Dynamics of transformation and fragmentation of composite liquid nano-particles

Recent research on particle size distributions and particle concentrations near a busy road cannot be explained by the conventional mechanisms for particle evolution of combustion aerosols. Specifically they appear to be inadequate to explain the experimental observations of particle transformation and the evolution of the total number concentration. This resulted in the development of a new mechanism based on their thermal fragmentation, for the evolution of combustion aerosol nano-particles. A complex and comprehensive pattern of evolution of combustion aerosols, involving particle fragmentation, was then proposed and justified. In that model it was suggested that thermal fragmentation occurs in aggregates of primary particles each of which contains a solid graphite/carbon core surrounded by volatile molecules bonded to the core by strong covalent bonds. Due to the presence of strong covalent bonds between the core and the volatile (frill) molecules, such primary composite particles can be regarded as solid, despite the presence of significant (possibly, dominant) volatile component. Fragmentation occurs when weak van der Waals forces between such primary particles are overcome by their thermal (Brownian) motion. In this work, the accepted concept of thermal fragmentation is advanced to determine whether fragmentation is likely in liquid composite nano-particles. It has been demonstrated that at least at some stages of evolution, combustion aerosols contain a large number of composite liquid particles containing presumably several components such as water, oil, volatile compounds, and minerals. It is possible that such composite liquid particles may also experience thermal fragmentation and thus contribute to, for example, the evolution of the total number concentration as a function of distance from the source. Therefore, the aim of this project is to examine theoretically the possibility of thermal fragmentation of composite liquid nano-particles consisting of immiscible liquid v components. The specific focus is on ternary systems which include two immiscible liquid droplets surrounded by another medium (e.g., air). The analysis shows that three different structures are possible, the complete encapsulation of one liquid by the other, partial encapsulation of the two liquids in a composite particle, and the two droplets separated from each other. The probability of thermal fragmentation of two coagulated liquid droplets is discussed and examined for different volumes of the immiscible fluids in a composite liquid particle and their surface and interfacial tensions through the determination of the Gibbs free energy difference between the coagulated and fragmented states, and comparison of this energy difference with the typical thermal energy kT. The analysis reveals that fragmentation was found to be much more likely for a partially encapsulated particle than a completely encapsulated particle. In particular, it was found that thermal fragmentation was much more likely when the volume ratio of the two liquid droplets that constitute the composite particle are very different. Conversely, when the two liquid droplets are of similar volumes, the probability of thermal fragmentation is small. It is also demonstrated that the Gibbs free energy difference between the coagulated and fragmented states is not the only important factor determining the probability of thermal fragmentation of composite liquid particles. The second essential factor is the actual structure of the composite particle. It is shown that the probability of thermal fragmentation is also strongly dependent on the distance that each of the liquid droplets should travel to reach the fragmented state. In particular, if this distance is larger than the mean free path for the considered droplets in the air, the probability of thermal fragmentation should be negligible. In particular, it follows form here that fragmentation of the composite particle in the state with complete encapsulation is highly unlikely because of the larger distance that the two droplets must travel in order to separate. The analysis of composite liquid particles with the interfacial parameters that are expected in combustion aerosols demonstrates that thermal fragmentation of these vi particles may occur, and this mechanism may play a role in the evolution of combustion aerosols. Conditions for thermal fragmentation to play a significant role (for aerosol particles other than those from motor vehicle exhaust) are determined and examined theoretically. Conditions for spontaneous transformation between the states of composite particles with complete and partial encapsulation are also examined, demonstrating the possibility of such transformation in combustion aerosols. Indeed it was shown that for some typical components found in aerosols that transformation could take place on time scales less than 20 s. The analysis showed that factors that influenced surface and interfacial tension played an important role in this transformation process. It is suggested that such transformation may, for example, result in a delayed evaporation of composite particles with significant water component, leading to observable effects in evolution of combustion aerosols (including possible local humidity maximums near a source, such as a busy road). The obtained results will be important for further development and understanding of aerosol physics and technologies, including combustion aerosols and their evolution near a source.

