The company’s pricing is often highly impacted by the estimation of competitors’ project costs, which also is the main scope in this degree project. The purpose is to develop a pricing model dealing with uncertainties, since this is a main issue in the current pricing process. A pre-study has been performed, followed by a model implementation. An analysis of the model was then made, before conclusions were drawn. Project cost estimation foremost, but also probability distribution functions and pricing as a general concept, were investigated in the mainly literary pre-study. Two suitable methods for project cost estimation were identified; Monte Carlo simulation and Hierarchy Probability Cost Analysis. These lead to a theoretical project cost estimation model. A model was implemented in Matlab. It treats project cost estimation, but no other pricing aspects. The model was developed based on the theoretical one to the extent possible. Project costs were broken down in sub costs which were included in a Monte Carlo simulation. Competitors’ project costs were estimated using this technique. To analyse the model’s accuracy was difficult. It differs from the theoretical one in terms of how probability distribution functions and correlations are estimated. These problems depend on projects with shifting characteristics and limited data and time. A solid framework has been created though. Improvement possibilities exist, e.g. more accurate estimates and a model handling other pricing aspects. The major threat is that nobody maintains the model. Anyway, estimates are not more than just estimates. The model should therefore be viewed as a helpful tool, not an answer. / Företagets prissättning påverkas ofta till stor del av estimeringen av konkurrenters projektkostnader, vilket också är huvudområdet i detta examensarbete. Syftet är att utveckla en prissättningsmodell som hanterar osäkerheter, då detta är ett stort problem i rådande prissättningsprocess. En förstudie har utförts, följt av en modellimplementation. En analys av modellen gjordes sedan, innan slutsatser drogs. Projektkostnadsestimering främst, men även sannolikhetsfunktioner och prissättning som ett allmänt koncept, undersöktes i den i huvudsak litterära förstudien. Två lämpliga metoder för projektkostnadsestimering identifierades; Monte Carlo-simulering och Hierarchy Probability Cost Analysis. Dessa ledde till en teoretisk modell för projektkostnadsestimering. En modell implementerades i Matlab. Den behandlar projektkostnadsestimering, men inga andra prissättningsaspekter. Modellen utvecklades baserat på den teoretiska i möjlig utsträckning. Projektkostnader bröts ner i delkostnader som estimerades för konkurrenterna. Dessa ingick i en Monte Carlo-simulering. Konkurrenters projektkostnader estimerades med hjälp av denna teknik. Att analysera modellens noggrannhet var svårt. Den skiljer sig från den teoretiska beträffande hur sannolikhetsfunktioner och korrelationer estimeras. Dessa problem beror på projekt med skiftande karaktärsdrag samt begränsad data och tid. Ett solitt ramverk har dock skapats. Förbättringsmöjligheter finns, t.ex. noggrannare estimat och en modell som behandlar andra prissättningsaspekter. Det huvudsakliga hotet är att ingen underhåller modellen. Hur som helst är estimat inte mer än estimat. Modellen ska därför ses som ett hjälpverktyg, inte ett facit.

