The identification of petroleum acids, also known as ‘naphthenic’ acids (NA), has been an analytical challenge for over 140 years. However, most recent interest in NA has arisen due to concerns over their presence and apparent associated toxic effect in oil platform produced waters and oil sands process waters (OSPW), respectively. Understanding the toxicity, transformations during biodegradation and remediation treatments and predicting the fate of NA in the environment will be aided by the identification of individual NA. However the elucidation of individual acid structures by standard chromatographic techniques, such as GC-MS, has so far been limited by the extreme complexity of the NA mixtures. Recent analysis of NA as the methyl ester derivatives, by multidimensional gas chromatography-mass spectrometry (GC×GC-MS), has resulted in the identification of several tri- to pentacyclic, aromatic and sulphur-containing acids as well as tricyclic diacids. Therefore the current investigation focused on the identification of the abundant bicyclic acids in petroleum and OSPW acid extracts, utilising the unparalleled chromatographic separation and mass spectrometric detection offered by GC×GC-MS. Analysis of fractionated NA as methyl esters, resulted in the first identification of several bicyclic acids in OSPW including several novel bridged bicyclic acids, several fused bicyclic acids, as well as some terpenoid-derived drimane and labdane acids. However, identifications were limited somewhat by a lack of reference mass spectra and lack of availability of reference compounds for co-chromatography. A complementary method, based on an historical approach, involving reduction of NA esters to hydrocarbons, was modified and substantially improved. Analysis of the hydrocarbons resulting from the reduced acids, by GC×GC-MS, and comparison of the hydrocarbon mass spectra with the more abundant reference spectra available for petroleum hydrocarbons, resulted in the identification of over 40 individual bicyclic acids including fused, bridged and terpenoid-derived acids. The study provides the most comprehensive analysis of one of the major classes of NA (the bicyclic acids) to date. The methods developed were applied to the structural elucidation of NA in commercial NA and OSPW NA and resulted in the identification of numerous alicyclic, aromatic and sulphur-containing acids, supporting and extending previous identifications. There is clear potential for this method to be used for the identification of other unknown acids and functionalised biomarkers in complex matrices. The new knowledge of the acid structures in petroleum and OSPW NA can now be used to inform future research into the environmental monitoring and toxicity of NA.

<div><div><div><p>Structural identification is a useful tool for detecting damage and damage evolution in a structure. The initiation of damage in a structure and its subsequent growth are mainly associated with nonlinear behaviors. While linear dynamics of a structure are easy to simulate, nonlinear structural dynamics have more complex dynamics and amplitude dependence that do require more sophisticated simulation tools and identification methods compared to linear systems. Additionally, there are generally many more parameters in nonlinear models and the responses may not be sensitive to all of them for all inputs. To develop model selection methods, an experiment is conducted that uses an existing device with repeatable behavior and having an expected model from the literature. In this case, an MR damper is selected as the experimental device. The objective of this research is to develop and demonstrate a method to select the most appropriate model from a set of identified stochastic models of a nonlinear device. The method is developed using numerical example of a common nonlinear system, and is then implemented on an experimental structural system with unknown nonlinear properties. Bayesian methods are used because they provide a distinct advantage over many other existing methods due to their ability to provide confidence on answers given the observed data and initial uncertainty. These methods generate a description of the parameters of the system given a set of observations. First, the selected model of the MR damper is simulated and used for demonstrating the results on a numerical example. Second, the model selection process is demonstrated on an experimental structure based on experimental data. This study explores the use of the Bayesian approach for nonlinear structural identification and identifies a number of lessons for others aiming to employ Bayesian inference.</p></div></div></div>

