Bongsoo Jang
Ulsan National Institute of Science and Technology · Mathematics
About the Lab
Professor Bongsoo Jang's research lab specializes in the development and application of advanced numerical and analytical methods for solving complex nonlinear and fractional differential equations arising in fluid dynamics, heat transfer, and mathematical physics. The lab focuses on innovative computational techniques such as modified differential transform methods, predictor-corrector schemes, and spectral methods tailored for fractional-order systems and multiphase flows in porous media. Key research directions include heat transfer in nanofluids, convection in complex geometries, and efficient algorithms for memory-intensive fractional derivatives. The lab emphasizes both theoretical rigor and practical implementation, aiming to deliver high-accuracy, computationally efficient solutions for real-world engineering and scientific problems.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15Evolutionary games of cyclic competitions have been extensively studied to gain insights into one of the most fundamental phenomena in nature: biodiversity that seems to be excluded by the principle of natural selection. The Rock-Paper-Scissors (RPS) game of three species and its extensions [e.g., the Rock-Paper-Scissors-Lizard-Spock (RPSLS) game] are paradigmatic models in this field. In all previous studies, the intrinsic symmetry associated with cyclic competitions imposes a limitation on the
The current article deals with the computational study of buoyant convection and heat dissipation processes of hybrid nanoliquid saturated in an inclined porous annulus. The fluid flow movement in the porous annular region is modeled using Darcy–Brinkman–Forchheimer model. The vertical boundaries of the cylinder are subjected to uniform but different heating profiles and horizontal surfaces are maintained adiabatic. In the current investigation, for the conservation laws which govern the conside
We present an efficient computational algorithm, namely, the enhanced multistage differential transform method (E‐MsDTM) for solving prey‐predator systems. Since the differential transform method (DTM) is based on the Taylor series, it is difficult to obtain accurate approximate solutions in large domain. To overcome this difficulty, the multistage differential transform method (MsDTM) has been introduced and succeeded to have reliable approximate solutions for many problems. In MsDTM, it is the
In this article, a considerably efficient predictor-corrector method (PCM) for solving Atangana–Baleanu Caputo (ABC) fractional differential equations (FDEs) is introduced. First, we propose a conventional PCM whose computational speed scales with quadratic time complexity O(N2) as the number of time steps N grows. A fast algorithm to reduce the computational complexity of the memory term is investigated utilizing a sum-of-exponentials (SOEs) approximation. The conventional PCM is equipped with
Research Areas
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