Impact of hydrogen generated by splitting water with nano-silicon and nano-aluminum on diesel engine performance

Efficient utilization of hydrogen generated during the reactions of nano-silicon/water and nano-aluminum/water in internal combustion engine has been investigated in the current work. Engine performance and emission studies of formulated and stabilized nanoemulsion fuels (water in diesel W/D), nano-aluminum in water/diesel (W/DA) and water in nano-silicon/diesel (W/DS) have been compared with those of diesel. Experimental investigations showed reduction in brake specific fuel consumption (BSFC) by 21% and 37%; rise in brake thermal efficiency (BTE) by 16% and 14% when engine was fueled with W/DA and W/DS respectively. For nanoemulsion fuels an increase in induced power was also recorded. Brake mean effective pressure, BTE and NOx emission dropped for W/D due to reduced exhaust gas temperatures. Nevertheless due to elevated peak cylinder pressures and exhaust gas temperatures a marginal rise in NOx, CO, HC and radiative heat emissions was observed with W/DA and W/DS.     

新型空气动力发动机进气门的研究

为实现气动发动机利用外界较高压力空气推动气缸内活塞并对外输出动力,本文设计一种利用电磁装置的新型进气门结构,它结构简单,能够实现对大流量高压气体的流量调节,使其能很好的满足气体发动机的工作要求。     

Integration of Adaptive Neuro Fuzzy Inference Systems and principal component analysis for the control of tertiary scale formation on tinplate at a hot mill

Scale is highly detrimental to surface quality for tinplate products. There are a large number of process variables at a typical hot mill and principal component analysis is a well-known technique for reducing the number of process variables. This paper estimates the principal components associated with the hot mill process variables and puts these through an Adaptive Neuro Fuzzy Inference System (ANFIS) to find those hot mill running conditions that will minimise the amount of scale observed on the bottom of the rolled strip. It was found that the variation observed in all the hot mill process variables could be captured through the use of just six principal components, and that using just three of these in an ANFIS was sufficient to identify those operating conditions leading to coils being produced with a consistently low scale count. Specifically, it was found that the best operating conditions for the hot mill were when the first component was lower than −0.098 the second lower than 0.8058 and the third higher than −0.482. These ranges in turn corresponded to certain hot mill temperatures that depended to some extent on the base chemistry of the incoming slab.     

Robust numerical approach to steady-state calibration of mean-value models

A numerically robust approach to steady-state calibration of nonlinear dynamic models is presented. The approach is based on explicit formulation of the constraints on validity of internal model signals by set of inequalities. The constrained optimization with feasible iterates guarantees that the model will never be evaluated with invalid internal signals. This overcomes numerical difficulties often encountered when dealing with highly nonlinear models. Because the approach uses a large number of slack variables, distributed least squares algorithm is proposed. The robustness of this approach is demonstrated on a steady-state calibration of turbocharged diesel engine model starting from grossly inaccurate initial estimates.     

Z6190Z_LD_K沼气发电机组的研制

本文介绍了由C6190ZL柴油机改制为单一燃料(沼气)发动机,并配置成发电机组的研制开发过程,论述了其结构特点、主要性能以及使用情况等。     

Performance indices of a common rail-system CI engine powered by diesel oil and biofuel blends

Conventional fuels used for supplying internal combustion piston engines include petrols and diesel oils produced from petroleum. These are a non-renewable energy source. The environmental policy of the European Union is geared towards increasing the share of renewable fuels in the overall energy consumption. An alternative fuel originating from a renewable source, which could be used for feeding self-ignition internal combustion engines are the fatty acid methyl esters (FAME) of plant oils. The paper reports selected results of testing a 1.3 MULTIJET SDE 90 PS self-ignition engine with the Common Rail reservoir feed system supplied with mixtures of diesel oil and rape oil fatty acid methyl esters (FAME). Tests were carried out on an engine test bed equipped with an eddy-current brake. The purpose of the tests was to determine the economic–energy and ecological indices of engine operation. The concentrations of exhaust gas gaseous components were measured using a MEXA-1600DEGR analyzer, while the particulate concentrations, with a MEXA-1230PM analyzer. In addition, the variations of working medium pressures in the engine chamber and of fuel pressure upstream the injector were recorded as a function of crankshaft rotation angle using the AVL IndiSmart 612 indication system for this purpose. The physicochemical properties of fuels used in the tests were determined using a fuel analyzer. The obtained testing results made it possible to determine and assess the operation indices of the engine fed with mixtures of diesel oil and rape oil fatty acid methyl esters (FAME) with slightly higher ester contents than the requirements of the currently applicable diesel oil standard.     