Charles University, Faculty of Pharmacy in Hradec Králové, Department of Pharmaceutical Botany Author: Hana Šimková Supervisor: prof. Ing. Lucie Cahlíková, Ph.D. Title of diploma thesis: Alkaloids of genus Narcissus: isolation, structural identification, biological activity Key words: Narcissus, alkaloids, biological activity, Alzheimer's disease, cytotoxic activity The aim of the diploma thesis was an isolation of alkaloids with a focus on minor fractions. These fractions were obtained from the summary alkaloid extract of Narcissus pseudonarcissus cv. Carlton. The method of preparative TLC was used for the isolation of alkaloids. Three substances of alkaloid origin marked as Fj 3-4/kr, F 7/2-1, F 7/2-3 were isolated from the assigned fractions. These substances were identified as alkaloids of homolycorine type lycorenine, homolycorine and hippeastrine by using GC-MS, NMR and optical rotation. The results were also compared with data in the literature. These three alkaloids were tested for their inhibitory activity against AChE, BuChE, POP and GSK-3β. The inhibitory activity against AChE and BuChE was compared with the reference substances galanthamine (IC50 AChE = 1,71 ± 0,07 μM, IC50 BuChE = 42,3 ± 1,3 μM) and huperzine A (IC50 AChE = 0,033 ± 0,001 μM, IC50 BuChE> 1000 μM). The inhibitory...

Damage and condition identi&amp / #64257 / cation of existing structures using non-destructive tests is a common challenge that has been worked on for a long time. In this study, two di&amp / #64256 / erent methods were developed to &amp / #64257 / nd existing force on cables as well as determine bending characteristics (EI coe&amp / #64259 / cients) of beam like structures (such as bridges). Comparing forces in symmetrically placed cables or against values obtained from design drawings would indicate structural imbalance as well as &amp / #64257 / nding EI coe&amp / #64259 / cients at a number of segments on a bridge girder might indicate weak regions that might possibly have undergone structural damage, having weak connections, lost composite action etc. With the help of the proposed algorithm, the sti&amp / #64256 / ness parameters of bridges can be assessed and the location of any damage that is in the magnitude which can a&amp / #64256 / ect displacement behavior of system can be located. The developed methods are demonstrated using the values analytically obtained from the created models and the e&amp / #64256 / ectiveness of the algorithm is criticized. Furthermore, several damage scenarios on a scaled lab beam was used to test the application using real experimental data / including tests on undamaged beam (for identi&amp / #64257 / cation) and tests on the damaged beam. Additional experiments were conducted on a cable stretched in the laboratory instrumented using a load cell to measure instantaneous axial load on the cable and compare these values against the values obtained from the developed tension measurement device. The results are compared and conclusions are derived.

La presente tesi si concentra sull’incertezza e sulla sua relazione con il rischio finanziario, due importanti concetti in economia e finanza. Il primo capitolo propone un approccio analitico in grado di separare gli shock connessi all’incertezza finanziaria dagli shock legati all’incertezze politiche, utilizzando un campione di paesi appartenti all’area Euro, dove la diffusione di shock da un paese all’altro (effetti di spillover) rendono l’identificazione più complessa. I risultati indicano che la BCE favorisce adottare una condotta proattiva verso gli shock di incertezza politica, e una più passiva verso gli shock di incertezza finanziaria. Il secondo capitolo discute il trade-off tra accuratezza della previsione e velocità di reazione che consente agli hedge fund di incrementare i profitti durante periodi caratterizzati da elevata incertezza. In questo capitolo si propone un metodo matematico per l’analisi di tale trade-off utilizzando un approccio Bayesiano. I risultati empirici e le simulazioni effettuate indicano che previsioni meno accurate sono associate ad aumenti di velocità. Infine, il terzo capitolo analizza alcune problematiche inerenti alla transizione ad un’economia a basso impatto ambientale, tenendo conto che la presenza di incertezza e asimmetrie informative potrebbero amplificare o limitare i pregiudizi comportamentali degli investitori. / This thesis focuses on broader or Knightian uncertainty and its relation with financial uncertainty or risk, given the overlaps existing between these two important concepts in the economics and finance literature. The first chapter adds to the existing stock of analytical methods able to disentangle financial from policy-related uncertainty shocks within a sample of Euro Area countries, where cross-border spill-overs can raise identification challenges. In terms of policy reactions, the results point to ECB having adopted a pro-active stance towards policy uncertainty shocks, but a more passive or accommodative stance towards financial uncertainty shocks. The second chapter discusses the trade-off between prediction accuracy and reaction speed that allows hedge funds to better time the market and profit during periods of turmoil and high uncertainty. It proposes a mathematical formulation of the trade-off that casts the decision-making process in a Bayesian framework. The empirical results, pointing to speed gains associated with less accurate predictions, are justified in a simulation exercise. The third chapter discusses some challenges arising from the ongoing transition to a low-carbon economy in a market context dominated by multiple uncertainty sources and information frictions that can either amplify or reduce investors’ own behavioural biases.

