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  • Finite element analysis of concrete filled lean duplex stainless steel columns

    Lam, Dennis; Yang, Jie; Dai, Xianghe (2019)
    In recent years, a new low nickel content stainless steel (EN 1.4162) commonly referred as ‘lean duplex stainless steel’ has been developed, which has over two times the tensile strength of the more familiar austenitic stainless steel but at approximately half the cost. This paper presents the finite element analysis of concrete filled lean duplex stainless steel columns subjected to concentric axial compression. To predict the performance of this form of concrete filled composite columns, a finite element model was developed and finite element analyses were conducted. The finite element model was validated through comparisons of the results obtained from the experimental study. A parametric study was conducted to examine the effect of various parameters such as section size, wall thickness, infill concrete strength, etc. on the overall behaviour and compressive resistance of this form of composite columns. Through both experimental and numerical studies, the merits of using lean duplex stainless steel hollow sections in concrete filled composite columns were highlighted. In addition, a new formula based on the Eurocode 4 was proposed to predict the cross-section capacity of the concrete filled lean duplex stainless steel composite columns subjected to axial compression.
  • Angiography simulation and planning using a multi-fluid approach

    Huang, D.; Tang, P.; Tang, W.; Wan, Tao Ruan (2019-01-22)
    Angiography is a minimally invasive diagnostic procedure in endovascular interventions. Training interventional procedures is a big challenge, due to the complexity of the procedures with the changes of measurement and visualization in blood flow rate, volume, and image contrast. In this paper, we present a novel virtual reality-based 3D interactive training platform for angiography procedure training. We propose a multi-fluid flow approach with a novel corresponding non-slip boundary condition to simulate the effect of diffusion between the blood and contrast media. A novel syringe device tool is also designed as an add-on hardware to the 3D software simulation system to model haptics through real physical interactions to enhance the realism of the simulation-based training. Experimental results show that the system can simulate realistic blood flow in complex blood vessel structures. The results are validated by visual comparisons between real angiography images and simulations. By combining the proposed software and hardware, our system is applicable and scalable to many interventional radiology procedures. Finally, we have tested the system with clinicians to assess its efficacy for virtual reality-based medical training.
  • Structure and functions of the ventral tube of the clover springtail Sminthurus viridis (Collembola Sminthuridae)

    Chen, C-G.; Chen, T.; Hua, B-Z.; Wan, Tao Ruan (2019-01-29)
    Springtails (Collembola) are unique in Hexapoda for bearing a ventral tube (collophore) on the first abdominal segment. Although numerous studies have been conducted on the functions of the ventral tube, its fine structure has not been thoroughly elucidated to date. In this paper, we observed the jumping behavior of the clover springtail Sminthurus viridis (Linnaeus, 1758) and dissected the ventral tube using light microscopy to elucidate the fine structure and the possible function of the ventral tube. The results show that a pair of eversible vesicles can be extended from the apical opening of the ventral tube. The eversible vesicles are furnished with numerous small papillae, and can be divided into a basal part and a distal part. The eversible vesicles have a central lumen connected to the tiny papillae and leading to the body cavity. The eversible vesicles can reach any part of the body, and may serve as following functions: (a) absorbing moisture; (b) uptaking water; (c) cleaning the body surface; and (d) fastening the body on a smooth surface.
  • Testing of a Full-Scale Composite Floor Plate

