Arturo de Risi

Optimization of the Combustion Chamber of Direct Injection Diesel Engines

The optimization procedure adopted in the present investigation is based on Genetic Algorithms (GA) and allows different fitness functions to be simultaneously maximized. The parameters to be optimized are related to the geometric features of the combustion chamber, which ranges of variation are very wide. For all the investigated configurations, bowl volume and squish-to-bowl volume ratio were kept constant so that the compression ratio was the same for all investigated chambers. This condition assures that changes in the emissions were caused by geometric variations only. The spray injection angle was also considered as a variable parameter. The optimization was simultaneously performed for different engine operating conditions, i.e. load and speed, and the corresponding fitness values were weighted according to their occurrence in the European Driving Test. The evaluation phase of the genetic algorithm was performed by simulating the behavior of each chamber with a modified version of the KIVA3V code. The parameters for the sprays and the combustion models were adjusted according to the experimental data of a commercial chamber geometry taken as baseline case. Three fitness functions were defined according to engine emission levels (soot, NOx and HC) and a penalty function was used to account for engine performance. The goal of the optimization process was to select a chamber giving the best compromise of the selected fitness functions. Furthermore, chambers optimizing each single fitness function were also analyzed. The influence of the geometric characteristics on emissions has also been investigated in the paper.

Optimization of High Pressure Common Rail Electro-injector Using Genetic Algorithms

The aim of the present investigation is the implementation of an innovative procedure to optimise the design of a high pressure common rail electroinjector. The optimization method is based on the use of genetic programming, a search procedure developed by John Holland at the University of Michigan. A genetic algorithm (GA) creates a random population which evolves combining the genetic code of the most capable individual of the previous generation. For the present investigation an algorithm which includes the operators of crossover, mutation and elitist reproduction has been developed. This genetic algorithm allows the optimization of both single and multicriteria problems. For the determination of the multi-objective fitness function, the concept of Pareto optimality has been implemented. The performance of the multiobjective genetic algorithm was examined by using appropriate mathematical functions and was compared with the single objective one. The proposed genetic algorithm was used to define the geometrical and dynamic characteristics of high pressure injectors that optimize the injection profile and the time response of the system. As evaluation function for the GA a 1D simulation code of injection systems, already developed and extensively tested by the authors, has been used. The 1D model is based on the concentrated volume method and includes the effect of friction on the dynamics of the movable parts. The conservation equations were integrated by using the characteristic method. The electromagnetic force on the anchor of the injector has been simulated with an empirical function obtained by fitting experimental data. For the optimization the geometrical and dynamical data of a commercial five holes VCO injector were used as baseline case and the best combination of different groups of parameter has been found. The optimized combinations of the investigated parameters were compared with the original values of the commercial injector. Finally a feasibility analysis of the optimized parameters was performed.

A COMBINED OPTIMIZATION METHOD FOR COMMON RAIL DIESEL ENGINES

The optimization method proposed in the present study consists of a multi-objective genetic algorithm combined with an experimental investigation carried out on a test bench, by using a DI Diesel engine. The genetic algorithm selects the injection parameters for each operating condition whereas the output measured by the experimental apparatus determines the fitness in the optimization process. The genetic algorithm creates a random population, which evolves combining the genetic code of the most capable individuals of the previous generation. Each individual of the population is represented by a set of parameters codified with a binary string. The evolution is performed using the operators of crossover, mutation and elitist reproduction. This genetic algorithm allows competitive fitness functions to be optimized with a single optimization process. For the determination of the overall fitness function the concept of Pareto optimality has been implemented. In this work, the input variables used for the optimization method are injection parameters like start of pilot and main injection, injection pressure and duration. The engine used is a FIAT 1929 cc DI diesel engine, in which the traditional injection system has been replaced by a common rail high pressure injection system.The competitive fitness functions were determined based on the measured values of fuel consumption, emissions levels (i.e. NOx, soot, CO, CO2, HC); combustion noise and overall engine noise, for each operating conditions. The optimization was performed for different engine speed and torque conditions typical of the EC driving cycles.

