Дисертації з теми "Analysis criteria"

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Numerous optimization problems involve systems with multiple and often contradictory criteria. Such contradictory criteria have been an issue for marine/naval engineering design studies for many years. This problem becomes more important when one considers novel ship types with very limited or no operational record. A number of approaches have been proposed to overcome these multiple criteria design optimization problems. This Thesis follows the Parameter Space Investigation (PSI) technique to address these problems. The PSI method is implemented with a software package called MOVI (Multi-criteria Optimization and Vector Identification). Two marine/naval engineering design optimization models were investigated using the PSI technique along with the MOVI software. The first example was a bulk carrier design model which was previously studied with other optimization methods. This model, which was selected due to its relatively small dimensionality and the availability of existing studies, was utilized in order to demonstrate and validate the features of the proposed approach. A more realistic example was based on the "MIT Functional Ship Design Synthesis Model" with a greater number of parameters, criteria, and functional constraints. A series of optimization studies conducted for this model demonstrated that the proposed approach can be implemented in a naval ship design environment and can lead to a large design parameter space exploration with minimum computational effort.
Lieutenant Junior Grade, Turkish Navy

Thesis (M.S. in Mechanical Engineering)--Naval Postgraduate School, March 2005.
Thesis Advisor(s): Fotis Papoulias, Roman B. Statnikov. Includes bibliographical references (p. 241). Also available online.

An important part of the study of dynamical systems is the fitting of models to time-series data. That is, given the data, a series of observations taken from a (not fully understood) system of interest, we would like to specify a model, a mathematical system which generates a sequence of “simulated” observations. Our aim is to obtain a “good” model — one that is in agreement with the data. We would like this agreement to be quantitative — not merely qualitative. The major subject of this thesis is the question of what good quantitative agreement means. Most approaches to this question could be described as “predictionist”. In the predictionist approach one builds models by attempting to answer the question, “given that the system is now here, where will it be next?” The quality of the model is judged by the degree to which the states of the model and the original system agree in the near future, conditioned on the present state of the model agreeing with that of the original system. Equivalently, the model is judged on its ability to make good short-term predictions on the original system. The main claim of this thesis is that prediction is often not the most appropriate criterion to apply when fitting models. We show, for example, that one can have models that, while able to make good predictions, have long term (or free-running) behaviour bearing little resemblance to that exhibited in the original time-series. We would hope to be able to use our models for a wide range of purposes other than just prediction — certainly we would like our models to exhibit good free-running behaviour. This thesis advocates a “behaviourist” approach, in which the criterion for a good model is that its long-term behaviour matches that exhibited by the data. We suggest that the behaviourist approach enjoys a certain robustness over the predictionist approaches. We show that good predictors can often be very poorly behaved, and suggest that well behaved models cannot perform too badly at the task of prediction. The thesis begins by comparing the predictionist and behaviourist approaches in the context of a number of simplified model-building problems. It then presents a simple theory for the understanding of the differences between the two approaches. Effective methods for the construction of well-behaved models are presented. Finally, these methods are applied to two real-world problems — modelling of the response of a voltage-clamped squid “giant” axon, and modelling of the “yearly sunspot number”.

This thesis presents a modification of existing entropy-based splitting criteria for classification and regression trees. Trees are typically grown using splitting criteria that choose optimal splits without taking future splits into account. This thesis examines localised splitting criteria that are based on local averaging in regression trees or local proportions in classification trees. The use of a localised criterion is motivated by the fact that future splits result in leaves that contain local observations, and hence local deviances provide a better approximation of the deviance of the fully grown tree. While most recent research has focussed on tree-averaging techniques that are aimed at taking a moderately successful splitting criterion and improving its predictive power, this thesis concentrates on improving the splitting criterion. Use of a localised splitting criterion captures local structures and enables later splits to capitalise on the placement of earlier splits when growing a tree. Using the localised splitting criterion results in much simpler trees for pure interaction data (data with no main effects) and can produce trees with fewer errors and lower residual mean deviances than those produced using a global splitting criterion when applied to real data sets with strong interaction effects. The superiority of the localised splitting criterion can persist when multiple trees are grown and averaged using simple methods. Although a single tree grown using the localised splitting criterion can outperform tree averaging using the global criterion, generally improvements in predictive performance are achieved by utilising the localised splitting criterion's property of detecting local discontinuities and averaging over sets of trees grown by placing splits where the deviance is locally minimal. Predictive performance improves further when the degree of localisation of the splitting criterion is randomly selected and weighted randomisation is used with locally minimal deviances to produce sets of trees to average over. Although state of the art methods quickly average very large numbers of trees, thus making the performance of the splitting criterion less critical, predictive performance when the localised criterion is used in bagging indicates that different splitting methods warrant investigation. The localised splitting criterion is most useful for growing one tree or a small number of trees to examine structure in the data. Structurally different trees can be obtained by simply splitting the data where the localised splitting criterion is locally optimal.

Multiple criteria decision analysis (MCDA) techniques are developed to address challenging classification problems arising in engineering management and elsewhere. MCDA consists of a set of principles and tools to assist a decision maker (DM) to solve a decision problem with a finite set of alternatives compared according to two or more criteria, which are usually conflicting. The three types of classification problems to which original research contributions are made are

1. Screening: Reduce a large set of alternatives to a smaller set that most likely contains the best choice.
2. Sorting: Arrange the alternatives into a few groups in preference order, so that the DM can manage them more effectively.
3. Nominal classification: Assign alternatives to nominal groups structured by the DM, so that the number of groups, and the characteristics of each group, seem appropriate to the DM.

Research on screening is divided into two parts: the design of a sequential screening procedure that is then applied to water resource planning in the Region of Waterloo, Ontario, Canada; and the development of a case-based distance method for screening that is then demonstrated using a numerical example.

Sorting problems are studied extensively under three headings. Case-based distance sorting is carried out with Model I, which is optimized for use with cardinal criteria only, and Model II, which is designed for both cardinal and ordinal criteria; both sorting approaches are applied to a case study in Canadian municipal water usage analysis. Sorting in inventory management is studied using a case-based distance method designed for multiple criteria ABC analysis, and then applied to a case study involving hospital inventory management. Finally sorting is applied to bilateral negotiation using a case-based distance model to assist negotiators that is then demonstrated on a negotiation regarding the supply of bicycle components.

A new kind of decision analysis problem, called multiple criteria nominal classification (MCNC), is addressed. Traditional classification methods in MCDA focus on sorting alternatives into groups ordered by preference. MCNC is the classification of alternatives into nominal groups, structured by the DM, who specifies multiple characteristics for each group. The features, definitions and structures of MCNC are presented, emphasizing criterion and alternative flexibility. An analysis procedure is proposed to solve MCNC problems systematically and applied to a water resources planning problem.

Mixing is a key process in microfluidic systems since that samples and reagents generally need to be mixed thoroughly before chemical or biological analysis or reactions. Micromixers are designed to fulfil this critical process. In general, the development of microdevices is a competitive field that requires from researchers shorter times and lower costs in prototyping. Computational Fluid Dynamics (CFD) helps in reducing the time from concept to device design. Intuition and experience of the designer is usually behind its application on design improvement, by analyzing some physical variables to determine the effect of design parameters and to adjust them accordingly to the pursued objectives. In this thesis, a design and optimization strategy is presented and used for the analysis and design of micromixers. The method systematically integrates CFD with an optimization strategy based on the use of Design of Experiments, Surrogate Modelling and Multi-Objective Genetic Algorithm techniques. The aim is to define optimum designs that give the trade-off of the performance parameters, which in this study are the mixing index, defined on the basis of mass concentration distribution, and the pressure drop in the microchannel. Three types of micromixers have been studied and their geometric parameters have been optimized. They are the Staggered Herringbone Mixer and two novel designs, a planar micromixer with baffles in the microchannel and a 3-D T-type micromixer. A completed fabrication method was implemented as part of this thesis work and it was used to fabricate some of the micromixers. Experimental measurements and published data have been used to validate the numerical results. The outcomes of this thesis demonstrate that using advanced optimisation techniques on the basis of CFD solutions and analyses allows the design of optimum micromixers for different operation conditions, which can be set by the designer, without being necessary to use a referential design to start the method.

