Fossil pollen record of composite sediment core TMD from Tso Moriri, analysis of modern surface pollen samples, mean annual precipitation reconstruction, and digitisation and recalibration of different discussed palaeoclimate proxy records

This paper presents a new fossil pollen record from Tso Moriri (32°54'N, 78°19'E, 4512 m a.s.l.) and seeks to reconstruct changes in mean annual precipitation (MAP) during the last 12,000 years. This high-alpine lake occupies an area of 140 km**2 in a glacial-tectonic valley in the northwestern Himalaya. The region has a cold climate, with a MAP <300 mm, and open vegetation. The hydrology is controlled by the Indian Summer Monsoon (ISM), but winter westerly-associated precipitation also affects the regional water balance. Results indicate that precipitation levels varied significantly during the Holocene. After a rapid increase in MAP, a phase of maximum humidity was reached between ca. 11 to 9.6 cal ka BP, followed by a gradual decline in MAP. This trend parallels the reduction in the Northern Hemisphere summer insolation. Comparison of different palaeoclimate proxy records reveal evidence for a stronger Holocene decrease in precipitation in the northern versus the southern parts of the ISM domain. The long-term trend of ISM weakening is overlaid with several short periods of greater dryness, which are broadly synchronous with the North Atlantic cold spells, suggesting reduced amounts of westerly-associated winter precipitation. Compared to the mid and late Holocene, it appears that westerlies had a greater influence on the western parts of the ISM domain during the early Holocene. During this period, the westerly-associated summer precipitation belt was positioned at Mediterranean latitudes and amplified the ISM-derived precipitation. The Tso Moriri pollen record and moisture reconstructions also suggest that changes in climatic conditions affected the ancient Harappan Civilisation, which flourished in the greater Indus Valley from approximately 5.2 to 3 cal ka BP. The prolonged Holocene trend towards aridity, punctuated by an interval of increased dryness (between ca. 4.5 to 4.3 cal ka BP), may have pushed the Mature Harappan urban settlements (between ca. 4.5 to 3.9 cal ka BP) to develop more efficient agricultural practices to deal with the increasingly acute water shortages. The amplified aridity associated with North Atlantic cooling between ca. 4 to 3.6 and around 3.2 cal ka BP further hindered local agriculture, possibly causing the deurbanisation that occurred from ca. 3.9 cal ka BP and eventual collapse of the Harappan Civilisation between ca. 3.5 to 3 cal ka BP.

An approach to operational modal analysis using the expectation maximization algorithm

This paper presents the Expectation Maximization algorithm (EM) applied to operational modal analysis of structures. The EM algorithm is a general-purpose method for maximum likelihood estimation (MLE) that in this work is used to estimate state space models. As it is well known, the MLE enjoys some optimal properties from a statistical point of view, which make it very attractive in practice. However, the EM algorithm has two main drawbacks: its slow convergence and the dependence of the solution on the initial values used. This paper proposes two different strategies to choose initial values for the EM algorithm when used for operational modal analysis: to begin with the parameters estimated by Stochastic Subspace Identification method (SSI) and to start using random points. The effectiveness of the proposed identification method has been evaluated through numerical simulation and measured vibration data in the context of a benchmark problem. Modal parameters (natural frequencies, damping ratios and mode shapes) of the benchmark structure have been estimated using SSI and the EM algorithm. On the whole, the results show that the application of the EM algorithm starting from the solution given by SSI is very useful to identify the vibration modes of a structure, discarding the spurious modes that appear in high order models and discovering other hidden modes. Similar results are obtained using random starting values, although this strategy allows us to analyze the solution of several starting points what overcome the dependence on the initial values used.

Hybrid topological derivative and gradient-based methods for electrical impedance tomography

We present a technique to reconstruct the electromagnetic properties of a medium or a set of objects buried inside it from boundary measurements when applying electric currents through a set of electrodes. The electromagnetic parameters may be recovered by means of a gradient method without a priori information on the background. The shape, location and size of objects, when present, are determined by a topological derivative-based iterative procedure. The combination of both strategies allows improved reconstructions of the objects and their properties, assuming a known background.

Maximum Likelihood Estimation of Modal Parameters in Structures Using the Expectation Maximization Algorithm

This paper presents a time-domain stochastic system identification method based on maximum likelihood estimation (MLE) with the expectation maximization (EM) algorithm. The effectiveness of this structural identification method is evaluated through numerical simulation in the context of the ASCE benchmark problem on structural health monitoring. The benchmark structure is a four-story, two-bay by two-bay steel-frame scale model structure built in the Earthquake Engineering Research Laboratory at the University of British Columbia, Canada. This paper focuses on Phase I of the analytical benchmark studies. A MATLAB-based finite element analysis code obtained from the IASC-ASCE SHM Task Group web site is used to calculate the dynamic response of the prototype structure. A number of 100 simulations have been made using this MATLAB-based finite element analysis code in order to evaluate the proposed identification method. There are several techniques to realize system identification. In this work, stochastic subspace identification (SSI)method has been used for comparison. SSI identification method is a well known method and computes accurate estimates of the modal parameters. The principles of the SSI identification method has been introduced in the paper and next the proposed MLE with EM algorithm has been explained in detail. The advantages of the proposed structural identification method can be summarized as follows: (i) the method is based on maximum likelihood, that implies minimum variance estimates; (ii) EM is a computational simpler estimation procedure than other optimization algorithms; (iii) estimate more parameters than SSI, and these estimates are accurate. On the contrary, the main disadvantages of the method are: (i) EM algorithm is an iterative procedure and it consumes time until convergence is reached; and (ii) this method needs starting values for the parameters. Modal parameters (eigenfrequencies, damping ratios and mode shapes) of the benchmark structure have been estimated using both the SSI method and the proposed MLE + EM method. The numerical results show that the proposed method identifies eigenfrequencies, damping ratios and mode shapes reasonably well even in the presence of 10% measurement noises. These modal parameters are more accurate than the SSI estimated modal parameters.

