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Current technology has produced a wide range of advanced micro-structured surfaces, designed for achieving the best wettability and adhesion performances for each specific application. In the context of in-flight icing simulations, this opens new challenges since the current most popular and successful ice accretion prediction tools neglect the details of the droplet behavior opting for a continuous film model. Here, a phenomenological model, following, in a Lagrangian approach, the evolution of the single droplets from the impinging to the onset of rivulets, is developed to simulate the performances of super-hydrophobic surfaces in icing application. Possible rebound and droplet spread on the impact, coalescence, single ice bead formation and droplet to rivulet transition are taken into account. The first validation shows how the models are able to predict the anti-icing capability of a super-hydrophobic surface coupled with a heating system.

PurposeThis paper presents an analysis of short-term (2025) scenarios for noise emission from civil air traffic in airport areas.MethodsFlight movements and noise levels at a given airport are predicted using a web-data-informed methodology based on the ECAC Doc.29 model. This methodology, developed by the authors in a previous work, relies on the collection and processing of air traffic web data to reconstruct flight events to be fed into the ECAC model. Three new elements have been included: i) topographic information from digital elevation models, ii) a fleet substitution algorithm to estimate the impact of newer aircraft, and iii) a generator of flight events to simulate the expected traffic increase.ResultsThe effects of these elements are observed in 2025 scenarios for the airports of London Heathrow, Frankfurt and Vienna-Schwechat. The results quantify the noise reduction from new aircraft and its increment due to the air traffic growth forecast by EUROCONTROL.

In spark-ignition (SI) engines, the achievement of a fast combustion with low cycle-to-cycle variation is highly dependent on the successful initiation of a flame kernel from the spark plug. Its growth can be sped up by increasing the electrical energy supply, but at the cost of higher plug wear, whereas too little energy may result in an ignition failure. Therefore, knowledge of the minimum ignition energy (MIE) of a fuel/air mixture is of key importance to guarantee a proper combustion process at minimal cost. To model the MIE several approaches have been proposed in literature, primarily derived from the experiments conducted by Lewis and Von Elbe and their resulting theory of quenching distances. However, these approaches appear in conflict with more recent experimental outcomes, and the impact of the ignition device is neglected. This work proposes a novel approach for modelling the MIE, which is based on a flame kernel expansion model recently proposed in another paper. In this approach, the proposed model, which has general validity, is specialized to the particular case of the estimation of the MIE, supplied via an electrical breakdown. A model advancement is also included that consists in the quantification, albeit at a preliminary level, of the impact of different gap distances and spark plug quenching effects on the flame kernel development. The results are validated against literature models and experimental data for two fuels, propane and hydrogen, and multiple equivalence ratios. In contrast with the noticeable MIE overestimation of literature models, for propane the proposed approach leads to better results compared to the experiments. Instead, for hydrogen a tendency towards a MIE underestimation is observed, especially for lean mixtures. The model is also tested for SI-engine-relevant conditions, showing satisfactory overall trends. The key source of error seems related to the very complex kernel-electrode interaction, the modelling of which will be improved in future developments.

This work presents a simple and effective phenomenological model for the prediction of the early growth of the flame kernel in SI engines, including its initiation as a result of the electrical breakdown of the fuel/air mixture between the spark plug electrodes. The present model aims to provide an improved description of the ignition-affected early phases of flame kernel development compared to the majority of models currently available in literature. In particular, these models focus on electrical energy supply and turbulence, whereas the stretch-induced kernel growth slowdown is quantified with linear models that are inconsistent with the small kernel radius. For the flame kernel initiation, this model replaces the current methods that rely on 1D heat diffusion within a plasma column with a more consistent analysis of post-breakdown conditions. Concerning the kernel growth, the present model couples the mass and energy conservation equations of a spherical kernel with the species and temperature profiles outside of it. This combination leads to a non-linear description of the flame stretch, according to which the kernel development is controlled by the Lewis-number-dependent balance between the heat gained via combustion and the heat lost via thermal diffusion. As a result, the kernel temperature differs from the adiabatic flame temperature, causing the laminar flame speed to change from its adiabatic value and ultimately affecting the overall kernel development. Kernel growth predictions are conducted for laminar flames and compared to literature data, showing a satisfactory agreement and highlighting the ability to describe the stretch-induced kernel slowdown, up to its possible extinction. A good agreement with literature data is also obtained for kernel expansions under moderately turbulent conditions, typical of internal combustion engines. The simple formulation of the present model enables swift integration into phenomenological combustion models for sparkignition engines, while simultaneously offering useful insight into the early kernel development even for CFD-based approaches.

