Modeling and Optimization of Performance of Four Stroke Spark Ignition Injector Engine

The performance of an engine whose basic design parameters are known can be predicted with the assistance of simulation programs into the less time, cost and near value of actual. This paper presents a comprehensive mathematical model of the performance parameters of four stroke spark ignition engine. The essence of this research work is to develop a mathematical model for the analysis of engine performance parameters of four stroke spark ignition engine before embarking on full scale construction, this will ensure that only optimal parameters are in the design and development of an engine and also allow to check and develop the design of the engine and it’s operation alternatives in an inexpensive way and less time, instead of using experimental method which requires costly research test beds. To achieve this, equations were derived which describe the performance parameters (sfc, thermal efficiency, mep and A/F). The equations were used to simulate and optimize the engine performance of the model for various engine speeds. The optimal values obtained for the developed bivariate mathematical models are: sfc is 0.2833kg/kwh, efficiency is 28.77% and a/f is 20.75. Keywords: Bivariate models, Engine performance, Injector engine, Optimization, Performance parameters, Simulation, Spark ignitio

Comparison of Multiple Linear and Quadratic Models in Estimating Road Crashes in Semi-Urban Two-Lane Roads: Case Study of Nsukka Municipal Council, South Eastern Nigeria

Road crashes are generally characterized by occurrence without prior notice as well as low or moderate to severe losses in terms of lives and properties. In particular, rural communities in developing countries count huge losses to crash exigencies due to lack of basic infrastructure. It is important that such accident trends which possess special and distinct features from those observed for Urban settlement be carefully studied and modeled for effective mitigation strategies. This paper proposes models that quantitatively assess the effects of various causal factors of crashes in rural roads of developing communities. Taking data from Nsukka municipality, South East Nigeria, it provides two reliable, statistically significant techniques of predicting accident rates on such roads. The results show that although important causal variables like “illiteracy, weather condition, alcohol and drugs” affect road accident, “reckless driving, over speeding, annual average daily traffic, poor road and mechanical faults” were variables that demand more assessment and control in road accident management in the studied location. Further, surface comparison of the developed models based on overall statistical indices suggests that multiple linear accident models are more accurate, though the quadratic accident model is statistically significant. A point by point calculation of deviations shows that the quadratic accident model, apart from its ability to take care of non-linearity effects of independent road accident variables, is actually more accurate than the linear model, except where the quadratic model suffered more numerical instability from the combination of numerical parameters