Aplicabilidad de la termografría para la inspección de los edificios rurales: Caso de una comarca española

This article is aimed a! establishing the chance of applying the infrared thermography techniquefor !he examination of rural buildings. The results from field worh are collected. The next issues were determined by thermography: Hidden materials and elements; dgerences behveen different materials; location of crach; localion of slructures; localion ofhumid areas; points ofheat losses and areas where the hot air is accumulated. It ispossible lo inspect a high number of buildings in a short time and get valuable results. The time where the inspection should be done is dependen1 on (he type of building: in (he evening for buildings with bearing walls and at daybreak for buildings with interior structures.En este articulo se pretende verijicar la posibilidad de utilización de la termografía infrarrojn como técnica de inspección del estado de los edificios rurales. Se reúnen los resultados obtenidos en varios trabajos de campo. Mediante esta técnica se puede analizar: localización de materiales y elementos ocultos, localización de diferentes materiales en fachada, presencia de grietas, localización de estructuras, localización de zonas húmedas y puntos de pérdidas de calot Esta técnica permite inspeccionar un alto número de edificios en un breve período de tiempo, proporcionando resultados válidos. Los resultados muestran que en función del tipo de edijicio las inspecciones se deben realizar en diferentes momeritos del dia: por la noche en los edificios con muros de catga y al amanecer en edificios con estructuras internas

Estudio de la maquinabilidad de aleaciones de aluminio-cobre

El cometido principal es establecer una metodología para analizar y evaluar la maquinabilidad de una aleación aluminio-cobre mecanizada en torno utilizando los recursos disponibles en los laboratorios de materiales y producción. El estudio se realizó mediante la medida del caudal de viruta, el dimensionado de la herramienta durante el proceso y su análisis microscópico. También se estudió el posible desgaste de la herramienta y qué factores han podido incrementar o disminuir dicho valor. Se han mecanizado ocho barras de una aleación 2030 T4 con dos herramientas de corte idénticas de carburo de wolframio. Esto permite usar cada filo de corte cada dos pasadas. No se obtuvo una medida de la maquinabilidad, sin embargo, el análisis de las variables de entrada y de salida concluye con la verificación de una buena maquinabilidad del material. Este estudio puede servir de referencia para el estudio de otras aleaciones de aluminio de forja

Tropical tree growth driven by dry-season climate variability

Interannual variability in the global land carbon sink is strongly related to variations in tropical temperature and rainfall. This association suggests an important role for moisture-driven fluctuations in tropical vegetation productivity, but empirical evidence to quantify the responsible ecological processes is missing. Such evidence can be obtained from tree-ring data that quantify variability in a major vegetation productivity component: woody biomass growth. Here we compile a pantropical tree-ring network to show that annual woody biomass growth increases primarily with dry-season precipitation and decreases with dry-season maximum temperature. The strength of these dry-season climate responses varies among sites, as reflected in four robust and distinct climate response groups of tropical tree growth derived from clustering. Using cluster and regression analyses, we find that dry-season climate responses are amplified in regions that are drier, hotter and more climatically variable. These amplification patterns suggest that projected global warming will probably aggravate drought-induced declines in annual tropical vegetation productivity. Our study reveals a previously underappreciated role of dry-season climate variability in driving the dynamics of tropical vegetation productivity and consequently in influencing the land carbon sink.We acknowledge financial support to the co-authors provided by Agencia Nacional de Promoción Científica y Tecnológica, Argentina (PICT 2014-2797) to M.E.F.; Alberta Mennega Stichting to P.G.; BBVA Foundation to H.A.M. and J.J.C.; Belspo BRAIN project: BR/143/A3/HERBAXYLAREDD to H.B.; Confederação da Agricultura e Pecuária do Brasil - CNA to C.F.; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES, Brazil (PDSE 15011/13-5 to M.A.P.; 88881.135931/2016-01 to C.F.; 88887.199858/2018-00 to G.A.-P.; Finance Code 001 for all Brazilian collaborators); Conselho Nacional de Desenvolvimento Científico e Tecnológico - CNPq, Brazil (ENV 42 to O.D.; 1009/4785031-2 to G.C.; 311874/2017-7 to J.S.); CONACYT-CB-2016-283134 to J.V.-D.; CONICET to F.A.R.; CUOMO FOUNDATION (IPCC scholarship) to M.M.; Deutsche Forschungsgemeinschaft - DFG (BR 1895/15-1 to A.B.; BR 1895/23-1 to A.B.; BR 1895/29-1 to A.B.; BR 1895/24-1 to M.M.); DGD-RMCA PilotMAB to B.T.; Dirección General de Asuntos del Personal Académico of the UNAM (Mexico) to R.B.; Elsa-Neumann-Scholarship of the Federal State of Berlin to F.S.; EMBRAPA Brazilian Agricultural Research Corporation to C.F.; Equatorian Dirección de Investigación UNL (21-DI-FARNR-2019) to D.P.-C.; São Paulo Research Foundation FAPESP (2009/53951-7 to M.T.-F.; 2012/50457-4 to G.C.; 2018/01847‐0 to P.G.; 2018/24514-7 to J.R.V.A.; 2019/08783-0 to G.M.L.; 2019/27110-7 to C.F.); FAPESP-NERC 18/50080-4 to G.C.; FAPITEC/SE/FUNTEC no. 01/2011 to M.A.P.; Fulbright Fellowship to B.J.E.; German Academic Exchange Service (DAAD) to M.I. and M.R.; German Ministry of Education, Science, Research, and Technology (FRG 0339638) to O.D.; ICRAF through the Forests, Trees, and Agroforestry research programme of the CGIAR to M.M.; Inter-American Institute for Global Change Research (IAI-SGP-CRA 2047) to J.V.-D.; International Foundation for Science (D/5466-1) to M.I.; Lamont Climate Center to B.M.B.; Miquelfonds to P.G.; National Geographic Global Exploration Fund (GEFNE80-13) to I.R.; USA’s National Science Foundation NSF (IBN-9801287 to A.J.L.; GER 9553623 and a postdoctoral fellowship to B.J.E.); NSF P2C2 (AGS-1501321) to A.C.B., D.G.-S. and G.A.-P.; NSF-FAPESP PIRE 2017/50085-3 to M.T.-F., G.C. and G.M.L.; NUFFIC-NICHE programme (HEART project) to B.K., E.M., J.H.S., J.N. and R. Vinya; Peru ‘s CONCYTEC and World Bank (043-2019-FONDECYT-BM-INC.INV.) to J.G.I.; Peru’s Fondo Nacional de Desarrollo Científico, Tecnológico y de Innovación Tecnológica (FONDECYT-BM-INC.INV 039-2019) to E.J.R.-R. and M.E.F.; Programa Bosques Andinos - HELVETAS Swiss Intercooperation to M.E.F.; Programa Nacional de Becas y Crédito Educativo - PRONABEC to J.G.I.; Schlumberger Foundation Faculty for the Future to J.N.; Sigma Xi to A.J.L.; Smithsonian Tropical Research Institute to R. Alfaro-Sánchez.; Spanish Ministry of Foreign Affairs AECID (11-CAP2-1730) to H.A.M. and J.J.C.; UK NERC grant NE/K01353X/1 to E.G.Peer reviewe

