Lateral-torsional buckling of cold-formed steel beams at ambient temperature

Cold-formed steel beams are increasingly used as floor joists and bearers in residential, industrial and commercial buildings. Their structural behaviour and moment capacities are influenced by lateral-torsional buckling and hence a research study was undertaken to investigate the lateral-torsional buckling behaviour of cold-formed steel lipped channel beams at ambient and elevated temperatures. For this purpose a finite element model of a simply supported cold-formed steel lipped channel beam under uniform bending was developed first and validated using available numberical and experimental results. It was then used in a detailed parametric study to simulate the lateral-torsional behaviour of cold-formed steel beams under varying conditions. The moment capacity results were then compared with the predictions from the current ambient temperature design rules in Australia, New Zealand, American and European codes for cold-formed steel structures. Some very interesting results have been obtained. European design rules are found to be conservative while Australian and American design rules are unsafe. This paper presents the results of finite element analyses for ambient temperature conditions, and the comparison with the current design rules.

Selective growth of carbon nanotubes on bare silicon : MWNT sinthesys on patterned substrates without predeposition of metal catalyst

Carbon nanotubes (CNTs) are expected to become the ideal constituent of many technologes, in particular for future generation electronics. This considerable interest is due to their unique electrical and mechanical properties. They show indeed super-high current-carrying capacity, ballistic electron transport and good field-emission properties. Then, these superior features make CNTs the most promising building blocks for electronic devices, as organic solar cells and organic light emitting devices (OLED). By using Focused Ion Beam (FIB) patterning it is possible to a obtain a high control on position, relative distances and diameter of CNTs. The present work shows how to grow three-dimensional architecture made of vertical-aligned CNTs directly on silicon. Thanks to the higher activity of a pre-patterned surface the synthesis process results very quick, cheap and simple. Such large area growths of CNTs could be used in preliminary test for application as electrodes for organic solar cells.

Axial shortening in reinforced concrete members using vibration characteristics - Part 1 - Theory

Differential axial shortening in vertical members of reinforced concrete high-rise buildings occurs due to shrinkage, creep and elastic shortening, which are time dependent effects of concrete. This has to be quantified in order to make adequate provisions and mitigate its adverse effects. This paper presents a novel procedure for quantifying the axial shortening of vertical members using the variations in vibration characteristics of the structure, in lieu of using gauges which can pose problems in use during and after the construction. This procedure is based on the changes in the modal flexiblity matrix which is expressed as a function of the mode shapes and the reciprocal of the natural frequencies. This paper will present the development of this novel procedure.

Axial shortening in reinforced concrete members using vibration characteristics - part 2 - Application

Controlling differential axial shortening in vertical load bearing concrete elements is a major concern for new generation tall buildings with complex geometries and mechanisms. Quantification of axial shortening using gauges to verify the pre-estimated numerical values used at the design stage is a well established method. This method makes adequate provision to mitigate the adverse effects during the construction. However, this method is becoming increasingly unusable due to its drawbacks. This highlights the need a novel method to quantify the axial shortening using ambient measurements. This paper will first brief introduce the method and then illustrate its application to a high-rise building with two outrigger and belt systems. Moreover, this procedure can be used as a health or performance monitoring tool of the building structure, both during and after construction.

A framework for analysing system intelligence of the building control system: a study of the integrated building management system

The lack of satisfactory consensus for characterizing the system intelligence and structured analytical decision models has inhibited the developers and practitioners to understand and configure optimum intelligent building systems in a fully informed manner. So far, little research has been conducted in this aspect. This research is designed to identify the key intelligent indicators, and develop analytical models for computing the system intelligence score of smart building system in the intelligent building. The integrated building management system (IBMS) was used as an illustrative example to present a framework. The models presented in this study applied the system intelligence theory, and the conceptual analytical framework. A total of 16 key intelligent indicators were first identified from a general survey. Then, two multi-criteria decision making (MCDM) approaches, the analytic hierarchy process (AHP) and analytic network process (ANP), were employed to develop the system intelligence analytical models. Top intelligence indicators of IBMS include: self-diagnostic of operation deviations; adaptive limiting control algorithm; and, year-round time schedule performance. The developed conceptual framework was then transformed to the practical model. The effectiveness of the practical model was evaluated by means of expert validation. The main contribution of this research is to promote understanding of the intelligent indicators, and to set the foundation for a systemic framework that provide developers and building stakeholders a consolidated inclusive tool for the system intelligence evaluation of the proposed components design configurations.

