A Numerical Comparison of the Behavior of a Braced Excavation Using Two and Three-Dimensional Creep Plastic Analyses

Current study deals with investigating the effects of both time factor and the selection of a constitutive model type on predicting deformations of an excavation braced by nailing using two and three-dimensional finite element analyses. In addition, the effects of stress path and the type of defined initial conditions of the analytical model on deformations of the floor and walls of the excavation are also studied. Time factor, in the form of earth materials’ creep, can largely be entered into calculation of deformations of excavations by conducting viscoelastic and viscoplastic analyses. On the other hand, there hasn’t been done a comprehensive study regarding the creep behavior of excavations through comparing the results of two-dimensional and three-dimensional numerical analyses so far. The results showed that it’s largely possible to approach the actual deformation behavior of an excavation by considering the constitutive model of soft soil creep, SSC model, in the numerical plastic analyses. The effects of stress path on the deformation behavior of the excavation walls and excavation floor are investigated by using OCR stress ratio and POP stress difference; These two factors, both of which are also analogous, represent a boundary value for swelling behavior of the excavation floor and an increasing rate for the deformation behavior of the excavation walls since the increase in OCR or POP is equal to the increase in the soil lateral pressure coefficient at rest.     

Spatial and temporal monthly precipitation forecasting using wavelet transform and neural networks,Qara-Qum catchment,Iran

This paper aims to provide a spatial and temporal analysis to prediction of monthly precipitation data which are measured at irregularly spaced synoptic stations at discrete time points. In the present study, the rainfall data were used which were observed at four stations over the Qara-Qum catchment, located in the northeast of Iran. Several models can be used to spatially and temporally predict the precipitation data. For temporal analysis, the wavelet transform with artificial neural network (WTANN) framework combines with the wavelet transform, and an artificial neural network (ANN) is used to analyze the nonstationary precipitation time-series. The time series of dew point, temperature, and wind speed are also considered as ancillary variables in temporal prediction. Furthermore, an artificial neural network model was used for comparing the results of the WTANN model. Therefore, four models were developed, including WTANN and ANN with and without ancillary data. Several statistical methods were used for comparing the results of the temporal analysis. It was evident that at three of the four stations, the WTANN models were more effective than the ANN models, and only at one station, the ANN model with ancillary data had better performance than the WTANN model without ancillary data. The values of correlation coefficient and RMSE for WTANN model with ancillary data for the validation period at Mashhad station which showed the best results were equal to 0.787 and 13.525 mm, respectively. Finally, an artificial neural network model was used as an alternative interpolating technique for spatial analysis.     

A Comparative Study Between Least Square and Total Least Square Methods for Time–Series Analysis and Quality Control of Sea Level Observations

In this study, the quality control of tide gauge observations is investigated by two methods of least square (LS-HE) and total least square harmonic estimation (TLS-HE). Particularly, it is shown how to deal with unexpected anomalies, including outliers, offset and gap in the time series of sea level height. To do so, at first the time series is constructed and then a method based on variance threshold is used to eliminate the possible outliers in the observations. Subsequently, a noise assessment algorithm is implemented and the signal is processed to find the possible times of offsets and to eliminate their corresponding observations from the time series. Finally, the signal is checked to find the periods of gap within the time series and then the gap area is predicted with correct observations. Gap filling analysis is performed in two contexts. In the first, only the significant frequencies of tide are considered in the modelling procedure, while in the second, all possible frequencies according to the period of observations are included. Our results show that for modelling and gap filling, the TLS-HE method has a better performance in a comparison with LS-HE method. Although, for offset and outlier detections, the LS-HE is recommended. It also indicates that the TLS-HE method provides a regular solution for gap filling analysis while LS-HE method needs a regularization scheme for which LSQR regularization is used.     

Regional ionosphere modeling in support of IRI and wavelet using GPS observations

Dual-frequency global navigation satellite systems (GNSS) observations provide most of the input data for development of global ionosphere map (GIM) of vertical total electron content (VTEC). The international GNSS service (IGS) develops different ionosphere products. The IGS tracking network stations are not homogeneously distributed around the world. The large gaps of this network in Middle East, e.g., Iran plateau, reduce the accuracy of the IGS GIMs over this region. Empirical ionosphere models, such as international reference ionosphere (IRI), also provide coarse forecasts of the VTEC values. This paper presents a new regional VTEC model based on the IRI 2007 and global positioning system (GPS) observations from Iranian Permanent GPS Network. The model consists of a given reference part from IRI model and an unknown correction term. Compactly supported base functions are more appropriate than spherical harmonics in regional ionosphere modeling. Therefore, an unknown correction term was expanded in terms of B-spline functions. The obtained results are validated through comparison with the observed VTEC derived from GPS observations.     

Evaluation of hazardous effects of near-fault earthquakes on earth dams by using EL and TNL numerical methods (case studies: Gheshlagh Oleya and Jamishan dams)

Natural Hazards - The main framework of the current study is the dynamic time-history analyses by applying actual near-fault earthquake records to the bedrocks of Gheshlagh Oleya and Jamishan earth...