Multi-fidelity analysis and uncertainty quantification of beam vibration using co-kriging interpolation method

2021 ◽  
Vol 398 ◽  
pp. 125987
Author(s):  
K V Vishal Krishnan ◽  
Ranjan Ganguli
Keyword(s):  
Uncertainty Quantification ◽  
Interpolation Method ◽  
Kriging Interpolation ◽  
Beam Vibration ◽  
Kriging Interpolation Method

Numerical Investigation of the Identifiability of Elastomer Mechanical Properties by Nano-Indentation and Shape-Manifold Approach

2021 ◽  
Author(s):  
Oumaima Ezzaamari ◽  
Guénhaël Le Quilliec ◽  
Florian Lacroix ◽  
Stéphane Méo
Keyword(s):  
Numerical Study ◽  
Interpolation Method ◽  
Structural Characteristics ◽  
Numerical Approach ◽  
Kriging Interpolation ◽  
Nano Indentation ◽  
Kriging Interpolation Method ◽  
Elastomeric Materials ◽  
Hyper Elastic ◽  
Characterization Test

ABSTRACT Various research is covering instrumented nano-indentation in the literature. However, studies on this characterization test remain limited when it comes to the local mechanical behavior of elastomeric materials. The application of nano-indentation on these materials is a difficult task given their complex mechanical and structural characteristics. We try to overcome these experimental limitations and find an effective numerical approach for local mechanical characterization of hyper-elastic materials. For such needs, we carried out a numerical study based on model reduction and shape manifold approach to investigate the parameters identification of different hyper-elastic constitutive laws by using instrumented indentation. Similarly, we studied the influence of the indenter geometry, the friction coefficient variation, and finally the indented material height effect. To this end, we constructed a reduced order model through a design of experiments by proper orthogonal decomposition combined with the kriging interpolation method.

scholarly journals Estimation of Ice Thickness and the Features of Subglacial Media Detected by Ground Penetrating Radar at the Baishui River Glacier No. 1 in Mt. Yulong, China

2020 ◽  
Vol 12 (24) ◽  
pp. 4105
Author(s):  
Jing Liu ◽  
Shijin Wang ◽  
Yuanqing He ◽  
Yuqiang Li ◽  
Yuzhe Wang ◽  
...  
Keyword(s):  
Ground Penetrating Radar ◽  
Interpolation Method ◽  
Kriging Interpolation ◽  
Ice Thickness ◽  
Grid Data ◽  
Differential Gps ◽  
Landsat Images ◽  
Kriging Interpolation Method ◽  
Bedrock Surface ◽  
Ground Penetrating

Using ground-penetrating radar (GPR), we measured and estimated the ice thickness of the Baishui River Glacier No. 1 of Yulong Snow Mountain. According to the position of the reflected media from the GPR image, combined with the radar waveform amplitude and polarity change information, the ice thickness and the changing medium position at the bottom of this temperate glacier were identified. Water paths were found in the measured ice, including ice caves and crevasses. A debris-rich ice layer was found at the bottom of the glacier, which produces strong abrasion and ploughing action at the bedrock surface. This results in the formation of different detrital layers stagnated at the ice-bedrock interface and numerous crevasses on the bedrock surface. Based on the obtained ice thickness and differential GPS data, combined with Landsat images, the kriging interpolation method was used to obtain grid data. The average ice thickness was 52.48 m and between 4740 and 4890 m above sea level, with a maximum depth of 92.83 m. The bedrock topography map of this area was drawn using digital elevation model from the Shuttle Radar Topography Mission. The central part of the glacier was characterized by small ice basins with distributed ice steps and ice ridges at the upper and lower parts.

