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Μελέτη περιβαλλοντικών παραμέτρων σε υδατικά περιβάλλοντα με χρήση Γεωγραφικών Συστημάτων Πληροφοριών (GIS) και Πολυδιάστατης Στατιστικής Ανάλυσης. / Study of environmental parameters in surface and groundwater environments using Geographic Information Systems (GIS)and Multivariate Statistical Analysis.Δημοπούλου, Γερασιμούλα 28 June 2007 (has links)
Η παρούσα μελέτη παρουσιάζει τρία μεθοδολογικά σχήματα τα οποία μπορούν να εφαρμοστούν στην χωρική και χρονική ανάλυση δεδομένων για την διαχείριση των υδατικών πόρων. Αποτελείται από τρία ανεξάρτητα μεταξύ τους τμήματα τα οποία είναι : α)Χρήση Γεωγραφικών Συστημάτων Πληροφοριών και Πολυδιάστατης Στατιστικής Ανάλυσης για την διερεύνηση των σχέσεων μεταξύ υπόγειων υδάτων και χρήσεων γης β)Μελέτη χρονικών υδροχημικών δεδομένων από ένα μεγάλης διάρκειας πρόγραμμα παρακολούθησης σε μιά ρηχή λίμνη με χρήση Πολυδιάστατης Στατιστικής Ανάλυσης και γ)Εφαρμογή της Clean φασματικής ανάλυσης σε υδροχημικά δεδομένα : Παραδείγματα από δύο λίμνες της Ελλάδας. / The present study intoduces three methodologies which can be applied in water resource management. It consist of three independed projects : a)Indentifing relationships between groundwater quality and landuse using GIS and Multivariate Statistical Analysis b)A long-term study of temporal hydrochemical data in a shallow lake using multivariate statistical techniques and c)Application of Clean Spectral Analysis to hydrochemical data : Case studies from two lakes, Greece.
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Caracterização de tecidos mamários através de modelos estatísticos utilizando o espalhamento de raios-x\". / Breast Tissue Characterization by Statistical Models Using X-Ray ScatteringDiego Merigue da Cunha 24 March 2006 (has links)
Em um exame mamográfico, quando os fótons de raios-X incidem sobre a mama, uma parte destes fótons é transmitida sem ser desviada da trajetória inicial (radiação transmitida primária), permitindo a formação da imagem mamográfica, e outra é dispersa de sua trajetória inicial pelo tecido (radiação espalhada), atuando de forma deletéria na imagem mamográfica. Entretanto, recentes investigações têm demonstrado que a radiação espalhada pode ser útil na caracterização de tecidos. O objetivo deste trabalho é desenvolver um modelo de diagnóstico de alterações no tecido mamário utilizando as informações presentes na distribuição angular da radiação espalhada (perfil de espalhamento). Os perfis de espalhamento de 40 amostras de tecidos mamários foram obtidos utilizando um difractômetro comercial SIEMENS D5005, operando em modo reflexão na energia de 8,04 keV e variando o detector da posição angular de 5º a 150º, correspondendo a um intervalo de x de 0,03Å-1 a 0,62 Å-1. As amostras de tecido foram previamente classificadas histopatologicamente como tecidos normais, fibroadenomas (neoplasias benignas) e diferentes tipos de carcinomas (neoplasias malignas). Neste trabalho, três modelos de diagnóstico baseados na análise estatística dos perfis de espalhamento foram desenvolvidos. O primeiro, analisa seis parâmetros extraídos dos perfis de espalhamento, já o segundo e o terceiro utilizam análise multivariada (análise de componentes principais e análise de discriminante, respectivamente) para reconhecimento de padrões. Para cada modelo, valores de sensibilidade, especificidade e índice de concordância entre o diagnóstico baseado no modelo utilizado e o diagnóstico histopatológico foram obtidos. Dentre os modelos desenvolvidos, aquele que utiliza análise de discriminante proporciona o melhor diagnóstico das alterações encontradas no tecido, permitindo diferenciar tecidos normais e neoplasias benignas e malignas. Com base nos resultados obtidos conclui-se que modelos baseados na análise estatística dos perfis de espalhamento permitem classificar histologicamente tecidos mamários. / In mammography, when x-ray