Evolution equation for a model of surface relaxation in complex networks

In this paper we derive analytically the evolution equation of the interface for a model of surface growth with relaxation to the minimum (SRM) in complex networks. We were inspired by the disagreement between the scaling results of the steady state of the fluctuations between the discrete SRM model and the Edward-Wilkinson process found in scale-free networks with degree distribution $P(k) \sim k^{-\lambda}$ for $\lambda <3$ [Pastore y Piontti {\it et al.}, Phys. Rev. E {\bf 76}, 046117 (2007)]. Even though for Euclidean lattices the evolution equation is linear, we find that in complex heterogeneous networks non-linear terms appear due to the heterogeneity and the lack of symmetry of the network; they produce a logarithmic divergency of the saturation roughness with the system size as found by Pastore y Piontti {\it et al.} for $\lambda <3$.Comment: 9 pages, 2 figure

Fluid flow and heat transfer analysis of TEFC machine end regions using more realistic end-winding geometry

In this paper a typical small low voltage TEFC motor (output power ~10 kW) has been studied using computational fluid dynamics. The complexity of the end winding geometries, often consisting of several insulated copper strands bound together, provides a challenge to the modelling and analysis of heat transfer and fluid flow phenomena occurring in the end region which typically is an area of most interest for thermal management. Approximated geometries are usually employed in order to model the end windings to reduce analysis time and cost. This paper presents a comparison of two cases, a typical simplified geometry and a more realistic geometry of end windings and uses these cases to highlight the challenges and impact on predicted heat transfer. A comparison of the two models indicate that the different representations of end winding geometries can affect the heat dissipation rate through the outer housing by up to 45%

Fluid flow and heat transfer analysis of TEFC machine end regions using more realistic end-winding geometry

Here, a typical small low-voltage totally enclosed fan-cooled (TEFC) motor (output power ∼10 kW) has been studied using computational fluid dynamics. The complexity of the end-winding geometries, often consisting of several insulated copper strands bound together, provides a challenge to the modelling and analysis of heat transfer and fluid flow phenomena occurring in the end region, which typically is an area of most interest for thermal management. Approximated geometries are usually employed in order to model the end windings to reduce the analysis time and cost. This paper presents a comparison of two cases, a typical simplified geometry and a more realistic geometry of end windings, and uses these cases to highlight the challenges and impact on predicted heat transfer. A comparison of the two models indicate that the different representations of end winding geometries can affect the heat dissipation rate through the outer housing by up to 45%

Numerical investigations of convective phenomena of oil impingement on end-windings

A novel experimental rig for analysing intensive liquid cooling of highly power-dense electrical machine components has been developed. Coupled fluid flow and heat transfer has been modelled, using computational fluid dynamics (CFD), to inform the design of a purpose-built enclosure for optimising the design of submerged oil jet cooling approaches for electrical machine stators. The detailed modelling methodology presented in this work demonstrates the value in utilising CFD as a design tool for oil-cooled electrical machines. The predicted performance of the final test enclosure design is presented, as well as examples of the sensitivity studies which helped to develop the design. The sensitivity of jet flow on resulting heat transfer coefficients has been calculated, whilst ensuring parasitic pressure losses are minimised. The CFD modelling will be retrospectively validated using experimental measurements from the test enclosure

Numerical investigations of convective phenomena of oil impingement on end-windings

A novel experimental rig for analysing intensive liquid cooling of highly power-dense electrical machine components has been developed. Coupled fluid flow and heat transfer have been modelled, using computational fluid dynamics (CFD), to inform the design of a purpose-built enclosure for optimising the design of submerged oil jet cooling approaches for electrical machine stators. The detailed modelling methodology presented in this work demonstrates the value in utilising CFD as a design tool for oil-cooled electrical machines. The predicted performance of the final test enclosure design is presented, as well as examples of the sensitivity studies which helped to develop the design. The sensitivity of jet flow on resulting heat transfer coefficients has been calculated, while ensuring parasitic pressure losses are minimised. The CFD modelling will be retrospectively validated using experimental measurements from the test enclosure

Multiplex Networks to Characterize Seizure Development in Traumatic Brain Injury Patients

Traumatic brain injury (TBI) may cause secondary debilitating problems, such as post-traumatic epilepsy (PTE), which occurs with unprovoked recurrent seizures, months or even years after TBI. Currently, the Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) has been enrolling moderate-severe TBI patients with the goal to identify biomarkers of epileptogenesis that may help to prevent seizure occurrence and better understand the mechanism underlying PTE. In this work, we used a novel complex network approach based on segmenting T1-weighted Magnetic Resonance Imaging (MRI) scans in patches of the same dimension (network nodes) and measured pairwise patch similarities using Pearson's correlation (network connections). This network model allowed us to obtain a series of single and multiplex network metrics to comprehensively analyze the different interactions between brain components and capture structural MRI alterations related to seizure development. We used these complex network features to train a Random Forest (RF) classifier and predict, with an accuracy of 70 and a 95% confidence interval of [67, 73%], which subjects from EpiBioS4Rx have had at least one seizure after a TBI. This complex network approach also allowed the identification of the most informative scales and brain areas for the discrimination between the two clinical groups: seizure-free and seizure-affected subjects, demonstrating to be a promising pilot study which, in the future, may serve to identify and validate biomarkers of PTE

Fluid flow and heat transfer analysis of TEFC machine end regions using more realistic end-winding geometry

In this paper a typical small low voltage TEFC motor (output power ~10 kW) has been studied using computational fluid dynamics. The complexity of the end winding geometries, often consisting of several insulated copper strands bound together, provides a challenge to the modelling and analysis of heat transfer and fluid flow phenomena occurring in the end region which typically is an area of most interest for thermal management. Approximated geometries are usually employed in order to model the end windings to reduce analysis time and cost. This paper presents a comparison of two cases, a typical simplified geometry and a more realistic geometry of end windings and uses these cases to highlight the challenges and impact on predicted heat transfer. A comparison of the two models indicate that the different representations of end winding geometries can affect the heat dissipation rate through the outer housing by up to 45%