• Title/Summary/Keyword: Input modeling

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Sketch-based Solid Prototype Modeling System with Dual Data Structure of Point-set Surfaces and Voxels

  • Takeuchi, Ryota;Watanabe, Taichi;Yamakawa, Soji
    • International Journal of CAD/CAM
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    • v.11 no.1
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    • pp.18-26
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    • 2011
  • This paper proposes a new solid-shape modeling system based on a lusterware-image illustration. The proposed method reconstructs a three dimensional solid shape from a set of rough sketches that are typically drawn in the early stages of the design process. The sketches do not have to be strictly accurate, and this tolerance to the roughness of the input sketches is one of the major advantages of the proposed method. The proposed system creates an initial shape based on the silhouette of the input lusterware-images. Then the user can edit the initial shape with intuitive cutting and dishing-up operations, which are based on sketching user interface. To achieve the goal, the system retains the geometric model with two representations: a point-set data and a volume data. This dual data structure allows the program to create an initial shape from the input images with little computational cost, and the user can apply cutting and dishing-up operations without substantially increasing computational and memory requirements. In this research, we have tested the proposed system by reconstructing solid models of some mechanical parts from rough sketches. The experimental results indicate that the proposed method is useful for the prototyping of a solid shape.

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Stochastic identification of masonry parameters in 2D finite elements continuum models

  • Giada Bartolini;Anna De Falco;Filippo Landi
    • Coupled systems mechanics
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    • v.12 no.5
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    • pp.429-444
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    • 2023
  • The comprehension and structural modeling of masonry constructions is fundamental to safeguard the integrity of built cultural assets and intervene through adequate actions, especially in earthquake-prone regions. Despite the availability of several modeling strategies and modern computing power, modeling masonry remains a great challenge because of still demanding computational efforts, constraints in performing destructive or semi-destructive in-situ tests, and material uncertainties. This paper investigates the shear behavior of masonry walls by applying a plane-stress FE continuum model with the Modified Masonry-like Material (MMLM). Epistemic uncertainty affecting input parameters of the MMLM is considered in a probabilistic framework. After appointing a suitable probability density function to input quantities according to prior engineering knowledge, uncertainties are propagated to outputs relying on gPCE-based surrogate models to considerably speed up the forward problem-solving. The sensitivity of the response to input parameters is evaluated through the computation of Sobol' indices pointing out the parameters more worthy to be further investigated, when dealing with the seismic assessment of masonry buildings. Finally, masonry mechanical properties are calibrated in a probabilistic setting with the Bayesian approach to the inverse problem based on the available measurements obtained from the experimental load-displacement curves provided by shear compression in-situ tests.

A Study on Validity of Applying Simplify modeling Method for Heating/Cooling Load Calculation (냉난방부하 계산의 단순화 모델링 기법 적용 타당성 검토에 관한 연구)

  • Kang, Yoon-Suk;Park, Jong-Il;Ihm, Pyeong-Chan
    • Proceedings of the SAREK Conference
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    • 2008.06a
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    • pp.1386-1391
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    • 2008
  • As the time goes by, the energy use in buildings are increasing threateningly. So, it is important to have an accurate energy load calculation for buildings. The accurate energy simulation program carries numerous input data. So, our purpose of this study is to verify the application of simplify modeling method which eliminates coordinates of building components instead of using full coordinates by using DOE2. After comparing original modeling method with simplify modeling method, we applied PAF for daylighting control in the building to verify the application of daylighting control in simplify modeling method. The results shows that there are little difference between original modeling and simplify modeling. Also it showed that application of daylighting control has little difference between original modeling so it is feasible to adapt simplify modeling. These results reveals that the application of simplify modeling is possible to predict energy load and use of the building.

