July temperature (TJUL) and total annual precipitation (ANNP) are reconstructed to better understand the spatial and temporal patterns of change in North America over the last 2,000 years using pollen databases. Using a customized application in R, the reconstructions use a composite averaging of multiple site reconstructions that show a distinct warmer Medieval Warm Period (MWP) compared to the colder Little Ice Age (LIA). Results show that, both multi-centennial scale periods are re- constructed as cooler than the last 50 years. Regional time series from several forested ecoregions show positive anomalies up to 0.6ºC during the MWP and anomalies up to -0.3ºC during the LIA. In order to test whether the TJUL reconstructions are biased to the modern calibration climate data, we show a distinct difference between the reconstructions when using station versus reanalysis-based modern TJUL fields. Reconstructions using station-based modern calibration data sets better reflect the centennial to multi-centennial scale climate variability as compared to the reanalysis-based modern calibration data sets that reveal a warm-bias. We justify the choice of the Whitmore et al. (2005) modern data set for large-scale pollen-based paleoclimate reconstructions. Finally we use Local Indicators of Spatial Association (LISA) to spatially filter the ANNP reconstructions in order to distinguish regional hydroclimate patterns from local site-specific conditions. Results show that a La Nina, positive North Atlantic Oscillation (+NAO) and positive Atlantic Multidecadal Oscillation (+AMO) state-like dominated both the MWP and Roman Warm Period (RWP), although the MWP was generally drier. In contrast, the Dark Ages Cold (DAC) period was likely dominated by El Nino, negative NAO and negative AMO state-like circulation. Minimum solar and high volcanic activity is likely to have contributed to more complex hydroclimate regional patterns during the LIA. The results presented in this dissertation can be used as benchmark data sets for future climate data-model comparisons in order to improve our understanding of natural climate variability during the past 2,000 years in the context of modern human-induced climate change.

Ce travail s’intéresse au problème de la rétroingénierie du son pour l’écoute active. Le format considéré correspond au CD audio. Le contenu musical est vu comme le résultat d’un enchaînement de la composition, l’enregistrement, le mixage et le mastering. L’inversion des deux dernières étapes constitue le fond du problème présent. Le signal audio est traité comme un mélange post-non-linéaire. Ainsi, le mélange est « décompressé » avant d'être « décomposé » en pistes audio. Le problème est abordé dans un contexte informé : l’inversion est accompagnée d'une information qui est spécifique à la production du contenu. De cette manière, la qualité de l’inversion est significativement améliorée. L’information est réduite de taille en se servant des méthodes de quantification, codage, et des faits sur la psychoacoustique. Les méthodes proposées s’appliquent en temps réel et montrent une complexité basse. Les résultats obtenus améliorent l’état de l’art et contribuent aux nouvelles connaissances. / This work deals with the problem of reverse audio engineering for active listening. The format under consideration corresponds to the audio CD. The musical content is viewed as the result of a concatenation of the composition, the recording, the mixing, and the mastering. The inversion of the two latter stages constitutes the core of the problem at hand. The audio signal is treated as a post-nonlinear mixture. Thus, the mixture is “decompressed” before being “decomposed” into audio tracks. The problem is tackled in an informed context: The inversion is accompanied by information which is specific to the content production. In this manner, the quality of the inversion is significantly improved. The information is reduced in size by the use of quantification and coding methods, and some facts on psychoacoustics. The proposed methods are applicable in real time and have a low complexity. The obtained results advance the state of the art and contribute new insights.

This thesis focuses on the development of a new method for the continuous<p>monitoring of civil engineering structures in order to locate small damages automatically. A<p>review of the very wide literature on Structural Health Monitoring (SHM) points first out that<p>the methods can be grouped in four categories based on their need or not of a numerical model,<p>as well as their need or not of information of the damaged structure to be applied. This state<p>of the art of the SHM methods highlights the requirement to reach each levels of SHM, which<p>is in particular for the localization of small damages in civil engineering structures the needs<p>for a non-model based output-only damage sensitive feature extraction technique. The origin of<p>the local sensitivity of strains to damages is also analyzed, which justifies their use for damage<p>localization.<p>A new method based on the modal filtering technique which consists in combining linearly<p>the sensor responses in a specific way to mimic a single degree of freedom system and which<p>was previously developed for damage detection is proposed. A very large network of dynamic<p>strain sensors is deployed on the structure and split into several independent local sensor networks.<p>Low computational cost and fast signal processing techniques are coupled to statistical<p>control charts for robust and fully automated damage localization.<p>The efficiency of the method is demonstrated using time-domain simulated data on a simply<p>supported beam and a three-dimensional bridge structure. The method is able to detect and<p>locate very small damages even in the presence of noise on the measurements and variability<p>of the baseline structure if strain sensors are used. The difficulty to locate damages from acceleration<p>sensors is also clearly illustrated. The most common classical methods for damage<p>localization are applied on the simply supported beam and the results show that the modal filtering<p>technique presents much better performances for an accurate localization of small damages<p>and is easier to automate.<p>An improvement of the modal filters method referred to as adaptive modal filters is next<p>proposed in order to enhance the ability to localize small damages, as well as to follow their<p>evolution through modal filters updating. Based on this study, a new damage sensitive feature<p>is proposed and is compared with other damage sensitive features to detect the damages with<p>modal filters to demonstrate its interest. These expectations are verified numerically with the<p>three-dimensional bridge structure, and the results show that the adaptation of the modal filters<p>increases the sensitivity of local filters to damages.<p>Experimental tests have been led first to check the feasibility of modal filters to detect damages<p>when they are used with accelerometers. Two case studies are considered. The first work<p>investigates the experimental damage detection of a small aircraft wing equipped with a network<p>of 15 accelerometers, one force transducer and excited with an electro-dynamic shaker. A<p>damage is introduced by replacing inspection panels with damaged panels. A modified version<p>of the modal filtering technique is applied and compared with the damage detection based principal<p>component analysis of FRFs as well as of transmissibilities. The three approaches succeed<p>in the damage detection but we illustrate the advantage of using the modal filtering algorithm as<p>well as of the new damage sensitive feature. The second experimental application aims at detecting<p>both linear and nonlinear damage scenarios using the responses of four accelerometers<p>installed on the three-storey frame structure previously developed and studied at Los Alamos<p>National Labs. In particular, modal filters are shown to be sensitive to both types of damages,<p>but cannot make the distinction between linear and nonlinear damages.<p>Finally, the new method is tested experimentally to locate damages by considering cheap<p>piezoelectric patches (PVDF) for dynamic strain measurements. Again, two case studies are investigated.<p>The first work investigates a small clamped-free steel plate equipped with 8 PVDFs sensors, and excited with a PZT patch. A small damage is introduced at different locations by<p>fixing a stiffener. The modal filters are applied on three local filters in order to locate damage.<p>Univariate control charts allow to locate automatically all the damage positions correctly.<p>The last experimental investigation is devoted to a 3.78m long I-steel beam equipped with 20<p>PVDFs sensors and excited with an electro-dynamic shaker. Again, a small stiffener is added to<p>mimic the effect of a small damage and five local filters are defined to locate the damage. The<p>damage is correctly located for several positions, and the interest of including measurements<p>under different environmental conditions for the baseline as well as overlapping the local filters<p>is illustrated.<p>The very nice results obtained with these first experimental applications of modal filters<p>based on strains show the real interest of this very low computational cost method for outputonly<p>non-model based automated damage localization of real structures. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished