Prediction of Upward Flame Spread over Polymers

In this work, the existing understanding of flame spread dynamics is enhanced through an extensive study of the heat transfer from flames spreading vertically upwards across 5 cm wide, 20 cm tall samples of extruded Poly (Methyl Methacrylate) (PMMA). These experiments have provided highly spatially resolved measurements of flame to surface heat flux and material burning rate at the critical length scale of interest, with a level of accuracy and detail unmatched by previous empirical or computational studies. Using these measurements, a wall flame model was developed that describes a flame’s heat feedback profile (both in the continuous flame region and the thermal plume above) solely as a function of material burning rate. Additional experiments were conducted to measure flame heat flux and sample mass loss rate as flames spread vertically upwards over the surface of seven other commonly used polymers, two of which are glass reinforced composite materials. Using these measurements, our wall flame model has been generalized such that it can predict heat feedback from flames supported by a wide range of materials. For the seven materials tested here – which present a varied range of burning behaviors including dripping, polymer melt flow, sample burnout, and heavy soot formation – model-predicted flame heat flux has been shown to match experimental measurements (taken across the full length of the flame) with an average accuracy of 3.9 kW m-2 (approximately 10 – 15 % of peak measured flame heat flux). This flame model has since been coupled with a powerful solid phase pyrolysis solver, ThermaKin2D, which computes the transient rate of gaseous fuel production of constituents of a pyrolyzing solid in response to an external heat flux, based on fundamental physical and chemical properties. Together, this unified model captures the two fundamental controlling mechanisms of upward flame spread – gas phase flame heat transfer and solid phase material degradation. This has enabled simulations of flame spread dynamics with a reasonable computational cost and accuracy beyond that of current models. This unified model of material degradation provides the framework to quantitatively study material burning behavior in response to a wide range of common fire scenarios.

Upper crustal structure of Madeira Island revealed from ambient noise tomography

We present the first image of the Madeira upper crustal structure, using ambient seismic noise tomography. 16 months of ambient noise, recorded in a dense network of 26 seismometers deployed across Madeira, allowed reconstructing Rayleigh wave Green's functions between receivers. Dispersion analysis was performed in the short period band from 1.0 to 4.0 s. Group velocity measurements were regionalized to obtain 2D tomographic images, with a lateral resolution of 2.0 km in central Madeira. Afterwards, the dispersion curves, extracted from each cell of the 2D group velocity maps, were inverted as a function of depth to obtain a 3D shear wave velocity model of the upper crust, from the surface to a depth of 2.0 km. The obtained 3D velocity model reveals features throughout the island that correlates well with surface geology and island evolution.

Computed Tomography Perfusion Can Guide Endovascular Therapy in Bilateral Carotid Artery Dissection

Carotid artery dissection (CAD) is a major cause of stroke in those under age 45, accounting for around 20% of ischaemic events[1,2]. In the absence of known connective tissue disorders, most dissections are traumatic[2]. First-line management is comprised of antiplatelet or anticoagulation therapy, but many traumatic dissections progress despite this and carry the risk of long-term complications from embolism or stenosis[3]. We report a case of traumatic bilateral carotid dissection leading to progressive neurological symptoms and hypoperfusion on computed tomography perfusion (CTP), despite escalation in anticoagulation, which led to emergency carotid stenting.

16α-[18F]-fluoro-17ß-oestradiol ([18F]FES): A biomarker for imaging oestrogen receptor expression with positron emission tomography (PET)

International audience

Numerical methods for solar tomography in the STEREO era

In this thesis, we propose several advances in the numerical and computational algorithms that are used to determine tomographic estimates of physical parameters in the solar corona. We focus on methods for both global dynamic estimation of the coronal electron density and estimation of local transient phenomena, such as coronal mass ejections, from empirical observations acquired by instruments onboard the STEREO spacecraft. We present a first look at tomographic reconstructions of the solar corona from multiple points-of-view, which motivates the developments in this thesis. In particular, we propose a method for linear equality constrained state estimation that leads toward more physical global dynamic solar tomography estimates. We also present a formulation of the local static estimation problem, i.e., the tomographic estimation of local events and structures like coronal mass ejections, that couples the tomographic imaging problem to a phase field based level set method. This formulation will render feasible the 3D tomography of coronal mass ejections from limited observations. Finally, we develop a scalable algorithm for ray tracing dense meshes, which allows efficient computation of many of the tomographic projection matrices needed for the applications in this thesis.