photons reach the breast, a fraction of these photons is transmitted without interaction with any tissues (primary transmitted radiation), allowing the formation of the mammographic image, and another fraction of them is deviated by the tissue from its initial trajectories (scattered radiation), reducing the image contrast. However, recent investigations have demonstrated that scattered radiation can be a useful diagnostic tool. The purpose of this work is to develop a diagnostic model for breast tissue characterization using the angular distribution of the scattered radiation (scattering profile). The scattering profiles of 40 breast tissue samples were obtained in a SIEMENS D5005 diffractometer, operating in reflection mode at 8,04keV, and varying the angular position of the detector from 5º to 150º, corresponding to an x interval from 0,03 Å-1 to 0,62 Å-1. All tissue samples were previously classified histopathologically as normal tissues, fibroadenomas (benign alteration) and several types of carcinomas (malignant alteration). Three models of diagnostic based on the statistical analysis of the scattering profiles were developed. The first one was constructed using six parameters extracted from the scattering profiles and the second and third models used the whole information from the scattering profiles. The latter two used multivariate analysis (principal component analysis and discriminant analysis, respectively) for pattern recognition. For each model, values of sensitivity, specificity and rate of agreement between the model diagnostic and histopathological results were obtained. Among the developed models, the discriminant analysis provides the best diagnostic of the lesions present in the tissues (normal tissues, benign and malignant alterations). From the results, it is possible to conclude that models based on the statistical analysis of the scattering profiles allow the histological classification of breast tissues.
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AnÃlise EstatÃstica Multivariada e Modelo GeoquÃmico Inverso no Estudo da Qualidade da Ãgua SubterrÃnea da Bacia de Forquilha em Quixeramobim-CearÃ.JoÃo Roberto FaÃanha de Almeida 16 November 2009 (has links)
Conselho Nacional de Desenvolvimento CientÃfico e TecnolÃgico / Os aqÃÃferos aluviais presentes na regiÃo semi-Ãrida do Nordeste brasileiro hospedam importantes recursos hÃdricos naturais para as populaÃÃes que vivem nessa regiÃo, devido a sua excelente qualidade, quando comparado aos aqÃÃferos localizados nas Ãreas de embasamento cristalino. No entanto, constituem recursos frÃgeis, sendo susceptÃveis a processos de degradaÃÃo da sua qualidade por aÃÃes antrÃpicas, variaÃÃes climÃticas ou modificaÃÃes hidrogeolÃgicas. Com o objetivo de identificar e quantificar os principais processos responsÃveis pelo aumento da salinidade observada no aqÃÃfero aluvial durante o perÃodo nÃo chuvoso usou-se, alÃm de estudos hidroquÃmicos (diagramas e estudo de razÃes iÃnicas), a anÃlise estatÃstica multivariada (agrupamento hierÃrquico e discriminante) e a modelagem geoquÃmica inversa. Os diagramas de Piper e Stiff mostraram a classificaÃÃo das Ãguas quanto à presenÃa dos Ãons dominantes, onde as Ãguas aluviais apresentaram caracterÃsticas intermediÃrias entre as Ãguas do aqÃÃfero fissural e Ãgua dos reservatÃrios. Com o diagrama de RAS obteve-se a mesma interpretaÃÃo. As relaÃÃes iÃnicas revelaram forte relaÃÃo das Ãguas aluviais com a litologia da regiÃo e a provÃvel dissoluÃÃo de aerossÃis contendo compostos de MgCl2 nos aqÃÃferos do embasamento cristalino. A anÃlise de agrupamento mostrou as similaridades entre os poÃos, enquanto a anÃlise discriminante ajudou a compreender o processo de salinizaÃÃo no aqÃÃfero aluvial. As modelagens geoquÃmicas inversas realizadas com o PHREEQC identificaram trocas catiÃnicas de CaX2, MgX2, NaX e KX, alÃm de precipitaÃÃes de K-mica e albita e dissoluÃÃes de anortita e