Tubular and Sector Heat Pipes with Interconnected Branches for Gas Turbine and/or Compressor Cooling

Designing turbines for either aerospace or power production is a daunting task for any heat transfer scientist or engineer. Turbine designers are continuously pursuing better ways to convert the stored chemical energy in the fuel into useful work with maximum efficiency. Based on thermodynamic principles, one way to improve thermal efficiency is to increase the turbine inlet pressure and temperature. Generally, the inlet temperature may exceed the capabilities of standard materials for safe and long-life operation of the turbine. Next generation propulsion systems, whether for new supersonic transport or for improving existing aviation transport, will require more aggressive cooling system for many hot-gas-path components of the turbine. Heat pipe technology offers a possible cooling technique for the structures exposed to the high heat fluxes. Hence, the objective of this dissertation is to develop new radially rotating heat pipe systems that integrate multiple rotating miniature heat pipes with a common reservoir for a more effective and practical solution to turbine or compressor cooling. In this dissertation, two radially rotating miniature heat pipes and two sector heat pipes are analyzed and studied by utilizing suitable fluid flow and heat transfer modeling along with experimental tests. Analytical solutions for the film thickness and the lengthwise vapor temperature distribution for a single heat pipe are derived. Experimental tests on single radially rotating miniature heat pipes and sector heat pipes are undertaken with different important parameters and the manner in which these parameters affect heat pipe operation. Analytical and experimental studies have proven that the radially rotating miniature heat pipes have an incredibly high effective thermal conductance and an enormous heat transfer capability. Concurrently, the heat pipe has an uncomplicated structure and relatively low manufacturing costs. The heat pipe can also resist strong vibrations and is well suited for a high temperature environment. Hence, the heat pipes with a common reservoir make incorporation of heat pipes into turbo-machinery much more feasible and cost effective.

Fuel level sensor based on polymer optical fiber Bragg gratings for aircraft applications

Safety in civil aviation is increasingly important due to the increase in flight routes and their more challenging nature. Like other important systems in aircraft, fuel level monitoring is always a technical challenge. The most frequently used level sensors in aircraft fuel systems are based on capacitive, ultrasonic and electric techniques, however they suffer from intrinsic safety concerns in explosive environments combined with issues relating to reliability and maintainability. In the last few years, optical fiber liquid level sensors (OFLLSs) have been reported to be safe and reliable and present many advantages for aircraft fuel measurement. Different OFLLSs have been developed, such as the pressure type, float type, optical radar type, TIR type and side-leaking type. Amongst these, many types of OFLLSs based on fiber gratings have been demonstrated. However, these sensors have not been commercialized because they exhibit some drawbacks: low sensitivity, limited range, long-term instability, or limited resolution. In addition, any sensors that involve direct interaction of the optical field with the fuel (either by launching light into the fuel tank or via the evanescent field of a fiber-guided mode) must be able to cope with the potential build up of contamination-often bacterial-on the optical surface. In this paper, a fuel level sensor based on microstructured polymer optical fiber Bragg gratings (mPOFBGs), including poly (methyl methacrylate) (PMMA) and TOPAS fibers, embedded in diaphragms is investigated in detail. The mPOFBGs are embedded in two different types of diaphragms and their performance is investigated with aviation fuel for the first time, in contrast to our previous works, where water was used. Our new system exhibits a high performance when compared with other previously published in the literature, making it a potentially useful tool for aircraft fuel monitoring.

La estrategia en la perdurabilidad empresarial. Un estudio de la segunda aerolínea más antigua del mundo: Avianca

Una de las principales dificultades que se presenta en Colombia, para el desarrollo económico y social, está dada por la falta de sostenibilidad de la gran mayoría de empresas en el país. Por este motivo, este trabajo se ha concentrado en investigar este problema y brindar herramientas que ayuden a fomentar una cultura de perdurabilidad. Con este fin, se ha realizado un estudio acerca de Avianca, una empresa referente en el país en lo que respecta a la perdurabilidad, posicionamiento y estrategia, pues, a lo largo de sus casi cien años de historia, ha superado retos y circunstancias, que, de haber actuado de otra manera, habrían podido llevarla a su fin.

Cloud Base Height Measurement System Based on Stereo Vision with Automatic Calibration

Clouds are important in weather prediction, climate studies and aviation safety. Important parameters include cloud height, type and cover percentage. In this paper, the recent improvements in the development of a low-cost cloud height measurement setup are described. It is based on stereo vision with consumer digital cameras. The cameras positioning is calibrated using the position of stars in the night sky. An experimental uncertainty analysis of the calibration parameters is performed. Cloud height measurement results are presented and compared with LIDAR measurements.

Normalização automática de descrições de hotéis

As descrições de produtos turísticos na área da hotelaria, aviação, rent-a-car e pacotes de férias baseiam-se sobretudo em descrições textuais em língua natural muito heterogénea com estilos, apresentações e conteúdos muito diferentes entre si. Uma vez que o sector do turismo é bastante dinâmico e que os seus produtos e ofertas estão constantemente em alteração, o tratamento manual de normalização de toda essa informação não é possível. Neste trabalho construiu-se um protótipo que permite a classificação e extracção automática de informação a partir de descrições de produtos de turismo. Inicialmente a informação é classificada quanto ao tipo. Seguidamente são extraídos os elementos relevantes de cada tipo e gerados objectos facilmente computáveis. Sobre os objectos extraídos, o protótipo com recurso a modelos de textos e imagens gera automaticamente descrições normalizadas e orientadas a um determinado mercado. Esta versatilidade permite um novo conjunto de serviços na promoção e venda dos produtos que seria impossível implementar com a informação original. Este protótipo, embora possa ser aplicado a outros domínios, foi avaliado na normalização da descrição de hotéis. As frases descritivas do hotel são classificadas consoante o seu tipo (Local, Serviços e/ou Equipamento) através de um algoritmo de aprendizagem automática que obtém valores médios de cobertura de 96% e precisão de 72%. A cobertura foi considerada a medida mais importante uma vez que a sua maximização permite que não se percam frases para processamentos posteriores. Este trabalho permitiu também a construção e população de uma base de dados de hotéis que possibilita a pesquisa de hotéis pelas suas características. Esta funcionalidade não seria possível utilizando os conteúdos originais. ABSTRACT: The description of tourism products, like hotel, aviation, rent-a-car and holiday packages, is strongly supported on natural language expressions. Due to the extent of tourism offers and considering the high dynamics in the tourism sector, manual data management is not a reliable or scalable solution. Offer descriptions - in the order of thousands - are structured in different ways, possibly comprising different languages, complementing and/or overlap one another. This work aims at creating a prototype for the automatic classification and extraction of relevant knowledge from tourism-related text expressions. Captured knowledge is represented in a normalized/standard format to enable new services based on this information in order to promote and sale tourism products that would be impossible to implement with the raw information. Although it could be applied to other areas, this prototype was evaluated in the normalization of hotel descriptions. Hotels descriptive sentences are classified according their type (Location, Services and/or Equipment) using a machine learning algorithm. The built setting obtained an average recall of 96% and precision of 72%. Recall considered the most important measure of performance since its maximization allows that sentences were not lost in further processes. As a side product a database of hotels was built and populated with search facilities on its characteristics. This ability would not be possible using the original contents.