CFD MODELING OF PILOT INJECTION AND EGR IN DI DIESEL ENGINES

The simulation of direct injection diesel engines requires accurate models to predict spray evolution and combustion processes. Several models have been proposed and widely tested for traditional injection strategies characterized by single injection pulse close to top dead center. Unfortunately, these models show some limits when applied to different injection strategies so that a correct simulation of engine performances and emission cannot be achieved without changing variables included in spray and combustion models. The aim of the present investigation is to improve the prediction capability of the KIVA3V code in case of pilot injection in order to use numerical simulations to define optimized pilot injection strategies. This goal was achieved by eliminating the hypotheses of constant fuel density and constant spray angle in the KIVA3V code and by using a modified version of the Shell model. The proposed modifications to the Shell model allow a better description of low temperature kinetics by the addition of two more radicals and three new kinetics reactions. The improvements in the code were verified by comparing experimental data and numerical results over a wide range of operating conditions including single injections, pilot injections and EGR.Copyright

An Experimental Study of High Pressure Nozzles in Consideration of Hole-to-Hole Spray Abnormalities

The present study focuses on the causes of dissimilarity in the flow structures of sprays produced by different holes of the same direct injection high-pressure diesel nozzle. To assess the effect of nozzle geometry on the transient spray structure, photographs of the spray plumes produced by VCO, mini-sac and reduced sac nozzles at different delays from the start of injection were acquired. Injected fuel volume, feeding pressure, injection duration, spray penetration and cone angle were measured for all the investigated nozzles. A statistical analysis of the acquired images and data showed that sprays from the same hole were highly repeatable even with clear hole-to-hole variation of the spray structure. In particular, for the three investigated nozzle geometries the effect of nozzle flow rate, hole inlet and outlet diameter, needle geometry and working time under engine conditions were investigated. Microscope pictures of the nozzle holes were also acquired. Measurements showed that no correlation exists between spray structure and micro-defects in the holes geometry caused by drilling operations in the range of the investigated conditions (injection pressure ranging between 40 and 140 MPa). Whereas a strong dependence on needle dynamics and on the eccentricity between the nozzle and the needle due to asymmetric feeding conditions was observed. A deterioration of the nozzle performances after a fatigue test of about 100 hour running in engine was observed for all the investigated nozzles due to the deposition of carbon particles on the interior wall of the nozzle holes.

A new advanced approach to the design of combustion chambers in diesel engines

An innovative methodology aimed at reducing emissions and improving fuel consumption has been developed for the design of internal combustion engines. The method allows the design of new combustion chambers by means of a fully automated procedure based on computational fluid dynamics (CFD) simulations, genetic algorithms and clustering. Four different engine operating conditions, i.e. load and speed values, were considered in the design of the combustion chamber. The results of the optimisation were used to understand the effect of the five geometrical parameters on the mechanism of formations of soot and NOx by analysing the distribution of temperature and equivalence ratio within the optimised chambers.

