Optimal seismic design of steel structures by an efficient soft computing based algorithm

The main aim of this study is to propose advanced soft computing techniques for the optimal seismic design of real steel structures subjected to natural ground motion records. For the solution of the optimization problem an efficient combination of the particle swarm optimization (PSO) and adaptive virtual sub-population (AVSP) algorithms is proposed. Also an efficient combination of the adaptive neuro-fuzzy inference system (ANFIS), wavelet transforms (WT) and radial basis function (RBF) neural networks, termed as fuzzy wavelet radial basis function (FWRBF), is proposed to accurately predict the structural responses. The numerical results demonstrate the computational advantages of the proposed methodology.     

斯特林发动机在分布式能源系统的应用

斯特林发动机是分布式能源系统中一种重要的能源转化装置。介绍了斯特林发动机的结构、工作过程及优缺点,分析了它在分布式能源系统中的应用,探讨了斯特林发动机的关键技术。     

基于ArcGIS的基础地理空间数据库系统设计

针对地理空间信息特点,在空间数据库技术支持下,结合最新的GIS和网络技术,采用ArcSDE空间数据引擎和Oracle数据库统一管理空间和属性数据,利用ArcEngine组件和Visual C＋＋技术实现了基础地理空间数据库管理系统的建设。     

发动机研发测试间的通风空调设计

介绍了某技术研发中心项目内的四个发动机研发测试间的通风空调设计,重点阐述了四季变化时测试间的空调控制方法,以及噪声控制措施,并总结了设计经验教训,对存在的问题进行剖析,从而达到既满足设计要求又节能的目的。     

基于MC9S12DG256的发动机电控系统硬件设计

介绍了一种基于Freescale公司16位高性能控制芯片MC9S12DG256的汽油机电控系统硬件设计方案,主要包括传感器及处理电路、微控制器和执行器及处理电路三大部分,以促进发动机电控系统的研究。     

Performance of a twin cylinder dual-fuel diesel engine using blends of neat Karanja oil and producer gas

In the present study, performance and emission analysis are done in a twin cylinder four-stroke dual-fuel diesel engine in two cases of operation. In the first case, the engine is tested using diesel, K10 (10% neat oil+90% diesel) and K20 (20% neat oil+80% diesel) in single mode and in the dual-fuel mode with an optimum producer gas flow rate of 21.49 kg/h under different load conditions. In the second case, the engine is tested using the same test fuels in the dual-fuel mode at different gas flow rates under a constant load of 10 kW. The study reveals that the dual-fuel operation of all test fuels shows a lower engine performance and better control of smoke and oxide of nitrogen emission compared with their single-mode operation under all load conditions. Whereas other emission parameters such as carbon monoxide, carbon dioxide and hydrocarbon are at a higher level.     

Combustion characteristics of the direct injection diesel engine fuelled with corn oil methyl ester

Petroleum-based fuels is a finite resource that is rapidly depleting. Consequently, petroleum reserves are not sufficient enough to last many years. In this research, an experimental investigation has been performed to give insight into the potential of biodiesel as an alternative fuel for direct injection (DI) diesel engines. The experimental work has been carried out to estimate the combustion characteristics of a single-cylinder, four-stroke, DI diesel engine fuelled with corn oil methyl ester (COME) and diesel blends. The COME was preheated to temperatures namely 50°C, 70°C and 90°C before it was supplied to the engine. The optimised preheated temperature of 70°C was chosen based on the higher brake thermal efficiency and lower specific fuel consumption. The performance, emission and combustion characteristics are evaluated by running the engine with COME and diesel blends at this preheated temperature. In this paper, the combustion characteristics are only discussed. The combustion characteristics such as ignition delay, maximum rate of pressure, heat release rate, cumulative heat release rate, mass fraction burned and combustion duration of COME methyl ester and diesel were evaluated and compared with neat diesel. The rate of pressure rise and maximum combustion pressure inside the cylinder were high for COME blends compared with neat diesel. The heat release rate of diesel is higher compared with COME blends. The ignition delay and combustion duration are decreased for COME blends compared with neat diesel. The cumulative heat release rate and mass fraction burnt of COME blends are higher than neat diesel.     

A neural network model for the prediction of compression ignition engine performance at different injection timings

Rapid depletion of fossil fuel and continuous increase in gasoline prices have stimulated the search of alternative fuels. This paper deals with the prediction of engine performance, emission and combustion characteristics of compression ignition engine fuelled with fish oil biodiesel using artificial neural network (ANN). Experimental investigations are carried out in a single cylinder constant speed direct injection diesel engine under variable load conditions at different injection timings?21⁰, 24⁰ and 27⁰ bTDC. The performance, combustion and emission characteristics are measured using an exhaust gas analyser, smoke meter, piezoelectric pressure transducer and crank angle encoder for different fuel blends and engine load conditions. For training the neural network, feed-forward back propagation algorithm is used. The developed ANN model predicts the performance, combustions and exhaust emissions with a correlation coefficients (R) of 0.97–0.99 and a mean relative error of 0.62–4.826%. The root mean square errors are found to be low. The developed model has found to predict accurately the engine performance, combustion and emission parameters at different injection timings.     

Combustion analysis of Jatropha methyl esters and Pongamia methyl esters with the addition of ethanol as fuel in a diesel engine

The aim of our project is to experimentally access the practical applications of ethanol and blending it with some lubricating oils in a direct injection compression ignition engine. This replacement of conventional diesel with ethanol requires some of the properties of ethanol to be altered. In order to increase the lubricating property of ethanol, it is blended with some lubricating oils. Some of the preferred lubricating oils are methyl esters of Jatropha oil, Pongamia oil, etc. Ethanol is blended with these lubricating oils to reduce the corrosive property of ethanol. The different fuel blends [Pongamia–ethanol (50–50) and Jatropha–ethanol (50–50)] are used in the direct injection CI engine, the combustion characteristics are calculated and they are compared with diesel and a perfect blend is analysed. The engine combustion parameters such as peak pressure, heat release rate (HRR) and cumulative heat release rate were computed. The combustion analysis revealed that the early rate of pressure rise causes the cylinder pressure to rise early in the case of alternate fuels with a resulting lower rate of pressure rise and peak pressure. However, HRR and cumulative HRR show a maximum for Pongamia–ethanol (50–50) when compared with the neat diesel fuel.     

Experimental investigation of compression ignition engine fuelled by a catalytic fuel reformer

Waste engine oil (WEO) as an alternative fuel for compression ignition (CI) engine is investigated in this study. WEO was thermally cracked with alumina catalyst in the catalytic fuel reformer (CFR). The gas obtained from the CFR was condensed using a water-cooled condenser for analytical purposes. The output of the condenser was named as WEOA (reformulated WEO with alumina catalyst). The different chemical properties of WEOA were analysed. The compositional analysis for diesel and WEOA was made using Fourier transform infra-red (FT-IR) and gas chromatography–mass spectrometer (GC–MS). The experimental investigation was conducted in a single-cylinder diesel engine and the performance and emissions were compared with those of diesel fuel. Experimental results concluded that the performance and emission level are better than those of diesel fuel. This study concludes that environmentally hazardous waste material such as WEO is recycled and converted into a useful resource and serves as an alternative source of fuel for CI engine.