This thesis addresses the metal nanocluster growth process on prepatterned substrates, the development of atomistic simulation method with respect to an acceleration of the atomistic transition states, and the continuum model of the ion-beam inducing semiconductor surface pattern formation mechanism. Experimentally, highly ordered Ag nanocluster structures have been grown on pre-patterned amorphous SiO2 surfaces by oblique angle physical vapor deposition at room temperature. Despite the small undulation of the rippled surface, the stripe-like Ag nanoclusters are very pronounced, reproducible and well-separated. The first topic is the investigation of this growth process with a continuum theoretical approach to the surface gas condensation as well as an atomistic cluster growth model. The atomistic simulation model is a lattice-based kinetic Monte-Carlo (KMC) method using a combination of a simplified inter-atomic potential and experimental transition barriers taken from the literature. An effective transition event classification method is introduced which allows a boost factor of several thousand compared to a traditional KMC approach, thus allowing experimental time scales to be modeled. The simulation predicts a low sticking probability for the arriving atoms, millisecond order lifetimes for single Ag monomers and about 1 nm square surface migration ranges of Ag monomers. The simulations give excellent reproduction of the experimentally observed nanocluster growth patterns. The second topic specifies the acceleration scheme utilized in the metallic cluster growth model. Concerning the atomistic movements, a classical harmonic transition state theory is considered and applied in discrete lattice cells with hierarchical transition levels. The model results in an effective reduction of KMC simulation steps by utilizing a classification scheme of transition levels for thermally activated atomistic diffusion processes. Thermally activated atomistic movements are considered as local transition events constrained in potential energy wells over certain local time periods. These processes are represented by Markov chains of multi-dimensional Boolean valued functions in three dimensional lattice space. The events inhibited by the barriers under a certain level are regarded as thermal fluctuations of the canonical ensemble and accepted freely. Consequently, the fluctuating system evolution process is implemented as a Markov chain of equivalence class objects. It is shown that the process can be characterized by the acceptance of metastable local transitions. The method is applied to a problem of Au and Ag cluster growth on a rippled surface. The simulation predicts the existence of a morphology dependent transition time limit from a local metastable to stable state for subsequent cluster growth by accretion. The third topic is the formation of ripple structures on ion bombarded semiconductor surfaces treated in the first topic as the prepatterned substrate of the metallic deposition. This intriguing phenomenon has been known since the 1960s and various theoretical approaches have been explored. These previous models are discussed and a new non-linear model is formulated, based on the local atomic flow and associated density change in the near surface region. Within this framework ripple structures are shown to form without the necessity to invoke surface diffusion or large sputtering as important mechanisms. The model can also be extended to the case where sputtering is important and it is shown that in this case, certain "magic" angles can occur at which the ripple patterns are most clearly defined. The results including some analytic solutions of the nonlinear equation of motions are in very good agreement with experimental observation.

The ageing state of the world's nuclear power infrastructure, and the need to reduce humanity s dependency on fossil fuels, requires that this electrical energy generating capacity is replaced. Economic factors, and its physical and chemical properties, make high purity iron-chromium binary alloys a strong candidate for use in the construction of the pressure vessels of the next generation of nuclear reactors. This relatively inexpensive metal retains the oxidation resistance property of so-called stainless steel alloys, and has demonstrated dimensional stability and low degradation under harsh experimental environments of temperature and radiation. In this work, we consider radiation induced interstitial damage to the atomic lattices of iron-chromium binary alloys using the atomistic modelling methods, Molecular Dynamics and Adaptive Kinetic Monte Carlo, simulating collision cascade sequences, and the migration of defects in the aftermath. Variations in chromium content does not effect the initial damage production in terms of the number of Frenkel pairs produced, but iron and chromium atoms are not evenly distributed in defect atoms with respect to the bulk concentration. In simulations conducted at low temperature, chromium is under-represented, and at high temperature, a greater proportion of interstitial atoms are chromium than in the lattice overall. The latter phenomena is most strongly pronounced in systems of low bulk chromium content. During the simulation of post-cascade defect migration, interstitials atoms are observed to form temporary clusters and vacancies align along adjacent lattice sites, with the two types of defect also migrating to annihilate by recombination. Calculating the energy spectra of cascade events corresponding to an example experimental configuration using the SRIM package, we investigated the evolution of lattice systems in which a sequence of multiple cascade events occurred, both with and without a physically representative time gap between events. These simulations gave us the opportunity to observe the behaviour of cascades in the proximity of damage remaining from previous events, such as the promotion of defect clustering when this occurs.

