Deformation modelling of structures enriched by inter-element continuity condition based on multi-sensor data fusion

Jafari, Marzieh

doi:10.1016/j.apm.2016.06.010

Cited by 8 publications

(3 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Currently, the data have been used which are developed for soil mechanics to assess the soil mass deformation which is saturated with saline solutions [8,9]. And this is the subject to the action of low-concentration natural groundwater [4].…”

Section: Introductionmentioning

confidence: 99%

Deformations of Soil Masses Under the Action of Human-Induced Factors

Kuzlo,

Moshynskyi,

Zhukovska

et al. 2024

IAPGOS

View full text Add to dashboard Cite

Significant changes in the stress-strain state cause a change in the soil profile of the massif, which is affected by various physical and chemical factors. In particular, groundwater filtration, mass transfer, heat transfer, dissolution and leaching of soil masses. This can lead to various types of accidents. Therefore, the study of the stress-strain state of the soil massif is an important topic. Nonlinear dependences in the form of polynomials of the modulus of deformation and Lame coefficients on the concentration of salt solutions and their temperature have been received in this research based on experimental research and their statistical processing. This allowed improving the mathematical model of the stress-strain state of the soil taking into account the nonlinear deformation processes occurring in the soil masses under the presence and filtration of saline solutions in non-isothermal conditions.

show abstract

Section: Introductionmentioning

confidence: 99%

Deformations of Soil Masses Under the Action of Human-Induced Factors

Kuzlo,

Moshynskyi,

Zhukovska

et al. 2024

IAPGOS

View full text Add to dashboard Cite

show abstract

“…Two panel analysis models were subsequently established to monitor the fixed and random patterns of special effects for dam deformation. M. Jafari 27 developed a dam deformation modeling method for multi-sensor measurements based on the numerical solution of inter-element continuity conditions. Dai and He 28 developed a multi-sensor data fusion method for rock-fill dam deformation variations based on a developed finite element method considering the inter-element continuity conditions of the deformation.…”

Section: Introductionmentioning

confidence: 99%

A spatio-temporal clustering and diagnosis method for concrete arch dams using deformation monitoring data

Huang

et al. 2018

Structural Health Monitoring

View full text Add to dashboard Cite

The timely analysis of deformation monitoring data and reasonable diagnosis of the structural health are key tasks in dam health monitoring studies. This article presents a spatio-temporal clustering and health diagnosis method for super-high concrete arch dams that uses deformation monitoring data obtained from plumb meters. The spatio-temporal expression of the deformation monitoring data is proposed first by upgrading a punctuated time series to a curved panel time series, including cross-sectional, dam axial, and temporal changing directions. Second, a comprehensive similarity indicator on three aspects, namely, the absolute distance, incremental distance, and growth rate distance, is constructed after a deep discussion on deformation similarity characteristics both temporally and spatially. Next, the temporal clustering method is proposed by keeping the key features, namely, extreme points and turning points, while eliminating extraneous details, namely, noise points. Finally, the optimal spatio-temporal clustering of dam deformation is achieved by designing a multi-scale fuzzy C-means method of data mining and its iterative algorithm. The proposed method is applied to the Jinping-I hydraulic structure, which is the highest concrete arch dam in the world. The clustering results is quite sensitive in different weight coefficients of the comprehensive similarity indicator and clustering numbers of fuzzy C-means method. The dam deformation behaviors on high-water-level, water-falling, and low-water-level periods are analyzed and diagnosed. The advanced version of proposed methods is verified by comparative analysis on dam health diagnosis results obtained from ordinary deformation distribution figures and the spatio-temporal clustering figures. The proposed method will facilitate the recognition of abnormal deformation areas and associated safety diagnoses.

show abstract

“…Mathematical models for assessment and prediction of strength and stability of hydrotechnical structures and their foundations are dealt with in the context of artificial neuronal networks in combination with the hybrid method of finite elements [17]; on the basis of dynamic analysis of concrete dams state in the frequency zone due to the change in oscillations shape [18]; as a result of solving differential equations with the view to modelling deformations on the basis of data obtained from the unified system of amalgamated sensors [19]; in terms of the theory of non-stationary temporal rows for the analysis of structural data by means of expectation maximization algorithm to find the values of probability models parameters maximum credibility [20]; using an approach combining wavelet analysis for creation of the initial model simulating data about the dam behavior and the subsequent building of the identification model which can relate the loads to the dam behavior [21].…”

Section: Introductionmentioning

confidence: 99%

Mathematical Modelling of Sayano-Shushenskaya Dam Displacement Process after 2009 Accident

Хорошилов¹

2018

JERA

View full text Add to dashboard Cite

The research presented in the article is of cutting-edge importance because it proves the necessity to develop prognostic mathematical models with the view to studying the behavior of high-head dams for identifying the regularities of their deformations development process and thus providing quantitative definition for the set criteria values of the diagnostic indices to ensure safe operation of such structures. The paper focuses on the peculiarities of building prognostic mathematical models of the dynamic type on the basis of recurrent equations of the 1stand 2ndorders of different types depending on the order of the mathematical model, number of the principal acting factors and discreteness of the input data, with decorrelation of the input actions and sequence of transport delay introduction. It is shown that the properties of the recurrent equation solution in the form of two first conditional moment generating functions of the displacement process of the observed points in the structure delineate a prognostic model which allows predicting the displacements of the observed points. The paper describes the sequence of estimation stages during the creation of prognostic mathematical models in respect to the character of the predictive problem for various time periods of the structure operation. Different combinations of input actions and discreteness of input data, as well as their decorrelation, have been used. We also applied transport delay in order to correctly consider the inertial delay of the dam under different loads. To account for the residual part of the inertial delay, which is affected by random and unaccounted for factors, we used the autoregression model of the process development regularity. To determine the order of the autoregression model, we calculated asymptotically unbiased ratings of the correlation function for the residual error as a difference between the actual and predicted displacements. Methodological specifics of constructing prognostic models have been established in the context of the factors above. Prognostic mathematical models of different types have been developed for the selected period of the dam operation and the results of prediction have been discussed.

show abstract

Deformation modelling of structures enriched by inter-element continuity condition based on multi-sensor data fusion

Cited by 8 publications

References 29 publications

Deformations of Soil Masses Under the Action of Human-Induced Factors

Deformations of Soil Masses Under the Action of Human-Induced Factors

A spatio-temporal clustering and diagnosis method for concrete arch dams using deformation monitoring data

Mathematical Modelling of Sayano-Shushenskaya Dam Displacement Process after 2009 Accident

Contact Info

Product

Resources

About