Wind uplift strength of trapezoidal steel cladding with closely spaced ribs

When crest-fixed thin trapezoidal steel cladding with closely spaced ribs is subjected to wind uplift/suction forces, local dimpling or pull-through failures occur prematurely at their screw connections because of the large stress concentrations in the cladding under the screw heads. Currently, the design of crest-fixed profiled steel cladding is mainly based on time consuming and expensive laboratory tests due to the lack of adequate design rules. In this research, a shell finite element model of crest-fixed trapezoidal steel cladding with closely spaced ribs was developed and validated using experimental results. The finite element model included a recently developed splitting criterion and other advanced features including geometric imperfections, buckling effects, contact modelling and hyperelastic behaviour of neoprene washers, and was used in a detailed parametric study to develop suitable design formulae for local failures. This paper presents the details of the finite element analyses, large scale experiments and their results including the new wind uplift design strength formulae for trapezoidal steel cladding with closely spaced ribs. The new design formulae can be used to achieve both safe and optimised solutions.

Bond–slip models for double strap joints strengthened by CFRP

This paper presents the results of a series of tension tests on CFRP bonded steel plate double strap joints. The main aim of this research is to provide detailed understanding of bond characteristics using experimental and numerical analysis of strengthened double strap joints under tension. A parametric study has been performed by numerical modelling with the variables of CFRP bond lengths, adhesive maximum strain and adhesive layer thicknesses. Finally, bond-slip models are proposed for three different types of adhesives within the range of the parametric study.

Linkage to chromosome 2q32.2-q33.3 in familial serrated neoplasia (Jass syndrome)

Abstract Causative genetic variants have to date been identified for only a small proportion of familial colorectal cancer (CRC). While conditions such as Familial Adenomatous Polyposis and Lynch syndrome have well defined genetic causes, the search for variants underlying the remainder of familial CRC is plagued by genetic heterogeneity. The recent identification of families with a heritable predisposition to malignancies arising through the serrated pathway (familial serrated neoplasia or Jass syndrome) provides an opportunity to study a subset of familial CRC in which heterogeneity may be greatly reduced. A genome-wide linkage screen was performed on a large family displaying a dominantly-inherited predisposition to serrated neoplasia genotyped using the Affymetrix GeneChip Human Mapping 10 K SNP Array. Parametric and nonparametric analyses were performed and resulting regions of interest, as well as previously reported CRC susceptibility loci at 3q22, 7q31 and 9q22, were followed up by finemapping in 10 serrated neoplasia families. Genome-wide linkage analysis revealed regions of interest at 2p25.2-p25.1, 2q24.3-q37.1 and 8p21.2-q12.1. Finemapping linkage and haplotype analyses identified 2q32.2-q33.3 as the region most likely to harbour linkage, with heterogeneity logarithm of the odds (HLOD) 2.09 and nonparametric linkage (NPL) score 2.36 (P = 0.004). Five primary candidate genes (CFLAR, CASP10, CASP8, FZD7 and BMPR2) were sequenced and no segregating variants identified. There was no evidence of linkage to previously reported loci on chromosomes 3, 7 and 9.

