Development of an Innovative Hybrid-Composite Floor System

This paper discusses the research carried out towards the development of a hybrid-composite floor plate systems (HCFPS) using polyurethane (PU), glass-fibre reinforced cement (GRC) and thin perforated steel laminate. HCFPS is configured in such a way where positive inherent properties of individual component materials are combined to offset any weakness and achieve the optimum performance. Finite Element modeling of HCFPS with ABAQUS 6.9-1, comparative studies of HCFPS with the steel deck composite system and experimental investigations which will be carried out are briefly described in the paper.

Unit commitment in power systems with plug-in hybrid electric vehicles

With the continued development of renewable energy generation technologies and increasing pressure to combat the global effects of greenhouse warming, plug-in hybrid electric vehicles (PHEVs) have received worldwide attention, finding applications in North America and Europe. When a large number of PHEVs are introduced into a power system, there will be extensive impacts on power system planning and operation, as well as on electricity market development. It is therefore necessary to properly control PHEV charging and discharging behaviors. Given this background, a new unit commitment model and its solution method that takes into account the optimal PHEV charging and discharging controls is presented in this paper. A 10-unit and 24-hour unit commitment (UC) problem is employed to demonstrate the feasibility and efficiency of the developed method, and the impacts of the wide applications of PHEVs on the operating costs and the emission of the power system are studied. Case studies are also carried out to investigate the impacts of different PHEV penetration levels and different PHEV charging modes on the results of the UC problem. A 100-unit system is employed for further analysis on the impacts of PHEVs on the UC problem in a larger system application. Simulation results demonstrate that the employment of optimized PHEV charging and discharging modes is very helpful for smoothing the load curve profile and enhancing the ability of the power system to accommodate more PHEVs. Furthermore, an optimal Vehicle to Grid (V2G) discharging control provides economic and efficient backups and spinning reserves for the secure and economic operation of the power system

Evolutionary design of bone scaffolds with reference to material selection

The favourable scaffold for bone tissue engineering should have desired characteristic features, such as adequate mechanical strength and three-dimensional open porosity, which guarantee a suitable environment for tissue regeneration. In fact, the design of such complex structures like bone scaffolds is a challenge for investigators. One of the aims is to achieve the best possible mechanical strength-degradation rate ratio. In this paper we attempt to use numerical modelling to evaluate material properties for designing bone tissue engineering scaffold fabricated via the fused deposition modelling technique. For our studies the standard genetic algorithm was used, which is an efficient method of discrete optimization. For the fused deposition modelling scaffold, each individual strut is scrutinized for its role in the architecture and structural support it provides for the scaffold, and its contribution to the overall scaffold was studied. The goal of the study was to create a numerical tool that could help to acquire the desired behaviour of tissue engineered scaffolds and our results showed that this could be achieved efficiently by using different materials for individual struts. To represent a great number of ways in which scaffold mechanical function loss could proceed, the exemplary set of different desirable scaffold stiffness loss function was chosen. © 2012 John Wiley & Sons, Ltd.

Relative entropy rate based model selection for linear hybrid system filters of uncertain nonlinear systems

Hybrid system representations have been exploited in a number of challenging modelling situations, including situations where the original nonlinear dynamics are too complex (or too imprecisely known) to be directly filtered. Unfortunately, the question of how to best design suitable hybrid system models has not yet been fully addressed, particularly in the situations involving model uncertainty. This paper proposes a novel joint state-measurement relative entropy rate based approach for design of hybrid system filters in the presence of (parameterised) model uncertainty. We also present a design approach suitable for suboptimal hybrid system filters. The benefits of our proposed approaches are illustrated through design examples and simulation studies.

