Computer model for vedavati ground water basin. Part 1. Well field model

It is shown that a leaky aquifer model can be used for well field analysis in hard rock areas, treating the upper weathered and clayey layers as a composite unconfined aquitard overlying a deeper fractured aquifer. Two long-duration pump test studies are reported in granitic and schist regions in the Vedavati river basin. The validity of simplifications in the analytical solution is verified by finite difference computations.

Bayesian model comparison in cosmology with Population Monte Carlo

We use Bayesian model selection techniques to test extensions of the standard flat LambdaCDM paradigm. Dark-energy and curvature scenarios, and primordial perturbation models are considered. To that end, we calculate the Bayesian evidence in favour of each model using Population Monte Carlo (PMC), a new adaptive sampling technique which was recently applied in a cosmological context. The Bayesian evidence is immediately available from the PMC sample used for parameter estimation without further computational effort, and it comes with an associated error evaluation. Besides, it provides an unbiased estimator of the evidence after any fixed number of iterations and it is naturally parallelizable, in contrast with MCMC and nested sampling methods. By comparison with analytical predictions for simulated data, we show that our results obtained with PMC are reliable and robust. The variability in the evidence evaluation and the stability for various cases are estimated both from simulations and from data. For the cases we consider, the log-evidence is calculated with a precision of better than 0.08. Using a combined set of recent CMB, SNIa and BAO data, we find inconclusive evidence between flat LambdaCDM and simple dark-energy models. A curved Universe is moderately to strongly disfavoured with respect to a flat cosmology. Using physically well-motivated priors within the slow-roll approximation of inflation, we find a weak preference for a running spectral index. A Harrison-Zel'dovich spectrum is weakly disfavoured. With the current data, tensor modes are not detected; the large prior volume on the tensor-to-scalar ratio r results in moderate evidence in favour of r=0.

High-throughput prediction of eucalypt lignin syringyl/guaiacyl content using multivariate analysis: a comparison between mid-infrared, near-infrared, and Raman spectroscopies for model development

BACKGROUND: In order to rapidly and efficiently screen potential biofuel feedstock candidates for quintessential traits, robust high-throughput analytical techniques must be developed and honed. The traditional methods of measuring lignin syringyl/guaiacyl (S/G) ratio can be laborious, involve hazardous reagents, and/or be destructive. Vibrational spectroscopy can furnish high-throughput instrumentation without the limitations of the traditional techniques. Spectral data from mid-infrared, near-infrared, and Raman spectroscopies was combined with S/G ratios, obtained using pyrolysis molecular beam mass spectrometry, from 245 different eucalypt and Acacia trees across 17 species. Iterations of spectral processing allowed the assembly of robust predictive models using partial least squares (PLS). RESULTS: The PLS models were rigorously evaluated using three different randomly generated calibration and validation sets for each spectral processing approach. Root mean standard errors of prediction for validation sets were lowest for models comprised of Raman (0.13 to 0.16) and mid-infrared (0.13 to 0.15) spectral data, while near-infrared spectroscopy led to more erroneous predictions (0.18 to 0.21). Correlation coefficients (r) for the validation sets followed a similar pattern: Raman (0.89 to 0.91), mid-infrared (0.87 to 0.91), and near-infrared (0.79 to 0.82). These statistics signify that Raman and mid-infrared spectroscopy led to the most accurate predictions of S/G ratio in a diverse consortium of feedstocks. CONCLUSION: Eucalypts present an attractive option for biofuel and biochemical production. Given the assortment of over 900 different species of Eucalyptus and Corymbia, in addition to various species of Acacia, it is necessary to isolate those possessing ideal biofuel traits. This research has demonstrated the validity of vibrational spectroscopy to efficiently partition different potential biofuel feedstocks according to lignin S/G ratio, significantly reducing experiment and analysis time and expense while providing non-destructive, accurate, global, predictive models encompassing a diverse array of feedstocks.