The HarmonyGrid : music, space and performance in grid music systems

This research explores music in space, as experienced through performing and music-making with interactive systems. It explores how musical parameters may be presented spatially and displayed visually with a view to their exploration by a musician during performance. Spatial arrangements of musical components, especially pitches and harmonies, have been widely studied in the literature, but the current capabilities of interactive systems allow the improvisational exploration of these musical spaces as part of a performance practice. This research focuses on quantised spatial organisation of musical parameters that can be categorised as grid music systems (GMSs), and interactive music systems based on them. The research explores and surveys existing and historical uses of GMSs, and develops and demonstrates the use of a novel grid music system designed for whole body interaction. Grid music systems provide plotting of spatialised input to construct patterned music on a two-dimensional grid layout. GMSs are navigated to construct a sequence of parametric steps, for example a series of pitches, rhythmic values, a chord sequence, or terraced dynamic steps. While they are conceptually simple when only controlling one musical dimension, grid systems may be layered to enable complex and satisfying musical results. These systems have proved a viable, effective, accessible and engaging means of music-making for the general user as well as the musician. GMSs have been widely used in electronic and digital music technologies, where they have generally been applied to small portable devices and software systems such as step sequencers and drum machines. This research shows that by scaling up a grid music system, music-making and musical improvisation are enhanced, gaining several advantages: (1) Full body location becomes the spatial input to the grid. The system becomes a partially immersive one in four related ways: spatially, graphically, sonically and musically. (2) Detection of body location by tracking enables hands-free operation, thereby allowing the playing of a musical instrument in addition to “playing” the grid system. (3) Visual information regarding musical parameters may be enhanced so that the performer may fully engage with existing spatial knowledge of musical materials. The result is that existing spatial knowledge is overlaid on, and combined with, music-space. Music-space is a new concept produced by the research, and is similar to notions of other musical spaces including soundscape, acoustic space, Smalley's “circumspace” and “immersive space” (2007, 48-52), and Lotis's “ambiophony” (2003), but is rather more textural and “alive”—and therefore very conducive to interaction. Music-space is that space occupied by music, set within normal space, which may be perceived by a person located within, or moving around in that space. Music-space has a perceivable “texture” made of tensions and relaxations, and contains spatial patterns of these formed by musical elements such as notes, harmonies, and sounds, changing over time. The music may be performed by live musicians, created electronically, or be prerecorded. Large-scale GMSs have the capability not only to interactively display musical information as music representative space, but to allow music-space to co-exist with it. Moving around the grid, the performer may interact in real time with musical materials in music-space, as they form over squares or move in paths. Additionally he/she may sense the textural matrix of the music-space while being immersed in surround sound covering the grid. The HarmonyGrid is a new computer-based interactive performance system developed during this research that provides a generative music-making system intended to accompany, or play along with, an improvising musician. This large-scale GMS employs full-body motion tracking over a projected grid. Playing with the system creates an enhanced performance employing live interactive music, along with graphical and spatial activity. Although one other experimental system provides certain aspects of immersive music-making, currently only the HarmonyGrid provides an environment to explore and experience music-space in a GMS.

Effects of corrugation frequency and aspect ratio on natural convection within an enclosure having sinusoidal corrugation over a heated top surface

Natural convection of a two-dimensional laminar steady-state incompressible fluid flow in a modified rectangular enclosure with sinusoidal corrugated top surface has been investigated numerically. The present study has been carried out for different corrugation frequencies on the top surface as well as aspect ratios of the enclosure in order to observe the change in hydrodynamic and thermal behavior with constant corrugation amplitude. A constant flux heat source is flush mounted on the top sinusoidal wall, modeling a wavy sheet shaded room exposed to sunlight. The flat bottom surface is considered as adiabatic, while the both vertical side walls are maintained at the constant ambient temperature. The fluid considered inside the enclosure is air having Prandtl number of 0.71. The numerical scheme is based on the finite element method adapted to triangular non-uniform mesh element by a non-linear parametric solution algorithm. The results in terms of isotherms, streamlines and average Nusselt numbers are obtained for the Rayleigh number ranging from 10^3 to 10^6 with constant physical properties for the fluid medium considered. It is found that the convective phenomena are greatly influenced by the presence of the corrugation and variation of aspect ratios.

Using Bayesian methods for the estimation of uncertainty in complex statistical models

