II. The numerical analysis A. Presentation ofthe model
We will study an assembly of three plates (Fig. 3.a) tightened together by a bolt, solicited transversally by a sinusoidal shaped load. Our model, developed on Abaqus (Fig. 3.b), only represents the head ofthe fastener, a part of its shank and its bearing plates. The bolt (diameter 9.52 mm, in red), is in titanium whereas the plate (with bore clearance of 30µm, in light grey) is in aluminum. The simulation is composed of 3 steps. The first one is an axial loading F 0 to apply a preload on section S b . A maximum preload of 28 000 N, chosen according to Airbus standards, corresponds to 60% ofthe yield strength for the Ti4Al6V. The second one is an axial torque C 0 applied to the section S b , to consider the reaction ofthe nut’s threads on the bolt’s threads due to the preload. The last one is the shear-loading ofthe assembly by a sinusoidal shear-load F t (t) at a frequency of 5 Hz, applied to the cylinder C t .
A CASE STUDY FOR PASSIVE COOLING IN AN URBAN TROPICAL ENVIRONMENT
A. Foucquier 1 , M. Boulinguez 2 , A. Jay 1 , K. Juhoor 2,3 , A. Bastide 3 , E.wurtz 1
1. Univ. Grenoble Alpes, INES, F-73375 Le Bourget du Lac, France - CEA, LITEN, Department of Solar Technologies, F-73375 Le Bourget du Lac, France 2. Intégrale Ingénierie, 70 rue Archambaud, 97410 Saint-Pierre, La Réunion, FRANCE
Given the fact that the aggregated team rankings are so dependent on the aggregation scheme, instead of trying to rank all teams individually, we tried to look for some consensus among clusters of teams, i.e. if the majority of reviewers may have thought, for instance, that teams A and B were ranked as top tier, teams C and D as middle tier, E and F as bottom tier and so on. In order to assess this, we ran a cluster analysis whose results depend on the particular chosen algorithm (K-mean, Ward’s, etc.) and on the definition of distances. We applied sensitivity analysis with respect to each algorithm choice and distance to determine if distinct clusters of teams could emerge. Our results showed that two distinct clusters of teams (“second tier” and “top tier” teams) could indeed be found, while smaller size clustering became too sensitive to the distance definition and algorithm choice. This showed that jury members did agree on which teams were “second tier” and which teams were ”top tier”, but weren’t able to find a consensus on how a particular team performed on an ordinal scale within these two groups.
• the amplitude of some frequencies which are not correlated to the BPF in the range [0, 2 × BP F ] is ofthe same order of magnitude than the BPF harmonics.
Theanalysisofthe LES results is completed using Power Spectrum Den- sity (PSD) representations of axial velocity signals, at four spans: h/H = 50%, 80%, 90% and 95%, Fig. 12. At mid-span, the results corroborate those obtained with the FFT: most ofthe energy is associated to the BPF and its harmonics (at this span, the use of a URANS method is thus pertinent to estimate the level of unsteadiness). When moving closer to the casing, a part ofthe unsteadiness is transferred from the BPF (and its harmonics) to turbulent flow patterns. At h/H = 80% and h/H = 90%, frequencies uncorrelated with BPF develops, Fig. 12(b-c): frequency f = 8, 700 Hz (and its harmonic f = 15, 800 Hz) is found to be correlated to an axial pulsation ofthe tip leakage flow. At h/H = 95%, the influence ofthe BPF is increased compared to other spans, Fig. 12(d), and the frequencies uncorrelated with the BPF (f = 8, 700 Hz and its harmonic f = 15, 800 Hz) contain now more energy than the BPF harmonics.
