Updating and verification for multi-scale finite element model of structure behavior

The method on concurrent multi-scale model of structural behavior (CMSM-of-SB) for the purpose of structural health monitoring including model updating and validating has been studied. The detailed process of model updating and validating is discussed in terms of reduced scale specimen of the steel box girder in longitudinal stiffening truss of a long span bridge. Firstly, some influence factors affecting the accuracy of the CMSM-of-SB including the boundary restraint regidity, the geometry and material parameters on the toe of the weld and its neighbor are analyzed using sensitivity method. Then, sensitivity-based model updating technology is adopted to update the developed CMSM-of-SB and model verification is carried out through calculating and comparing stresses on different locations under various loading from dynamic characteristic and static response. It can be concluded that the CMSM-of-SB based on the substructure method is valid.

A model of coupled thermal, mechanical, and electrostatic field effects in III-N thin film heterostructures

A one-dimensional coupled multi-physics based model has been developed to accurately compute the effects of electrostatic, mechanical, and thermal field interactions on the electronic energy band structure in group III-nitrides thin film heterostructures. Earlier models reported in published literature assumes electro-mechanical field with uniform temperature thus neglecting self-heating. Also, the effects of diffused interface on the energy band structure were not studied. We include these effects in a self-consistent manner wherein the transport equation is introduced along with the electro-mechanical models, and the lattice structural variation as observed in experiments are introduced at the interface. Due to these effects, the electrostatic potential distribution in the heterostructure is altered. The electron and hole ground state energies decrease by 5% and 9%, respectively, at a relative temperature of 700 K, when compared with the results obtained from the previously reported electro-mechanical model assuming constant and uniform temperature distribution. A diffused interface decreases the ground state energy of electrons and holes by about 11% and 9%, respectively, at a relative temperature of 700 K when compared with the predictions based on uniform temperature based electro-mechanical model. (C) 2013 AIP Publishing LLC.

ASYMPTOTIC PRESERVING SCHEME FOR A KINETIC MODEL DESCRIBING IN COMPRESSIBLE FLUIDS

The kinetic theory of fluid turbulence modeling developed by Degond and Lemou in 7] is considered for further study, analysis and simulation. Starting with the Boltzmann like equation representation for turbulence modeling, a relaxation type collision term is introduced for isotropic turbulence. In order to describe some important turbulence phenomenology, the relaxation time incorporates a dependency on the turbulent microscopic energy and this makes difficult the construction of efficient numerical methods. To investigate this problem, we focus here on a multi-dimensional prototype model and first propose an appropriate change of frame that makes the numerical study simpler. Then, a numerical strategy to tackle the stiff relaxation source term is introduced in the spirit of Asymptotic Preserving Schemes. Numerical tests are performed in a one-dimensional framework on the basis of the developed strategy to confirm its efficiency.

Modified Simplified Rate Equation Model of Flowing Chemical Oxygen-Iodine Laser and its Application

A modified simplified rate equation (RE) model of flowing chemical oxygen-iodine laser (COIL), which is adapted to both the condition of homogeneous broadening and inhomogeneous broadening being of importance and the condition of inhomogeneous broadening being predominant, is presented for performance analyses of a COIL. By using the Voigt profile function and the gain-equal-loss approximation, a gain expression has been deduced from the rate equations of upper and lower level laser species. This gain expression is adapted to the conditions of very low gas pressure up to quite high pressure and can deal with the condition of lasing frequency being not equal to the central one of spectral profile. The expressions of output power and extraction efficiency in a flowing COIL can be obtained by solving the coupling equations of the deduced gain expression and the energy equation which expresses the complete transformation of the energy stored in singlet delta state oxygen into laser energy. By using these expressions, the RotoCOIL experiment is simulated, and obtained results agree well with experiment data. Effects of various adjustable parameters on the performances of COIL are also presented.

Modified Simplified Rate Equation Model of Flowing Chemical Oxygen-Iodine Laser and its Application

A modified simplified rate equation (RE) model of flowing chemical oxygen-iodine laser (COIL), which is adapted to both the condition of homogeneous broadening and inhomogeneous broadening being of importance and the condition of inhomogeneous broadening being predominant, is presented for performance analyses of a COIL. By using the Voigt profile function and the gain-equal-loss approximation, a gain expression has been deduced from the rate equations of upper and lower level laser species. This gain expression is adapted to the conditions of very low gas pressure up to quite high pressure and can deal with the condition of lasing frequency being not equal to the central one of spectral profile. The expressions of output power and extraction efficiency in a flowing COIL can be obtained by solving the coupling equations of the deduced gain expression and the energy equation which expresses the complete transformation of the energy stored in singlet delta state oxygen into laser energy. By using these expressions, the RotoCOIL experiment is simulated, and obtained results agree well with experiment data. Effects of various adjustable parameters on the performances of COIL are also presented.

