• Title/Summary/Keyword: multi-component data

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Realistic simulation of reinforced concrete structural systems with combine of simplified and rigorous component model

  • Chen, Hung-Ming;Iranata, Data
    • Structural Engineering and Mechanics
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    • v.30 no.5
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    • pp.619-645
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    • 2008
  • This study presents the efficiency of simulating structural systems using a method that combines a simplified component model (SCM) and rigorous component model (RCM). To achieve a realistic simulation of structural systems, a numerical model must be adequately capturing the detailed behaviors of real systems at various scales. However, capturing all details represented within an entire structural system by very fine meshes is practically impossible due to technological limitations on computational engineering. Therefore, this research develops an approach to simulate large-scale structural systems that combines a simplified global model with multiple detailed component models adjusted to various scales. Each correlated multi-scale simulation model is linked to others using a multi-level hierarchical modeling simulation method. Simulations are performed using nonlinear finite element analysis. The proposed method is applied in an analysis of a simple reinforced concrete structure and the Reuipu Elementary School (an existing structure), with analysis results then compared to actual onsite observations. The proposed method obtained results very close to onsite observations, indicating the efficiency of the proposed model in simulating structural system behavior.

Multi-axial Vibration Test on MAST System with Field Data (국내도로 주행 시험을 통한 6축 진동시험 방법에 관한 연구)

  • Kim, Chan-Jung;Bae, Chul-Yong;Lee, Bang-Hyun;Kwon, Seong-Jin;Na, Byung-Chul
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.16 no.7 s.112
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    • pp.704-711
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    • 2006
  • Vibration test on MAST(multi axial simulation table) system has several advantage over one-axial vibration test that could simulate 6-DOF, 3-axial translation and 3-axial moment, at the same time. Since field vibration motion can be fully represented with 6-DOF, multi-axial vibration test on vehicle component is widely conducted in technical leading companies to make sure its fatigue performance in vibration environment. On the way to fulfill the process, editing technique of obtained field data is key issue to success a reliable vibration testing with MAST system. Since the original signals are not only too large to fulfill it directly, but all of the measured data is not guarantee its convergency on generating its driving files, editing technique of the original signals are highly required to make some events that should meet the equal fatigue damage on the target component In this paper, key technique on editing a field data feasible for MAST system is described based on energy method in vibration fatigue. To explain its technique explicitly, author first introduced a process on field data acquisition of two vehicle component and then, representing events are produced to keep up with the editing strategy about a energy method. In the final chapter, a time information regarding a vibration test on MAST system is derived from the energy data which is critical information to perform a vibration test.

Retrieving Land surface Component Temperature Using Multi-Angle Thermal Infrared Data

  • Wenjie, Fan;Xiru, Xu
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.1362-1364
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    • 2003
  • As non-isothermal mixed pixel is widely existed, the pixel-mean temperature cannot adequately represent the actual thermal state of land surface. The row crop was chosen as target to discuss the problem of component temperature retrieval. At first, the matrix model was found to express the thermal radiant directionality of the target. Then correlation of multi-angle infrared radiance was analyzed. In order to increase the retrieving accuracy, we chose the retrievable parameters and established the iterative method combining with inverse matrix to retrieve component temperature. It was proved by field experiment that the method could improve the retrieving accuracy and stability remarkably.

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A Study on Matching Pursuit Interpolation with Moveout Correction (시간차 보정을 적용한 Matching Pursuit 내삽 기법 연구)

