Strong ground motion record selection for the reliable prediction of the mean seismic collapse capacity of a structure group

How to select a limited number of strong ground motion records (SGMRs) is an important challenge for the seismic collapse capacity assessment of structures. The collapse capacity is considered as the ground motion intensity measure corresponding to the drift‐related dynamic instability in the structural system. The goal of this paper is to select, from a general set of SGMRs, a small number of subsets such that each can be used for the reliable prediction of the mean collapse capacity of a particular group of structures, i.e. of single degree‐of‐freedom systems with a typical behaviour range. In order to achieve this goal, multivariate statistical analysis is first applied, to determine what degree of similarity exists between each selected small subset and the general set of SGMRs. Principal Component analysis is applied to identify the best way to group structures, resulting in a minimum number of SGMRs in a proposed subset. The structures were classified into six groups, and for each group a subset of eight SGMRs has been proposed. The methodology has been validated by analysing a first‐mode‐dominated three‐storey‐reinforced concrete structure by means of the proposed subsets, as well as the general set of SGMRs. The results of this analysis show that the mean seismic collapse capacity can be predicted by the proposed subsets with less dispersion than by the recently developed improved approach, which is based on scaling the response spectra of the records to match the conditional mean spectrum. Copyright © 2010 John Wiley & Sons, Ltd.     

The role of tourism in rural development: Evidence from Iran

GeoJournal - Tourism can play an important role in diversifying the rural economy and its expanding in rural areas contributes to the sustainability of the population and the economy of these areas...     

A Comparative Study of Landsat‐7 and Landsat‐8 Data Using Image Processing Methods for Hydrothermal Alteration Mapping

Comparing spaceborne satellite images of Landsat‐8 Operational Land Imager (OLI) and Landsat‐7 Enhanced Thematic Mapper plus (ETM+) was undertaken to investigate the relative accuracy of mapping hydrothermal alteration minerals. The study investigated the northern part of Rabor, which contains copper mineralization occurrences, and is located in the Kerman Cenozoic magmatic assemblage (KCMA), Iran. Image processing methods of band ratio, principal component analysis (PCA), and spectral angle mapper (SAM) were used to map the distribution of hydrothermally altered rocks associated with the porphyry copper mineralization. The band ratio combination of both sensors for mapping altered areas showed similar outcomes. PCA exposed variations in the spatial distribution of hydroxyl‐bearing minerals. The representation of hydrothermal areas using OLI data was more satisfactory than when using ETM+ data. SAM analysis found similar results for mapping hydroxyl‐bearing zones. Verification of the results came through ground investigation and laboratory studies. Rock samples (n = 56) were collected to validate results using thin sections, X‐ray diffraction (XRD) and spectral analyses. Field observations and laboratory analysis revealed that phyllic and propylitic alterations dominate the alteration zones in the study area. Argillic and iron oxides/hydroxides alterations were observed to a lesser degree. The results indicate that alteration maps prepared by OLI data using PCA for visual interpretation are more suitable than those of ETM+ due to a higher radiometric resolution and lower interference between vegetation and altered areas. As the spectral bandwidth of ETM+ band 7 covers absorption feature of propylitic alteration, better mapping of propylitic alterations is achieved using ETM+ data.     

Integrating cellular automata,artificial neural network,and fuzzy set theory to simulate threatened orchards: application to Maragheh,Iran

Urbanization processes challenge the growth of orchards in many cities in Iran. In Maragheh, orchards are crucial ecological, economical, and tourist sources. To explore orchards threatened by urban expansion, this study first aims to develop a new model by coupling cellular automata (CA) and artificial neural network with fuzzy set theory (CA–ANN–Fuzzy). While fuzzy set theory captures the uncertainty associated with transition rules, the ANN considers spatial and temporal nonlinearities of the driving forces underlying the urban growth processes. Second, the CA–ANN–Fuzzy model is compared with two existing approaches, namely a basic CA and a CA coupled with an ANN (CA–ANN). Third, we quantify the amount of orchard loss during the last three decades as well as for the upcoming years up to 2025. Results show that CA–ANN–Fuzzy with 83% kappa coefficient performs significantly better than conventional CA (with 51% kappa coefficient) and CA–ANN (with 79% kappa coefficient) models in simulating orchard loss. The historical data shows a considerable loss of 26% during the last three decades, while the CA–ANN–Fuzzy simulation reveals a considerable future loss of 7% of Maragheh’s orchards in 2025 due to urbanization. These areas require special attention and must be protected by the local government and decision-makers.     

Monitoring above-zone temperature variations associated with CO2 and brine leakage from a storage aquifer

CO₂ injection in saline aquifers induces temperature changes owing to processes such as Joule–Thomson cooling, endothermic water vaporization, exothermic CO₂ dissolution besides the temperature discrepancy between injected and native fluids. CO₂ leaking from the injection zone, in addition to initial temperature contrast due to the geothermal gradient, undergoes similar processes, causing temperature changes in the above zone. Numerical simulation tools were used to evaluate temperature changes associated with CO₂ leakage from the storage aquifer to an above-zone monitoring interval and to assess the monitorability of CO₂ leakage on the basis of temperature data. The impact of both CO₂ and brine leakage on temperature response is considered for three cases (1) a leaky well co-located with the injection well, (2) a leaky well distant from the injector, and (3) a leaky fault. A sensitivity analysis was performed to determine key operational and reservoir parameters that control the temperature signal in the above zone. Throughout the analysis injection-zone parameters remain unchanged. Significant pressure drop upon leakage causes expansion of CO₂ associated with Joule–Thomson cooling. However, brine may begin leaking before CO₂ breakthrough at the leakage pathway, causing heating in the above zone. Thus, unlike the pressure which increases in response to both CO₂ and brine leakage, the temperature signal may differentiate between the leaking fluids. In addition, the strength of the temperature signal correlates with leakage velocity unlike pressure signal whose strength depends on leakage rate. Increasing leakage conduit cross-sectional area increases leakage rate and thus increases pressure change in the above zone. However, it decreases leakage velocity, and therefore, reduces temperature cooling and signal. It is also shown that the leakage-induced temperature change covers a small area around the leakage pathway. Thus, temperature data will be most useful if collected along potential leaky wells and/or wells intersecting potential leaky faults.     

Micromechanical approach to swelling behavior of capillary-porous media with coupled physics

A detailed multiscale analysis is presented of the swelling phenomenon in unsaturated clay-rich materials in the linear regime through homogenization. Herein, the structural complexity of the material is formulated as a three-scale, triple porosity medium within which microstructural information is transmitted across the various scales, leading ultimately to an enriched stress-deformation relation at the macroscopic scale. As a side note, such derived relationship leads to a tensorial stress partitioning that is reminiscent of a Terzaghi-like effective stress measure. Otherwise, a major result that stands out from previous works is the explicit expression of swelling stress and capillary stress in terms of micromechanical interactions at the very fine scale down to the clay platelet level, along with capillary stress emerging due to interactions between fluid phases at the different scales, including surface tension, pore size, and morphology. More importantly, the swelling stress is correlated with the disjoining forces due to electrochemical effects of charged ions on clay minerals and van der Waals forces at the nanoscale. The resulting analytical expressions also elucidate the role of the various physics in the deformational behavior of clayey material. Finally, the capability of the proposed formulation in capturing salient behaviors of unsaturated expansive clays is illustrated through some numerical examples.