Digital elevation model error in terrain analysis

Digital elevation models (DEMs) have been an important topic in geography and surveying sciences for decades due to their geomorphological importance as the reference surface for gravita-tion-driven material flow, as well as the wide range of uses and applications. When DEM is used in terrain analysis, for example in automatic drainage basin delineation, errors of the model collect in the analysis results. Investigation of this phenomenon is known as error propagation analysis, which has a direct influence on the decision-making process based on interpretations and applications of terrain analysis. Additionally, it may have an indirect influence on data acquisition and the DEM generation. The focus of the thesis was on the fine toposcale DEMs, which are typically represented in a 5-50m grid and used in the application scale 1:10 000-1:50 000. The thesis presents a three-step framework for investigating error propagation in DEM-based terrain analysis. The framework includes methods for visualising the morphological gross errors of DEMs, exploring the statistical and spatial characteristics of the DEM error, making analytical and simulation-based error propagation analysis and interpreting the error propagation analysis results. The DEM error model was built using geostatistical methods. The results show that appropriate and exhaustive reporting of various aspects of fine toposcale DEM error is a complex task. This is due to the high number of outliers in the error distribution and morphological gross errors, which are detectable with presented visualisation methods. In ad-dition, the use of global characterisation of DEM error is a gross generalisation of reality due to the small extent of the areas in which the decision of stationarity is not violated. This was shown using exhaustive high-quality reference DEM based on airborne laser scanning and local semivariogram analysis. The error propagation analysis revealed that, as expected, an increase in the DEM vertical error will increase the error in surface derivatives. However, contrary to expectations, the spatial au-tocorrelation of the model appears to have varying effects on the error propagation analysis depend-ing on the application. The use of a spatially uncorrelated DEM error model has been considered as a 'worst-case scenario', but this opinion is now challenged because none of the DEM derivatives investigated in the study had maximum variation with spatially uncorrelated random error. Sig-nificant performance improvement was achieved in simulation-based error propagation analysis by applying process convolution in generating realisations of the DEM error model. In addition, typology of uncertainty in drainage basin delineations is presented.

An analytical approach to the study of a class of bi-state social interaction processes

Sufficient conditions for obtaining an equivalent linear model to classes of non-linear, bi-state, social interaction processes are derived. These parametric constraints, when satisfied, permit analytical determination of the dynamics of the non-linear process of social interaction.

Multi-channel curve crossing problems: analytically solvable model

We have proposed a general method for finding the exact analytical solution for the multi-channel curve crossing problem in the presence of delta function couplings. We have analysed the case where aa potential energy curve couples to a continuum (in energy) of the potential energy curves.

A New Threshold Voltage Model for Omega Gate Cylindrical Nanowire Transistor

In this work, for the first time, we present a physically based analytical threshold voltage model for omega gate silicon nanowire transistor. This model is developed for long channel cylindrical body structure. The potential distribution at each and every point of the of the wire is derived with a closed form solution of two dimensional Poisson's equation, which is then used to model the threshold voltage. Proposed model can be treated as a generalized model, which is valid for both surround gate and semi-surround gate cylindrical transistors. The accuracy of proposed model is verified for different device geometry against the results obtained from three dimensional numerical device simulators and close agreement is observed.

The Cooperative Research Centre for Living with Autism (Autism CRC) conceptual model to promote mental health for adolescents with ASD