Exploration and Production (E&P) project costs within the oil industry are continuously increasing reflecting a reality of more harsh environments, remote locations with minimal existing infrastructure and cost increases for materials and skilled resources. The significant capital expenditures translate to a number of projects either for new or revamped production facilities. Successful project completion requires a series of correct decisions throughout the project life-cycle namely design, construction, operations, maintenance and decommissioning. Using a Reliability, Availability and Maintainability (RAM) model as part of the project decision process is an E&P industry best practice that recently gained acceptance in Hess Corporation. This paper presents the RAM methodology and the gains from its application in a capital project. / text

As transportation funding becomes increasingly constrained, it is imperative that decision makers invest precious resources wisely and effectively. Transportation planners need effective tools for anticipating outcomes (or ranges of outcomes) in order to select preferred project alternatives and evaluate funding options for competing projects. To this end, this thesis work describes multiple applications of a new Project Evaluation Toolkit (PET) for highway project assessment. The PET itself was developed over a two-year period by the thesis author, in conjunction with Dr. Kara Kockelman, Dr. Chi Xie, and some support by others, as described in Kockelman et al. (2010) and the PET Users Guidebook (Fagnant et al. 2011). Using just link-level traffic counts (and other parameter values, if users wish to change defaults), PET quickly estimates how transportation network changes impact traveler welfare (consisting of travel times and operating costs), travel time reliability, crashes, and emissions. Summary measures (such as net present values and benefit-cost ratios) are developed over multi-year/long-term horizons to quantify the relative merit of project scenarios. This thesis emphasizes three key topics: a background and description of PET, case study evaluations using PET, and sensitivity analysis (under uncertain inputs) using PET. The first section includes a discussion of PET’s purpose, operation and theoretical behavior, much of which is taken from Fagnant et al. (2010). The second section offers case studies on capacity expansion, road pricing, demand management, shoulder lane use, speed harmonization, incident management and work zone timing along key links in the Austin, Texas network. The final section conducts extensive sensitivity testing of results for two competing upgrade scenarios (one tolled, the other not); the work examines how input variations impact PET outputs over hundreds of model applications. Taken together, these investigations highlight PET’s capabilities while identifying potential shortcomings. Such findings allow transportation planners to better appreciate the impacts that various projects can have on the traveling public, how project evaluation may best be tackled, and how they may use PET to anticipate impacts of projects they may be considering, before embarking on more detailed analyses and finalizing investment decisions. / text

Io, the innermost Galilean satellite of Jupiter, exhibits a wide variety of complex phenomena such as interaction with Jupiter’s magnetosphere, volcanic activity, and a rarefied multi-species sublimating and condensing atmosphere with an ionosphere. Io’s orbital resonance with Jupiter and the other Galilean satellites produces intense tidal heating. This makes Io the most volcanically active body in the solar system with plumes that rise hundreds of kilometers above the surface. In the present work, the interaction of Io’s atmosphere with the Jovian plasma torus is simulated via the Direct Simulation Monte Carlo (DSMC) method and the aurora produced via electron-neutral excitation collisions is examined using electron transport Monte Carlo simulation. The electron-transport Monte Carlo simulation models the electron collisions with the neutral atmosphere and their transport along field lines as they sweep past Io, using a pre-computed steady atmosphere and magnetic field. As input to the Monte Carlo simulation, the neutral atmosphere was first modeled using prior 2D sunlit continuum simulations of Io’s atmosphere produced by others. In order to justify the use of a sunlit atmosphere for eclipse, 1D two-species (SO2 and a non-condensable) DSMC simulations of Io’s atmospheric dynamics during and immediately after eclipse were performed. It was found that the inclusion of a non-condensable species (SO or O2) leads to the formation of a diffusion layer which prevents rapid collapse. The degree to which the diffusion layer slowed the atmospheric collapse was found to be extremely sensitive to both the initial non-condensable mole fraction and the reaction (or sticking) probability on the surface of the “non-condensable”. Furthermore, upon egress, vertical stratification of the atmosphere occurred with the non-condensable species being lifted to higher altitudes by the rapid sublimation of SO2 as the surface warms. Simulated aurorae (specifically the [OI] 6300 Å and the S2, SO, and SO2 molecular band emission in the middle ultraviolet) show good agreement