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Reliable flutter analysis of aircraft structures is a major requirement to determine safe flight envelops. Dynamically equivalent finite element model of an aircraft structure correlating well with experimental modal is a major requirement for a reliable flutter analysis. Currently available model updating techniques require enormous time and engineering work to achieve appropriate finite element models of aircraft structures. The method developed within the scope of this thesis work aims to remove important disadvantages of common model updating procedures. In doing this, the method starts with a simple finite element mesh obtained by connecting measurement points, used in the Ground Vibration Test of an aircraft structure, with 3 D Euler-Bernoulli beam elements. Initial estimates of the geometric and material properties are determined by solving structural identification equations derived from the mass and stiffness orthogonality of experimental modes. By using those initial estimates, an initial finite element model is constructed. Starting from this initial finite element model, structural identification equations are updated and solved iteratively by using experimental natural frequencies and eigenvectors of the v updated finite element model representing the same mode shapes with measured normal modes. Iterations are continued until eigen solution of the updated finite element model closely correlates with experimental modal data. The applicability of the method is illustrated on a scaled aircraft model and a real aircraft structure. The results are quite satisfactory but the method requires further improvements to achieve a much better correlation level in case of real aircraft structures.

[pt] A modelagem numérica tem-se mostrado uma ferramenta valiosa na avaliação e previsão do comportamento estrutural a partir de informações experimentais. Neste trabalho faz-se um estudo de certos problemas de identificação de sistemas estruturais. O principal objetivo reside na avaliação e interpretação computacional de parâmetros estruturais com base em resultados de ensaios mecânicos não- destrutivos. Foram desenvolvidos e codificados algoritmos, em diferentes formatos computacionais, para o tratamento deste problema. O desenvolvimento é aplicável a qualquer tipo de estrutura modelada por elementos finitos. No trabalho são exemplificadas estruturas em forma de conjuntos de massas e molas, vigas em flexão no plano, vigas em torção e flexão, arcos, pórticos e treliças. Analisa-se a determinação de termos de rigidez e massa a partir de informações globais e locais sobre deslocamentos, deformações e freqüências de vibração. São apresentados estudos que indicam a possibilidade de determinar, com as técnicas numéricas aqui desenvolvidas, a localização e magnitude dos danos ocorridos nas estruturas, a partir da resposta estática ou dinâmica da estrutura, mesmo com reduzidas informações sobre a resposta da estrutura não danificada. Isto foi aqui estendido à determinação de tensões e carregamentos,através da consideração de efeitos de não-linearidade geométrica. Apresentam-se também critérios para projeto de experimentos, de forma a maximizar a sensibilidade aos parâmetros buscados e minimizar sua correlação. Ilustra-se através de vários exemplos o desenvolvimento teórico e numérico aqui apresentado. / [en] Numerical modeling is a valuable tool in the evaluation and prediction of structural behavior from given experimental data. This work presents a study of some problems of identification of structural systems. The main objective is the computer evaluation and interpretation of structural parameters from the results of non-destructive mechanical tests.Algorithms were developed and coded, in different computational formats, to treat this problem.The development is applicable to any type of structure modeled by finite elements. Examples presented in this work are sets of masses and springs, beams in pane bending, beams in bending and torsion, arches, frames and trusses. The determination of stiffness and mass terms, from local and global information on displacements, strains and frequencies, is discussed. The studies indicate that, using the numerical techniques developed herein, it is possible to determine a location and magnitude of damages occurred in structures, from the static or dynamic response data, resorting to limited information on the response of the undamaged structure. Such techniques were extended to the evaluation of stresses and loadings, by taking into account effects of geometric nonlinearity. Criteria for design of experiments are presented, which allow for maximum sensitivity and minimum correlation of the structural parameters under concern.Several examples are presented to illustrate the theoretical and numerical techniques developed herein.