Despite an increased risk of mental health problems in adolescents with Autism Spectrum Disorder (ASD), there is limited research on effective prevention approaches for this population. Funded by the Cooperative Research Centre for Living with Autism, a theoretically and empirically supported school-based preventative model has been developed to alter the negative trajectory and promote wellbeing and positive mental health in adolescents with ASD. This conceptual paper provides the rationale, theoretical, empirical and methodological framework of a multilayered intervention targeting the school, parents, and adolescents on the spectrum. Two important interrelated protective factors have been identified in community adolescent samples, namely the sense of belonging (connectedness) to school, and the capacity for self and affect regulation in the face of stress (i.e., resilience). We describe how a confluence of theories from social psychology, developmental psychology and family systems theory, along with empirical evidence (including emerging neurobiological evidence) supports the interrelationships between these protective factors and many indices of wellbeing. However, the characteristics of ASD (including social and communication difficulties, and frequently difficulties with changes and transitions, and diminished optimism and self-esteem) impair access to these vital protective factors. The paper describes how evidenced-based interventions at the school level for promoting inclusive schools (using the Index for Inclusion), and interventions for adolescents and parents to promote resilience and belonging (using the Resourceful Adolescent Program (RAP)), are adapted and integrated for adolescents with ASD. This multisite proof of concept study will confirm whether this multilevel school-based intervention is promising, feasible and sustainable.

Optimal resource allocation in conflicts with the Lanchester linear law (2,1) model

This paper presents a detailed analysis of a model for military conflicts where the defending forces have to determine an optimal partitioning of available resources to counter attacks from an adversary in two different fronts in an area fire situation. Lanchester linear law attrition model is used to develop the dynamical equations governing the variation in force strength. Here we address a static resource allocation problem namely, Time-Zero-Allocation (TZA) where the resource allocation is done only at the initial time. Numerical examples are given to support the analytical results.

A semi-analytical solution for multilayer diffusion in a composite medium consisting of a large number of layers

Diffusion in a composite slab consisting of a large number of layers provides an ideal prototype problem for developing and analysing two-scale modelling approaches for heterogeneous media. Numerous analytical techniques have been proposed for solving the transient diffusion equation in a one-dimensional composite slab consisting of an arbitrary number of layers. Most of these approaches, however, require the solution of a complex transcendental equation arising from a matrix determinant for the eigenvalues that is difficult to solve numerically for a large number of layers. To overcome this issue, in this paper, we present a semi-analytical method based on the Laplace transform and an orthogonal eigenfunction expansion. The proposed approach uses eigenvalues local to each layer that can be obtained either explicitly, or by solving simple transcendental equations. The semi-analytical solution is applicable to both perfect and imperfect contact at the interfaces between adjacent layers and either Dirichlet, Neumann or Robin boundary conditions at the ends of the slab. The solution approach is verified for several test cases and is shown to work well for a large number of layers. The work is concluded with an application to macroscopic modelling where the solution of a fine-scale multilayered medium consisting of two hundred layers is compared against an “up-scaled” variant of the same problem involving only ten layers.

Site characterization model using least-square support vector machine and relevance vector machine based on corrected SPT data (N-c)

Statistical learning algorithms provide a viable framework for geotechnical engineering modeling. This paper describes two statistical learning algorithms applied for site characterization modeling based on standard penetration test (SPT) data. More than 2700 field SPT values (N) have been collected from 766 boreholes spread over an area of 220 sqkm area in Bangalore. To get N corrected value (N,), N values have been corrected (Ne) for different parameters such as overburden stress, size of borehole, type of sampler, length of connecting rod, etc. In three-dimensional site characterization model, the function N-c=N-c (X, Y, Z), where X, Y and Z are the coordinates of a point corresponding to N, value, is to be approximated in which N, value at any half-space point in Bangalore can be determined. The first algorithm uses least-square support vector machine (LSSVM), which is related to aridge regression type of support vector machine. The second algorithm uses relevance vector machine (RVM), which combines the strengths of kernel-based methods and Bayesian theory to establish the relationships between a set of input vectors and a desired output. The paper also presents the comparative study between the developed LSSVM and RVM model for site characterization. Copyright (C) 2009 John Wiley & Sons,Ltd.