with observations of Io in eclipse and an attempt was made to use the simulations to constrain the upstream torus electron temperature and Io’s atmospheric composition, structure, and volcanic activity. It is found that the position of the bright [OI] 6300 Å wake spot relative to Io’s equator depends on the position of Io relative to the plasma torus’ equator and the asymmetric electron number flux that results. Using HST/STIS UV-Vis spectra, the upstream electron temperature is weakly constrained to be between 3 eV and 8 eV depending on the flux of a low energy (35 eV), non-thermal component of the plasma (more non-thermal flux requires lower thermal plasma temperatures to fit the spectrum). Furthermore, an upper limit of 5% of the thermal torus density (or 180 cm−3 based on the Galileo J0 plasma density at Io) is obtained for the low energy non-thermal component of the plasma. These limits are consistent with Galileo observations of the upstream torus temperature and estimates for the the non-thermal component. Finally, plume activity and S2 content during eclipse observations with HST/STIS were constrained by examining the emission intensity along the spatial axis of the aperture. During the August 1999 UV-Vis observations, the auroral simulations indicate that the large volcanoes Pele and Surt were inactive whereas Tvashtar was active and that Dazhbog and possibly Loki were also actively venting gas. The S2 content inferred for the large Pele-type plumes was between 5% (Tvashtar) and 30% (Loki, if active), consistent with prior observations (Spencer et al., 2000; Jessup et al., 2007). A 3D DSMC simulation of Io’s sublimation and sputtered atmosphere including photo- and plasma-chemistry was developed. In future work these atmospheric simulations will replace the continuum target atmosphere in the auroral model and thus enable a better match to the observed high altitude auroral emission. In the present work, the plasma interaction is modeled by a flux of ions and electrons which flow around and through Io’s atmosphere along pre-computed fields and interact with the neutral gas. A 3D DSMC simulation of Io’s atmosphere assuming a simple thermal model for the surface just prior to ingress into eclipse and uniform frost coverage has been performed in order to understand how Io’s general atmospheric dynamics are affected by the new plasma model with chemistry and sputtering. Sputtering was found to supply most of the nightside atmosphere (producing an SO2 column of ~5×1013 cm−2); however, the dense dayside sublimation atmosphere was found to block sputtering of the surface. The influence of the dynamic plasma pressure on the day-to-night circumplanetary flow was found to be quite substantial causing the day-to-night wind across the dawn terminator to flow slightly towards the equator. This results in a region of high density near the equator that extends far (~2000 km for the condensable species) onto the nightside across the dawn terminator. Thus, even without thermal lag due to rotation or variable surface frost, highly asymmetric equatorial column densities relative to the subsolar point are obtained. The non-condensable O2, which is a trace species on the dayside, is the dominant species on the nightside despite increased SO2 sputtering because the loss rate of O2 is slow. Finally, a very intriguing O2 flow feature was observed near the dusk terminator where the flow from the leading hemisphere (pushed by the plasma) meets the flow from the dayside trailing hemisphere. Since the O2 does not condense on the surface, it slowly convects towards the poles and then back onto the nightside, eventually to be dissociated or stripped away by the plasma. / text

Η μεσόμορφη κατάσταση είναι μια ενδιάμεση κατάστασή της ύλης μεταξύ στερεής και υγρής φάσης και περιλαμβάνει δύο μεγάλες κατηγορίες, την υγροκρυσταλλική και την περιστροφική φάση, στις οποίες παρατηρούνται ιεραρχημένες δομές υπό συγκεκριμένες συνθήκες. Ανάλογη συμπεριφορά εμφανίζουν και τα ημιφθοριωμένα αλκάνια κατά το σχηματισμό κρυστάλλων σε στοιβάδες (λαμέλες) με μικρή ή μεγάλη τάξη στη μεσοφάση τους τα οποία έχουν μοριακό τύπο CmF2m+1CnH2n+1 και χρησιμοποιούνται κατά κόρον σε βιοϊατρικές εφαρμογές. Ένα από αυτά τα αλκάνια είναι το F(CF2)12(CH2)12H ή αλλιώς F12H12, ένα γραμμικό δισυσταδικό μόριο για το οποίο έχει παρατηρηθεί ότι μεταπίπτει από μία μεσοφάση με δομή διστρωματικής λαμέλας σε μεσοφάση μικρότερης τάξης και δομής μονομοριακής λαμέλας καθώς η θερμοκρασία αυξάνει. Στη παρούσα εργασία, με τον ανασχεδιασμό ενός ατομιστικού αλγορίθμου Monte Carlo (MC) μελετήθηκε η μεσόμορφη κατάσταση του F12H12 και συγκεκριμένα στόχος ήταν η πρόβλεψη της αυτό-οργάνωσης του συστήματος στον κύριο όγκο (bulk system) και στην ενδιάμεση κατάστασή του. Όμως για να καταστεί εφικτή αυτή η μελέτη, ήταν αναγκαία η εύρεση από την διεθνή βιβλιογραφία ενός μοριακού μοντέλου, το οποίο θα μπορούσε να προβλέψει με την καλύτερη δυνατή ακρίβεια τις ιδιότητές του υπό μελέτη συστήματος. Προς την κατεύθυνση αυτή, δοκιμάστηκαν τρία μοριακά μοντέλα με διαφορετικές παραμέτρους αλληλεπίδρασης των ατομιστικών μονάδων του μορίου. Τα αποτελέσματα των προσομοιώσεων Monte Carlo δεν ήταν τα αναμενόμενα, σύμφωνα με τα διαθέσιμα πειραματικά δεδομένα. Η ιδέα της εφαρμογή της μεθόδου μοριακής δυναμικής για τη μελέτη της μεσόμορφης