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  • Public defence: 2024-04-23 13:00 F3, Stockholm
    Rodríguez Gálvez, Borja
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    An Information-Theoretic Approach to Generalization Theory2024Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    In this thesis, we investigate the in-distribution generalization of machine learning algorithms, focusing on establishing rigorous upper bounds on the generalization error. We depart from traditional complexity-based approaches by introducing and analyzing information-theoretic bounds that quantify the dependence between a learning algorithm and the training data.

    We consider two categories of generalization guarantees:

    • Guarantees in expectation. These bounds measure performance in the average case. Here, the dependence between the algorithm and the data is often captured by the mutual information or other information measures based on ƒ-divergences. While these measures offer an intuitive interpretation, they might overlook the geometry of the algorithm's hypothesis class. To address this limitation, we introduce bounds using the Wasserstein distance, which incorporates geometric considerations at the cost of being mathematically more involved. Furthermore, we propose a structured, systematic method to derive bounds capturing the dependence between the algorithm and an individual datum, and between the algorithm and subsets of the training data, conditioned on knowing the rest of the data. These types of bounds provide deeper insights, as we demonstrate by applying them to derive generalization error bounds for the stochastic gradient Langevin dynamics algorithm.      
    • PAC-Bayesian guarantees. These bounds measure the performance level with high probability. Here, the dependence between the algorithm and the data is often measured by the relative entropy. We establish connections between the Seeger--Langford and Catoni's bounds, revealing that that the former is optimized by the Gibbs posterior. Additionally, we introduce novel, tighter bounds for various types of loss functions, including those with a bounded range, cumulant generating function, moment, or variance. To achieve this, we introduce a new technique to optimize parameters in probabilistic statements.

    We also study the limitations of these approaches. We present a counter-example where most of the existing (relative entropy-based) information-theoretic bounds fail, and where traditional approaches do not. Finally, we explore the relationship between privacy and generalization. We show that algorithms with a bounded maximal leakage generalize. Moreover, for discrete data, we derive new bounds for differentially private algorithms that vanish as the number of samples increases, thus guaranteeing their generalization even with a constant privacy parameter. This is in contrast with previous bounds in the literature, that require the privacy parameter to decrease with the number of samples to ensure generalization.

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  • Public defence: 2024-04-24 09:30 FA32, Stockholm
    Wang, Wanhong
    KTH, School of Engineering Sciences (SCI), Physics, Nuclear Power Safety.
    Development and Application of Uncertainty Analysis Approaches for MELCOR Simulations of Severe Accidents2024Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The contemporary needs in advancing safety analysis methods and the increasing stringency in light water reactor (LWR) safety in the post-Fukushima era require more advanced and systematical approaches for severe accident analyses. The best estimate plus uncertainty (BEPU) methods are among such approaches and have been widely used for deterministic safety analysis (DSA) of design basis accidents (DBAs). However, the BEPU analyses of severe accidents (SAs) are not straightforward due to the complexity of SA phenomena and the specialties of SA simulation tools. It is therefore necessary to develop BEPU approaches for severe accidents.  

    This thesis work starts from an application of the conventional BEPU approach using various uncertainty quantification (UQ) methods of 95/95 tolerance limits to MELCOR simulations of severe accidents, with the aim to identify their capabilities in MELCOR simulations of severe accidents. Both parametric and nonparametric UQ methods, including goodness-of-fit test, Wilks’ methods, Baren and Hall’s linear interpolation and Hutson fractional statistics, are applied to postulated severe accident scenarios in a Nordic boiling water reactor (BWR). It is found that (i) a small sample size or a low order in these UQ methods tends to cause conservative estimates, and (ii) a large sample size has many unsuccessful MELCOR calculation cases and fixing of the cases incurs an explosive computational cost. To solve this problem, two alternative approaches are supposed to be developed in the next step.

    The first alternative approach is to develop a bootstrapped artificial neural network (ANN) model to be employed in UQ; and the second alternative approach is to couple deterministic sampling (DS) methods with a fixed/dynamic coverage factor. The first alternative approach overcomes the problem in the conventional BEPU approach, i.e. the explosive computation cost due to fixing many crashed MELCOR cases otherwise it ruins randomness of samples. The idea behind this approach is to use surrogate models (SMs) developed from successful MELCOR calculations to predict the relation between major uncertain inputs and outputs. As a result, an UQ with numerically equivalent estimate of 95/95 tolerance limits can be done. The approach is applied to a severe accident scenario due to station blackout (SBO) in a Nordic BWR and results are compared with those of the conventional approach. The second approach is proposed for realistic estimates with reduced computational costs. Its theoretical basis is that DS methods can use far fewer samples to produce approximately convergent estimates of the statistical moments of outputs (figures of merits). By introducing a fixed or dynamic coverage factor, the information on the first two statistical moments can be extended to 95th percentiles or so-called numerically equivalent estimates of 95/95 tolerance limits. The second approach is applied to a severe accident scenario of SBO in a Swedish PWR and compared with the conventional approach.

