• Title/Summary/Keyword: Growth Prediction

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Effect of Temper-Embrittlement on Surface Crack Growth and Fatigue Life Prediction (재질열화가 표면 균열 진전에 미치는 영향과 수명 예측에 관한 연구)

  • 권재도
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.13 no.5
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    • pp.921-927
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    • 1989
  • One of the most important problems in recent life prediction is to introduce the degradation effects into life prediction procedure. In the present paper, the effect of the material degradation on the fatigue surface crack growth and fatigue life prediction in a 2 1/4 Cr-1Mo steel were investigated. The 2 1/4 Cr-1Mo steel has been used in a plant having operated for over 60000hours and subjected to material degradation due to temper-embitterment. A Monte-Carlo simulation was made on the basis of the data obtained in the experiment in order to determine the P-S-N diagrams of surface crack growth for the degraded and recovered steels.

Estimation of Coverage Growth Functions

  • Park, Joong-Yang;Lee, Gye-Min;Kim, Seo-Yeong
    • Communications for Statistical Applications and Methods
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    • v.18 no.5
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    • pp.667-674
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    • 2011
  • A recent trend in software reliability engineering accounts for the coverage growth behavior during testing. The coverage growth function (representing the coverage growth behavior) has become an essential component of software reliability models. Application of a coverage growth function requires the estimation of the coverage growth function. This paper considers the problem of estimating the coverage growth function. The existing maximum likelihood method is reviewed and corrected. A method of minimizing the sum of squares of the standardized prediction error is proposed for situations where the maximum likelihood method is not applicable.

Land Use Feature Extraction and Sprawl Development Prediction from Quickbird Satellite Imagery Using Dempster-Shafer and Land Transformation Model

  • Saharkhiz, Maryam Adel;Pradhan, Biswajeet;Rizeei, Hossein Mojaddadi;Jung, Hyung-Sup
    • Korean Journal of Remote Sensing
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    • v.36 no.1
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    • pp.15-27
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    • 2020
  • Accurate knowledge of land use/land cover (LULC) features and their relative changes over upon the time are essential for sustainable urban management. Urban sprawl growth has been always also a worldwide concern that needs to carefully monitor particularly in a developing country where unplanned building constriction has been expanding at a high rate. Recently, remotely sensed imageries with a very high spatial/spectral resolution and state of the art machine learning approaches sent the urban classification and growth monitoring to a higher level. In this research, we classified the Quickbird satellite imagery by object-based image analysis of Dempster-Shafer (OBIA-DS) for the years of 2002 and 2015 at Karbala-Iraq. The real LULC changes including, residential sprawl expansion, amongst these years, were identified via change detection procedure. In accordance with extracted features of LULC and detected trend of urban pattern, the future LULC dynamic was simulated by using land transformation model (LTM) in geospatial information system (GIS) platform. Both classification and prediction stages were successfully validated using ground control points (GCPs) through accuracy assessment metric of Kappa coefficient that indicated 0.87 and 0.91 for 2002 and 2015 classification as well as 0.79 for prediction part. Detail results revealed a substantial growth in building over fifteen years that mostly replaced by agriculture and orchard field. The prediction scenario of LULC sprawl development for 2030 revealed a substantial decline in green and agriculture land as well as an extensive increment in build-up area especially at the countryside of the city without following the residential pattern standard. The proposed method helps urban decision-makers to identify the detail temporal-spatial growth pattern of highly populated cities like Karbala. Additionally, the results of this study can be considered as a probable future map in order to design enough future social services and amenities for the local inhabitants.

TGC-based Fish Growth Estimation Model using Gaussian Process Regression Approach (가우시안 프로세스 회귀를 통한 열 성장 계수 기반의 어류 성장 예측 모델)

  • Juhyoung Sung;Sungyoon Cho;Da-Eun Jung;Jongwon Kim;Jeonghwan Park;Kiwon Kwon;Young Myoung Ko
    • Journal of Internet Computing and Services
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    • v.24 no.1
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    • pp.61-69
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    • 2023
  • Recently, as the fishery resources are depleted, expectations for productivity improvement by 'rearing fishery' in land farms are greatly rising. In the case of land farms, unlike ocean environments, it is easy to control and manage environmental and breeding factors, and has the advantage of being able to adjust production according to the production plan. On the other hand, unlike in the natural environment, there is a disadvantage in that operation costs may significantly increase due to the artificial management for fish growth. Therefore, profit maximization can be pursued by efficiently operating the farm in accordance with the planned target shipment. In order to operate such an efficient farm and nurture fish, an accurate growth prediction model according to the target fish species is absolutely required. Most of the growth prediction models are mainly numerical results based on statistical analysis using farm data. In this paper, we present a growth prediction model from a stochastic point of view to overcome the difficulties in securing data and the difficulty in providing quantitative expected values for inaccuracies that existing growth prediction models from a statistical point of view may have. For a stochastic approach, modeling is performed by introducing a Gaussian process regression method based on water temperature, which is the most important factor in positive growth. From the corresponding results, it is expected that it will be able to provide reference values for more efficient farm operation by simultaneously providing the average value of the predicted growth value at a specific point in time and the confidence interval for that value.

