M.Sc. Ali Navid

M.Sc. Ali Navid
Wissenschaftlicher Mitarbeiter
Gustav-Zeuner-Straße 7, 09599 Freiberg, Zimmer 318
Telefon +49 3731 39 3754
Ali [dot] Navidiwtt [dot] tu-freiberg [dot] de
Beruflicher Werdegang
- Seit 07/2021: Wissenschaftlicher Mitarbeiter am Institut für Wärmetechnik und Thermodynamik, Lehrstuhl für Gas- und Wärmetechnische Anlagen
- 2018 - 2019: PhD Student, TU Chemnitz, Fahrzeugsystemdesign
Hochschulausbildung
- 2014 - 2016: Master of Science, Urmia University, Urmia; Mechanical Engineering, Energy Conversion
M.Sc. Thesis: Optimization of a baseline diesel engine with evolutionary NLPQL and non-evolutionary Genetic algorithms in order to reduce emissions and boost efficiency - 2008 - 2013: Bachelor of Science, Urmia University of Technology, Urmia, Mechanical Engineering in heat and fluid
Forschungsthemen
- MiGWa: "Kombinierte Glasschmelze mit Mikrowellen und H2-Oxyfuelverbrennung" des Verbundprojektes "KlimPro: CO2-Einsparung bei der Glasherstellung durch neuartige und klimaschonende Beheizung"
Publikationen
Book translation: Ali Navid, Translation of “Fluid Mechanics: fundamentals and application” by Yunus A. Cengel and John M. Cimbala 3rd edition” to Farsi, Mcgraw-Hill publications (in Iran: Motafakeran publications), 2015.
Ali Navid, Shahram Khalilarya, Hadi Taghavifar, “Comparing multi-objective non-evolutionary NLPQL and evolutionary genetic algorithm optimization of a DI diesel engine: DoE estimation and creating surrogate model”, Energy Conversion and Management 126 (2016): 385-399.
Taghavifar, Hadi, Samad Jafarmadar, Hamid Taghavifar, and Ali Navid, "Application of DoE evaluation to introduce the optimum injection strategy-chamber geometry of diesel engine using surrogate epsilon-SVR." Applied thermal engineering 106 (2016): 56-66.
Jafarmadar, S., Hadi Taghavifar, Hamid Taghavifar, and A. Navid, "Numerical assessment of flow dynamics for various DI diesel engine designs considering swirl number and uniformity index." Energy Conversion and Management 110 (2016): 347-355.
Ali Navid, Shahram Khalilarya, Mohammad Abbasi, “Diesel engine optimization with multi-objective performance characteristics by non-evolutionary Nelder-Mead algorithm: Sobol sequence and Latin hypercube sampling methods comparison in DoE process”, Fuel 228 (2018): 349-367.
Ali Navid, Shahram Khalilarya, “Evaluation of a diesel engine optimized by non-evolutionary NLPQL and evolutionary genetic algorithms and assessing second law efficiency: analysis in Exergy Loss and Chemical Exergy”, Applied Thermal Engineering 159 (2019): 113794.