    The comparative results show that the two alternative approaches work well in uncertainty quantification of MELCOR simulations of the postulated severe accident scenarios chosen. For instance, given the mass of H2 production and the timing of vessel failure as the figures of merit (FOMs), the first alternative approach predicts the 95/95 estimates similar to those of the conventional approach. Besides, a high order nonparametric method can be used in the bootstrapped ANN model for stable and realistic estimates, which is almost impossible for the conventional approach due to the requirement of numerous MELCOR calculations. For the second approach, a fixed coverage factor 1.65 should be used when the outputs (figures of merits) are symmetrically distributed like normal distribution. Otherwise, a dynamic coverage factor from a fitted beta distribution should be used to avoid unrealistic estimates when the outputs are strongly skewed. It is thus concluded that the two proposed alternative approaches have potentials to replace the conventional approach of uncertainty quantification for MELCOR simulations of severe accidents, in case of too high computational cost due to a large sample size or many unsuccessful MELCOR calculations incurred in the conventional approach.

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  • Public defence: 2024-04-26 10:00 F3, Stockholm
    Broms, Anna
    KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Numerical Analysis, NA.
    Accuracy, efficiency and robustness for rigid particle simulations in Stokes flow2024Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The thesis concerns simulation techniques for systems of nano- to micro-scaled rigid particles immersed in a viscous fluid, ubiquitous in nature and industry. With negligible fluid inertia, the set of PDEs known as the Stokes equations can be used to model the hydrodynamics. For a dynamic study, the PDEs have to be solved at any given instance of time, provided the particle configuration and any non-hydrodynamic interactions. The resulting particle velocities can then be used to update the particle coordinates, and the equations repeatedly solved anew. For any simulation result of a physical system to be reliable, it is crucial to control different error contributions, with two error types here particularly in focus: those related to solving the Stokes equations and those related to the update in time.

    The PDEs can be recast as boundary integral equations (BIEs) that hold on the particle surfaces. Hydrodynamic interactions are challenging: they are simultaneously long-ranged and expensive to resolve both in time and space for closely interacting particles. The latter is caused by strong lubrication forces resulting from bodies in relative motion. We approach two alternative and related techniques to BIEs that allow for more cost-effective simulations, namely the rigid multiblob method and the method of fundamental solutions. The former is a regularisation technique that allows for generally shaped particles in large systems, both with and without thermal fluctuations. We make two improvements: the basic error level is tied to the discretisation and set by solving a small optimisation problem off-line for each given particle shape, and the accuracy for closely interacting particles is improved by pair-corrections. With the method of fundamental solutions, we present a technique with linear or close to linear scaling in the number of particles, depending on if a so-called resistance or mobility problem is solved. For circles and spheres, the accuracy can be controlled to a target level independently of the particle separations. This is done by the introduction of a small set of image points for every pair of particles close to contact that well manage to represent lubrication forces.        

    In the model, particles can neither touch nor overlap, and our work on time-stepping is tied to the problem of contact avoiding. We develop a new strategy that guarantees contact free simulations in 3D, essential for studying the system of particles over long time spans.   

    Controlled accuracy in solutions to the Stokes equations can together with robust timestepping allow for simulations that can complement physical experiments of particle systems for a better understanding of their behaviour, to drive the development in fields such as materials science, biomedical engineering and environmental engineering.