Road smoothness is one of the most important road functional characteristics because it affects ride quality, operation cost, and vehicle dynamic load. There are many types of devices that measure the road profile, which is often used to compute different smoothness indices. The development of performance-based specifications and pavement warranties that use ride quality as a performance measure has increased the need for accurate measurement of pavement smoothness. For this reason, researchers have compared and evaluated the performance of available profilers and several profiler accuracy criteria have been proposed. However, there is not a definite answer on the ability of available profilers to accurately measure the actual road profile as well as the various smoothness indices. A recent profiler round-up compared the performance of 68 profilers on five test sections at Virginia Smart Road. The equipment evaluated included high-speed, light-weight, and walking-speed profilers, in addition to the reference device (rod and level). The test sites included two sites with traditional hot-mix asphalt (HMA) surfaces, one with a coarse-textured HMA surface, one on a continuously reinforced concrete pavement (CRCP), and one on a jointed plain concrete pavement (JCP). This investigation used a sample of the data collected during the experiment to compare the profiles and International Roughness Index (IRI) measured by each type of equipment with each other and with the reference. These comparisons allowed determination of the accuracy and repeatability capabilities of the existing equipment, evaluation of the appropriateness of various profiler accuracy criteria, and recommendations of usage criteria for different applications. The main conclusion of this investigation is that there are profilers available that can produce the level of accuracy (repeatability and bias) required for construction quality control and assurance. However, the analysis also showed that the accuracy varies significantly even with the same type of device. None of the inertial profilers evaluated met the current IRI bias standard requirements on all five test sites. On average, the profilers evaluated produced more accurate results on the conventional smooth pavement than on the coarse textured pavements. The cross-correlation method appears to have some advantages over the conventional point-to-point statistics method for comparing the measured profiles. On the sites investigated, good cross-correlation among the measured and reference profiles assured acceptable IRI accuracy. Finally, analysis based on Power Spectral Density and gain method showed that the profiler gain errors are nonuniformly distributed and that errors at different wavelengths have variable effects on the IRI bias.
Master of Science

Nowadays, the interest in the synchronous reluctance machines is growing up due to their several merits in comparison to other machine types. These machines offer high torque density with respect to the induction machines. Their torque density is slightly lower than permanent magnet synchronous machines even though the lower performance is compensated by a much cheaper rotor. Since synchronous reluctance machines do not induce voltage when the stator is not supplied, there are not short circuit currents and braking torques due to the electrical faults, e.g. they have high fault tolerant capability. In addition, synchronous reluctance machine has a robust structure, and a wide constant power speed range. For these aforementioned reasons, these machines are employed in several applications. However, there is a prominent defect of this kind of machines which is the low power factor. This defect is addressed by assisting the motor by permanent magnets within the flux barriers of the rotor leading to the permanent magnet assisted synchronous reluctance motor. In addition, these kinds of machines has high torque ripple. This is due to the high harmonic content in the magneto motive force which interacts with the rotor anisotropy. Several approaches are proposed to reduce the torque ripple, such as: (a) using skewed rotor, (b) adopting two different flux-barrier geometries in the same lamination, i.e., asymmetric rotor, (c) using equally spaced the flux-barrier ends along the rotor periphery, and (d) optimization approaches were applied to smooth the torque. The synchronous reluctance machine is becoming of great interest in the last years, due to two key reasons: (i) the increase of rare earth permanent magnet cost and (ii) the increasing request of high-efficiency machines. Therefore, the reluctance motor and the ferrite permanent assisted reluctance motor are becoming competitors of both surface-mounted permanent magnet machines and induction machines in many applications. Such motors are also becoming particularly interesting when the control is based on the sensor-less rotor position detection. Even if there is a great interest in this kind of machines, there is a few work about the analytical design of their rotor, e.g. about how to select the end barrier angles, designing the iron ribs, and designing the permanent magnet robust towards the demagnetization. In the majority of the cases the reluctance machine is analyzed by using finite element analysis. The results are precise and useful for achieving a specific geometry to be prototyped, but they refer to that particular solution and they lose generality. In other words, it is difficult to find general rules to design reluctance machines, since the analysis approach is focused on a single objective. During the manufacturing process, there are some manufacturing imprecision, such as mass unbalance, bearing tolerance, shaft bow, and etc., cause eccentricity fault. Eccentricity may cause magnetic and dynamic problems with additional vibrations, noises, and torque pulsations. Although the eccentricity faults in induction and permanent magnet motors are extensively investigated, there are a few publications on synchronous reluctance machines with eccentricity. It is important to study the effect of rotor eccentricity on these machines because of their high anisotropy and critical iron parts in the rotor (iron ribs). For the aim of designing the iron ribs thicknesses, the unbalanced magnetic force acting on theses ribs should be accurately estimated. Main contribution of the thesis This thesis aims to give an useful analytical approach for reaching a preliminary geometry of both synchronous reluctance and permanent magnet assisted synchronous reluctance motors, as starting point for a successive optimization. For more accurate design of the rotor iron ribs, the electro-magnetic force acting on the rotor, in different rotor eccentricity cases, are analytically computed. In addition, a comparative studies (analytically and FE) between the synchronous reluctance, permanent magnet assisted, and surface mounted permanent magnet machines, in different eccentricity cases, is carried out. Therefore, this thesis is divided into four main parts. At the first part, an analytical model based on the magnetic equivalent lumped network of the reluctance motor is discussed. This model studies the magnetic performance of the concentric synchronous reluctance motor. Then, this analytical model is adopted in order to study the impact of different eccentricity scenarios (static and dynamic eccentricity) on the reluctance motor. Different stator windings configurations (distributed and concentrated windings) and different rotor geometries (symmetric and asymmetric rotor) are considered. After that, the eccentric synchronous reluctance machine is compared with the eccentric permanent magnet assisted synchronous reluctance machine. The impact of the barrier dimensions, the rotor geometry, and the permanent magnet type is highlighted in this comparison. Furthermore, an analytical comparison between the reluctance motor and the surface mounted permanent magnet motor is carried out in different cases of eccentricity. The axial non uniform displacement of the rotor axis from the stator axis, at one end and both ends of the axis, are involved in this analytical comparison. The second part aims to achieve more realistic estimation of the electromagnetic forces acting on the rotor by considering the effect of stator slots and the magnetic voltage drop due to the actual B-H curve of the motor iron. The analytical model is developed for both eccentric and concentric synchronous reluctance motor. Then, an experimental validation of the analytical and FE analysis is carried out. At the third part, an analytical approach for designing the permanent magnet of the permanent magnet assisted reluctance motor is proposed. The width and the thickness are selected so as to achieve the desired no-load air-gap flux density and resist the demagnetization under the desired loading conditions, respectively. Both complete and simplified analytical analyses are discussed. In addition, the analytical approach is presented in both cases of neglecting and considering the rotor iron ribs. Then, from the previously mentioned three parts of this thesis, a rapid multi-objectives analytical approach is proposed to achieve the initial design of the synchronous reluctance and permanent magnet assisted synchronous reluctance motors. Finally, at the fourth part, a graphical user interface application for concentric and eccentric synchronous reluctance motor is developed. This application estimates stator and rotor scalar magnetic potential, air-gap flux density, electromagnetic torque, magnetic force acting on the rotor. The input parameters of this application are - the geometrical data of the stator and rotor, - the electric loading (kA/m), the electric load angle in (electric degree), - the rotor geometry type, e.g., symmetric or asymmetric rotor geometry, - number of flux-barriers per rotor pole, - eccentricity type or no eccentricity, e.g., healthy case, - the eccentricity value. Then, the user can run the application to estimate the magnetic performance of both concentric and eccentric synchronous reluctance motor.
Negli ultimi vent'anni l'interesse per le macchine sincrone a riluttanza è notevolmente cresciuto. Lo sviluppo e la ricerca dedicata a questi motori, supportata dai diversi vantaggi che presentano rispetto ad altri tipi di macchine, ha permesso a questa tipologia di macchina di guadagnarsi uno quota di mercato in diverse applicazioni industriali. I motori a riluttanza offrono una piu alta densità di coppia rispetto ai motori asincroni. Tuttavia, se confrontati con i motori sincroni a magneti permanenti, essi presentano una densità di coppia ed una efficenza minori. Tale decremento delle prestazioni rispetto alle macchine a magneti permanenti è tuttavia compensato dalla complessiva riduzione del costo di costruzione del rotore. In aggiunta, essi presentano una struttura rotorica piu robusta delle macchine sincrone a magneti superficiali e consentono di ottenere un piu ampio range di funzionamento a potenza costante. I principali svantaggi delle macchine sincrone a riluttanza sono il basso fattore di potenza e le elevate oscillazioni di coppia. Il primo svantaggio, correlato alla assenza di alcun sistema di eccitazione sul rotore, viene normalmente mitigato attraverso l'introduzione di magneti permanenti all'interno delle barriere di flusso. Questo tipo di configurazione prende il nome di motore a riluttanza assistita da magnete permanente. Il secondo svantaggio, ossia l'eccessivo torque ripple, è dovuto all'elevato contenuto armonico della forza magnetomotrice che interagisce con l'anisotropia rotorica. Diversi approcci sono stati proposti in letteratura allo scopo di ridurre tali oscillazioni, tra i quali: (a) lo skewing del rotore, (b) barriere rotoriche geometricamente asimmetriche rispetto all'asse interpolare, (c) barriere rotoriche asimmetriche rispetto all'asse polare, (d) equa distribuzione delle barriere lungo la periferia del rotore, e (e) l'ottimizzazione della intera geometria delle barriere. Il grande interesse suscitato negli ultimi anni è dovuto principalmente a due motivi: (i) l'aumento di costo delle terre rare, utilizzate in magneti ad elevato contenuto energetico (NdFeB e SmCo); (ii) la crescente richiesta di macchine ad alta efficienza. Pertanto, il motore a riluttanza e il motore a riluttanza assistito da magneti permanenti stanno diventando concorrenti di entrambe le macchine a magneti permanenti e macchine a asincrone in molte applicazioni. Un altro vantaggio intrinseco delle macchine sincrone a riluttanza è che non inducono tensione a vuoto, quando il rotore è fermo, conseguentemente le correnti di corto circuito e coppie frenanti che si possono creare a causa dei guasti elettrici, sono trascurabili. Per quanto concerne l'aspetto controllistico è doveroso sottolineare il crescente interesse verso le le macchine sicrone a riluttanza. Tale interesse è sostanzialmente giustificato dalla naturale propensione della stessa macchina ad essere controllata senza alcun sensore di velocità. Sebbene vi sia un grande interesse per questo tipo di macchine, ci sono pochi lavori sulla progettazione analitica del loro rotore, ad esempio su come selezionare gli angoli di fine barriera, il dimensionamento dei ponticelli di ferro ed dettagli sulla progettazione robusta nei confronti della smagnetizzazione dei magneti permanenti. Nella maggior parte dei casi la macchina riluttanza viene analizzata mediante analisi agli elementi finiti. I risultati sono precisi e utili per realizzare una geometria specifica, ma si riferiscono ad una particolare soluzione perdendo generalità. In altre parole, è difficile trovare regole generali per progettare macchine a riluttanza. Per colmare questa lacuna, questa tesi si propone di fornire un approccio analitico utile alla determinazione di una geometria preliminare del motore, come punto di partenza per un'ottimizzazione successiva. La progettazione accurata dei ponticelli di ferro del rotore e gli effetti sulla forza elettromagnetica che agisce sul rotore con diversi gradi di eccentricità sono considerati. Questo lavoro di tesi è suddiviso in quattro parti principali. Un modello analitico basato sul circuito magnetico equivalente a parametri concentrati del motore a riluttanza viene presentato e discusso nella prima parte. Questo modello studia il rendimento magnetico del motore sincrono a riluttanza concentrica. Lo stesso modello analitico è utilizzato per lo studio di differenti casi di eccentricità ed il loro impatto sulle prestazioni del motore a riluttanza. Motori a riluttanza con diversi tipi di avvolgimenti statici e diverse geometrie di rotore, simmetriche ed asimmetriche, vengono considerate. Lo stesso metodo viene applicato a motori a riluttanza con magneti permanenti e confrontata con il motore a riluttanza eccentrico. I risultati prodotti dai modelli utilizzati vensono confrontati tramie simulazioni agli elementi finiti. Inoltre, un confronto analitico tra il motore a riluttanza e motore a magneti permanenti superficiali viene condotta in diversi casi di eccentricità. La seconda parte si propone di stimare in modo più accurato le forze elettromagnetiche agenti sul rotore, considerando l'effetto delle cave di statore e la caduta di tensione magnetica dovuta alla effettiva curva B-H del lamierino ferromagnetico. Il modello analitico è indicato per macchine con e senza presenza di eccentricità. Infine, misure sperimentali vengono condotte per validare la bonta' dei modelli analitici ed agli elementi finiti. Nella terza parte, si propone un approccio analitico per la progettazione del motore a riluttanza assistito da magneti permanenti. La larghezza e lo spessore dei magneti sono scelti in modo da realizzare la densità di flusso a vuoto al trafetto desiderata e resistere alla smagnetizzazione che si possono presentare in condizioni di sovraccarico. Infine, un rapido approccio analitico e multi-obiettivo è proposto per la progettazione preliminare di motori a riluttanza e motori a riluttanza assistiti. Nella quarta parte è stata sviluppata un'interfaccia utente grafica per l'analisi del motore a riluttanza. Questa applicazione stima i potenziali scalari magnetici di statore e rotore, la densità di flusso al traferro, la coppia elettromagnetica, la forza magnetica che agisce sul rotore. I parametri di ingresso di questa applicazione sono: - dati geometrici dello statore e del rotore, - carico elettrico (kA / m), e la sua fase (grado elettrico), - il tipo di geometria del rotore, ad esempio, simmetrico o asimmetrico (Macaone), - Numero di barriere di flusso per polo del rotore, - il tipo di eccentricità o nessuna eccentricità, per esempio, il caso con rotore concentrico, - il valore di eccentricità. Perciò, l'utente può usare l'applicazione per stimare le prestazioni della macchina.