κατάστασης των F12H12 κρίθηκε απαραίτητη για την εξισορρόπηση του συστήματος σε εύλογο χρονικό υπολογιστικό διάστημα, αλλά και για τη χρήση της ως εργαλείο ελέγχου της αξιοπιστίας του αλγορίθμου MC και των μοριακών μοντέλων. Από τα αποτελέσματα προσομοιώσεων MD εξακριβώθηκε η ορθότητα του αλγορίθμου MC και προέκυψε το συμπέρασμα ότι τα εξεταζόμενα μοριακά μοντέλα αδυνατούν να προβλέψουν με ακρίβεια και επιτυχία τα πειραματικά δεδομένα, καθώς τουλάχιστον τα δύο από αυτά εντοπίζουν τη μετάβαση φάσης από την ισοτροπική στην μεσόμορφη κατάσταση μικρότερης τάξης σε διαφορετικές συνθήκες (μικρότερη θερμοκρασία, μεγαλύτερη πυκνότητα) από αυτές των πειραματικά μετρούμενων. Σε αυτές τις συνθήκες εφαρμόστηκε και η μέθοδος προσομοίωσης Monte Carlo η οποία δεν είχε την δυνατότητα να εξισορροπήσει το υπό μελέτη σύστημα σε μικρές θερμοκρασίες και να προβλέψει την μετάβαση φάσης. Σε κάθε περίπτωση θα ήταν εξαιρετικά ενδιαφέρουσα η περαιτέρω μελέτη του συστήματος F12H12. / Semifluorinated alkanes (SFAs) are diblock molecules, which consist of two immiscible and incompatible moieties, the perfluorinated segment (CF2)m and the hydrοgenated segment (CH2)n, which are covalently linked to form the copolymer with the general chemical structure F(CF2)m(CH2)nH, abbreviated as FmHn. The (CF2)m and (CH2)n segments have different conformation, as the first one adopts a twisted 15/7 helical structure, whereas the other prefers an all-trans zigzag conformation. Due to the incompatibility between the two segments and consequently their asymmetric structure, SFAs are capable of remarkable phenomena, such as structural transitions, formation of ordered structure and aggregations in non-polar solvents, influenced by the existence of significant dipole moment and surface activity. In spite of the absence of hydrophilic polar head group from the diblock, SFAs possess an amphiphilic character and form Langmuir monolayers at the air/water interface. Furthermore, because of their biocompatibility and their tendency to stabilize interfacial films and control properties of biological colloidal systems, they have been used as additional components in fluorocarbon-in-water emulsion applicants to artificial blood formulation, in phospholipid liposomes that act as drug delivery systems, in ophthalmology as endotamponades, in vitreoretinal surgery and in lung surfactant therapy. Despite the amply of studies as far as the structure and the behavior of solid state SFAs, the identification of phase transition structure has not clearly spelled out, but for some FmHn it has eventually been described as liquid crystalline or smectic phase. Experimental efforts to predict the solid state packing structures in the bulk and the phase state of SFAs, arising from the incommensurable cross-section of the two opposing moieties, with comparable segment lengths and especially for F12Hn compounds have attracted the scientific interest in the literature. DSC measurements indicate the existence of solid-solid phase transitions for F12Hn with n= 8, 10 and 12. Two different crystal packings with layered structure have been observed below the melting point of F12Hn by SAXS and electron density profiles. It is proposed that F12Hn chains with 8 ≤ n ≤ 14 form an antiparallel monolayer packing below their melting point and at lower temperature it follows the transformation to a tilted bilayer lamella, as the Bragg spacings are larger than the end-to-end distance of the individual molecules. For the same group of F12Hn, their phase is referred as a mesomorphic phase below the melting transition and it is described as a “smectic liquid crystalline phase”, whereas at the solid-solid transition the hydrogenated segment presents a fluidlike character. Semifluorinated alkane F(CF2)m(CH2)n with m=n=12 is a linear, symmetric diblock, that is abbreviated as F12H12. It exhibits interesting morphologies not only in the air/water interface, as it forms Langmuir monolayers consisting of “spherical cap” substructures with the orientation of the perfluorocarbon segment on the air1, but also in the bulk state. The DCS experiments and the thermodynamic pressure-volume temperature measurements proposed that the F12H12 system undergoes solid-solid transitions and especially favors two first order transitions. Brillouin spectroscopy, X-ray scattering studies and NMR experiments showed that F121H12 below its melting point exhibits phases that are denoted as layered smectic phases or lamellar phases. In particular, below Tm ~361-363K (melting point) a mesophase exists, whose structure is composed from a monolayer lamella in which hydrocarbon and perfluorinated segments display interdigitation. At lower temperatures (Ts ~351-353K) the system exhibits a denser solid phase that comprises of a fluorocarbon bilayer lamella with interdigitated hydrocarbon segments. In this present work, we report results of constant pressure atomistic molecular simulations, both using molecular dynamics and Monte Carlo methods and adopting a molecular united model, for predicting the phase transition and the solid bulk-phase assembly of F12H12 molecules. Furthermore, thermodynamic and structural properties are studied and thus the evaluation of the predictions obtained from the two methods is sought through comparison with the available experimental data.