K-feldspato, evidenciando a aÃÃo intempÃrica das Ãguas sobre as rochas. A grande dissoluÃÃo de CO2 nas Ãguas aluviais justifica a caracterÃstica bicarbonatada dessas Ãguas. A contribuiÃÃo volumÃtrica de Ãguas do aqÃÃfero fissural, como forma de justificar o aumento da salinidade nos poÃos aluviais, foi estimada entre 1,53% e 27,99% para diferentes pontos, na mÃdia foi de 15,8%. No entanto, esta contribuiÃÃo representa quase 64% da salinidade no aluviÃo. / The alluvial aquifers in the semi-arid region of Brazilâs Northeast host an important natural water resource for the populations that live in that region, owing to its excellent quality, when compared to the crystalline basement rock aquifers. However, they are fragile resources and are susceptible to processes of degradation of quality by anthropic action, climatic changes or hydrogeological modifications. The objective of this research is to identify and quantify the primary processes responsible for the increase in salinity observed in the alluvial aquifers during the dry season. Besides hydrochemical analysis (Piper and Stiff diagrams and ionic relations), multivariate statistical analysis (hierarchical clustering and discriminant analyses) and inverse geochemical modeling were also used. The Piper and Stiff diagrams presented water classification according to dominant ions, where the alluvial water showed intermediate characteristics between the hard-rock basement aquifer water and that from the reservoirs. With the SAR diagram, the same result was observed. The ionic relations revealed a strong relation of the alluvial water with the lithology of the region and the probable dissolution of aerosols containing composites of the MgCl2 type in the aquifers of the crystalline rock shield. Cluster analysis showed the similarities between the wells, whereas discriminant analysis helped to understand the process of salinization in the alluvial aquifer. The inverse geochemical modeling carried out with PHREEQC identified cationic exchanges of CaX2, MgX2, NaX and KX, as well as precipitation of K-mica and albite and dissolutions of anorthite and K-feldspar, evidencing the intemperic action of the water on the rocks. Strong dissolution of CO2 in the alluvial water justifies the bicarbonated characteristics of that water. The volume contribution from crystalline rock aquifer water was estimated as between 1.53% and 27.99% at different points with a mean value of 15.8%. However, this contribution represents nearly 64% of the salinity of the water in the alluvium.
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Avaliação de alterações em redes de drenagem de microbacias como subsídio ao zoneamento geoambiental de bacias hidrográficas: aplicação na bacia hidrográfica do Rio Capivari - SP. / Alteration evaluation in microbasin drainage systems as a subsidy to the geoenvironmental zoning of hydrographic basins: application in the Capivari river hydrographic basin.Eduardo Goulart Collares 01 December 2000 (has links)
A rede de drenagem se constitui em importante indicador de alterações ocorridas na composição da paisagem de bacias hidrográficas, seja por mudanças na sua estruturação, forma ou então por ganho ou perda de canais. O objetivo deste trabalho é apresentar e aplicar uma proposta metodológica, com base em análise morfométrica temporal das redes de drenagem de microbacias, visando a avaliação das alterações e o zoneamento regional de uma bacia hidrográfica. A metodologia envolve o uso de imagens de sensoriamento remoto e técnicas de geoprocessamento para a caracterização das atividades antrópicas e levantamento das variáveis morfométricas em duas datas, com um intervalo de 23 anos. A avaliação das alterações e a consequente classificação das microbacias são efetuadas com base em análise estatística multivariada. A proposta foi aplicada na bacia hidrográfica do rio Capivari e os resultados comprovam que ocorreram alterações significativas