Prediction of solid block masonry prism compressive strength using FE model

Masonry strength is dependent upon characteristics of the masonry unit,the mortar and the bond between them. Empirical formulae as well as analytical and finite element (FE) models have been developed to predict structural behaviour of masonry. This paper is focused on developing a three dimensional non-linear FE model based on micro-modelling approach to predict masonry prism compressive strength and crack pattern. The proposed FE model uses multi-linear stress-strain relationships to model the non-linear behaviour of solid masonry unit and the mortar. Willam-Warnke's five parameter failure theory developed for modelling the tri-axial behaviour of concrete has been adopted to model the failure of masonry materials. The post failure regime has been modelled by applying orthotropic constitutive equations based on the smeared crack approach. Compressive strength of the masonry prism predicted by the proposed FE model has been compared with experimental values as well as the values predicted by other failure theories and Eurocode formula. The crack pattern predicted by the FE model shows vertical splitting cracks in the prism. The FE model predicts the ultimate failure compressive stress close to 85 of the mean experimental compressive strength value.

Simplified theory of carrier back-scattering in semiconducting carbon nanotubes: A Kane's model approach

We present a simplified yet analytical formulation of the carrier backscattering coefficient for zig-zag semiconducting single walled carbon nanotubes under diffusive regime. The electron-phonon scattering rate for longitudinal acoustic, optical, and zone-boundary phonon emissions for both inter- and intrasubband transition rates have been derived using Kane's nonparabolic energy subband model.The expressions for the mean free path and diffusive resistance have been formulated incorporating the aforementioned phonon scattering. Appropriate overlap function in Fermi's golden rule has been incorporated for a more general approach. The effect of energy subbands on low and high bias zones for the onset of longitudinal acoustic, optical, and zone-boundary phonon emissions and absorption have been analytically addressed. 90% transmission of the carriers from the source to the drain at 400 K for a 5 mu m long nanotube at 105 V m(-1) has been exhibited. The analytical results are in good agreement with the available experimental data. (c) 2010 American Institute of Physics.

A Model for Creating Strategic Alliances. A Study of Inter-firm Cooperation in the North European ICT Sector

In this study, it is argued that the view on alliance creation presented in the current academic literature is limited, and that using a learning approach helps to explain the dynamic nature of alliance creation. The cases in this study suggest that a wealth of inefficiency elements can be found in alliance creation. These elements can further be divided into categories, which help explain the dynamics of alliance creation. The categories –combined with two models brought forward by the study– suggest that inefficiency can be avoided through learning during the creation process. Some elements are especially central to this argumentation. First, the elements related to the clarity and acceptance of the strategy of the company, the potential lack of an alliance strategy and the elements related to changes in the strategic context. Second, the elements related to the length of the alliance creation processes and the problems a long process entails. It is further suggested that the different inefficiency elements may create a situation, where the alliance creation process is –sequentially and successfully– followed to the end, but where the different inefficiencies create a situation where the results are not aligned with the strategic intent. The proposed solution is to monitor and assess the risk for inefficiency elements during the alliance creation process. The learning, which occurs during the alliance creation process as a result of the monitoring, can then lead to realignments in the process. This study proposes a model to mitigate the risk related to the inefficiencies. The model emphasizes creating an understanding of the other alliance partner’s business, creating a shared vision, using pilot cooperation and building trust within the process. An analytical approach to assessing the benefits of trust is also central in this view. The alliance creation approach suggested by this study, which emphasizes trust and pilot cooperation, is further critically reviewed against contracting as a way to create alliances.

A unified model for auxiliary switch commutated DC-DC converters

A novel ZVS auxiliary switch commutated variation for all DGDC converter topologies has been proposed in 2006. With proper designation of the circuit variables (throw current I and the pole voltage V), all these converters are seen to be governed by an identical set of equations. With idealized switches, the steady-state performance is obtainable in an analytical form. The conversion ratio of the converter topologies is obtained. A generalized equivalent circuit emerges for all these converters from the steady-state conversion ratio. It also provides a dynamic model as well. With these generalized steady-state equivalent circuits, small signal analysis of these converters may be carried out readily. It enables one to use the familiar state space averaged results of the standard PWM DGDC converters for the resonant counterparts. Th dc and ac models reveals that dc and low frequency behaviour of the proposed family of converters is similiar to that of its PWM parent