장봉수 교수
Bongsoo Jang
UNIST · 수학
연구실 소개
장봉수 교수의 연구실은 비선형 동역학, 분수계수 미분방정식, 그리고 생태계의 다양성 유지 메커니즘을 해석하는 데 초점을 맞춘 응용수학 및 수치해석 분야의 연구를 수행하고 있습니다. 특히, 로크-보자르-스코어스 게임과 같은 사이클적 경쟁 모델을 통해 생물다양성의 공존 상태를 분석하고, 고차원 비선형 생태계 모델의 수치적 해법을 개발하는 데 주력하고 있습니다. 또한, 분수계수 미분방정식의 정확한 수치해법과 고속 알고리즘 개발을 통해 열전달, 유동 및 복합 물리현상의 해석 능력을 강화하고 있습니다.
연구 현황
연구 성과 추이
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
주요 논문
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
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