na composição da rede de drenagem no período de análise. As variáveis morfométricas que mais contribuíram para a avaliação das alterações foram a Densidade de Drenagem e Densidade Hidrográfica. Dentre as microbacias que mais se alteraram estão as urbanas ou em processo de urbanização e, dentre aquelas onde as alterações foram menos pronunciadas estão as microbacias rurais, com predomínio de pastagens e/ou cana de açúcar. / The drainage system is an important indicator of the alterations occurred in the composition of the hydrographic basin environment, either due to changes in their structure and shape or due to channel loss and gain. The objective of this project is to present and apply a methodological proposal, based on time morphometric analysis of the microbasin drainage systems, aiming at the alteration evaluation and the regional zoning of a hydrographic basin. The methodology involves the use of remote images and geoprocessing techniques for the characterization of the anthropic activities and the determination of the morphometric variables on two dates, with a 23-year interval. The evaluation of the alterations and the consequent microbasin classification are carried out based on multivariate statistical analysis. The proposal was applied on Capivari river hydrographic basin, and the results prove that there were significative alterations in the drainage system composition in the analyzed period. The morphometric variables which most contributed to the alteration evaluation were the Drainage Density and the Hydrographic Density. Among the microbasins which were most altered there are the urban and under urbanization ones, and among those which had less significative alterations there are the rural microbasins, prevailing the pasture lands and sugar-cane raising.
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The application of multivariate statistical analysis and batch process control in industrial processesLin, Haisheng January 2010 (has links)
To manufacture safe, effective and affordable medicines with greater efficiency, process analytical technology (PAT) has been introduced by the Food and Drug Agency to encourage the pharmaceutical industry to develop and design well-understood processes. PAT requires chemical imaging techniques to be used to collect process variables for real-time process analysis. Multivariate statistical analysis tools and process control tools are important for implementing PAT in the development and manufacture of pharmaceuticals as they enable information to be extracted from the PAT measurements. Multivariate statistical analysis methods such as principal component analysis (PCA) and independent component analysis (ICA) are applied in this thesis to extract information regarding a pharmaceutical tablet. ICA was found to outperform PCA and was able to identify the presence of five different materials and their spatial distribution around the tablet.Another important area for PAT is in improving the control of processes. In the pharmaceutical industry, many of the processes operate in a batch strategy, which introduces difficult control challenges. Near-infrared (NIR) spectroscopy is a non-destructive analytical technique that has been used extensively to extract chemical and physical information from a product sample based on the scattering effect of light. In this thesis, NIR measurements were incorporated as feedback information into several control strategies. Although these controllers performed reasonably well, they could only regulate the NIR spectrum at a number of wavenumbers, rather than over the full spectrum.In an attempt to regulate the entire NIR spectrum, a novel control algorithm was developed. This controller was found to be superior to the only comparable controller and able to regulate the NIR similarly. The benefits of the proposed controller were demonstrated using a benchmark simulation of a batch reactor.
