Development of a Modular Knowledge-Discovery Framework based on Machine Learning - for the Interdisciplinary Analysis of Complex Phenomena in the Context of GDI Combustion Processes - Dissertation

Aug 5, 2026

A doctoral dissertation presenting a modular knowledge-discovery framework built using machine learning to support interdisciplinary analysis of complex phenomena. The work is placed in the context of GDI combustion processes and targets how knowledge extraction can be structured, integrated, and applied across multiple perspectives. It includes formal academic details such as supervision, examination date, and publication identifiers, situating the research within the Engineering Information Management series of KIT (Karlsruhe Institute of Technology).

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages210

Reading Time8 h 49 min

AccessFree to download

Dissertation Overview

Title, Author, and Affiliation

Academic Degree and Examination Details

Publication and Licensing Information

Reihe Informationsmanagement im Engineering Karlsruhe Massimiliano Botticelli Development of a modular Knowledge-Discovery Framework based on Machine Learning for the interdisciplinary analysis of complex phenomena in the context of GDI combustion processes Band 2 – 2023 Massimiliano Botticelli Development of a modular Knowledge-Discovery Framework based on Machine Learning for the interdisciplinary analysis of complex phenomena in the context of GDI combustion processes Reihe Informationsmanagement im Engineering Karlsruhe Band 2 – 2023 Herausgeber Karlsruher Institut für Technologie Institut für Informationsmanagement im Ingenieurwesen (IMI) o. Prof. Dr. Dr.-Ing. Dr. h.c. Jivka Ovtcharova Eine Übersicht aller bisher in dieser Schriftenreiheerschienenen Bände finden Sie am Ende des Buchs. Development of a modular Knowledge-Discovery Framework based on Machine Learning for the interdisciplinary analysis of complex phenomena in the context of GDI combustion processes by Massimiliano Botticelli Karlsruher Institut für Technologie Institut für Informationsmanagement im Ingenieurwesen Development of a modular Knowledge-Discovery Framework based on Machine Learning: for the interdisciplinary analysis of complex phenomena in the context of GDI combustion processes Zur Erlangung des akademischen Grades eines Doktors der Ingenieurwissenschaften von der KIT-Fakultät für Maschinenbau des Karlsruher Instituts für Technologie (KIT) genehmigte Dissertation von Massimiliano Botticelli, M. Eng. Tag der mündlichen Prüfung: 30. Januar 2023 Hauptreferentin: Prof. Dr. Dr.-Ing. Dr. h. c. Jivka Ovtcharova Korreferent: [Prof. Dr. sc. techn. Thomas Koch](Prof. Dr. sc. techn. Thomas Koch) Impressum Karlsruher Institut für Technologie (KIT) KIT Scientific Publishing Straße am Forum 2 D-76131 Karlsruhe KIT Scientific Publishing is a registered trademark of Karlsruhe Institute of Technology. Reprint using the book cover is not allowed. [www.ksp.kit.edu](www.ksp.kit.edu) This document – excluding parts marked otherwise, the cover, pictures and graphs – is licensed under a Creative Commons Attribution-Share Alike 4.0 International License (CC BY-SA 4.0): [https://creativecommons.org/licenses/by-sa/4.0/deed.en](https://creativecommons.org/licenses/by-sa/4.0/deed.en) The cover page is licensed under a Creative Commons Attribution-No Derivatives 4.0 International License (CC BY-ND 4.0): [https://creativecommons.org/licenses/by-nd/4.0/deed.en](https://creativecommons.org/licenses/by-nd/4.0/deed.en) Print on Demand 2023 – Gedruckt auf FSC-zertifiziertem Papier ISSN 1860-5990 ISBN 978-3-7315-1295-0 DOI 10. 5445/KSP/1000158016 When you know a thing, to hold that you know it; when you do not know a thing, to allow that you do not know it; this is knowledge The Analects, Confucius

FAQs

What is the main objective of the dissertation?

To develop a modular knowledge-discovery framework based on machine learning for interdisciplinary analysis of complex phenomena in the context of GDI combustion processes.

In what application context is the framework intended to be used?

The framework is designed for analyzing complex phenomena related to GDI (gasoline direct injection) combustion processes.

When was the dissertation defense (mündliche Prüfung) held?

The document lists the date of the oral examination as 30 January 2023.

Aug 5, 2026

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