Interaction of Acoustic Waves with a Laminar Line-Flame

A systematic study was conducted to elucidate the effects of acoustic perturbations on laminar diffusion line-flames and the conditions required to cause acoustically-driven extinction. Flames were produced from the fuels n-pentane, n-hexane, n-heptane, n-octane, and JP-8, using fuel-laden wicks. The wicks were housed inside of a burner whose geometry produced flames that approximated a two dimensional flame sheet. The acoustics utilized ranged in frequency between 30-50 Hz and acoustic pressures between 5-50 Pa. The unperturbed mass loss rate and flame height of the alkanes were studied, and they were found to scale in a linear manner consistent with Burke-Schumann. The mass loss rate of hexane-fueled flames experiencing acoustic perturbations was then studied. It was found that the strongest influence on the mass loss rate was the magnitude of oscillatory air movement experienced by the flame. Finally, acoustic perturbations were imposed on flames using all fuels to determine acoustic extinction criterion. Using the data collected, a model was developed which characterized the acoustic conditions required to cause flame extinction. The model was based on the ratio of an acoustic Nusselt Number to the Spalding B Number of the fuel, and it was found that at the minimum speaker power required to cause extinction this ratio was a constant. Furthermore, it was found that at conditions where the ratio was below this constant, a flame could still exist; at conditions where the ratio was greater than or equal to this constant, flame extinction always occurred.

Optical micro-tomography “OPenT” allows the study of large toadfish Halobatrachus didactylus embryos and larvae

Batrachoidids, which include midshipman and toadfish are less known among embryologists, but are common in other fields. They are characteristic for their acoustic communication, and develop hearing and sound production while young juveniles. They lay large benthic eggs (>5mm) with a thick chorion and adhesive disk and slow development, which are particularly challenging for studying embryology. Here we took advantage of a classical tissue clearing technique and the OPenT open-source platform for optical tomography imaging, to image a series of embryos and larvae from 3 to 30mm in length, which allowed detailed 3D anatomical reconstructions non-destructively. We documented some of the developmental stages (early and late in development) and the anatomy of the delicate stato-acoustic organs, swimming bladder and associated sonic muscles. Compared to other techniques accessible to developmental biology labs, OPenT provided advantages in terms of image quality, cost of operation and data throughput, allowing identification and quantitative morphometrics of organs in larvae, earlier and with higher accuracy than is possible with other imaging techniques.

Transmission electron tomography: quality assessment and enhancement for three-dimensional imaging of nanostructures

Nanotechnology has revolutionised humanity's capability in building microscopic systems by manipulating materials on a molecular and atomic scale. Nan-osystems are becoming increasingly smaller and more complex from the chemical perspective which increases the demand for microscopic characterisation techniques. Among others, transmission electron microscopy (TEM) is an indispensable tool that is increasingly used to study the structures of nanosystems down to the molecular and atomic scale. However, despite the effectivity of this tool, it can only provide 2-dimensional projection (shadow) images of the 3D structure, leaving the 3-dimensional information hidden which can lead to incomplete or erroneous characterization. One very promising inspection method is Electron Tomography (ET), which is rapidly becoming an important tool to explore the 3D nano-world. ET provides (sub-)nanometer resolution in all three dimensions of the sample under investigation. However, the fidelity of the ET tomogram that is achieved by current ET reconstruction procedures remains a major challenge. This thesis addresses the assessment and advancement of electron tomographic methods to enable high-fidelity three-dimensional investigations. A quality assessment investigation was conducted to provide a quality quantitative analysis of the main established ET reconstruction algorithms and to study the influence of the experimental conditions on the quality of the reconstructed ET tomogram. Regular shaped nanoparticles were used as a ground-truth for this study. It is concluded that the fidelity of the post-reconstruction quantitative analysis and segmentation is limited, mainly by the fidelity of the reconstructed ET tomogram. This motivates the development of an improved tomographic reconstruction process. In this thesis, a novel ET method was proposed, named dictionary learning electron tomography (DLET). DLET is based on the recent mathematical theorem of compressed sensing (CS) which employs the sparsity of ET tomograms to enable accurate reconstruction from undersampled (S)TEM tilt series. DLET learns the sparsifying transform (dictionary) in an adaptive way and reconstructs the tomogram simultaneously from highly undersampled tilt series. In this method, the sparsity is applied on overlapping image patches favouring local structures. Furthermore, the dictionary is adapted to the specific tomogram instance, thereby favouring better sparsity and consequently higher quality reconstructions. The reconstruction algorithm is based on an alternating procedure that learns the sparsifying dictionary and employs it to remove artifacts and noise in one step, and then restores the tomogram data in the other step. Simulation and real ET experiments of several morphologies are performed with a variety of setups. Reconstruction results validate its efficiency in both noiseless and noisy cases and show that it yields an improved reconstruction quality with fast convergence. The proposed method enables the recovery of high-fidelity information without the need to worry about what sparsifying transform to select or whether the images used strictly follow the pre-conditions of a certain transform (e.g. strictly piecewise constant for Total Variation minimisation). This can also avoid artifacts that can be introduced by specific sparsifying transforms (e.g. the staircase artifacts the may result when using Total Variation minimisation). Moreover, this thesis shows how reliable elementally sensitive tomography using EELS is possible with the aid of both appropriate use of Dual electron energy loss spectroscopy (DualEELS) and the DLET compressed sensing algorithm to make the best use of the limited data volume and signal to noise inherent in core-loss electron energy loss spectroscopy (EELS) from nanoparticles of an industrially important material. Taken together, the results presented in this thesis demonstrates how high-fidelity ET reconstructions can be achieved using a compressed sensing approach.