Forest measurements are inherently spatial. Soil productivity varies spatially at fine scales and tree growth responds by changes in growth-age trajectories. Measuring spatial variability is a perquisite to more effective analysis and statistical testing. In this study, current techniques of partial redundancy analysis and constrained cluster analysis are used to explore how spatial variables determine structure in a managed regular spaced plantation. We will test for spatial relationships in the data and then explore how those spatial relationships are manifested into spatially recognizable structures. The objectives of this research are to measure, test, and map spatial variability in simulated forest plots. Partial redundancy analysis was found to be a good method for detecting the presence or absence of spatial relationships (~95% accuracy). We found that the Calinski-Harabasz method consistently performed better at detecting the correct number of clusters when compared to several other methods. While there is still more work that can be done we believe that constrained cluster analysis has promising applications in forestry and that the Calinski-Harabasz criterion will be most useful.
Master of Science

This study is conducted with the aims to develop a new ranking method for multi-criteria decision making problem with conflicting criteria. Such a problem has a set of Pareto solutions, where the act of improving a value of one solution will result in depreciating some of the others. Thus, in this type of problem, there is no unique solution. However, out of many available options, the Decision Maker eventually has to choose only one solution. With this problem as the motivation, the current study develops a compromise ranking algorithm, namely a trade-off ranking method. The trade-off ranking method able to give a trade-off solution with the least compromise compared to other choices as the best solution. The properties of the algorithm are studied in the thesis on several test cases. The proposed method is compared against several multi-criteria decision making methods with ranking based on the distance measure, which are the TOPSIS, relative distance and VIKOR. The sensitivity analysis and uncertainty test are carried out to examine the methods robustness. A critical criteria analysis is also done to test for the most critical criterion in a multi-criteria problem. The decision making method is considered further in a fuzzy environment problem where the fuzzy trade-off ranking is developed and compared against existing fuzzy decision making methods.

The pearl oyster Pinctada martensii or Pinctada fucata is the oyster for produce the South China Sea Pearl, and the production of pearl oyster Pinctada martensii plays a key role for the economic and social welfare of the coastal areas. To guarantee both rich and sustainability of providing pearl oyster productions, addressing the suitable areas for aquaculture is a very important consideration in any aquaculture activities. Relatively rarely, in the case of site selection research, the researchers use GIS analysis to identify suitable sites in fishery industry in China. Therefore, I decided to help the local government to search suitable sites form the view of GIS context. This study was conducted to find the optimal sites for suspended culture of pearl oyster Pinctada martensii using GIS-based multi-criteria analysis. The original idea came from the research of Radiarta and his colleagues in 2008 in Japan. Most of the parameters in the GIS model were extracted from remote sensing data (Moderate Resolution Imaging Spectroradiometer and Landsat 7). Eleven thematic layers were arranged into three sub-models, namely: biophysical model, social-economic model and constraint model. The biophysical model includes sea surface temperature, chlorophyll-α concentration, suspended sediment concentration and bathymetry. The criteria in the social-economic model are distance to cities and towns and distance to piers. The constraint model was used to exclude the places from the research area where the natural conditions cannot be fulfilled for the development of pearl oyster aquaculture; it contains river mouth, tourism area, harbor, salt fields / shrimp ponds, and non-related water area. Finally those GIS sub-models were used to address the optimal sites for pearl oyster Pinctada martensii culture by using weighted linear combination evaluation. In the final result, suitability levels were arranged from 1 (least suitable) to 8 (most suitable), and about 2.4% of the total potential area had the higher levels (level 6 and 7). These areas were considered to be the places that have the most suitable conditions for pearl oyster Pinctada martensii for costal water of Yingpan.

With the rapid advancement of technologies, software is gaining its popularity in assisting our daily activities in the last decades. This circumstance causes a rising concerns about a software product with high quality which lead to a question about the justification whether a software product has high quality. Therefore, a numerous of researches and studies had spent a lot of effort in software product quality assessment in order to justify whether the software product(s) under study have satisfactory quality. One of the foremost approaches to assess software product quality is the application of the quality models. For example, quality model ISO 9126. However, the quality models do not provide an explicit way to aggregate the performance of different quality aspects nor handling the various interests raised from different perspective or stakeholders. Although many studies have been conducted to aggregate the different measures of quality attributes, they are still not capable to include the various interests raised by different software product stakeholders. Therefore, some studies have attempted to apply MCDA methods in order to aggregate the measure of quality attributes as the ultimate software product quality and handling the various quality interests. However, they do not provide any rational about their particular choice of MCDA methods. Most of them justify their choice by referring to high popularity of the selected MCDA method. Without studying the suitability of MCDA methods in the application domain of the software product, it is difficult to conclude whether the chosen MCDA methods fit in the intended software engineering discipline. Furthermore, there is no systematic approach available to help other software practitioners in selecting the MCDA method that will be suitable for their needs and constraints in software product quality assessment. This thesis aims to provide the key concepts for an effective selection of suitable MCDA method for the purpose of software product quality assessment. A foremost part of this thesis presents two systematic reviews. The first review illustrates the evaluation of the characteristics of MCDA methods. The second review identifies the major needs and constraints of the software quality assessment potential MCDA method has to consider in order to be used for assessing quality of software products. Based on the results from both systematic reviews, a selection framework named MCDA-SQA framework is formulated. This framework is intended to assist the software practitioners to systematically select and adapt appropriate MCDA method(s) in order to fulfil their quality assessment needs and the respective environmental concerns.