The following thesis deals with methods to increase the reliability of the results in life cycle assessment. The paper is divided into two parts. The first part points out the typologies and sources of uncertainty in LCA and summarises the existing methods dealing with it. The methods are critically discussed and pros and cons are contrasted. Within the second part a case study is carried out. This study calculates the carbon footprint of a cosmetic product of Li-iL GmbH. Thereby the whole life cycle of the powder bath Blaue Traube is analysed. To increase the reliability of the result a procedure, derived from the first part, is applied. Recommendations to enhance the product´s sustainability are then given to the decision-makers of the company. Finally the applied procedure for dealing with uncertainty in LCAs is evaluated. The aims of the thesis are to make a contribution to the understanding of uncertainty in life cycle assessment and to deal with it in a more consistent manner. As well, the carbon footprint of the powder bath shall be based on appropriate assumptions and shall consider occurring uncertainties. Basing on discussed problems, a method is introduced to avoid the problematic merging of variability uncertainty and data uncertainty to generate probability distributions. The introduced uncertainty importance analysis allows a consistent differentiation of these types of uncertainty. Furthermore an assessment of the used data of LCA studies is possible. The method is applied at a PCF study of the bath powder Blaue Traube of Li-iL GmbH. Thereby the analysis is carried out over the whole life cycle (cradle-to-grave) as well as cradle-to-gate. The study gives a practical example to the company determining the carbon footprint of products. In addition, it meets the requirements of ISO guidelines of publishing the study and comparing it with other products. Within the PCF study the introduced method allows a differentiation of variability uncertainty and knowledge uncertainty. The included uncertainty importance analysis supports the assessment of each aggregated unit process within the analysed product system. Finally this analysis can provide a basis to collect additional, more reliable or uncertain data for critical processes.

This thesis addresses the metal nanocluster growth process on prepatterned substrates, the development of atomistic simulation method with respect to an acceleration of the atomistic transition states, and the continuum model of the ion-beam inducing semiconductor surface pattern formation mechanism. Experimentally, highly ordered Ag nanocluster structures have been grown on pre-patterned amorphous SiO2 surfaces by oblique angle physical vapor deposition at room temperature. Despite the small undulation of the rippled surface, the stripe-like Ag nanoclusters are very pronounced, reproducible and well-separated. The first topic is the investigation of this growth process with a continuum theoretical approach to the surface gas condensation as well as an atomistic cluster growth model. The atomistic simulation model is a lattice-based kinetic Monte-Carlo (KMC) method using a combination of a simplified inter-atomic potential and experimental transition barriers taken from the literature. An effective transition event classification method is introduced which allows a boost factor of several thousand compared to a traditional KMC approach, thus allowing experimental time scales to be modeled. The simulation predicts a low sticking probability for the arriving atoms, millisecond order lifetimes for single Ag monomers and about 1 nm square surface migration ranges of Ag monomers. The simulations give excellent reproduction of the experimentally observed nanocluster growth patterns. The second topic specifies the acceleration scheme utilized in the metallic cluster growth model. Concerning the atomistic movements, a classical harmonic transition state theory is considered and applied in discrete lattice cells with hierarchical transition levels. The model results in an effective reduction of KMC simulation steps by utilizing a classification scheme of transition levels for thermally activated atomistic diffusion processes. Thermally activated atomistic movements are considered as local transition events constrained in potential energy wells over certain local time periods. These processes are represented by Markov chains of multi-dimensional Boolean valued functions in three dimensional lattice space. The events inhibited by the barriers under a certain level are regarded as thermal fluctuations of the canonical ensemble and accepted freely. Consequently, the fluctuating system evolution process is implemented as a Markov chain of equivalence class objects. It is shown that the process can be characterized by the acceptance of metastable local transitions. The method is applied to a problem of Au and Ag cluster growth on a rippled surface. The simulation predicts the existence of a morphology dependent transition time limit from a local metastable to stable state for subsequent cluster growth by accretion. The third topic is the formation of ripple structures on ion bombarded semiconductor surfaces treated in the first topic as the prepatterned substrate of the metallic deposition. This intriguing phenomenon has been known since the 1960s and various theoretical approaches have been explored. These previous models are discussed and a new non-linear model is formulated, based on the local atomic flow and associated density change in the near surface region. Within this framework ripple structures are shown to form without the necessity to invoke surface diffusion or large sputtering as important mechanisms. The model can also be extended to the case where sputtering is important and it is shown that in this case, certain "magic" angles can occur at which the ripple patterns are most clearly defined. The results including some analytic solutions of the nonlinear equation of motions are in very good agreement with experimental observation.:1 Introduction: Atomistic Models 1 1.1 Density Functional Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.1.1 Schroedinger equation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.1.2 Density functional theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2 Molecular Dynamics Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.2.1 Lagrangian mechanics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.2.2 MD algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.3 Lattice Monte Carlo simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 1.3.1 Thermodynamic variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 1.3.2 Metropolis Algorithm and limit theorem . . . . . . . . . . . . . . . . . . . . . 15 1.3.3 Kinetic Monte Carlo Simulation . . . . . . . . . . . . . . . . . . . . . . . . . 18 1.3.4 Imaginary time reaction diffusion . . . . . . . . . . . . . . . . . . . . . . . . . 24 2 Cluster Growth on Pre-patterned Surfaces 29 2.1 Nanocluster growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 2.1.1 Classical nucleation theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 2.1.2 Cluster growth on substrates . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 2.1.3 Experimental motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 2.2 Local flux and surface ad-monomer diffusion . . . . . . . . . . . . . . . . . . . . . . 35 2.2.1 Surface topography and local flux . . . . . . . . . . . . . . . . . . . . . . . . 35 2.2.2 Surface gas diffusion under inhomogeneous flux . . . . . . . . . . . . . . . . . 37 2.2.3 Surface migration of ad-monomers . . . . . . . . . . . . . . . . . . . . . . . . 40 2.2.4 Simulation vs. experimental gauge . . . . . . . . . . . . . . . . . . . . . . . . 45 2.3 Nucleation models: Surface gas condensation . . . . . . . . . . . . . . . . . . . . . . 46 2.3.1 Simulation setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 2.3.2 Simulation parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 2.3.3 Evolution of sticking probability . . . . . . . . . . . . . . . . . . . . . . . . . 49 2.3.4 Evolution of Ag cluster growth . . . . . . . . . . . . . . . . . . . . . . . . . . 54 2.3.5 Simulation time and system evolution . . . . . . . . . . . . . . . . . . . . . . 57 2.4 Extended cluster growth model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 2.4.1 Modified setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 2.4.2 Simulation result . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 2.4.3 Comparison with experiment . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 2.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 3 A Markov chain model of transition states 63 3.1 Acceleration of thin film growth simulation . . . . . . . . . . . . . . . . . . . . . . . 63 3.2 Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 3.3 Transition states of Markov chains . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 3.3.1 Local transition events . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 3.3.2 The Monte-Carlo method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 3.4 Effective transitions of objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 3.4.1 Convergence of the local fluctuation . . . . . . . . . . . . . . . . . . . . . . . 67 3.4.2 The importance of individual local transitions . . . . . . . . . . . . . . . . . . 68 3.4.3 The modified algorithm for effective transition states . . . . . . . . . . . . . . 69 3.5 Cluster growth simulation models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 3.5.1 The configuration energy and migration barriers . . . . . . . . . . . . . . . . 72 3.5.2 Transition events . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 3.5.3 Comparison with Experiment . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 3.5.4 Cluster growth stability evaluation . . . . . . . . . . . . . . . . . . . . . . . . 78 3.6 Stability of modified convergence limit . . . . . . . . . . . . . . . . . . . . . . . . . . 80 3.6.1 Acceleration of convergence to Gibbs field . . . . . . . . . . . . . . . . . . . . 80 3.6.2 Relative convergence speed . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 3.6.3 1D Ag models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 3.6.4 Stability theorem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 3.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 4 Ion beam inducing surface pattern formation 89 4.1 Ion-inducing pattern formation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 4.1.1 Bradley-Harper equation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 4.1.2 Nonlinear continuum models . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 4.1.3 Other approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 4.2 Simulation of surface defects induced by ion beams . . . . . . . . . . . . . . . . . . . 94 4.2.1 MD simulation of single ion impact . . . . . . . . . . . . . . . . . . . . . . . . 94 4.2.2 Monte-Carlo simulations of surface modification . . . . . . . . . . . . . . . . 96 4.2.3 Curvature dependent surface diffusion . . . . . . . . . . . . . . . . . . . . . . 102 4.3 Continuum model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 4.3.1 Equation of motion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 4.3.2 A travelling wave solution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 4.3.3 Lyapunov stability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 4.3.4 Comparison with experiment . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 4.3.5 Approximate solutions for other angles . . . . . . . . . . . . . . . . . . . . . . 110 4.4 Contribution of other effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 4.4.1 Surface diffusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 4.4.2 Surface Sputtering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 4.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 5 Summary 119 Appendix 123 A The discrete reaction diffusion equation . . . . . . . . . . . . . . . . . . . . . . . . . 123 B The derivation of the solution (2.20) . . . . . . . . . . . . . . . . . . . . . . . . . . . 124 C Contribution of overlapping migration area . . . . . . . . . . . . . . . . . . . . . . . 125 D The RGL potential . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 E Stability of the traveling wave solution . . . . . . . . . . . . . . . . . . . . . . . . . . 127

Master of Science / Department of Industrial & Manufacturing Systems Engineering / Chih-Hang Wu / The recent economic crisis has been partially blamed on the decline in the housing market. This decline in the housing market resulted in an estimated 87% decline in value of collateralized debt obligations (CDOs) between 2007 and 2008. This drastic decline in home values was sudden and unanticipated, thus it was incomprehensible for many investors how this would affect CDOs. This shows that while analytical techniques can be used to price CDOs, these techniques cannot be used to demonstrate the behavior of CDOs under radically different economic circumstances. To better understand the behavior of CDOs under different economic circumstances, numerical techniques such as Monte Carlo simulation can be used instead of analytical techniques to price CDOs. Andersen et al (2005) proposed a method for calculating the probability of defaults that could then be used in the Monte Carlo simulation to price the collateralized debt obligation. The research proposed by Andersen et al (2005) demonstrates the process of calculating correlated probability of defaults for a group of obligors. This calculation is based on the correlations between the obligors using copulas. Using this probability of default, the price of a collateralized debt obligation can be evaluated using Monte Carlo simulation. Monte Carlo simulation provides a more simple yet effective approach compared to analytical pricing techniques. Simulation also allows investors to have a better understanding of the behaviors of CDOs compared to analytical pricing techniques. By analyzing the various behaviors under uncertainty, it can be observed how a downturn in the economy could affect CDOs. This thesis extends on the use of copulas to simulate the correlation between obligors. Copulas allow for the creation of one joint distribution using a set of independent distributions thus allowing for an efficient way of modeling the correlation between obligors. The research contained within this thesis demonstrates how Monte Carlo simulation can be used to effectively price collateralized debt obligations. It also shows how the use of copulas can be used to accurately characterize the correlation between obligor defaults for pricing collateralized debt obligations. Numerical examples for both the obligor defaults and the price of collateralized debt obligations are presented to demonstrate the results using Monte Carlo simulation.

The purpose of this thesis is to provide a detailed description of recent methods and scientific basis for characterizing earthquake sources within a certain region with distinct tectonic environments. The focus will be on those characteristics that are most significant to the ground-shaking hazard and on how we can incorporate our current knowledge into hazard analyses for engineering design purposes. I treat two particular geographical areas where I think current hazard analysis methods are in need of significant improvement, and suggest some approaches that have proven to be effective in past applications elsewhere. A combined hazard procedure is used to estimate seismicity in northern Central America, where there appear to be four tectonic environments for modeling the seismogenic sources and in Iran, where the large earthquakes usually occur on known faults. A preferred seismic hazard model for northern Central America and the western Caribbean plate based on earthquake catalogs, geodetic measurements, and geological information is presented. I used the widely practiced method of relating seismicity data to geological data to assess the various seismic hazard parameters and test parameter sensitivities. The sensitivity and overall uncertainty in peak ground acceleration (PGA) estimates are calculated for northwestern Iran by using a specific randomized blocks design. A Monte Carlo approach is utilized to evaluate the ground motion hazard and its uncertainties in northern Central America. A set of new seismic hazard maps, exhibiting probabilistic values of peak ground acceleration (PGA) with 50%, 10%, and 5% probabilities of exceedance (PE) in 50 years, is presented for the area of relevance. Disaggregation of seismic hazard is carried out for cities of San Salvador and Guatemala by using a spatial distribution of epicenters around these sites to select design ground motion for seismic risk decisions. In conclusion, consideration of the effect of parameters such as seismic moment, fault rupture, rupture directivity and stress drop are strongly recommended in estimating the near field ground motions. The rupture process of the 2002 Changureh earthquake (Mw = 6.5), Iran, was analyzed by using the empirical Green’s function (EGF) method. This method simulates strong ground motions for future large earthquakes at particular sites where no empirical data are available.

