Passive flexibility effect on oscillating foil energy harvester

It is well-known that structural flexibility enhances the performance of flapping foil propellers. There is, however, much less knowledge about the effect of deformability on the flow energy extraction capacity of flapping foils. Following our recent work on an oscillating foil energy harvesting device with prescribed foil deformations1, we investigate the fully-coupled dynamics of a flapping foil energy harvester with a passively deformable foil. Towards this end, we computationally study the dynamics of a foil with realistic internal structure (containing a rigid leading edge and a flexible trailing edge with a stiffener) in energy harvesting regime through a fluid-structure interaction scheme. To examine the effect of different levels of flexibility, various materials (ranging from metals such as copper to virtual materials with arbitrary elasticity and density) for the stiffener have been tested. With the virtual materials, the effects of Young’s modulus coefficient and density ratio have been studied. Our simulation results show that flexibility around the trailing edge could enhance the overall energy extraction performance. For example, with a copper stiffener, an increase of 32.2% in efficiency can be reached at high reduced frequency. The performance enhancement is achieved mostly in cases with low Young’s modulus coefficient and density ratio. A possible underlying mechanism is that the specific foil deformations in these cases encourage the generation and shedding of vortices from the foil leading edge, which is known to be beneficial to flow energy extraction

A Solution to the Ambiguity Problem in Depth Contouring

Depth contours on a chart are important for safe navigation. The ambiguity problem can appear when points of equal depth are joined in contouring. Unreasonable solutions may mistake a shallow area for a deep one, which could result in a potential danger for navigation. A solution is presented to solve the ambiguity problem using constrained lines formed by two shallow depths. The constrained lines are used to limit the joining of the points with equal depth. Experimental results demonstrate that the proposed solution can reduce the dangers of producing non-existent deep areas in bathymetric contouring.Las isobatas en una carta son importantes para la seguridad de la navegaciôn. El problema de ambiguedad puede aparecer cuando puntos de igual profundidad se unen en el trazado de la isobata. Soluciones no razonadas pueden confundir un area somera por una profunda, lo que podria resultar en un peligro potencial a la navegaciôn. Una soluciôn se présenta para resolver el problema de ambigüedad utilizando lineas forzadas formadas por dos profundidades s orneras. Las lineas forzadas se ut Uizan para limitar la union de puntos con igual profundidad. Los resultados expérimentales demuestran que la soluciôn propuesta puede reducir los peligros de producir areas profundas no existentes en los contornos batimétricos.Sur une carte, les isobathes sont importantes en ce qui concerne la sécurité de la navigation. Le problème de l'ambiguïté peut apparaître lorsque des points de profondeur égale se rejoignent sur le tracé de l'isobathe. Certaines solutions non fondées rationnellement peuvent prendre par erreur une zone peu profonde pour une zone profonde, ce qui peut entraîner un danger potentiel pour la navigation. Une solution est présentée pour résoudre le problème de l’ambiguïté en utilisant des lignes contraintes formées par deux faibles profondeurs. Les lignes contraintes sont utilisées pour limiter la réunion de points d’une égale profondeur. Des résultats expérimentaux ont montré que la solution proposée peut réduire les dangers liés à la création de zones profondes non existantes dans le tracé bathymétrique

Robust Training under Label Noise by Over-parameterization

Recently, over-parameterized deep networks, with increasingly more network parameters than training samples, have dominated the performances of modern machine learning. However, when the training data is corrupted, it has been well-known that over-parameterized networks tend to overfit and do not generalize. In this work, we propose a principled approach for robust training of over-parameterized deep networks in classification tasks where a proportion of training labels are corrupted. The main idea is yet very simple: label noise is sparse and incoherent with the network learned from clean data, so we model the noise and learn to separate it from the data. Specifically, we model the label noise via another sparse over-parameterization term, and exploit implicit algorithmic regularizations to recover and separate the underlying corruptions. Remarkably, when trained using such a simple method in practice, we demonstrate state-of-the-art test accuracy against label noise on a variety of real datasets. Furthermore, our experimental results are corroborated by theory on simplified linear models, showing that exact separation between sparse noise and low-rank data can be achieved under incoherent conditions. The work opens many interesting directions for improving over-parameterized models by using sparse over-parameterization and implicit regularization.Comment: 25 pages, 4 figures and 6 tables. Code is available at https://github.com/shengliu66/SO

Reducing the bottom-hole differential pressure by vortex and hydraulic jet methods

Reducing the bottom-hole differential pressure (BHDP) of a gas/oil well and so as to reduce the “chip hold-down effect” can significantly improve the rate of penetration (ROP). The fluid vortex and hydraulic jet methods are used to reduce the BHDP while the wellbore pressure is unchangeable to prevent wellbore instability. The depressurization theories of the two hydraulic pressure drawdown methods are studied. The structures, depressurization mechanism, depressurization capacity, and the current researches and developments of the hydraulic pressure drawdown tools, including the vortex tools and the jet hydraulic pressure drawdown tools (JHPDTs), are analyzed. Using field tests and flow field numerical calculation methods, the key factors which affect depressurization capacity of the vortex tools and the JHPDTs, and the design principles of the vortex bit and the jet pump bit are proposed. Different depressurization methods and structures are simulated, which shows the vortex and jet pump combination bit with 106 mm distance is preferable

2,3,4,6-Tetra-O-acetyl-1-O-(4-methoxy­cinnamo­yl)-β-d-glucopyran­ose

Mol­ecules of the title compound, C24H28O12, are linked by inter­molecular C—H⋯O hydrogen bonds. Bond lengths and angles are normal

Risk factors for high-altitude headache upon acute high-altitude exposure at 3700 m in young Chinese men: a cohort study.

BackgroundThis prospective and observational study aimed to identify demographic, physiological and psychological risk factors associated with high-altitude headache (HAH) upon acute high-altitude exposure.MethodsEight hundred fifty subjects ascended by plane to 3700 m above Chengdu (500 m) over a period of two hours. Structured Case Report Form (CRF) questionnaires were used to record demographic information, physiological examinations, psychological scale, and symptoms including headache and insomnia a week before ascending and within 24 hours after arrival at 3700 m. Binary logistic regression models were used to analyze the risk factors for HAH.ResultsThe incidence of HAH was 73.3%. Age (p =0.011), physical labor intensity (PLI) (p =0.044), primary headache history (p <0.001), insomnia (p <0.001), arterial oxygen saturation (SaO2) (p =0.001), heart rate (HR) (p =0.002), the Self-Rating Anxiety Scale (SAS) (p <0.001), and the Epworth Sleepiness Scale (ESS) (p <0.001) were significantly different between HAH and non-HAH groups. Logistic regression models identified primary headache history, insomnia, low SaO2, high HR and SAS as independent risk factors for HAH.ConclusionsInsomnia, primary headache history, low SaO2, high HR, and high SAS score are the risk factors for HAH. Our findings will provide novel avenues for the study, prevention and treatment of HAH