The thesis applies the theories of Multi Criteria Decision Analysis (MCDA) with a constructive research to the environment of real estate portfolio management. The aim of the research is to create a preference model for sorting real estates. There are multiple conflicting and incommensurable criteria involved in MCDA that cause a challenging decision situation for the decision maker. The advantage of using MCDA is decision maker’s ability to learn and understand both his own and others’ values and judgments. These benefits are received by actions such as taking the decision maker’s preferences into account and concerning the decision problem explicitly by structuring and synthesizing the information. Previously, Multi Attribute theories have been successfully applied to the portfolio selection of road pavement and bridge repairing projects, for example. The research was implemented in three sections from which the first one was a theoretical review that sought to present the basics of MCDA by defining the Multi Attribute Value Theory (MAVT) process. After theoretical review followed the data collection and analysis that aimed to identify the guiding criteria for the decision making and the attributes by which the achievement of the criteria being measured. The thesis was outlined to consider only the effect of the property specific endogenous factors. The last section of the study, construction, applies the information got from the previous sections by creating a preference model for the decision making of property portfolio management. The process and value tree described in the study were constructed from the perspective of real estate owners who own properties only as an investment. As a result of the thesis, five criteria were formed by which the sorting of real estates is evaluated. The criteria were: a macro location that seeks to describe the macro environmental development, a micro location that takes a stand on how reachable the real estate is, a contract price that presented the income side of the cash flow, a repairing need that was included because it has a high effect on the outcomes, and the ability to develop which means the capability of a building to produce financial benefits with the development operations. The suggested attributes for the criteria were for macro location the new construction production of the property type in relation to the development of areal GDP, for micro location the transportation time and type from the areal center, for the contract price the average of the contract prices in relation to the area of each rental agreement, for repairing needs the repairing costs got from the long term repairing plan and for ability to develop was seen that best option to measure the achievement of it would be expert opinion. The study did not take a stand on the weights of the criteria nor the value functions of the attributes because it would require focusing on the single real estate investor whereas this thesis was desired to keep on the general level. As a whole, it was concluded that creating a universal model for sorting real estates is not possible because of the unique nature of the weights and value functions. Therefore it would be more appropriate to execute the model constructing process with the case investor. The process described in this study should, however, give readiness to create a preference model for the investors that were in the focus of this work. The preference model formed as a result of the process will propose an interest of sorting based on the endogenous property specific features. However, the model should be used only as an assistance in decision making so that the decision maker would use it to support his decisions
Diplomityö pyrkii konstruktiivisen tutkimuksen avulla soveltamaan monikriteerisiä päätösanalyysiteorioita (Multi Criteria Decision Analysis — MCDA) kiinteistöportfoliohallinnan päätöksentekoon. Teorioita sovelletaan työssä kehittämällä kiinteistöportfoliohallinnan päätöksentekoa avustava malli. MCDA on oppi metodeista ja lähestymistavoista, joissa eri vaihtoehtojen paremmuutta arvioidaan suhteessa päätöksentekijän asettamiin tavoitteisiin. Teorioiden käsittelemien päätösongelmien luonteeseen kuuluvat useat ristiriitaiset ja yhteismitattomat kriteerit, jotka tekevät päätöksenteosta erittäin haasteellista. MCDA:n tuoma arvo päätöksentekoon syntyy sen jäsennellystä ja selkeästä tavasta käsitellä päätösongelmaa, minkä johdosta päätöksentekijä tulee tietoisemmaksi itse päätösongelmasta sekä omista ja muiden sidosryhmien arvoista ja tavoitteista. Monikriteerisiä päätösanalyysiteorioita on sovellettu aiemmin esimerkiksi infrapuolella siltojen kunnossapitoprojektien valintaan. Kehitetyn matemaattisen mallin avulla pystyttiin analyyttisesti arvioimaan kunkin vaihtoehdon hyvyyttä ja poimimaan siltakannasta eniten päätöksentekijän tavoitteita vastaavat kohteet. Tutkimus toteutettiin kolmessa osiossa, joista ensimmäisessä selvitettiin MCDA:n perusteet määrittämällä kirjallisuuskatsauksen avulla päätöksentekijän preferenssejä mallintava MAVT-prosessi. Kirjallisuuskatsauksen jälkeen seurasi työn empiirinen osio, mikä pyrki haastatteluiden avulla selvittämään kiinteistöportfoliohallinnan päätöksentekoa ohjaavat kriteerit ja niiden toteutumista mittaavat attribuutit. Työ keskittyi käsittelemään vain kiinteistökohtaisten sisäsyntyisten tekijöiden vaikutusta kiinteistöportfoliohallintaan. Lopuksi empiriasta saatujen tuloksien pohjalta kuvattiin MAVT prosessi kyseessä olevassa kontekstissa ja kehitettiin esimerkkimalli kiinteistöportfoliohallinnan päätöksenteon tueksi. Esitetty malli on suunnattu yksityisille kiinteistönomistajille, jotka omistavat liike- ja toimistokiinteistöjä vain sijoitusmielessä. Tutkimuksen tuloksena saatiin viisi kiinteistöportfoliohallinnan päätöksentekoa ohjaavaa kriteeriä: makrosijainti, mikrosijainti, sopimushinta, kiinteistön korjaustarpeet ja kiinteistön kehittymiskyky. Sijainti kriteerit pyrkivät huomioimaan sekä makroympäristön kehittymisen että kiinteistön saavutettavuuden. Sopimushinta ja kiinteistön korjaustarpeet puolestaan kuvaavat kiinteistön kassavirran negatiivisen ja positiivisen puolen tärkeimpiä tekijöitä. Kiinteistön kehittymiskyvyllä tarkoitetaan kuinka paljon kehitystoimenpiteillä nähdään saatavan taloudellista hyötyä. Edelle mainittujen kriteereiden attribuuteiksi ehdotettiin makrosijainnille alueellisen BKT:n suhdetta uusiin rakennushankkeisiin, mikrosijainnille keskimääräistä matka-aikaa ja kulkuvälinevaihtoehtoja aluekeskukseen, sopimushinnalle kohteen sopimushintojen neliöillä painotettua keskiarvoa, korjaustarpeille pitkän tähtäimen suunnitelmasta saatavaa korjaustarvearviota ja kiinteistön kehittymiskyvylle asiantuntijan toteuttamaa arviota kiinteistön kehityskelpoisuudesta. Tutkimus ei ottanut kantaa kriteereiden painotukseen tai attribuuttien mittaustulosten pisteyttämiseen, koska työ haluttiin pitää yleisellä tasolla ja edellä mainitut toimenpiteet olisivat vaatineet työn rajaamista koskemaan vain yhtä kiinteistösijoittajaa. Kokonaisuudessaan nähtiin, että yleisen mallin kehittäminen kiinteistöportfoliohallintaan on mahdotonta, johtuen mallissa käytettävien painotusten ja arvofunktioiden yksilöllisestä luonteesta. Tästä johtuen preferenssimallin laadinta olisikin parempi toteuttaa käyttäen vain yhtä kiinteistönomistajaa. Tässä työssä kuvattu prosessi antaa kuitenkin työn kohteena olleille kiinteistönomistajille valmiudet luoda kvantitatiivinen malli oman päätöksenteon tueksi. Prosessin tuloksena saatava malli ehdottaa perustuen kiinteistön sisäsyntyisiin tekijöihin, miten kiinteistöt tulisi lajitella eri salkkuihin. Malli on kuitenkin tarkoitettu vain päätöksentekijän avuksi, ei päätöksentekijäksi

Includes abstract.
Includes bibliographical references.
When facilitating decisions in which some performance evaluations are uncertain, a decision must be taken about how this uncertainty is to be modelled. This involves, in part, choosing an uncertainty format {a way of representing the possible outcomes that may occur. It seems reasonable to suggest {and is an aim of the thesis to show {that the choice of how uncertain quantities are represented will exert some influence over the decision-making process and the final decision taken. Many models exist for multi-criteria decision analysis (MCDA) under conditions of uncertainty; perhaps the most well-known are those based on multi-attribute utility theory [MAUT, e.g. 147], which uses probability distributions to represent uncertainty. The great strength of MAUT is its axiomatic foundation, but even in its simplest form its practical implementation is formidable, and although there are several practical applications of MAUT reported in the literature [e.g. 39, 270] the number is small relative to its theoretical standing. Practical applications often use simpler decision models to aid decision making under uncertainty, based on uncertainty formats that `simplify' the full probability distributions (e.g. using expected values, variances, quantiles, etc). The aim of this thesis is to identify decision models associated with these `simplified' uncertainty formats and to evaluate the potential usefulness of these models as decision aids for problems involving uncertainty. It is hoped that doing so provides some guidance to practitioners about the types of models that may be used for uncertain decision making. The performance of simplified models is evaluated using three distinct methodological approaches {computer simulation, `laboratory' choice experiments, and real-world applications of decision analysis {in the hope of providing an integrated assessment. Chapter 3 generates a number of hypothetical decision problems by simulation, and within each problem simulates the hypothetical application of MAUT and various simplified decision models. The findings allow one to assess how the simplification of MAUT models might impact results, but do not provide any general conclusions because they are based on hypothetical decision problems and cannot evaluate practical issues like ease-of-use or the ability to generate insight that are critical to good decision aid. Chapter 4 addresses some of these limitations by reporting an experimental study consisting of choice tasks presented to numerate but unfacilitated participants. Tasks involved subjects selecting one from a set of five alternatives with uncertain attribute evaluations, with the format used to represent uncertainty and the number of objectives for the choice varied as part of the experimental design. The study is limited by the focus on descriptive rather than real prescriptive decision making, but has implications for prescriptive decision making practice in that natural tendencies are identified which may need to be overcome in the course of a prescriptive analysis.

