Strengthening of circular hollow steel tubular sections using high modulus CFRP sheets

This paper describes the behaviour of very high strength (VHS) circular steel tubes strengthened by carbon fibre reinforced polymer (CFRP) and subjected to axial tension. A series of tests were conducted with different bond lengths and number of layers. The distribution of strain through the thickness of CFRP layers and along CFRP bond length was studied. The strain was found to generally decrease along the CFRP bond length far from the joint. The strain through the thickness of the CFRP layers was also found to decrease from bottom to top layer. The effective bond length for high modulus CFRP was established. Finally empirical models were developed to estimate the maximum load for a given CFRP arrangement.

Damage localisation in beams and plates using vibration characteristics

Dynamic computer simulation techniques are used to develop and apply a multi-criteria procedure, incorporating changes in natural frequencies, modal flexibility and the modal strain energy, for damage localisation in beams and plates. Numerically simulated modal data obtained through finite element analyses are used to develop algorithms based on changes of modal flexibility and modal strain energy before and after damage and used as the indices for assessment of the state of structural health. The proposed procedure is illustrated through its application to flexural members under different damage scenarios and the results confirm its feasibility for damage assessment.

Large-scale fabrication of H2(H2O)Nb2O6 and Nb2O5 hollow microspheres

Hollow micro-sized H2(H2O)Nb2O6 spheres constructed by nanocrystallites have been successfully synthesized via a bubble-template assisted hydrothermal process. In the reaction process, H2O2 acts as a bubble generator and plays a key role in the formation of the hollow structure. An in situ bubble-template mechanism has been proposed for the possible formation of the hollow structure. The spherelike assemblies of these H2(H2O)Nb2O6 nanoparticles have been transformed into their corresponding pseudohexagonal phase Nb2O5 through a moderate annealing dehydration process without destroying the hierarchical structure. Optical properties of the as-prepared hollow spheres were investigated. It is exciting that the absorption edge of the hollow Nb2O5 microspheres shifts about 18 nm to the violet compared with bulk powders in the UV/vis spectra, indicating its superior optical properties.

Shear tests of Litesteel beams with web openings

This paper presents the details of experimental studies on the shear strength of a recently developed, cold-formed steel beam known as LiteSteel Beam (LSB) with web openings. The innovative LSB sections have the beneficial characteristics of torsionally rigid closed rectangular flanges combined with economical fabrication processes from a single strip of high strength steel. They combine the stability of hot-rolled steel sections with the high strength to weight ratio of conventional cold-formed steel sections. The LSB sections are commonly used as flexural members in the building industry. Current practice in flooring systems is to include openings in the web element of floor joists or bearers so that building services can be located within them. Shear behaviour of LSBs with web openings is more complicated while their shear strengths are considerably reduced by the presence of web openings. However, limited research has been undertaken on the shear behaviour and strength of LSBs with web openings. Therefore a detailed experimental study involving 26 shear tests was undertaken to investigate the shear behaviour and strength of different LSB sections. Simply supported test specimens of LSBs with an aspect ratio of 1.5 were loaded at midspan until failure. This paper presents the details of this experimental study and the results. Experimental results showed that the current design rules in cold-formed steel structures design codes (AS/NZS 4600) [1] are very conservative for the shear design of LSBs with web openings. Improved design equations have been proposed for the shear strength of LSBs with web openings based on experimental results from this study.

Shear strength of LiteSteel beams with web openings

This paper presents the details of numerical studies on the shear strength of a recently devel-oped, cold-formed steel channel beam known as LiteSteel Beam (LSB) with web openings. The LSB sections are commonly used as floor joists and bearers in residential, industrial and commercial buildings. In these ap-plications they often include web openings for the purpose of locating services. This has raised concerns over the shear capacity of LSB floor joists and bearers. Therefore experimental and numerical studies were under-taken to investigate the shear behavior and strength of LSBs with web openings. In this research, finite ele-ment models of LSBs with web openings in shear were developed to simulate the shear behavior of LSBs. It was found that currently available design equations are conservative or unconservative for the shear design of LSBs with web openings. Improved design equations have been proposed for the shear capacity of LSBs with web openings based on both experimental and numerical study results.