This thesis deals with safety verification analysis of collision avoidance systems for unmanned vehicles. The safety of the vehicle is dependent on collision avoidance algorithms and associated control laws, and it must be proven that the collision avoidance algorithms and controllers are functioning correctly in all nominal conditions, various failure conditions and in the presence of possible variations in the vehicle and operational environment. The current widely used exhaustive search based approaches are not suitable for safety analysis of autonomous vehicles due to the large number of possible variations and the complexity of algorithms and the systems. To address this topic, a new optimisation-based verification method is developed to verify the safety of collision avoidance systems. The proposed verification method formulates the worst case analysis problem arising the verification of collision avoidance systems into an optimisation problem and employs optimisation algorithms to automatically search the worst cases. Minimum distance to the obstacle during the collision avoidance manoeuvre is defined as the objective function of the optimisation problem, and realistic simulation consisting of the detailed vehicle dynamics, the operational environment, the collision avoidance algorithm and low level control laws is embedded in the optimisation process. This enables the verification process to take into account the parameters variations in the vehicle, the change of the environment, the uncertainties in sensors, and in particular the mismatching between model used for developing the collision avoidance algorithms and the real vehicle. It is shown that the resultant simulation based optimisation problem is non-convex and there might be many local optima. To illustrate and investigate the proposed optimisation based verification process, the potential field method and decision making collision avoidance method are chosen as an obstacle avoidance candidate technique for verification study. Five benchmark case studies are investigated in this thesis: static obstacle avoidance system of a simple unicycle robot, moving obstacle avoidance system for a Pioneer 3DX robot, and a 6 Degrees of Freedom fixed wing Unmanned Aerial Vehicle with static and moving collision avoidance algorithms. It is proven that although a local optimisation method for nonlinear optimisation is quite efficient, it is not able to find the most dangerous situation. Results in this thesis show that, among all the global optimisation methods that have been investigated, the DIviding RECTangle method provides most promising performance for verification of collision avoidance functions in terms of guaranteed capability in searching worst scenarios.

In recent years, metal-organic frameworks (MOFs) have been identified as promising adsorbents in a number of industrially relevant, yet challenging, separations, including the removal of propane from propane/propylene mixtures and the separation of mixtures of xylene isomers. The highly tuneable nature of MOFs - wherein structures may be constructed from a variety of diverse building blocks – has resulted in the publication of a staggering number of frameworks incorporating a wide range of network topologies, pore shapes and pore diameters. As a result, there are a huge number of candidate adsorbents to consider for a given separation. Molecular simulation techniques allow the identification of those structural features and characteristics of a MOF which exert the greatest influence on the adsorption and separation of the compounds of interest, providing insights which can both guide the selection and accelerate the development of adsorbents for a specific application. The separation of propane/propylene mixtures via adsorption has typically focused on selective adsorption of the olefin, propylene, via specific olefin-adsorbent interactions. These propylene-selective MOFs result in processes which selectively remove the most abundant species in the process stream and are typically characterised by high heats of adsorption, resulting in large adsorption units and adsorbents which are difficult to regenerate. In this work, the capability of MOFs to selectively adsorb propane over propylene is explored, potentially allowing for the design of smaller and more energy-efficient adsorption units. By studying a range of different MOFs as well as carbon-based model pores, it was found that the low-pressure selectivity of the structure is determined by the strength of the electrostatic interaction between propylene and the framework, while the adsorptive preference at industrially-relevant pressures is dominated by the enhanced packing efficiency of propylene over propane. The confinement of C3 molecules, however, may be employed to negate this entropic advantage and guide the development of materials which selectively adsorb propane over propylene. It has recently been reported that the adsorptive preference of a MOF for one xylene isomer over another may be predicted based solely on the pore size distribution of the structure. In this work, the impact of pore size on selectivity was studied systematically in both one-dimensional model pore systems of varying geometries and analogous published MOF structures. The ability of the framework to discriminate between xylene molecules in these systems was found to be determined primarily by the different packing arrangements available to the different isomers – while small pores were found to favour the slimmest of the isomers, larger pores were found to favour the more compact ortho- isomer. Finally, the adsorption and diffusion of xylene isomers in a more complex MOF, UiO-66(Zr), was studied in depth. Simulations were able to correctly predict the previously-reported preference of the MOF for ortho-xylene (oX). The smaller volume of the oX molecule compared to the other isomers was found to be responsible both for an enhanced entropic contribution and higher guest-host interaction energies. The importance of framework flexibility in the diffusion of xylene isomers in UiO-66(Zr) was also explored, with distortion of the structure in response to interaction with adsorbed molecules found to be essential in allowing xylenes to diffuse through the pore space.