    Lam, Dennis; Dai, Xianghe; Sheehan, Therese (2019)
    A full-scale composite floor plate was tested to investigate the flexural behavior and in-plane effects of the floor slab in a grillage of composite beams that reduces the tendency for longitudinal splitting of the concrete slab along the line of the primary beams. This is important in cases where the steel decking is discontinuous when it is orientated parallel to the beams. In this case, it is important to demonstrate that the amount of transverse reinforcement required to transfer local forces from the shear connectors can be reduced relative to the requirements of Eurocode 4. The mechanism under study involved in-plane compression forces being developed in the slab due to the restraining action of the floor plate, which was held in position by the peripheral composite beams; while the secondary beams acted as transverse ties to resist the forces in the floor plate that would otherwise lead to splitting of the slab along the line of the primary beams. The tendency for cracking along the center line of the primary beam and at the peripheral beams was closely monitored. This is the first large floor plate test that has been carried out under laboratory conditions since the Cardington tests in the early 1990s, although those tests were not carried out to failure. This floor plate test was designed so that the longitudinal force transferred by the primary beams was relatively high (i.e., it was designed for full shear connection), but the transverse reinforcement was taken as the minimum of 0.2% of the concrete area. The test confirmed that the primary beams reached their plastic bending resistance despite the discontinuous decking and transverse reinforcement at the minimum percentage given in Eurocode 4. Based on this test, a reduction factor due to shear connectors at edge beams without U-bars is proposed.
  • Cost evaluation and optimisation of hybrid multi effect distillation and reverse osmosis system for seawater desalination

    Al-Obaidi, M.A.; Filippini, G.; Manenti, F.; Mujtaba, Iqbal M. (2019-04-15)
    In this research, the effect of operating parameters on the fresh water production cost of hybrid Multi Effect Distillation (MED) and Reverse Osmosis (RO) system is investigated. To achieve this, an earlier comprehensive model developed by the authors for MED + RO system is combined with two full-scale cost models of MED and RO processes collected from the literature. Using the economic model, the variation of the overall fresh water cost with respect to some operating conditions, namely steam temperature and steam flow rate for the MED process and inlet pressure and flow rate for the RO process, is accurately investigated. Then, the hybrid process model is incorporated into a single-objective non-linear optimisation framework to minimise the fresh water cost by finding the optimal values of the above operating conditions. The optimisation results confirm the economic feasibility of the proposed hybrid seawater desalination plant.
  • Ranking strategies to support toxicity prediction: a case study on potential lxr binders

    Palczewska, Anna Maria; Kovarich, S.; Ciacci, A.; Fioravanzo, E.; Bassan, A.; Neagu, Daniel (2019)
    The current paradigm of toxicity testing is set within a framework of Mode-of-Action (MoA)/Adverse Outcome Pathway (AOP) investigations, where novel methodologies alternative to animal testing play a crucial role, and allow to consider causal links between molecular initiating events (MIEs), further key events and an adverse outcome. In silico (computational) models are developed to support toxicity assessment within the MoA/AOP framework. This paper focuses on the evaluation of potential binding to the Liver X Receptor (LXR), as this has been identified among the MIEs leading to liver steatosis within an AOP framework addressing repeated dose and target-organ toxicity. The objective of this study was the development of a priority setting strategy, by means of in silico approaches and chemometric tools, to allow for the screening and ranking of chemicals according to their toxicity potential. As a case study, the present paper outlines the methodologies and procedures that have been developed in the context of the COSMOS/cosmetics safety assessment project [4], which developed computational methods in view of supporting cosmetics safety assessment, to rank chemicals based on their potential binding to LXR. Chemicals are ranked based on molecular and QSAR modelling outcomes. The contribution in this paper is threefold: the QSAR model for LXR dataset, an application of molecular modeling approaches, which have been developed and optimized for drug discovery, in the context of toxicology, and finally ranking chemicals based on diverse modelling outcomes. The novelty in this paper consists of the employment of linear (logistic regression) and non-linear (Random Forest) models in the context of ranking chemicals. The results show that these methods can be successfully applied for prioritization of compounds of major concern for potential liver toxicity, and that they perform better than the ranking methods reported in the literature to date (such as total ordering or data fusion).
  • Recent Progress in the Design of 4G/5G Reconfigurable Filters