Numerical Modeling of Fracture Process Using Element-Free Method

2013 ◽  
Vol 427-429 ◽  
pp. 146-149
Author(s):  
Cheng Fan
Keyword(s):  
Interpolation Method ◽  
Kriging Interpolation ◽  
Computational Accuracy ◽  
Simple Method ◽  
Solution Domain ◽  
Kriging Interpolation Method ◽  
Finite Covers ◽  
Crack Problems ◽  
Cover Systems ◽  
Element Free

A new element-free formulation of Kriging interpolation procedure based on finite covers technique and Kriging interpolation method which integrates the flexibilities of the manifold method in dealing with discontinuity and the element-free features of the moving Kriging interpolation. Two cover systems are employed in this method. Mathematical cover of the solution domain under consideration are used to construct shape function and physical cover is used to reproduce the geometry of the solution domain. The mathematical covers can take any types of shape and is much easily formed compared with those in the conventional MM. The presented method can overcome some difficulties in conventional element-free Galerkin methods in treating discontinuous crack problems. The fundamental theory of this procedure is illustrated and numerical analyses of examples show that the proposed procedure is an effective and simple method with higher computational accuracy.

Integration of statistical and spatial methods for distributing precipitation in tropical areas

2012 ◽  
Vol 44 (6) ◽  
pp. 982-994 ◽  
Author(s):  
Mandana Abedini ◽  
Md Azlin Md Said ◽  
Fauziah Ahmad
Keyword(s):  
Multivariate Regression ◽  
Interpolation Method ◽  
Rainfall Data ◽  
Environmental Research ◽  
Kriging Interpolation ◽  
Slope Aspect ◽  
Annual Average ◽  
Rain Gauges ◽  
Kriging Interpolation Method ◽  
Topographical Factors

The high spatial resolution of precipitation distribution is a major concern for experts in environmental research and planning. This paper establishes a combination of multivariate regression algorithm and spatial analysis to predict distribution of precipitation, considering the four topographical factors of altitude, slope, aspect and location. Annual average and seasonal rainfall data were collected in nine rain gauges in Ulu Kinta Catchment in East Malaysia from 1974 to 2010. To examine records and fill gaps from long-term rain gauges, homogeneity analysis was performed using the double-mass curve method. Estimated missing rainfall data were also tested using index gauges from network rainfall stations. Multivariate regression analysis was conducted to propose an empirical equation for the study area. Topographical factors were considered from a 90 m resolution digital elevation model. The multivariate regression model was found to clarify 74% of spatial variability of precipitation on annual average and 78% during wet season. However, the correlation coefficient for the dry season decreased sharply to 63%. By using the kriging interpolation method, the estimated annual average improved to 78.4%; the average improved to 65.2 and 80.3% in the dry and wet seasons, respectively. This confirms the efficiency and significance of the model and its potential for use in other tropical catchments.

The Flow Units Study Based on Reservoir Architecture

2011 ◽  
Vol 361-363 ◽  
pp. 66-69
Author(s):  
Cong Jun Feng ◽  
Zhi Dong Bao ◽  
Ying Wang
Keyword(s):  
Oil Recovery ◽  
Interpolation Method ◽  
Flow Unit ◽  
Kriging Interpolation ◽  
Empirical Formulas ◽  
Reservoir Architecture ◽  
Flow Units ◽  
Kriging Interpolation Method ◽  
The Relationship

In the case of Fourth Member of Quantou Formation (K1q4) in Well X5-16 of Fuyu Oilfield, it integrates the theory of reservoir architecture and methodology for flow-unit analysis to characterize the architectural units and their permeable features in reservoirs. As the research found, point bars are very developed in low-sinuosity meandering distributary channels. Therefore, parameter modeling for reservoirs, confined by reservoir architecture is firstly constructed from empirical formulas and integrating the data from closely-spaced wells in dense pattern area. At this basis, clustering analysis with optimized reservoir parameters help demarcate the classification of flow units and further the Kriging interpolation method is introduced for interwell flow unit prediction. Besides, the study also illustrates the relationship between the lateral accretion and the flow unit. Finally, the research achievements were confirmed by successfully matching the production data, so as to predict how the remaining oil distributes, or to adjust the development plan, as well as enhance the oil recovery.

