Draft:TusharJadhav
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Tushar Dhanajirao Jadhav (born 15 May 1983) is an Indian aerospace and multi-physics simulation engineer, researcher, and technical manager. He is recognized for his contributions to flight dynamics, computational fluid dynamics (CFD), model-based systems engineering (MBSE), and digital twin technology within the aerospace, defense, and energy sectors.
Jadhav's notable research includes developing advanced fluid dynamics normalization workflows during his postgraduate studies at the Indian Institute of Technology Madras (IIT Madras). He currently serves as a Technical Manager at Fluid Codes / QuantaSim in Dubai, United Arab Emirates.
Early Life and Education
Jadhav was born on 15 May 1983 and is originally from the town of Karad in Maharashtra, India. He pursued his early technical education in aeronautical engineering, earning his bachelor's degree from the Aeronautical Society of India (AeSI) in Chennai in 2007, where he specialized in aerodynamics.
He subsequently cleared the graduate admissions process to join the Indian Institute of Technology Madras (IIT Madras) in December 2007. At IIT Madras, he conducted extensive research in experimental fluid mechanics and turbulence under the supervision of Dr. N. R. Panchapakesan. He graduated with a Master of Science (By Research) in Aerospace Engineering in October 2010.
Academic Research and Self-Similarity Scale Development
During his master's program, Jadhav specialized in the fluid mechanics of interacting shear flows. His thesis focused on mass entrainment, mixing behavior, and centerline velocity decay in non-circular and multiple nozzle arrays.
Jadhav pioneered an analytical approach to describe the self-similar regions of fluid jets. Prior academic literature frequently evaluated multi-jet arrays utilizing geometric scaling properties like hydraulic diameter. Jadhav demonstrated that because fluid momentum flux varies quadratically with velocity while mass flux scales linearly, geometric scales failed to provide accurate baseline comparisons. He formulated a normalized scaling system explicitly derived from combined inlet mass flux and total inlet momentum flux to define an equivalent velocity scale and an equivalent length scale. Through this framework, he proved that the statistics of fluid properties in a fully coalesced, far-field self-similar region depend entirely on these flow-derived scales rather than the initial physical nozzle geometries.
Professional Career
Early Career and Ansys
Following a brief tenure as a Research Project Officer at IIT Madras, Jadhav worked in Pune, India, as a Lead Simulation Engineer. Over an 11-year tenure, he delivered multi-physics optimization and scale-resolving simulations for prominent global aerospace original equipment manufacturers (OEMs), including General Electric, Pratt & Whitney, and Honeywell Aerospace. His technical assignments spanned combustion dynamics, turbomachinery aerodynamics, and reverse engineering structural failure mechanics.
During this period, Jadhav pioneered strategic research workflows combining machine learning algorithms with automated turbulence model tuning, notably collaborating on developments for the GEKO (Generalized k-omega) and LES-GPU solver frameworks. Additionally, his efforts driving industrial simulation applications across the Asia-Pacific region contributed to commercial software adoption within the automotive sector.
Fluid Codes / QuantaSim
Jadhav later relocated to Dubai, UAE, to assume the role of Technical Manager for Modeling and Simulation at Fluid Codes / QuantaSim. In this role, he has managed engineering and engineering-consulting projects spanning aerospace, defense, and process engineering domains.
Operating as an engineering consultant, he has driven and supported specialized simulation deliverables for many high-profile industrial partners, below are few examples:
- Calidus Simulation Support: Provided technical expertise for flying qualities and stability & control investigations across multiple airframe configurations. He built automated fluid dynamics workflows to generate aerodynamic databases, extract stability derivatives, and conduct controllability assessments across low-speed, cruise, and high angle-of-attack profiles.
- EDGE Group Training Program: Contributed to the design and delivery of a 9-month UAV engineering boot camp curriculum, supporting modules covering the drone development lifecycle from conceptual sizing and aerodynamic characterization to propulsion integration and flight operations.
- Saudi Aramco Digital Twin Initiative: Supported the development of multi-fidelity physics models using 1D Modelica frameworks and 3D computational fluid dynamics-based Reduced Order Models (ROMs) to deliver interactive digital twin demonstrations for specialized processing applications.
Selected Publications
Jadhav has authored and co-authored several peer-reviewed technical articles published via major international engineering bodies:
Fluid Dynamics & Multi-Jet Interactions
- Jadhav, T., et al. (2010). "Multiple Round Jets – An Experimental and Computational Study." 37th National & 4th International Conference on Fluid Mechanics and Fluid Power (FMFP), IIT Madras.[1]
- Jadhav, T., et al. (2010). "Numerical Investigation of Multiple Round Jets." 5th International Conference on Theoretical, Applied, Computational and Experimental Mechanics (ICTACEM2010).[2]
Aeroacoustics & Combustion Engineering
- Jadhav, T., et al. (2014). "Broadband Model for Impedance Boundary Condition in a Navier–Stokes Solver." AIAA Aviation Forum.[3]
- Jadhav, T., et al. (2017). "Mode Shapes and Dominant Frequency Predictions in a Swirl-Stabilized Premixed Air–Methane Combustor Using Modal Analysis and Large Eddy Simulations (LES)." ASME Turbo Expo 2017.[4]
- Kandekar, A., Jadhav, T., et al. (2018). "HVAC System Noise Prediction Through CFD Simulation." SAE Technical Paper 2019-26-0210.[5]
- Jadhav, T., et al. (2018). "Spectral Analysis of Aero-acoustic Noise Using CAE Tools." NAFEMS CAASE18 Conference.[6]
- Zore, K., Jadhav, T., et al. (2020). "Aeroacoustics Noise Prediction of Low-Mach-Number Flow Using Hybrid Wave Equation Model." Noise-Con Conference.[7]
Shape Optimization & Applied Turbulence Modeling
- Mentor, F., Jadhav, T., et al. (2019). "Tuning the GEKO Turbulence Model: 1st Automotive CFD Prediction Workshop." CFD Workshop Proceedings.[8]
- Ren, C., Jadhav, T., et al. (2020). "Aerodynamic Optimization of Vehicle Configuration Based on Adjoint Method." SAE Technical Paper 2020-01-0915.[9]
- Jadhav, T., et al. (2020). "Adjoint for Scale Resolving Simulations." NAFEMS CAASE20 Conference.[10]
- Zhou, H., Jadhav, T., et al. (2021). "Multi-Objective Aerodynamic Optimization of Vehicle Shape Using Adjoint Approach Based on Steady-State and Transient Flow." SAE International.[11]
- Wu, H., Jadhav, T., et al. (2022). "Adjoint-Based Model Tuning and Machine Learning Strategy for Turbulence Model Improvement." SAE International Journal.[12]