    Al-Yasir, Yasir; Ojaroudi Parchin, Naser; Abd-Alhameed, Raed A.; Abdulkhaleq, Ahmed M.; Noras, James M. (2019-01-20)
    Currently, several microwave filter designs contend for use in wireless communications. Among various microstrip filter designs, the reconfigurable planar filter presents more advantages and better prospects for communication applications, being compact in size, light-weight and cost-effective. Tuneable microwave filters can reduce the number of switches between electronic components. This paper presents a review of recent reconfigurable microwave filter designs, specifically on current advances in tuneable filters that involve high-quality factor resonator filters to control frequency, bandwidth and selectivity. The most important materials required for this field are also highlighted and surveyed. In addition, the main references for several types of tuneable microstrip filters are reported, especially related to new design technologies. Topics surveyed include microwave and millimetre wave designs for 4G and 5G applications, which use varactors and MEMSs technologies.
  • Probabilistic inequalities and measurements in bipartite systems

    Vourdas, Apostolos (2019-01)
    Various inequalities (Boole inequality, Chung–Erdös inequality, Frechet inequality) for Kolmogorov (classical) probabilities are considered. Quantum counterparts of these inequalities are introduced, which have an extra 'quantum correction' term, and which hold for all quantum states. When certain sufficient conditions are satisfied, the quantum correction term is zero, and the classical version of these inequalities holds for all states. But in general, the classical version of these inequalities is violated by some of the quantum states. For example in bipartite systems, classical Boole inequalities hold for all rank one (factorizable) states, and are violated by some rank two (entangled) states. A logical approach to CHSH inequalities (which are related to the Frechet inequalities), is studied in this context. It is shown that CHSH inequalities hold for all rank one (factorizable) states, and are violated by some rank two (entangled) states. The reduction of the rank of a pure state by a quantum measurement with both orthogonal and coherent projectors, is studied. Bounds for the average rank reduction are given.
  • Impact resistance of deflection-hardening fiber reinforced concretes with different mixture parameters

    Banyhussan, Q.S.; Yildirim, G.; Anil, O.; Erdem, R.T.; Ashour, Ashraf F.; Sahmaran, M. (2019)
    The impact behavior of deflection-hardening High Performance Fiber Reinforced Cementitious Concretes (HPFRCs) was evaluated herein. During the preparation of HPFRCs, fiber type and amount, fly ash to Portland cement ratio and aggregate to binder ratio were taken into consideration. HPFRC beams were tested for impact resistance using free-fall drop-weight test. Acceleration, displacement and impact load vs. time graphs were constructed and their relationship to the proposed mixture parameters were evaluated. The paper also aims to present and verify a nonlinear finite element analysis, employing the incremental nonlinear dynamic analysis, concrete damage plasticity model and contact surface between the dropped hammer and test specimen available in ABAQUS. The proposed modelling provides extensive and accurate data on structural behavior, including acceleration, displacement profiles and residual displacement results. Experimental results which are further confirmed by numerical studies show that impact resistance of HPFRC mixtures can be significantly improved by a proper mixture proportioning. In the presence of high amounts of coarse aggregates, fly ash and increased volume of hybrid fibers, impact resistance of fiberless reference specimens can be modified in a way to exhibit relatively smaller displacement results after impact loading without risking the basic mechanical properties and deflection-hardening response with multiple cracking.
  • Long-term drying shrinkage of self-compacting concrete: experimental and analytical investigations

    Abdalhmid, Jamila M.; Ashour, Ashraf F.; Sheehan, Therese (2019-03-30)
    The present study investigated long-term drying shrinkage strains of self-compacting concrete (SCCs). For all SCCs mixes, Portland cement was replaced with 0–60% of fly ash (FA), fine and course aggregates were kept constant with 890 kg/m3 and 780 kg/m3, respectively. Two different water binder ratios of 0.44 and 0.33 were examined for both SCCs and normal concrete (NCs). Fresh properties of SCCs such as filling ability, passing ability, viscosity and resistance to segregation and hardened properties such as compressive and flexural strengths, water absorption and density of SCCs and NCs were also determined. Experimental results of drying shrinkage were compared to five existing models, namely the ACI 209R-92 model, BSEN-92 model, ACI 209R-92 (Huo) model, B3 model, and GL2000. To assess the quality of predictive models, the influence of various parameters (compressive strength, cement content, water content and relative humidity) effecting on the drying shrinkage strain as considered by the models are studied. The results showed that, using up to 60% of FA as cement replacement can produce SCC with a compressive strength as high as 30 MPa and low drying shrinkage strain. SCCs long-term drying shrinkage from 356 to 1000 days was higher than NCs. ACI 209R-92 model provided a better prediction of drying shrinkage compared with the other models.
  • Experimental investigation of bond behaviour of two common GFRP bar types in high-strength concrete

