Modeling non-stationarity in intensity, duration and frequency of extreme rainfall over India

Significant changes are reported in extreme rainfall characteristics over India in recent studies though there are disagreements on the spatial uniformity and causes of trends. Based on recent theoretical advancements in the Extreme Value Theory (EVT), we analyze changes in extreme rainfall characteristics over India using a high-resolution daily gridded (1 degrees latitude x 1 degrees longitude) dataset. Intensity, duration and frequency of excess rain over a high threshold in the summer monsoon season are modeled by non-stationary distributions whose parameters vary with physical covariates like the El-Nino Southern Oscillation index (ENSO-index) which is an indicator of large-scale natural variability, global average temperature which is an indicator of human-induced global warming and local mean temperatures which possibly indicate more localized changes. Each non-stationary model considers one physical covariate and the best chosen statistical model at each rainfall grid gives the most significant physical driver for each extreme rainfall characteristic at that grid. Intensity, duration and frequency of extreme rainfall exhibit non-stationarity due to different drivers and no spatially uniform pattern is observed in the changes in them across the country. At most of the locations, duration of extreme rainfall spells is found to be stationary, while non-stationary associations between intensity and frequency and local changes in temperature are detected at a large number of locations. This study presents the first application of nonstationary statistical modeling of intensity, duration and frequency of extreme rainfall over India. The developed models are further used for rainfall frequency analysis to show changes in the 100-year extreme rainfall event. Our findings indicate the varying nature of each extreme rainfall characteristic and their drivers and emphasize the necessity of a comprehensive framework to assess resulting risks of precipitation induced flooding. (C) 2014 Elsevier B.V. All rights reserved.

LANDSCAPE DYNAMICS MODELING THROUGH INTEGRATED MARKOV, FUZZY-AHP AND CELLULAR AUTOMATA

Multi temporal land use information were derived using two decades remote sensing data and simulated for 2012 and 2020 with Cellular Automata (CA) considering scenarios, change probabilities (through Markov chain) and Multi Criteria Evaluation (MCE). Agents and constraints were considered for modeling the urbanization process. Agents were nornmlized through fiizzyfication and priority weights were assigned through Analytical Hierarchical Process (AHP) pairwise comparison for each factor (in MCE) to derive behavior-oriented rules of transition for each land use class. Simulation shows a good agreement with the classified data. Fuzzy and AHP helped in analyzing the effects of agents of growth clearly and CA-Markov proved as a powerful tool in modelling and helped in capturing and visualizing the spatiotemporal patterns of urbanization. This provided rapid land evaluation framework with the essential insights of the urban trajectory for effective sustainable city planning.

Modeling of solar radiation management: a comparison of simulations using reduced solar constant and stratospheric sulphate aerosols

The climatic effects of Solar Radiation Management (SRM) geoengineering have been often modeled by simply reducing the solar constant. This is most likely valid only for space sunshades and not for atmosphere and surface based SRM methods. In this study, a global climate model is used to evaluate the differences in the climate response to SRM by uniform solar constant reduction and stratospheric aerosols. Our analysis shows that when global mean warming from a doubling of CO2 is nearly cancelled by both these methods, they are similar when important surface and tropospheric climate variables are considered. However, a difference of 1 K in the global mean stratospheric (61-9.8 hPa) temperature is simulated between the two SRM methods. Further, while the global mean surface diffuse radiation increases by similar to 23 % and direct radiation decreases by about 9 % in the case of sulphate aerosol SRM method, both direct and diffuse radiation decrease by similar fractional amounts (similar to 1.0 %) when solar constant is reduced. When CO2 fertilization effects from elevated CO2 concentration levels are removed, the contribution from shaded leaves to gross primary productivity (GPP) increases by 1.8 % in aerosol SRM because of increased diffuse light. However, this increase is almost offset by a 15.2 % decline in sunlit contribution due to reduced direct light. Overall both the SRM simulations show similar decrease in GPP (similar to 8 %) and net primary productivity (similar to 3 %). Based on our results we conclude that the climate states produced by a reduction in solar constant and addition of aerosols into the stratosphere can be considered almost similar except for two important aspects: stratospheric temperature change and the consequent implications for the dynamics and the chemistry of the stratosphere and the partitioning of direct versus diffuse radiation reaching the surface. Further, the likely dependence of global hydrological cycle response on aerosol particle size and the latitudinal and height distribution of aerosols is discussed.