The research objectives of this thesis were to contribute to Bayesian statistical methodology by contributing to risk assessment statistical methodology, and to spatial and spatio-temporal methodology, by modelling error structures using complex hierarchical models. Specifically, I hoped to consider two applied areas, and use these applications as a springboard for developing new statistical methods as well as undertaking analyses which might give answers to particular applied questions. Thus, this thesis considers a series of models, firstly in the context of risk assessments for recycled water, and secondly in the context of water usage by crops. The research objective was to model error structures using hierarchical models in two problems, namely risk assessment analyses for wastewater, and secondly, in a four dimensional dataset, assessing differences between cropping systems over time and over three spatial dimensions. The aim was to use the simplicity and insight afforded by Bayesian networks to develop appropriate models for risk scenarios, and again to use Bayesian hierarchical models to explore the necessarily complex modelling of four dimensional agricultural data. The specific objectives of the research were to develop a method for the calculation of credible intervals for the point estimates of Bayesian networks; to develop a model structure to incorporate all the experimental uncertainty associated with various constants thereby allowing the calculation of more credible credible intervals for a risk assessment; to model a single day’s data from the agricultural dataset which satisfactorily captured the complexities of the data; to build a model for several days’ data, in order to consider how the full data might be modelled; and finally to build a model for the full four dimensional dataset and to consider the timevarying nature of the contrast of interest, having satisfactorily accounted for possible spatial and temporal autocorrelations. This work forms five papers, two of which have been published, with two submitted, and the final paper still in draft. The first two objectives were met by recasting the risk assessments as directed, acyclic graphs (DAGs). In the first case, we elicited uncertainty for the conditional probabilities needed by the Bayesian net, incorporated these into a corresponding DAG, and used Markov chain Monte Carlo (MCMC) to find credible intervals, for all the scenarios and outcomes of interest. In the second case, we incorporated the experimental data underlying the risk assessment constants into the DAG, and also treated some of that data as needing to be modelled as an ‘errors-invariables’ problem [Fuller, 1987]. This illustrated a simple method for the incorporation of experimental error into risk assessments. In considering one day of the three-dimensional agricultural data, it became clear that geostatistical models or conditional autoregressive (CAR) models over the three dimensions were not the best way to approach the data. Instead CAR models are used with neighbours only in the same depth layer. This gave flexibility to the model, allowing both the spatially structured and non-structured variances to differ at all depths. We call this model the CAR layered model. Given the experimental design, the fixed part of the model could have been modelled as a set of means by treatment and by depth, but doing so allows little insight into how the treatment effects vary with depth. Hence, a number of essentially non-parametric approaches were taken to see the effects of depth on treatment, with the model of choice incorporating an errors-in-variables approach for depth in addition to a non-parametric smooth. The statistical contribution here was the introduction of the CAR layered model, the applied contribution the analysis of moisture over depth and estimation of the contrast of interest together with its credible intervals. These models were fitted using WinBUGS [Lunn et al., 2000]. The work in the fifth paper deals with the fact that with large datasets, the use of WinBUGS becomes more problematic because of its highly correlated term by term updating. In this work, we introduce a Gibbs sampler with block updating for the CAR layered model. The Gibbs sampler was implemented by Chris Strickland using pyMCMC [Strickland, 2010]. This framework is then used to consider five days data, and we show that moisture in the soil for all the various treatments reaches levels particular to each treatment at a depth of 200 cm and thereafter stays constant, albeit with increasing variances with depth. In an analysis across three spatial dimensions and across time, there are many interactions of time and the spatial dimensions to be considered. Hence, we chose to use a daily model and to repeat the analysis at all time points, effectively creating an interaction model of time by the daily model. Such an approach allows great flexibility. However, this approach does not allow insight into the way in which the parameter of interest varies over time. Hence, a two-stage approach was also used, with estimates from the first-stage being analysed as a set of time series. We see this spatio-temporal interaction model as being a useful approach to data measured across three spatial dimensions and time, since it does not assume additivity of the random spatial or temporal effects.

Sky high and back again : the evolution of simulation-based design from aerospace to construction

Emerging from the challenge to reduce energy consumption in buildings is a need for research and development into the more effective use of simulation as a decision-support tool. Despite significant research, persistent limitations in process and software inhibit the integration of energy simulation in early architectural design. This paper presents a green star case study to highlight the obstacles commonly encountered with current integration strategies. It then examines simulation-based design in the aerospace industry, which has overcome similar limitations. Finally, it proposes a design system based on this contrasting approach, coupling parametric modelling and energy simulation software for rapid and iterative performance assessment of early design options.

Support for energy-oriented design in the Australian context

There is a need for decision support tools that integrate energy simulation into early design in the context of Australian practice. Despite the proliferation of simulation programs in the last decade, there are no ready-to-use applications that cater specifically for the Australian climate and regulations. Furthermore, the majority of existing tools focus on achieving interaction with the design domain through model-based interoperability, and largely overlook the issue of process integration. This paper proposes an energy-oriented design environment that both accommodates the Australian context and provides interactive and iterative information exchanges that facilitate feedback between domains. It then presents the structure for DEEPA, an openly customisable system that couples parametric modelling and energy simulation software as a means of developing a decision support tool to allow designers to rapidly and flexibly assess the performance of early design alternatives. Finally, it discusses the benefits of developing a dynamic and concurrent performance evaluation process that parallels the characteristics and relationships of the design process.