Stochastic programming combines ideas from deterministic optimization with probability and statistics to produce more accurate models of optimization problems involving uncertainty. However, due to their size, stochastic programming problems can be extremely difficult to solve and instead approximate solutions are used. Therefore, there is a need for methods that can accurately identify optimal or near optimal solutions. In this dissertation, we focus on improving Monte-Carlo sampling-based methods that assess the quality of potential solutions to stochastic programs by estimating optimality gaps. In particular, we aim to reduce the bias and/or variance of these estimators. We first propose a technique to reduce the bias of optimality gap estimators which is based on probability metrics and stability results in stochastic programming. This method, which requires the solution of a minimum-weight perfect matching problem, can be run in polynomial time in sample size. We establish asymptotic properties and present computational results. We then investigate the use of sampling schemes to reduce the variance of optimality gap estimators, and in particular focus on antithetic variates and Latin hypercube sampling. We also combine these methods with the bias reduction technique discussed above. Asymptotic properties of the resultant estimators are presented, and computational results on a range of test problems are discussed. Finally, we apply methods of assessing solution quality using antithetic variates and Latin hypercube sampling to a sequential sampling procedure to solve stochastic programs. In this setting, we use Latin hypercube sampling when generating a sequence of candidate solutions that is input to the procedure. We prove that these procedures produce a high-quality solution with high probability, asymptotically, and terminate in a finite number of iterations. Computational results are presented.

The goal of radiotherapy is to operate within the therapeutic window - delivering doses of ionizing radiation to achieve locoregional tumour control, while minimizing normal tissue toxicity. A greater therapeutic ratio can be achieved by utilizing radiosensitizing agents designed to enhance the effects of radiation at the tumour. Gold nanoparticles (AuNP) represent a novel radiosensitizer with unique and attractive properties. AuNPs enhance local photon interactions, thereby converting photons into localized damaging electrons. Experimental reports of AuNP radiosensitization reveal this enhancement effect to be highly sensitive to irradiation source energy, cell line, and AuNP size, concentration and intracellular localization. This thesis explored the physics and some of the underlying mechanisms behind AuNP radiosensitization. A Monte Carlo simulation approach was developed to investigate the enhanced photoelectric absorption within AuNPs, and to characterize the escaping energy and range of the photoelectric products. Simulations revealed a 10^3 fold increase in the rate of photoelectric absorption using low-energy brachytherapy sources compared to megavolt sources. For low-energy sources, AuNPs released electrons with ranges of only a few microns in the surrounding tissue. For higher energy sources, longer ranged photoelectric products travelled orders of magnitude farther. A novel radiobiological model called the AuNP radiosensitization predictive (ARP) model was developed based on the unique nanoscale energy deposition pattern around AuNPs. The ARP model incorporated detailed Monte Carlo simulations with experimentally determined parameters to predict AuNP radiosensitization. This model compared well to in vitro experiments involving two cancer cell lines (PC-3 and SK-BR-3), two AuNP sizes (5 and 30 nm) and two source energies (100 and 300 kVp). The ARP model was then used to explore the effects of AuNP intracellular localization using 1.9 and 100 nm AuNPs, and 100 and 300 kVp source energies. The impact of AuNP localization was most significant for low-energy sources. At equal mass concentrations, AuNP size did not impact radiosensitization unless the AuNPs were localized in the nucleus. This novel predictive model of AuNP radiosensitization could help define the optimal use of AuNPs in potential clinical strategies by determining therapeutic AuNP concentrations, and recommending when active approaches to cellular accumulation are most beneficial.

