---
title: "Anubhav Choudhary - CFD Engineer in Bengaluru | Tal"
description: "Meet Anubhav Choudhary, CFD Engineer (3 YOE) | EV Battery & Powertrain Thermal Management | CHT, Multiphase (VOF), Turbulence Modeling | ANSYS Fluent, STAR-CCM+ | Automotive OEM (GM via TCS) based in Bengaluru. AI stack includes ChatGPT and Glean."
image: "https://tal.club/meet/anubhav-choudhary/share-image"
---

# Anubhav Choudhary on Tal

## Headline

CFD Engineer \(3 YOE\) \| EV Battery & Powertrain Thermal Management \| CHT, Multiphase \(VOF\), Turbulence Modeling \| ANSYS Fluent, STAR\-CCM\+ \| Automotive OEM \(GM via TCS\)

## About

CFD Engineer with 3 years of experience in EV battery, powertrain, and thermal management systems, solving complex fluid\-flow and heat transfer problems using physics\-driven simulation\. My work focuses on conjugate heat transfer \(CHT\), multiphase flows \(VOF\), and system\-level thermal management, applying strong fundamentals in fluid dynamics and heat transfer to improve performance, reliability, and design efficiency\. At Tata Consultancy Services \(Client: General Motors\), I have worked on: • EV battery and ICE cooling systems \(coolant flow distribution, fill & drain analysis\)• E\-motor thermal management \(rotor and stator cooling optimization\) • Turbocharger thermal analysis \(CHT, oil & coolant interaction\) • Crankcase ventilation and fuel tank slosh simulations \(multiphase behavior\) Worked closely with design teams to translate simulation insights into geometry and system\-level improvements, enhancing cooling performance and resolving flow\-related issues\.Some key outcomes: • Reduced peak rotor temperature by 10°C, improving durability • Increased stator heat transfer coefficient by 22%, enhancing thermal performance • Developed ML\-based surrogate models for centrifugal pumps with 92% prediction accuracy, reducing design cycle time by 30% Technical expertise: • ANSYS Fluent, STAR\-CCM\+, Simerics • Turbulence models \(k\-ε, k\-ω SST\), multiphase \(VOF\), rotating flows \(MRF\) • Mesh optimization, y\+ control, and convergence strategies • Python \(NumPy, Pandas, Scikit\-learn\) I enjoy solving engineering problems that require a balance of physics understanding, numerical accuracy, and system\-level thinking, particularly in battery cooling, powertrain thermal systems, and multiphysics simulations\. I’m currently open to opportunities in product\-based companies where I can contribute to advanced CFD, thermal management, and simulation\-driven design in EV, automotive, or energy systems\.

## Location

Bengaluru

## AI stack

ChatGPT

Glean

## Work experience

CFD Engineer at Tata Consultancy Services, Sep 2023 \- Present · 3 y, Bengaluru, Karnataka, India, Working within the Powertrain & Thermal Systems domain, delivering CFD\-driven solutions for EV battery cooling, e\-motor thermal management, and automotive fluid systems, focusing on physics\-based modeling, numerical accuracy, and design optimization\. 🔹 Key Contributions: • Performed system\-level CFD simulations for EV and ICE cooling systems, analyzing coolant flow distribution, fill & drain behavior, and thermal performance to improve system reliability and efficiency\. • Conducted conjugate heat transfer \(CHT\) simulations of turbocharger assemblies using appropriate turbulence models \(k\-ε, k\-ω SST\), identifying coolant boiling risks and mitigating oil coking issues\. • Optimized e\-motor cooling \(rotor & stator\) through flow and geometry modifications, achieving: • 10°C reduction in peak rotor temperature • 22% improvement in stator heat transfer coefficient \(HTC\) • Simulated multiphase flows \(VOF\) for coolant systems and fuel tank slosh analysis, identifying air entrainment, flow instabilities, and pump inlet exposure issues\. • Developed high\-quality computational domains with mesh optimization \(inflation layers, y\+ control, polyhedral/trimmed cells\), ensuring solution stability and accuracy\. • Ensured numerical reliability through mesh independence studies, residual convergence monitoring, and solver parameter tuning\. • Executed simulations involving rotating machinery \(MRF/rotating reference frames\) for pumps and thermal systems\. • Developed Python\-based AI/ML surrogate models \(Scikit\-learn\) for centrifugal pump performance prediction, achieving 92% accuracy and reducing design cycle time by 30%\. • Collaborated with cross\-functional design teams to translate CFD insights into geometry and system\-level design improvements, enhancing cooling performance, reducing NVH issues, and improving product reliability\.

Summer Intern at Micro Turners Group \- India, Jun 2017 \- Jul 2017 · 2 mos, Nalagarh, Himachal Pradesh, India, • Gained hands\-on exposure to the end\-to\-end manufacturing process of gears and shafts, from raw materialGained exposure to end\-to\-end manufacturing of automotive components \(gears and shafts\), including machining, heat treatment, and quality control processes\. • Studied heat treatment processes \(annealing, quenching, tempering\) to enhance material strength and durability\. • Observed integration of CNC machining and automation in precision manufacturing\. • Applied mechanical engineering fundamentals to understand process optimization and defect reduction in production environments\. preparation to final quality inspection\. \- Worked on heat treatment processes including annealing, quenching, and tempering to enhance component strength and durability\. \- Learned about automation and CNC machining integration in precision manufacturing\. \- Applied material science & mechanical engineering concepts to real\-world challenges in process optimization and defect reduction\.

## Education

M\.tech, Industrial design, National Institute of Technology Rourkela

Bachelor of Engineering \- BE, Mechanical Engineering, UIETH, Panjab University

[View the original profile](https://tal.club/meet/anubhav-choudhary)

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