The backbone of our industrialised society and economy is electricity. To avoid a catastrophic situation, a plan for how to act during a power shortage is crucial. Previous research shows that decision models provide support to decision makers providing efficient energy rationing during power shortages in the Netherlands, United States and Canada. The existing research needs to be expanded with a group decision model to enable group decisions. This study is conducted with a case study approach where the Swedish emergency preparedness plan in case of power shortage, named Styrel, is explored and used to evaluate properties of a proposed group decision model. The study consist of a qualitative phase and a quantitative phase including a Monte Carlo simulation of group decisions in Styrel evaluated with correlation analysis. The qualitative results show that participants in Styrel experience the group decisions as time-consuming and unstructured. The current decision support is not used in neither of the two counties included in the study, with the motivation that the preferences provided by the decision support are misleading. The proposed group decision model include a measurable value function assigning values to priority classes for electricity users, an additive model to represent preferences of individual decision makers and an additive group decision model to aggregate preferences of several individual decision makers into a group decision. The conducted simulation indicate that the proposed group decision model evaluated in Styrel is sensitive to significant changes and more robust to moderate changes in preference differences between priority classes.

<p>Three methods of sensitivity and unceartainty analysis have been applied to the operative stormwater- and recipient model StormTac. The study area is the watershed of lake Flaten in the municipality Salem. StormTac’s submodels for stormwater, pollutant transport and the recipient are cosidired. In the sensitivity assessment, the model parametres and inputs were varied one at a time by a constant percentage according to the “one at a time” (OAAT) method and the response of the outputs were calculated. It was found that the stormwater- and baseflow were most sensitive to perturbations in the perciptation. Unceartainty analysis using Monte Carlo simulation was performed in two different ways. (1) All model parametres and inputs were included with defined unceartainties and the resulting unceartainty for the target variable was quantified. Thereafter, whith the purpose to estimate the contribution of all the parametres and inputs, the cumulative uncertainty for the target variable, each parameters/inputs unceartainty was omitted one at the time. The most crucial uncertainty for the storm water flow was the runoff coefficient for forestland and the perciptation (i.e the differens between the 90- and 10-percentile for the storm water flow was reduced whith 44 % and 33 % respectively). (2) To identify optimal parameter intervals, the probability for an acceptable value of the target variable was plotted against each parameters value range. The result suggests that for some of the parametres i StormTac, the ranges should be changed.</p> / <p>Den operativa dagvatten- och recipientmodellen StormTac har applicerats på sjön Flatens avrinningsområde i Salems kommun. StormTac:s delmodeller för dagvatten, föroreningstransport och recipienten studerades. Tre olika metoder för att undersöka osäkerheten och känsligheten hos parametrar och indata i delmodellerna tillämpades. I känslighetsanalysen (OAAT-metoden) behäftades parametervärdena och indata med systematiska fel och responsen hos utdata beräknades. Dag- och basvattenflödet var känsligast mot fel i nederbördsdata, medan kväve-, fosfor- och kopparbelastningen till recipienten var känsligast mot respektive förorenings dagvattenkoncentration från områden med bebyggelse. Varje parameter och indatas bidrag till den kumulativa osäkerheten hos utdata uppskattades med hjälp av Montecarlosimulering. Genom att för varje effektvariabel studera differensen mellan 90- och 10-percentilen när osäkerheten hos en parameter/indata i taget utelämnades, kunde varje parameters/indatas bidrag till modellresultatets osäkerhet kvantifieras. För dagvattenflödet bidrog avrinningskoefficienten för skogmark med 44 % av osäkerheten och nederbörden med 33 %. Montecarloanlys praktiserades även för att identifiera optimala intervall för parametrarna i modellen. Sannolikheten för ett accepterat värde på den simulerade effektvariabeln plottades mot varje parameters värdemängd. För vissa parametrar indikerade resultatet att intervallen kan förändras mot hur de i nuläget ser ut i StormTac. Uniforma sannolikhetsfördelningar, begränsade av StormTac:s min- och maxvärden för parametrarna och ± 50% av orginalvärdet för indata, användes i båda osäkerhetsanalyserna.</p>