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  • Public defence: 2024-04-26 13:00 Kollegiesalen, Brinellvägen 8, KTH Campus, Stockholm
    Allahvirdizadeh, Reza
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Structural Engineering and Bridges.
    Improving the Dynamic Design Philosophy of High-Speed Railway Bridges Using Reliability-Based Methods2024Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Modern railway infrastructures, especially bridges, are exposed to significant vibrations with potential safety implications. In this context, previous studies have shown the inconsistency and inadequacy of some conventional design methods necessitaing them to be improved. The assessment of safety inherently deals with uncertainties. Therefore, the current study is dedicated to this objective using reliability-based methods. Of the various possible failure modes, the investigations presented here are limited to running safety and passenger comfort. The investigation of these limit-states requires constructing complex computational models with train-track-bridge interaction capabilities. However, the application of these computationally intensive models in the context of structural reliability does not appear to be feasible. Simplifying the system, the vertical acceleration and the deflection of the bridge serve as implicit limit-state measures. Initially, using First Order Reliability Method (FORM) revealed limitations in the application of the current safety factor, resulting in inconsistent reliability indices. Therefore, probabilistic design curves are proposed, defining minimum required bridge mass and stiffness based on cross-section types, span configurations and train speeds. These results are obtained by formulating a FORM-based optimization. Subsequently, the results are used to investigate the sensitivity of the estimated failure probabilities with respect to the contributing basic random variables. Acknowledging the limitations of FORM, surrogate-assisted simulation-based reliability assessments were used for further investigations. A comparison of the performance of widely used regression-based surrogate models under an identical active learning scheme showed the superior performance of the Kriging method over the others. Within areliability-based design optimization framework, this Kriging model facilitates the generation of new probabilistic design curves. This is achieved by reformulating the conventional method to account for the dependency between design variables using the copula concept. In addition, the surrogate model aided in calibrating the safety factor associated with the vertical acceleration threshold, leading to a proposal of 1.38 as a new safety factor. Subsequently, the influence of soil-structure interaction on the estimated reliability indices is evaluated using an ensemble of classification-based surrogate models. Results highlighted its beneficial contribution in terms of increased damping for shorter spans, countered by adverse effects due to frequency shortening in longer bridges. Finally, the epistemic uncertainties arising from the limited knowledge of the vertical acceleration threshold are investigated. It is found that neglecting these uncertainties can lead to an overestimation of allowable train speeds by about 13%.

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  • Public defence: 2024-04-29 13:00 https://kth-se.zoom.us/j/68660447128, Stockholm
    Favero, Federico
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
    Light Rhythms: Exploring the Perceptual and Behavioural Effects of Daylight and Artificial Light Conditions in a Scandinavian Context2024Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    This compilation thesis collects multidisciplinary work on the study of the impact of light rhythms on perception and behaviour. The thesis was structured to answer and discuss the questions: “How does a person feel and behave inan illuminated space?” and “Do variable light conditions influence perception, appraisal and motion?”. In order to answer the questions, I applied methods from design, psychology and behavioural science, conducted literature reviews and performed two experimental studies. In response to the first question, the outcome of the five papers included in the thesis show that light and lighting rhythms elicit specific acute and long-term effects. These effects impact on these categories of aspects: visual and perceptual, appraisal and experience, behavioural and physiological. To structure and visualize these diverse aspects, I introduce the CLAPP framework: Context Light(ing) Action (behaviour), Perception, Person. The framework highlights the complex interplay between light, environment, and human response, by displaying features related to spatial and light rhythms, effects of light on mind and body, and personal features. The framework can provide structure and direction for education and research activities within the scope of Architectural Lighting Design. In response to the second research question, results from the experimental studies reveal that, even after eliminating view and sunlight, variable daylight conditions elicit better mood, higher pleasure, and influence motion, compared to artificial light conditions. The results of this thesis may contribute to achieving the UN sustainability goals, specifically to improve the well-being of the population (SDG3), to design a built-environment that is safe and resilient (SDG 11), and to promote the uses of affordable and clean energy (SDG 7). Building on the experience gained during this thesis work, I am confident that multidisciplinary collaboration will enable to integrate the diverse aspects included in the CLAPP framework, paving the way for the design of spaces that are both resilient and supportive of health.

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  • Public defence: 2024-04-30 10:00 F3 (Flodis), Stockholm
    Zha, Li
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Chemistry, Glycoscience. KTH, School of Biotechnology (BIO), Centres, Albanova VinnExcellence Center for Protein Technology, ProNova.
    Surface Engineering of Cellulose Nanofibers for Advanced Biocomposites2024Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Nanocellulose, originated from cellulose, the primary structural component of the cell walls of plants, has garnered significant attention for its excellent mechanical, optical, and barrier properties, as well as its renewable and sustainable nature. Various forms of nanocellulose, including cellulose nanocrystals and cellulose nanofibers (CNFs), are produced by breaking down lignocellulosic fibers into nanoscale dimensions, typically through mechanical or chemical processes. The large surface area and rich hydroxyl groups of CNFs are ideal for surface modifications, offering great versatility in the development of functional biocomposite materials. This thesis aims to design CNF-based composites with integrated multifunctionalities, including redispersibility, biocompatibility, mechanical robustness, wet integrity, as well as optical transparency, through surface engineering of cellulose nanofibers. The methodology involves strategically selecting CNFs, integrating CNFs with biopolymers, applying surface modifications, and implementing facile processing techniques. 