Bridges are critical components of highway networks, which provide mobility and economical vitality to a nation. Ensuring the safety and regular operation as well as accurate structural assessment of bridges is essential. Structural Identification (St-Id) can be utilized for better assessment of structures by integrating experimental and analytical technologies in support of decision-making. St-Id is defined as creating parametric or nonparametric models to characterize structural behavior based on structural health monitoring (SHM) data. In a recent study by the ASCE St-Id Committee, St-Id framework is given in six steps, including modeling, experimentation and ultimately decision making for estimating the performance and vulnerability of structural systems reliably through the improved simulations using monitoring data. In some St-Id applications, there can be challenges and considerations related to this six-step framework. For instance not all of the steps can be employed; thereby a subset of the six steps can be adapted for some cases based on the various limitations. In addition, each step has its own characteristics, challenges, and uncertainties due to the considerations such as time varying nature of civil structures, modeling and measurements. It is often discussed that even a calibrated model has limitations in fully representing an existing structure; therefore, a family of models may be well suited to represent the structure’s response and performance in a probabilistic manner. The principle objective of this dissertation is to investigate nonparametric and parametric St-Id approaches by considering uncertainties coming from different sources to better assess the structural condition for decision making. In the first part of the dissertation, a nonparametric StId approach is employed without the use of an analytical model. The new methodology, which is iv successfully demonstrated on both lab and real-life structures, can identify and locate the damage by tracking correlation coefficients between strain time histories and can locate the damage from the generated correlation matrices of different strain time histories. This methodology is found to be load independent, computationally efficient, easy to use, especially for handling large amounts of monitoring data, and capable of identifying the effectiveness of the maintenance. In the second part, a parametric St-Id approach is introduced by developing a family of models using Monte Carlo simulations and finite element analyses to explore the uncertainty effects on performance predictions in terms of load rating and structural reliability. The family of models is developed from a parent model, which is calibrated using monitoring data. In this dissertation, the calibration is carried out using artificial neural networks (ANNs) and the approach and results are demonstrated on a laboratory structure and a real-life movable bridge, where predictive analyses are carried out for performance decrease due to deterioration, damage, and traffic increase over time. In addition, a long-span bridge is investigated using the same approach when the bridge is retrofitted. The family of models for these structures is employed to determine the component and system reliability, as well as the load rating, with a distribution that incorporates various uncertainties that were defined and characterized. It is observed that the uncertainties play a considerable role even when compared to calibrated model-based predictions for reliability and load rating, especially when the structure is complex, deteriorated and aged, and subjected to variable environmental and operational conditions. It is recommended that a family-of-models approach is suitable for structures that have less redundancy, high operational importance, are deteriorated, and are performing under close capacity and demand levels

This work is focusing to study the structural behavior of Composite Overwrapped Pressure Vessels (COPVs). These COPVs are found in many engineering applications. In the aerospace field, they are installed onto spaceships and aid the reorientation of the spacecraft in very far and airless, therefore frictionless, orbits to save energy and fuel. The intent of this research is to analyze the difference in performance of both perfectly intact and purposely damaged tanks. Understanding both the source and location of a structural fault will help NASA engineers predict the performance of COPVs subject to similar conditions, which could prevent failures of important missions. The structural behavior of six tanks is investigated by means of experimental modal analysis. Knowledge of statistical signal processing methods allows to sort out and extract meaningful features from the data as to gain understanding of the performance of the structures. Structural identification is carried out using Narrow Band and Broad Band algorithms. A comparison through correlation tables and figures presents the differences in natural frequencies, mode shapes and damping ratios of all structures. A careful analysis displays the deviation of these modal parameters in the damaged tanks, highlighting the evident structural defects.