Impact of downstream lakes on dam break wave attenuation

In this study, the effect of downstream lakes or ponds on dam break flow was investigated. To do this, a robust finite volume method with Harten-Lax-van Leer contact surface Riemann’s solver technique for flux evaluation has been used. For space discretization, a triangular mesh grid was used and a complete software with mesh generator was developed. A reservoir with a long downstream channel was assumed, and many scenarios such as a single lake with various lengths, widths and positions along the channel and multiple consecutive lakes as symmetric and non-symmetric with respect to the channel centerline were considered. The numerical modeling of dam break flow along the channel showed that the downstream lake can decrease the speed and depth of the dam break wave front and the amount of this wave attenuation was very dependent on the storage volume of the lake and vortexes which were established in the lake.

     

Socioeconomic impacts of environmental risks in the western Makran zone (Chabahar,Iran)

Natural Hazards - The western Makran subduction zone is capable of producing considerable tsunami run-up heights that penetrate up to 5 km inland. In this study, we show how climate change...     

Innovative mitigation method for buried pipelines crossing faults

A new remediation technique is proposed to mitigate large deformations imposed on buried pipeline systems subject to permanent ground deformation. With this technique, low-density gravel(LDG) with high porosity, such as pumice,is used as backfill in the trench containing the pipe near an area susceptible to PGD. This countermeasure decreases soil resistance, soil-pipe interaction forces and strain on the pipe as the pipeline deformation mechanism changes to a more desirable shape. Expanded polys...     

A fast joint seismic data reconstruction by sparsity‐promoting inversion

Seismic field data are often irregularly or coarsely sampled in space due to acquisition limits. However, complete and regular data need to be acquired in most conventional seismic processing and imaging algorithms. We have developed a fast joint curvelet‐domain seismic data reconstruction method by sparsity‐promoting inversion based on compressive sensing. We have made an attempt to seek a sparse representation of incomplete seismic data by curvelet coefficients and solve sparsity‐promoting problems through an iterative thresholding process to reconstruct the missing data. In conventional iterative thresholding algorithms, the updated reconstruction result of each iteration is obtained by adding the gradient to the previous result and thresholding it. The algorithm is stable and accurate but always requires sufficient iterations. The linearised Bregman method can accelerate the convergence by replacing the previous result with that before thresholding, thus promoting the effective coefficients added to the result. The method is faster than conventional one, but it can cause artefacts near the missing traces while reconstructing small‐amplitude coefficients because some coefficients in the unthresholded results wrongly represent the residual of the data. The key process in the joint curvelet‐domain reconstruction method is that we use both the previous results of the conventional method and the linearised Bregman method to stabilise the reconstruction quality and accelerate the recovery for a while. The acceleration rate is controlled through weighting to adjust the contribution of the acceleration term and the stable term. A fierce acceleration could be performed for the recovery of comparatively small gaps, whereas a mild acceleration is more appropriate when the incomplete data has a large gap of high‐amplitude events. Finally, we carry out a fast and stable recovery using the trade‐off algorithm. Synthetic and field data tests verified that the joint curvelet‐domain reconstruction method can effectively and quickly reconstruct seismic data with missing traces.     

Numerical simulation of groundwater flow and contamination transport in Nahavand plain aquifer,west of Iran

Numerical simulation of groundwater flow used for the estimation of hydraulic and hydrologic parameters which is an important tool for the management of aquifers. This study presents the results of a mathematical model developed for the simulation of groundwater flow in Nahavand plain aquifer in the southwest Hamadan province. For this purpose Groundwater Modeling Software (GMS) was used which supports the MODFLOW-2000 code. After gathering required data such as the hydrological, hydrogeological and topography maps, a 3D hydrogeological model of plain was constructed with borehole and surface elevation data. Then MODFLOW was used for simulation of flow. After initial simulation of the flow, the model was calibrated in steady state with trial-and-error and parameter estimation methods the observed head of groundwater table monitoring data of 1997. Results of calibration show that error between observed head and computed head is in allowable range. Also results of computed head with model show that groundwater flow is in the direction of the dominate slope (southeast to northwest). Finally MODPATH code which simulates advective transport of particles was used for estimation of flow path and source of contaminants.     