    In Paper I, inspiration from plant cell wall was drawn to customize the interaction between water and CNFs. By Incorporating mixed-linkage beta-glucan from barley, superior rehydration, redispersion, and recycling of dried CNFs have been achieved. This advancement holds the potential to enhance the transportation and processability of CNF-based materials.

    In Paper II, by leveraging the interaction between CNF and water, a facile material processing technique was introduced to fabricate CNF/regenerated silk fibroin (RSF) composites. This involved rehydration and swelling of TEMPO-oxidized CNF nanopaper structures with both random-oriented CNF and nematic-ordered CNF in the RSF solutions. Remarkably, the CNF/RSF composite films thus prepared exhibited exceptional mechanical properties in both dry conditions and in PBS, and demonstrated excellent biocompatibility when cultured with L929 fibroblast cell.

    In Paper III, CNF/alginate double-network composites were prepared to investigate the impact of interfibrillar interactions and the G/M ratio (guluronic acid/mannuronic acid) of alginates on mechanical performance. The composite incorporating TEMPO-oxidized CNF and alginate with higher mannuronic acid content and molecular weight, exhibited high Young’s modulus of 20.3 GPa and high tensile strength of 331 MPa. The interfacial calcium ion crosslinking between CNF and alginate played a pivotal role in improving these properties. Furthermore, this composite was successfully demonstrated as a barrier spray coating for banana, significantly reducing weight loss when stored under ambient conditions, suggesting its potential for applications in food packaging.

    In paper IV, carboxymethyl cellulose (CMC) was functionalized with quaternary ammonium salts, and subsequently used to modify the interface between holocellulose fibers network and acrylic resin. Strong and transparent composites were successfully fabricated, without the need for organic solvents or harsh chemicals that are often used during the covalent surface modification of cellulose. The hydrophobic functionalized CMCs facilitated homogeneous resin impregnation in cellulose fiber network, producing composites with enhanced interfacial adhesion strength, increased optical transparency and mechanical strength.

  • Public defence: 2024-05-03 09:00 F3, Stockholm
    Asta, Nadia
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Fibre- and Polymer Technology, Fibre Technology.
    Fundamentals of Interactions between Cellulose Materials and its Implications on Properties of Fibrous Networks2024Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Fundamental research plays a pivotal role in the development of sustainable solutions that benefit both our environment and everyday lives. Cellulose, as an abundant and renewable resource, holds immense potential for sustainable applications. However, navigating the complexities of molecular and supramolecular structure of cellulose poses significant challenges in harnessing its full potential. By delving into fundamental research, we aim to uncover the underlying mechanisms governing cellulose interactions, paving the way for innovative advancements in sustainable material development.This thesis uncovers the intricate relationship between fundamental research and applied methodologies by showing how molecular contact and structure at the interface of cellulose-rich materials will control the development of the macroscopic mechanical properties of networks from cellulose-rich fibres. The study encompasses various facets, ranging from the development of model materials for studying interfacial interactions to the preparation of fibrous networks with tailored properties.In the initial part of the work the research delves into the development of model materials to investigate interactions at smooth interfaces of regenerated cellulose. The study reveals the crucial role of the making and breaking of cellulose interface, or sometimes interphase, in the development of adhesive joints. Experimental findings demonstrate how chemical additives influence the interactions between cellulose surfaces, thereby modulating the structural and adhesive properties at the interface. Furthermore, by utilizing model materials, insights are gained into fibre-fibre interactions and the influence of surface treatments on network formation and mechanical performance. Lastly, the research focused on investigating the preparation of fibrous networks at different densities and amount of adsorbed additives, providing a comprehensive understanding of how network density and composition affect mechanical properties of the networks.This work not only exemplifies a synergistic approach, where fundamental insights into molecular contacts and interface structures are translated into practical applications for enhancing macroscopic properties but also highlights the importance of integrating fundamental and applied methodologies in molecular engineering, offering novel strategies for advancing sustainable paper production practices and contributing to the attainment of sustainable development goals.

