Effect of ground motion selection methods on seismic collapse fragility of RC frame buildings

Variation in the seismic collapse fragility of reinforced concrete frame buildings predicted using different ground motion (GM) selection methods is investigated in this paper. To simulate the structural collapse, a fiber‐element modelling approach with path‐dependent cyclic nonlinear material models that account for concrete confinement and crushing, reinforcement buckling as well as low cycle fatigue is used. The adopted fiber analysis approach has been found to reliably predict the loss in vertical load carrying capacity of structural components in addition to the sidesway mode of collapse due to destabilizing P–Δ moments at large inelastic deflections. Multiple stripe analysis is performed by conducting response history analyses at various hazard levels to generate the collapse fragility curves. To select GMs at various hazard levels, two alternatives of uniform hazard spectrum (UHS), conditional mean spectrum (CMS) and generalized conditional intensity measure (GCIM) are used. Collapse analyses are repeated based on structural periods corresponding to initial un‐cracked stiffness and cracked stiffness of the frame members. A return period‐based intensity measure is then introduced and applied in estimating collapse fragility of frame buildings. In line with the results of previous research, it is shown that the choice of structural period significantly affects the collapse fragility predictions. Among the GM selection methods used in this study, GCIM and CMS methods predict similar collapse fragilities for the case study building investigated herein, and UHS provides the most conservative prediction of the collapse capacity, with approximately 40% smaller median collapse capacity compared to the CMS method. The results confirm that collapse probability prediction of buildings using UHS offers a higher level of conservatism in comparison to the other selection methods. Copyright © 2017 John Wiley & Sons, Ltd.     

SOM-DRASTIC: using self-organizing map for evaluating groundwater potential to pollution

Groundwater is considered as the most important water resource, especially in arid and semi-arid regions, so it is crucial to impede this source of water to be contaminated. One of the most common methods to assess groundwater vulnerability is DRASTIC method. However, the subjectivity existing in defining DRASTIC weights and ratings as well as inadaptability of the parameters involved in this method with special geology, hydrogeology, land use and climatic conditions have urged researchers to modify this method. In this paper, a new method combining a special type of the neural networks called Self-Organizing Map (SOM) and the traditional DRASTIC model resulting in the hybrid SOM-DRASTIC model is applied to modify and improve DRASTIC Model. The traditional DRASTIC method holds a summation among all negative effects of different factors contributing to vulnerability, while the proposed hybrid method is able of classifying the groundwater vulnerability and deriving the real relation existing between the DRASTIC parameters as the inputs and the vulnerability class as the output of the method. The vulnerability assessment process was performed on the Zayandeh-Rud river basin aquifers in Iran. The SOM-DRASTIC identified the northern parts of the study area as the most vulnerable areas with a drastically fractured structure, while the traditional DRASTIC ranked the western parts as the most vulnerable regions with a high rate of net recharge. The results demonstrate that the proposed method can be used by managers and decision-makers as an alternative robust tool for vulnerability-based classification and land use planning.     

Performance evaluation of WAVEWATCH III model in the Persian Gulf using different wind resources

The third-generation wave model, WAVEWATCH III, was employed to simulate bulk wave parameters in the Persian Gulf using three different wind sources: ERA-Interim, CCMP, and GFS-Analysis. Different formulations for whitecapping term and the energy transfer from wind to wave were used, namely the Tolman and Chalikov (J Phys Oceanogr 26:497–518, 1996), WAM cycle 4 (BJA and WAM4), and Ardhuin et al. (J Phys Oceanogr 40(9):1917–1941, 2010) (TEST405 and TEST451 parameterizations) source term packages. The obtained results from numerical simulations were compared to altimeter-derived significant wave heights and measured wave parameters at two stations in the northern part of the Persian Gulf through statistical indicators and the Taylor diagram. Comparison of the bulk wave parameters with measured values showed underestimation of wave height using all wind sources. However, the performance of the model was best when GFS-Analysis wind data were used. In general, when wind veering from southeast to northwest occurred, and wind speed was high during the rotation, the model underestimation of wave height was severe. Except for the Tolman and Chalikov (J Phys Oceanogr 26:497–518, 1996) source term package, which severely underestimated the bulk wave parameters during stormy condition, the performances of other formulations were practically similar. However, in terms of statistics, the Ardhuin et al. (J Phys Oceanogr 40(9):1917–1941, 2010) source terms with TEST405 parameterization were the most successful formulation in the Persian Gulf when compared to in situ and altimeter-derived observations.     

