• Title/Summary/Keyword: Structure identification

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Isolation and Identification of 13-Deacetyl-taxchinin I, a New Taxoid from Plant Cell Cultures of Taxus chinensis (식물세포 Taxus chinensis 배양으로부터 신물질 13-Deacetyl-taxchinin I의 분리 및 동정)

  • 김진현;기은숙;유시용;최형균;홍승서;이현수
    • KSBB Journal
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    • v.15 no.6
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    • pp.560-565
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    • 2000
  • 13-Deacetyl-taxchinin I, a taxoid having a rearranged 11(15\longrightarrow1)-abeo-taxane skeleton, has been isolated and identified from plant cell cultures of Taxus chinensis. The compound has not previously been encountered in nature. Its structure was elucidated by 1-and 2D NMR techniques including H-H COSY, HMQC, and HMBC experiments. This taxoid also provides information for better understanding of structure-activity relationships and biosynthesis, as well as improving the quality control of paclitaxel production.

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Structural joint modeling and identification: numerical and experimental investigation

  • Ingole, Sanjay B.;Chatterjee, Animesh
    • Structural Engineering and Mechanics
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    • v.53 no.2
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    • pp.373-392
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    • 2015
  • In the present work, structural joints have been modeled as a pair of translational and rotational springs and frequency equation of the overall system has been developed using sub-structure synthesis. It is shown that using first few natural frequencies of the system, one can obtain a set of over-determined system of equations involving the unknown stiffness parameters. Method of multi-linear regression is then applied to obtain the best estimate of the unknown stiffness parameters. The estimation procedure has been developed first for a two parameter joint model and then for a three parameter model, in which cross coupling terms are also included. Two cases of structural connections have been considered, first with a cantilever beam with support flexibility and then a pair of beams connected through lap joint. The validity of the proposed method is demonstrated through numerical simulation and by experimentation.

Element Level System Identification Method without Input Data (미지의 입력자료를 이용한 요소수준의 구조물 손상도 추정기법)

  • Cho, Hyo-Nam;Choi, Young-Min;Moon, Chang
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1997.04a
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    • pp.89-96
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    • 1997
  • Most civil engineering structures, such as highway bridges, towers, power plants and offshore structures suffer structural damages over their service lives caused by adverse loading such as heavy transportation loads, machine vibrations, earthquakes, wind and wave forces. Especially, if excessive load would be acted on the structure, general or partial stiffness should be degraded suddenly and service lives should be shortened eventually For realistic damage assessment of these civil structures, System Identification method using only structure dynamic response data with unknown input excitation is required and thus becoming more challenging problem. In this paper, an improved Iterative Least Squares method is proposed, which seems to be very efficient and robust method, because only the dynamic response data such as acceleration, velocity and displacement is used without input data, and no information on the modal properties is required. The efficiency and robustness of the proposed method is proved by numerical problems and real single span beam model test.

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Application of Docking Methods: An Effective In Silico Tool for Drug Design

  • Kulkarni, Seema;Madhavan, Thirumurthy
    • Journal of Integrative Natural Science
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    • v.6 no.2
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    • pp.100-103
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    • 2013
  • Using computational approaches we can dock small molecules into the structures of Macromolecular targets and then score their potential complementarity to binding sites is widely used in hit identification and lead optimization techniques. This review seeks to provide the application of docking in structure-based drug design (binding mode prediction, Lead Identification and Lead optimization), and also discussed how to manage errors in docking methodology in order to overcome certain limitations of docking and scoring algorithm.

Generalized Fuzzy Modeling

  • Hwang, Hee-Soo;Joo, Young-Hoon;Woo, Kwang-Bang
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.1145-1150
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    • 1993
  • In this paper, two methods of fuzzy modeling are prsented to describe the input-output relationship effectively based on relation characteristics utilizing simplified reasoning and neuro-fuzzy reasoning. The methods of modeling by the simplified reasoning and the neuro-fuzzy reasoning are used when the input-output relation of a system is 'crisp' and 'fuzzy', respectively. The structure and the parameter identification in the modeling method by the simplified reasoning are carried out by means of FCM clustering and the proposed GA hybrid scheme, respectively. The structure and the parameter identification in the modeling method by the neuro-fuzzy reasoning are carried out by means of GA and BP algorithm, respectively. The feasibility of the proposed methods are evaluated through simulation.

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An Analysis of Applications and Issues in Library RFID System (도서관 RFID 시스템의 어플리케이션 및 문제점 분석에 관한 연구)

  • Lee, Eung-Bong
    • Journal of Information Management
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    • v.39 no.2
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    • pp.27-43
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    • 2008
  • This paper analyzes feasibility studies regarding the structure, applications and issues of the library RFID system. In this study, the structure and principle, operation mode and middleware of library RFID system are reviewed in detail, Finally this paper analyzed and proposed the RFID applications that could be efficient to information management and user service of library and the major problems and improvements of library RFID system.