EXPERIENCE OF OPERATING OPEN TOP BIOMASS GASIFIER USING A LOW DENSITY FUEL-COCONUT FRONDS

Use of fuel other than woody generally has been limited to rice husk and other residues are rarely tried as a fuel in a gasification system. With the availability of woody biomass in most countries like India, alternates fuels are being explored for sustainable supply of fuel. Use of agro residues has been explored after briquetting. There are few feedstock's like coconut fronts, maize cobs, etc, that might require lesser preprocessing steps compared to briquetting. The paper presents a detailed investigation into using coconut fronds as a fuel in an open top down draft gasification system. The fuel has ash content of 7% and was dried to moisture levels of 12 %. The average bulk density was found to be 230 kg/m3 with a fuel size particle of an average size 40 mm as compared to 350 kg/m3 for a standard wood pieces. A typical dry coconut fronds weighs about 2.5kgs and on an average 6 m long and 90 % of the frond is the petiole which is generally used as a fuel. The focus was also to compare the overall process with respect to operating with a typical woody biomass like subabul whose ash content is 1 %. The open top gasification system consists of a reactor, cooling and cleaning system along with water treatment. The performance parameters studied were the gas composition, tar and particulates in the clean gas, water quality and reactor pressure drop apart from other standard data collection of fuel flow rate, etc. The average gas composition was found to be CO 15 1.0 % H-2 16 +/- 1% CH4 0.5 +/- 0.1 % CO2 12.0 +/- 1.0 % and rest N2 compared to CO 19 +/- 1.0 % H-2 17 +/- 1.0 %, CH4 1 +/- 0.2 %, CO2 12 +/- 1.0 % and rest N2. The tar and particulate content in the clean gas has been found to be about 10 and 12 mg/m3 in both cases. The presence of high ash content material increased the pressure drop with coconut frond compared to woody biomass.

COMPUTATIONAL MODELING OF A MULTI-LAYERED PIEZO-COMPOSITE BEAM MADE UP OF MFC

The Variational Asymptotic Method (VAM) is used for modeling a coupled non-linear electromechanical problem finding applications in aircrafts and Micro Aerial Vehicle (MAV) development. VAM coupled with geometrically exact kinematics forms a powerful tool for analyzing a complex nonlinear phenomena as shown previously by many in the literature 3 - 7] for various challenging problems like modeling of an initially twisted helicopter rotor blades, matrix crack propagation in a composite, modeling of hyper elastic plates and various multi-physics problems. The problem consists of design and analysis of a piezocomposite laminate applied with electrical voltage(s) which can induce direct and planar distributed shear stresses and strains in the structure. The deformations are large and conventional beam theories are inappropriate for the analysis. The behavior of an elastic body is completely understood by its energy. This energy must be integrated over the cross-sectional area to obtain the 1-D behavior as is typical in a beam analysis. VAM can be used efficiently to approximate 3-D strain energy as closely as possible. To perform this simplification, VAM makes use of thickness to width, width to length, width multiplied by initial twist and strain as small parameters embedded in the problem definition and provides a way to approach the exact solution asymptotically. In this work, above mentioned electromechanical problem is modeled using VAM which breaks down the 3-D elasticity problem into two parts, namely a 2-D non-linear cross-sectional analysis and a 1-D non-linear analysis, along the reference curve. The recovery relations obtained as a by-product in the cross-sectional analysis earlier are used to obtain 3-D stresses, displacements and velocity contours. The piezo-composite laminate which is chosen for an initial phase of computational modeling is made up of commercially available Macro Fiber Composites (MFCs) stacked together in an arbitrary lay-up and applied with electrical voltages for actuation. The expressions of sectional forces and moments as obtained from cross-sectional analysis in closed-form show the electro-mechanical coupling and relative contribution of electric field in individual layers of the piezo-composite laminate. The spatial and temporal constitutive law as obtained from the cross-sectional analysis are substituted into 1-D fully intrinsic, geometrically exact equilibrium equations of motion and 1-D intrinsic kinematical equations to solve for all 1-D generalized variables as function of time and an along the reference curve co-ordinate, x(1).

Girsanov Transformation-Based Reliability Modeling and Testing of Actively Controlled Structures

The problem of estimation of the time-variant reliability of actively controlled structural dynamical systems under stochastic excitations is considered. Monte Carlo simulations, reinforced with Girsanov transformation-based sampling variance reduction, are used to tackle the problem. In this approach, the external excitations are biased by an additional artificial control force. The conflicting objectives of the two control forces-one designed to reduce structural responses and the other to promote limit-state violations (but to reduce sampling variance)-are noted. The control for variance reduction is fashioned after design-point oscillations based on a first-order reliability method. It is shown that for structures that are amenable to laboratory testing, the reliability can be estimated experimentally with reduced testing times by devising a procedure based on the ideas of the Girsanov transformation. Illustrative examples include studies on a building frame with a magnetorheologic damper-based isolation system subject to nonstationary random earthquake excitations. (C) 2014 American Society of Civil Engineers.