crystal method) to compute the free energy per particle ofthe crystal as a function of temperature, at constant pressure (the density was chosen such that PE0). From the free energy per particle, we directly obtain the chemical potential ofthe particles in the crystal. Table 2 summarizes these results. For the cluster- ﬂuid phase, we determined the chemical potential by using the Widom particle insertion method (see Methods) at volume fractions between f ¼ 0.026 and f ¼ 0.0104 and pressure C0. The results are plotted in Fig. 3b,c for HS and LS, respectively, where they are compared with the chemical potential ofthe crystalline states (black symbols *) obtained from the free energy calculated using the Einstein crystal method and thermodynamic integration (see Methods). For HS the clusters are clearly more stable than the crystalline states. Going to LS instead, the crystalline states have comparable or lower free energies, supporting the idea that in this case the clusters, even though they persist throughout the simulation runs, are only metastable. In all cases, the shapes ofthe clusters change with their size: small clusters tend to be roughly spherical, whereas larger clusters are more elongated. A quantitative measure ofthe elongation is given by the normalized asphericity b=R 2 g (see Methods), which equals zero for a spherically symmetric object, þ 1 for a needle and 0.5 for a disk. The dependence ofthe asphericity on the cluster size is plotted in Fig. 4a. The data show that upon going from the HS to the LS potential the asphericity decreases: small- and intermediate-size clusters have a ﬁbrillar shape in HS and MS, whereas they are much more spherical in LS, where the asphericity emerges only for much larger clusters (see Supplementary Fig. 1). Analysisofthe particle arrangements inside the aggregates reveals that the (metastable) clusters for the LS case are quite crystalline (see Supplementary Fig. 2). The rotational invariants ^ w 6 and ^ w 4 computed from the local bond orientational order (BOO; see Methods) 39 allow us to distinguish face-centred cubic (fcc) or hexagonal close-packed (hcp) crystals from the orientational order typical of Bernal spirals (BS), which is compatible with the ﬁbrillar growth ofthe clusters in HS and MS. Figure 4b shows indeed that the nature ofthe local packing in the LS clusters is quite different from that in the HS clusters: for the LS potential, the local packing in clusters appears to fall in the fcc–hcp range, whereas the HS clusters have a structure that is more similar to
The expander model is more complex and may require experimental studies in order to capture all ofthe thermal, fluid, and mechanical inefficiencies present; such realism is important in determining whether the model neglects any large losses present in an actual FPE. It seems feasible to build an apparatus that would allow the total clearance fraction and S/D ratio to be varied by using a movable warm-end cylinder head. Such a device could also explore variations in blow-in and blow-out factors by using a flexible control algorithm combined with warm-end bleed flows when necessary, and oversized low-resistance valves could be used in conjunction with adjustable throttles to vary the operating frequency. Though some variables such as the piston length and gap width would be more difficult to alter without constructing multiple pistons (and the diameter would be impractical to vary without constructing multiple expanders altogether), the data obtained from varying the other parameters along with the working fluid, pressure, pressure ratio, and temperature would likely provide enough data to assess the accuracy ofthe expander model in this thesis.
length for the current, di/dt and dj/dt ranges investigated.
Prearc-arc transition is a complex phenomenon. Many works dedicated to exploding wires have been published with higher current densities and using essentially capacitive discharges . In these experiments authors have concluded that wire first melts inside and secondly burns. Apparition of metallic vapor before arcing stage in our experiment lets us to assume that wire is surrounded by vapor before breaking. These vapors could become an arc-channel after the mechanical disruption ofthe wire, actually their temperature is quite high but their density should be measured to better understand their role in conductivity. Simulation shows that considering homogeneous temperature along the wire is not correct although it permits to make first approximations. Future working will be devoted in temperature, electron density and electric field measurements during respectively solid state and plasma state.
