संत लौंगोवाल अभियांत्रिकी एवं प्रौद्योगिकी संस्थान लौंगोवाल, संगरूर, पंजाब

(शिक्षा मंत्रालय, भारत सरकार के अधीन सम विश्वविद्यालय)

Sant Longowal Institute of Engineering and Technology, Longowal, Sangrur, Punjab

(Deemed to be University, under Ministry of Education, Govt. of India)

Finite Element Modeling for Bi-Directional Transport Phenomena During Atmospheric Deep Fat Frying of Kofta: Simulation and Experimental Validations

Authors: Rahul Das and Kamlesh Prasad

Book: Transforming Food Analysis and Control: Non-Destructive Technologies and Innovations

Editors: K. Prasad, S. Shekhar, M. K. Paswan, and R. Ahuja

Publisher: SLIET Longowal

Publication year: 2026

Publication date: 2026-07-20

ISBN: 978-81-990304-1-1 (e-book); 978-81-990304-0-4 (hardback)

Chapter pages: 149–180

DOI: To be added after DOI registration.

Abstract

The growing demand for convenient, nutritionally improved, and lower-oil traditional foods has encouraged the development of optimized ready-to-use (RTU) mixes to deliver consistent quality. In this context, the present study focuses on optimizing banana and chickpea flour for the development of an RTU kofta dry composite mix using a statistical optimization technique. A 2D axisymmetric finite element method (FEM) was applied to model atmospheric deep-fat frying at 170°C for 180 s, with a 30 s time interval, for a kofta ball using COMSOL Multiphysics 6.0. Simulated results showed that the surface temperature quickly reached the bulk temperature of frying oil, while the center temperature gradually increased to 113°C after 180 s as expected. The dry-basis moisture content at the surface decreased by 52.60% during frying, while the oil content increased by 11.17%. However, the crumb portion exhibited minimal change in both moisture and oil content. The optimized kofta had a 42.68% reduction in surface oil compared to the control, with comparable texture and flavor. Experimental data were used to validate the FEM predictions using statistical parameters such as mean absolute error, mean square error, root mean square error, chi-square, and coefficient of multiple determination, highlighting the accuracy of the FEM in tracking HMT phenomena. Future research should focus on refining the HMT model for different-shaped and sized food products, improving oil absorption mechanisms, exploring alternative frying methods, such as air frying and vacuum frying, to further reduce oil content at the pilot plant or industrial scale to maintain the product quality.

Keywords: Atmospheric deep fat frying; Composite mix; COMSOL Multiphysics; Heat and mass transfer; Microstructure

Full text: Download the chapter PDF