scholarly journals Spatial variability and trends of the rain intensity over Greece

2010 ◽  
Vol 26 ◽  
pp. 65-69 ◽  
Author(s):  
H. D. Kambezidis ◽  
I. K. Larissi ◽  
P. T. Nastos ◽  
A. G. Paliatsos
Keyword(s):  
Confidence Level ◽  
Temporal Variability ◽  
Interpolation Method ◽  
Kendall Test ◽  
Kriging Interpolation ◽  
Spatial And Temporal Variability ◽  
Rain Intensity ◽  
Kriging Interpolation Method ◽  
Bartlett Test ◽  
The Mean

Abstract. In this study, the spatial and temporal variability of the mean annual rain intensity in Greece are examined during a 41-year period (1962–2002). The meteorological datasets concern monthly rain amounts (mm) and the respective monthly durations (h) recorded at thirty two meteorological stations of the Hellenic National Meteorological Service, which are uniformly distributed on Greek territory, in order to calculate the mean monthly rain intensity. All the rain time series used in the analysis were tested by the application of the short-cut Bartlett test of homogeneity. The spatial distribution of the mean annual rain intensity is studied using the Kriging interpolation method, while the temporal variability, concerning the mean annual rain intensity trends along with their significance (Mann-Kendall test), is analysed. The findings of the analysis show that statistically significant negative trends (95% confidence level) appear mainly in the west sub-regions of Greece, while statistically significant positive trends (95% confidence level) appear in the wider area of Athens and the complex of Cyclades Islands. Further analysis concerning the seasonal rain intensity is needed, because there are different seasonal patterns, taking into account that, convective rain in Greece occurs mainly within the summer season.

scholarly journals Epidemiology and spatial distribution of Echinococcus granulosus in sheep and goats slaughtered in a hyperendemic European Mediterranean area

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Antonio Bosco ◽  
Leucio Camara Alves ◽  
Paola Cociancic ◽  
Alessandra Amadesi ◽  
Paola Pepe ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Echinococcus Granulosus ◽  
Interpolation Method ◽  
Mediterranean Area ◽  
Sensu Stricto ◽  
Kriging Interpolation ◽  
Sheep And Goats ◽  
Basilicata Region ◽  
Kriging Interpolation Method ◽  
Target Organs

Abstract Background Cystic echinococcosis (CE) is a worldwide parasitic zoonosis caused by the larval stage of Echinococcus granulosus sensu lato affecting livestock, particularly sheep and goats. However, often this parasitosis is underestimated. For this reason, this study aimed to evaluate the epidemiological features and spatial distribution of CE in sheep and goats slaughtered in a hyperendemic Mediterranean area. Methods A survey was conducted in the Basilicata region (southern Italy) from 2014 to 2019. A total of 1454 animals (1265 sheep and 189 goats) from 824 farms were examined for hydatid cyst detection by visual inspection, palpation and incision of target organs. All the CE cysts were counted and classified into five morphostructural types (unilocular, multiseptate, calcified, caseous and hyperlaminated). Molecular analysis was performed on 353 cysts. For spatial analysis, a kriging interpolation method was used to create risk maps, while clustering was assessed by Moran’s I test. Results CE prevalence of 72.2% (595/824) and 58.4% (849/1454) was observed at the farm and animal levels, respectively, with higher values in sheep (62.9%) than goats (28.0%). The liver and lungs were the most frequently infected organs in both sheep and goats. Most of recovered cysts were of the calcified and multiseptate morphotypes. All the isolates were identified as E. granulosus sensu stricto (genotypes G1–G3). Spatial distribution showed a moderate clustering of positive animals. Conclusion The findings of this study can be used to better understand the eco-epidemiology of echinococcosis and to improve CE surveillance and prevention programs in regions highly endemic for CE. Graphical abstract

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