Vapour layer formation by electrical discharges through electrically conducting liquids-modelling and experiment

Experimental and finite element modelling methods are used to study the formation of vapour layers in electrical discharges through saline solutions. The experiments utilize shadowgraphic and photometric methods to observe the time dependence of thin vapour layers and plasma formation around electrodes driven by moderate voltage (<500 V) pulses, applied to an electrode immersed in a conducting saline solution. Finite element multiphysics software, coupling thermal and electrical effects, is employed to model the vapour layer formation. All relevant electrical and thermal properties of the saline are incorporated into the model, but hydrodynamic and surface tension effects are ignored. Experimental shadowgraph and modelling images are compared, as are current histories, and the agreement is very good. The comparison of experiment and modelling gives insight into both vapour layer production and subsequent plasma production. We show that, for example, superheating of the saline above its normal vaporization temperature may be playing a significant role in vapour formation. We also show that electric fields of approaching 10(7) V m(-1) can be achieved in the vapour layer.

Implementation of a non-orthogonal model for the finite element simulation of textile composite draping

In the pursuit of producing high quality, low-cost composite aircraft structures, out-of-autoclave manufacturing processes for textile reinforcements are being simulated with increasing accuracy. This paper focuses on the continuum-based, finite element modelling of textile composites as they deform during the draping process. A non-orthogonal constitutive model tracks yarn orientations within a material subroutine developed for Abaqus/Explicit, resulting in the realistic determination of fabric shearing and material draw-in. Supplementary material characterisation was experimentally performed in order to define the tensile and non-linear shear behaviour accurately. The validity of the finite element model has been studied through comparison with similar research in the field and the experimental lay-up of carbon fibre textile reinforcement over a tool with double curvature geometry, showing good agreement.

Issues in fe modelling of FRP strengthened masonry arch bridges

Externally bonding of FRP composites is an effective technique for retrofitting historical masonry arch structures. A major failure mode in such strengthened structures is the debonding of FRP from the masonry. The bond behaviour between FRP and masonry thus plays a crucial role in these structures. Major challenges exist in the finite element modelling of such structures, such as modelling of mixed Mode-I and Mode-II bond behaviour between the FRP and the curved masonry substrate, modelling of existing damages in the masonry arches, consideration of loading history in the unstrengthened and strengthened structure etc. This paper presents a rigorous FE model for simulating FRP strengthened masonry arch structures. A detailed solid model was developed for simulating the masonry and a mixed-mode interface model was used for simulating the FRP-to-masonry bond behaviour. The model produces results in very close agreement with test results.

Probe-level linear model fitting and mixture modeling results in high accuracy detection of differential gene expression

Affiliation: Institut de recherche en immunologie et en cancérologie, Université de Montréal

Late Quaternary highstands at Lake Chilwa, Malawi: frequency, timing and possible forcing mechanisms in the last 44ka

The extensive shoreline deposits of Lake Chilwa, southern Malawi, a shallow water body today covering 600 km2 of a basin of 7500 km2, are investigated for their record of late Quaternary highstands. OSL dating, applied to 36 samples from five sediment cores from the northern and western marginal sand ridges, reveal a highstand record spanning 44 ka. Using two different grouping methods, highstand phases are identified at 43.7–33.3 ka, 26.2–21.0 ka and 17.9–12.0 ka (total error method) or 38.4–35.5 ka, 24.3–22.3 ka, 16.2–15.1 ka and 13.5–12.7 ka (Finite Mixture Model age components) with two further discrete events recorded at 11.01 ± 0.76 ka and 8.52 ± 0.56 ka. Highstands are comparable to the timing of wet phases from other basins in East and southern Africa, demonstrating wet conditions in the region before the LGM, which was dry, and a wet Lateglacial, which commenced earlier in the southern compared to northern hemisphere in East Africa. We find no evidence that wet phases are insolation driven, but analysis of the dataset and GCM modelling experiments suggest that Heinrich events may be associated with enhanced monsoon activity in East Africa in both timing and as a possible causal mechanism.