Energy-oriented design tools for collaboration in the cloud

Emerging from the challenge to reduce energy consumption in buildings is the need for energy simulation to be used more effectively to support integrated decision making in early design. As a critical response to a Green Star case study, we present DEEPA, a parametric modeling framework that enables architects and engineers to work at the same semantic level to generate shared models for energy simulation. A cloud-based toolkit provides web and data services for parametric design software that automate the process of simulating and tracking design alternatives, by linking building geometry more directly to analysis inputs. Data, semantics, models and simulation results can be shared on the fly. This allows the complex relationships between architecture, building services and energy consumption to be explored in an integrated manner, and decisions to be made collaboratively.

Building information modeling in the Australian architecture engineering and construction industry

Building Information Modeling (BIM) is a modern approach to the design, documentation, delivery, and life cycle management of buildings through the use of project information databases coupled with object-based parametric modeling. BIM has the potential to revolutionize the Architecture, Engineering and Construction (AEC) industry in terms of the positive impact it may have on information flows, working relationships between project participants from different disciplines and the resulting benefits it may achieve through improvements to conventional methods. This chapter reviews the development of BIM, the extent to which BIM has been implemented in Australia, and the factors which have affected the up-take of BIM. More specifically, the objectives of this chapter are to investigate the adoption of BIM in the Australian AEC industry and factors that contribute towards the uptake (or non uptake) of BIM. These objectives are met by a review of the related literature in the first instance, followed by the presentation of the results of a 2007 postal questionnaire survey and telephone interviews of a random sample of professionals in the Australian AEC industry. The responses suggest that less than 25 percent of the sample had been involved in BIM – rather less than might be expected from reading the literature. Also, of those who have been involved with BIM, there has been very little interdisciplinary collaboration. The main barriers impeding the implementation of BIM widely across the Australian AEC industry are also identified. These were found to be primarily a lack of BIM expertise, lack of awareness and resistance to change. The benefits experienced as a result of using BIM are also discussed. These include improved design consistency, better coordination, cost savings, higher quality work, greater productivity and increased speed of delivery. In terms of conclusion, some suggestions are made concerning the underlying practical reasons for the slow up-take of BIM and the successes for those early adopters. Prospects for future improvement are discussed and proposals are also made for a large scale worldwide comparative study covering industry-wide participants

Mixed convection laminar flow along a horizontal plate subject to streamwise sinusoidal surface temperature

Mixed convection of a two-dimensional laminar incompressible flow along a horizontal flat plate with streamwise sinusoidal surface temperature has been numerically investigated for different values of Rayleigh number and Reynolds number for constant values of Prandtl number, amplitude and frequency of periodic temperature. The numerical scheme is based on the finite element method adapted to rectangular non-uniform mesh elements by a non-linear parametric solution algorithm. The fluid considered in this study is air. The results are obtained for the Rayleigh number and Reynolds number ranging from 102 to 104 and 1 to 100, respectively, with constant physical properties for the fluid medium considered. Velocity and temperature profiles, streamlines, isotherms, and average Nusselt numbers are presented to observe the effect of the investigating parameters on fluid flow and heat transfer characteristics. The present results show that the convective phenomena are greatly influenced by the variation of Rayleigh numbers and Reynolds number.

Effect of differentially heating and consequent transient behaviour for natural convection within an enclosure of sinusoidal corrugated side walls

Unsteady natural convection due to differentially heating of the sinusoidal corrugated side walls of a modified square enclosure has been numerically investigated. The fluid inside the enclosure is air, initially as quiescent. The flat top and bottom surfaces are considered as adiabatic. The numerical scheme is based on the finite element method adapted to triangular non-uniform mesh element by a non-linear parametric solution algorithm. The results are obtained for the Rayleigh number, Ra ranging from 1e+05 to 1e+08 for different corrugation amplitude and frequency with constant physical properties for the fluid medium considered. The streamlines, isotherms and average Nusselt numbers are presented to observe the effect of sudden heating and its consequent transient behavior on fluid flow and heat transfer characteristics for the range of governing parameters. The present results show that the transient phenomena are greatly influenced by the variation of the aforementioned parameters.