The Subsea blowout preventer (BOP) which is latched to a subsea wellhead is one of several barriers in the well to prevent kicks and blowouts and it is the most important and critical equipment, as it becomes the last line of protection against blowout. The BOP system used in Subsea drilling operations is considered a Safety – Critical System, with a high severity consequence following its failure. Following past offshore blowout incidents such as the most recent Macondo in the Gulf of Mexico, there have been investigations, research, and improvements sought for improved understanding of the BOP system and its operation. This informs the need for a systematic re-evaluation of the Subsea BOP system to understand its associated risk and reliability and identify critical areas/aspects/components. Different risk analysis techniques were surveyed and the Failure modes effect and criticality analysis (FMECA) selected to be used to drive the study in this thesis. This is due to it being a simple proven cost effective process that can add value to the understanding of the behaviours and properties of a system, component, software, function or other. The output of the FMECA can be used to inform or support other key engineering tasks such as redesigning, enhanced qualification and testing activity or maintenance for greater inherent reliability and reduced risk potential. This thesis underscores the application of the FMECA technique to critique associated risk of the Subsea BOP system. System Functional diagrams was developed with boundaries defined, a FMECA were carried out and an initial select list of critical component failure modes identified. The limitations surrounding the confidence of the FMECA failure modes ranking outcome based on Risk priority number (RPN) is presented and potential variations in risk interpretation are discussed. The main contribution in this thesis is an innovative framework utilising Multicriteria decision making (MCDA) analysis techniques with consideration of fuzzy interval data is applied to the Subsea BOP system critical failure modes from the FMECA analysis. It utilised nine criticality assessment criteria deduced from expert consultation to obtain a more reliable ranking of failure modes. The MCDA techniques applied includes the technique for order of Preference for similarity to the Ideal Solution (TOPSIS), Fuzzy TOPSIS, TOPSIS with interval data, and Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE). The outcome of the Multi-criteria analysis of the BOP system clearly shows failures of the Wellhead connector, LMRP hydraulic connector and Control system related failure as the Top 3 most critical failure with respect to a well control. The critical failure mode and components outcome from the analysis in this thesis is validated using failure data from industry database and a sensitivity analysis carried out. The importance of maintenance, testing and redundancy to the BOP system criticality was established by the sensitivity analysis. The potential for MCDA to be used for more specific analysis of criteria for a technology was demonstrated. Improper maintenance, inspection, testing (functional and pressure) are critical to the BOP system performance and sustenance of a high reliability level. Material selection and performance of components (seals, flanges, packers, bolts, mechanical body housings) relative to use environment and operational conditions is fundamental to avoiding failure mechanisms occurrence. Also worthy of notice is the contribution of personnel and organisations (by way of procedures to robustness and verification structure to ensure standard expected practices/rules are followed) to failures as seen in the root cause discussion. OEMs, operators and drilling contractors to periodically review operation scenarios relative to BOP system product design through the use of a Failure reporting analysis and corrective action system. This can improve design of monitoring systems, informs requirement for re-qualification of technology and/or next generation designs. Operations personnel are to correctly log in failures in these systems, and responsible Authority to ensure root cause analysis is done to uncover underlying issue initiating and driving failures.

The proposal and the axiomatization of new fuzzy integrals has a central role in modern Multiple Criteria Decision Analysis. In this thesis we propose some generalizations of well known fuzzy integrals (Choquet, Shilkret and Sugeno). We propose and characterize bipolar fuzzy integrals, which are generalization of the most famous fuzzy integrals to the case of bipolar scale, i.e. those symmetric scale where it is possible for each value to find the opposite. We also deal with the generalization of the concept of universal integral (recently proposed to generalize several fuzzy integrals) to the case of bipolar scales. We also provide the characterization of the bipolar universal integral with respect to a level dependent bi-capacity. Finally, we consider the problem to adapt classical definitions of fuzzy integrals to the case of imprecise interval evaluations. More precisely, standard fuzzy integrals used in MCDA request that the starting evaluations of a choice on various criteria must be expressed in terms of exact-evaluations. We present the robust Choquet, Shilkret and Sugeno integrals, computed with respect to an interval capacity. These are quite natural generalizations of the Choquet, Shilkret and Sugeno integrals, useful to aggregate interval-evaluations of choice alternatives into a single overall evaluation.

Test coverage criteria introduces metrics to measure the adequacy of a test suite as well as defined rules for performing software testing. This makes it possibly to formally define requirements for testing in various industries where software quality is essential, such as in aviation. This bachelor thesis aims to study the effectiveness of 11 different coverage criteria in two ways. Firstly how effective they are at finding faults and secondly their cost effectiveness. Test cases were created for each individual criteria for three different programs. The effectiveness of these test cases was then measured using mutation analysis. The results revealed that the scale of the experiment was too small to truly draw any conclusions regarding effectiveness. It was however shown that due to the “test noise” effect, the effectiveness of the test criteria can differ notably. It was also shown that test coverage criteria alone may not be sufficient in order to perform efficient testing.

There are several current challenges to the competitiveness of the Norwegian maritime sector. The short sea shipping industry is facing tougher requirements on the environmental performance of vessel technologies, mainly from the quality and type of fuels utilized. Other challenges are high production costs and increasing global competition. For Norwegian ship owners, an additional challenge is the increase in road cargo transportation. A technology shift in the maritime sector may be necessary to meet these challenges. In this thesis, we argue that in order to make this shift happen, better decision support tools (DST) must be implemented.In this thesis, a Multi-criteria Decision Analysis (MCDA) model has been made for the Norwegian maritime sector. The Analytic Hierarchy Process (AHP) has been applied to a case study at a Norwegian ship owner, based on a vessel investment at Egil Ulvan Rederi AS. In this study, marine diesel oil (MDO) and liquefied natural gas (LNG) have been identified as alternatives. To obtain the most preferred alternative, the ship owner’s preferences for the following criteria were identified; air emissions, cost, technical performance and risk. The results shows that LNG was the most preferred alternative. This thesis proposes a systematic approach combining MCDA and Systems Engineering (SE). The results indicate the importance of including environment as a parameter in maritime decision-making, and may be especially important in areas subject to strict regulations on ship exhausts. It also indicates that MCDA, and AHP, can be used to aid decision makers in structuring their priorities in a decision-making context.

L’aide multicritère à la décision (AMCD) vise à faciliter et améliorer la qualité du processus de prise de décision. Les méthodes d’AMCD permettent de traiter les problèmes de choix, rangement et classification. Ces méthodes impliquent généralement la construction d’un modèle. Déterminer les valeurs des paramètres de ces modèles n’est pas aisé. Les méthodes d’apprentissage indirectes permettent de simplifier cette tâche en apprenant les paramètres du modèle de décision à partir de jugements émis par un décideur tels que “l’alternative a est préférée à l’alternative b” ou “l’alternative a doit être classifiée dans la meilleure catégorie”. Les informations données par le décideur sont généralement parcimonieuses. Le modèle d’AMCD est appris au cours d’un processus interactif entre le décideur et l’analyste. L’analyste aide le décideur à formuler et revoir ses jugements si nécessaire. Le processus s’arrête une fois qu’un modèle satisfaisant les préférences du décideur a été trouvé. Le “preference learning” (PL) est un sous domaine du “machine learning” qui s’intéresse à l’apprentissage des préférences. Les algorithmes de ce domaine sont capables de traiter de grands jeux de données et sont validés au moyen de jeux de données artificiels et réels. Les jeux de données traités en PL sont généralement collectés de différentes sources et sont entachés de bruit.Contrairement à l’AMCD, il existe peu ou pas d’interaction avec l’utilisateur en PL. Le jeu de données fourni en entrée à l’algorithme est considéré comme un échantillon éventuellement bruité d’une “réalité” ou “vérité de terrain”. Les algorithmes utilisés dans ce domaine ont des propriétés statistiques fortes leur permettant de s’affranchir du bruit dans ces jeux de données. Dans cette thèse, nous développons des algorithmes d’apprentissage permettant d’apprendre lesparamètres de modèles d’AMCD. Plus précisément, nous développons une métaheuristique afin d’apprendre les paramètres d’un modèle appelé MR-Sort (“majority rule sorting”). Cette métaheuristique est testée sur des jeux de donnéesartificiels et réels utilisés dans le domaine du PL. Nous utilisons cet algorithme afin de traiter un problème concret dans le domaine médical. Ensuite nous modifions la métaheuristique afin d’apprendre les paramètres d’un modèle plus expressif appelé NCS (“non-compensatory sorting”). Finalement, nous développons un nouveau type de règle de veto pour les modèles MR-Sort et NCS qui permet de prendre les coalitions de critères en compte. La dernière partie de la thèse introduit les méthodes d’optimisation semi-définie positive (SDP) dans le contexte de l’aide multicritère à la décision. Précisément, nous utilisons l’optimisation SDP afin d’apprendre les paramètres d’un modèle de fonction de valeur additive
Multiple-criteria decision analysis (MCDA) aims at providing support in order to make a decision. MCDA methods allow to handle choice, ranking and sorting problems. These methods usually involve the elicitation of models. Eliciting the parameters of these models is not trivial. Indirect elicitation methods simplify this task by learning the parameters of the decision model from preference statements issued by the decision maker (DM) such as “alternative a is preferred to alternative b” or “alternative a should be classified in the best category”. The information provided by the decision maker are usually parsimonious. The MCDA model is learned through an interactive process between the DM and the decision analyst. The analyst helps the DM to modify and revise his/her statements if needed. The process ends once a model satisfying the preferences of the DM is found. Preference learning (PL) is a subfield of machine learning which focuses on the elicitation of preferences. Algorithms in this subfield are able to deal with large data sets and are validated withartificial and real data sets. Data sets used in PL are usually collected from different sources and aresubject to noise. Unlike in MCDA, there is little or no interaction with the user in PL. The input data set is considered as a noisy sample of a “ground truth”. Algorithms used in this field have strong statistical properties that allow them to filter noise in the data sets.In this thesis, we develop learning algorithms to infer the parameters of MCDA models. Precisely, we develop a metaheuristic designed for learning the parameters of a MCDA sorting model called majority rule sorting (MR-Sort) model. This metaheuristic is assessed with artificial and real data sets issued from the PL field. We use the algorithm to deal with a real application in the medical domain. Then we modify the metaheuristic to learn the parameters of a more expressive model called the non-compensatory sorting (NCS) model. After that, we develop a new type of veto rule for MR-Sort and NCS models which allows to take criteria coalitions into account. The last part of the thesis introduces semidefinite programming (SDP) in the context of multiple-criteria decision analysis. We use SDP to learn the parameters of an additive value function model