Background Stress echocardiography (SE) has an established role in evidence-based guidelines, but recently its breadth and variety of applications have extended well beyond coronary artery disease (CAD). We lack a prospective research study of SE applications, in and beyond CAD, also considering a variety of signs in addition to regional wall motion abnormalities. Methods In a prospective, multicenter, international, observational study design, > 100 certified high-volume SE labs (initially from Italy, Brazil, Hungary, and Serbia) will be networked with an organized system of clinical, laboratory and imaging data collection at the time of physical or pharmacological SE, with structured follow-up information. The study is endorsed by the Italian Society of Cardiovascular Echography and organized in 10 subprojects focusing on: contractile reserve for prediction of cardiac resynchronization or medical therapy response; stress B-lines in heart failure; hypertrophic cardiomyopathy; heart failure with preserved ejection fraction; mitral regurgitation after either transcatheter or surgical aortic valve replacement; outdoor SE in extreme physiology; right ventricular contractile reserve in repaired Tetralogy of Fallot; suspected or initial pulmonary arterial hypertension; coronary flow velocity, left ventricular elastance reserve and B-lines in known or suspected CAD; identification of subclinical familial disease in genotype-positive, phenotype- negative healthy relatives of inherited disease (such as hypertrophic cardiomyopathy). Results We expect to recruit about 10,000 patients over a 5-year period (2016-2020), with sample sizes ranging from 5,000 for coronary flow velocity/ left ventricular elastance/ B-lines in CAD to around 250 for hypertrophic cardiomyopathy or repaired Tetralogy of Fallot. This data-base will allow to investigate technical questions such as feasibility and reproducibility of various SE parameters and to assess their prognostic value in different clinical scenarios. Conclusions The study will create the cultural, informatic and scientific infrastructure connecting high-volume, accredited SE labs, sharing common criteria of indication, execution, reporting and image storage of SE to obtain original safety, feasibility, and outcome data in evidence-poor diagnostic fields, also outside the established core application of SE in CAD based on regional wall motion abnormalities. The study will standardize procedures, validate emerging signs, and integrate the new information with established knowledge, helping to build a next-generation SE lab without inner walls.

The efficacy of non-invasive ventilation (NIV) in acute respiratory failure secondary to SARS-CoV-2 infection remains controversial. Current literature mainly examined efficacy, safety and potential predictors of NIV failure provided out of the intensive care unit (ICU). On the contrary, the outcomes of ICU patients, intubated after NIV failure, remain to be explored. The aims of the present study are: (1) investigating in-hospital mortality in coronavirus disease 2019 (COVID-19) ICU patients receiving endotracheal intubation after NIV failure and (2) assessing whether the length of NIV application affects patient survival. This observational multicenter study included all consecutive COVID-19 adult patients, admitted into the twenty-five ICUs of the COVID-19 VENETO ICU network (February–April 2020), who underwent endotracheal intubation after NIV failure. Among the 704 patients admitted to ICU during the study period, 280 (40%) presented the inclusion criteria and were enrolled. The median age was 69 [60–76] years; 219 patients (78%) were male. In-hospital mortality was 43%. Only the length of NIV application before ICU admission (OR 2.03 (95% CI 1.06–4.98), p  = 0.03) and age (OR 1.18 (95% CI 1.04–1.33), p  < 0.01) were identified as independent risk factors of in-hospital mortality; whilst the length of NIV after ICU admission did not affect patient outcome. In-hospital mortality of ICU patients intubated after NIV failure was 43%. Days on NIV before ICU admission and age were assessed to be potential risk factors of greater in-hospital mortality.

