Doubly spectral stochastic finite element method (DSSFEM) for random field problems

Uncertainties in complex dynamic systems play an important role in the prediction of a dynamic response in the mid- and high-frequency ranges. For distributed parameter systems, parametric uncertainties can be represented by random fields leading to stochastic partial differential equations. Over the past two decades, the spectral stochastic finite-element method has been developed to discretize the random fields and solve such problems. On the other hand, for deterministic distributed parameter linear dynamic systems, the spectral finite-element method has been developed to efficiently solve the problem in the frequency domain. In spite of the fact that both approaches use spectral decomposition (one for the random fields and the other for the dynamic displacement fields), very little overlap between them has been reported in literature. In this paper, these two spectral techniques are unified with the aim that the unified approach would outperform any of the spectral methods considered on their own. An exponential autocorrelation function for the random fields, a frequency-dependent stochastic element stiffness, and mass matrices are derived for the axial and bending vibration of rods. Closed-form exact expressions are derived by using the Karhunen-Loève expansion. Numerical examples are given to illustrate the unified spectral approach.

A Method for Evaluation of Product Lifecycle Alternatives under Uncertainty

In each stage of product development, we need to take decisions, by evaluating multiple product alternatives based on multiple criteria. Classical evaluation methods like weighted objectives method assumes certainty about information available during product development. However, designers often must evaluate under uncertainty. Often the likely performance, cost or environmental impacts of a product proposal could be estimated only with certain confidence, which may vary from one proposal to another. In such situations, the classical approaches to evaluation can give misleading results. There is a need for a method that can aid in decision making by supporting quantitative comparison of alternatives to identify the most promising alternative, under uncertain information about the alternatives. A method called confidence weighted objectives method is developed to compare the whole life cycle of product proposals using multiple evaluation criteria under various levels of uncertainty with non crisp values. It estimates the overall worth of proposal and confidence on the estimate, enabling deferment of decision making when decisions cannot be made using current information available.

Structured Learning for Non-Smooth Ranking losses

Learning to rank from relevance judgment is an active research area. Itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major techniques in use. Listwise structured learning has been applied recently to optimize important non-decomposable ranking criteria like AUC (area under ROC curve) and MAP(mean average precision). We propose new, almost-lineartime algorithms to optimize for two other criteria widely used to evaluate search systems: MRR (mean reciprocal rank) and NDCG (normalized discounted cumulative gain)in the max-margin structured learning framework. We also demonstrate that, for different ranking criteria, one may need to use different feature maps. Search applications should not be optimized in favor of a single criterion, because they need to cater to a variety of queries. E.g., MRR is best for navigational queries, while NDCG is best for informational queries. A key contribution of this paper is to fold multiple ranking loss functions into a multi-criteria max-margin optimization.The result is a single, robust ranking model that is close to the best accuracy of learners trained on individual criteria. In fact, experiments over the popular LETOR and TREC data sets show that, contrary to conventional wisdom, a test criterion is often not best served by training with the same individual criterion.

A Reliable method of obtaining Breakthrough Curves of ions in Soils using Transport Equation

Molecular diffusion plays a dominant role in transport of contaminants through fine-grained soils with low hydraulic conductivity. Attenuation processes occur while contaminants travel through the soils. Effective diffusion coefficient (De) is expected to take into consideration various attenuation processes. Effective diffusion coefficient has been considered to develop a general approach for modelling of contaminant transport in soils.The effective diffusion coefficient of sodium in presence of sulphate has been obtained using the column test.The reliability of De, has been checked by comparing theoretical breakthrough curves of sodium ion in soils obtained using advection diffusion equation with the experimental curve.

Site Characterization of Bangalore using Geophysical Method

A number of geophysical methods have been proposed for near-surface site characterization and measurement of shear wave velocity by using a great variety of testing configurations, processing techniques,and inversion algorithms. In particular, two widely-used techniques are SASW (Spectral Analysis of SurfaceWaves) and MASW (Multichannel Analysis of SurfaceWaves). MASW is increasingly being applied to earthquake geotechnical engineering for the local site characterization, microzonation and site response studies.A MASW is a geophysical method, which generates a shear-wave velocity (Vs) profile (i.e., Vs versus depth)by analyzing Raleigh-type surface waves on a multichannel record. MASW system consisting of 24 channels Geode seismograph with 24 geophones of 4.5 Hz frequency have been used in this investigation. For the site characterization program, the MASW field experiments consisting of 58 one-dimensional shear wave velocity tests and 20 two-dimensional shear wave tests have been carried out. The survey points have been selected in such a way that the results supposedly represent the whole metropolitan Bangalore having an area of 220 km2.The average shear wave velocity of Bangalore soils have been evaluated for depths of 5m, 10m, 15m, 20m, 25m and 30 m. The subsoil site classification has been made for seismic local site effect evaluation based on average shear wave velocity of 30m depth (Vs30) of sites using National Earthquake Hazards Reduction Program (NEHRP) and International Building Code (IBC) classification. Soil average shearwave velocity estimated based on overburden thickness from the borehole information is also presented. Mapping clearly indicates that the depth of soil obtained from MASW is closely matching with the soil layers in bore logs. Among total 55 locations of MASW survey carried out, 34 locations were very close to the SPT borehole locations and these are used to generate correlation between Vs and corrected “N” values. The SPT field “N” values are corrected by applying the NEHRP recommended corrections.