System reliability of randomly vibrating structures: Computational modeling and laboratory testing

The problem of determination of system reliability of randomly vibrating structures arises in many application areas of engineering. We discuss in this paper approaches based on Monte Carlo simulations and laboratory testing to tackle problems of time variant system reliability estimation. The strategy we adopt is based on the application of Girsanov's transformation to the governing stochastic differential equations which enables estimation of probability of failure with significantly reduced number of samples than what is needed in a direct simulation study. Notably, we show that the ideas from Girsanov's transformation based Monte Carlo simulations can be extended to conduct laboratory testing to assess system reliability of engineering structures with reduced number of samples and hence with reduced testing times. Illustrative examples include computational studies on a 10 degree of freedom nonlinear system model and laboratory/computational investigations on road load response of an automotive system tested on a four post Lest rig. (C) 2015 Elsevier Ltd. All rights reserved.

Modeling of Piezocomposites using Variational Asymptotic Method

This work presents the development of piezocomposites made up of Macro Fiber Composites (MFCs) for aerospace applications and specifically involves, their computational analysis, material characterization and certain parametric studies. MFC was developed by NASA Langley Research Center in 1996 and currently is being distributed by Smart Material Co. 1] worldwide and finds applications both as an actuator as well as for sensor in various engineering applications. In this work, MFC is being modeled as an actuator and a theoretical formulation based on Variational Asymptotic Method (VAM) 2] is presented to analyse the laminates made up of MFCs. VAM minimizes the total electro-mechanical energy for the MFC laminate and approaches the exact solution asymptotically by making use of certain small parameters inherent to the problem through dimensional reduction. VAM provides closed form solutions for 1D constitutive law, recovery relations of warpings, 3D stress/strain fields and displacements and hence an ideal tool for carrying out parametric and design studies in such applications. VAM is geometrically exact and offers rigorous material characterization through cross-sectional analysis and dimensional reduction.

Modeling Ultrasonic NDE and Guided Wave based Structural Health Monitoring

Structural Health Monitoring (SHM) systems require integration of non-destructive technologies into structural design and operational processes. Modeling and simulation of complex NDE inspection processes are important aspects in the development and deployment of SHM technologies. Ray tracing techniques are vital simulation tools to visualize the wave path inside a material. These techniques also help in optimizing the location of transducers and their orientation with respect to the zone of interrogation. It helps in increasing the chances of detection and identification of a flaw in that zone. While current state-of-the-art techniques such as ray tracing based on geometric principle help in such visualization, other information such as signal losses due to spherical or cylindrical shape of wave front are rarely taken into consideration. The problem becomes a little more complicated in the case of dispersive guided wave propagation and near-field defect scattering. We review the existing models and tools to perform ultrasonic NDE simulation in structural components. As an initial step, we develop a ray-tracing approach, where phase and spectral information are preserved. This enables one to study wave scattering beyond simple time of flight calculation of rays. Challenges in terms of theory and modelling of defects of various kinds are discussed. Various additional considerations such as signal decay and physics of scattering are reviewed and challenges involved in realistic computational implementation are discussed. Potential application of this approach to SHM system design is highlighted and by applying this to complex structural components such as airframe structures, SHM is demonstrated to provide additional value in terms of lighter weight and/or longevity enhancement resulting from an extension of the damage tolerance design principle not compromising safety and reliability.

MODELING AND SIMULATION OF A THREE-WHEELED MOBILE ROBOT ON UNEVEN TERRAINS WITH TWO-DEGREE-OF-FREEDOM SUSPENSION MECHANISMS

A wheeled mobile robot (WMR) will move on an uneven terrain without slip if its torus-shaped wheels tilt in a lateral direction. An independent two degree-of-freedom (DOF) suspension is required to maintain contact with uneven terrain and for lateral tilting. This article deals with the modeling and simulation of a three-wheeled mobile robot with torus-shaped wheels and four novel two-DOF suspension mechanism concepts. Simulations are performed on an uneven terrain for three representative pathsa straight line, a circular, and an S'-shaped path. Simulations show that a novel concept using double four-bar mechanism performs better than the other three concepts.

Current trends in modeling hostpathogen interactions

The rapid emergence of infectious diseases calls for immediate attention to determine practical solutions for intervention strategies. To this end, it becomes necessary to obtain a holistic view of the complex hostpathogen interactome. Advances in omics and related technology have resulted in massive generation of data for the interacting systems at unprecedented levels of detail. Systems-level studies with the aid of mathematical tools contribute to a deeper understanding of biological systems, where intuitive reasoning alone does not suffice. In this review, we discuss different aspects of hostpathogen interactions (HPIs) and the available data resources and tools used to study them. We discuss in detail models of HPIs at various levels of abstraction, along with their applications and limitations. We also enlist a few case studies, which incorporate different modeling approaches, providing significant insights into disease. (c) 2013 Wiley Periodicals, Inc.