Modeling and optimization of biodiesel engine performance using kernel-based extreme learning machine and cuckoo search

This study presents the optimization of biodiesel engine performance that can achieve the goal of fewer emissions, low fuel cost and wide engine operating range. A new biodiesel engine modeling and optimization framework based on extreme learning machine (ELM) is proposed. As an accurate model is required for effective optimization result, kernel-based ELM (K-ELM) is used instead of basic ELM because K-ELM can provide better generalization performance, and the randomness of basic ELM does not occur in K-ELM. By using K-ELM, a biodiesel engine model is first created based on experimental data. Logarithmic transformation of dependent variables is used to alleviate the problems of data scarcity and data exponentiality simultaneously. With the K-ELM engine model, cuckoo search (CS) is then employed to determine the optimal biodiesel ratio. A flexible objective function is designed so that various user-defined constraints can be applied. As an illustrative study, the fuel price in Macau is used to perform the optimization. To verify the modeling and optimization framework, the K-ELM model is compared with a least-squares support vector machine (LS-SVM) model, and the CS optimization result is compared with particle swarm optimization and experimental results. The evaluation result shows that K-ELM can achieve comparable performance to LS-SVM, resulting in a reliable prediction result for optimization. It also shows that the optimization results based on CS is effective.     

Adaptive Neuro-Fuzzy inference system analysis on sorption studies of strontium and cesium cations onto a novel impregnated nano-zeolite

In this research, a novel impregnated nano-zeolite (NAASMS-Z) was synthesized and characterized using different characterization techniques. Excellent properties, such as high specific surface area (~502.77 m²/g), low pore size (~8.92 Å) and the existence of numerous functional groups caused the efficient elimination of Sr²⁺ and Cs⁺ cations from aquatic systems. The sorption performance of the nano-particles was enhanced by impregnation up to 60% in the aquatic media. The kinetic study indicated that the elimination process of both the concerned cations is controlled by external film mass transfer through the boundary within the first 30 min then controlled by intra-particle diffusion. The sorption equilibrium data suggested that the sorption process occurs on the heterogeneous sorbent surface. Parameters affecting the elimination of Sr²⁺ and Cs⁺ from a single metal sorption system, such as pH, initial contaminant concentration (C_i) and contact time (t), were investigated and optimized. A predictive model based on an Adaptive Neuro-Fuzzy Inference system (ANFIS) analysis was applied to evaluate the experimental parameters affecting the elimination of Sr²⁺ and Cs⁺ cations from aquatic system. A Mamdani-type FIS was employed to justify a collection of 16 rules (If-Then format) by means of centroid membership functions. The suggested fuzzy model revealed high predictive concert with high correlation coefficient (R²) and satisfactory deviation from the experimental data, affirming its appropriateness to predict Sr²⁺ and Cs⁺ elimination efficacy from the studied system. Rooted in experimental data and statistical analysis, the synthetized material was effective for treating contaminated aquatic solutions containing Sr²⁺ and Cs⁺ cations.     

Using combustion net torque for estimation of combustion properties from measurements of crankshaft torque

Two methods, both based on the concept of combustion net torque, for estimation of combustion properties using measurements of crankshaft torque data are investigated in this work. The first of the proposed methods estimates entire burned mass fraction traces from corresponding combustion net torque traces. This is done by solving a convex optimization problem that is based on a derived analytical relation between the two quantities. The other proposed estimation method estimates the well established combustion phasing measure referred to as 50% burned mass fraction directly from combustion net torque using a nonlinear black-box mapping. The methods are assessed using both simulations and experimental data gathered from a 5-cylinder light-duty diesel engine equipped with a crankshaft torque sensor and cylinder pressure sensors that are used for reference measurements. The results indicate that both methods work well but the method that estimates entire burned mass fraction traces is more sensitive to torque data quality. Based on the experimental crankshaft torque data, the direct combustion phasing estimation method delivers estimates with a bias of less than 1 CAD and a cycle-to-cycle standard deviation of less than 2.7 CAD for all cylinders.     

Study of antioxidant effect on oxidation stability and emissions in a methyl ester of neem oil fuelled DI diesel engine

Biodiesel as an alternative diesel fuel prepared from vegetable oils or animal fats has attracted more and more attention because of its renewable and environmental-friendly nature. But biodiesel undergoes oxidation and degenerate more quickly than mineral diesel. Further several studies report NO_x emissions increases for biodiesel fuel compared with conventional diesel fuel. In this paper, the experimental investigation of the effect of antioxidant additive (Butylated hydroxytoluene) on oxidation stability and NO_x emissions in a methyl ester of neem oil fuelled direct injection diesel engine has been reported. The antioxidant additive is mixed in various proportions (100–400 ppm) with methyl ester of neem oil. The oxidation stability was tested in Rancimat apparatus and emissions, performance in a computerized 4-stroke water-cooled single cylinder diesel engine of 3.5 kW rated power. Results show that the antioxidant additive is effective in increasing the oxidation stability and in controlling the NO_x emissions of methyl ester of neem oil fuelled diesel engines.