Several studies have shown that foragers spend a considerable portion of their lifespan learning and improving their foraging skills through experience [44,59,61]. They gradually increase their foraging performance over a period of more than a week, and then, performances reach a plateau  or decrease . Our data suggest that the pre-foraging stage is also of paramount importance to maximize the foraging stage. It, therefore, seems that the more days that they spend accumulating experience, the better their future foraging performance. As a matter of fact, experimentally induced precocious foragers exhibit some deficit in developing spatial memory as compared to normal-aged foragers . It is also possible that a consequent pre-foraging activity is required not only to optimize cognitive functions but also physiological functions associated with flight capacities, like a decrease in body mass , an increase in cytochrome concentrations , thoracic glycogen levels , citrate synthase levels and troponin T 10A expression , which yield a strong increase in flight metabolic rate [64,65]. The physiological maturation hypothesis seems supported by the fact that the foraging stage is more strongly correlated to the number of days between AFE and AOF than by the actual amount of pre-foraging experience (number and minutes of pre-foraging flights). In turn, the amount of pre-foraging experience was more strongly correlated to the foraging intensity, suggesting again a positive influence of pre-foraging activity on future foraging skills probably via learning and/or physiological maturation. Nevertheless, manipulative experiments would be needed to understand how precisely the pre-foraging stage influences foraging.
In the present study, the flow through the fan stageof a high bypass ratio turbofan at windmill is studied numerically. First, steady mixing plane simulations are validated against detailed experimental engine test-bed measurements, at several locations within the fan stage and close to the core/bypass flow splitter. Good agreement between the numerical and experimental results is obtained. A local flow analysis is proposed, evidencing several characteristics ofthe flow in windmilling: in the rotor, the size ofthe separation zone is found to increase from hub to tip, and in the stator, massive flow separation occurs at mid-span, which leads to the formation of two streamwise counter-rotating vortices. Then, the Nonlinear Harmonic (NLH) method is applied to a section (at 70 % ofthe relative span) ofthe fan stage. A modal analysis is performed, showing a specific behavior at windmill: the massively separated flows in the rotor and the stator entail strong rotor/stator interactions modes. Finally, the unsteady flow pattern is examined: the velocity defect ofthe rotor wake, which periodically increases the flow angle on the stator, is shown to trigger a periodic movement ofthe reattachment point at the trailing edge ofthe stator, associated with vortex shedding from the lower side ofthe vane. The implication of this qualitative flow behavior on the method to extract CFD results for comparisons with experiments is discussed.
Later-stage tumours showed enrichment in pathways mostly involved in transcription, translation, mitochondrial electron transport chain, and actin cytoskeleton organization (Supplemental Table 6A). This relects the overall higher me- tabolism and growth rate of more advanced cancers. Interest- ingly, there was also enrichment in genes in the IL-6 signaling pathway; these included phospholipase C gamma subunit (PL- CG1), FYN oncogene, ras-related small GTP-binding protein (RAC1), heat shock protein 90kDA alpha A1 (HSP90AA1), and protein phosphatase2 regulatory subunit B, gamma (PPP2R2C). FYN is a tyrosine kinase that has been implicated in the control of cell growth. HSP90AA1 is a chaperone for tyrosine kinases EGFR, MET and ALK, 52 all of which are oncogenic drivers of
Aside from what was learned from the actual visual display ofthe triangle model and the process of analyzing the prototype information, the challenges of applying the model remain to be discussed. Each prototype was successfully assigned a place on the Houde and Hill (1997) triangle model. In general, the model was extremely easy to apply to the physical prototypes created in MIT’s senior design course. However, it was slightly challenging to isolate design questions centered on role for a few ofthe sample prototypes. This challenge can most likely be attributed to the discovery that role and look and feel questions are very closely related when considering physical prototypes. For example, the SushiBot technical review prototype had a strong focus on how users would interact with the product. Due to the interactive nature of SushiBot, the designers felt that the appearance and personality ofthe prototype had a significant influence on how the customers would use the product. Depending on the personality of SushiBot, the user would be more or less inclined to pick up or play with the robot. In this way, design questions of role and look and feel were interdependent. It is possible that this complication is relevant to physical models, but not the interaction design prototypes originally used with the Houde and Hill (1997) triangle model.