Shear strength and design of LiteSteel beams

This paper presents the details of a parametric study based on finite element analyses (FEA) and development of design rules for the shear strength of a recently developed, cold-formed steel channel beam known as LiteSteel Beam (LSB). The LSB sections are commonly used as flexural members in residential, in-dustrial and commercial buildings. In order to ensure safe and efficient designs of LSBs, many research stu-dies have been undertaken on the flexural behaviour of LSBs. However, no research has been undertaken on the shear behaviour of LSBs. Therefore a detailed investigation including both numerical and experimental studies was undertaken to investigate the shear behaviour of LSBs. Both the experimental and FEA parametric study results showed that the current design rules in cold-formed steel design codes are very conservative for the shear design of LSBs. New shear strength equations for LSBs were proposed based on the experimental and FEA parametric study results.

Validation Gating for Non-Linear Non-Gaussian Target Tracking

This paper develops a general theory of validation gating for non-linear non-Gaussian mod- els. Validation gates are used in target tracking to cull very unlikely measurement-to-track associa- tions, before remaining association ambiguities are handled by a more comprehensive (and expensive) data association scheme. The essential property of a gate is to accept a high percentage of correct associ- ations, thus maximising track accuracy, but provide a su±ciently tight bound to minimise the number of ambiguous associations. For linear Gaussian systems, the ellipsoidal vali- dation gate is standard, and possesses the statistical property whereby a given threshold will accept a cer- tain percentage of true associations. This property does not hold for non-linear non-Gaussian models. As a system departs from linear-Gaussian, the ellip- soid gate tends to reject a higher than expected pro- portion of correct associations and permit an excess of false ones. In this paper, the concept of the ellip- soidal gate is extended to permit correct statistics for the non-linear non-Gaussian case. The new gate is demonstrated by a bearing-only tracking example.

Asset life prediction and maintenance decision-making using a non-linear non-Gaussian state space model

Estimating and predicting degradation processes of engineering assets is crucial for reducing the cost and insuring the productivity of enterprises. Assisted by modern condition monitoring (CM) technologies, most asset degradation processes can be revealed by various degradation indicators extracted from CM data. Maintenance strategies developed using these degradation indicators (i.e. condition-based maintenance) are more cost-effective, because unnecessary maintenance activities are avoided when an asset is still in a decent health state. A practical difficulty in condition-based maintenance (CBM) is that degradation indicators extracted from CM data can only partially reveal asset health states in most situations. Underestimating this uncertainty in relationships between degradation indicators and health states can cause excessive false alarms or failures without pre-alarms. The state space model provides an efficient approach to describe a degradation process using these indicators that can only partially reveal health states. However, existing state space models that describe asset degradation processes largely depend on assumptions such as, discrete time, discrete state, linearity, and Gaussianity. The discrete time assumption requires that failures and inspections only happen at fixed intervals. The discrete state assumption entails discretising continuous degradation indicators, which requires expert knowledge and often introduces additional errors. The linear and Gaussian assumptions are not consistent with nonlinear and irreversible degradation processes in most engineering assets. This research proposes a Gamma-based state space model that does not have discrete time, discrete state, linear and Gaussian assumptions to model partially observable degradation processes. Monte Carlo-based algorithms are developed to estimate model parameters and asset remaining useful lives. In addition, this research also develops a continuous state partially observable semi-Markov decision process (POSMDP) to model a degradation process that follows the Gamma-based state space model and is under various maintenance strategies. Optimal maintenance strategies are obtained by solving the POSMDP. Simulation studies through the MATLAB are performed; case studies using the data from an accelerated life test of a gearbox and a liquefied natural gas industry are also conducted. The results show that the proposed Monte Carlo-based EM algorithm can estimate model parameters accurately. The results also show that the proposed Gamma-based state space model have better fitness result than linear and Gaussian state space models when used to process monotonically increasing degradation data in the accelerated life test of a gear box. Furthermore, both simulation studies and case studies show that the prediction algorithm based on the Gamma-based state space model can identify the mean value and confidence interval of asset remaining useful lives accurately. In addition, the simulation study shows that the proposed maintenance strategy optimisation method based on the POSMDP is more flexible than that assumes a predetermined strategy structure and uses the renewal theory. Moreover, the simulation study also shows that the proposed maintenance optimisation method can obtain more cost-effective strategies than a recently published maintenance strategy optimisation method by optimising the next maintenance activity and the waiting time till the next maintenance activity simultaneously.