Submarine deposition of volcaniclastic material from the 1995-2005 eruptions of Soufriere Hills volcano, Montserrat

Soufrière Hills volcano, Montserrat, has been erupting since 1995. During the current eruption, a large part of the material produced by the volcano has been transported into the sea, modifying the morphology of the submarine flanks of the volcano. We present a unique set of swath bathymetric data collected offshore from Montserrat in 1999, 2002 and 2005. From 1999 to 2002, pyroclastic flows associated with numerous dome collapses entered the sea to produce 100 Mm3 deposit. From 2002 to 2005, the 290 Mm3 submarine deposit is mainly from the 12–13 July 2003 collapse. These data allow us to estimate that, by May 2005, at least 482 Mm3 of material had been deposited on the sea floor since 1995. We compare on-land characteristics and volumes of dome collapse events with the submarine deposits and propose a new analysis of their emplacement on the submarine flanks of the volcano. The deposition mechanism shows a slope dependence, with the maximum thickness of deposit before the break in the slope, probably because of the type of the dense granular flow involved. We conclude that from 1995 to 2005 more than 75% of the erupted volume entered the sea.

A hybrid model for studying spatial aspects of infectious diseases

We consider a hybrid model, created by coupling a continuum and an agent-based model of infectious disease. The framework of the hybrid model provides a mechanism to study the spread of infection at both the individual and population levels. This approach captures the stochastic spatial heterogeneity at the individual level, which is directly related to deterministic population level properties. This facilitates the study of spatial aspects of the epidemic process. A spatial analysis, involving counting the number of infectious agents in equally sized bins, reveals when the spatial domain is nonhomogeneous.

Towards visualising people’s ecology of hybrid personal learning environments

Ambient media architecture can provide place-based collaborative learning experiences and pathways for social interactions that would not be otherwise possible. This paper is concerned with ways of enhancing peer-to-peer learning affordances in library spaces; how can the library facilitate the community of library users to learn from each other? We report on the findings of a study that employed a participatory design method where participants were asked to reflect and draw places, social networks, and activities that they use to work (be creative, productive), play (have fun, socialize, be entertained), and learn (acquire new information, knowledge, or skills). The results illustrate how informal learning – learning outside the formal education system – is facilitated by a personal selection of physical and socio-cultural environments, as well as online tools, platforms, and networks. This paper sheds light on participants’ individually curated ecologies of their work, play, and learning related networks and the hybrid (physical and digital) nature of these places. These insights reveal opportunities for ambient media architecture to increase awareness of and connections between people’s hybrid personal learning environments.

A hybrid approach to combining CART and logistic regression for stock ranking

The benefits of applying tree-based methods to the purpose of modelling financial assets as opposed to linear factor analysis are increasingly being understood by market practitioners. Tree-based models such as CART (classification and regression trees) are particularly well suited to analysing stock market data which is noisy and often contains non-linear relationships and high-order interactions. CART was originally developed in the 1980s by medical researchers disheartened by the stringent assumptions applied by traditional regression analysis (Brieman et al. [1984]). In the intervening years, CART has been successfully applied to many areas of finance such as the classification of financial distress of firms (see Frydman, Altman and Kao [1985]), asset allocation (see Sorensen, Mezrich and Miller [1996]), equity style timing (see Kao and Shumaker [1999]) and stock selection (see Sorensen, Miller and Ooi [2000])...

Measurement of structural changes to a food material during dehydration

Rates of dehydration/rehydration are important quality parameters for dried products. Theoretically, if there are no adverse effects on the integrity of the tissue structure, it should absorb water to the same moisture content of the initial product before drying.The purpose of this work is to semi-automate the process of detection of cell structure boundaries as a food is dehydrated and rehydrated. This will enable food materials researchers to quantify changes to material’s structure as these processes take place. Images of potato cells as they were dehydrated and rehydrated were taken using an electron microscope. Cell boundaries were detected using an image processing algorithm. Average cell area and perimeter at each stage of dehydration were calculated and plotted versus time. The results show that the algorithm can successfully identify cell boundaries.

A hybrid stereo matching algorithm incorporating the rank constraint

A fundamental problem faced by stereo vision algorithms is that of determining correspondences between two images which comprise a stereo pair. This paper presents work towards the development of a new matching algorithm, based on the rank transform. This algorithm makes use of both area-based and edge-based information, and is therefore referred to as a hybrid algorithm. In addition, this algorithm uses a number of matching constraints, including the novel rank constraint. Results obtained using a number of test pairs show that the matching algorithm is capable of removing most invalid matches. The accuracy of matching in the vicinity of edges is also improved.

