An automatic multi-stepping approach to aircraft ice prediction

Flying an aircraft in icing conditions may seriously degrade its aerodynamical performance and threaten the flight safety. Over the years, new technologies and improved procedures have limited the potential risks caused by aircraft icing. Experimental studies being very expensive, numerous computer codes have been developed to simulate ice shapes and tackle the problem. Typically in these codes, a flow solution and key icing parameters are evaluated around a clean un-iced geometry and their values remain constant during the entire simulation. This approach may be acceptable for short exposure times or when the ice shape only slightly deforms the initial geometry. However, in other cases, the values of the icing parameters may vary and the simulation will loose its accuracy: for large shapes, the presence of the ice influences the surrounding airflow significantly, altering the value of icing parameters and ultimately the ice accretion. Calculating more accurate ice shapes therefore requires to periodically recompute the flow field around the body during the simulation and determine updated values for icing parameters. This procedure, known as multi-stepping, is investigated in this thesis and adapted to the new threedimensional icing code ICECREMO2. Several multi-step algorithms are presented and tested on cylinders and airfoils. When possible, the ice shapes simulated are compared with experimental results. The first multi-step calculations were generally performed manually. The user had to perform a rather tedious work and inappropriate instructions could lead to severe inaccuracies in the simulations. To avoid these difficulties, a fully automated procedure will be developed including all stages of a multi-step computation. This significantly reduces user interaction and the overall computing time. The present research work forms part of the ICECREMO2 project. ICECREMO2 is a three-dimensional ice accretion and water flow code developed collaboratively by Airbus UK, BAe Systems, Dunlop Aerospace, Rolls-Royce, GKN Westland Helicopters, QinetiQ and Cranfield University under the auspices of the UK Department of Trade and Industry. iEThOS - Electronic Theses Online ServiceGBUnited Kingdo

Pebble bed: reflector treatment and pressure\ud velocity coupling

In this report, we describe some models and numerical methods used to simulate the flow and temperature in a pebble bed modular nuclear reactor. The reactor core is filled with around 450000 spheres containing low enriched uranium and helium is forced through these hot pebbles to cool the system down. The group first investigated the flow model in the pebbles. Numerical aspects were then considered to tackle difficulties encountered with the flow simulation and the temperature inside the pebbles. Numerical schemes are presented that can significantly improve the accuracy of the computed results

c-Met overexpression in inflammatory breast carcinomas: automated quantification on tissue microarrays

Inflammatory breast carcinoma (IBC) is a rare but aggressive tumour associated with poor outcome owing to early metastases. Increased expression of c-Met protein correlates with reduced survival and high metastatic risk in human cancers including breast carcinomas and is targetable by specific drugs, that could potentially improve the prognosis. In the present study, we compared c-Met expression in IBC (n=41) and non-IBC (n=480) immunohistochemically (Ventana Benchmark autostainer) in two tissue microarrays (TMA) along with PI3K and E-cadherin. The results were quantified through an automated image analysis device (SAMBA Technologies). We observed that (i) c-Met was significantly overexpressed in IBC as compared with non-IBC (P<0.001), (ii) PI3K was overexpressed (P<0.001) in IBC, suggesting that the overexpressed c-Met is functionally active at least through the PI3K signal transduction pathway; and (iii) E-cadherin was paradoxically also overexpressed in IBC. We concluded that overexpressed c-Met in IBC constitutes a potential target for specific therapy for the management of patients with poor-outcome tumours such as IBC. Automated image analysis of TMA proved to be a valuable tool for high-throughput immunohistochemical quantification of the expression of intratumorous protein markers

Angiogenesis is associated with the onset of hyperplasia in human ductal breast disease

BACKGROUND: The precise timing of the angiogenic switch and the role of angiogenesis in the development of breast malignancy is currently unknown. METHODS: Therefore, the expression of CD31 (pan endothelial cells (ECs)), endoglin (actively proliferating ECs), hypoxia-inducible factor-1 (HIF-1alpha), vascular endothelial growth factor-A (VEGF) and tissue factor (TF) were quantified in 140 surgical specimens comprising normal human breast, benign and pre-malignant hyperplastic tissue, in situ and invasive breast cancer specimens. RESULTS: Significant increases in angiogenesis (microvessel density) were observed between normal and benign hyperplastic breast tissue (P<0.005), and between in situ and invasive carcinomas (P<0.0005). In addition, significant increases in proliferating ECs were observed in benign hyperplastic breast compared with normal breast (P<0.05) cancers and in invasive compared with in situ cancers (P<0.005). Hypoxia-inducible factor-1alpha, VEGF and TF expression were significantly associated with increases in both angiogenesis and proliferating ECs (P<0.05). Moreover, HIF-1alpha was expressed by 60-75% of the hyperplastic lesions, and a significant association was observed between VEGF and TF in ECs (P<0.005) and invasive tumour cells (P<0.01). CONCLUSIONS: These findings are the first to suggest that the angiogenic switch, associated with increases in HIF-1alpha, VEGF and TF expression, occurs at the onset of hyperplasia in the mammary duct, although the greatest increase in angiogenesis occurs with the development of invasion

Adherence to inhaled corticosteroids and long-acting β2-agonists in asthma:A MASK-air study

Introduction Adherence to controller medication is a major problem in asthma management, being difficult to assess and tackle. mHealth apps can be used to assess adherence. We aimed to assess the adherence to inhaled corticosteroids+long-acting β2-agonists (ICS+LABA) in users of the MASK-air® app, comparing the adherence to ICS+formoterol (ICS+F) with that to ICS+other LABA. Materials and methods We analysed complete weeks of MASK-air® data (2015-2022; 27 countries) from patients with self-reported asthma and ICS+LABA use. We compared patients reporting ICS+F versus ICS+other LABA on adherence levels, symptoms and symptom-medication scores. We built regression models to assess whether adherence to ICS+LABA was associated with asthma control or short-acting beta-agonist (SABA) use. Sensitivity analyses were performed considering the weeks with no more than one missing day. Results In 2598 ICS+LABA users, 621 (23.9%) reported 4824 complete weeks and 866 (33.3%) reported weeks with at most one missing day. Higher adherence (use of medication ≥80% of weekly days) was observed for ICS+other LABA (75.1%) when compared to ICS+F (59.3%), despite both groups displaying similar asthma control and work productivity. The ICS+other LABA group was associated with more days of SABA use than the ICS+F group (median=71.4% versus 57.1% days). Each additional weekly day of ICS+F use was associated with a 4.1% less risk in weekly SABA use (95%CI=-6.5;-1.6%;p=0.001). For ICS+other LABA, the percentage was 8.2 (95%CI=-11.6;-5.0%;p<0.001). Conclusions In asthma patients adherent to the MASK-air app, adherence to ICS+LABA was high. ICS+F users reported lower adherence but also a lower SABA use and a similar level of control