김태완 교수
Tae Wan Kim
서울대학교 · 공학
연구실 소개
김태완 교수의 연구실은 건설공학과 생물학적 구조를 융합한 혁신적 기술 개발에 주력하고 있습니다. 특히 도시 환경에서의 모듈러 건설의 도전 과제와 성공 요인을 분석하며, 지능형 건설 방법론과 안전성 향상을 위한 이원화된 공법 평가를 수행하고 있습니다. 또한, 게코 뱀부리의 첨단 점착 메커니즘을 모방한 나노구조 재료 개발을 통해 신소재 응용 분야로의 확장을 모색하고 있습니다.
연구 현황
연구 성과 추이
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
주요 논문
15A series of platinum catalysts supported on ordered mesoporous carbon (CMK-3) with different Pt loadings from 1 to 10 wt% have been prepared, and their catalytic activities for hydrogen production viaaqueous-phase reforming (APR) of ethylene glycol (EG) have been investigated. Characterization by X-ray powder diffraction, transmission electron microscopy, N2 sorption, and CO chemisorption techniques reveal that an ordered mesostructure, high surface area, large pore volume, and uniform mesopore
Helping others can have a positive effect on both the giver and the receiver. However, supporting someone with depression can be complicated and overwhelming. To address this, we proposed a Facebook-based social bot displaying depressive symptoms and disclosing vulnerable experiences that allows users to practice providing reactions online. We investigated how 55 college students interacted with the social bot for three weeks and how these support-giving experiences affected their mental health
Skid-steer vehicle can generate a large traction force, which is especially good for navigation on a rough terrain. However, the turning motion is so sensitive to slippage effect that designing a controller is still challenging problem. Also, the motion of the vehicle is affected not only by wheel motion, but also by the road properties and the characteristics of wheel control. With this in mind, we employ a model predictive control (MPC) with an on-line model learning. The velocity model, which
Cholic acid-conjugated methylcellulose-polyethylenimines (MCPEI-CAs) were synthesized and characterized for drug delivery systems. Their synthesis was confirmed by ¹H NMR and FT-IR analysis. Induced circular dichroism result with Congo red showed that methylcellulose (MC) and polyethylenimine-grafted cationic derivative (MC-PEI) would have helical conformation and random coil structure, respectively. It was found that MCPEI-CAs could form positively charged (>30 mV Zeta-potential) and spherical
Reaction time, driver sensitivity, and time headway are traffic parameters that are critical for understanding and modeling traffic stability and wave propagation. Both theoretical and empirical relationships between these three parameters are examined with vehicle trajectory data. A few clear and distinct relationships are identified, and driver reaction time is found to be closely related to time headway, especially in the deceleration phase. Time headway can be accurately predicted when react
Path tracking control for autonomous vehicle using model predictive control (MPC) algorithm maintains maneuverability by calculating a sequence of control input which minimizes a tracking error. The weakness of this method is that the performance of MPC may decrease significantly when the priori prediction model is not accurate. Therefore, it is important to keep the vehicle stable when MPC having model error. This paper uses an on-line model-based reinforcement learning (RL) to decrease the pat
Congested traffic shows very complicated stochastic features such as irregular transition of flow-density relations and the growth/decay of perturbations. In this paper, gap time is identified as a primary random variable in congested traffic and the wave speed is determined according to the relative difference between gap time and driver's reaction time. The growth or decay of perturbations are explained in accordance with the random transition of observation points in the fundamental diagram.
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