  • Lee, Jaekang;Byun, Joongmoo;Seol, Soon Jee;Kim, Young
    • Geophysics and Geophysical Exploration
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    • v.21 no.2
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    • pp.103-111
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    • 2018
  • The recent research aim of seismic trace interpolation is to effectively interpolate the data with spatial aliasing. Among various interpolation methods, the Matching Pursuit interpolation, that finds the proper combination of basis functions which can best recover traces, has been developed. However, this method cannot interpolate aliased data. Thus, the multi-component Matching Pursuit interpolation and moveout correction method have been proposed for interpolation of spatially aliased data. It is difficult to apply the multi-component Matching Pursuit interpolation to interpolating the OBC (Ocean Bottom Cable) data which is the multi-component data obtained at the ocean bottom because the isolation of P wave component is required in advance. Thus, in this study, we dealt with an effective single-component matching Pursuit interpolation method in OBC data where P-wave and S-wave are mixed and spatial aliasing is present. To do this, we proposed the Ricker wavelet based single-component Matching Pursuit interpolation workflow with moveoutcorrection and systematically investigated its effectiveness. In this workflow, the spatial aliasing problem is solved by applying constant value moveout correction to the data before the interpolation is performed. After finishing the interpolation, the inverse moveout correction is applied to the interpolated data using the same constant velocity. Through the application of our workflow to the synthetic OBC seismic data, we verified the effectiveness of the proposed workflow. In addition, we showed that the interpolation of field OBC data with severe spatial aliasing was successfully performed using our workflow.

Optimization of Data Placement using Principal Component Analysis based Pareto-optimal method for Multi-Cloud Storage Environment

  • Latha, V.L. Padma;Reddy, N. Sudhakar;Babu, A. Suresh
    • International Journal of Computer Science & Network Security
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    • v.21 no.12
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    • pp.248-256
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    • 2021
  • Now that we're in the big data era, data has taken on a new significance as the storage capacity has exploded from trillion bytes to petabytes at breakneck pace. As the use of cloud computing expands and becomes more commonly accepted, several businesses and institutions are opting to store their requests and data there. Cloud storage's concept of a nearly infinite storage resource pool makes data storage and access scalable and readily available. The majority of them, on the other hand, favour a single cloud because of the simplicity and inexpensive storage costs it offers in the near run. Cloud-based data storage, on the other hand, has concerns such as vendor lock-in, privacy leakage and unavailability. With geographically dispersed cloud storage providers, multicloud storage can alleviate these dangers. One of the key challenges in this storage system is to arrange user data in a cost-effective and high-availability manner. A multicloud storage architecture is given in this study. Next, a multi-objective optimization problem is defined to minimise total costs and maximise data availability at the same time, which can be solved using a technique based on the non-dominated sorting genetic algorithm II (NSGA-II) and obtain a set of non-dominated solutions known as the Pareto-optimal set.. When consumers can't pick from the Pareto-optimal set directly, a method based on Principal Component Analysis (PCA) is presented to find the best answer. To sum it all up, thorough tests based on a variety of real-world cloud storage scenarios have proven that the proposed method performs as expected.

Assessment of Water Quality using Multivariate Statistical Techniques: A Case Study of the Nakdong River Basin, Korea

  • Park, Seongmook;Kazama, Futaba;Lee, Shunhwa
    • Environmental Engineering Research
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    • v.19 no.3
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    • pp.197-203
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    • 2014
  • This study estimated spatial and seasonal variation of water quality to understand characteristics of Nakdong river basin, Korea. All together 11 parameters (discharge, water temperature, dissolved oxygen, 5-day biochemical oxygen demand, chemical oxygen demand, pH, suspended solids, electrical conductivity, total nitrogen, total phosphorus, and total organic carbon) at 22 different sites for the period of 2003-2011 were analyzed using multivariate statistical techniques (cluster analysis, principal component analysis and factor analysis). Hierarchical cluster analysis grouped whole river basin into three zones, i.e., relatively less polluted (LP), medium polluted (MP) and highly polluted (HP) based on similarity of water quality characteristics. The results of factor analysis/principal component analysis explained up to 83.0%, 81.7% and 82.7% of total variance in water quality data of LP, MP, and HP zones, respectively. The rotated components of PCA obtained from factor analysis indicate that the parameters responsible for water quality variations were mainly related to discharge and total pollution loads (non-point pollution source) in LP, MP and HP areas; organic and nutrient pollution in LP and HP zones; and temperature, DO and TN in LP zone. This study demonstrates the usefulness of multivariate statistical techniques for analysis and interpretation of multi-parameter, multi-location and multi-year data sets.