A multi-output two-stage locally regularized model construction method using the extreme learning machine

This paper investigates the construction of linear-in-the-parameters (LITP) models for multi-output regression problems. Most existing stepwise forward algorithms choose the regressor terms one by one, each time maximizing the model error reduction ratio. The drawback is that such procedures cannot guarantee a sparse model, especially under highly noisy learning conditions. The main objective of this paper is to improve the sparsity and generalization capability of a model for multi-output regression problems, while reducing the computational complexity. This is achieved by proposing a novel multi-output two-stage locally regularized model construction (MTLRMC) method using the extreme learning machine (ELM). In this new algorithm, the nonlinear parameters in each term, such as the width of the Gaussian function and the power of a polynomial term, are firstly determined by the ELM. An initial multi-output LITP model is then generated according to the termination criteria in the first stage. The significance of each selected regressor is checked and the insignificant ones are replaced at the second stage. The proposed method can produce an optimized compact model by using the regularized parameters. Further, to reduce the computational complexity, a proper regression context is used to allow fast implementation of the proposed method. Simulation results confirm the effectiveness of the proposed technique. © 2013 Elsevier B.V.

Multi-agent model for robotic assembly system

In this paper, a multi-agent based model for a robotic assembly system is presented. Firstly, an organization model is used to construct the multi-agent model. Secondly, a dynamic self-organizing method is then put forward for the multi-agent robotic system to bid and contract the operations. Thirdly, a real multi-agent robotic system is built and assembly experiments are carried out. Finally, the experimental results confirm that the present multi-agent robotic system has flexibility, adaptation and stability.

A new transfer learning framework with application to model-agnostic multi-task learning

Learning from small number of examples is a challenging problem in machine learning. An effective way to improve the performance is through exploiting knowledge from other related tasks. Multi-task learning (MTL) is one such useful paradigm that aims to improve the performance through jointly modeling multiple related tasks. Although there exist numerous classification or regression models in machine learning literature, most of the MTL models are built around ridge or logistic regression. There exist some limited works, which propose multi-task extension of techniques such as support vector machine, Gaussian processes. However, all these MTL models are tied to specific classification or regression algorithms and there is no single MTL algorithm that can be used at a meta level for any given learning algorithm. Addressing this problem, we propose a generic, model-agnostic joint modeling framework that can take any classification or regression algorithm of a practitioner’s choice (standard or custom-built) and build its MTL variant. The key observation that drives our framework is that due to small number of examples, the estimates of task parameters are usually poor, and we show that this leads to an under-estimation of task relatedness between any two tasks with high probability. We derive an algorithm that brings the tasks closer to their true relatedness by improving the estimates of task parameters. This is achieved by appropriate sharing of data across tasks. We provide the detail theoretical underpinning of the algorithm. Through our experiments with both synthetic and real datasets, we demonstrate that the multi-task variants of several classifiers/regressors (logistic regression, support vector machine, K-nearest neighbor, Random Forest, ridge regression, support vector regression) convincingly outperform their single-task counterparts. We also show that the proposed model performs comparable or better than many state-of-the-art MTL and transfer learning baselines.

A Multi-Stage Stochastic Non-Linear Model for Reactive Power Planning Under Contingencies

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Multi-scale simulation using a hybrid mass-spring system and finite element model

Ply-scale finite element (FE) models are widely used to predict the performance of a composite structure based on material properties of individual plies. When simulating damage, these models neglect microscopic fracture processes which may have a significant effect on how a crack progresses within and between plies of a multidirectional laminate. To overcome this resolution limitation a multi-scale modelling technique is employed to simulate the effect micro-scale damage events have on the macro-scale response of a structure. The current paper discusses the development and validation of a hybrid mass-spring system and finite element modelling technique for multi-scale analysis. The model developed here is limited to elastic deformations; however, it is the first key step towards an efficient multi-scale damage model well suited to simulation of fracture in fibre reinforced composite materials. Various load cases have been simulated using the model developed here which show excellent accuracy compared to analytical and FE results. Future work is discussed, including extension of the model to incorporate damage modelling.

A mathematical model of chlamydial infection incorporating movement of chlamydial particles

We present a spatiotemporal mathematical model of chlamydial infection, host immune response and spatial movement of infectious particles. The re- sulting partial differential equations model both the dynamics of the infection and changes in infection profile observed spatially along the length of the host genital tract. This model advances previous chlamydia modelling by incorporating spatial change, which we also demonstrate to be essential when the timescale for movement of infectious particles is equal to, or shorter than, the developmental cycle timescale. Numerical solutions and model analysis are carried out, and we present a hypothesis regarding the potential for treatment and prevention of infection by increasing chlamydial particle motility.