  • Public defence: 2024-05-03 10:00 Air&Fire, Solna
    Gnann, Christian
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science.
    Finding order in chaos: Dissecting single-cell heterogeneity in space and time2024Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The cell is the smallest unit of life and contains DNA, RNA, proteins and a variety of other macromolecules. In recent years, technological advances in the field of single cell biology have revealed a staggering amount of phenotypic heterogeneity between cells in a population, which were previously considered homogenous. Previous work has largely been focused on studies of RNA. As proteins however are the ultimate effectors of genetic information, this thesis aims to provide a protein-centered view on cellular heterogeneity, particularly focusing on cell cycle and cellular metabolism.

    Most of my work has been performed within the framework of the Human Protein Atlas project. In the context of this project, we mapped the spatial distribution of more than 13.000 human proteins with subcellular resolution and found that around a quarter of all human proteins exhibit protein expression heterogeneity.

    In Paper I, we hypothesized that a majority of the observed cellular heterogeneity can be explained by differences in cell cycle progression. Therefore, we generated a map of proteomic and transcriptomic heterogeneity at subcellular resolution, which we precisely aligned to the cell cycle position of individual cells. This approach allowed us to identify hundreds of previously unknown cell cycle-related proteins. With sustained proliferative signaling representing a hallmark of cancer, novel cell-cycle proteins could serve as potential new drug targets against cancer. We further show that a large part of cell cycle dependent proteome variability is not established by transcriptomic cycling. This suggests that post-translational modifications are a major contributor to the regulation of cell cycle dependent protein level changes. Therefore, in Paper II, we carried out a deep phosphoproteome mass spectrometry profiling of the same cellular model as in Paper I and identified almost 5,000 cell cycle dependent phosphosites on over 2,000 proteins. The unprecedented scale of our phosphoproteomic data allows us to link cell cycle dependent protein expression dynamics to phosphorylation events. Furthermore, we identify a large set of proteins with stable expression levels and fluctuating phosphorylation patterns along cell cycle progression that likely alters protein function.

    Despite identifying hundreds of novel cell cycle dependent proteins in paper I, we observed that the majority of heterogeneously expressed proteins display variable expression independent of cell cycle progression, among them a large number of metabolic enzymes. Thus, we sought to describe the extent of subcellular metabolic complexity in human cells and tissues in Paper III. While we confirm metabolic compartmentalization in our dataset, we show that around 50% of metabolic enzymes localize to multiple cellular compartments. By integrating public protein-protein interaction data with our subcellular location information, we identify several enzymes with novel compartment-specific functions. Additionally, we observe a strongly elevated number of heterogeneously expressed enzymes compared to the background of the human proteome that is largely independent of cell cycle progression. We show that this heterogeneity can be manifested in the lineage of a single cell and is conserved in situ. To conclude, we suggest that the extensive metabolic heterogeneity can establish functional metabolic states in a population of human cells.

    Finally, in Paper IV, we assessed the heterogeneity of the mitochondrial proteome as they are metabolic powerhouses containing an elevated number of cell cycle independent variably expressed proteins. In this study, we correlated the variable expression of over 400 mitochondrial proteins to the expression of rate limiting enzymes in important mitochondrial pathways; such as the TCA cycle and ROS metabolism. We show that enzymes in the same pathways often correlate in their expression, indicating that their expression variability may contribute to the establishment of metabolic states.

    Altogether, the thesis illuminates the spatiotemporal complexity of the human proteome established by protein multilocalization and expression heterogeneity as fundamental non-genetic means of functional cell regulation.

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    Finding order in chaos - Dissecting single-cell heterogeneity in space and time
  • Public defence: 2024-05-03 10:00 Kollegiesalen, Brinellvägen 8, Stockholm
    Mohammadi, Mohammad
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Soil and Rock Mechanics.
    Risk Management in Tunneling Projects: Estimation and Planning2024Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Cost overruns and schedule delays are frequently observed occurrences in the construction of transport infrastructure projects. Such phenomena lead to the mismanagement of significant amounts of both public and private resources.An examination of the literature reveals that uncertainty stands out as one of the potential primary causes of cost overruns and schedule delays. To address the impact of uncertainty on time and cost estimations in transport infrastructure projects, probabilistic approaches can be employed. 