[12,16,25-31] and Table S2 summarises the trials with no available data. Four trials [16,27,30,31] had different radiotherapy modalities between the two arms, including three trials [16,30,31] comparing shorter vs. longer radiotherapy duration. Central randomisation was used in all trials, except one that used sealed envelopes . In total, out ofthe 80 patients initially excluded from the individual trial analyses, data concerning 75 patients were recovered. The median follow-up was 10 years without any difference between the treatment arms. Patient characteristics were well balanced between the two arms oftheanalysis (Table S3). Three trials [16,26,28] were categorised as having similar chemotherapy compliance in both arms, and they had a proportion of at least 79% of patients who were compliant with chemotherapy (i.e. receiving all their cycles) (Table S4). Five trials [12,25,27,29,31] had different chemotherapy (CT) compliance, with all of them exhibiting a lower compliance rate in the “earlier or shorter” arm. For the CCWFU62286 trial, we had no data available on
bust solutions. Furthermore, Thiele et. al. [ 19 ] describe a two-stage robust
approach to address general linear programs affected by uncertain right hand side. The robust formulation they obtained is a convex (not linear) program, and they propose a cutting plane algorithm to exactly solve the problem. In- deed, at each iteration, they have to solve an NP-hard recourse problem on an exact way, which is time-expensive. Here, we go further in theanalysisofthe recourse problem ofthe location transportation problem, in particular we define a tight bound for the mixed-integer reformulation.
In this book chapter, we considered a simplified launcher stage fallout model to analyze, without loss of generality, the efficiency ofthe proposed methods. Our objective was to determine the most influential factors on the fallout and on its failure probability. For that purpose, we first apply a new scheme of estimation of moment independent sensitivity measures (δ-sensitivity measures) that has a low computational cost. Theses indices take the entire fallout distribution probability into account unlike classical Sobol’ indices that focus on the distribution variance. We noticed in this test case that the influence ofthe input ”propellant mass perturbation at separation” was underestimated by Sobol’ indices while it is the most influential factors according to δ-sensitivity measures. In a second part, we assume that the launcher stage fallout model is affected by a bi-level uncertainty and propose a numerical estimation strategy to estimate the predictive failure probability and its sensitivities w.r.t. the hyper-parameters ofthe prior distribution. This estimation strategy, called ARA/NAIS, relies on the use of an augmented space (ARA) coupled to a nonparametric importance sampling (NAIS) scheme. Thus, this strategy allows to estimate, with a better efficiency than CMC, both the predictive failure probability and its sensitivities by just post-processing the samples used to estimate the predictive failure probability. This study shows the benefits of using an ARA/NAIS strategy when the failure event becomes very rare, especially for complex models. Acknowledgements The first and second author contributed equally to this work. The first two authors are currently enrolled in a PhD program, respectively funded by Universit´ e Toulouse III – Paul Sabatier and co-funded by ONERA – The French Aerospace Lab & SIGMA Clermont. Their financial supports are gratefully acknowledged. The authors would like to thank Dr. Lo¨ıc Brevault (Research scientist at ONERA – The French Aerospace Lab) for having provided the launch vehicle fallout zone estimation code.
ring in different situations (sexual/asexual reproduc- tion, regeneration) and by different set of morphogen- esis lead to thestage common for all Porifera: that ofthe rhagon, which can be characterized by its struc- tural similarity across this phylum. We propose that this stage can be considered not only as a phylotipic stage, but also as a model of putative ancestral sponge—a spongotype. Thestageof rhagon is typical for Demospongiae, and it corresponds to olintus, characteristic of Calcarea (Figs. 4, 5a). In order to confirm or disprove these conclusions, it is necessary to conduct a detailed study ofthe molecular mecha- nisms that regulate the formation of rhagon in repre- sentatives of different phylogenetic groups of sponges. Such a study will improve our understanding ofthe mechanisms involved in the evolution ofthe body plans of sponges and other multicellular animals.