Sequential Monte Carlo for Bayesian sequentially designed experiments for discrete data

In this paper we present a sequential Monte Carlo algorithm for Bayesian sequential experimental design applied to generalised non-linear models for discrete data. The approach is computationally convenient in that the information of newly observed data can be incorporated through a simple re-weighting step. We also consider a flexible parametric model for the stimulus-response relationship together with a newly developed hybrid design utility that can produce more robust estimates of the target stimulus in the presence of substantial model and parameter uncertainty. The algorithm is applied to hypothetical clinical trial or bioassay scenarios. In the discussion, potential generalisations of the algorithm are suggested to possibly extend its applicability to a wide variety of scenarios

Strategic project evaluation for open pit mining ventures using real options and allied econometric techniques

Open pit mine operations are complex businesses that demand a constant assessment of risk. This is because the value of a mine project is typically influenced by many underlying economic and physical uncertainties, such as metal prices, metal grades, costs, schedules, quantities, and environmental issues, among others, which are not known with much certainty at the beginning of the project. Hence, mining projects present a considerable challenge to those involved in associated investment decisions, such as the owners of the mine and other stakeholders. In general terms, when an option exists to acquire a new or operating mining project, , the owners and stock holders of the mine project need to know the value of the mining project, which is the fundamental criterion for making final decisions about going ahead with the venture capital. However, obtaining the mine project’s value is not an easy task. The reason for this is that sophisticated valuation and mine optimisation techniques, which combine advanced theories in geostatistics, statistics, engineering, economics and finance, among others, need to be used by the mine analyst or mine planner in order to assess and quantify the existing uncertainty and, consequently, the risk involved in the project investment. Furthermore, current valuation and mine optimisation techniques do not complement each other. That is valuation techniques based on real options (RO) analysis assume an expected (constant) metal grade and ore tonnage during a specified period, while mine optimisation (MO) techniques assume expected (constant) metal prices and mining costs. These assumptions are not totally correct since both sources of uncertainty—that of the orebody (metal grade and reserves of mineral), and that about the future behaviour of metal prices and mining costs—are the ones that have great impact on the value of any mining project. Consequently, the key objective of this thesis is twofold. The first objective consists of analysing and understanding the main sources of uncertainty in an open pit mining project, such as the orebody (in situ metal grade), mining costs and metal price uncertainties, and their effect on the final project value. The second objective consists of breaking down the wall of isolation between economic valuation and mine optimisation techniques in order to generate a novel open pit mine evaluation framework called the ―Integrated Valuation / Optimisation Framework (IVOF)‖. One important characteristic of this new framework is that it incorporates the RO and MO valuation techniques into a single integrated process that quantifies and describes uncertainty and risk in a mine project evaluation process, giving a more realistic estimate of the project’s value. To achieve this, novel and advanced engineering and econometric methods are used to integrate financial and geological uncertainty into dynamic risk forecasting measures. The proposed mine valuation/optimisation technique is then applied to a real gold disseminated open pit mine deposit to estimate its value in the face of orebody, mining costs and metal price uncertainties.

New design rules for the shear strength of LiteSteel Beams

Abstract: The LiteSteel Beam (LSB) is a new cold-formed hollow flange channel section produced using dual electric resistance welding and automated continuous roll-forming technologies. The innovative LSB sections have many beneficial characteristics and are commonly used as flexural members in building construction. However, limited 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. Finite element models of LSBs in shear were developed to simulate the nonlinear ultimate strength behaviour of LSBs including their elastic buckling characteristics, and were validated by comparing their results with experimental test results. Validated finite element models were then used in a detailed parametric study into the shear behaviour of LSBs. The parametric study results showed that the current design rules in cold-formed steel structures design codes are very conservative for the shear design of LSBs. Significant improvements to web shear buckling occurred due to the presence of torsionally rigid rectangular hollow flanges while considerable post-buckling strength was also observed. This paper therefore proposes improved shear strength design rules for LSBs within the current cold-formed steel code guidelines. It presents the details of the parametric study and the new shear strength equations. The new equations were also developed based on the direct strength method. The proposed shear strength equations have the potential to be used with other conventional cold-formed steel sections such as lipped channel sections.