    Saleh, N.; Ashour, Ashraf F.; Lam, Dennis; Sheehan, Therese (2019-03-20)
    Although several research studies have been conducted on investigating the bond stress – slip behaviour of Glass-Fibre Reinforced Polymer (GFRP) bars embedded in high strength concrete (HSC) using a pull-out method, there is no published work on the bond behaviour of GFRP bars embedded in high strength concrete using a hinged beam. This paper presents the experimental work consisted of testing 28 hinged beams prepared according to RILEM specifications. The investigation of bond performance of GFRP bars in HSC was carried out by analysing the effect of the following parameters: bar diameter (9.5, 12.7 and 15.9 mm), embedment length (5 and 10 times bar diameter), surface configuration (helical wrapping with slight sand coating (HW-SC) and sand coating (SC)) and bar location (top and bottom). Four hinged beams reinforced with 16 mm steel bar were also tested for comparison purposes. The majority of beam specimens failed by pull-out. Visual inspection of the test specimens showed that the bond failure of GFRP (HW-SC) bars usually occurred owing to the bar surface damage, while the bond failure of GFRP (SC) bars was caused due to the detachment of sand coating. The GFRP bars with helical wrapping and sand coated surface configurations showed different bond behaviour and it was found that the bond performance of the sand coated surface was better than that of the helically wrapped surface. Bond strength reduced as the embedment length and bar diameter increased. It was also observed that the bond strength for the bottom bars was higher than that of the top bars. The bond strength was compared against the prediction methods given in ACI-440.1R, CSA-S806 and CSA-S6 codes. All design guidelines underestimated the bond strength of both GFRP re-bars embedded in high strength concrete.
  • Analysis of unreinforced and reinforced shallow piled embankments subject to cyclic loading

    Aqoub, K.; Mohamed, Mostafa H.A.; Sheehan, Therese (2019)
    Reinforced piled embankment technique is becoming increasingly utilised for the construction over soft grounds due to its efficiency on reducing potential settlement, speed of construction and associated cost. Most of previous studies focused on developing understanding for the behaviour of thick embankments that are loaded with a static surcharge load. Data for the behaviour of shallow piled embankments under cyclic loadings are scarce. In this study, an experimental programme was undertaken using a fully instrumented testing rig to generate data and improve our understanding for the behaviour of unreinforced and reinforced shallow piled embankments subject to monotonic and cyclic loadings that were applied over a predetermined area of the embankment. The experimental results showed that collapse of soil arching is imminent and occurs during the first few cycles of load. However, regain of strength and recovery of the arching effect was observable during further stages of cyclic loadings due to densification of the embankment material and deformation of the soft subsoil. Inclusion of reinforcement layers was found to enhance the performance of load transfer mechanisms by concentrating stresses on pile caps. The results clearly showed a significant reduction in surface settlement, soft subsoil settlement and heaving with increasing the number of reinforcement layers.
  • Computational complexity analysis of decision tree algorithms