Rademacher and Gaussian complexities: Risk bounds and structural results

We investigate the use of certain data-dependent estimates of the complexity of a function class, called Rademacher and Gaussian complexities. In a decision theoretic setting, we prove general risk bounds in terms of these complexities. We consider function classes that can be expressed as combinations of functions from basis classes and show how the Rademacher and Gaussian complexities of such a function class can be bounded in terms of the complexity of the basis classes. We give examples of the application of these techniques in finding data-dependent risk bounds for decision trees, neural networks and support vector machines.

Vector quantization based Gaussian modeling for speaker verification

Gaussian mixture models (GMMs) have become an established means of modeling feature distributions in speaker recognition systems. It is useful for experimentation and practical implementation purposes to develop and test these models in an efficient manner particularly when computational resources are limited. A method of combining vector quantization (VQ) with single multi-dimensional Gaussians is proposed to rapidly generate a robust model approximation to the Gaussian mixture model. A fast method of testing these systems is also proposed and implemented. Results on the NIST 1996 Speaker Recognition Database suggest comparable and in some cases an improved verification performance to the traditional GMM based analysis scheme. In addition, previous research for the task of speaker identification indicated a similar system perfomance between the VQ Gaussian based technique and GMMs

Gaussian process models for sensor-centric robot localisation

This paper presents an approach to building an observation likelihood function from a set of sparse, noisy training observations taken from known locations by a sensor with no obvious geometric model. The basic approach is to fit an interpolant to the training data, representing the expected observation, and to assume additive sensor noise. This paper takes a Bayesian view of the problem, maintaining a posterior over interpolants rather than simply the maximum-likelihood interpolant, giving a measure of uncertainty in the map at any point. This is done using a Gaussian process framework. To validate the approach experimentally, a model of an environment is built using observations from an omni-directional camera. After a model has been built from the training data, a particle filter is used to localise while traversing this environment

PySSM : a Python module for Bayesian inference of linear Gaussian state space models

PySSM is a Python package that has been developed for the analysis of time series using linear Gaussian state space models (SSM). PySSM is easy to use; models can be set up quickly and efficiently and a variety of different settings are available to the user. It also takes advantage of scientific libraries Numpy and Scipy and other high level features of the Python language. PySSM is also used as a platform for interfacing between optimised and parallelised Fortran routines. These Fortran routines heavily utilise Basic Linear Algebra (BLAS) and Linear Algebra Package (LAPACK) functions for maximum performance. PySSM contains classes for filtering, classical smoothing as well as simulation smoothing.

Plastic bending behaviour and section moment capacities of mono-symmetric LiteSteel Beams with web openings

Recently developed cold-formed LiteSteel beam (LSB) sections have found increasing popularity in residential, industrial and commercial buildings due to their light weight and cost-effectiveness. Currently, there is significant interest in the use of LSB sections as flexural members in floor joist systems, although they can be used as flexural and compression members in a range of building systems. The plastic bending behaviour and section moment capacity of LSB sections with web holes can be assumed to differ from those without, but have yet to be investigated. Hence, no appropriate design rules for determining the section moment capacity of LSB sections with web holes are yet available. This paper presents the results of an investigation of the plastic bending behaviour and section moment capacity of LSB sections with circular web holes. LSB sections with varying circular hole diameters and degrees of spacing were considered. The paper also describes the simplified finite element (FE) modelling technique employed in this study, which incorporates all of the significant behavioural effects that influence the plastic bending behaviour and section moment capacity of these sections. The numerical and experimental test results and associated findings are also presented.