A Study on Effects of the Residual Stresses Around Cold Working Hole of the Aircraft Structure (항공기 구조물의 체결용 HOLE을 COLD WORKING 할때 생성되는 잔류응력의 영향연구)

  • 강수준;최청호
    • Journal of the Korea Institute of Military Science and Technology
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    • v.2 no.1
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    • pp.101-109
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    • 1999
  • The objective of this research is to study effects of the residual stresses on the crack growth and the life of the structure, caused by cold working around the hole of the aircraft structure which will be jointed by rivets and bolts, etc. The compensated Morrow's equation, by experimental data from the materials AL7075-T6 and AL2024-T3, is suggested to calculate the values of the fatigue life prediction of the structure. Also, the compensated Forman's equation, by experimental data from a material AL7075-T6, is suggested to calculate the values of the crack growth prediction of the structure. It is founded that the calculated values from the suggested equations are almost close to the known values of the fatigue life prediction and the crack growth prediction. It is shown that this paper, associated with an initial research on the effects of residual stresses around hole, gives a direction to study the problem at the aircraft maintenance field.

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A Study on Prediction of Crack growth Rate Under Creep-Fatigue Interaction (크리이프-피로 상호작용하의 균열성장속도 예측에 관한 연구)

  • Joo, Won-Sik;Cho, Seok-Swoo
    • Journal of Ocean Engineering and Technology
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    • v.9 no.2
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    • pp.98-111
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    • 1995
  • High temperature low cycle fatigue shows that cycle-dependent crack growth owing to cyclic plastic deformation occurred simultaneosly with time-dependent crack growth owing to intergranular deformation. Consequently, to estimate crack growth rate uniquely, many to investigators have proposed various kinds of parameters and theories but these could not produce satisfactory results. Therefore the goal of this study is focused on prediction of crack growth rate using predominant damage rule, linear cumulative damage rule and transitional parameter ${\Delta}J_c/{\Delta}J_f$. On the basis of these sinusoidal loading waveform at 600$^{\circ}C$ and 700$^{\circ}C$.

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An Observation Supporting System for Predicting Citrus Fruit Production

  • Kang, Hee Joo;Yoo, Seung Tae;Yang, Young Jin
    • Agribusiness and Information Management
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    • v.7 no.1
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    • pp.1-9
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    • 2015
  • The purpose of this study is to develop a growth prediction model that can predict growth and development information influencing the production of citrus fruits: the growth model algorithm that can predict floral leaf ratio, number of fruit sets, fruit width, and overweight depending on the main period of growth and development with consideration of the applied weather factors. Every year, large scale of manpower was mobilized to investigate the production of outdoor-grown citrus fruits, but it was limited to recycling the data without an observation supporting system to systemize the database. This study intends to create a systematical database based on the basic data obtained through the observation supporting system in application of an algorithm according to the accumulated long term data and prepare a base for its continuous improvement and development. The importance of the observed data is increasingly recognized every year, and the citrus fruit observation supporting system is important for utilizing an effective policy and decision making according to various applications and analysis results through an interconnection and an integration of the investigated statistical data. The citrus fruit is a representative crop having a great ripple effect in Jeju agriculture. An early prediction of the growth and development information influencing the production of citrus fruits may be helpful for decision making in supply and demand control of agricultural products.

Development of Diameter Growth and Mortality Prediction Models of Pinus Koraiensis Based on Periodic Annual Increment (정기평균생장을 이용한 잣나무 임분의 흉고직경 생장예측모델 및 고사예측모델의 개발)

  • Kim, Seonyoung;Seol, Ara;Chung, Joosang
    • Journal of Korean Society of Forest Science
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    • v.100 no.1
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    • pp.1-7
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    • 2011
  • The objective of this study was to improve the performance of the existing individual-tree/distantindependent stand growth model in predicting the growth of Pinus koraiensis forest stands. The parameters of diameter growth and mortality prediction models were estimated using periodic annual increment (PAI) of permanent plots and the performance of the models were compared with that of the existing ones using mean anuual increment (MAI). The diameter growth model includes crown ratio, potential diameter growth and modifier to compute for competitions of trees of a stand. In deriving the mortality prediction model, the parameters were estimated based on PAI which was also estimated as the function of MAI due to the lacking of permanent plot data. The results of this study showed that the newly-estimated functions based on PAI provide more realistic patterns in diameter growth of individual trees. The new approach using PAI in mortality model seems to overcome the over-estimate problem by the MAI-based model in estimating mortality of stand trees.

Fatigue Growth Life Prediction for Collinear Multiple Surface Cracks (동일평면상에 존재하는 복수표면균열의 피로성장수명예측)

  • Lee, J.H.;Choy, Y.S.;Kim, Y.J.
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.17 no.7 s.94
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    • pp.1668-1677
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    • 1993
  • The objective of this paper is to develop a computational model for predicting the fatigue propagation of collinear multiple surface cracks under constant amplitude and variable amplitude loadings. After examining fatigue crack growth behavior for CT specimens and single surface crack specimens, empirical equations of(11) and(12) are proposed for the prediction of fatigue life in a multiple surface crack geometry. The accuracy of the proposed model is verified using a life prediction computer program. Several case studies were performed to check the accuracy of the proposed model and to verify the usefulness of the developed program. Good agreement is observed between the numerical results based on the proposed model and the published experimental data.