Steel rings as seismic fuses for enhancing ductility of cross braced frames

A new remedy is proposed in this study to increase the ductility of cross-braced frames to a level comparable with ductile moment frames. The suggested system consists of one or two concentric steel rings installed in the cross-braced bay vertically. The steel rings are designed such that they fail in bending sooner than failure of the braces in compression. Then the rings act as seismic fuses with multiple bending plastic hinges. Using nonlinear static analysis, it is shown that the proposed system can be designed to behave like cross-braced frames with regard to stiffness and strength, and like special moment frames with regard to ductility. Seismic design factors for the proposed system are recommended based on nonlinear pushover and cyclic analysis studies.

     

A procedure for damage-based seismic design of moment frame structures

Bulletin of Earthquake Engineering - A new method for seismic design of structures with the aim of controlling earthquake damage to a prescribed level is presented in this paper. The method is...     

A Multiple SVM System for Classification of Hyperspectral Remote Sensing Data

With recent technological advances in remote sensing sensors and systems, very high-dimensional hyperspectral data are available for a better discrimination among different complex land-cover classes. However, the large number of spectral bands, but limited availability of training samples creates the problem of Hughes phenomenon or ‘curse of dimensionality’ in hyperspectral data sets. Moreover, these high numbers of bands are usually highly correlated. Because of these complexities of hyperspectral data, traditional classification strategies have often limited performance in classification of hyperspectral imagery. Referring to the limitation of single classifier in these situations, Multiple Classifier Systems (MCS) may have better performance than single classifier. This paper presents a new method for classification of hyperspectral data based on a band clustering strategy through a multiple Support Vector Machine system. The proposed method uses the band grouping process based on a modified mutual information strategy to split data into few band groups. After the band grouping step, the proposed algorithm aims at benefiting from the capabilities of SVM as classification method. So, the proposed approach applies SVM on each band group that is produced in a previous step. Finally, Naive Bayes (NB) as a classifier fusion method combines decisions of SVM classifiers. Experimental results on two common hyperspectral data sets show that the proposed method improves the classification accuracy in comparison with the standard SVM on entire bands of data and feature selection methods.     

Prediction of climate change effects on the runoff regime of a forested catchment in northern Iran

ABSTRACT

The southern coast of the Caspian Sea in northern Iran is bordered by a mountain range with forested catchments which are susceptible to droughts and floods. This paper examines possible changes to runoff patterns from one of these catchments in response to climate change scenarios. The HEC-HMS rainfall–runoff model was used with downscaled future rainfall and temperature data from 13 global circulation models, and meteorological and hydrometrical data from the Casilian (or “Kassilian”) Catchment. Annual and seasonal predictions of runoff change for three future emissions scenarios were obtained, which suggest significantly higher spring rainfall with increased risk of flooding and significantly lower summer rainfall leading to a higher probability of drought. Flash floods arising from extreme rainfall may become more frequent, occurring at any time of year. These findings indicate a need for strategic planning of water resource management and mitigation measures for increasing flood hazards.

EDITOR M.C. Acreman ASSOCIATE EDITOR not assigned     

Chemical zoning of Ca-amphiboles in amphibolites,from the Hamedan area,West Iran

Amphibolite layers of the Hamedan area (Sanandaj-Sirjan zone, west Iran) contain amphibole crystals with strong optical zoning. These amphibolites occur as interlayers in middle Jurassic, Buchan-type andalusite-garnet-staurolite and sillimanite-garnet-andalusite schist of the area that were intruded by late Jurassic magmatic bodies of the Alvand plutonic complex. Electron microprobe analyses results show that the zoned amphiboles have ferrohornblende cores that change to ferroedenite toward the rims. The core-to rim increase of Al, Fe, Na, and K and decrease of Si and Mg along with edenitic substitution in amphiboles is consistent with increase in metamorphic grade. Thermobarometry calculations based on amphibole composition and hornblende-plagioclase thermometry provided 492 to 508 ^o C and 4.3 to 4.9 kbar for the inner cores, 495 to 514 ^o C and 4.5 to 5.1 kbar for the outer cores, 538 to 564 ^o C and 5.3 to 5.8 kbar for the inner rims and 552 to 573 ^o C and 5.5 to 5.9 kbar for the outer rims, respectively. These results point to a nearly isobaric prograde P-T path for the Hamedan area amphibolites, compatible with a metamorphic evolution dominated by the thermal perturbation associated with the late Jurassic magmatism of the northern Sanandaj-Sirjan zone.     

