The University of Tokyo · 공학
이 교수의 연구실은 구조물의 안정성과 내구성을 높이기 위한 최적화 및 수치해석 기법을 중심으로 연구를 전개하고 있습니다. 특히 비선형 구조 해석, 구속조건을 고려한 최적 설계, 불확실성에 대한 내재적 저항력(로버스트니) 분석에 초점을 맞추고 있으며, 구조물의 재료 비용과 성능을 동시에 고려한 최적화 설계 기법을 개발하고 있습니다. 주요 응용 분야로는 지진 하중에 대한 저항성 향상, 케이블 구조물의 평형 형상 해석, 보조 감쇠 장치의 최적 배치 등이 있습니다.
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
"This book concerns matter that is intrinsically difficult: convex optimization, complementarity and duality, nonsmooth analysis, linear and nonlinear programming, etc. The author has skillfully introduced these and many more concepts, and woven them into a seamless whole by retaining an easy and consistent style throughout. The book is not all the
A new formulation is presented for the three-dimensional incremental quasi-static problems with unilateral frictional contact. Under the assumptions of small rotations and small strains, a second-order cone linear complementarity problem is formulated, which consists of complementarity conditions defined by bilinear functions and second-order cone constraints. The equilibrium configurations are obtained by using a combined smoothing and regularization method for the second-order cone complementa
The redundancy of a structure refers to the extent of degradation the structure can suffer without losing some specified elements of its functionality. However, because future structural degradation is unknown during design and analysis, it is evident that structural redundancy is related to robustness against uncertainty. This paper proposes a quantitative and widely applicable concept of strong redundancy and shows its relation to the info-gap robustness of the structure. In particular, one of
Abstract This paper presents a mixed integer programming (MIP) formulation for robust topology optimization of trusses subjected to the stress constraints under the uncertain load. A design‐dependent uncertainty model of the external load is proposed for dealing with the variation of truss topology in the course of optimization. For a truss with the discrete member cross‐sectional areas, it is shown that the robust topology optimization problem can be reduced to an MIP problem, which is solved g
SUMMARY Supplemental damping is known as an efficient and practical means to improve seismic response of building structures. Presented in this paper is a mixed‐integer programming approach to find the optimal placement of supplemental dampers in a given shear building model. The damping coefficients of dampers are treated as discrete design variables. It is shown that a minimization problem of the sum of the transfer function amplitudes of the interstory drifts can be formulated as a mixed‐inte
Abstract A new formulation is presented for equilibrium shape analysis of cable networks considering geometrical and material non‐linearities. Friction between cables and joint devices is also considered. The second‐order cone programming (SOCP) problem which has the same solution as that of minimization of total potential energy is solved to obtain the equilibrium configuration. The optimality conditions are derived to verify that the solution satisfies equilibrium conditions and friction laws.
A tensegrity structure is a prestressed pin-jointed structure consisting of continuously connected tensile members (cables) and disjoint compressive members (struts). This paper addresses topology optimization of tensegrity structures subjected to self-weight loads, where the compliance, i.e., the strain energy at the equilibrium state, is to be minimized. It is shown that the optimization problem can be formulated as a mixed integer linear programming (MILP) problem. The proposed method does no
The paper presents a global optimization method to compute the minimum limit load factor of trusses subjected to unknown but bounded loads.We assume that the external forces consist of a part proportional to a load factor and a part that is uncertain around its nominal value.The worst-case limit load factor is introduced as the smallest limit load factor realized with some uncertain parameters.In order to detect the worst case, we have to find the global optimal solution of a nonconvex optimizat