Abstract
The enhancement of the early design stages, in the production of aeronautical engines, has been shown decisive, for developing efficient and reliable final products. Nevertheless, in most of industrial engineering design problems, the amount of design variables is large. Moreover, several nonlinearities characterize the behaviour of the physical phenomena involved and the derivatives are seldom known for all the functions. Besides, objective functions exhibit several local extremes, whereas the designer as well as the practitioner is usually interested in the global one. In this context, stochastic and evolutionary optimization have been shown capable to provide reliable solutions while keeping the computational cost at a reasonable level. Existing tools for the design and optimization of engine components deal with the optimal and detailed design of specific engine components, thus requiring several computational time and efforts to gain optimized design parameters. Hence, existing tools fit for later design phases. Conversely, this paper proposes an integrated design and optimization environment, for automatically designing optimal aeronautical piston engine configuration, still in the conceptual design stage. The optimization is performed using the MATLAB genetic algorithm (GA) toolbox®, while the automatic design of the optimized components is carried out in cascade to the optimization phase. In particular, a single-objective GA is used to evaluate the optimal dimensions of engine components related to motion, namely: crankshaft, connecting rods and screws, flywheel, propeller shaft and torsional vibration damper. For testing the efficiency of the integrated environment, the conceptual design of components of a 4-in-line Diesel aeronautical piston engine is proposed, starting from an existing similar engine. Results show a reduction of the 20 % of weight of the crankshaft in comparison to the original configuration. The proposed environment seems to be a promising tool for a fast and reliable conceptual design of piston engines for aeronautical purposes.
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Renzi, C. A genetic algorithm-based integrated design environment for the preliminary design and optimization of aeronautical piston engine components. Int J Adv Manuf Technol 86, 3365–3381 (2016). https://doi.org/10.1007/s00170-016-8433-7
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DOI: https://doi.org/10.1007/s00170-016-8433-7