Performance of quasilinear elastic constitutive models in simulation of geosynthetic encased columns

Past numerical simulations of geosynthetic encased columns (GECs) using different versions of the quasilinear elastic hyperbolic model for the encased granular material have, in certain cases, yielded unrealistic results. In this paper the cause of such results is investigated by performing three-dimensional finite element analyses of GECs in soft clay, utilizing three common functional forms of the hyperbolic model for the encased granular material. Results indicate that one form of the hyperbolic model can predict an unrealistic lateral response for GECs during application of load to the column. In addition, the inability of hyperbolic models to properly account for soil behavior near failure compromises their ability to realistically capture the behavior of encased granular soil in GECs. Modeling the behavior of soil near failure is essential for properly simulating the behavior of GECs, as soil shear failure is necessary to mobilize the tensile stresses in the encasement and improve the stress–displacement response of the GEC. Although this type of hyperbolic model behavior was demonstrated for the specific case of encased soil in a GEC, the limitations of the hyperbolic model described herein apply equally to other geotechnical problems in which some portion of the soil mass is at or near failure.     

Evaluation of the Iranian guideline for deismic rehabilitation of existing buildings

The Iranian Guideline for Seismic Rehabilitation of Existing Buildings （GSREB）, which is currently used for vulnerability assessment of existing buildings in Iran, is evaluated in this paper. The vulnerability of sample buildings of a variety stories with special steel moment resisting frames, designed according to the Standard No.2800 requirements, is assessed by GSREB. In the vulnerability assessment, different analysis methods were used and the results, in terms of usage ratio, defined as the ratio of the strength/deformation demand to the corresponding capacity, are compared. Numerical results show that some columns of these buildings do not satisfy the life safety performance criteria in the design hazard level. Moreover, the target displacement estimated by the Displacement Coefficient Method （DCM） is larger than the maximum displacement calculated by nonlinear dynamic analysis.     

Application of soft-computing techniques in forecasting sediment load and concentration

ABSTRACT

This paper investigates conventional and soft-computing methods for the estimation of suspended sediment concentration (SSC) and load (SSL) in rivers. Frequently used methods of sediment rate curve (SRC) and multi-nonlinear regression, and soft-computing methods of multi-layer perceptron, multi-linear regression and adaptive neuro-fuzzy inference system are implemented using various hydrological and hydraulic parameters for the Little Kickapoo Creek Watershed, Illinois, USA. All methods performed equally well in the estimation of SSL, without any noticeable outperformance from any from the methods. However, the application of soft-computing methods decreased SSC estimation errors considerably as compared to the results of SRC. The results are significant in the way they reconcile traditionally used hydrological parameters into the soft-computing methods. Overall, soft-computing methods are recommended for the estimation of SSC in rivers because of their reasonably better performance and ease of implementation.     

Monthly stream flow forecasting via dynamic spatio-temporal models

In this research, a dynamic linear spatio-temporal model (DLSTM) was developed and evaluated for monthly streamflow forecasting. For parameter estimation, coupled expectation–maximization (EM) algorithm and Kalman filter was adopted. This combination enables the model to estimate the state vector and parameters concurrently. Different forecast scenarios including various combinations of upstream stations were considered for downstream station streamflow forecasting. Several statistical criteria, nonparametric and visual tests were used for model evaluation. Results indicated that the spatio-temporal model performed acceptably in almost all scenarios. The dynamic model was able to capitalize on coupled spatial and temporal information provided that there is spatial connectivity in the studied hydrometric stations network. Moreover, threshold level method was used for model evaluation in drought and wet periods. Results indicated that, in validation phase, the model was able to forecast the drought duration and volume deficit/over threshold, although volume deficit/over threshold could not be accurately simulated.