Constant depth microfluidic networks based on a generalised Murray’s law for Newtonian and power-law fluids

This paper was presented at the 4th Micro and Nano Flows Conference (MNF2014), which was held at University College, London, UK. The conference was organised by Brunel University and supported by the Italian Union of Thermofluiddynamics, IPEM, the Process Intensification Network, the Institution of Mechanical Engineers, the Heat Transfer Society, HEXAG - the Heat Exchange Action Group, and the Energy Institute, ASME Press, LCN London Centre for Nanotechnology, UCL University College London, UCL Engineering, the International NanoScience Community, www.nanopaprika.eu.Microfluidic bifurcating networks of rectangular cross-sectional channels are designed using a novel biomimetic rule, based on Murray’s law. Murray’s principle is extended to consider the flow of power-law fluids in planar geometries (i.e. of constant depth rectangular cross-section) typical of lab-on-a-chip applications. The proposed design offers the ability to control precisely the shear-stress distributions and to predict the flow resistance along the network. We use an in-house code to perform computational fluid dynamics simulations in order to assess the extent of the validity of the proposed design for Newtonian, shear-thinning and shear-thickening fluids under different flow conditions

Applications of stochastic modeling in air traffic management : Methods, challenges and opportunities for solving air traffic problems under uncertainty

In this paper we provide a wide-ranging review of the literature on stochastic modeling applications within aviation, with a particular focus on problems involving demand and capacity management and the mitigation of air traffic congestion. From an operations research perspective, the main techniques of interest include analytical queueing theory, stochastic optimal control, robust optimization and stochastic integer programming. Applications of these techniques include the prediction of operational delays at airports, pre-tactical control of aircraft departure times, dynamic control and allocation of scarce airport resources and various others. We provide a critical review of recent developments in the literature and identify promising research opportunities for stochastic modelers within air traffic management

An Optimisation Framework for Airline Fleet Maintenance Scheduling with Tail Assignment Considerations

Fierce competition between airlines has led to the need of minimising the operating costs while also ensuring quality of service. Given the large proportion of operating costs dedicated to aircraft maintenance, cooperation between airlines and their respective maintenance provider is paramount. In this research, we propose a framework to develop commercially viable and maintenance feasible flight and maintenance schedules. Such framework involves two multi-objective mixed integer linear programming (MMILP) formulations and an iterative algorithm. The first formulation, the airline fleet maintenance scheduling (AMS) with violations, minimises the number of maintenance regulation violations and the number of not airworthy aircraft; subject to limited workshop resources and current maintenance regulations on individual aircraft flying hours. The second formulation, the AMS with tail assignment (TA) allows aircraft to be assigned to different flights. In this case, subject to similar constraints as the first formulation, six lexicographically ordered objective functions are minimised. Namely, the number of violations, maximum resource level, number of tail reassignments, number of maintenance interventions, overall resource usage, and the amount of maintenance required by each aircraft at the end of the planning horizon. The iterative algorithm ensures fast computational times while providing good quality solutions. Additionally, by tracking aircraft and using precise flying hours between maintenance opportunities, we ensure that the aircraft are airworthy at all times. Computational tests on real flight schedules over a 30-day planning horizon show that even with multiple airlines and workshops (16000 flights, 529 aircraft, 8 maintenance workshops) our solution approach can construct near-optimal maintenance schedules within minutes

Conditional tests of marginal homogeneity based on ϕ-divergence test statistics

AbstractIn this work, using the well-known result that symmetry is equivalent to quasi-symmetry and marginal homogeneity simultaneously holding, two families of test statistics based on ϕ-divergence measures are introduced for testing conditional marginal homogeneity assuming that quasi-symmetry holds

An exploratory canonical analysis approach for multinomial populations based on the ϕ\phi-divergence measure

summary:In this paper we consider an exploratory canonical analysis approach for multinomial population based on the $\phi$-divergence measure. We define the restricted minimum $\phi$-divergence estimator, which is seen to be a generalization of the restricted maximum likelihood estimator. This estimator is then used in $\phi$-divergence goodness-of-fit statistics which is the basis of two new families of statistics for solving the problem of selecting the number of significant correlations as well as the appropriateness of the model

Considering spatial and temporal flexibility in optimizing one-way electric carsharing systems

