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Artificial Intelligence and Data Driven Optimization of Internal Combustion Engines 1st Edition Jihad Badra (Editor)

Name: Artificial Intelligence and Data Driven Optimization of Internal Combustion Engines 1st Edition Jihad Badra (Editor)
SKU: EB-38470328
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Artificial Intelligence and Data Driven Optimization of Internal Combustion Engines 1st Edition Jihad Badra (Editor) Digital Instant Download

Author(s): Jihad Badra (editor), Pinaki Pal (editor), Yuanjiang Pei (editor), Sibendu Som (editor)

ISBN(s): 9780323884570, 0323884571

Edition: 1

File Details: PDF, 14.25 MB

Year: 2022

Language: English

SKU: EB-38470328 Category: Computers - Artificial Intelligence (AI) Tags: 0323884571, 9780323884570, Artificial Intelligence, Data Driven Optimization, Internal Combustion Engines, Jihad Badra (editor), Pinaki Pal (editor), Sibendu Som (editor), Yuanjiang Pei (editor)

Description

Artificial Intelligence and Data Driven Optimization of Internal Combustion Engines 1st Edition Jihad Badra (Editor) – Ebook Instant Download/Delivery ISBN(s): 9780323884570,0323884571

Product details:

• ISBN 10:0323884571
• ISBN 13:9780323884570
• Author(s): Jihad Badra (editor), Pinaki Pal (editor), Yuanjiang Pei (editor), Sibendu Som (editor)

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

Table contents:

Chapter 1. Introduction
Chapter 2. Optimization of fuel formulation using adaptive learning and artificial intelligence
Chapter 3. Artificial intelligence–enabled fuel design
Chapter 4. Engine optimization using computational fluid dynamics and genetic algorithms
Chapter 5. Computational fluid dynamics–guided engine combustion system design optimization using design of experiments
Chapter 6. A machine learning-genetic algorithm approach for rapid optimization of internal combustion engines
Chapter 7. Machine learning–driven sequential optimization using dynamic exploration and exploitation
Chapter 8. Artificial-intelligence-based prediction and control of combustion instabilities in spark-ignition engines
Chapter 9. Using deep learning to diagnose preignition in turbocharged spark-ignited engines

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