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Analysis of Sensitivity, Correlation Coefficient and PCA of Input and Output Parameters using Fire Modeling (화재모델링을 이용한 입출력 변수의 민감도, 상관계수 분석과 주성분 분석)

  • Nam, Gi Tae;Kim, Jeong Jin;Yoon, Seok Pyo;Kim, Jun Kyoung
    • Journal of the Korean Society of Safety
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    • v.34 no.5
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    • pp.46-54
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    • 2019
  • Even though the fire performance-based design concept has been introduced for various structures and buildings, which have their own specific fire performance level, the uncertainties of input parameters always exist and, then, could reduce significantly the reliability of the fire modeling. Sensitivity analysis was performed with three limited input parameters, HRRPUA, type of combustible materials, and mesh size, which are significantly important for fire modeling. The output variables are limited to the maximum HRR, the time reaching the reference temperature($60^{\circ}C$), and that to reach limited visible distance(5 m). In addition, correlation coefficient analysis was attempted to analyze qualitatively and quantitatively the degree of relation between input and output variables above. Finally, the relationship among the three variables is also analyzed by the principal component analysis (PCA) to systematically analyze the input data bias. Sensitivity analysis showed that the type of combustible materials is more sensitive to maximum HRR than the ignition source and mesh size. However, the heat release parameter of the ignition source(HRR) is shown to be much more sensitive than the combustible material types and mesh size to both time to reach the reference temperature and that to reach the critical visible distance. Since the derived results can not exclude the possibility that there is a dependency on the fire model applied in this study, it is necessary to generalize and standardize the results of this study for the fire models such as various buildings and structures.

The Development of Interface technology Between 3D Modeling Data and Cable Engineering Program Data (전선로 3D Modeling 데이터와 케이블 엔지니어링 데이터의 연계 기술개발)

  • Cho, Sung-Don;Yoo, Gi-Hong;Kim, Soon-Goo
    • Proceedings of the KIEE Conference
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    • 2007.07a
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    • pp.400-401
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    • 2007
  • 3D Modeling S/W인 PDS(Plant Design System)의 Electrical Raceway Modeling Software인 EE-Raceway로 작성된 DB에서 트레이, 트레이 Link, Fitting 데이터를 추출하여 케이블 엔지니어링 프로그램의 Input 자료로 활용하는 연계기술과 활용에 대하여 소개하고자 한다

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Relationship among Degree of Time-delay, Input Variables, and Model Predictability in the Development Process of Non-linear Ecological Model in a River Ecosystem (비선형 시계열 하천생태모형 개발과정 중 시간지연단계와 입력변수, 모형 예측성 간 관계평가)

  • Jeong, Kwang-Seuk;Kim, Dong-Kyun;Yoon, Ju-Duk;La, Geung-Hwan;Kim, Hyun-Woo;Joo, Gea-Jae
    • Korean Journal of Ecology and Environment
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    • v.43 no.1
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    • pp.161-167
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    • 2010
  • In this study, we implemented an experimental approach of ecological model development in order to emphasize the importance of input variable selection with respect to time-delayed arrangement between input and output variables. Time-series modeling requires relevant input variable selection for the prediction of a specific output variable (e.g. density of a species). Inadequate variable utility for input often causes increase of model construction time and low efficiency of developed model when applied to real world representation. Therefore, for future prediction, researchers have to decide number of time-delay (e.g. months, weeks or days; t-n) to predict a certain phenomenon at current time t. We prepared a total of 3,900 equation models produced by Time-Series Optimized Genetic Programming (TSOGP) algorithm, for the prediction of monthly averaged density of a potamic phytoplankton species Stephanodiscus hantzschii, considering future prediction from 0- (no future prediction) to 12-months ahead (interval by 1 month; 300 equations per each month-delay). From the investigation of model structure, input variable selectivity was obviously affected by the time-delay arrangement, and the model predictability was related with the type of input variables. From the results, we can conclude that, although Machine Learning (ML) algorithms which have popularly been used in Ecological Informatics (EI) provide high performance in future prediction of ecological entities, the efficiency of models would be lowered unless relevant input variables are selectively used.