The successful energy design of buildings requires that special attention be paid to the conceptual stage. However, it is a difficult task to find the most promising design alternatives satisfying several conflicting criteria. This thesis presents a simple multi-criteria decisions analysis method that could assist designers in green building design. Variables in the model include those alternatives that are common options when a residential building is to be constructed. The individual components that are considered are the building envelope, heating, ventilation and air conditioning (HVAC) system, service water heating, power and lighting. The key actors, objectives and methodology of multi-criteria decisions analysis are presented and finally a case study for a residential building in Athens is performed. The criteria by which to evaluate each building component of the newly built construction were identified by the decision-makers. Subsequently, decision frameworks for the selection of roof, walls, windows, heating system, energy source for heating system, power source, lighting and service water heating system were built. The method is followed step-by-step to conclude on the optimal building components based on their score. Due to the equal scoring of the windows and an inapplicable combination of electric underfloor heating with air-to-water heat pump, the method is characterized by low accuracy. The fact that the building components have been treated individually sets the method as a basic one and indicates that a more complex one should be preferred when more trustworthy results are needed.

In several types of embedded systems the applications are deployed both as software and as hardware components. For such systems, the partitioning decision is highly important since the implementation in software or hardware heavily influences the system properties. In the industry, it is rather common practice to take deployment decisions in an early stage of the design phase and based on a limited number of aspects. Often such decisions are taken based on hardware and software designers‟ expertise and do not account the requirements of the entire system and the project and business development constraints. This approach leads to several disadvantages such as redesign, interruption, etc. In this scenario, we see the need of approaching the partitioning process from a multiple decision perspective. As a consequence, we start by presenting an analysis of the most important and popular Multiple Criteria Decision Analysis (MCDA) methods and tools. We also identify the key requirements on the partitioning process. Subsequently, we evaluate all of the MCDA methods and tools with respect to the key partitioning requirements. By using the key partitioning requirements the methods and tools that the best suits the partitioning are selected. Finally, we propose two MCDA-based partitioning processes and validate their feasibility thorough an industrial case study.

PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
Tubos de aço de grande diâmetro, baixa espessura e alta resistência mecânica, possuem tendência à formação de rugas no lado compressivo do curvamento (intrados) ao serem curvados a frio. A presente dissertação descreve os principais códigos de projeto nacionais e internacionais, quanto à presença de rugas provenientes desse tipo de curvamento em dutos, e propõe um ângulo para o qual há a formação do enrugamento. Os códigos internacionais mostram-se conservadores quanto à presença de rugas nos tubos curvados, uma vez que o enrugamento é uma mudança geométrica que, a princípio, gera concentração de tensões e susceptibilidade à ocorrência de falhas por fadiga. Esta dissertação faz uso do método de elementos finitos para modelar a formação do enrugamento e determinar fatores de concentração de tensões, nestas regiões, para carregamentos de pressão interna. Os fatores encontrados são comparados com resultados encontrados na literatura e utilizados no cálculo contra a fadiga por meio de diferentes métodos: Markl, inclinações universais de Manson e ASME seção VIII divisão 2. Neste estudo foram utilizados tubos de aço estrutural API X70 com razão diâmetro espessura (D/t) variando de 20 a 100, modelados por meio do software Abaqus(r). Foram obtidas curvas com ângulo de 4°/diâmetro e enrugamentos severos, com razão entre a altura da ruga e o diâmetro do tubo (d/D) da ordem de 6,5% e fator de concentração de tensão chegando a 1,89. Os modelos de tubo enrugado não apresentaram falha na resistência mecânica à pressão interna aplicada, quando esta é suficiente para obtenção de tensão circunferencial nominal equivalente a 100% do limite de escoamento do material. Os resultados de vida em fadiga para os diferentes métodos aplicados variam de acordo com o método utilizado, mas todos apresentam redução na vida do tubo com presença de enrugamento severo. O estudo propõe que se utilize para o cálculo da vida em fadiga um procedimento conservador que associa o fator de concentração de tensão determinado por Rosenfeld com o método de cálculo contra a fadiga recomendado pelo código ASME VIII. O estudo sugere ainda, que sejam realizadas novas análises de forma a considerar o efeito Bauschinger e a instabilidade à flexão do modelo não avaliados no presente trabalho.
Large diameter, thin walled, high mechanical resistance steel pipe has a tendency to wrinkle on the compressive side (the intrados) of the bend when it is cold bent. This dissertation describes the principal national and international design codes that apply to wrinkling resulting from pipe cold bending, and it proposes an angle at which such wrinkling occurs. The international codes prove to be conservative regarding wrinkling in bent pipe, since a wrinkle is a geometric change, which at first causes a stress concentration and susceptibility to fatigue failure. The dissertation uses the finite element method to model the formation of wrinkling and to determine stress concentration factors in these areas for internal pressure loading. The resulting factors are compared with the results found in the literature and are utilized in calculating fatigue life by means of the following methods: Mark1, Mansons universal inclinations and ASME Section VIII Division 2. In this study API X70 structural pipe with a diameter thickness (D/t) ratio varying from 20 to 100 was utilized, and modeled using Abaqus(r) software. Bends with an angle of 4°/diameter and severe wrinkling resulted, with a ratio between the peak of the wrinkle and the diameter of the pipe (d/D) of about 6.5% and a stress concentration factor nearing 1.89. The wrinkled pipe models did not reveal any lack of mechanical resistance to the applied internal pressure when it is sufficient for obtaining a nominal circumferential stress equivalent to 100% of the yielding limit of the material. The fatigue life results for the different methods varied according to the method that was utilized, but all displayed a reduction in pipe life if there was severe wrinkling. The study proposes a conservative procedure to be utilized for calculating fatigue life. This procedure associates the stress concentration factor determined by Rosenfeld with the method for calculating fatigue recommended by the ASME VIII code. Furthermore, the study suggests that new analyses may be performed in order to consider the Bauschinger effect and the model bend instability, which the study did not evaluated.

Due to the rapid growth of the wind energy market over the last decade, the future of the industry will consequently see the dismantling of many wind turbines, both due to wind turbines reaching the end of their service life and to make way for surpassing technology, leaving behind a large amount of material that must be dealt with. Furthermore, due to the advancing technology of wind turbines, there has been a decline in the number of medium sized wind turbines being manufactured. This study aims to address the problem of future waste mitigation, whilst attempting to capture the medium scale market. As such, the study has looked at the idea of transitioning towards a circular economy, in which wind turbines are not considered as waste at the end of their service life, but rather an opportunity to recapture value through remanufacturing. This was approached by identifying the driver and barriers of remanufactured products, utilising knowledge from other industries with developed remanufacturing sectors. A Multi-Criteria Decision Analysis (MCDA) has been performed using the PROMETHEE II method with the objective of drawing a comparison of three scenarios, enveloped by a theoretical wind turbine selection project. The scenarios were created by the author and considered the implementation of a new wind turbine and remanufactured wind turbines. Upon examining the results of the multi criteria decision analysis, it was seen that the benefits of implementing remanufactured turbines were preferred by the majority of the stakeholders involved.

