• Title/Summary/Keyword: Structural Feature

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Thermal denaturation analysis of protein

  • Miyazawa, Mitsuhiro
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1628-1628
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    • 2001
  • Near infrared (NIR) spectroscopy is a powerful technique for non-destructive analysis that can be obtained in a wide range of environments. Recently, NIR measurements have been utilized as probe for quantitative analysis in agricultural, industrial, and medical sciences. In addition, it is also possible to make practical application on NIR for molecular structural analysis. In this work, Fourier transform near infrared (FT-NIR) measurements were carried out to utilize extensively in the relative amounts of different secondary structures were employed, such as Iysozyme, concanavalin A, silk fibroin and so on. Several broad NIR bands due to the protein absorption were observed between 4000 and $5000\;^{-1}$. In order to obtain more structural information from these featureless bands, second derivative and Fourier-self-deconvolution procedures were performed. Significant band separation was observed near the feature at $4610\;^{-1}$ ,. Particularly the peak intensity at $4525\;^{-1}$ shows a characteristic change with thermal denaturation of fibroin. The structural information can be also obtained by mid-IR and CD spectral. Correlation of NIR spectra with protein structure is discussed.

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Automatic Generation of Orthogonal Arrays and Its Application to a Two-Step Structural Optimization (실험에 적합한 직교 배열표의 자동 생성 및 2 단계 구조 최적화에의 적용)

  • 이수범;곽병만
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.27 no.12
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    • pp.2047-2054
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    • 2003
  • In this paper, an approach of automatically finding and modifying the most appropriate orthogonal array (GO) is suggested and applied to a new structural optimization procedure with two steps. GO is motivated by the situation where finding a proper orthogonal array from the tables in the literature is difficult or impossible. Now the Taguchi method is made available for various numbers of variables and levels. In the two-step structural optimization, the Taguchi method equipped with GO and a shape optimization using the finite differencing method is consecutively applied. The existence or non-existence of an element can be taken as a factor level and this feature is utilized finding the best topology from a set of potential topologies suggested from the user's expertise. This greatly enhances applicability and one can expect a better result than the case in which each step is applied independently because these steps are complementary each other.

Nonlinear programming approach for a class of inverse problems in elastoplasticity

  • Ferris, M.C.;Tin-Loi, F.
    • Structural Engineering and Mechanics
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    • v.6 no.8
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    • pp.857-870
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    • 1998
  • This paper deals with a special class of inverse problems in discrete structural plasticity involving the identification of elastic limits and hardening moduli on the basis of information on displacements. The governing equations lead naturally to a special and challenging optimization problem known as a Mathematical Program with Equilibrium Constraints (MPEC), a key feature of which is the orthogonality of two sign-constrained vectors or so-called "complementarity" condition. We investigate numerically the application of two simple algorithms, both based on the use of the general purpose nonlinear programming code CONOPT accessed via the GAMS modeling language, for solving the suitably reformulated problem. Application is illustrated by means of two numerical examples.

The Cross Section Optimization of P.C Box-Girder Bridge Constructed by Free Cantilever Method (FCM 으로 가설되는 P.C 박스거더교의 횡단면 최적설계)

  • 방명석;김일곤;조현준
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1991.04a
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    • pp.56-60
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    • 1991
  • Free Cantilever Method(FCM) is one of the most effective construction methods when precast prestressed concrete box girders are erected in the construction site. The special feature of FCM is that precast segments are erected in cantilever on the pier and connected in the middle of span to form the complete superstructure. Therefore each structural subsystem will be shown in each construction step and it should be analyzed for design whenever the segment is erected. In this study, the computer program was developed to optimally design the P.C box girder bridge considering tile construction sequence and verified by comparing the calculated results with the data of existing P.C box girder bridges. the sensitivity analysis was performed to show the efficiency of the developed program.

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ANN-based Real-Time Damage Detection Algorithm using Output-only Acceleration Signals (가속도를 이용한 인공신경망 기반 실시간 손상검색기법)

  • Kim, Jung-Tae;Park, Jae-Hyung;Do, Han-Sung
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2007.04a
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    • pp.43-48
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    • 2007
  • In this study, an ANN-based damage detection algorithm using acceleration signals is developed for alarming locations of damage in beam-type structures. A new ANN-algorithm using output-only acceleration responses is designed for damage detection in real time. The cross-covariance of two acceleration signals measured at two different locations is selected as the feature representing the structural condition. Neural networks are trained for potential loading patterns and damage scenarios of the target structure for which its actual loadings are unknown. The feasibility and practicality of the proposed method are evaluated from laboratory-model tests on free-free beams for which accelerations were measured before and after several damage cases.

