Prof. P. Anbazhagan, Department of Civil Engineering, IISc Bangalore
Brief Resume of Research and Development
Seismic microzonation studies
A methodology for seismic hazard and microzonation of urban centers considering all possible hazards due to earthquake was proposed. This methodology covers calculations and mapping of seismological hazards, geotechnical hazards of site effects, liquefaction, landslides and tsunami hazards. These hazard parameters are estimated based on the region and integrated by assigning proper ranks and weights based on their importance. Integrated hazard index values are used to prepare the final zonation map of the region. This proposed methodology for seismic microzonation was adopted for microzonation of Bangalore. At present, preparation of microzonation map of Lucknow city is under progress. In future these maps will help to revise our countries current seismic code provision as this methodology is being used for the preparation of microzonation maps of many other cities. More details
Rock depth mapping and site classification system for shallow engineering bedrock
Rock depth plays an important role in the modification of seismic waves emerging from deeper and denser materials in the sub-surface regime. Studies have been carried out to map the weathered and engineering bedrock using Multichannel Analysis of Surface Wave (MASW) and the results have been compared with borehole data. 1-D and 2-D surveys are carried out. The dispersion of surface waves are modeled using Knopoffs method, while phase velocities are modeled using the bisection method. The shear wave velocity (SWV) was derived by inverting the dispersive phase velocity and was used to locate rock depths. The depth of weathered rock obtained by considering SWV of 330�30 m/s matches well with the borehole data. The engineering bed rock having SWV of 760�60 m/s is comparable with the depth of engineering rock estimated from the borehole data. This study shows that SWV can be used to estimate the depth of weathered and engineering bedrock in residual terrains, which are important for geotechnical applications, site response and microzonation studies. Further, Geostatistical model based on Ordinary Kriging technique, Artificial Neural Network (ANN) and Support Vector Machine (SVM) models have been developed to predict rock depth levels.
Equivalent SPT N and SWV values for 30 m depths were used for seismic site classification as per recommendation of the National Earthquake Hazards Reduction Program (NEHRP) and International Building Code (IBC). When the depth of the engineering bedrock is shallow, it is found that site classification based on 30 m depth gives a stiffer site class and lower spectral acceleration coefficients. Hence adopting NEHRP/ IBC site classification system for shallow bedrock sites may lead to erroneous estimation of spectral values and amplification.
Correlation between SPT N value and shear modulus for residual soil
Correlations between SPT N values and shear modulus have been developed for sedimentary soils, but such correlations are not available for residual soils. To develop a new correlation between SPT N values and the low strain shear modulus (Gmax) for the regional soil deposits, SPT N and SWV measurements were carried out in a residually formed soil zone. The in- situ density of the soil layers were evaluated using standard procedure. The low strain shear moduli were calculated using measured SWV and soil density that allowed for the development of correlations between SPT, N and Gmax. The role of correction factors for SPT N and SWV in regression modeling was examined. It was found that the best regression model can be obtained for uncorrected value of N and shear modulus in comparison to corrected N and corrected modulus values. The developed equation between N and Gmax is suitable for residual soils (i.e., silty sand or sandy silt) with less percentage of clay.
New road damage intensity scale
Seismic vulnerability of transportation network is equally important as that of civil structures. Conventional seismic vulnerability analysis of roads and transportation networks are carried out using Modified Mercalli Intensity (MMI) scale. The MMI scale is found inadequate to define the damages caused to roads from earthquakes. Hence a new intensity scale has been developed to quantify road damages from earthquakes based on available data. The proposed scale has been called as Road Damage Scale (RDS), which classifies five levels of road damages based on various parameters. The proposed scale has a bearing with the seismic data such as magnitude and epicenter distance and allows forecast of damages to roads from earthquake.
Rail ballast fouling and definition of optimum and critical fouling points for identification
Breakdown of aggregates, transportation of coal/ore and soil intrusion from sub grade contaminates the rail track; this contamination is called as ballast fouling. Due to ballast fouling, the conditions of the rail track may deteriorate considerably depending up on the type of fouling material and the degree of fouling. Presently there is no comprehensive guideline to identify the critical degree of fouling by different types of fouling materials and this has prompted the present study. SWV of clean and fouled ballast were measured in model and field track sections. These SWV values are correlated with the degree of fouling and type of fouling materials. It is found that the SWV of fouled ballast increases with contamination reaches a maximum value and then decreases. This character is used to define optimum and critical fouling points (OFP and CFP). Fouling of ballast reduces voids and there by decreases the drainage. Combined model of permeability and SWV with percentage fouling shows that the drainage condition and SWV of the fouled ballast reduces below acceptable limit beyond CFP. Ground penetrating radar (GPR) with different ground coupled antennas was used to identify the ballast fouling conditions in model and field track sections. Both seismic survey and GPR were compared for the first time and it is found that the seismic survey is relatively slow in comparison to GPR survey. However seismic survey gives quantifiable results, while GPR survey is faster and superior in estimating the depth of fouling.
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