Sustainability is a fairly new emerging business concept for manufacturing industry and this thesis will focus on smartphone manufacturing industry. In 2015 there were 1.86 billion smartphone users and it is estimated to increase to 2.87 billion in 2020. Currently the average lifetime of a smartphone is 21 months and According to Consumer Technology Association the technical life expectancy of a smartphone is 4.7 years. The European Commission approximated that from 17–20 kg of electronic waste is produced per person per year and that smartphones are contributors for increase of electronic waste. Also the smartphone manufacturing process has an impact on the people who are involved with manufacturing and resource extraction process.  Related social problems include conflict minerals, issues in manufacturing campuses, health problems and excessive worktimes. There has been suspicion that large manufacturing companies use labour market in areas that have a high risk of poverty or lack of national authority that can protect labour rights. To investigate these emerging issues that has an impact on smartphone manufacturing sustainability, a sustainability ranking criteria for individual smartphones devices and their manufactures was developed. Furthermore, the aim of the research is to develop a ranking system using life cycle perspective and to evaluate sustainability of a smartphones upcycling, recycling, and social aspects. This aim will be accomplished by the following objectives: Develop evaluation system for smartphones using Multi-Criteria Analysis (MCA) to evaluate sustainability; Comparing sustainability of smartphones Fairphone 2, iPhone 7, Samsung Galaxy S7 and LG G5, using developed Multi-Criteria Analysis (MCA); Conducting general sustainability- focused survey about consumer demand for sustainable and ethical electronics. The method used in this research to assess smartphone sustainability was Multi-Criteria Analysis(MCA), based on eco-design trends and three pillars of sustainability, – economic, environmental and social. Eco-design will be supported using EcoDesing Roadmap by Conrad Luttropp and Göran Brohammer. In parallel with MCA method a survey was developed to briefly assess consumer’s behaviour in terms of choosing sustainable electronics. For better understanding about the consumer value on purchase decision, a survey was made considering the technical and sustainable aspects. The results of this survey will be used as indicator. Furthermore, results from this research (Table 1 MCA evaluation results) revealed that majority of chosen smartphones where lacking sustainable products aspects. This MCA ranking system also confirm that for sustainable designed smartphone it is equally important to have well established environmental management system for overall manufacturing process and afterlife of smartphone. Continuing, after conducting deeper analysis with combined results from MCA, survey revealed that general public are willing to pay more for sustainable products, but consumers lack information about the overall manufacturers` sustainability, as well Indicating that communication between manufacturers and consumers are very weak or even one way. The conclusion of the study about Smartphone sustainability assessment using multi-criteria analysis and the consumer survey has provided better understanding about the lack of transparency and complex logistics manufacturing process of smartphone. The lack of qualitative data and transparency from the manufactures side is a major issue that creates lot of uncertainties about smartphone manufacturing process and social issues for workforce that is involved in this manufacturing process.

This thesis presents a modification of existing entropy-based splitting criteria for classification and regression trees. Trees are typically grown using splitting criteria that choose optimal splits without taking future splits into account. This thesis examines localised splitting criteria that are based on local averaging in regression trees or local proportions in classification trees. The use of a localised criterion is motivated by the fact that future splits result in leaves that contain local observations, and hence local deviances provide a better approximation of the deviance of the fully grown tree. While most recent research has focussed on tree-averaging techniques that are aimed at taking a moderately successful splitting criterion and improving its predictive power, this thesis concentrates on improving the splitting criterion. Use of a localised splitting criterion captures local structures and enables later splits to capitalise on the placement of earlier splits when growing a tree. Using the localised splitting criterion results in much simpler trees for pure interaction data (data with no main effects) and can produce trees with fewer errors and lower residual mean deviances than those produced using a global splitting criterion when applied to real data sets with strong interaction effects. The superiority of the localised splitting criterion can persist when multiple trees are grown and averaged using simple methods. Although a single tree grown using the localised splitting criterion can outperform tree averaging using the global criterion, generally improvements in predictive performance are achieved by utilising the localised splitting criterion's property of detecting local discontinuities and averaging over sets of trees grown by placing splits where the deviance is locally minimal. Predictive performance improves further when the degree of localisation of the splitting criterion is randomly selected and weighted randomisation is used with locally minimal deviances to produce sets of trees to average over. Although state of the art methods quickly average very large numbers of trees, thus making the performance of the splitting criterion less critical, predictive performance when the localised criterion is used in bagging indicates that different splitting methods warrant investigation. The localised splitting criterion is most useful for growing one tree or a small number of trees to examine structure in the data. Structurally different trees can be obtained by simply splitting the data where the localised splitting criterion is locally optimal.

Context. The approach of developing software systems with the use of third partycomponents i.e. COTS or OSS has increased globally. In this study API product refers toeither a software component or a software service or both packaged together, that can beaccessed through an API. Developers are faced with plethora of alternative choices to selectan API product. With this increase in components adoption, API product providers are facedwith challenge of designing their product to be more attractive than others. This needs theproviders to be educated about the developer behavior when they choose an API product.Understanding the selection practices of developers can help providers to improve thepackaging of API products, making them more suitable for selection. Objectives. The objectives of this study is to investigate the criteria that developers usewhen reasoning about acceptability of a software component. Methods. A background study is performed to identify the evaluation criteria proposed inthe literature. An empirical study using Qualitative content analysis is performed. In the study the 480 reviews of different API products are analyzed to understand the criteria frompractitioners’ perspective. Results. 9 relevant criteria that developer use to reason about accepting or rejecting an APIProduct are identified. 30 sub criteria related to the 9 criteria are described in the study. Conclusions. This study concludes that the identified 9 criteria play an important role indeveloper assessment of the API product. It is also found that the criteria have significantimpact on the ratings of API product. These criteria could guide API product providers tomake better choices when developing the product.

A Monte Carlo study was performed to investigate the ability of MSCAL to recover by Euclidean metric multi-dimensional scaling (MDS) the true structure for dissimilarity data with different underlying error distributions. Error models for three typical error distributions: normal, lognormal, and squared normal are implemented in MSCAL through data transformations incorporated into the criterion function. Recovery of the true configuration and true distances for (i) single replication data with low error levels and (ii) matrix conditional data with high error levels was studied as a function of the type of error distribution, fitting criterion, and dimensionality. Results indicated that if the data conform to the error distribution hypotheses, then the corresponding fitting criteria provide improved recovery, but only for data with low error levels when the true dimensionality is known.

In the energy field, the decisions need to take into consideration several factors such as the needs of the population, the environment, suitability, capital cost, sustainability, political goals and the actors involved, with their interests and preferences. The lack of homogeneity in all the factors that must be consider makes it necessary to design a process that guides the analysis process of any type of decision-maker. Decision analysis methods have been developed to aid decision-makers identify a problem, determine the criteria to be consider and their importance, recognize the stakeholders that need to be involved and pose the different alternatives to resolve or to best address the problem. These techniques range from simple to more mathematically oriented ones, from single criterion evaluation to multiple criteria, and from purely qualitative or quantitative to mixed techniques. Within the field of decision analysis, multi-criteria techniques are better suited to aid in decision situations in the energy field as these decisions require several considerations beside economic ones. This thesis uses theories and notions of decision analysis to construct a framework to be used in any energy related decision situations by non-experts. The framework tackles common challenges faced by multi-criteria decision analysis methods, including the identification of stakeholders and decision-makers, the aggregation of various decision-makers, preferences and heterogeneous inputs, and the selection of suitable criteria, alternatives and methods.

GDP and GDP per capita are widely used to gauge for living standards across countries. However, they have originally not been constructed for this purpose and are therefore subject to significant limitations. This paper aims at developing a better and non-monetary development index with which cross-country living standards can be assessed. This index, the BDI, can then be utilized for policy making. When constructing the BDI, this study utilizes time series analysis and panel unit root tests. A major finding of this study is that the BDI does indeed produce statistically significantly different results/ rankings for a special set of countries, compared to GDP and GDP per capita.

Geographic Information System (GIS) technologies and remote sensing (RS) technologies have developed rapidly in recent years, and they have been widely used indaily life of ordinary people. The combination of these two remarkable technologies isuseful for location decision making and has been applied in different kinds of study cases.Guangyuan is one of the fastest developing cities in the southwest of China. Especiallyafter the Wenchuan earthquake in 2008, the development in economic and urbanreconstruction increased rapidly. Many infrastructure constructions and the reformprojects are in progress. At the same time, China's urban sewage treatment facilities areseriously inadequate. Only a small percentage of sewage has been treated by sewagetreatment plants in China. So the purpose of this study is to select an optimal site for asewage treatment plant in Guangyuan in a scientific way.In this particular study, based on GIS software and GIS-based multi-criteria analysis(MCA), a decision making model has been built for optimal site selection for a sewagetreatment plant. Two types of data were used in this study. Digital elevation model andsatellite image, several factor maps and constraint maps were created for the final analysis.The analytic hierarchy process was used to apply the weights for each factor along withformula method, in order to get the best result and find the optimal site. Finally, a MCAmodel has been made to be an example for future similar studies.In the end, an optimal site has been selected. Although aims are achieved in this study,there are still some limitations in different perspectives of the study. In the future, moreprecise data can be used in MCA studies, data limitations could be reduced with thedevelopment of RS techniques. In the future, more similar studies will be finished, whichmeans more scientific papers can provide reliable references of determining the criteriaand weights.

Community benefit schemes in the context of wind power are increasingly provisioned by developers as a means of generating local socio-economic and environmental value, fostering social relations and strengthening acceptance. Determining an appropriate and effective benefit scheme can prove challenging, given the variation of exposed stakeholders, diversity in schemes and the lack of decision making guidance. A multi-criteria decision aid framework for identifying the most appropriate scheme(s) for a hypothetical wind power project is developed. The framework is based on AHP and PROMETHEE II decision support tool, where six (6) alternative schemes are assessed using the preferences of five (5) stakeholders and their relevant criteria. The framework was applied to a fictitious development on the island of Gotland. Results from the applied example indicate that the most locally suited outcome was the ownership based models. It is anticipated that the methodological framework can help identify the scheme(s) that respond to the needs and preferences of the locality. Moreover, a decision making platform of this nature can provide practical support to developers, communities and local authorities, and contribute to a more effective and efficient development and negotiation process surrounding community benefit schemes.