    In this doctoral thesis, first a conceptual risk model has been formulated specifically for the purpose of enhancing time and cost estimations in tunneling projects. This risk model serves as a tool to scrutinize and contrast existing probabilistic time and cost estimation models for tunnel projects, aiming to identify potential areas for improvement. Furthermore, the conceptual model is utilized to delve into the factors influencing the accuracy of subjective assessments regarding the input parameters in time estimation models. It also explores methods for incorporating the role of tunneling phases into the subjective assessment of these input parameters.

    Then, enhancements and updates are introduced to the existingKTH model for time and cost estimation in tunneling projects. This model primarily targets three main sources of uncertainty: variability in construction performance, geological uncertainties, and the potential incidence of disruptive events. The analysis and improvements related to modelling of construction performance involve three sequential steps. In the first step, the construction process is modeled using the work breakdown structure (WBS), enabling a more realistic assessment of tunneling time. Subsequently, in the second step, PERT distributions are employed to model the uncertainty in the duration of unit activities, compared to the commonly used triangular distributions. The third step involves a detailed examination of a real tunnelling project's data to identify components contributing to construction performance variability for unit activities. This analysis pinpoints three main components: typical performance variability, minor performance delays, and minor machinery delays. These components are integrated into the KTH model, resulting in its further update concerning construction performance variability. 

    A novel approach is introduced into the KTH model by leveraging the Metropolis-Hastings (MH) algorithm within the framework of Markov Chain Monte Carlo (MCMC) simulation to address geological uncertainties along the tunnel route. This method facilitates round-by-round simulation of the tunneling process and allows the model to accommodate uncertainty in the critical path for tunneling projects involving multiple headings. These enhancements aim to improve decision-making processes and mitigate risks associated with schedule delays and cost overruns. Additionally, the magnitude of disruptive events are now modeled as stochastic variables, an improvement on the original version of the KTH model.

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  • Public defence: 2024-05-03 13:00 F3, Lindstedtsvägen 26, KTH Campus, Stockholm
    Evens, Siegfried
    KTH, School of Architecture and the Built Environment (ABE), Philosophy and History, History of Science, Technology and Environment.
    Streams, Steams, and Steels: A Transnational History of Risk Regulation in Nuclear Power Plants (1850–1985)2024Doctoral thesis, monograph (Other academic)
    Abstract [en]

    Water is essential to produce nuclear energy and prevent nuclear disasters. As light water reactors are increasingly seen as a solution to achieving a sustainable energy transition and battling the climate crisis, it is more important than ever to investigate the risks of using water for nuclear power production. However, the reactor technologies that manage all that water and steam – pressure vessels, steam generators, pipes, valves, and pumps – have not received much attention from historians, STS scholars, and risk sociologists. Therefore, this dissertation aims to study the risk regulation of these crucial reactor components and materials by national and international actors from a historical perspective.

    Relying on archival sources from the US, France, Sweden, and multiple international organisations, as well as on interviews, this dissertation aims to write a new, longue durée history of nuclear safety, going back to the origins of water and steam risk management in the nineteenth century. Such a historical perspective on nuclear risk regulation reveals two important insights. Firstly, in the 1950s and 1960s, the usage of water and steam technologies in nuclear reactors revealed new types of risks. These ‘ambi-nuclear risks’ are a hybrid of older steam risks, such as leaks, breaks, and explosions, and new risks of radiation and contamination. Secondly, between the 1950s and 1980s, new regimes were created in the US, France, and Sweden to regulate these risks. Initially, during the 1950s, non-nuclear steam regulations were applied directly to the first nuclear power plants. Yet, as power plants increased in size, accidents occurred, and nuclear technologies became increasingly controversial, ‘ambi-nuclear risk regimes’ were created to adapt or ‘nuclearise’ the older regulations. They included new safety measures and methodologies that were directed toward preventing radiation releases, but at the same time they mobilised older technologies, institutions, knowledges, and ideas related to thermal hydraulics and metallurgy. Ambi-nuclear risk regimes were shaped by a wide variety of historical actors through negotiating boundaries between ‘nuclear’ and ‘non-nuclear’ knowledges, components, risks, and regulations. Private or semi-private engineering associations played a particularly vital role in this.