    Sani, Habiba M.; Lei, Ci; Neagu, Daniel (2018)
    Decision tree is a simple but powerful learning technique that is considered as one of the famous learning algorithms that have been successfully used in practice for various classification tasks. They have the advantage of producing a comprehensible classification model with satisfactory accuracy levels in several application domains. In recent years, the volume of data available for learning is dramatically increasing. As a result, many application domains are faced with a large amount of data thereby posing a major bottleneck on the computability of learning techniques. There are different implementations of the decision tree using different techniques. In this paper, we theoretically and experimentally study and compare the computational power of the most common classical top-down decision tree algorithms (C4.5 and CART). This work can serve as part of review work to analyse the computational complexity of the existing decision tree classifier algorithm to gain understanding of the operational steps with the aim of optimizing the learning algorithm for large datasets.
  • Agent based micro-simulation of a passenger rail system using customer survey data and an activity based approach

    Makinde, O.; Neagu, Daniel; Gheorghe, Marian (2019)
    Passenger rail overcrowding is fast becoming a problem in major cities worldwide. This problem therefore calls for efficient, cheap and prompt solutions and policies, which would in turn require accurate modelling tools to effectively forecast the impact of transit demand management policies. To do this, we developed an agent-based model of a particular passenger rail system using an activity based simulation approach to predict the impact of public transport demand management pricing strategies. Our agent population was created using a customer/passenger mobility survey dataset. We modelled the temporal flexibility of passengers, based on patterns observed in the departure and arrival behavior of real travelers. Our model was validated using real life passenger count data from the passenger rail transit company, after which we evaluated the use of peak demand management instruments such as ticketing fares strategies, to influence peak demand of a passenger rail transport system. Our results suggest that agent-based simulation is effective in predicting passenger behavior for a transportation system, and can be used in predicting the impact of demand management policies.
  • Classification of heterogeneous data based on data type impact of similarity

    Ali, N.; Neagu, Daniel; Trundle, Paul R. (2019)
    Real-world datasets are increasingly heterogeneous, showing a mixture of numerical, categorical and other feature types. The main challenge for mining heterogeneous datasets is how to deal with heterogeneity present in the dataset records. Although some existing classifiers (such as decision trees) can handle heterogeneous data in specific circumstances, the performance of such models may be still improved, because heterogeneity involves specific adjustments to similarity measurements and calculations. Moreover, heterogeneous data is still treated inconsistently and in ad-hoc manner. In this paper, we study the problem of heterogeneous data classification: our purpose is to use heterogeneity as a positive feature of the data classification effort by using consistently the similarity between data objects. We address the heterogeneity issue by studying the impact of mixing data types in the calculation of data objects’ similarity. To reach our goal, we propose an algorithm to divide the initial data records based on pairwise similarity for classification subtasks with the aim to increase the quality of the data subsets and apply specialized classifier models on them. The performance of the proposed approach is evaluated on 10 publicly available heterogeneous data sets. The results show that the models achieve better performance for heterogeneous datasets when using the proposed similarity process.
  • Standardising the Capture and Processing of Custody Images

    Jilani, Shelina K.; Ugail, Hassan; Cole, S.; Logan, Andrew J. (2018)
    Custody images are a standard feature of everyday Policing and are commonly used during investigative work to establish whether the perpetrator and the suspect are the same. The process of identification relies heavily on the quality of a custody image because a low-quality image may mask identifying features. With an increased demand for high quality facial images and the requirement to integrate biometrics and machine vision technology to the field of face identification, this research presents an innovative image capture and biometric recording system called the Halo. Halo is a pioneering system which (1) uses machine vision cameras to capture high quality facial images from 8 planes of view (including CCTV simulated), (2) uses high quality video technology to record identification parades and, (3) records biometric data from the face by using a Convolutional Neural Networks (CNN) based algorithm, which is a supervised machine learning technique. Results based on our preliminary experiments have concluded a 100% facial recognition rate for layer 34 within the VGG-Face model. These results are significant for the sector of forensic science, especially digital image capture and facial identification as they highlight the importance of image quality and demonstrates the complementing nature a robust machine learning algorithm has on an everyday Policing process.
  • Towards Lattice-Boltzmann modelling of unconfined gas mixing in anaerobic digestion