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Compact-disc microfluidic methods for characterization of therapeutic antibodies : Analysis of post-translational modificationsTran, Thi Thuy January 2012 (has links)
Characterization of post-translational modifications (PTMs) of therapeutic proteins is very important during the bioprocess development to maintain desired product quality and during the submission process to regulatory authorities for product approval. Monitoring glycosylation in pharmacokinetic studies can be useful to evaluate the dependence of clearance rates on different glycoforms. The cost and efficiency of characterization affect the speed to market of biopharmaceutical proteins. A reduction in the number of manual processing steps, cost of reagents and consumption of sample, as well as the time required for chemical analysis, is therefore necessary. The research presented in this thesis is focused on the potential of using microfluidic discs for automated, miniaturized, parallel and rapid sample preparation for PTM characterization of therapeutic monoclonal antibodies. Paper I describes the method development for N-linked glycosylation profiling. Several sample preparation steps have been performed in an integrated process in the microfluidic compact disc (CD). Paper II demonstrates the use of the method presented in paper I in combination with multivariate statistics for discrimination of glycosylation profiles of different therapeutic antibodies and simulation of a real case of quality control. Paper III is focused on a method for monitoring changes in glycosylation profiles of therapeutic antibodies in serum over time by incubation with an exoglycosidase enzyme. Paper IV describes the method for peptide mapping of therapeutic antibodies. In addition, recent work (unpublished results) assesses the potential of this method for methionine oxidation detection. The developed methods were fast, robust with low sample/reagent consumption. Generation of glycosylation profile data for one sample was established in approximately 2 h. The amount of samples and antigens loaded into the CD platform for one replicate was less than 0.3 μg and approximately 0.06 μg, respectively. Furthermore, considering the parallel function of the CD, conducting the analysis for 54 samples can be completed within a day. / <p>At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 3: Manuscript.</p>
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Water Quality Modelling Using Multivariate Statistical Analysis and Remote Sensing in South FloridaHajigholizadeh, Mohammad 07 November 2016 (has links)
The overall objective of this dissertation research is to understand the spatiotemporal dynamics of water quality parameters in different water bodies of South Florida. Two major approaches (multivariate statistical techniques and remote sensing) were used in this study. Multivariate statistical techniques include cluster analysis (CA), principal component analysis (PCA), factor analysis (FA), discriminant analysis (DA), absolute principal component score-multiple linear regression (APCS-MLR) and PMF receptor modeling techniques were used to assess the water quality and identify and quantify the potential pollution sources affecting the water quality of three major rivers of South Florida. For this purpose, a 15-year (2000–2014) data set of 12 water quality variables, and about 35,000 observations were used. Agglomerative hierarchical CA grouped 16 monitoring sites into three groups (low pollution, moderate pollution, and high pollution) based on their similarity of water quality characteristics. DA, as an important data reduction method, was used to assess the water pollution status and analysis of its spatiotemporal variation. PCA/FA identified potential pollution sources in wet and dry seasons, respectively, and the effective mechanisms, rules, and causes were explained. The APCS-MLR and PMF models apportioned their contributions to each water quality variable.
Also, the bio-physical parameters associated with the water quality of the two important water bodies of Lake Okeechobee and Florida Bay were investigated based on remotely sensed data. The principal objective of this part of the study is to monitor and assess the spatial and temporal changes of water quality using the application of integrated remote sensing, GIS data, and statistical techniques. The optical bands in the region from blue to near infrared and all the possible band ratios were used to explore the relation between the reflectance of a waterbody and observed data. The developed MLR models appeared to be promising for monitoring and predicting the spatiotemporal dynamics of optically active and inactive water quality characteristics in Lake Okeechobee and Florida Bay. It is believed that the results of this study could be very useful to local authorities for the control and management of pollution and better protection of water quality in the most important water bodies of South Florida.
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Multiscale process monitoring with singular spectrum analysisKrishnannair, Syamala 12 1900 (has links)
Thesis (MScEng (Process Engineering))--University of Stellenbosch, 2010. / Thesis presented in partial fulfilment of the requirements for the degree
of
Master of Science in Engineering
(Extractive Metallurgy)
In the Department of Process Engineering
at the University of Stellenbosch / ENGLISH ABSTRACT: Multivariate statistical process control (MSPC) approaches are now widely used for performance monitoring, fault detection and diagnosis in chemical processes. Conventional MSPC approaches are based on latent variable projection methods such as principal component analysis and partial least squares. These methods are suitable for handling linearly correlated data sets, with minimal autocorrelation in the variables. Industrial plant data invariably violate these conditions, and several extensions to conventional MSPC methodologies have been proposed to account for these limitations.
In practical situations process data usually contain contributions at multiple scales because of different events occurring at different localizations in time and frequency. To account for such multiscale nature, monitoring techniques that decompose observed data at different scales are necessary. Hence the use of standard MSPC methodologies may lead to unreliable results due to false alarms and significant loss of information.