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Performance of Feature-based Stitching Algorithms for Multiple Images Captured by Tunnel Scanning System (터널 스캐닝 다중 촬영 영상의 특징점 기반 접합 알고리즘 성능평가)

  • Lee, Tae-Hee;Park, Jin-Tae;Lee, Seung-Hun;Park, Sin-Zeon
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.26 no.5
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    • pp.30-42
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    • 2022
  • Due to the increase in construction of tunnels, the burdens of maintenance works for tunnel structures have been increasing in Korea. In addition, the increase of traffic volume and aging of materials also threatens the safety of tunnel facilities, therefore, maintenance costs are expected to increase significantly in the future. Accordingly, automated condition assessment technologies like image-based tunnel scanning system for inspection and diagnosis of tunnel facilities have been proposed. For image-based tunnel scanning system, it is key to create a planar image through stitching of multiple images captured by tunnel scanning system. In this study, performance of feature-based stitching algorithms suitable for stitching tunnel scanning images was evaluated. In order to find a suitable algorithm SIFT, ORB, and BRISK are compared. The performance of the proposed algorithm was determined by the number of feature extraction, calculation speed, accuracy of feature matching, and image stitching result. As for stitching performance, SIFT algorithm was the best in all parts of tunnel image. ORB and BRISK also showed satisfactory performance and short calculation time. SIFT can be used to generate precise planar images. ORB and BRISK also showed satisfactory stitching results, confirming the possibility of being used when real-time stitching is required.

Structural Characteristic Analysis of an Ultra-Precision Machine for Machining Large-Surface Micro-Features (초정밀 대면적 미세 형상 가공기의 구조 특성 해석)

  • Kim, Seok-ll;Lee, Won-Jae
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.31 no.12
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    • pp.1173-1179
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    • 2007
  • In recent years, research to machine large-surface micro-features has become important because of the light guide panel of a large-scale liquid crystal display and the bipolar plate of a high-capacity proton exchange membrane fuel cell. In this study, in order to realize the systematic design technology and performance improvements of an ultra-precision machine for machining the large-surface micro-features, a structural characteristic analysis was performed using its virtual prototype. The prototype consisted of gantry-type frame, hydrostatic feed mechanisms, linear motors, brushless DC servo motor, counterbalance mechanism, and so on. The loop stiffness was estimated from the relative displacement between the tool post and C-axis table, which was caused by a cutting force. Especially, the causes of structural stiffness deterioration were identified through the structural deformation analysis of sub-models.

An eigenspace projection clustering method for structural damage detection

  • Zhu, Jun-Hua;Yu, Ling;Yu, Li-Li
    • Structural Engineering and Mechanics
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    • v.44 no.2
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    • pp.179-196
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    • 2012
  • An eigenspace projection clustering method is proposed for structural damage detection by combining projection algorithm and fuzzy clustering technique. The integrated procedure includes data selection, data normalization, projection, damage feature extraction, and clustering algorithm to structural damage assessment. The frequency response functions (FRFs) of the healthy and the damaged structure are used as initial data, median values of the projections are considered as damage features, and the fuzzy c-means (FCM) algorithm are used to categorize these features. The performance of the proposed method has been validated using a three-story frame structure built and tested by Los Alamos National Laboratory, USA. Two projection algorithms, namely principal component analysis (PCA) and kernel principal component analysis (KPCA), are compared for better extraction of damage features, further six kinds of distances adopted in FCM process are studied and discussed. The illustrated results reveal that the distance selection depends on the distribution of features. For the optimal choice of projections, it is recommended that the Cosine distance is used for the PCA while the Seuclidean distance and the Cityblock distance suitably used for the KPCA. The PCA method is recommended when a large amount of data need to be processed due to its higher correct decisions and less computational costs.

Versatile robotic platform for structural health monitoring and surveillance

  • Esser, Brian;Huston, Dryver R.
    • Smart Structures and Systems
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    • v.1 no.4
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    • pp.325-338
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    • 2005
  • Utilizing robotic based reconfigurable nodal structural health monitoring systems has many advantages over static or human positioned sensor systems. However, creating a robot capable of traversing a variety of civil infrastructures is a difficult task, as these structures each have unique features and characteristics posing a variety of challenges to the robot design. This paper outlines the design and implementation of a novel robotic platform for deployment on ferromagnetic structures as an enabling structural health monitoring technology. The key feature of this design is the utilization of an attachment device which is an advancement of the common magnetic base found in the machine tool industry. By mechanizing this switchable magnetic circuit and redesigning it for light weight and compactness, it becomes an extremely efficient and robust means of attachment for use in various robotic and structural health monitoring applications. The ability to engage and disengage the magnet as needed, the very low power required to do so, the variety of applicable geometric configurations, and the ability to hold indefinitely once engaged make this device ideally suited for numerous robotic and distributed sensor network applications. Presented here are examples of the mechanized variable force magnets, as well as a prototype robot which has been successfully deployed on a large construction site. Also presented are other applications and future directions of this technology.

Kernelized Structure Feature for Discriminating Meaningful Table from Decorative Table (장식 테이블과 의미 있는 테이블 식별을 위한 커널 기반의 구조 자질)

  • Son, Jeong-Woo;Go, Jun-Ho;Park, Seong-Bae;Kim, Kweon-Yang
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.5
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    • pp.618-623
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    • 2011
  • This paper proposes a novel method to discriminate meaningful tables from decorative one using a composite kernel for handling structural information of tables. In this paper, structural information of a table is extracted with two types of parse trees: context tree and table tree. A context tree contains structural information around a table, while a table tree presents structural information within a table. A composite kernel is proposed to efficiently handle these two types of trees based on a parse tree kernel. The support vector machines with the proposed kernel dised kuish meaningful tables from the decorative ones with rich structural information.