Modellazione e simulazione di sistemi meccanici ad elevato numero di gradi di libertà mediante metodi non convenzionali e sistemi CAD

Recent developments in piston engine technology have increased performance in a very significant way. Diesel turbocharged/turbo compound engines, fuelled by jet fuels, have great performances. The focal point of this thesis is the transformation of the FIAT 1900 jtd diesel common rail engine for the installation on general aviation aircrafts like the CESSNA 172. All considerations about the diesel engine are supported by the studies that have taken place in the laboratories of the II Faculty of Engineering in Forlì. This work, mostly experimental, concerns the transformation of the automotive FIAT 1900 jtd – 4 cylinders – turbocharged – diesel common rail into an aircraft engine. The design philosophy of the aluminium alloy basement of the spark ignition engine have been transferred to the diesel version while the pistons and the head of the FIAT 1900 jtd are kept in the aircraft engine. Different solutions have been examined in this work. A first V 90° cylinders version that can develop up to 300 CV and whose weight is 30 kg, without auxiliaries and turbocharging group. The second version is a development of e original version of the diesel 1900 cc engine with an optimized crankshaft, that employ a special steel, 300M, and that is verified for the aircraft requirements. Another version with an augmented stroke and with a total displacement of 2500 cc has been examined; the result is a 30% engine heavier. The last version proposed is a 1600 cc diesel engine that work at 5000 rpm, with a reduced stroke and capable of more than 200 CV; it was inspired to the Yamaha R1 motorcycle engine. The diesel aircraft engine design keeps the bore of 82 mm, while the stroke is reduced to 64.6 mm, so the engine size is reduced along with weight. The basement weight, in GD AlSi 9 MgMn alloy, is 8,5 kg. Crankshaft, rods and accessories have been redesigned to comply to aircraft standards. The result is that the overall size is increased of only the 8% when referred to the Yamaha engine spark ignition version, while the basement weight increases of 53 %, even if the bore of the diesel version is 11% lager. The original FIAT 1900 jtd piston has been slightly modified with the combustion chamber reworked to the compression ratio of 15:1. The material adopted for the piston is the aluminium alloy A390.0-T5 commonly used in the automotive field. The piston weight is 0,5 kg for the diesel engine. The crankshaft is verified to torsional vibrations according to the Lloyd register of shipping requirements. The 300M special steel crankshaft total weight is of 14,5 kg. The result reached is a very small and light engine that may be certified for general aviation: the engine weight, without the supercharger, air inlet assembly, auxiliary generators and high pressure body, is 44,7 kg and the total engine weight, with enlightened HP pump body and the titanium alloy turbocharger is less than 100 kg, the total displacement is 1365 cm3 and the estimated output power is 220 CV. The direct conversion of automotive piston engine to aircrafts pays too huge weight penalties. In fact the main aircraft requirement is to optimize the power to weight ratio in order to obtain compact and fast engines for aeronautical use: this 1600 common rail diesel engine version demonstrates that these results can be reached.

Sviluppo di algoritmi di RCP per la stima della coppia indicata erogata da un motore a combustione interna.

Combustion control is one of the key factors to obtain better performances and lower pollutant emissions for diesel, spark ignition and HCCI engines. An algorithm that allows estimating, as an example, the mean indicated torque for each cylinder, could be easily used in control strategies, in order to carry out cylinders trade-off, control the cycle to cycle variation, or detect misfires. A tool that allows evaluating the 50% of Mass Fraction Burned (MFB50), or the net Cumulative Heat Release (CHRNET), or the ROHR peak value (Rate of Heat Release), could be used to optimize spark advance or to detect knock in gasoline engines and to optimize injection pattern in diesel engines. Modern management systems are based on the control of the mean indicated torque produced by the engine: they need a real or virtual sensor in order to compare the measured value with the target one. Many studies have been performed in order to obtain an accurate and reliable over time torque estimation. The aim of this PhD activity was to develop two different algorithms: the first one is based on the instantaneous engine speed fluctuations measurement. The speed signal is picked up directly from the sensor facing the toothed wheel mounted on the engine for other control purposes. The engine speed fluctuation amplitudes depend on the combustion and on the amount of torque delivered by each cylinder. The second algorithm processes in-cylinder pressure signals in the angular domain. In this case a crankshaft encoder is not necessary, because the angular reference can be obtained using a standard sensor wheel. The results obtained with these two methodologies are compared in order to evaluate which one is suitable for on board applications, depending on the accuracy required.

Nondestructive evaluation of concrete compression strength by means of Artificial Neural Network (ANN)

The evaluation of structural performance of existing concrete buildings, built according to standards and materials quite different to those available today, requires procedures and methods able to cover lack of data about mechanical material properties and reinforcement detailing. To this end detailed inspections and test on materials are required. As a consequence tests on drilled cores are required; on the other end, it is stated that non-destructive testing (NDT) cannot be used as the only mean to get structural information, but can be used in conjunction with destructive testing (DT) by a representative correlation between DT and NDT. The aim of this study is to verify the accuracy of some formulas of correlation available in literature between measured parameters, i.e. rebound index, ultrasonic pulse velocity and compressive strength (SonReb Method). To this end a relevant number of DT and NDT tests has been performed on many school buildings located in Cesena (Italy). The above relationships have been assessed on site correlating NDT results to strength of core drilled in adjacent locations. Nevertheless, concrete compressive strength assessed by means of NDT methods and evaluated with correlation formulas has the advantage of being able to be implemented and used for future applications in a much more simple way than other methods, even if its accuracy is strictly limited to the analysis of concretes having the same characteristics as those used for their calibration. This limitation warranted a search for a different evaluation method for the non-destructive parameters obtained on site. To this aim, the methodology of neural identification of compressive strength is presented. Artificial Neural Network (ANN) suitable for the specific analysis were chosen taking into account the development presented in the literature in this field. The networks were trained and tested in order to detect a more reliable strength identification methodology.