    This thesis thus shows how nuclear safety as we know it today became nuclear as the result of a transnational long-term process that was greatly determined by much older non-nuclear water and steam risks. The results of this dissertation contribute to ongoing scholarly debates on risk, nuclear technologies, and water in fields like History of Technology, Environmental3History, STS, and Risk Sociology. Most importantly, the thesis expands the time frame in which nuclear risk has traditionally been studied. It challenges dominant conceptions of nuclear power as innovative or exceptional, instead connecting questions of nuclear risk to longer historical developments in water management and industrialisation. This demonstrates the importance of historical contingency for understanding risk and preventing (nuclear) disasters.

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    Evens Dissertation
  • Public defence: 2024-05-07 14:00 F3
    Correnty, Siobhán
    KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Numerical Analysis, NA. KTH, Centres, SeRC - Swedish e-Science Research Centre.
    Numerical methods for parameterized linear systems2024Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Solving linear systems of equations is a fundamental problem in engineering. Moreover, applications involving the solution to linear systems arise in the social sciences, business, and economics. Specifically, the research conducted in this dissertation explores solutions to linear systems where the system matrix depends nonlinearly on a parameter. The parameter can be a scalar or a vector, and a change in the parameter results in a change in the solution. Such a setting arises in the study of partial differential equations and time-delay systems, and we are interested in obtaining solutions corresponding to many values of the parameter simultaneously. The methods developed in this thesis can also be used to solve parameter estimation problems. Furthermore, software has been developed and is available online. 

    This thesis consists of four papers and presents both algorithms and theoretical analysis. In Paper A, a linearization based on an infinite Taylor series expansion is considered. Specifically, the linearized system is a shifted parameterized system, and the parameter is a scalar. The GMRES method is used to solve the systems corresponding to many values of the parameter, and only one Krylov subspace basis matrix is required. Convergence analysis is based on solutions to a nonlinear eigenvalue problem and the magnitude of the parameter. Notably, the algorithm is carried out in a finite number of computations. 

    The approach in Paper B is based on a preconditioned linearized system solved using the inexact GMRES method. In this setting, the linearization incorporates all terms in an infinite Taylor series expansion, and the preconditioner is applied approximately using iterative methods. Solutions corresponding to many values of the scalar parameter are generated from one subspace, and this is done in a finite number of linear algebra operations. Theoretical analysis, based on the error in the application of the preconditioner and the magnitude of the parameter, leads to a bound on the residual. 

    Paper C proposes a short recurrence Krylov subspace method for solving linear systems that depend on a scalar parameter. In particular, a Chebyshev approximation is used to construct a linearization, and the linearized system is solved in a Bi-CG setting. Additionally, shift-and-invert preconditioning leads to fast convergence of the Krylov method for many different values of the parameter. An inexact variant of the method is also derived and analyzed. 

    In Paper D, a reduced order model is constructed from snapshots to solve parameterized linear systems. Specifically, the parameter is a vector of dimension 2, and the sampling is performed on a sparse grid using the method proposed in Paper C. A tensor decomposition is utilized to build the model. Approaches of this kind are not always successful, and it is not known a priori if a decomposition will converge on a given set of snapshots. This work offers a novel way to generate a new set of snapshots in the same parameter space, to be used if the decomposition does not converge, with little extra computation. 

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  • Public defence: 2024-05-15 10:00 https://kth-se.zoom.us/j/67779557414, Stockholm
    Khodadadi, Abolfazl
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems. KTH Royal Institute of Technology.
    Electricity Market Design Strategies for Hydro-dominated Power Systems: Exploring Optimal Bidding, Planning, and Strategic Operation through Various Market Design Strategies2024Doctoral thesis, monograph (Other academic)
    Abstract [en]

    The existing wholesale power markets in Nordic countries play a vital role in ensuring the planned balance between supply and demand. However, these markets do not guarantee real-time operational security of the power system. This responsibility falls on the transmission system operator (TSO), who balances consumption and generation in real-time to maintain a secure state.

    To address these issues, a series of research studies have been performed in this thesis to delve into the intricacies of Nordic balancing markets and propose strategies to enhance their efficiency and effectiveness. These studies have been conducted around the hydropower units as the main generation sources in the Nordic electricity markets. These studies recognize the potential benefits of versatile balancing markets and increased trade of flexible resources with Continental Europe. 

    Additionally, the research results shed light on the optimal bidding strategies for hydropower plants (HPPs) in the day-ahead energy and manual frequency restoration reserve (mFRR) markets. HPPs play a crucial role as a flexible energy source, and their participation in these markets requires careful planning and decision-making. The studies consider various factors such as market rules, mFRR capacity market, future electricity prices, and the impact of active-time duration of balancing energy market offers on revenue generation. This inclusion provides a more realistic revenue portfolio for the operators based on the possibility of not being dispatched in the balancing market. 

