Analysis of shear‐dominated RC columns using the nonlinear truss analogy

This paper uses nonlinear truss models for the analysis of shear‐dominated reinforced concrete (RC) columns subjected to cyclic loading. A previously established method, aimed to the analysis of RC walls, is enhanced to allow simulations of column members. The concrete constitutive equations are modified to account for the contribution of the aggregate interlock to the shear resistance. Additionally, an equation is proposed to determine the inclination angle of the diagonal members in the truss models. The modeling approach is validated using the results of quasi‐static and dynamic tests on shear‐dominated RC columns. The combination of predictive capabilities and conceptual simplicity establishes truss‐based models as an attractive approach for the systematic analysis of shear‐dominated RC frame construction. Copyright © 2014 John Wiley & Sons, Ltd.     

River–groundwater connectivity in a karst system,Wellington, New South Wales,Australia

The characterization of river–aquifer connectivity in karst environments is difficult due to the presence of conduits and caves. This work demonstrates how geophysical imaging combined with hydrogeological data can improve the conceptualization of surface-water and groundwater interactions in karst terrains. The objective of this study is to understand the association between the Bell River and karst-alluvial aquifer at Wellington, Australia. River and groundwater levels were continuously monitored, and electrical resistivity imaging and water quality surveys conducted. Two-dimensional resistivity imaging mapped the transition between the alluvium and karst. This is important for highlighting the proximity of the saturated alluvial sediments to the water-filled caves and conduits. In the unsaturated zone the resistivity imaging differentiated between air- and sediment-filled karst features, and in the saturated zone it mapped the location of possible water- and sediment-filled caves. Groundwater levels are dynamic and respond quickly to changes in the river stage, implying that there is a strong hydraulic connection, and that the river is losing and recharging the adjacent aquifer. Groundwater extractions (1,370 ML, megalitres, annually) from the alluvial aquifer can cause the groundwater level to fall by as much as 1.5 m in a year. However, when the Bell River flows after significant rainfall in the upper catchment, river-leakage rapidly recharges the alluvial and karst aquifers. This work demonstrates that in complex hydrogeological settings, the combined use of geophysical imaging, hydrograph analysis and geochemical measurements provide insights on the local karst hydrology and groundwater processes, which will enable better water-resource and karst management.     

A method for matching response spectra of endurance time excitations via the Fourier transform

The endurance time(ET) method is a dynamic analysis in which structures are subjected to intensifying excitations, also known as ET excitation functions(ETEF). The ET method is a tool for structural response prediction. The main advantage of the ET method over conventional approaches is its much lower demand for computational efforts. The concept of acceleration spectra is used in generating existing ETEFs. It is expected that ETEF acceleration spectra increase consistently with time and remain proportional to a target spectrum. Nonlinear unconstrained optimization is commonly used to generate ETEFs. Generating new ETEFs is a complicated time-consuming mathematical problem. If the target acceleration spectrum changes, new ETEFs must be generated. This study intends to modify existing ETEFs to be compatible with a desired acceleration spectrum. This process, called spectral matching, obviates the need for using the complicated generating procedure in simulating new ETEFs. ETEFs spectral matching is introduced in this paper for the first time. A Fourier-based method for ETEFs spectral matching is proposed. This algorithm is then applied in a case study. Results are presented to prove the efficiency of the algorithm.     

Prediction of Water Quality Index by Support Vector Machine: a Case Study in the Sefidrud Basin,Northern Iran

Water Resources - The objectives of this study were to predict the water quality index using Support Vector Machine (SVM) model and to identify the most important attributes affecting the...