In this thesis a multiscale methodology based on the use of singular spectrum analysis is proposed. Singular spectrum analysis (SSA) is a linear method that extracts information from the short and noisy time series by decomposing the data into deterministic and stochastic components without prior knowledge of the dynamics affecting the time series. These components can be classified as independent additive time series of slowly varying trend, periodic series and aperiodic noise. SSA does this decomposition by projecting the original time series onto a data-adaptive vector basis obtained from the series itself based on principal component analysis (PCA).
The proposed method in this study treats each process variable as time series and the autocorrelation between the variables are explicitly accounted for. The data-adaptive nature of SSA makes the proposed method more flexible than other spectral techniques using fixed basis functions. Application of the proposed technique is demonstrated using simulated, industrial data and the Tennessee Eastman Challenge process. Also, a comparative analysis is given using the simulated and Tennessee Eastman process. It is found that in most cases the proposed method is superior in detecting process changes and faults of different magnitude accurately compared to classical statistical process control (SPC) based on latent variable methods as well as the wavelet-based multiscale SPC. / AFRIKAANSE OPSOMMING: Meerveranderlike statistiese prosesbeheerbenaderings (MSPB) word tans wydverspreid benut vir werkverrigtingkontrolering, foutopsporing en .diagnose in chemiese prosesse. Gebruiklike MSPB word op latente veranderlike projeksiemetodes soos hoofkomponentontleding en parsiele kleinste-kwadrate gebaseer. Hierdie metodes is geskik om lineer gekorreleerde datastelle, met minimale outokorrelasie, te hanteer. Nywerheidsaanlegdata oortree altyd hierdie voorwaardes, en verskeie MSPB is voorgestel om verantwoording te doen vir hierdie beperkings.
Prosesdata afkomstig van praktiese toestande bevat gewoonlik bydraes by veelvuldige skale, as gevolg van verskillende gebeurtenisse wat by verskillende lokaliserings in tyd en frekwensie voorkom. Kontroleringsmetodes wat waargenome data ontbind by verskillende skale is nodig om verantwoording te doen vir sodanige multiskaalgedrag. Derhalwe kan die gebruik van standaard-MSPB weens vals alarms en beduidende verlies van inligting tot onbetroubare resultate lei.
In hierdie tesis word . multiskaalmetodologie gebaseer op die gebruik van singuliere spektrumontleding (SSO) voorgestel. SSO is . lineere metode wat inligting uit die kort en ruiserige tydreeks ontrek deur die data in deterministiese en stochastiese komponente te ontbind, sonder enige voorkennis van die dinamika wat die tydreeks affekteer. Hierdie komponente kan as onafhanklike, additiewe tydreekse geklassifiseer word: stadigveranderende tendense, periodiese reekse en aperiodiese geruis. SSO vermag hierdie ontbinding deur die oorspronklike tydreeks na . data-aanpassende vektorbasis te projekteer, waar hierdie vektorbasis verkry is vanaf die tydreeks self, gebaseer op hoofkomponentontleding.
Die voorgestelde metode in hierdie studie hanteer elke prosesveranderlike as . tydreeks, en die outokorrelasie tussen veranderlikes word eksplisiet in berekening gebring. Aangesien die SSO metode aanpas tot data, is die voorgestelde metode meer buigsaam as ander spektraalmetodes wat gebruik maak van vaste basisfunksies. Toepassing van die voorgestelde tegniek word getoon met gesimuleerde prosesdata en die Tennessee Eastman-proses. . Vergelykende ontleding word ook gedoen met die gesimuleerde prosesdata en die Tennessee Eastman-proses. In die meeste gevalle is dit gevind dat die voorgestelde metode beter vaar om prosesveranderings en .foute met verskillende groottes op te spoor, in vergeleke met klassieke statistiese prosesbeheer (SP) gebaseer op latente veranderlikes, asook golfie-gebaseerde multiskaal SP.
