A prediction method using grey model for cumulative plastic deformation under cyclic loads

Ren, Xingwei; Tang, Yiqun; Li, Jun; Qi, Yang

doi:10.1007/s11069-012-0248-8

Cited by 43 publications

(22 citation statements)

References 16 publications

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“…As the retaining walls completely block (cutoff) the groundwater flow in the confined aquifer of AqI, dewatering within the foundation pit has no influence on the surrounding environment. Since it is difficult and uneconomic to construct retaining walls deep into AdII in practice, therefore Pattern 5 is seldom adopted, whereas Pattern 4 is usually adopted for reducing the water level in AqI for deep excavations (Wu, 2003;Tang et al, 2008aTang et al, , 2008bTang et al, , 2008cRen et al, 2012;Wang, 2013a, 2013b). system, and a water head monitoring system.…”

Section: Umentioning

confidence: 99%

Evaluation of the blocking effect of retaining walls on groundwater seepage in aquifers with different insertion depths

Shen

et al. 2014

Engineering Geology

118

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Section: Umentioning

confidence: 99%

Evaluation of the blocking effect of retaining walls on groundwater seepage in aquifers with different insertion depths

Shen

et al. 2014

Engineering Geology

118

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“…It can realize the prediction of system behavior using fewer data and less complicated mathematical calculation [37]. Ren et al [38] predicted the long-term cumulative plastic deformation of subgrade under cyclic loads using grey model. Wang and Li [39] adopted grey model for pavement smoothness prediction.…”

Section: Introductionmentioning

confidence: 99%

Effects of Diatomite and SBS on Freeze-Thaw Resistance of Crumb Rubber Modified Asphalt Mixture

Wei

Jiao

2017

Advances in Materials Science and Engineering

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Asphalt mixture is susceptible to moisture damage under the effect of freeze-thaw (F-T) cycles. In this paper, crumb rubber (CR) was used to modify stone mastic asphalt (SMA) and the effects of diatomite and styrene butadiene styrene (SBS) on antifreezing performances of crumb rubber modified SMA (CRSMA) were investigated. Regression analysis and modified grey model (MGM) were used to construct the prediction models for properties of modified mixtures. CRSMA, CR and diatomite modified SMA (CRDSMA), and CR and SBS modified SMA (CRSSMA) were prepared in laboratory, respectively. Process of F-T cycles was designed. Air void, indirect tensile strength (ITS), and indirect tensile stiffness modulus (ITSM) were measured to evaluate the antifreezing performances of CRSMA, CRDSMA, and CRSSMA. Results indicate that air voids increase with the increasing of F-T cycles. ITS and ITSM all decrease with the increasing of F-T cycles. The addition of diatomite and SBS can reduce the air void and improve the ITS and ITSM of CRSMA. CRSSMA presents the lowest air void, highest tensile strength, and largest stiffness modulus, which reveals that CRSSMA has the best F-T resistance among three different kinds of mixtures. Moreover, MGM (1, 2) models present more favorable accuracy in prediction of air void and ITS compared with regression ones.

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“…After 30 years of development, a framework of system analysis and evaluation [22], model prediction [23][24][25], and decision control [26] has been established as the main technical system. The gray prediction model is the core component of gray system theory.…”

Section: Introductionmentioning

confidence: 99%

Forecasting the Short-Term Traffic Flow in the Intelligent Transportation System Based on an Inertia Nonhomogenous Discrete Gray Model

2017

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The traffic-flow system has basic dynamic characteristics. This feature provides a theoretical basis for constructing a reasonable and effective model for the traffic-flow system. The research on short-term traffic-flow forecasting is of wide interest. Its results can be applied directly to advanced traffic information systems and traffic management, providing real-time and effective traffic information. According to the dynamic characteristics of traffic-flow data, this paper extends the mechanical properties, such as distance, acceleration, force combination, and decomposition, to the traffic-flow data vector. According to the mechanical properties of the data, this paper proposes four new models of structural parameters and component parameters, inertia nonhomogenous discrete gray models (referred to as INDGM), and analyzes the important properties of the model. This model examines the construction of the inertia nonhomogenous discrete gray model from the mechanical properties of the data, explaining the classic NDGM modeling mechanism in the meantime. Finally, this paper analyzes the traffic-flow data of Whitemud Drive in Canada and studies the relationship between the inertia model and the traffic-flow state according to the data analysis of the traffic-flow state. A simulation accuracy and prediction accuracy of up to 0.0248 and 0.0273, respectively, are obtained.

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A prediction method using grey model for cumulative plastic deformation under cyclic loads

Cited by 43 publications

References 16 publications

Evaluation of the blocking effect of retaining walls on groundwater seepage in aquifers with different insertion depths

Evaluation of the blocking effect of retaining walls on groundwater seepage in aquifers with different insertion depths

Effects of Diatomite and SBS on Freeze-Thaw Resistance of Crumb Rubber Modified Asphalt Mixture

Forecasting the Short-Term Traffic Flow in the Intelligent Transportation System Based on an Inertia Nonhomogenous Discrete Gray Model

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