Computational Methods for Identification of Vibrating Structures

System identification deals with the problem of building mathematical models of dynamical systems based on observed data from the system" [1]. In the context of civil engineering, the system refers to a large scale structure such as a building, bridge, or an offshore structure, and identification mostly involves the determination of modal parameters (the natural frequencies, damping ratios, and mode shapes). This paper presents some modal identification results obtained using a state-of-the-art time domain system identification method (data-driven stochastic subspace algorithms [2]) applied to the output-only data measured in a steel arch bridge. First, a three dimensional finite element model was developed for the numerical analysis of the structure using ANSYS. Modal analysis was carried out and modal parameters were extracted in the frequency range of interest, 0-10 Hz. The results obtained from the finite element modal analysis were used to determine the location of the sensors. After that, ambient vibration tests were conducted during April 23-24, 2009. The response of the structure was measured using eight accelerometers. Two stations of three sensors were formed (triaxial stations). These sensors were held stationary for reference during the test. The two remaining sensors were placed at the different measurement points along the bridge deck, in which only vertical and transversal measurements were conducted (biaxial stations). Point estimate and interval estimate have been carried out in the state space model using these ambient vibration measurements. In the case of parametric models (like state space), the dynamic behaviour of a system is described using mathematical models. Then, mathematical relationships can be established between modal parameters and estimated point parameters (thus, it is common to use experimental modal analysis as a synonym for system identification). Stable modal parameters are found using a stabilization diagram. Furthermore, this paper proposes a method for assessing the precision of estimates of the parameters of state-space models (confidence interval). This approach employs the nonparametric bootstrap procedure [3] and is applied to subspace parameter estimation algorithm. Using bootstrap results, a plot similar to a stabilization diagram is developed. These graphics differentiate system modes from spurious noise modes for a given order system. Additionally, using the modal assurance criterion, the experimental modes obtained have been compared with those evaluated from a finite element analysis. A quite good agreement between numerical and experimental results is observed.

Operational Modal Analysis using Expectation Maximization Algorithm

This paper presents a time-domain stochastic system identification method based on Maximum Likelihood Estimation and the Expectation Maximization algorithm. The effectiveness of this structural identification method is evaluated through numerical simulation in the context of the ASCE benchmark problem on structural health monitoring. Modal parameters (eigenfrequencies, damping ratios and mode shapes) of the benchmark structure have been estimated applying the proposed identification method to a set of 100 simulated cases. The numerical results show that the proposed method estimates all the modal parameters reasonably well in the presence of 30% measurement noise even. Finally, advantages and disadvantages of the method have been discussed.

Coleccion de las obras sueltas, assi en prosa, como en verso

Contiene : Laurel de Apolo, p. 1-221; La selva sin amor: égloga pastoral, p. 223-255 ; Al quadro y retrato de su magestad, que hizo Pedro Pablo de Rubens, p. 256--259 ; Epistola de don Michael de Solis ..., p. 260-273 ; Sonetos, p. 273-276 ; Epistolas de Lope de Vega Carpio a varias personas, p. 277-509 ; Eregia en la muerte de Elisio de Medinilla, p. 510-517

Coleccion de las obras sueltas, assi en prosa, como en verso

Contiene : El Isidro: poema castellano, p. 1-336 ; Justa poética y alabanzas juntas que hizo la ... Villa de Madrid al bienaventurado San Isidro ... / recopiladas por Lope de Vega Carpio, p. 337-614

Coleccion de las obras sueltas, assi en prosa, como en verso

Contiene: Fiestas del SSmo. Sacramento repartidas en doce Actos Sacramentales .../ compuesta por el Phenix de España Fray Lope Felix de Vega Carpio ... ; recogidas por el Lic. Joseph Ortiz de Villena ...

Coleccion de las obras sueltas, assi en prosa, como en verso

Contiene: Fama postuma a la vida y muerte del doctor Fray Lope Felix de Vega Carpio y elogios panegyricos a la inmortalidad de su nombre / escritas por los más esclarecidos ingenios ; solicitados por el doctor Juan Perez de Montalvan

Análisis de las metodologías de evaluación de riesgos en obras de edificación. Nueva metodología adaptada a edificación

La evaluación de riesgos examina la prevención analizando probabilidad de que se produzca un daño en base a exposición al peligro. Diversas metodologías analizan trabajo y entorno, dependiendo del tipo de empresa, de trabajo, cantidad de trabajadores, localización, etc., evaluando independientemente riesgos específicos de seguridad, higiene, ergonomía y psicosociología. Se basan en valoraciones subjetivas de causas y consecuencias de accidentes. Como los puestos de trabajo en edificación son muy variables en el tiempo, con interdependencias y desplazamientos por la obra, se ha realizado una investigación teórico-analítica de metodologías de evaluación de riesgos laborales, proponiéndose una nueva adaptada a obras de edificación y a factores de riesgo reales. Se denomina nivel de la acción preventiva y se basa en la tolerancia del riesgo, añadiendo el factor de la realidad constructiva, y en los riesgos de complejidad de obra, entorno social y respuesta económica del contratista.