Effect of superstructure stiffness on liquefaction-induced failure Mechanisms

Soil liquefaction following strong earthquakes causes extensive damage to civil engineering structures. Foundations of buildings, bridges etc can suffer excessive rotation/settlement due to liquefaction. Many of the recent earthquakes bear testimony for such damage. In this article a hypothesis that "Superstructure stiffness can determine the type of liquefaction-induced failure mechanism suffered by the foundations" is proposed. As a rider to this hypothesis, it will be argued that liquefaction will cause failure of a foundation system in a mode of failure that offers least resistance. Evidence will be offered in terms of field observations during the 921 Ji-Ji earthquake in 1999 in Taiwan and Bhuj earthquake of 2001 in India. Dynamic centrifuge test data and finite element analyses results are presented to illustrate the traditional failure mechanisms. Copyright © 2010, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Information theory, inference, and learning algorithms

Fun and exciting textbook on the mathematics underpinning the most dynamic areas of modern science and engineering.

Automated 3D Structure Inference of Civil Infrastructure Using a Stereo Camera Set

The commercial far-range (>10m) infrastructure spatial data collection methods are not completely automated. They need significant amount of manual post-processing work and in some cases, the equipment costs are significant. This paper presents a method that is the first step of a stereo videogrammetric framework and holds the promise to address these issues. Under this method, video streams are initially collected from a calibrated set of two video cameras. For each pair of simultaneous video frames, visual feature points are detected and their spatial coordinates are then computed. The result, in the form of a sparse 3D point cloud, is the basis for the next steps in the framework (i.e., camera motion estimation and dense 3D reconstruction). A set of data, collected from an ongoing infrastructure project, is used to show the merits of the method. Comparison with existing tools is also shown, to indicate the performance differences of the proposed method in the level of automation and the accuracy of results.

Understanding ground deformation mechanisms during multi-propped excavation in soft clay

To maximize the utility of high land cost in urban development, underground space is commonly exploited, both to reduce the load acting on the ground and to increase the space available. The execution of underground constructions requires the use of appropriate retaining wall and bracing systems. Inadequate support systems have always been a major concern, as any excessive ground movement induced during excavation could cause damage to neighboring structures, resulting in delays, disputes and cost overruns. Experimental findings on the effect of wall stiffness, depth of the stiff stratum away from the wall toe and wall toe fixity condition are presented and discussed. © 2012 Taylor & Francis Group.

Linear gaussian computations for near-exact Bayesian Monte Carlo inference in skewed alpha-stable time series models

In this paper we study parameter estimation for time series with asymmetric α-stable innovations. The proposed methods use a Poisson sum series representation (PSSR) for the asymmetric α-stable noise to express the process in a conditionally Gaussian framework. That allows us to implement Bayesian parameter estimation using Markov chain Monte Carlo (MCMC) methods. We further enhance the series representation by introducing a novel approximation of the series residual terms in which we are able to characterise the mean and variance of the approximation. Simulations illustrate the proposed framework applied to linear time series, estimating the model parameter values and model order P for an autoregressive (AR(P)) model driven by asymmetric α-stable innovations. © 2012 IEEE.

Decomposing signals into a sum of amplitude and frequency modulated sinusoids using probabilistic inference

There are many methods for decomposing signals into a sum of amplitude and frequency modulated sinusoids. In this paper we take a new estimation based approach. Identifying the problem as ill-posed, we show how to regularize the solution by imposing soft constraints on the amplitude and phase variables of the sinusoids. Estimation proceeds using a version of Kalman smoothing. We evaluate the method on synthetic and natural, clean and noisy signals, showing that it outperforms previous decompositions, but at a higher computational cost. © 2012 IEEE.

Failure mechanisms in brittle laminates

Steady-state tunneling and plane-strain delamination of an H-shape crack are examined for elastic, isotropic multi layers. Both tunneling and delamination are analysed by employing linear elastic fracture mechanics within a 2D finite element framework. Failure maps are produced to reveal the sensitivity of cracking path to the relative toughness of layer and interface, and to the stiffness mismatch of layers.

Optimal inference of sameness.

Deciding whether a set of objects are the same or different is a cornerstone of perception and cognition. Surprisingly, no principled quantitative model of sameness judgment exists. We tested whether human sameness judgment under sensory noise can be modeled as a form of probabilistically optimal inference. An optimal observer would compare the reliability-weighted variance of the sensory measurements with a set size-dependent criterion. We conducted two experiments, in which we varied set size and individual stimulus reliabilities. We found that the optimal-observer model accurately describes human behavior, outperforms plausible alternatives in a rigorous model comparison, and accounts for three key findings in the animal cognition literature. Our results provide a normative footing for the study of sameness judgment and indicate that the notion of perception as near-optimal inference extends to abstract relations.

Separating poroviscoelastic deformation mechanisms in hydrogels

Hydrogels have applications in drug delivery, mechanical actuation, and regenerative medicine. When hydrogels are deformed, load-relaxation arising from fluid flow - poroelasticity - and from rearrangement of the polymer network - viscoelasticity - is observed. The physical mechanisms are different in that poroelastic relaxation varies with experimental length-scale while viscoelastic does not. Here, we show that poroviscoelastic load-relaxation is the product of the two individual responses. The difference in length-scale dependence of the two mechanisms can be exploited to uniquely determine poroviscoelastic properties from simultaneous analysis of multi-scale indentation experiments, providing insight into hydrogel physical behavior. © 2013 American Institute of Physics.

Statistical inference for single- and multi-band probabilistic amplitude demodulation.

Amplitude demodulation is an ill-posed problem and so it is natural to treat it from a Bayesian viewpoint, inferring the most likely carrier and envelope under probabilistic constraints. One such treatment is Probabilistic Amplitude Demodulation (PAD), which, whilst computationally more intensive than traditional approaches, offers several advantages. Here we provide methods for estimating the uncertainty in the PAD-derived envelopes and carriers, and for learning free-parameters like the time-scale of the envelope. We show how the probabilistic approach can naturally handle noisy and missing data. Finally, we indicate how to extend the model to signals which contain multiple modulators and carriers.

Failure mechanisms in fibrous scaffolds.

Polymeric fibrous scaffolds have been considered as replacements for load-bearing soft tissues, because of their ability to mimic the microstructure of natural tissues. Poor toughness of fibrous materials results in failure, which is an issue of importance to both engineering and medical practice. The toughness of fibrous materials depends on the ability of the microstructure to develop toughening mechanisms. However, such toughening mechanisms are still not well understood, because the detailed evolution at the microscopic level is difficult to visualize. A novel and simple method was developed, namely, a sample-taping technique, to examine the detailed failure mechanisms of fibrous microstructures. This technique was compared with in situ fracture testing by scanning electron microscopy. Examination of three types of fibrous networks showed that two different failure modes occurred in fibrous scaffolds. For brittle cracking in gelatin electrospun scaffolds, the random network morphology around the crack tip remained during crack propagation. For ductile failure in polycaprolactone electrospun scaffolds and nonwoven fabrics, the random network deformed via fiber rearrangement, and a large number of fiber bundles formed across the region in front of the notch tip. These fiber bundles not only accommodated mechanical strain, but also resisted crack propagation and thus toughened the fibrous scaffolds. Such understanding provides insight for the production of fibrous materials with enhanced toughness.