Nonparametric Geostatistical Simulation of Subsurface Facies: Tools for Validating the Reproduction of,and Uncertainty in,Facies Geometry

Delineation of facies in the subsurface and quantification of uncertainty in their boundaries are significant steps in mineral resource evaluation and reservoir modeling, which impact downstream analyses of a mining or petroleum project. This paper investigates the ability of nonparametric geostatistical simulation algorithms (sequential indicator, single normal equation and filter-based simulation) to construct realizations that reproduce some expected statistical and spatial features, namely facies proportions, boundary regularity, contact relationships and spatial correlation structure, as well as the expected fluctuations of these features across the realizations. The investigation is held through a synthetic case study and a real case study, in which a pluri-Gaussian model is considered as the reference for comparing the simulation results. Sequential indicator simulation and single normal equation simulation based on over-restricted neighborhood implementations yield the poorest results, followed by filter-based simulation, whereas single normal equation simulation with a large neighborhood implementation provides results that are closest to the reference pluri-Gaussian model. However, some biases and inaccurate fluctuations in the realization statistics (facies proportions, indicator direct and cross-variograms) still arise, which can be explained by the use of a single finite-size training image to construct the realizations.

     

Monitoring hawksbill turtle nesting sites in some protected areas from the Persian Gulf

Iranian nesting populations of the critically endangered hawksbill turtle(Eretmochelys imbricate) are some of the most important in the Indian Ocean. In this study, four of the most important hawksbill nesting grounds in the Persian Gulf, situated within three Iranian marine protected areas, were surveyed during nesting season,including Nakhiloo, Ommolgorm and Kharko Islands and the mainland beaches of the Naiband Marine-Coastal National Park(NMCNP). We present GIS maps of these key nesting grounds and describe sand texture of key nesting zones, along with conservation recommendations. About 9.2(28.3%) out of 32.5 km of all shores surveyed in this study were used by nesting hawksbill turtles follows: Nakhiloo: 1.4 km(52% of potential nesting area);Ommolgorm: 1.94 km(40%); Kharko: 3.4 km(28%), and NMCNP: 2.46 km(18.9%). The average nesting density was calculated as 131 nests/km at Nakhiloo, 76 nests/km at Ommolgorm, 7 nests/km at Kharko, and 15 nests per km at NMCNP. Highest nesting density was observed in Nakhiloo and Ommolgorm. It is thought that high hawksbill nesting density in these islands seems likely a result of limiting adequate nesting shores rather than the size of population, and also low density in Kharko and NMCNP more related to past and current pressures and low population density. With the exception of Ommolgorm Island, sands at the nesting grounds were well sorted.Grain size indicated that female hawksbill turtles in the Iranian Persian Gulf nest in sands that are generally mixed, with mean grain size ranging from coarse sands(0.4Φ;～0.5–1 mm) to fine sands(2Φ;～0.25 mm). We provide and discuss conservation recommendations and suggestions for future.     

Reliability and sensitivity analysis of wedge stability in the abutments of an arch dam using artificial neural network

In this study, the seismic stability of arch dam abutments is investigated within the framework of the probabilistic method. A large concrete arch dam is considered with six wedges for each abutment. The seismic safety of the dam abutments is studied with quasi-static analysis for different hazard levels. The Londe limit equilibrium method is utilized to calculate the stability of the wedges in the abutments. Since the finite element method is time-consuming, the neural network is used as an alt...     

U, Th, K and Cs activity concentrations along the southern coast of the Caspian Sea, Iran

The determination of activity concentrations of the radioactive elements ²³⁸U, ²³²Th, ⁴⁰K and ¹³⁷Cs was performed on grab samples taken from a polluted environment. The samples were sliced into strata from 5 cm depth, dried and ground to sieved through a 170 mesh size prior to the analysis. Activity concentration was quantified using gamma spectroscopy. The results showed that the concentrations of activity in the sediment samples are 177 ± 12.4, 117 ± 11.5, 1085 ± 101.6 and 131 ± 4.8 Bq kg⁻¹ for ²³⁸U, ²³²Th, ⁴⁰K and ¹³⁷Cs, respectively. In general, the distribution of activity concentrations along the southern coast of the Caspian Sea area exceeded international limits. The hazard index of the samples was 0.19-0.88, with an average of 0.49. The mean values of radium equivalent activity and dose rate are 176 Bq kg⁻¹ and 63 nGy h⁻¹, respectively.     