Structural damage detection based on MAC flexibility and frequency using moth-flame algorithm

  • Ghannadi, Parsa;Kourehli, Seyed Sina
    • Structural Engineering and Mechanics
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    • v.70 no.6
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    • pp.649-659
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    • 2019
  • Vibration-based structural damage detection through optimization algorithms and minimization of objective function has recently become an interesting research topic. Application of various objective functions as well as optimization algorithms may affect damage diagnosis quality. This paper proposes a new damage identification method using Moth-Flame Optimization (MFO). MFO is a nature-inspired algorithm based on moth's ability to navigate in dark. Objective function consists of a term with modal assurance criterion flexibility and natural frequency. To show the performance of the said method, two numerical examples including truss and shear frame have been studied. Furthermore, Los Alamos National Laboratory test structure was used for validation purposes. Finite element model for both experimental and numerical examples was created by MATLAB software to extract modal properties of the structure. Mode shapes and natural frequencies were contaminated with noise in above mentioned numerical examples. In the meantime, one of the classical optimization algorithms called particle swarm optimization was compared with MFO. In short, results obtained from numerical and experimental examples showed that the presented method is efficient in damage identification.

On-load Parameter Identification of an Induction Motor Using Univariate Dynamic Encoding Algorithm for Searches

  • Kim, Jong-Wook;Kim, Nam-Gun;Choi, Seong-Chul;Kim, Sang-Woo
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.852-856
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    • 2004
  • An induction motor is one of the most popular electrical apparatuses owing to its simple structure and robust construction. Parameter identification of the induction motor has long been researched either for a vector control technique or fault detection. Since vector control is a well-established technique for induction motor control, this paper concentrates on successive identification of physical parameters with on-load data for the purpose of condition monitoring and/or fault detection. For extracting six physical parameters from the on-load data in the framework of the induction motor state equation, unmeasured initial state values and profiles of load torque have to be estimated as well. However, the analytic optimization methods in general fail to estimate these auxiliary but significant parameters owing to the difficulty of obtaining their gradient information. In this paper, the univariate dynamic encoding algorithm for searches (uDEAS) newly developed is applied to the identification of whole unknown parameters in the mathematical equations of an induction motor with normal operating data. Profiles of identified parameters appear to be reasonable and therefore the proposed approach is available for fault diagnosis of induction motors by monitoring physical parameters.

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Identification of Fractional-derivative-model Parameters of Viscoelastic Materials Using an Optimization Technique (최적화 기법을 이용한 점탄성물질의 분수차 미분모델 물성계수 추정)

  • Kim, Sun-Yong;Lee, Doo-Ho
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.16 no.12 s.117
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    • pp.1192-1200
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    • 2006
  • Viscoelastic damping materials are widely used to reduce noise and vibration because of its low cost and easy implementation, for examples, on the body structure of passenger cars, air planes, electric appliances and ships. To design the damped structures, the material property such as elastic modulus and loss factor is essential information. The four-parameter fractional derivative model well describes the dynamic characteristics of the viscoelastic damping materials with respect to both frequency and temperature. However, the identification procedure of the four-parameter is very time-consuming one. In this study a new identification procedure of the four-parameters is proposed by using an FE model and a gradient-based numerical search algorithm. The identification procedure goes two sequential steps to make measured frequency response functions(FRF) coincident with simulated FRFs: the first one is a peak alignment step and the second one is an amplitude adjustment step. A numerical example shows that the proposed method is useful in identifying the viscoelastic material parameters of fractional derivative model.

Optimal reduction from an initial sensor deployment along the deck of a cable-stayed bridge

  • Casciati, F.;Casciati, S.;Elia, L.;Faravelli, L.
    • Smart Structures and Systems
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    • v.17 no.3
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    • pp.523-539
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    • 2016
  • The ambient vibration measurement is an output-data-only dynamic testing where natural excitations are represented, for instance, by winds and typhoons. The modal identification involving output-only measurements requires the use of specific modal identification techniques. This paper presents the application of a reliable method (the Stochastic Subspace Identification - SSI) implemented in a general purpose software. As a criterion toward the robustness of identified modes, a bio-inspired optimization algorithm, with a highly nonlinear objective function, is introduced in order to find the optimal deployment of a reduced number of sensors across a large civil engineering structure for the validation of its modal identification. The Ting Kau Bridge (TKB), one of the longest cable-stayed bridges situated in Hong Kong, is chosen as a case study. The results show that the proposed method catches eigenvalues and eigenvectors even for a reduced number of sensors, without any significant loss of accuracy.