7 resultados para Raster scanning

em Universidad Politécnica de Madrid


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Cold-drawn steel rods and wires retain significant residual stresses as a consequence of the manufacturing process. These residual stresses are known to be detrimental for the mechanical properties of the wires and their durability in aggressive environments. Steel makers are aware of the problem and have developed post-drawing processes to try and reduce the residual stresses on the wires. The present authors have studied this problem for a number of years and have performed a detailed characterization of the residual stress state inside cold-drawn rods, including both experimental and numerical techniques. High-energy synchrotron sources have been particularly useful for this research. The results have shown how residual stresses evolve as a consequence of cold-drawing and how they change with subsequent post-drawing treatments. The authors have been able to measure for the first time a complete residual strain profile along the diameter in both phases (ferrite and cementite) of a cold-drawn steel rod.

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El paquete raster proporciona un gran número de funciones para procesar datos geográficos de tipo raster. El diseño de este paquete, basado en clases S4, hace el análisis de estos datos más amigable al usuario. También ha ocasionado el desarrollo de paquetes más específicos para trabajar con datos raster en R. rasterVis proporciona un conjunto de métodos de visualización e interacción gráfica, desde gráficos de nivel y contorno, histogramas o matrices de dispersión, hasta gráficos apropiados para datos espacio-temporales. gdistance proporciona nuevas clases para cálculos basados en rutas y movimientos a través de espacios discretizados. Implementa métodos como la distancia de coste e introduce métodos recientemente desarrollados basados en caminos aleatorios. En la charla se explicará el diseño del paquete raster y se demostrará las posibilidades que ofrecen estos paquetes con ejemplos concretos

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The objective of this work is to non-destructively determine the residual stress profile in the bulk of two characteristic types of alumina-based composites, with the aim of improving their durability and structural integrity.

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La mayoría de las aplicaciones forestales del escaneo laser aerotransportado (ALS, del inglés airborne laser scanning) requieren la integración y uso simultaneo de diversas fuentes de datos, con el propósito de conseguir diversos objetivos. Los proyectos basados en sensores remotos normalmente consisten en aumentar la escala de estudio progresivamente a lo largo de varias fases de fusión de datos: desde la información más detallada obtenida sobre un área limitada (la parcela de campo), hasta una respuesta general de la cubierta forestal detectada a distancia de forma más incierta pero cubriendo un área mucho más amplia (la extensión cubierta por el vuelo o el satélite). Todas las fuentes de datos necesitan en ultimo termino basarse en las tecnologías de sistemas de navegación global por satélite (GNSS, del inglés global navigation satellite systems), las cuales son especialmente erróneas al operar por debajo del dosel forestal. Otras etapas adicionales de procesamiento, como la ortorectificación, también pueden verse afectadas por la presencia de vegetación, deteriorando la exactitud de las coordenadas de referencia de las imágenes ópticas. Todos estos errores introducen ruido en los modelos, ya que los predictores se desplazan de la posición real donde se sitúa su variable respuesta. El grado por el que las estimaciones forestales se ven afectadas depende de la dispersión espacial de las variables involucradas, y también de la escala utilizada en cada caso. Esta tesis revisa las fuentes de error posicional que pueden afectar a los diversos datos de entrada involucrados en un proyecto de inventario forestal basado en teledetección ALS, y como las propiedades del dosel forestal en sí afecta a su magnitud, aconsejando en consecuencia métodos para su reducción. También se incluye una discusión sobre las formas más apropiadas de medir exactitud y precisión en cada caso, y como los errores de posicionamiento de hecho afectan a la calidad de las estimaciones, con vistas a una planificación eficiente de la adquisición de los datos. La optimización final en el posicionamiento GNSS y de la radiometría del sensor óptico permitió detectar la importancia de este ultimo en la predicción de la desidad relativa de un bosque monoespecífico de Pinus sylvestris L. ABSTRACT Most forestry applications of airborne laser scanning (ALS) require the integration and simultaneous use of various data sources, pursuing a variety of different objectives. Projects based on remotely-sensed data generally consist in upscaling data fusion stages: from the most detailed information obtained for a limited area (field plot) to a more uncertain forest response sensed over a larger extent (airborne and satellite swath). All data sources ultimately rely on global navigation satellite systems (GNSS), which are especially error-prone when operating under forest canopies. Other additional processing stages, such as orthorectification, may as well be affected by vegetation, hence deteriorating the accuracy of optical imagery’s reference coordinates. These errors introduce noise to the models, as predictors displace from their corresponding response. The degree to which forest estimations are affected depends on the spatial dispersion of the variables involved and the scale used. This thesis reviews the sources of positioning errors which may affect the different inputs involved in an ALS-assisted forest inventory project, and how the properties of the forest canopy itself affects their magnitude, advising on methods for diminishing them. It is also discussed how accuracy should be assessed, and how positioning errors actually affect forest estimation, toward a cost-efficient planning for data acquisition. The final optimization in positioning the GNSS and optical image allowed to detect the importance of the latter in predicting relative density in a monospecific Pinus sylvestris L. forest.

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A system dedicated to the optical transmittance characterization of Fresnel lenses has been developed at NREL, in collaboration with the UPM. The system quantifies the optical efficiency of the lens by generating a performance map. The shape of the focused spot may also be analyzed to understand change in the lens performance. The primary instrument components (lasers and CCD detector) have been characterized to confirm their capability for performing optical transmittance measurements. Measurements performed on SoG and PMMA lenses subject to a variety of indoor conditions (e.g., UV and damp heat) identified differences in the optical efficiency of the evaluated lenses, demonstrating the ability of the Scanning Lens Instrument (SLI) to distinguish between the aged lenses.

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Canonical Correlation Analysis for Interpreting Airborne Laser Scanning Metrics along the Lorenz Curve of Tree Size Inequality

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The purpose of this study was to compare a number of state-of-the-art methods in airborne laser scan- ning (ALS) remote sensing with regards to their capacity to describe tree size inequality and other indi- cators related to forest structure. The indicators chosen were based on the analysis of the Lorenz curve: Gini coefficient ( GC ), Lorenz asymmetry ( LA ), the proportions of basal area ( BALM ) and stem density ( NSLM ) stocked above the mean quadratic diameter. Each method belonged to one of these estimation strategies: (A) estimating indicators directly; (B) estimating the whole Lorenz curve; or (C) estimating a complete tree list. Across these strategies, the most popular statistical methods for area-based approach (ABA) were used: regression, random forest (RF), and nearest neighbour imputation. The latter included distance metrics based on either RF (NN–RF) or most similar neighbour (MSN). In the case of tree list esti- mation, methods based on individual tree detection (ITD) and semi-ITD, both combined with MSN impu- tation, were also studied. The most accurate method was direct estimation by best subset regression, which obtained the lowest cross-validated coefficients of variation of their root mean squared error CV(RMSE) for most indicators: GC (16.80%), LA (8.76%), BALM (8.80%) and NSLM (14.60%). Similar figures [CV(RMSE) 16.09%, 10.49%, 10.93% and 14.07%, respectively] were obtained by MSN imputation of tree lists by ABA, a method that also showed a number of additional advantages, such as better distributing the residual variance along the predictive range. In light of our results, ITD approaches may be clearly inferior to ABA with regards to describing the structural properties related to tree size inequality in for- ested areas.