid solid oxide fuel cell and gas turbine (SOFC/GT) system in comparison with retrofitted system with steam injection. It is proposed to use hot gas turbine exhaust gases heat in a heat recovery steam generator to produce steam and inject it into gas turbine. Based on a steady-state model of the processes, exergy flow rates are calculated for all components and a detailed exergy analysis is performed. The components with the highest proportion of irreversibility in the hybrid systems are identified and compared. It is shown that steam injection decreases the wasted exergy from the system exhaust and boosts the exergetic efficiency by 12.11%. Also, 17.87% and 12.31% increase in exergy output and the thermal efficiency, respectively, is demonstrated. A parametric study is also performed for different values of compression pressure ratio, current density and pinch point temperature difference.     

MILP model for emergy optimization in EIP water networks

The eco-industrial park (EIP) concept provides a framework in which several plants can cooperate with each other and exchange their wastewater to minimize total freshwater consumption. Emergy analysis is a methodology that considers the total, cumulative energy which has been consumed within a system; thus, by minimizing emergy, an environmentally optimal EIP can be designed. This article presents a mixed-integer linear programming (MILP) model for minimizing emergy of an interplant water network in an EIP. The methodology accounts for the environmental impacts of water use, energy consumption, and capital goods within the EIP in a balanced manner. The proposed technique is then demonstrated by solving a case study from literature.     

Application of ANFIS-GA as a novel and accurate tool for estimation of interfacial tension of carbon dioxide and hydrocarbon

In the recent years, the enhancement oil recovery processes become the one of the interesting topics in petroleum engineering because of declination of oil reservoirs. One of the most popular processes is the carbon dioxide injection that has special importance because of its environmentally friendly and high efficiency of displacement. The interfacial tension (IFT) between carbon dioxide and hydrocarbon is known as a key parameter in this process so in the present investigation the Adaptive neuro-fuzzy inference system (ANFIS) was coupled with Genetic Algorithm (GA) to create a novel tool for prediction IFT between carbon dioxide and hydrocarbon in terms of temperature, pressure, molecular weight of alkane, gas and liquid densities. The outputs of predicting model were compared with experimental IFT statistically and graphically. The comparisons showed that predicting model has acceptable accuracy in prediction of IFT of hydrocarbon and carbon dioxide.     

Multi-objective optimization of solid oxide fuel cell/gas turbine combined heat and power system: A comparison between particle swarm and genetic algorithms

Many studies have attempted to optimize integrated Solid Oxide Fuel Cell-Gas Turbine (SOFC-GT), although different and somehow conflicting results are reported employing various algorithms. In this study, Multi-Objective Optimization (MOO) is employed to approach the optimal design of SOFC-GT considering all prevailing factors. The emphasis is placed on the evaluation of the Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) performance as two effective approaches for solving the multi-objective and non-linear optimization problems. Multi- objective optimization is carried out on two vital objectives; the electrical efficiency and the overall output power of the system. The considerable achievements are the set of optimal points that aim to identify the system optimal performance which provides a practical basis for the decision-makers to choose the appropriate target functions. For the studied conditions, the two algorithms nearly exhibit similar performance, while the PSO is faster and more efficient in terms of computational effort. The PSO appears to achieve its ultimate parameter values in fewer generations compared to the GA algorithm under the examined circumstances. It is found that the maximum power of 410 kW is accomplished employing the GA optimization method with an efficiency of 64%, while PSO method yields the maximum power of 419.19 kW at the efficiency of 58.9%. The results stress that PSO offers more satisfactory convergence and fidelity of the solution for the SOFC-GT MOO problems.     

Structural investigation of the collapse of the 16‐story Plasco building due to fire

On January 19, 2017, the 16‐story Plasco tower located in Tehran, the capital city of Iran, collapsed in several stages, due to a fire lasting 3.5 h. This paper presents the results of numerical investigations on how the structure behaved during that incident. In this regard, initially, a part of floor system including main truss girders, secondary truss beams, tie beams, and reinforced concrete slab is simulated to study its deformed shape and collapse modes. Then 2D and 3D models of the building are developed to evaluate the global behavior of the structure under fire. The results show that at elevated temperatures, deflection of the floor system, main trusses, and out‐of‐plane bending of the beam‐to‐column gusset plates become excessive, leading to partial collapse of floor, in the location of fire initiation. Also, 2D models show that thermal expansion and catenary action of heated truss induce large lateral displacement and bending moment in perimeter column that cause failure of this column at about 650°C. Finally, 3D models indicate that general collapse of the building is initiated by buckling of the external columns located in the southern perimeter of the building. This result is in good agreement with videos and photos showing actual collapse of the structure.     

Design and analysis of DC gain and transconductance boosted recycling folded cascode OTA

A new technique for improving the transconductance and low frequency output impedance of recycling folded cascode (RFC) amplifiers is presented. This enhancement was achieved by using a positive feedback and upgrading the recycling structure. The new structure profits from better transconductance, slew rate, and DC gain in comparison with conventional folded cascode (FC) amplifier. Moreover, the input referred noise is reduced and the phase-margin improved. The enhanced amplifier, simulated in 0.18 μm CMOS technology, exhibits a DC gain enhancement of 16.3 dB as well as 115.5 MHz increase in gain bandwidth compared to conventional FC configuration. The amplifier consumes 360 μW @ 1.2 V which makes it suitable for low-voltage applications.