Analysis and clustering of residential customers energy behavioral demand using smart meter data

Clustering methods are increasingly being applied to residential smart meter data, providing a number of important opportunities for distribution network operators (DNOs) to manage and plan the low voltage networks. Clustering has a number of potential advantages for DNOs including, identifying suitable candidates for demand response and improving energy profile modelling. However, due to the high stochasticity and irregularity of household level demand, detailed analytics are required to define appropriate attributes to cluster. In this paper we present in-depth analysis of customer smart meter data to better understand peak demand and major sources of variability in their behaviour. We find four key time periods in which the data should be analysed and use this to form relevant attributes for our clustering. We present a finite mixture model based clustering where we discover 10 distinct behaviour groups describing customers based on their demand and their variability. Finally, using an existing bootstrapping technique we show that the clustering is reliable. To the authors knowledge this is the first time in the power systems literature that the sample robustness of the clustering has been tested.

Mechanical behaviour of functionally graded carbon nanofibre/phenolic nanocomposites: numerical modelling and experimental validation

In this study, a finite element-based model was developed to investigate the mechanical behaviour of functionally graded carbon nanofibre (CNF)/phenolic nanocomposites. Four functionally graded nanocomposites (FGNs), a non-graded nanocomposite (NGN), and a pure phenolic with the same geometry and total carbon nanofibre content were designed and fabricated. Flexural tests were conducted to validate the proposed finite element model. Close agreement was obtained between experimental results and numerical predictions. The results showed that flexural modulus can be improved about 45% by controlling the CNF content across the thickness of the samples.

Experimental studies and modelling of the deformation behaviour of multiple nanolayers

Microcompression tests were performed on monolithic Cu and Fe thin films and a Cu/Fe multilayer that had each individual layer of 200 nm thick, to understand the mechanical behaviour of multiple nanolayers. The micron-sized pillars were prepared by focused-ion beam (FIB) technique and compressed with a flat punch in a nanoindenter. The flow curves of the monolithic Cu and Fe thin films and Cu/Fe multilayer were extracted from the microcompression tests. The monolithic Cu thin film bulges in the top region of the pillar, while the Fe thin film cracks due to its columnar grain structure. For the Cu/Fe multilayer, the ductile Cu layers accommodate the majority of plastic deformation upon compression, while cracking in the Fe layers leads to the failure of the multilayer. Finite element models of microcompression tests were also developed to provide insights into the deformation behaviours of the multilayer and monolithic thin films. © 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Finite element analysis of warpage in laminated aluminium alloy plates for machining of primary aeronautic parts

The aim of this paper consists in presenting a method of simulating the warpage in 7xxx series aluminium alloy plates. To perform this simulation finite element software MSC.Patran and MSC.Marc were used. Another result of this analysis will be the influence on material residual stresses induced on the raw material during the rolling process upon the warpage of primary aeronautic parts, fabricated through machining (milling) at Embraer. The method used to determinate the aluminium plate residual stress was Layer Removal Test. The numerical algorithm Modified Flavenot Method was used to convert layer removal and beam deflection in stress level. With such information about the level and profile of residual stresses become possible, during the step that anticipate the manufacturing to incorporate these values in the finite-element approach for modelling warpage parts. Based on that warpage parameter surely the products are manufactured with low relative vulnerability propitiating competitiveness and price. © 2007 American Institute of Physics.

Dynamic characterisation of four nine-story large-panel R.C. buildings in Bishkek (Kyrgyzstan): A comparison between experimental ambient vibration analysis and numerical finite element modeling

With the outlook of improving seismic vulnerability assessment for the city of Bishkek (Kyrgyzstan), the global dynamic behaviour of four nine-storey r.c. large-panel buildings in elastic regime is studied. The four buildings were built during the Soviet era within a serial production system. Since they all belong to the same series, they have very similar geometries both in plan and in height. Firstly, ambient vibration measurements are performed in the four buildings. The data analysis composed of discrete Fourier transform, modal analysis (frequency domain decomposition) and deconvolution interferometry, yields the modal characteristics and an estimate of the linear impulse response function for the structures of the four buildings. Then, finite element models are set up for all four buildings and the results of the numerical modal analysis are compared with the experimental ones. The numerical models are finally calibrated considering the first three global modes and their results match the experimental ones with an error of less then 20%.