Measuring up! Bringing everything we know together to make the researcher profile “sing”.

The search is ongoing for the perfect researcher profile with fully integrated citations, plus links to publications, research data, esteem measures, media releases, plus social media feeds and links to the researchers place of work.

Sensing Shape Recovery Using Conductivity Noise in Thin Films of NiTi Shape Memory Alloys

Low frequency fluctuations in the electrical resistivity, or noise, have been used as a sensitive tool to probe into the temperature driven martensite transition in dc magnetron sputtered thin films of nickel titanium shape-memory alloys. Even in the equilibrium or static case, the noise magnitude was more than nine orders of magnitude larger than conventional metallic thin films and had a characteristic dependence on temperature. We observe that the noise while the temperature is being ramped is far larger as compared to the equilibrium noise indicating the sensitivity of electrical resistivity to the nucleation and propagation of domains during the shape recovery. Further, the higher order statistics suggests the existence of long range correlations during the transition. This new characterization is based on the kinetics of disorder in the system and separate from existing techniques and can be integrated to many device applications of shape memory alloys for in-situ shape recovery sensing.

Modeling of active fiber composite for delamination sensing

In order to demonstrate the feasibility of Active Fiber Composites (AFC) as sensors for detecting damage, a pretwisted strip made of AFC with symmetric free-edge delamination is considered in this paper. The strain developed on the top/bottom of the strip is measured to detect and assess delamination. Variational Asymptotic Method (VAM) is used in the development of a non-classical non-linear cross sectional model of the strip. The original three dimensional (3D) problem is simplified by the decomposition into two simpler problems: a two-dimensional (2D) problem, which provides in a compact form the cross-sectional properties using VAM, and a non-linear one-dimensional (1D) problem along the length of the beam. This procedure gives the non-linear stiffnesses, which are very sensitive to damage, at any given cross-section of the strip. The developed model is used to study a special case of cantilevered laminated strip with antisymmetric layup, loaded only by an axial force at the tip. The charge generated in the AFC lamina is derived in closed form in terms of the 1D strain measures. It is observed that delamination length and location have a definite influence on the charge developed in the AFC lamina. Also, sensor voltage output distribution along the length of the beam is obtained using evenly distributed electrode strip. These data could in turn be used to detect the presence of damage.

The influence of hard-segments on two-phase structure and shape memory properties of PCL-based segmented polyurethanes

Poly(epsilon-caprolactone)-based segmented polyurethanes (PCLUs) were prepared from poly(epsilon-caprolactone) diol, diisocyanates (DI), and 1,4-butanediol. The DIs used were 4,4'-diphenylmethane diisocyanate (MDI), 2,4-toluenediisocyanate (TDI), iso-phorone diisocyanate (IPDI), and hexamethylene diisocyanate (HDI). Differential scanning calorimetry, small-angle X-ray scattering, and dynamic mechanical analysis were employed to characterize the two-phase structures of all PCLUs. It was found that HDI- and MDI-based PCLUs had higher degree of microphase separation than did IPDI- and TDI-based PCLUs, which was primarily due to the crystallization of HDI- and MDI-based hard-segments. As a result, the HDI-based PCLU exhibited the highest recovery force up to 6 MPa and slowest stress relaxation with increasing temperature. Besides, it was found that the partial damage in hard-segment domains during the sample deformation was responsible for the incomplete shape-recovery of PCLUs after the first deformation, but the damage did not develop during the subsequent deformation.