Infrastructure Sustainability : Damage Assessment in Multiple-Girder Composite Bridges Using Vibration Characteristics

Assessing the structural health state of urban infrastructure is crucial in terms of infrastructure sustainability. This chapter uses dynamic computer simulation techniques to apply a procedure using vibration-based methods for damage assessment in multiple-girder composite bridges. In addition to changes in natural frequencies, this multi-criteria procedure incorporates two methods, namely, the modal flexibility and the modal strain energy method. Using the numerically simulated modal data obtained through finite element analysis software, algorithms based on modal flexibility and modal strain energy change, before and after damage, are obtained and used as the indices for the assessment of structural health state. The feasibility and capability of the approach is demonstrated through numerical studies of a proposed structure with six damage scenarios. It is concluded that the modal strain energy method is capable of application to multiple-girder composite bridges, as evidenced through the example treated in this chapter.

Did the goodwill accounting standard impose material economic consequences on Australian acquirers?

This research explores the empirical association between takeover bid premium and acquired (purchased) goodwill, and tests whether the strength of the association changes after the passage of approved accounting standard AASB 1013 in Australia in 1988. AASB 1013 mandated capitalization and amortization of acquired goodwill to the income statement over a maximum period of 20 years. We use regressions to assess how the association between bid premium and acquired goodwill varies in the pre-AASB and post-AASB 1013 periods after controlling for confounding factors. Our results show that reducing the variety of accounting policy options available to bidder management after an acquisition results in a systematic reduction in the strength of the association between premium and goodwill.

Combined marrow stromal cell-sheet techniques and high-strength biodegradable composite scaffolds for engineered functional bone grafts

In this study, cell sheets comprising multilayered porcine bone marrow stromal cells (BMSC) were assembled with fully interconnected scaffolds made from medical-grade polycaprolactone–calcium phosphate (mPCL–CaP), for the engineering of structural and functional bone grafts. The BMSC sheets were harvested from culture flasks and wrapped around pre-seeded composite scaffolds. The layered cell sheets integrated well with the scaffold/cell construct and remained viable, with mineralized nodules visible both inside and outside the scaffold for up to 8 weeks culture. Cells within the constructs underwent classical in vitro osteogenic differentiation with the associated elevation of alkaline phosphatase activity and bone-related protein expression. In vivo, two sets of cell-sheet-scaffold/cell constructs were transplanted under the skin of nude rats. The first set of constructs (554mm3) were assembled with BMSC sheets and cultured for 8 weeks before implantation. The second set of constructs (10104mm3) was implanted immediately after assembly with BMSC sheets, with no further in vitro culture. For both groups, neo cortical and well-vascularised cancellous bone were formed within the constructs with up to 40% bone volume. Histological and immunohistochemical examination revealed that neo bone tissue formed from the pool of seeded BMSC and the bone formation followed predominantly an endochondral pathway, with woven bone matrix subsequently maturing into fully mineralized compact bone; exhibiting the histological markers of native bone. These findings demonstrate that large bone tissues similar to native bone can be regenerated utilizing BMSC sheet techniques in conjunction with composite scaffolds whose structures are optimized from a mechanical, nutrient transport and vascularization perspective.

A penalty-based genetic algorithm for the composite SaaS placement problem in the cloud

Cloud computing is a latest new computing paradigm where applications, data and IT services are provided over the Internet. Cloud computing has become a main medium for Software as a Service (SaaS) providers to host their SaaS as it can provide the scalability a SaaS requires. The challenges in the composite SaaS placement process rely on several factors including the large size of the Cloud network, SaaS competing resource requirements, SaaS interactions between its components and SaaS interactions with its data components. However, existing applications’ placement methods in data centres are not concerned with the placement of the component’s data. In addition, a Cloud network is much larger than data center networks that have been discussed in existing studies. This paper proposes a penalty-based genetic algorithm (GA) to the composite SaaS placement problem in the Cloud. We believe this is the first attempt to the SaaS placement with its data in Cloud provider’s servers. Experimental results demonstrate the feasibility and the scalability of the GA.

A hybrid genetic algorithm for the optimal constrained web service selection problem in web service composition

Web service composition is an important problem in web service based systems. It is about how to build a new value-added web service using existing web services. A web service may have many implementations, all of which have the same functionality, but may have different QoS values. Thus, a significant research problem in web service composition is how to select a web service implementation for each of the web services such that the composite web service gives the best overall performance. This is so-called optimal web service selection problem. There may be mutual constraints between some web service implementations. Sometimes when an implementation is selected for one web service, a particular implementation for another web service must be selected. This is so called dependency constraint. Sometimes when an implementation for one web service is selected, a set of implementations for another web service must be excluded in the web service composition. This is so called conflict constraint. Thus, the optimal web service selection is a typical constrained ombinatorial optimization problem from the computational point of view. This paper proposes a new hybrid genetic algorithm for the optimal web service selection problem. The hybrid genetic algorithm has been implemented and evaluated. The evaluation results have shown that the hybrid genetic algorithm outperforms other two existing genetic algorithms when the number of web services and the number of constraints are large.