El CMC, tamaño y forma de micelas son características importantes en la determinación de sus principales propiedades y campos de aplicación. Esta tesis tiene dos partes, las transiciones de forma de las micelas que se trata con "Single chain Field Theory, /SCMFT)" y simulaciones de Monte Carlo. El SCMFT reveló todas las características esenciales de las transiciones de forma esférica a cilíndrica y esférica a disco de las micelas. MC muestra que las transiciones esfera a cilindro se produce a través de una región en que esferas y cilindros coexisten junto con otras formas intermedias.

Hadron Therapy is an advanced radiotherapy technique for cancer treatment. It offers a better irradiation ballistic than conventional techniques and therefore requires appropriate quality assurance procedures. In this work, we upgraded the GEANT4-based GATE Monte Carlo platform in order to recalculate the TPS dose distributions in view of further benchmarking. In a first step, we selected an appropriate simulation environment (physics models and parameters) in order to produce accurate and efficient simulations. GATE simulations were validated using measurements and other Monte Carlo codes for depth-dose and transverse profiles. While a good agreement was found for depth-dose profiles, larger discrepancies were pointed out for transverse profiles. In a second step, we developed a modeling method to simulate active scanning beam delivery systems, which does not require to simulate the components of the treatment nozzle. The method has been successfully applied to an IBA proton therapy system and validated against measurements for complex treatment plans. Interfaces have also been developed in order to link DICOM RT ION PLAN and DICOM RT DOSE with GATE. Finally, we compared in a third step the TPS and Monte Carlo dose distributions in homogeneous and heterogeneous configurations. The beam models of both dose engines were in satisfactory agreement, allowing further evaluation of clinical treatment plans. A two-field prostate plan has been evaluated, showing a satisfactory agreement between the TPS and Monte Carlo, and demonstrating the novel capabilities of the platform for the evaluation of the TPS. To summarize, we selected an appropriate simulation environment for proton therapy, proposed a modeling method for active scanning systems and presented a method to compare the TPS and Monte Carlo dose distributions. All tools developed in GATE were or will be publicly released. A detailed validation stage of the system including absolute dosimetry is still necessary, in order to quantitatively evaluate its accuracy in various homogeneous and heterogeneous configurations. In this thesis, we have demonstrated that the GATE Monte Carlo platform is a good candidate for the simulation of active scanning delivery systems, allowing further TPS benchmarking. Moreover, the GATE platform also handles imaging applications, such as PET or prompt-gamma imaging towards online treatment monitoring and paves the way of interdisciplinary research advances.

The thesis studies the martingale properties, probabilistic methods and efficient unbiased Monte Carlo simulation methods for various time-homogeneous diffusion models commonly used in mathematical finance. Some of the popular stochastic volatility models such as the Heston model, the Hull-White model and the 3/2 model are special cases. The thesis consists of the following three parts: Part I: Martingale properties in time-homogeneous diffusion models: Part I of the thesis studies martingale properties of stock prices in stochastic volatility models driven by time-homogeneous diffusions. We find necessary and sufficient conditions for the martingale properties. The conditions are based on the local integrability of certain deterministic test functions. Part II: Analytical pricing methods in time-homogeneous diffusion models: Part II of the thesis studies probabilistic methods for determining the Laplace transform of the first hitting time of an integral functional of a time-homogeneous diffusion, and pricing an arithmetic Asian option when the stock price is modeled by a time-homogeneous diffusion. We also consider the pricing of discrete variance swaps and discrete gamma swaps in stochastic volatility models based on time-homogeneous diffusions. Part III: Nearly Unbiased Monte Carlo Simulation: Part III of the thesis studies the unbiased Monte Carlo simulation of option prices when the characteristic function of the stock price is known but its density function is unknown or complicated.