Application of Genetic Algorithms for the Optimisation of Diesel Engine Combustion PDF Download
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Author: María Teresa Abad Lozano
Publisher:
ISBN: 9783832512897
Category :
Languages : en
Pages : 154
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Book Description
Author: María Teresa Abad Lozano
Publisher:
ISBN: 9783832512897
Category :
Languages : en
Pages : 154
Get Book Here
Book Description
Author: Yu Shi
Publisher: Springer Science & Business Media
ISBN: 0857296191
Category : Technology & Engineering
Languages : en
Pages : 323
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Book Description
Computational Optimization of Internal Combustion Engines presents the state of the art of computational models and optimization methods for internal combustion engine development using multi-dimensional computational fluid dynamics (CFD) tools and genetic algorithms. Strategies to reduce computational cost and mesh dependency are discussed, as well as regression analysis methods. Several case studies are presented in a section devoted to applications, including assessments of: spark-ignition engines, dual-fuel engines, heavy duty and light duty diesel engines. Through regression analysis, optimization results are used to explain complex interactions between engine design parameters, such as nozzle design, injection timing, swirl, exhaust gas recirculation, bore size, and piston bowl shape. Computational Optimization of Internal Combustion Engines demonstrates that the current multi-dimensional CFD tools are mature enough for practical development of internal combustion engines. It is written for researchers and designers in mechanical engineering and the automotive industry.
Author: Jost Weber
Publisher: Cuvillier Verlag
ISBN: 3867277249
Category : Dieselmotor - Gemischbildung - Verbrennung - Numerische Strömungssimulation - Flamelet-Modell - Genetischer Algorithmus
Languages : en
Pages : 265
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Book Description
Author: Basilios Hamosfakidis
Publisher:
ISBN:
Category :
Languages : en
Pages : 340
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Book Description
Author: C.Y. Choi
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
An extensive evaluation was conducted to determine the feasibility of coupling the Genetic Algorithm (GA) optimization methodology with a combustion CFD code for production use. This methodology was applied to a Caterpillar research diesel engine and the optimal design produced by the GA was tested. Results showed that the optimal design performed as predicted at a target high-load operating condition by reducing both NOx and soot at equivalent brake specific fuel consumption (BSFC) when compared to a baseline Mexican-hat bowl and conventional nozzle configuration. Furthermore, the CFD code correctly predicted the magnitude of change in performance between optimal and baseline designs in 5 out of 6 emissions metrics over 3 operating modes. The optimal design did not outperform the baseline at all modes tested; however, results have validated both the predictive capability of the code as well as the feasibility of using a GA to produce viable engine designs that meet performance targets. The results suggest that to produce a design that is truly optimal over the entire speed-load range of a diesel engine, multi-modal optimizations should be performed in the future.
Author: Jihad Badra
Publisher: Elsevier
ISBN: 032388458X
Category : Technology & Engineering
Languages : en
Pages : 262
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Book Description
Artificial Intelligence and Data Driven Optimization of Internal Combustion Engines summarizes recent developments in Artificial Intelligence (AI)/Machine Learning (ML) and data driven optimization and calibration techniques for internal combustion engines. The book covers AI/ML and data driven methods to optimize fuel formulations and engine combustion systems, predict cycle to cycle variations, and optimize after-treatment systems and experimental engine calibration. It contains all the details of the latest optimization techniques along with their application to ICE, making it ideal for automotive engineers, mechanical engineers, OEMs and R&D centers involved in engine design. - Provides AI/ML and data driven optimization techniques in combination with Computational Fluid Dynamics (CFD) to optimize engine combustion systems - Features a comprehensive overview of how AI/ML techniques are used in conjunction with simulations and experiments - Discusses data driven optimization techniques for fuel formulations and vehicle control calibration
Author: P. V. Farrell
Publisher:
ISBN:
Category :
Languages : en
Pages : 4
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Book Description
A computational optimization study was performed for a heavy-duty direct-injection diesel engine using the recently developed KIVA-GA computer code. The effects of 11 engine input parameters on emissions and performance were studied. Start of injection (SOI), amount of EGR, boost pressure and eight parameters defining the fuel injection rate-shape were included in the search. The optimized configuration results in very low soot and NO(x) emissions together with relatively low fuel consumption.
Author: David D. Wickman
Publisher:
ISBN:
Category :
Languages : en
Pages : 240
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Book Description
Author: K. Diao
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Yong Sun
Publisher:
ISBN:
Category :
Languages : en
Pages : 234
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Book Description
