Response of Pile Under Dynamic Loading

The need for a better understanding of soil pile interaction problem under dynamic loading especially in a nonlinear soil medium has always been felt by engineers. This paper presents a PC based Finite Element I Finite Difference analysis of a Three Dimensional soil pile interaction problem in Elasto Plastic soil under transient and periodic dynamic loading. Assuming separation of variable is permitted method of Finite Element has been used over space and then the solution proceeds over time by explicit integration. Numerical experimentation with a 3 x 3 x 3 model offers a stable response which (qualitatively) with Green\u27s function obtained by other authors. Permanent settlement in elasto plastic soil under periodic loading has also been obtained

Multilepton Signatures of the Higgs Boson through its Production in Association with a Top-quark Pair

We consider the possible production of the Higgs Boson in association with a top-quark pair and its subsequent decay into a tau-lepton pair or a W-boson pair. This process can give rise to many signatures of the Higgs boson. These signatures can have electrons, muons, tau jets, bottom jets and/or light flavour jets. We analyze the viability of some of these signatures. We will look at those signatures where the background is minimal. In particular, we explore the viability of the signatures "isolated 4 electron/muon" and "isolated 3 electron/muon + a jet" The jet can be due to a light flavour quark/gluon, a bottom quark, or a tau lepton. Of all these signatures, we find that "isolated 3 electron/muon + a tau jet", with an extra bottom jet, can be an excellent signature of this mode of the Higgs boson production. We show that this signature may be visible within a year, once the Large Hadron Collider (LHC) restarts. Some of the other signatures would also be observable after the LHC accumulates sufficient luminosity.Comment: 11 pages, 1 Figur

Pseudo-value regression of clustered multistate current status data with informative cluster sizes

Multistate current status (CS) data presents a more severe form of censoring due to the single observation of study participants transitioning through a sequence of well-defined disease states at random inspection times. Moreover, these data may be clustered within specified groups, and informativeness of the cluster sizes may arise due to the existing latent relationship between the transition outcomes and the cluster sizes. Failure to adjust for this informativeness may lead to a biased inference. Motivated by a clinical study of periodontal disease (PD), we propose an extension of the pseudo-value approach to estimate covariate effects on the state occupation probabilities (SOP) for these clustered multistate CS data with informative cluster or subcluster sizes. In our approach, the proposed pseudo-value technique initially computes marginal estimators of the SOP utilizing nonparametric regression. Next, the estimating equations based on the corresponding pseudo-values are reweighted by functions of the cluster sizes to adjust for informativeness. We perform a variety of simulation studies to study the properties of our pseudo-value regression based on the nonparametric marginal estimators under different scenarios of informativeness. For illustration, the method is applied to the motivating PD dataset, which encapsulates the complex data-generating mechanism.Comment: 19 pages, 5 figures, 5 table

Dynamic Plasticity in Pile-Soil Interaction Problems

The dynamic soil-pile interaction problem is solved by the method of characteristics. The nonlinear, non-homogeneous problem was idealized as a piecewise linear problem. The numerical instability of semi-infinite soil column model has been reported, and a stable model, wherein the soil column below, the pile tip is replaced by a single spring and dashpot, has also been presented. The results obtained from the method of characteristics have been compared with those obtained by explicit finite difference scheme. The convergence and stability were studied numerically

Realization of optical fiber regenerated gratings by rapid cooling and split annealing

Rapid cooling, or quenching, during regeneration of seed gratings in standard single-mode silica optical fiber is explored. It is shown that regeneration can be broken up into stages in time. The novel, to the best of our knowledge, method of ``split annealing'' offers a unique tool for optimiz-ing regeneration and studying fundamental glass science within a one-dimensional bi-material system. We demon-strate regeneration at temperatures as high as T= 1200 degrees C for the first time as well as opening up an approach suited to batch processing of regenerated gratings. (c) 2022 Optica Publishing Grou

Optimum Placement of Long Gauge FBG Sensor in Reinforced Concrete Bridge: A Case Study

In the world today, civil infrastructure plays a major role in the advancement of the modern age. They are huge in scale, complex in their behaviour and create great impact in everyday life. To ensure safety of these structures, assessment of their structural integrity is an important and challenging task. The sole purpose of structural health monitoring is to detect damage in the structures and suggest suitable rehabilitation measures. Various sensors are employed to achieve the task of damage detection and establish a warning system to avoid failure of the structures. For large structures, long-gauge Fibre Bragg Grating (FBG) sensors which are sensitive to the global behaviour, can be suitably used for this purpose. However, health monitoring of a structure with large number of sensors is expensive and hence there is a need to optimize the number of sensors deployed to minimize the cost of the exercise without compromising on performance assessment. For this purpose, several optimization algorithms are available in literature. In this study, the Effective Independence Method (EIM) which optimizes the response of the structure based on modal analysis, is used to derive the Optimum sensor placement (OSP) protocol for a reinforced concrete (RC) bridge-deck in Poland, the geometry of which has been taken from literature. This will enable the placement of 40 long gauge FBG sensors in regions for efficient damage response in the bridge-deck. Further, the optimum orientation of the sensors is further validated with a finite element model of the bridge-deck, where a moving load is applied, and strains are recorded in the sensing fibre in both longitudinal (along length) and transverse (along breadth) alignments. It has been found that long gauge FBG sensors placed in the transverse direction are more efficient in damage detection than when they are placed longitudinally

Code Mixed Cross Script Factoid Question Classification - A Deep Learning Approach

[EN] Before the advent of the Internet era, code-mixing was mainly used in the spoken form. However, with the recent popular informal networking platforms such as Facebook, Twitter, Instagram, etc., in social media, code-mixing is being used more and more in written form. User-generated social media content is becoming an increasingly important resource in applied linguistics. Recent trends in social media usage have led to a proliferation of studies on social media content. Multilingual social media users often write native language content in non-native script (cross-script). Recently Banerjee et al. [9] introduced the code-mixed cross-script question answering research problem and reported that the ever increasing social media content could serve as a potential digital resource for less-computerized languages to build question answering systems. Question classification is a core task in question answering in which questions are assigned a class or a number of classes which denote the expected answer type(s). In this research work, we address the question classification task as part of the code-mixed cross-script question answering research problem. We combine deep learning framework with feature engineering to address the question classification task and enhance the state-of-the-art question classification accuracy by over 4% for code-mixed cross-script questions.The work of the third author was partially supported by the SomEMBED TIN2015-71147-C2-1-P MINECO research project.Banerjee, S.; Kumar Naskar, S.; Rosso, P.; Bandyopadhyay, S. (2018). Code Mixed Cross Script Factoid Question Classification - A Deep Learning Approach. Journal of Intelligent & Fuzzy Systems. 34(5):2959-2969. https://doi.org/10.3233/JIFS-169481S2959296934