A revision of the flutter margin method to predict in real-time the limit cycle oscillations onset speed with structural freeplay present in the plunge axis

Computational fluid dynamic and order reducing methods have been extensively applied to predict the flutter onset speed of several types of aircrafts. However, the accuracy required by certification standards still ascribes flight testing as the only method available that safely validates the flight envelope of an aircraft. In particular, free-flutter conditions must be demonstrated in the target flight envelope, and several methods have been developed to determine the flutter onset speed in real-time when expanding the envelope during flight testing. Among the methods, the damping versus velocity technique combined with a flutter margin implementation remains the most common technique used for envelope expansion. Even with the popularity and ‘‘easy to implement’’ characteristics of this method, several shortcomings can adversely affect the identification of non-stable conditions during envelope expansion. Notably, the limit cycle oscillations conditions, distinct from flutter, cannot be accurately identified. This study proposes to apply a similar methodology to the flutter margin to anticipate limit cycle oscillations associated with freeplay in the plunge axis of a bi-dimensional airfoil that is aeroelastically representative of the tested aircraft. Analytical considerations are conducted to support this new approach, and a computer model is used to validate the proposed methodology

Environmental effect compensation for damage detection in structures using artificial neural networks and chirplet transform

One of the open problems to implement Structural Health Monitoring techni ques based on guided waves in real structures is the interference of the environme ntal effects in the damage diagnosis problem. This paper deals with the compensation of one of the envir onmental effects, the temperature. It is well known that the guided wave form is modified by temperature variation and causes errors in damage diagnosis. This happens because the waveform has an influence due to temperature changes of the same order tan he damage presence, which makes difficult to separate both effects in order to avoid false positives. Therefore it is necessary to quantify and compensate the temperature effect over the waveforms. There are several approaches to compensate the temperature effect such as Optimal Baseline Selection (OBS) or Baseline Signal Stretching (BSS). In this paper, the experimental data analysis consists on applying the Chirplet Transform (CT) to extract Environmental Sensitive Features (ESF) from raw data. Then, the measure of the environmental condition is related with the ESF training an ANN. The relati onship between the temperature and the ESF is captured by the ANN and then it can be use d to compensate the temperature effect in the guided wave data at a different temperat ure. When the ESF is compensated only the Damage Sensitive Feature (DSF) information is present in the experimental data acquired. Several tests were performed in a range of temperatures under damaged/undamaged conditions and used the experimental data to build and test the models. This method improves the benefits of the OBS(without the need of a big database of baselines, difficult to obtain in complex structures)with the wide range of applicability and simplicity of BSS. Another advantage of this method is its independency from structure arrangement and the type of sensors used for guided waves data acquisition because it is purely data driven. Moreover, it can be used for the simultaneous compensation of a variety of measurable environmental or operation conditions, which affects the guided wavedata acquisition, in example, temperatura and load compensation