A Preliminary Study on the Effect of Low Temperature Kinetics on Engine Modeling

Modeling autoignition in diesel engines is a challenging task because of the wide range of equivalence ratios over which it takes place. A variety of detailed autoignition models has been proposed in literature for different fuels. Since these models include about one thousand chemical reactions and more than one hundred species, their application to CFD engines simulations requires a very high computational time, so that they are of no practical interest. In order to lower the computational time, a number of reduced models has been developed including the shell model, which is one of the most used. This model does not take into account low temperature kinetics and consists of seven reactions and three radicals. The use of this model in engine simulations shows its limits when applied to delayed injections because of the predominant influence of the low temperature kinetics. A modified version of the shell model is proposed in the present study. It includes the effect of low temperature kinetics by the addition of two more radicals and three new kinetics reactions. The model has been implemented in a modified version of the KIVA3V code. The performance of the new kinetic scheme has been investigated by computing the ignition delay at different operating conditions in bomb like simulations. The investigated operating conditions were obtained by changing gas temperature and pressure, air to fuel ratio (i.e., oxygen concentration). The effect of the pre-exponential factor in the rate of production of the intermediate agent has also been investigated. The model has also been applied to predict autoignition of a commercial small bore direct injection diesel engine for different injection timings. Results showed that, for delayed injections, the new model was able to better predict the heat released and the pressure traces. The influence of the modified shell model on engine emissions has also been analyzed. INTRODUCTION In compression ignition engines, the combustion process starts from the autoignition of the fuel-oxygen mixture and the ignition delay has a strong influence on engine performance and pollutant emissions. In fact, the two main parameters characterizing the autoignition process are the initial temperature at which autoignition can develop and the time delay before ignition. The detailed kinetic mechanism of the autoignition process includes about one thousand chemical reactions and over a hundred species. Thus, its application to CFD simulations codes requires high computational times. A group of researchers from Shell Research, Ldt. developed a reduced kinetic scheme introducing generic species with kinetic rate constants deduced from experimental data [1] in order to predict knock in spark ignition engines. This model was modified to assure mass conservation [3] and to adjust kinetic rates to fit experimental data [2]. Theobald [4] applied the shell model to diesel engine autoignition phenomena by modifying the kinetic rate. Since then, the shell model has been widely applied in CFD simulations of diesel engine [5] and has been shown to successfully predict ignition processes happening before top dead center.On the other hand, this reduced scheme fails to predict both the ignition delay and the pressure rate of change in the case of delayed injections. This reveals that the shell model does not adequately describe the ignition phenomena which take place at low temperatures. To improve the prediction capability of the model, Cox et al. [6] and Hu et al [7] increased the number of reactions introducing the chemistry controlling the hydrocarbon oxidation process at low temperatures. But the main advantage of the shell model is the low number of species and reactions, which makes this model suitable for CFD applications. Thus, improvements should not substantially increase the complexity of the model. To achieve this twofold goal (i.e., a simple scheme able to predict low temperature hydrocarbon ignition) Gaballo [8] developed a modified version of the shell model by adding two more species and three kinetic reactions. In the present investigation, this modified version of shell model has been implemented in the KIVA3V code [11] and its capability to predict the low temperature autoignition process has been checked. Experimental data from a small bore direct injection diesel engine have been used for comparison. Moreover, the numerical pressure traces obtained with the modified version of the shell model have been compared with the results of the original shell model and the effect of the low temperature chemistry on the soot and NOx engine emissions has been also investigated.

Experimental Measurements of Al2O3 and CuO Nanofluids Interaction with Microwaves

AbstractNanofluids belong to a new generation of heat transfer fluids. Their thermal properties make them suitable to be employed in high-performance energy systems. In this paper a new setup for investigating the interactions between microwaves and nanofluids is presented. This is a new issue in this field and only one other experimental campaign has been carried out in the scientific world so far. The design of this experimental setup together with the preliminary results on two different water-based nanofluids (Al2O3 and CuO nanofluids) opens a new frontier in the field of heat transfer in nanofluids.

Surface Plasmon Resonance Optical Sensors for Engine Oil Monitoring

Lubricant systems are fundamental in engines (automotive, aviation, rail etc.) and in any industrial system where surfaces of moving mechanical parts are in contact. An improper lubrication due to oil degradation over a long period of time can lead to unwanted component failure and increased maintenance costs. Present study, unlike methods developed until now for detecting oil degradation (loss of mechanical, physical, chemical and optical properties) focuses on the development of a Surface Plasmon Resonance (SPR) transduction methodology able to measure lubricant degradation in real time observing the change in the refractive index. This approach answers to environmental regulation and user requirements on performance, lifetime expectancy and engine efficiency.

Performance Optimization of Building Integrated-Mounted Wind Turbine

Building integrated-mounted wind turbine (BUWT) is one of the most promising renewable energy devices. However, this renewable energy technology is not fully spread principally due to two factors such as uncertainty in the prediction of wind velocity and high turbulence intensity around the building. In this work, the Taguchi method and the analysis of variance (ANOVA) on a horizontal-axis wind turbine has been applied, to study the influence of geometrical parameters such as building depth, width and height, as well as turbine position on the roof and turbine height. To evaluate the above-cited effects, the airflow around an isolated building of parametrical dimension has been simulated using a Computation Fluid Dynamic (CFD) code calibrated against experimental data in a previous paper from the authors. The results reported in the present paper outline the relative effects of the main building geometrical parameters on the performance of a rooftop installed wind turbine and establish basic guidelines for the optimal location of such turbines.