    Dapelo, Davide; Trunk, R.; Krause, M.J.; Bridgeman, John (2019-02-15)
    A novel Lattice-Boltzmann model to simulate gas mixing in anaerobic digestion is developed and described. For the first time, Euler–Lagrange multiphase, non-Newtonian and turbulence modelling are applied jontly with a novel hybrid boundary condition. The model is validated in a laboratory-scale framework and flow patterns are assessed through Particle Imaging Velocimetry (PIV) and innovative Positron-Emission Particle Tracking (PEPT). The model is shown to reproduce the experimental flow patterns with fidelity in both qualitative and quantitative terms. The model opens up a new approach to computational modelling of the complex multiphase flow in anaerobic digesters and offers specific advantages, such as computational efficiency, over an analogous Euler-Lagrange finite-volume computational fluid dynamics approach.
  • Synergistic toughening and compatibilisation effect of Poly(butylene succinate) in PLA/poly-caprolactone blends

    Kassos, Nikolaos; Kelly, Adrian L.; Gough, Timothy D.; Gill, A.A. (2019-03)
    Binary and ternary blends of a polylactic acid matrix with polycaprolactone (PCL) and polybutylene succinate (PBS) were produced by twin screw extrusion, containing up to 30wt% loading. Mechanical, thermal and rheological characterisation techniques were used to quantify properties of the different blend formulations and miscibility was investigated using scanning electron microscopy. PCL is known to act as an impact modifier in PLA but to cause a corresponding reduction in strength. Results showed that addition of both PBS and PCL seperatly caused a reduction in melt viscosity, elastic modulus and tensile strength, but an increase in impact strength and strain at break. Analysis of morphology suggested that immiscibility was evident, particularly at higher PCL and PBS loadings. Results indicated that incorporation of a small loading of PBS had a synergistic effect on the PLA-PCL blend properties. Miscibility was improved and enhanced mechanical properties were observed for a ternary blend containing 5wt% of both PBS and PCL compared to blends containing 10% of each polymer alone.
  • Turbulent Rectangular Compound Open Channel Flow Study Using Multi-Zonal Approach

    Pu, Jaan H. (2019)
    In this paper, an improved Shiono-Knight model (SKM) has been proposed to calculate the rectangular compound open channel flows by considering a Multi-Zonal (MZ) approach in modelling turbulence and secondary flows across lateral flow direction. This is an effort to represent natural flows with compound shape more closely. The proposed model improves the estimation of secondary flow by original SKM model to increase the accuracy of depthaveraged velocity profile solution formed within the transitional region between different sections (i.e. between main-channel and floodplain) of compound channel. This proposed MZ model works by sectioning intermediate zones between floodplain and main-channel for running computation in order to improve the modelling accuracy. The modelling results have been validated using the experimental data by national UK Flood Channel Facility (FCF). It has been proven to work reasonably well to model secondary flows within the investigated compound channel flow cases and hence produce better representation to their flow lateral velocity profile.
  • Failure Analysis Modelling in an Infrastructure as a Service (Iaas) Environment

    Mohammed, Bashir; Modu, Babagana; Maiyama, Kabiru M.; Ugail, Hassan; Awan, Irfan U.; Kiran, M. (2018)
    Failure Prediction has long known to be a challenging problem. With the evolving trend of technology and growing complexity of high-performance cloud data centre infrastructure, focusing on failure becomes very vital particularly when designing systems for the next generation. The traditional runtime fault-tolerance (FT) techniques such as data replication and periodic check-pointing are not very effective to handle the current state of the art emerging computing systems. This has necessitated the urgent need for a robust system with an in-depth understanding of system and component failures as well as the ability to predict accurate potential future system failures. In this paper, we studied data in-production-faults recorded within a five years period from the National Energy Research Scientific computing centre (NERSC). Using the data collected from the Computer Failure Data Repository (CFDR), we developed an effective failure prediction model focusing on high-performance cloud data centre infrastructure. Using the Auto-Regressive Moving Average (ARMA), our model was able to predict potential future failures in the system. Our results also show a failure prediction accuracy of 95%, which is good.

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