Predicting active material utilisation in LiFePO4 electrodes using a multi-scale mathematical model

A mathematical model is developed to simulate the discharge of a LiFePO4 cathode. This model contains 3 size scales, which match with experimental observations present in the literature on the multi-scale nature of LiFePO4 material. A shrinking-core is used on the smallest scale to represent the phase-transition of LiFePO4 during discharge. The model is then validated against existing experimental data and this validated model is then used to investigate parameters that influence active material utilisation. Specifically the size and composition of agglomerates of LiFePO4 crystals is discussed, and we investigate and quantify the relative effects that the ionic and electronic conductivities within the oxide have on oxide utilisation. We find that agglomerates of crystals can be tolerated under low discharge rates. The role of the electrolyte in limiting (cathodic) discharge is also discussed, and we show that electrolyte transport does limit performance at high discharge rates, confirming the conclusions of recent literature.

Deposition of hydroxyapatite and calcium oxalate dihydrate on a heat exchanger tube

Most studies on the characterisation of deposits on heat exchangers have been based on bulk analysis, neglecting the fine structural features and the compositional profiles of layered deposits. Attempts have been made to fully characterise a fouled stainless steel tube obtained from a quintuple Roberts evaporator of a sugar factory using X-ray diffraction and scanning electron microscopy techniques. The deposit contains three layers at the bottom of the tube and two layers on the other sections and is composed of hydroxyapatite, calcium oxalate dihydrate and an amorphous material. The proportions of these phases varied along the tube height. Energy-dispersive spectroscopy and XRD analysis on the surfaces of the outermost and innermost layers showed that hydroxyapatite was the major phase attached to the tube wall, while calcium oxalate dihydrate (with pits and voids) was the major phase on the juice side. Elemental mapping of the cross-sections of the deposit revealed the presence of a mineral, Si-Mg-Al-Fe-O, which is probably a silicate mineral. Reasons for the defects in the oxalate crystal surfaces, the differences in the crystal size distribution from bottom to the top of the tube and the composite fouling process have been postulated.

Partitioning composite web services for decentralized execution using a genetic algorithm

Composite web services comprise several component web services. When a composite web service is executed centrally, a single web service engine is responsible for coordinating the execution of the components, which may create a bottleneck and degrade the overall throughput of the composite service when there are a large number of service requests. Potentially this problem can be handled by decentralizing execution of the composite web service, but this raises the issue of how to partition a composite service into groups of component services such that each group can be orchestrated by its own execution engine while ensuring acceptable overall throughput of the composite service. Here we present a novel penalty-based genetic algorithm to solve the composite web service partitioning problem. Empirical results show that our new algorithm outperforms existing heuristic-based solutions.

QoS-oriented sesource allocation and scheduling of multiple composite web services in a hybrid cloud using a random-key genetic algorithm

In cloud computing resource allocation and scheduling of multiple composite web services is an important challenge. This is especially so in a hybrid cloud where there may be some free resources available from private clouds but some fee-paying resources from public clouds. Meeting this challenge involves two classical computational problems. One is assigning resources to each of the tasks in the composite web service. The other is scheduling the allocated resources when each resource may be used by more than one task and may be needed at different points of time. In addition, we must consider Quality-of-Service issues, such as execution time and running costs. Existing approaches to resource allocation and scheduling in public clouds and grid computing are not applicable to this new problem. This paper presents a random-key genetic algorithm that solves new resource allocation and scheduling problem. Experimental results demonstrate the effectiveness and scalability of the algorithm.

A cooperative coevolutionary algorithm for the composite SaaS Placement Problem in the Cloud

Cloud computing has become a main medium for Software as a Service (SaaS) hosting as it can provide the scalability a SaaS requires. One of the challenges in hosting the SaaS is the placement process where the placement has to consider SaaS interactions between its components and SaaS interactions with its data components. A previous research has tackled this problem using a classical genetic algorithm (GA) approach. This paper proposes a cooperative coevolutionary algorithm (CCEA) approach. The CCEA has been implemented and evaluated and the result has shown that the CCEA has produced higher quality solutions compared to the GA.