Computational modeling of reactive hot pressing of zirconium carbide

A model of reactive hot pressing of zirconium carbide (ZrCx, 0.5 < x < 1) has been constructed that incorporates four processes that occur in parallel: creep of zirconium (Zr), reaction of Zr and carbon (C), increase in volume fraction of hard phase with progressive reaction that reduces the creep of Zr and, finally, de-densification associated with volume reduction during reaction. The reasonable agreement of the model with experimental results verifies that plastic deformation of Zr is the main factor that is responsible for the low-temperature reactive densification of ZrC and that ZrC may be treated as a rigid inclusion that contributes little to densification. It predicts that densification is impaired by increasing carbon stoichiometry due to the increasing amount of starting hard phase and the greater contraction upon reaction. Additionally, the model predicts that mixtures of Zr and ZrC should show equal or better densification than Zr and C mixtures.

Modeling harvest rates and numbers from age and sex ratios: A demonstration for elephant populations

Illegal harvest rates of wildlife populations are often unknown or difficult to estimate from field data due to under-reporting or incomplete detection of carcasses. This is especially true for elephants that are killed for ivory or in conflicts with people. We describe a method to infer harvest rates from coarse field data of three population parameters, namely, adult female to male ratio, male old-adult to young-adult ratio, and proportion of adult males in the population using Jensen's (2000) 2-sex, density-dependent Leslie matrix model. The specific combination of male and female harvest rates and numbers can be determined from the history of harvest and estimate of population size. We applied this technique to two populations of elephants for which data on age structure and records of mortality were available-a forest-dwelling population of the Asian elephant (at Nagarahole, India) and an African savannah elephant population (at Samburu, Kenya) that had experienced male-biased harvest regimes over 2-3 decades. For the Nagarahole population, the recorded numbers of male and female elephants killed illegally during 1981-2000 were 64% and 88% of the values predicted by the model, respectively, implying some non-detection or incomplete reporting while for the Samburu population the recorded and modeled numbers of harvest during 1990-1999 closely matched. This technique, applicable to any animal population following logistic growth model, can be especially useful for inferring illegal harvest numbers of forest elephants in Africa and Asia. (C) 2013 Elsevier Ltd. All rights reserved.

ANRC Hybrid Test Bed Implementation and an End-to-End Performance Characterization of Dynamic Spectrum Access

An abundance of spectrum access and sensing algorithms are available in the dynamic spectrum access (DSA) and cognitive radio (CR) literature. Often, however, the functionality and performance of such algorithms are validated against theoretical calculations using only simulations. Both the theoretical calculations and simulations come with their attendant sets of assumptions. For instance, designers of dynamic spectrum access algorithms often take spectrum sensing and rendezvous mechanisms between transmitter-receiver pairs for granted. Test bed designers, on the other hand, either customize so much of their design that it becomes difficult to replicate using commercial off the shelf (COTS) components or restrict themselves to simulation, emulation /hardware-in-Ioop (HIL), or pure hardware but not all three. Implementation studies on test beds sophisticated enough to combine the three aforementioned aspects, but at the same time can also be put together using COTS hardware and software packages are rare. In this paper we describe i) the implementation of a hybrid test bed using a previously proposed hardware agnostic system architecture ii) the implementation of DSA on this test bed, and iii) the realistic hardware and software-constrained performance of DSA. Snapshot energy detector (ED) and Cumulative Summation (CUSUM), a sequential change detection algorithm, are available for spectrum sensing and a two-way handshake mechanism in a dedicated control channel facilitates transmitter-receiver rendezvous.

A mobile robot with a two-degree-of-freedom suspension for traversing uneven terrain with minimal slip: Modeling, simulation and experiments

It is known in literature that a wheeled mobile robot (WMR) with fixed length axle will slip on an uneven terrain. One way to avoid wheel slip is to use a torus-shaped wheel with lateral tilt capability which allows the distance between the wheel-ground contact points to change even with a fixed length axle. Such an arrangement needs a two degree-of-freedom (DOF) suspension for the vertical and lateral tilting motion of the wheel. In this paper modeling, simulation, design and experimentation with a three-wheeled mobile robot, with torus-shaped wheels and a novel two DOF suspension allowing independent lateral tilt and vertical motion, is presented. The suspension is based on a four-bar mechanism and is called the double four-bar (D4Bar) suspension. Numerical simulations show that the three-wheeled mobile robot can traverse uneven terrain with low wheel slip. Experiments with a prototype three-wheeled mobile robot moving on a constructed uneven terrain along a straight line, a circular arc and a path representing a lane change, also illustrate the low slip capability of the three-wheeled mobile robot with the D4Bar suspension. (C) 2015 Elsevier Ltd. All rights reserved.