Optimal design of soil dynamic compaction using genetic algorithm and fuzzy system

Computational intelligent techniques, such as fuzzy and genetic algorithm, have proven to be useful in modeling of complex nonlinear phenomena such as dynamic compaction. Dynamic compaction method is used to improve the mechanical behavior of underlying soil layers especially loose granular materials. The method involves the repeated impart of high-energy impacts to the soil surface using steel or concrete tampers with weights ranging 10–40 ton and with drop heights ranging 10–40 m. A relatively exact estimation of dynamic compaction level is of major concern to geotechnical engineers. This paper develops a fuzzy set base method for the analysis of dynamic compaction phenomenon. In this model, the input variables are tamper weight, height of tamper drop, print spacing, tamper radius, number of impact and soil layer geotechnical properties. The main shortcoming of this technique is uncertainty to locate the best sketch of dynamic compaction to gain maximum effect of this method of soil improvement. Therefore, this paper describes the incorporation of genetic algorithm methodology using fuzzy system for determining the optimum design of dynamic compaction. Subsequently, it will be shown that the genetic algorithm has some abilities in the optimization of dynamic compaction design. Also different manners of this algorithm are compared and then the optimized structure of genetic algorithm will be suggested for dynamic compaction.     

Trends and occurrences of nitrate in the groundwater of the West Bank, Palestine

Groundwater is the major source of water to the Palestinians. Efficient management of this resource requires a good understanding of its status. This understanding necessitates a characterization of the quality of the utilizable volumes. This paper focuses on the assessment of nitrate concentrations in the aquifers of the West Bank, Palestine. A preliminary statistical analysis is carried out for the spatial and temporal distributions of the nitrate concentrations. GIS is utilized to facilitate the analysis and to efficiently account for the spatiality of nitrate concentrations. The analysis was carried out at different spatial levels and key parameters including soil type, watersheds, depth, population, and rainfall. It is observed that elevated nitrate concentrations in the groundwater greatly coincide with increasing rainfall, particularly in the last few years. Results confirm that the annual mean nitrate concentration in the Western groundwater basin has an increasing trend over the period from 1982 to 2004 indicating its vulnerability to contamination. This result can be attributed to the agricultural activities along with the high groundwater recharge. However, leaking septic and sewer systems are considerably causing nitrate contamination of groundwater in populated areas. Overall, the recommendations call for an immediate intervention to manage the quality problems in the West Bank aquifers.     

Petrochemistry of sandstones from Neoproterozoic basins of the Bastar craton, Central Indian Shield: Implications for paleoweathering, provenance and tectonic history

Petrographic analysis and chemical analysis of major and trace elements including rare earth elements of the Neoproterozoic sandstones from the Chandarpur Group and the Tiratgarh Formation have been carried out to determine their provenance, tectonic setting and weathering conditions. All sandstone samples are highly enriched in quartz but very poor in feldspar and lithic fragments. Petrographically and geochemically these sandstones are classified as subarkose, sublitharenite and arenite. The Chemical Index of Alteration (CIA mean 68) and Th/U ratios (mean 4.2) for these sandstones suggest their moderate weathering nature. Generally, all sandstone samples are strongly depleted in major elements (except SiO₂), trace elements (except Zr) and REE in comparison with Post Archean Australian Shale (PAAS) and Upper Continental Crust (UCC). Their mineralogy and mean of elemental ratios suitable for determination of provenance and tectonic setting, e.g. Al₂O₃/SiO₂ (0.02), K₂O/Na₂O (10), Eu/Eu* (0.67), (La/Lu)n (10.4), La/Sc (3), Th/Sc (1.2), La/Co (0.22), Th/Co (0.08), and Cr/Th (7.2), support a felsic source and a passive margin tectonic setting for these sandstones. Also these key elemental ratios do not show much variation over a range of SiO₂. Thus we attest their significance in determining source rock characteristics of quartz rich sandstones. Chondrite‐normalized REE patterns with LREE enrichment and a strong negative Eu anomaly are also attributed to felsic source rock characteristics for these sandstones. The source rocks identified are granite and gneiss of the Bastar craton. Minor amounts may have been derived from older supracrustals of the Bastar craton. However, the major element data of the Paleoproterozoic Sakoli schists when compared with those of the Neoproterozoic sandstones indicate that the schists were derived from a mafic source and deposited in an active continental margin tectonic setting. There is, however, little difference in CIA values between the Paleoproterozoic Sakoli schists and Neoproterozoic sandstones, indicating prevailing of similar (moderate‐intense) weathering conditions throughout the Proterozoic in the Bastar craton. Our study also suggests a change in the provenance and tectonic setting of deposition of sediments from dominantly a mafic source and an active continental margin in the Paleoproterozoic to dominantly granite and gneiss (felsic source) and a passive continental margin in the Neoproterozoic in the Bastar craton.