Hybrid energy storage for energy harvesting powered wireless sensor networks

Science Foundation Ireland (CSET - Centre for Science, Engineering and Technology, grant 07/CE/I1147); Scientific Foundation Ireland (ITOBO (398-CRP))

Inter layer and cooperative design strategies for green mobile networks

The promise of a truly mobile experience is to have the freedom to roam around anywhere and not be bound to a single location. However, the energy required to keep mobile devices connected to the network over extended periods of time quickly dissipates. In fact, energy is a critical resource in the design of wireless networks since wireless devices are usually powered by batteries. Furthermore, multi-standard mobile devices are allowing users to enjoy higher data rates with ubiquitous connectivity. However, the bene ts gained from multiple interfaces come at a cost in terms of energy consumption having profound e ect on the mobile battery lifetime and standby time. This concern is rea rmed by the fact that battery lifetime is one of the top reasons why consumers are deterred from using advanced multimedia services on their mobile on a frequent basis. In order to secure market penetration for next generation services energy e ciency needs to be placed at the forefront of system design. However, despite recent e orts, energy compliant features in legacy technologies are still in its infancy, and new disruptive architectures coupled with interdisciplinary design approaches are required in order to not only promote the energy gain within a single protocol layer, but to enhance the energy gain from a holistic perspective. A promising approach is cooperative smart systems, that in addition to exploiting context information, are entities that are able to form a coalition and cooperate in order to achieve a common goal. Migrating from this baseline, this thesis investigates how these technology paradigm can be applied towards reducing the energy consumption in mobile networks. In addition, we introduce an additional energy saving dimension by adopting an interlayer design so that protocol layers are designed to work in synergy with the host system, rather than independently, for harnessing energy. In this work, we exploit context information, cooperation and inter-layer design for developing new energy e cient and technology agnostic building blocks for mobile networks. These technology enablers include energy e cient node discovery and short-range cooperation for energy saving in mobile handsets, complemented by energy-aware smart scheduling for promoting energy saving on the network side. Analytical and simulations results were obtained, and veri ed in the lab on a real hardware testbed. Results have shown that up to 50% energy saving could be obtained.

Robust suspicious behaviour detection for smart surveillance systems

Video surveillance technology, based on Closed Circuit Television (CCTV) cameras, is one of the fastest growing markets in the field of security technologies. However, the existing video surveillance systems are still not at a stage where they can be used for crime prevention. The systems rely heavily on human observers and are therefore limited by factors such as fatigue and monitoring capabilities over long periods of time. To overcome this limitation, it is necessary to have “intelligent” processes which are able to highlight the salient data and filter out normal conditions that do not pose a threat to security. In order to create such intelligent systems, an understanding of human behaviour, specifically, suspicious behaviour is required. One of the challenges in achieving this is that human behaviour can only be understood correctly in the context in which it appears. Although context has been exploited in the general computer vision domain, it has not been widely used in the automatic suspicious behaviour detection domain. So, it is essential that context has to be formulated, stored and used by the system in order to understand human behaviour. Finally, since surveillance systems could be modeled as largescale data stream systems, it is difficult to have a complete knowledge base. In this case, the systems need to not only continuously update their knowledge but also be able to retrieve the extracted information which is related to the given context. To address these issues, a context-based approach for detecting suspicious behaviour is proposed. In this approach, contextual information is exploited in order to make a better detection. The proposed approach utilises a data stream clustering algorithm in order to discover the behaviour classes and their frequency of occurrences from the incoming behaviour instances. Contextual information is then used in addition to the above information to detect suspicious behaviour. The proposed approach is able to detect observed, unobserved and contextual suspicious behaviour. Two case studies using video feeds taken from CAVIAR dataset and Z-block building, Queensland University of Technology are presented in order to test the proposed approach. From these experiments, it is shown that by using information about context, the proposed system is able to make a more accurate detection, especially those behaviours which are only suspicious in some contexts while being normal in the others. Moreover, this information give critical feedback to the system designers to refine the system. Finally, the proposed modified Clustream algorithm enables the system to both continuously update the system’s knowledge and to effectively retrieve the information learned in a given context. The outcomes from this research are: (a) A context-based framework for automatic detecting suspicious behaviour which can be used by an intelligent video surveillance in making decisions; (b) A modified Clustream data stream clustering algorithm which continuously updates the system knowledge and is able to retrieve contextually related information effectively; and (c) An update-describe approach which extends the capability of the existing human local motion features called interest points based features to the data stream environment.