Design and Implementation of Query Classification Component in Multi-Level DBMS for Location Based Service (위치기반 서비스를 위한 다중레벨 DBMS에 질의 분류 컴포넌트의 설계 및 구현)

  • Jang Seok-Kyu;Eo Sang Hun;Kim Myung-Heun;Bae Hae-Young
    • The KIPS Transactions:PartD
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    • v.12D no.5 s.101
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    • pp.689-698
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    • 2005
  • Various systems are used to provide the location based services. But, the existing systems have some problems which have difficulties in dealing with faster services for above million people. In order to solve it, a multi-level DBMS which supports both fast data processing and large data management support should be used. The multi-level DBMS with snapshots has all the data existing in disk database and the data which are required to be processed for fast processing are managed in main memory database as snapshots. To optimize performance of this system for location based services, the query classification component which classifies the queries for efficient snapshot usage is needed. In this paper, the query classification component in multi-level DBMS for location based services is designed and implemented. The proposed component classifies queries into three types: (1) memory query, (2) disk query, (3) hybrid query, and increases the rate of snapshot usage. In addition, it applies division mechanisms which divide aspatial and spatial filter condition for partial snapshot usage. Hence, the proposed component enhances system performance by maximizing the usage of snapshot as a result of the efficient query classification.

Software Development for the Analysis and Prediction of Packing Density of Multi-sized Mixture Particles (Multi-sized 혼합입자의 충전 분율 해석 및 예측을 위한 소프트웨어 개발)

  • Oh, Min;Hong, Seong Uk
    • Applied Chemistry for Engineering
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    • v.18 no.6
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    • pp.636-642
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    • 2007
  • Software program to predict the packing density of multi-sized and multi-component particulate system was developed. For this purpose, the experiment to measure the packing density of AP (ammonium perchlorate) and Al (aluminum) particles with different sizes and their mixtures was carried out. The packing densities obtained from various experiments were compared with the predicted data from the developed software program. In the case of the packing density of the binary system, which is comprised of two different size particles and/or two different components, the relative errors were ranged 0.25~13.13%, and in the same venue the relative errors of the ternary system were 0.25~13.13%. Agreement between experimental data and the predicted results is reasonably accurate. In order to achieve the targeted packing density, the software program calculated the contour of the component particles and this will contribute the formulation of optimal packing systems.

MAST Vibration on MAST System with Field Data (국내도로 주행 시험을 통한 6축 진동시험 방법에 관한 연구)

  • Kim, Chan-Jung;Bae, Chul-Yong;Lee, Bong-Hyun;Kwon, Seong-Jin;Na, Byung-Chul
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2006.05a
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    • pp.764-769
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    • 2006
  • Vibration test on MAST(multi axial simulation table) system has several advantage over one-axial vibration test that could simulate 6-DOF, 3-axial translation and 3-axial moment, at the same time. Since field vibration motion can be fully represented with 6-DOF, multi-axial vibration test on vehicle component is widely conducted in technical leading companies to make sure its fatigue performance in vibration environment. On the way to fulfill the process, editing technique of obtained field data is key issue to success a reliable vibration testing with MAST system. Since the original signals are not only too large to fulfill it directly, but all of the measured data is not guarantee its convergency on generating its driving files, editing technique of the original signals are highly required to make some events that should meet the equal fatigue damage on the target component In this paper, key technique on editing a field data feasible for MAST system is described based on energy method in vibration fatigue. To explain its technique explicitly, author first introduced a process on field data acquisition of two vehicle component and then, representing events are produced to keep up with the editing strategy about a energy method. In the final chapter, a time information regarding a vibration test on MAST system is derived from the energy data which is critical information to perform a vibration test.

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Robust group independent component analysis (로버스트 그룹 독립성분분석)

  • Kim, Hyunsung;Li, XiongZhu;Lim, Yaeji
    • The Korean Journal of Applied Statistics
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    • v.34 no.2
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    • pp.127-139
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    • 2021
  • Independent Component Analysis is a popular statistical method to separate independent signals from the mixed data, and Group Independent Component Analysis is an its multi-subject extension of Independent Component Analysis. It has been applied Functional Magnetic Resonance Imaging data and provides promising results. However, classical Group Independent Component Analysis works poorly when outliers exist on data which is frequently occurred in Magnetic Resonance Imaging scanning. In this study, we propose a robust version of the Group Independent Component Analysis based on ROBPCA. Through the numerical studies, we compare proposed method to the conventional method, and verify the robustness of the proposed method.