Background Pathophysiological features of coronavirus disease 2019-associated acute respiratory distress syndrome (COVID-19 ARDS) were indicated to be somewhat different from those described in nonCOVID-19 ARDS, because of relatively preserved compliance of the respiratory system despite marked hypoxemia. We aim ascertaining whether respiratory system static compliance (Crs), driving pressure (DP), and tidal volume normalized for ideal body weight (VT/kg IBW) at the 1st day of controlled mechanical ventilation are associated with intensive care unit (ICU) mortality in COVID-19 ARDS. Methods Observational multicenter cohort study. All consecutive COVID-19 adult patients admitted to 25 ICUs belonging to the COVID-19 VENETO ICU network (February 28th–April 28th, 2020), who received controlled mechanical ventilation, were screened. Only patients fulfilling ARDS criteria and with complete records of Crs, DP and VT/kg IBW within the 1st day of controlled mechanical ventilation were included. Crs, DP and VT/kg IBW were collected in sedated, paralyzed and supine patients. Results A total of 704 COVID-19 patients were screened and 241 enrolled. Seventy-one patients (29%) died in ICU. The logistic regression analysis showed that: (1) Crs was not linearly associated with ICU mortality ( p value for nonlinearity = 0.01), with a greater risk of death for values < 48 ml/cmH 2 O; (2) the association between DP and ICU mortality was linear ( p value for nonlinearity = 0.68), and increasing DP from 10 to 14 cmH 2 O caused significant higher odds of in-ICU death (OR 1.45, 95% CI 1.06–1.99); (3) VT/kg IBW was not associated with a significant increase of the risk of death (OR 0.92, 95% CI 0.55–1.52). Multivariable analysis confirmed these findings. Conclusions Crs < 48 ml/cmH 2 O was associated with ICU mortality, while DP was linearly associated with mortality. DP should be kept as low as possible, even in the case of relatively preserved Crs, irrespective of VT/kg IBW, to reduce the risk of death.

This paper introduces a custom-built low-cost camera ring device designed for automatic cast synthesis, able to accurately and instantly scan body parts. The scanned mesh will be used as a backbone model for the cast design and 3D printing. The system is based on the multi-view active stereo principle and it is composed of a circular array of 16 synchronized cameras (Fig. 1) and 4 equally distributed IR pseudo-random laser pattern projectors. We employ a custom multi-view stereo reconstruction pipeline based on (Schönberger et al., 2016), which guarantees optimal results without the downsides of the supervised data-driven multi-view stereo algorithms, i.e. data collection and ground truth labeling. Additionally, inspired by (Duda and Frese, 2018), we propose a novel, automated calibration system to extract intrinsic and extrinsic camera parameters which are required to perform robust multi-view stereo reconstructions.

Approximating the stationary probability of a state in a Markov chain through Markov chain Monte Carlo techniques is, in general, inefficient. Standard random walk approaches require Õ(τ/π(v)) operations to approximate the probability π(v) of a state v in a chain with mixing time τ, and even the best available techniques still have complexity Õ(τ1.5/π(v)0.5); and since these complexities depend inversely on π(v), they can grow beyond any bound in the size of the chain or in its mixing time. In this paper we show that, for time-reversible Markov chains, there exists a simple randomized approximation algorithm that breaks this “small-π(v) barrier”.

Hydropower remains a key renewable energy source in the pursuit of the decarbonization of the economy, although the relatively high potential impact of the hydro-morphological alterations it may cause poses significant concerns for aquatic ecosystems. In the last years, new technologies and practices have been increasingly adopted to minimize the impacts of hydropower plants, while improving efficiency and flexibility of energy generation. The overall effect of these innovations may be a more sustainable design and operation of hydropower, striking a better balance between the objectives of decarbonization and ecosystem protection. This contribution presents and discusses a few representative examples of hydropower installations from companies in Italy, France, Switzerland, Belgium and the USA, where solutions have been adopted in this direction. The case studies cover (1) ecologically improved and low head hydropower converters (Vortex turbine, Hydrostatic Pressure Machine, VLH and Girard-optimized turbines, hydrokinetic turbines), hydropeaking reduction (2) new control systems, governors and digitalization, (3) hydropower as a strategy for local sustainable development and (4) energy recovery in existing hydraulic infrastructures and aqueducts. It was found that better-governing systems can extend the life span of runners, for example avoiding the runner uplift during a trip. Digitalization can improve efficiency by 1.2%. New sustainable practices and turbines with better ecological behavior can minimize environmental impacts, like the reduction of fish mortality, improvement of fish habitat availability, reduction of oil for lubrication purposes and generation of economic incomes for local development. The use of existing structures reduces the total installation cost: examples are the total saving of 277 €/kW by reusing irrigation pipes and reservoirs, or the reduction of the investment period from 9 years to 6 years by turbining the environmental flow. Innovative low head hydropower converters can exhibit good ecological behavior, with reduced costs (<5000 €/kW) especially when installed in existing weirs. Results are discussed, contextualized and generalized to provide engineering data and tools to support future realizations of similar case studies; normalized costs, efficiency improvement, best practices and new technologies are discussed.