Innovative hybrid composite floor plate system

New materials technology has provided the potential for the development of an innovative Hybrid Composite Floor Plate System (HCFPS) with many desirable properties, such as light weight, easy to construct, economical, demountable, recyclable and reusable. Component materials of HCFPS include a central Polyurethane (PU) core, outer layers of Glass-fibre Reinforced Cement (GRC) and steel laminates at tensile regions. HCFPS is configured such that the positive inherent properties of individual component materials are combined to offset any weakness and achieve optimum performance. Research has been carried out using extensive Finite Element (FE) computer simulations supported by experimental testing. Both the strength and serviceability requirements have been established for this lightweight floor plate system. This paper presents some of the research towards the development of HCFPS along with a parametric study to select suitable span lengths.

Nagelschmidtite bioceramics with osteostimulation properties : material chemistry activating osteogenic genes and WNT signalling pathway of human bone marrow stromal cells

Bioactive materials with osteostimulation properties are of great importance to promote osteogenic differentiation of human bone marrow stromal cells (hBMSCs) for potential bone regeneration. We have recently synthesized nagelschmidtite (NAGEL, Ca7Si2P2O16) ceramic powders which showed excellent apatite-mineralization ability. The aim of this study was to investigate the interaction of hBMSCs with NAGEL bioceramic bulks and their ionic extracts, and to explore the osteostimulation properties of NAGEL bioceramics and the possible molecular mechanism. The cell attachment, proliferation, bone-related gene expression (ALP, OPN and OCN) and WNT signalling pathways (WNT3a, FZD6, AXIN2 and CTNNB) of hBMSCs cultured on NAGEL bioceramic disks were systematically studied. We further investigated the biological effects of ionic products from NAGEL powders on cell proliferation and osteogenic differentiation of hBMSCs by culturing cells with NAGEL extracts. Furthermore, the effect of NAGEL bioceramics on the osteogenic differentiation in hBMSCs was also investigated with the addition of cardamonin, a WNT inhibitor. The results showed that NAGEL bioceramic disks supported the attachment and proliferation of hBMSCs, and significantly enhanced the bone-related gene expression and WNT signalling pathway of hBMSCs, compared to conventional beta-tricalcium phosphate (β-TCP) bioceramic disks and blank controls. The ionic products from NAGEL powders also significantly promoted the proliferation, bone and WNT-related gene expression of hBMSCs. It was also identified that NAGEL bioceramics could bypass the action of the WNT inhibitor (10 μM) to stimulate the selected osteogenic genes in hBMSCs. Our results suggest that NAGEL bioceramics possess excellent in vitro osteostimulation properties. The possible mechanism for the osteostimulation may be directly related to the released Si, Ca and P-containing ionic products from NAGEL bioceramics which activate bone-related gene expression and WNT signalling pathway of hBMSCs. The present study suggests that NAGEL bioceramics are a potential bone regeneration material with significant osteostimulation capacity.

A hybrid simulation framework to assess the impact of renewable generators on a distribution network

With an increasing number of small-scale renewable generator installations, distribution network planners are faced with new technical challenges (intermittent load flows, network imbalances…). Then again, these decentralized generators (DGs) present opportunities regarding savings on network infrastructure if installed at strategic locations. How can we consider both of these aspects when building decision tools for planning future distribution networks? This paper presents a simulation framework which combines two modeling techniques: agent-based modeling (ABM) and particle swarm optimization (PSO). ABM is used to represent the different system units of the network accurately and dynamically, simulating over short time-periods. PSO is then used to find the most economical configuration of DGs over longer periods of time. The infrastructure of the framework is introduced, presenting the two modeling techniques and their integration. A case study of Townsville, Australia, is then used to illustrate the platform implementation and the outputs of a simulation.