Paleoseismological Analysis Along the Astara Fault System (Talesh Mountain, North Iran)

The Astara Fault System(AFS) is located in the northwest Alborz, east of Talesh Mountain(TM) and west of the South Caspian Basin(SCB). The AFS is one of the basement rock faults in Iran that is heavily involved in seismotectonic activity of the Talesh region, and to which subsidence of the SCB is attributed. There is little information available concerning previous AFS seismic activities and its properties. In order to elucidate the seismic behavior and activities of the AFS, we conducted a research study on paleoseismology of the fault. Based on paleoseismic evidence, two scenarios could be taken into consideration, one of which has three and another has four seismic events with magnitudes Mw in the range of 6.7 to 7.2. Evidence of these seismic events is within sedimentary succession as they have occurred during the past 3 ka(this age is determined based on the deposition rate of the region). Six carbon samples were taken for C~(14) age determination tests, the results of which clearly demonstrated that the EvIV(scenario A) and EvⅢ(scenario B) had occurred before 27,444 cal BP, while other events occurred in the time period between 27,444 cal BP and 3 ka ago. If we consider the occurrence of three or four seismic events(based on the two scenarios) to be between 27,444 cal BP and 3 ka ago, the average recurrence interval is 7,119 ± 1,017, but evidence for these events has been removed. If we assume EvI to be the youngest event(in both scenarios), the minimum elapsed time is therefore 3 ka.     

Stochastic Modeling Approach for the Evaluation of Backbreak due to Blasting Operations in Open Pit Mines

Backbreak is an undesirable side effect of bench blasting operations in open pit mines. A large number of parameters affect backbreak, including controllable parameters (such as blast design parameters and explosive characteristics) and uncontrollable parameters (such as rock and discontinuities properties). The complexity of the backbreak phenomenon and the uncertainty in terms of the impact of various parameters makes its prediction very difficult. The aim of this paper is to determine the suitability of the stochastic modeling approach for the prediction of backbreak and to assess the influence of controllable parameters on the phenomenon. To achieve this, a database containing actual measured backbreak occurrences and the major effective controllable parameters on backbreak (i.e., burden, spacing, stemming length, powder factor, and geometric stiffness ratio) was created from 175 blasting events in the Sungun copper mine, Iran. From this database, first, a new site-specific empirical equation for predicting backbreak was developed using multiple regression analysis. Then, the backbreak phenomenon was simulated by the Monte Carlo (MC) method. The results reveal that stochastic modeling is a good means of modeling and evaluating the effects of the variability of blasting parameters on backbreak. Thus, the developed model is suitable for practical use in the Sungun copper mine. Finally, a sensitivity analysis showed that stemming length is the most important parameter in controlling backbreak.     

Evaluation of liquefaction potential based on CPT results using evolutionary polynomial regression

In this paper a new approach is presented, based on evolutionary polynomial regression (EPR), for determination of liquefaction potential of sands. EPR models are developed and validated using a database of 170 liquefaction and non-liquefaction field case histories for sandy soils based on CPT results. Three models are presented to relate liquefaction potential to soil geometric and geotechnical parameters as well as earthquake characteristics. It is shown that the EPR model is able to learn, with a very high accuracy, the complex relationship between liquefaction and its contributing factors in the form of a function. The attained function can then be used to generalize the learning to predict liquefaction potential for new cases not used in the construction of the model. The results of the developed EPR models are compared with a conventional model as well as a number of neural network-based models. It is shown that the proposed EPR model provides more accurate results than the conventional model and the accuracy of the EPR results is better than or at least comparable to that of the neural network-based models proposed in the literature. The advantages of the proposed EPR model over the conventional and neural network-based models are highlighted.     

Hazards of mechanized tunnel excavation in H<Subscript>2</Subscript>S bearing ground in Aspar tunnel,Iran

Occurrence of hydrogen sulfide gas (H₂S) is one of the most important engineering geological hazards during tunneling. Its hazards and consequent challenges are very difficult and costly to solve. During site investigation, one of the tasks for engineering geologists is prediction and evaluation of the risk of H₂S gas in the underground spaces. In this study, water conveyance tunnel of Aspar, which was excavated in H₂S-bearing environments, is discussed. The tunnel is excavated in the hydrocarbon formations. Applied experiments suggest that geological formations pertaining to hydrocarbon resources are crucial in formation and reservation of H₂S gas. This paper briefly discusses hazards and geological sources of H₂S, as well as remedial measures for decreasing the risks and problems in excavation of the tunnel. To predict the risk of H₂S gas in the underground spaces, it is possible to use some precursors such as: sulfur springs, organic traces, organic argillaceous rocks, exposure of H₂S odor from fresh surface of rock and smell of H₂S during boreholes drilling. Controlling the inflow of groundwater into the excavation, diluting the concentration of H₂S, training the personnel and utilization of some proper safety equipment have been used to mitigate risks and problems in tunnel excavation.     