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Vibration response of the polar supply and research vessel the S. A. Agulhas II in Antarctica and the Southern oceanSoal, Keith Ian 12 1900 (has links)
Thesis (MEng) -- Stellenbosch University, 2014. / ENGLISH ABSTRACT: Full scale measurements were conducted on the polar supply and research vessel
the S.A. Agulhas II during a 78 day voyage from Cape Town to Antarctica in
2013/2014. Investigations were conducted into the effect of vibration on human
comfort and the structural dynamic response of the vessel. Vibration measured
in the bridge of the vessel is found to have little effect on human comfort for a
standing person and is classified as not uncomfortable according to BS ISO 2631-1.
Structural fatigue as a result of vibration is found to reach levels where damage
is possible in the stern and where damage is probable in the bow during open
water navigation, according to ship vibration guidelines by Germanischer Lloyd.
Multivariate statistical analyses are performed to investigate the relationships between
multiple predictor variables and vibration response. Factor analysis revealed
data structure from which specific physical phenomena could be identified. Multivariable
linear regression models are developed to predict vibration response and
are found to provide more accurate predictions in open water than in ice. The
2-node, 3-node and 4-node normal bending modes of the structure are identified
using operational modal analysis while the vessel was moored in the harbour. The
natural frequencies, damping ratios and mode shapes are estimated and compared
using LMS Operational PolyMAX and ARTeMIS CCSSI. A comparison of operational
modal analysis results to the STX Finland finite element model show that
the vessel’s modes occur at lower frequencies than numerically predicted. Clear
potential is identified to further investigate structural vibration and operational
modal analysis algorithm development in future research. / AFRIKAANSE OPSOMMING: Volskaal metings was op die poolvoorsienings en navorsingskip die S.A. Agulhas
II uitgevoer tydens ’n 78 dae reis van Kaapstad tot Antarktika in 2013/2014.
Ondersoeke is uitgevoer met betrekking tot die effek van vibrasie op menslike gemak
en die strukturele dinamiese reaksie van die vaartuig. Vibrasie wat in die brug
van die skip gemeet is, het min invloed op menslike gemak vir ’n staande persoon
en word geklassifiseer as nie ongemaklik volgens BS ISO 2631-1. Strukturele vermoeidheid
as gevolg van vibrasie bereik vlakke waar skade moontlik is in die spieël
en waar skade waarskynlik is in die boog tydens navigasie in oop water, volgens
skip vibrasie riglyne deur Germanischer Lloyd. Meerveranderlike statistiese ontledings
is uitgevoer om die verhoudings tussen verskeie voorspellerveranderlikes
en vibrasieterugvoer te ondersoek. Faktorontleding het data struktuur openbaar
waaruit spesifieke fisiese verskynsels geïdentifiseer kan word. Multi-veranderlike lineêre
regressiemodelle was ontwikkel om vibrasie reaksie te voorspel en lewer meer
akkurate voorspellings in oop water as in ys. Die 2-nodus, 3-nodus en 4-nodus normale
buig modes van die struktuur is geïdentifiseer met behulp van operasionele
modale analise terwyl die skip vasgemeer in die hawe is. Die natuurlike frekwensie,
demping verhoudings en mode vorms is beraam en vergelyk met behulp van
LMS operasionele Polymax en ARTeMIS CCSSI. ’n vergelyking van operasionele
modale analise resultate en ’n STX Finland eindige element model toon dat die
vaartuig se modusse voorkom by laer frekwensies as wat numeries voorspel word.
Duidelike potensiaal is geïdentifiseer om strukturele vibrasie en die ontwikkeling
van operasionele modale analise algoritmes te ondersoek in toekomstige navorsing.
