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.     

Prediction of longitudinal dispersion coefficient in natural rivers using a cluster-based Bayesian network

The longitudinal dispersion coefficient is a key element in determining the distribution and transmission of pollution, especially when cross-sectional mixing is completed. However, the existing predictive techniques for this purpose exhibit great amounts of uncertainty. The main objective of this study is to present a more accurate model for predicting longitudinal dispersion coefficient in natural rivers and streams. Bayesian network (BN) approach was considered in the modeling procedure. Two forms of input variables including dimensional and dimensionless parameters were examined to find the best model structure. In order to increase the performance of the model, the clustering method as a preprocessing data technique was applied to categorize the data in separate groups with similar characteristics. An expansive data set consisting of 149 field measurements was used for training and testing steps of the developed models. Three performance evaluation criteria were adopted for comparison of the results of the different models. Comparison of the present results with the artificial neural network (ANN) model and also well-known existing equations showed the efficiency of the present model. The performance of dimensionless BN model 30% is more than dimensional ones in terms of the root mean square error. The accuracy criterion was increased from 70 to 83% by performing clustering analysis on the BN model. The BN-cluster model 43% is more accurate than ANN model in terms of the accuracy criterion. The results indicate that the BN-cluster model give 16% better results than the best available considered model in terms of the accuracy criterion. The developed model provides a suitable approach for predicting pollutant transport in natural rivers.     

Postgrouted helical piles behavior through physical modeling by FCV

Piling procedure may disturb the surrounding soil, due to the installation particularly for cast-in-place piles. It causes a reduction in the soil strength parameters and, consequently, pile capacity. To overcome shortcomings and also for improving piles’ capacity, postgrouting as a compensation method is recognized and more developed in recent years. Helical piles, those are used widely in marine and land projects, although, are driven by torque implementation, but soil disturbance is noticed, where number of the helices become up to 3 and more. In this paper, an experimental study program is performed by frustum-confined vessel (FCV) to investigate bearing capacity of model helical piles and also postgrouted cases’ performance. FCV has been used because of its linear distribution of vertical and horizontal stresses from zero at top to maximum at bottom which simulates real field stress conditions. Through experimental study, small-scale helical model piles were made of 4-mm-thick steel plate and have been used with a length of 750?mm. The shaft and helix diameters of model piles have been 32 and 89?mm, respectively. So, the helix-to-shaft ratio (wing ratio) was about 2.8. The helical model piles installed in fine-grained sand as a surrounding soil and then axial loading tests before and after grouting were performed to achieve ultimate pile capacity. Results indicated postgrouting can improve both ratios of toe and frictional soil–pile interactions including upgrading β and N_t factors. In addition, the post grouting phenomena can change the pile geometry due to treated soil bond, resulting better functioning. Therefore, it is a proper method to improve helical piles performance and compensate installation effects in capacity mobilization.     

Strike-slip faulting, rotation, and along-strike elongation in the Kopeh Dagh mountains, NE Iran

The Kopeh Dagh is a linear mountain range separating the shortening in Iran from the stable, flat Turkmenistan platform. In its central part is an array of active right-lateral strike-slip faults that obliquely cut the range and produce offsets of several kilometres in the geomorphology and geological structure. They are responsible for major destructive earthquakes in the 19th and 20th centuries and represent an important seismic hazard for this now-populous region of NE Iran. These strike-slip faults all end in thrusts, revealed by the uplift and incision of Late Quaternary river terraces, and do not continue beyond the Atrak river valley, which forms the southern margin of the Kopeh Dagh. The cumulative offset on these strike-slip faults, and their associated rotation about vertical axes, can account for ∼60 km of N–S shortening. This value is similar to estimates of the Late Quaternary N–S right-lateral shear between central Iran and Afghanistan, which must be accommodated in NE Iran. The strike-slip faults also require ∼30 km of along-strike extension of the Kopeh Dagh, which is taken up by the westward component of motion between the South Caspian Basin and both Eurasia and Central Iran. It is probable that these motions occurred over the last ∼10 Ma.     

Design and implementation of a model predictive observer for AHRS

A GPS-aided Inertial Navigation System (GAINS) is used to determine the orientation? position and velocity of ground and aerial vehicles. The data measured by Inertial Navigation System (INS) and GPS are commonly integrated through an Extended Kalman Filter (EKF). Since the EKF requires linearized models and complete knowledge of predefined stochastic noises? the estimation performance of this filter is attenuated by unmodeled nonlinearity and bias uncertainties of MEMS inertial sensors. The Attitude Heading Reference System (AHRS) is applied based on the quaternion and Euler angles methods. A moving horizon-based estimator such as Model Predictive Observer (MPO) enables us to approximate and estimate linear systems affected by unknown uncertainties. The main objective of this research is to present a new MPO method based on the duality principle between controller and observer of dynamic systems and its implementation in AHRS mode of a low-cost INS aided by a GPS. Asymptotic stability of the proposed MPO is proven by applying Lyapunov’s direct method. The field test of a GAINS is performed by a ground vehicle to assess the long-time performance of the MPO method compared with the EKF. Both the EKF and MPO estimators are applied in AHRS mode of the MEMS GAINS for the purpose of real-time performance comparison. Furthermore? we use flight test data of the GAINS for evaluation of the estimation filters. The proposed MPO based on both the Euler angles and quaternion methods yields better estimation performances compared to the classic EKF.     