Mixture modeling for joint analysis of survival, discrete, and continuous data

Mixture modeling is commonly used to model categorical latent variables that represent subpopulations in which population membership is unknown but can be inferred from the data. In relatively recent years, the potential of finite mixture models has been applied in time-to-event data. However, the commonly used survival mixture model assumes that the effects of the covariates involved in failure times differ across latent classes, but the covariate distribution is homogeneous. The aim of this dissertation is to develop a method to examine time-to-event data in the presence of unobserved heterogeneity under a framework of mixture modeling. A joint model is developed to incorporate the latent survival trajectory along with the observed information for the joint analysis of a time-to-event variable, its discrete and continuous covariates, and a latent class variable. It is assumed that the effects of covariates on survival times and the distribution of covariates vary across different latent classes. The unobservable survival trajectories are identified through estimating the probability that a subject belongs to a particular class based on observed information. We applied this method to a Hodgkin lymphoma study with long-term follow-up and observed four distinct latent classes in terms of long-term survival and distributions of prognostic factors. Our results from simulation studies and from the Hodgkin lymphoma study demonstrated the superiority of our joint model compared with the conventional survival model. This flexible inference method provides more accurate estimation and accommodates unobservable heterogeneity among individuals while taking involved interactions between covariates into consideration.^

The role of material characterisation in the crush modelling of thermoplastic composite structures

The predictive capability of high fidelity finite element modelling, to accurately capture damage and crush behaviour of composite structures, relies on the acquisition of accurate material properties, some of which have necessitated the development of novel approaches. This paper details the measurement of interlaminar and intralaminar fracture toughness, the non-linear shear behaviour of carbon fibre (AS4)/thermoplastic Polyetherketoneketone (PEKK) composite laminates and the utilisation of these properties for the accurate computational modelling of crush. Double-cantilever-beam (DCB), four-point end-notched flexure (4ENF) and Mixed-mode bending (MMB) test configurations were used to determine the initiation and propagation fracture toughness in mode I, mode II and mixed-mode loading, respectively. Compact Tension (CT) and Compact Compression (CC) test samples were employed to determine the intralaminar longitudinal tensile and compressive fracture toughness. V-notched rail shear tests were used to measure the highly non-linear shear behaviour, associated with thermoplastic composites, and fracture toughness. Corresponding numerical models of these tests were developed for verification and yielded good correlation with the experimental response. This also confirmed the accuracy of the measured values which were then employed as input material parameters for modelling the crush behaviour of a corrugated test specimen.

Mixture of time-dependent growth models with an application to blue swimmer crab length-frequency data

Understanding how aquatic species grow is fundamental in fisheries because stock assessment often relies on growth dependent statistical models. Length-frequency-based methods become important when more applicable data for growth model estimation are either not available or very expensive. In this article, we develop a new framework for growth estimation from length-frequency data using a generalized von Bertalanffy growth model (VBGM) framework that allows for time-dependent covariates to be incorporated. A finite mixture of normal distributions is used to model the length-frequency cohorts of each month with the means constrained to follow a VBGM. The variances of the finite mixture components are constrained to be a function of mean length, reducing the number of parameters and allowing for an estimate of the variance at any length. To optimize the likelihood, we use a minorization–maximization (MM) algorithm with a Nelder–Mead sub-step. This work was motivated by the decline in catches of the blue swimmer crab (BSC) (Portunus armatus) off the east coast of Queensland, Australia. We test the method with a simulation study and then apply it to the BSC fishery data.

Multi-scale simulation using a hybrid mass-spring system and finite element model

Ply-scale finite element (FE) models are widely used to predict the performance of a composite structure based on material properties of individual plies. When simulating damage, these models neglect microscopic fracture processes which may have a significant effect on how a crack progresses within and between plies of a multidirectional laminate. To overcome this resolution limitation a multi-scale modelling technique is employed to simulate the effect micro-scale damage events have on the macro-scale response of a structure. The current paper discusses the development and validation of a hybrid mass-spring system and finite element modelling technique for multi-scale analysis. The model developed here is limited to elastic deformations; however, it is the first key step towards an efficient multi-scale damage model well suited to simulation of fracture in fibre reinforced composite materials. Various load cases have been simulated using the model developed here which show excellent accuracy compared to analytical and FE results. Future work is discussed, including extension of the model to incorporate damage modelling.