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Classificação de domínios mineralógicos e caracterização de minérios de níquel da mina de Santa Rita - BA, em apoio à geometalurgia. / Classification of mineralogical domais and characterization of nickel ore from Santa Rita mine - BA, in support of geometallurgy.Contessotto, Renato 16 March 2017 (has links)
A Mina de Santa Rita, situada no complexo máfico-ultramáfico Fazenda Mirabela, é uma intrusão máfica-ultramáfica, mineralizada a sulfetos de níquel e cobre, situada no sudeste do Estado da Bahia, município de Itagibá. Esse depósito é composto por rochas de idade Paleoproterozóica, metamorfizadas em fácies granulito. Os sulfetos de níquel e cobre ocorrem disseminados e, preferencialmente, associados a harzburgitos, olivina ortopiroxenitos e ortopiroxenitos. O minério é composto por uma grande variedade de Mg-silicatos, sendo que o níquel ocorre essencialmente como pentlandita nos peridotitos, além de se apresentar como elemento menor em silicatos e espinélios em rochas mais máficas. Informações de processo demonstram a impossibilidade de se estabelecer uma correlação robusta entre a composição química do minério e seu comportamento na etapa de beneficiamento mineral. Desta forma, o conhecimento da variabilidade mineralógica no depósito é de fundamental importância para o planejamento de lavra e processamento mineral. Mais de 300 amostras do plano de mineração de curto prazo (2013-2017) relativas a intervalos de furos de sondagem considerados no estudo de viabilidade econômica (período de 1985-2004) foram agrupadas em domínios mineralógicos, utilizando a análise estatística multivariada de dados de difração de raios X (DRX-AEM). Dezessete domínios mineralógicos inicialmente definidos são essencialmente diferenciados com base na presença e conteúdos relativos dos principais minerais de ganga: serpentina, olivina e piroxênio. Amostras representativas dos principais domínios mineralógicos, pré-definidos por DRX-AEM, foram submetidas a estudos de caracterização mineralógica de detalhe por análise de imagens (MEV-MLA). Os resultados indicam que os grupos com composições mais peridotíticas e/ou carbonáticas, com maiores conteúdos de serpentina, apresentam menor tempo de moagem para atingir P95 igual a 0,15 mm; maior alteração dos grãos de pentlandita; maior parcela de total de níquel associado a silicatos; menor grau de liberação dos sulfetos; e maior quantidade de sulfetos abaixo de 10 ?m, em relação aos grupos de composição mais piroxenítica. / The Santa Rita mine, located in the mafic-ultramafic complex Fazenda Mirabela, is a mafic-ultramafic intrusion mineralized to nickel and copper sulphides located in the southeast of Bahia state, Itagibá municipality. The nickel sulphide deposit comprises a portion of a mafic-ultramafic layered complex under granulite metamorphism facies. Disseminated Ni and Cu sulphides form a stratiform body parallel to the lithostratigraphic contacts extending upwards essentially from the harzburgite unit and through the olivine orthopyroxenite unit. The nickel content is mainly associated to pentlandite in peridotitic rocks but also enriched in silicates and spinels in mafic rocks (dunites). Industrial plant benchmark data have shown the unfeasibility of establishing a strong relation between the ore chemical composition and its behavior in the mineral beneficiation process. Therefore, the knowledge of the mineralogical variability in the deposit is crucial for mine planning and mineral/metallurgical processing. More than 300 samples from drill core samples from the feasibility studies (period of 1985-2004) included in the short-term mining plan (2013-2017) were clustered into geological domains applying multivariate statistical analysis (MSA) of X-ray diffraction data (XRD). Results discriminated seventeen initial mineralogical domains considering the content of major gangue minerals: serpentine, olivine and pyroxene. Representative samples of the main mineralogical domains pre-defined by XRD-MSA ore-types were later subject to sieve size analysis followed by detailed mineralogical studies by automated SEM image analysis (MLA). The results indicate that groups with more peridotite and / or carbonatic compositions, with higher content of serpentine, have less time of grinding to reach P95 equal to 0,15 mm; high level of pentlandite alteration; greater portion of nickel associated into silicates; lower sulphides liberation degree; and a higher amount of sulphides below 10 ?m; in relation to the most pyroxenic composition groups.
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