Carsharing is a shared-use vehicle model that allows users to rent cars for short periods of times. There are different types of systems according to their operational properties. In round-trip carsharing systems users are expected to return vehicles to their pickup locations. One-way systems relax this restriction and allows users to return cars to different drop-off locations. In station-based systems, there are designated parking locations to which vehicles should be returned. Free-floating systems relax this restriction and allow users to park vehicles to any legal parking locations within a designated area. In this research we are dealing with operational planning decisions in station-based one-way electric carsharing systems with dynamic relocations. Different than the previous work in literature, we introduce spatial and temporal flexibility to the system by considering multiple pick-up and drop-off times and locations at different prices to increase total profit of the system

Modelling and solving the combined inventory routing problem with risk consideration

This work proposes a multi-objective extension of a real-world inventory routing problem (IRP), a generalisation of the classical vehicle routing problem (VRP) with vendor managed inventory (VMI) replenishment. While many mathematical formulations and solution models already exist, this study incorporates business related and risk considerations that makes it unique. It is known that a significant volume of hazardous materials travels every day. Consideration of risks arising from the transportation of hazardous materials as a criterion for selecting distribution routes could potentially reduce the likelihood of accidents and/or the expected consequences of accident

Choroidal metastases in testicular choriocarcinoma, successful treatment with chemo- and radiotherapy: a case report

<p>Abstract</p> <p>Background</p> <p>Choriocarcinoma is a very rare cause of ocular metastasis. Only 18 male patients have been reported on, 4 of whom survived, but with significant loss of vision.</p> <p>Case presentation</p> <p>A 26-year-old Caucasian man, suffering from testicular choriocarcinoma with pulmonary, cerebral, renal, hepatic and osseous metastases, underwent left radical orchiectomy. While being treated with chemotherapy, he presented with loss of vision in the left eye. Ophthalmoscopy revealed bilateral non-pigmented, hemorrhagic choroidal tumours, compatible with secondary lesions. Continued chemotherapy and stereotactic radiotherapy of the skull and spine lead to full remission with excellent vision, after more than 4 years of follow up.</p> <p>Conclusion</p> <p>Testicular choriocarcinoma is an exceptional cause of choroidal metastasis, potentially asymptomatic and with specific clinical features. Radiotherapy can complement radical orchiectomy and chemotherapy, to achieve full remission and maintain good vision.</p

Incorporating declared capacity uncertainty in optimizing airport slot allocation

Slot allocation is the mechanism used to allocate capacity at congested airports. A number of models have been introduced in the literature aiming to produce airport schedules that optimize the allocation of slot requests to the available airport capacity. A critical parameter affecting the outcome of the slot allocation process is the airport’s declared capacity. Existing airport slot allocation models treat declared capacity as an exogenously defined deterministic parameter. In this presentation we propose a new robust optimization formulation based on the concept of stability radius. The proposed formulation considers endogenously the airport’s declared capacity and expresses it as a function of its throughput. We present results from the application of the proposed approach to a congested airport and we discuss the trade-off between the declared capacity of the airport and the efficiency of the slot allocation process

Investigating the effect of temporal and spatial flexibility on the performance of one-way electric carsharing systems

One-way electric carsharing systems provide an environmentally friendly option for facilitating urban mobility needs. However, the management of one-way electric carsharing systems presents operational challenges stemming from the need to relocate cars in order to strike an optimum balance between demand and supply. As a result, the cost associated with vehicle relocation operations represents a significant proportion of the total operating cost. In the context of electric carsharing systems, the problem of vehicle relocation is further exacerbated by the car battery charging requirements. The introduction of temporal and spatial flexibility regarding the pick-up and drop-off of vehicles provides the means of improving the efficiency of one-way electric carsharing systems. However, the literature currently lacks models that can be used to investigate the effect of temporal and spatial flexibility on the performance of one-way electric carsharing systems. In this paper, we are introducing an integrated modeling and solution framework for investigating the effect of temporal and/or spatial flexibility, and different options for processing trip requests to the profitability and utilization of one-way electric carsharing systems. The application of the proposed framework to a realistic size system suggests that spatial flexibility has a stronger effect on the system performance than temporal flexibility. Furthermore, both spatial and temporal flexibility can increase the profitability of the system by serving more customers with fewer vehicle relocation needs