Groundwater pesticides residue in the southwest of Iran-Shushtar plain

Study area with an area of about 415 km² is located from 31°40′ to 32°05′ northern latitudes and 48°45′ to 49°00′ eastern longitudes 85 km to the north-east of Ahwaz city, in the north of Khuzestan province, and south west of Iran. The purpose of this study is: (1) the determination of the pesticides concentration in the groundwater of the Shushtar plain (Mian-Ab) and (2) the assessment of geology, hydrogeology and anthropogenic activities impacts the groundwater quality. Thirty-seven groundwater samples were taken from product wells based on the standard methods. A simple and efficient automated method for extraction and preconcentration was used. In this method, a pyrrole-based polymer was synthesized and applied as an efficient sorbent for micro-solid-phase extraction. After extraction, analytes were desorbed in ethyl acetate and analyzed using gas chromatography–flame. The study area is surrounded by Aghajari Formation dominated by silt and clay sediments and the Bakhtiari Formation dominated by sand and gravel. Existence of these formations affects the aquifer sediments and the hydrogeological properties. In the study area, the sediments grade from gravel and sand in the north and east into silt and clay to the south and west, respectively. The topsoil in the south of the study area contains more clay sediments. In this study, the concentration of two common herbicides, i.e., 2,4-D and clodinafop propargyl and two pesticides, i.e., permethrin and diazinon, in the groundwater of Mian-Ab aquifer was assessed. Chemical analysis results showed that the 2,4-D residue in the groundwater has the highest concentration (15 ppm). About 50% of the samples have concentration values more than the maximum contamination level based on EPA drinking standard. The pesticides concentrations decrease from the north to the south of the study area. Pesticides influx to the groundwater in the south of the area is prevented or diminished due to the specific geological situation and soil type. Distribution pattern of population centers, which increase to the north of the study area, and the role of groundwater as the main source of drinking water are two important issues that must be considered in management of pesticides use in the area.     

A synthetic Earth gravity model based on a topographic-isostatic model

The Earth??s gravity field is related to the topographic potential in medium and higher degrees, which is isostatically compensated. Hence, the topographic-isostatic (TI) data are indispensable for extending an available Earth Gravitational Model (EGM) to higher degrees. Here we use TI harmonic coefficients to construct a Synthetic Earth Gravitational Model (SEGM) to extend the EGMs to higher degrees. To achieve a high-quality SEGM, a global geopotential model (EGM96) is used to describe the low degrees, whereas the medium and high degrees are obtained from the TI or topographic potential. This study differes from others in that it uses a new gravimetric-isostatic model for determining the TI potential. We test different alternatives based on TI or only topographic data to determine the SEGM. Although the topography is isostatically compensated only to about degree 40?C60, our study shows that using a compensation model improves the SEGM in comparison with using only topographic data for higher degree harmonics. This is because the TI data better adjust the applied Butterworth filter, which bridges the known EGM and the new high-degree potential field than the topographic data alone.     

Peak displacement patterns for the performance-based seismic design of steel eccentrically braced frames

Performance-based seismic design(PBSD) aims to assess structures at different damage states. Since damage can be directly associated to displacements, seismic design with consideration of displacement seems to be logical. In this study, simple formulae to estimate the peak floor displacement patterns of eccentrically braced frames(EBFs) at different performance levels subjected to earthquake ground motions are proposed. These formulae are applicable in a PBSD and especially in direct displacement-based design(DDBD). Parametric study is conducted on a group of 30 EBFs under a set of 15 far field and near field accelerograms which they scaled to different amplitudes to adapt various performance levels. The results of thousands of nonlinear dynamic analyses of EBFs have been post-processed by nonlinear regression analysis in order to recognize the major parameters that influence the peak displacement pattern of these frames. Results show that suggested displacement patterns have relatively good agreement with those acquired by an exact nonlinear dynamic analysis.     

Second order adiabatic invariants associated with the two-body problem with slowly varying mass

An adiabatic invariant is characterized by the property that its derivative is small and oscillatory. Therefore, assuming that such a quantity is constant does not lead to a cumulative error as t. In this paper, using action and angle variables, adiabatic invariants to 0(1) and 0() are found for the two-body problem with a slowly varying gravitational constant.     

Predicting landscape sensitivity to present and future floods in the Pacific Northwest,USA

Floods are the most frequent natural disaster, causing more loss of life and property than any other in the USA. Floods also strongly influence the structure and function of watersheds, stream channels, and aquatic ecosystems. The Pacific Northwest is particularly vulnerable to climatically driven changes in flood frequency and magnitude, because snowpacks that strongly influence flood generation are near the freezing point and thus sensitive to small changes in temperature. To improve predictions of future flooding potential and inform strategies to adapt to these changes, we mapped the sensitivity of landscapes to changes in peak flows due to climate warming across Oregon and Washington. We first developed principal component‐based models for predicting peak flows across a range of recurrence intervals (2‐, 10‐, 25‐, 50‐, and 100‐years) based on historical instantaneous peak flow data from 1000 gauged watersheds in Oregon and Washington. Key predictors of peak flows included drainage area and principal component scores for climate, land cover, soil, and topographic metrics. We then used these regression models to predict future peak flows by perturbing the climate variables based on future climate projections (2020s, 2040s, and 2080s) for the A1B emission scenario. For each recurrence interval, peak flow sensitivities were computed as the ratio of future to current peak flow magnitudes. Our analysis suggests that temperature‐induced changes in snowpack dynamics will result in large (>30–40%) increases in peak flow magnitude in some areas, principally the Cascades, Olympics, and Blue Mountains and parts of the western edge of the Rocky Mountains. Flood generation processes in lower elevation areas are less likely to be affected, but some of these areas may be impacted by floodwaters from upstream. These results can assist land, water, and infrastructure managers in identifying watersheds and resources that are particularly vulnerable to increased peak flows and developing plans to increase their resilience. Copyright © 2015 John Wiley & Sons, Ltd.