(Context-based Annotation for Pen Input Device Environment) (펜 입력 장치 환경을 고려한 컨텍스트 기반 Annotation)

  • 김재경;손원성;임순범;최윤철
    • Journal of KIISE:Software and Applications
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    • v.30 no.5_6
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    • pp.559-569
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    • 2003
  • Annotation is used for inscribing personal opinion, explanation, and summary. Various methods for processing annotation efficiently in digital document environments are being studied. However, previous studies placed much emphasis on function of annotation, so either they did not support Intuitive paper-based input interface or the systems that support it still have low reusability problems, because relation between annotation and original document are not explicit. Thus, in our study, we define context-based annotation modeling for digital document environments, and suggest annotation interface based on the modeling. To design annotation model, we define annotation types, context information of document, and relationship between annotation and original document. Also, a system based on the modeling is implemented to support pen-based annotation and annotation DTD. As a result, unlike previous studies, it is possible to explicitly define context-based annotation in pen-based input environments. We present various functions using the modeling and various possibilities of application.

Probabilistic Modeling of Photovoltaic Power Systems with Big Learning Data Sets (대용량 학습 데이터를 갖는 태양광 발전 시스템의 확률론적 모델링)

  • Cho, Hyun Cheol;Jung, Young Jin
    • Journal of the Korean Institute of Intelligent Systems
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    • v.23 no.5
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    • pp.412-417
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    • 2013
  • Analytical modeling of photovoltaic power systems has been receiving significant attentions in recent years in that it is easy to apply for prediction of its dynamics and fault detection and diagnosis in advanced engineering technologies. This paper presents a novel probabilistic modeling approach for such power systems with a big data sequence. Firstly, we express input/output function of photovoltaic power systems in which solar irradiation and ambient temperature are regarded as input variable and electric power is output variable respectively. Based on this functional relationship, conditional probability for these three random variables(such as irradiation, temperature, and electric power) is mathematically defined and its estimation is accomplished from ratio of numbers of all sample data to numbers of cases related to two input variables, which is efficient in particular for a big data sequence of photovoltaic powers systems. Lastly, we predict the output values from a probabilistic model of photovoltaic power systems by using the expectation theory. Two case studies are carried out for testing reliability of the proposed modeling methodology in this paper.

Modeling of a linear GMR Isolator Utilizing Spin Valves (스핀밸브를 이용한 선형 GMR 아이솔레이터의 모델링)

  • Park, S.;Jo, S.
    • Journal of the Korean Magnetics Society
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    • v.14 no.6
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    • pp.232-235
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    • 2004
  • Linear GMR isolator which is profitable for transmitting analog signal was modeled and the output voltage and current in relation to the input current were investigated. GMR isolator modeling was divided into two parts, namely magnetic and electric parts. The flow chart of the modeling was drawn in which the MR curve of the spin valves were incorporated to obtain the electrical voltage output. For magnetic modeling, 3-dimensional model of planar coil was analyzed by FEM method to obtain the magnetic field strength corresponding to the input current. Coil efficiency of the planar coil having magnetic core layer was shown to have about 1.5 times larger than that of the coil without the magnetic core layer. The feedback coil current(output current) corresponding to the input coil current was calculated to be within ${\pm}$0.25 mA of the linear fitting function of I$\_$out/= I$\_$in/-5 mA. Also, the response time and output waveforms were obtained when the coil current was a rectangular waveform. The rise time and fall time was 6 ${\mu}\textrm{s}$, respectively when the slew rate of the op-amp was 0.3 V/${\mu}\textrm{s}$.

The influence of vertical ground motion on the seismic behavior of RC frame with construction joints

  • Yu, Jing;Liu, Xiaojun
    • Earthquakes and Structures
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    • v.11 no.3
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    • pp.407-420
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    • 2016
  • The aim of this study is to investigate the effect of vertical ground motion (VGM) on seismic behavior of reinforced concrete (RC) regular frame with construction joints, and determine more proper modeling method for cast-in-situ RC frame. The four-story RC frames in the regions of 7, 8 and 9 earthquake intensity were analyzed with nonlinear dynamic time-history method. Two different methods of ground motion input, horizontal ground motion (HGM) input only, VGM and HGM input simultaneously were performed. Seismic responses in terms of the maximum vertex displacement, the maximum inter-story drift distribution and the plastic hinge distribution were analyzed. The results show that VGM might increase or decrease the horizontal maximum vertex displacement depending on the value of axial load ratio of column. And it will increase the maximum inter-story drift and change its distribution. Finally, proper modeling method is proposed according to the distribution of plastic hinges, which is in well agreement with the actual earthquake damage.