Forecasting Daily Seepage Discharge of an Earth Dam Using Wavelet–Mutual Information–Gaussian Process Regression Approaches

Because of their sensitive structure, earth dams might face failure due to seepage phenomenon. In order to prevent such failure, some equipment like piezometers are installed in the body or foundation of earth dams. This study investigated the importance of piezometer installation level in dam body or foundation using mutual information–wavelet–Gaussian process regression. 27 Piezometers in three section along with reservoir level were employed to predict one-step-ahead seepage discharge of Zonouz earth dam. The daily data of 1 year of piezometer level and reservoir level were collected for this purpose. In order to find the best possible input combination, three groups of modeling scenarios were defined using piezometers and reservoir level time series. As some input combinations had more than two variables, decomposed time series were imposed into mutual information (MI) tool in order to decrement input variables and find the most correlated input–output features. Afterward, mentioned features were imposed into optimized Gaussian process regression (GPR) to be predicted. Different kernels were selected as core tool of GPR, but results demonstrated the capability of radial basis function (RBF) kernel. GPR–RBF structure were optimized using cross-validation technique. Results indicated that input combination including piezometer level and reservoir level of section II, especially piezometer 203 time series led to the best result among all scenarios.     

Finite Element Modeling of Extensional Structures in the Annapurna Region of Central Himalayas

Two-dimensional, elastic, plane-strain, finite element model are generated to investigate the extensional structures mainly normal fault in the Annapurna region, central Himalaya. The numerical study was performed on the Miocene geologic profile considering both of the convergent displacement and rock layer properties in the regime. Results show that the normal fault primarily influenced by model geometry, rheology (layer properties) and boundary condition (applied convergence displacement). Simulated normal fault density exhibits very high intensity in Lesser Himalaya then in the Tethys Himalaya and low intensity in the Higher Himalaya, suggesting the vulnerability of fault development to low-grade metamorphic rock than the high-grade rocks. The location of normal fault predicted by the numerical model analysis is consistent to the position of normal fault segments by Kaneko (J Geol Soc Jpn 103(3):203–226, 1997). In this studies, it also believed that the presence of these normal faults and underthrusting of the sub-Himalayan sequence with associated tectonic forces, the Himalayan Metamorphic belt has been exhumed and differentially domal uplifted and then segmented into several blocks.     

Conversion factors for design spectral accelerations including soil–structure interaction

In this paper maximum response of a single degree of freedom system resting on a flexible base is determined under consistent earthquakes and the results are presented as acceleration spectra including soil–structure interaction (SSI). Flexibility of base is modeled using frequency-dependent springs and dampers. The spring–damper coefficients are calculated for the desired natural mode of vibration of a multi-degree-of-freedom system. Consistency of earthquakes is maintained considering their magnitude, distance, local soil type, and return period. The latter parameter is accounted for by the use of earthquake categories identified by their similar spectral values. Ratio of spectral acceleration modification factors with SSI from this study to those calculated using the ASCE 7-10 procedure are determined for each case. Examination of the resulting curves shows that the mentioned code is conservative/non-conservative in estimation of spectral responses with SSI in certain cases for the lower/higher modes of vibration. The code’s procedure is modified using the developed curves for a conversion factor.     

Development of Rock Engineering Systems-Based Models for Flyrock Risk Analysis and Prediction of Flyrock Distance in Surface Blasting

The environmental effects of blasting must be controlled in order to comply with regulatory limits. Because of safety concerns and risk of damage to infrastructures, equipment, and property, and also having a good fragmentation, flyrock control is crucial in blasting operations. If measures to decrease flyrock are taken, then the flyrock distance would be limited, and, in return, the risk of damage can be reduced or eliminated. This paper deals with modeling the level of risk associated with flyrock and, also, flyrock distance prediction based on the rock engineering systems (RES) methodology. In the proposed models, 13 effective parameters on flyrock due to blasting are considered as inputs, and the flyrock distance and associated level of risks as outputs. In selecting input data, the simplicity of measuring input data was taken into account as well. The data for 47 blasts, carried out at the Sungun copper mine, western Iran, were used to predict the level of risk and flyrock distance corresponding to each blast. The obtained results showed that, for the 47 blasts carried out at the Sungun copper mine, the level of estimated risks are mostly in accordance with the measured flyrock distances. Furthermore, a comparison was made between the results of the flyrock distance predictive RES-based model, the multivariate regression analysis model (MVRM), and, also, the dimensional analysis model. For the RES-based model, R ² and root mean square error (RMSE) are equal to 0.86 and 10.01, respectively, whereas for the MVRM and dimensional analysis, R ² and RMSE are equal to (0.84 and 12.20) and (0.76 and 13.75), respectively. These achievements confirm the better performance of the RES-based model over the other proposed models.