Multi-scale numerical simulations of thermal expansion properties of CNT-reinforced nanocomposites

In this work, the thermal expansion properties of carbon nanotube (CNT)-reinforced nanocomposites with CNT content ranging from 1 to 15 wt% were evaluated using a multi-scale numerical approach, in which the effects of two parameters, i.e., temperature and CNT content, were investigated extensively. For all CNT contents, the obtained results clearly revealed that within a wide low-temperature range (30°C ~ 62°C), thermal contraction is observed, while thermal expansion occurs in a high-temperature range (62°C ~ 120°C). It was found that at any specified CNT content, the thermal expansion properties vary with temperature - as temperature increases, the thermal expansion rate increases linearly. However, at a specified temperature, the absolute value of the thermal expansion rate decreases nonlinearly as the CNT content increases. Moreover, the results provided by the present multi-scale numerical model were in good agreement with those obtained from the corresponding theoretical analyses and experimental measurements in this work, which indicates that this multi-scale numerical approach provides a powerful tool to evaluate the thermal expansion properties of any type of CNT/polymer nanocomposites and therefore promotes the understanding on the thermal behaviors of CNT/polymer nanocomposites for their applications in temperature sensors, nanoelectronics devices, etc.

Australia's disabling income support system : tracing the history of the Australian disability income support system 1908 to 2007 : disablism, citizenship and the basic income proposal

The present study examined the historical basis of the Australian disability income support system from 1908 to 2007. Although designed as a safety net for people with a disability, the disability income support system within Australia has been highly targeted. The original eligibility criteria of "permanently incapacitated for work", medical criteria and later "partially capacitated for work" potentially contained ideological inferences that permeated across the time period. This represents an important area for study given the potential consequence for disability income support to marginalise people with a disability. Social policy and disability policy theorists, including Saunders (2007, Social Policy Research Centre [SPRC]) and Gibilisco (2003) have provided valuable insight into some of the effects of disability policy and poverty. Yet while these theorists argued for some form of income support they did not propose a specific form of income security for further exploration. Few studies have undertaken a comprehensive review of the history of disability income support within the Australian context. This thesis sought to redress these gaps by examining disability income support policy within Australia. The research design consisted of an in-depth critical historical-comparative policy analysis methodology. The use of critical historical-comparative policy analysis allowed the researcher to trace the construction of disability within the Australian disability income support policy across four major historical epochs. A framework was developed specifically to guide analysis of the data. The critical discourse analysis method helped to understand the underlying ideological dimensions that led to the predominance of one particular approach over another. Given this, the research purpose of the study centred on: i. Tracing the history of the Australian disability income support system. ii. Examining the historical patterns and ideological assumptions over time. iii. Exploring the historical patterns and ideological assumptions underpinning an alternative model (Basic Income) and the extent to which each model promotes the social citizenship of people with a disability. The research commitment to a social-relational ontology and the quest for social change centred on the idea that "there has to be a better way" in the provision of disability income support. This theme of searching for an alternative reality in disability income support policy resonated throughout the thesis. This thesis found that the Australian disability income support system is disabling in nature and generates categories of disability on the basis of ableness. From the study, ableness became a condition for citizenship. This study acknowledged that, in reality, income support provision reflects only one aspect of the disabling nature of society which requires redressing. Although there are inherent tensions in any redistributive strategy, the Basic Income model potentially provides an alternative to the Australian disability income support system, given its grounding in social citizenship. The thesis findings have implications for academics, policy-makers and practitioners in terms of developing better ways to understand disability constructs in disability income support policy. The thesis also makes a contribution in terms of promoting income support policies based on the rights of all people, not just a few.

A multi-objective optimization approach for coordinating available transfer capability with risk control

In the electricity market environment, coordination of system reliability and economics of a power system is of great significance in determining the available transfer capability (ATC). In addition, the risks associated with uncertainties should be properly addressed in the ATC determination process for risk-benefit maximization. Against this background, it is necessary that the ATC be optimally allocated and utilized within relative security constraints. First of all, the non-sequential Monte Carlo stimulation is employed to derive the probability density distribution of ATC of designated areas incorporating uncertainty factors. Second, on the basis of that, a multi-objective optimization model is formulated to determine the multi-area ATC so as to maximize the risk-benefits. Then, the solution to the developed model is achieved by the fast non-dominated sorting (NSGA-II) algorithm, which could decrease the risk caused by uncertainties while coordinating the ATCs of different areas. Finally, the IEEE 118-bus test system is served for demonstrating the essential features of the developed model and employed algorithm.