Statistical modeling the effect of sediment physicochemical properties on the concentration of heavy metal (case study: Musa Creek,SW Iran)

Heavy metal accumulation in sediments is important even at low levels due to their irresolvable character and harmful effects. Therefore, contamination of creeks, especially their sediments, is highly important for scientific communities. This study investigates the relationship between heavy metal accumulation and some physicochemical parameters of sediments (pH, EC, calcium carbonate, texture, specific gravity, density, porosity and percentage of organic matter) in a stretch of Musa Creek beaches. The results showed that the studied sediments are extremely salty and have slight variations in terms of pH. Although there are mostly clay-sized sediments in the studied area, their mineralogical composition contains calcite with smaller amounts of dolomite, aragonite and halite minerals. The correlation between each of the parameters and heavy metal concentration was modeled using OLS regression. Cr, Ni, Zn and Pb concentrations are positively correlated with each other and inversely correlated with Cd. The accumulation of heavy metals is directly related to parameters such as EC, organic matter, clay and silt, specific gravity and porosity; it is negatively related to calcium carbonate, sand and density parameters. Owing to slight variations, the pH parameter lacks any significant correlation with heavy metal concentrations.     

Determination of Storage Coefficients During Pumping and Recovery

An aquifer test is used mostly to determine the storage coefficient and transmissivity. Although residual drawdown data are widely used in estimating the transmissivity of aquifers, the estimation of storage coefficients with recovery data is controversial. Some researchers have proposed methods to estimate storage coefficients with recovery data by assuming equality of storage coefficients for the recovery and pumping periods (S = S′). The aim of this study is to determine storage coefficients without such an assumption, that is, S≠S′. The method is a modified version of Banton‐Bangoy's method without considering drawdown data due to pumping. Drawdown is plotted vs. the logarithmic ratio (t′/t) or time since pumping stopped to the duration of pumping and the ratio of storage coefficient during recovery to the storage coefficient from the pumping period (S′/S). The method is verified with one case study and two synthetic examples. Thus, it is possible to determine storage coefficient of pumping period accurately without any data from pumping period by recovery data.     

Inverse problem theory to chemo-poroelastic parameters estimation: an analytical/experimental investigation

Shale formation swelling is one of the main factors affecting wellbore instability and associated problems in drilling operation. In order to eliminate these problems, it is important to investigate formation characteristics and understand mechanisms of rock-fluid interaction, from chemical/mechanical point of view. Shale membrane efficiency is known as an important parameter affecting wellbore instability. In order to measure this parameter, many mathematical models and experimental efforts have been carried out which consider mechanical-chemical processes for rock-fluid interactions. In this study, the field equations governing the problem have been derived based on the linear chemo-poroelastic theory and solved using analytical/numerical methods. Afterward, a comprehensive workflow to characterize the chemo-poroelastic parameters of illite-rich shale is conducted in the laboratory. In fact, mineralogical and apparent properties of shale sample have been described and some setups were performed such as triaxial test and membrane efficiency. Then genetic algorithm has been applied to solve an inverse problem and get a match between experimental data and modeling results. Ultimately, the three important properties in shale-fluid interactions, i.e., shale membrane efficiency, hydraulic, and chemical diffusivity coefficient have been estimated. Comparing the simulation results with the experimental data indicates that the simulation model can appropriately simulate the pore pressure transmission test. With this approach, the required parameters can be estimated with good accuracy without using time-consuming and costly tests.     

Evaluating Boolean,AHP and WLC methods for the selection of waste landfill sites using GIS and satellite images

The city of Saqqez has a population of 140,000 people, making it one of the largest cities in Iran. Population growth, consumerism, and change in eating habits, such as the increased use of packaged products, is causing the accumulation of waste in this city to increase. In this study, the selection of a waste landfill site for Saqqez focused on 13 layers of geography information that was used by the IDRISI and Arc GIS software. Different models of the analytic multi-criteria decision-making process, such as an analytical hierarchy process (AHP), weighted linear combination (WLC), and Boolean logic, were used to manage layers to establish specific databases for urban waste landfills. Satellite images (Landsat ETM⁺ and SPOT 5), proposed sites and a land use map of the study area were also used. The results of this study indicated that two methods (AHP and WLC) in the early stages had better decision-making powers for locating landfill sites when compared to Boolean logic. Overlapping and compounding the similarities between these models in Arc GIS software, a 74-ha site was found. This site will be able to accept 130 tons of waste per day for the next 20 years.