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This thesis provides data analysis on the selection process of the FY 2009–2011 Army Active Guard/Reserve (AGR) colonel selection boards. In this analytic study, logistic regression is used to study what variables influence colonel selection. The focus of this study is to aid Army senior leaders in the mentoring and development of future senior leaders by identifying criteria key to the selection of Army AGR colonels. A data set is compiled from 1144 individual promotion packets submitted across three selection boards. The 1144 packets correspond to 684 individuals. The findings suggest one’s zone of consideration, age, longest deployment, senior service college completion, possession of a master’s degree, battalion command, number of ratings as a lieutenant colonel, and the total percentage above center of mass ratings have a significant influence on selection.

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Nesta tese, reconsideramos os critÃrios que caracterizam as funÃÃes discursivas dos processos anafÃricos a partir da anÃlise de anÃncios publicitÃrios. Tivemos como objetivo identificar as funÃÃes discursivas presentes nos gÃneros notÃcia, anÃncio, artigo de opiniÃo e piada, tendo como ponto de partida o quadro de funÃÃes sugerido por Ciulla (2008). Tomamos como pressuposta uma perspectiva cognitivo-discursiva da referenciaÃÃo, pela qual tem sido ampliada a concepÃÃo de anÃforas. Uma abordagem discursiva para a anÃlise de processos referenciais deve considerar nÃo apenas a expressÃo referencial em si, mas o conjunto de elementos contextuais convocados para a negociaÃÃo sociocognitivo-discursiva dos referentes. Partindo desse pressuposto, julgamos necessÃrio realizar uma rediscussÃo dos critÃrios utilizados para a anÃlise das funÃÃes discursivas desempenhadas pelos processos anafÃricos. Tomamos como fonte teÃrica para o estudo das funÃÃes discursivas o trabalho de Ciulla (2008), que objetivou estabelecer critÃrios que permitissem uma visÃo ampliada dos processos referenciais que nÃo apenas revelasse funÃÃes, mas tambÃm levasse em conta a mutabilidade caracterÃstica do processo de construÃÃo referencial e, portanto, suportasse constantes acrÃscimos e ajustes, conforme a observaÃÃo das diversas situaÃÃes de uso. Especificamente, extraÃmos do trabalho de Ciulla (2008) o quadro de funÃÃes discursivas sugeridas pela autora, a fim de as testarmos em outros gÃneros, neste caso, a notÃcia, o anÃncio, o artigo de opiniÃo e a piada. Tal aplicaÃÃo exige uma reorganizaÃÃo do quadro de funÃÃes, levando em consideraÃÃo as caracterÃsticas contextuais em que esses gÃneros sÃo praticados.
In this thesis, we reconsider the criteria that characterize the discursive functions of anaphoric processes from the analysis of advertisements. The goal was to identify the discursive functions present in the genres news, add, opinion article and joke, taking as its starting point the framework of functions suggested by Ciulla (2008). We assumed a cognitive-discursive perspective of referral, through which has been expanded the conception of anaphoras. A discursive approach for the analysis of referential processes must consider not only the referred expression itself, but also the set of contextual elements arranged to the sociocognitive-discursive negotiation of the referents. Based on this assumption, we believe it is necessary to conduct a rediscussion of the criteria used for the analysis of the discursive functions performed by the anaphoric processes. The main framework for the study of the discursive function is the work of Ciulla (2008), which aims at establishing criteria that allow a boader view of referential processes that could not only reveal functions, but could also take into account the characteristic mutability of the process of referential construction and that could, therefore, stand constant additions and adjustments, according to the observation of the diverse situations of use. Specifically, we extracted from Ciulla's work (2008) the framework of discursive functions suggested by the author in order to test it in other genres: news, add, opinion article and joke. This application demands a reorganization of the mentioned framework, considering the contextual characteristics in which these genres are practiced.

In the present study a methodology and a spreadsheet model were developed with the aim of integrating techno-economic and environmental objectives simultaneously during decision making. The model was developed specifically for the copper industry, mainly due to the wide array of different processing technologies and operational synergies that exist in this industry.

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FACEPE
Ambientes dinâmicos e distribuídos são sistemas descentralizados que fornecem aos usuários recursos de consultas sobre um conjunto de fontes de dados heterogêneas, distribuídas e autônomas (peers). Sistemas de Integração de Dados, Peer Data Management System (PDMS) e Dataspaces são exemplos de tais sistemas. Eles são constituídos por peers que pertencem a um domínio específico e estão ligados entre si por meio de correspondências semânticas. No entanto, um desafio inerente em ambientes dinâmicos e distribuídos é o processo de reformulação de consulta entre um par de peers. Quando um usuário coloca uma consulta em um peer, a fim de adquirir mais informações, a consulta deve ser reformulada de acordo com o esquema dos peers vizinhos. Neste processo podem surgir alguns problemas como a perda semântica e a degradação da consulta. A perda semântica e degradação da consulta são problemas relacionados à perda de conceitos semânticos durante a reformulação. Por outro lado, em um ambiente semanticamente rico, ao invés de uma perda semântica, a consulta pode ter um enriquecimento semântico por meio da agregação de conceitos semanticamente relacionados durante a reformulação. Neste sentido, a consulta do usuário pode ser enriquecida e resultados semânticos mais ricos podem ser recuperados. Critérios de qualidade da informação têm sido usados em alguns trabalhos para avaliar o nível de qualidade dos elementos de um ambiente dinâmico e distribuído como, por exemplo, peers, dados e a resposta da consulta. Estes critérios são medidas dinâmicas proporcionadas pelo sistema e servem como uma pontuação que pode ser constantemente avaliada para obter o nível real de qualidade. Neste trabalho, apresentamos quatro critérios de qualidade da informação que medem a perda e o ganho de conceitos semânticos durante a reformulação da consulta entre os pares de peers. Nós apresentamos um exemplo da nossa abordagem e os algoritmos de avaliação de critérios. Também damos as nossas definições para os problemas de perda semântica e degradação da consulta. Por fim, apresentamos a experimentação que fizemos com o PDMS SPEED e os resultados obtidos.
Dynamic distributed environments are decentralized systems that provide users with querying capabilities over a set of heterogeneous, distributed and autonomous data sources (peers). Data Integration Systems, Peer Data Management Systems (PDMS) and Dataspaces are examples of such systems. They are composed by peers that belong to a specific domain and are linked to each other by correspondences (semantic connections). Nonetheless, a challenge inherent to dynamic distributed environments is the query reformulation process between a pair of peers. When a user poses a query at a peer, in order to acquire more information, the query should be reformulated in accordance with the neighbor peers schema. In this process some problems as semantic loss and query degradation can arise. The semantic loss and query degradation are problems related to the loss of semantic concepts during query reformulation. In the other hand, in such a semantic environment instead of a semantic loss the query can have a semantic enrichment by aggregating semantic related concepts during reformulation. In this sense, the user’s query can be enriched and semantically richer results can be delivered. Information Quality criteria has been used in some works to evaluate the level of quality of the distributed dynamic environment’s elements such as, peers, data and query answer. These criteria are dynamic measures provided by the system and serve as scores that can be constantly evaluated to get the actual level of quality. In this work we present four Information Quality criteria that measure the loss and enrichment of semantic concepts during query reformulation among peers. We present an example of our analysis and the algorithms that implement the evaluation of the presented criteria. We also give our definitions to the semantic loss and query degradation problems. Finally, we present the experimentation we have done with the SPEED PDMS and the obtained results.

The effects of uncertainties on the simulation component and the decision component of the USDA-ARS Water Quality Decision Support System (WQDSS) are studied. For the simulation component, a generalized second order covariance propagation equation for multiple response models is developed to account for model nonlinearities and complexities. The equation permits the calculation of the covariance matrix of several model responses as a function of their first and second order sensitivities to variations in model parameters and the cross moments of the parameter vector. The equation is complemented by developing an applied approach that aims to identify model nonlinearities, isolate response discontinuities, and simplify the computational efforts associated with analytical uncertainty analysis. As for the decision component, a generalized closed form solution of the WQDSS's decision model is derived to allow consideration of a vector of quantitative scale factors. The factors indicate the relative importance of the studied decision criteria. A procedure that is based on computing these scale factors and assigning importance orders proportional to the effects of the uncertainties on the scoring function transformation of the individual criteria is also developed and tested. To test the methodology, the covariance matrix of twelve model responses is estimated based on uncertainties in sixteen soil related parameters using (a) direct simulation, (b) first order propagation and (c) second order propagation. Comparing the first and second order propagated matrices to those resulting from actual simulations of four agricultural management systems attests to the superiority of the second order equation. The effects of uncertainties on the decision recommendations are identified through experimental combinations of three different importance orders and four possible alternative ranking schemes. Two of the importance orders and their associated scale factors are based on the uncertainties in evaluating decision criteria. The ranking methods are based on varying the point at which averaging of the data takes place with respect to the decision process. Results indicate that the decision model is less sensitive to changes in the point of averaging than it is with respect to variations in the importance orders and the scale factors.