    Furthermore, the research explores the concept of flexible stochastic scheduling strategies in hydropower-dominated energy markets. By considering day-ahead energy markets, mFRR markets, and the interaction between different market setups. These strategies provide the necessary flexibility for both the planning and operational stages. The aim is to maximize the profits of the hydropower units while addressing the opportunity cost of saving water and meeting the mFRR capacity requirements imposed by the TSO. Participation in new market setups is an increasingly interesting framework for the operator after the recent introduction of those markets and the results of this section help them to form more profitable decision-making frameworks for their assets. 

    Moreover, the optimal strategic portfolio assessment of HPPs in a multi-settlement market is discussed. Recognizing the increasing electricity prices and the growing penetration of renewable energy resources, these studies leverage bilevel programming problems to model the strategic behavior of HPPs in day-ahead and frequency containment reserve markets. The proposed approaches aim to enhance decision-making processes, promote market efficiency, and enable effective asset management in a dynamic and evolving energy landscape to make more informed multi-market trading decisions. 

    Also, the research examines the dimensioning of frequency restoration reserves in a multi-area power system, specifically focusing on the Nordic case study. By adopting a sequential dimensioning methodology and employing chance-constrained optimization, the studies allocate reserves based on system needs, optimize line flows, and reduce total reserve requirements. The results highlight the potential for sharing reserves among bidding zones in the Nordic synchronous area, contributing to a more efficient and coordinated power system operation.

    Lastly, a thorough investigation has been performed to assess the effectiveness of the current contract-for-difference contracts as the main support schemes for the development of new renewable energy assets. Case studies have been conducted to demonstrate quantitatively the pros and cons of different proposals and provide new hints for policy-makers about their future decisions. 

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  • Public defence: 2024-05-24 13:00 E3, Stockholm
    Lindberg, Aleksandra
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Chemical Engineering, Applied Electrochemistry.
    Selectivity and gas composition in electrochemical systems by mass spectrometry2024Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    This doctoral thesis presents experimental studies of gaseous products of two electrochemical systems: the chlorate process and the nickel-metal hydride (NiMH) battery, employing mass spectrometry.

    The cathodic efficiency for the hydrogen evolution reaction (HER) of the chlorate process was investigated by employing ex-situ synthesized MnOx electrodes. Without the addition of toxic chromium (VI), used today in industry, high cathodic efficiency was achieved. The effect of different annealing temperatures in the electrode preparation on HER efficiency was examined. The addition of 1000 times lower concentrations of chromium (VI) than used in the industry today, together with in-situ added molybdate,showed promising results in keeping high cathodic efficiency and selectivity towards HER. The evolution of oxygen decreases anodic efficiency and also presents a safety risk due to simultaneously proceeding of HER in the undivided cell. The amount of produced oxygen by two types of electrodes TiRu and TiRuSnSb, was followed. Oxygen is produced by homogenous hypochlorite decomposition, heterogeneously by different electrode surface present in the electrolyte solution and anodically during the electrolysis i.e. electrochemically.

    Investigating gas composition in batteries presents a challenge due to the complexity of reactions leading to the gas evolution.Additionally, the gas consumption has a significant impact on the amount and constituents of the collected gases. The methodology for investigating gas composition of the NiMH battery without influencing the battery performance was established. Two technologies, sampler and microcapillary, gave reasonable and complementing results.

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  • Public defence: 2024-06-03 10:00 Atrium, Stockholm
    Sariyar, Sanem
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Spatiotemporal Profiling of Human Development Using Multiplexed Imaging2024Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Human development is complex and intricate, where the positions of cells, expression of key markers, and cell-cell interactions contribute to the development of various organs from different germ layers and the establishment of the body axis. Therefore, understanding human development within spatial and temporal aspects is crucial. Spatial and temporal aspects can be studiedthrough multiplexed imaging, which enables the assessment of multiple markers on the same tissue, offering critical insights into protein expressions in the cells and tissues. Within the scope of this thesis, we focused on the spatial and single-cell profiling of cell types during the first trimester of human development, both at the systemic and organ levels, using multiplexed imaging. Paper I of this thesis presents a spatial and single-cell map of the developing human lung in the first trimester. We used multiplexed imaging on post-conception week 6 to 13 lungs employing a 30-plex antibody panel and, as a result, analyzed nearly 1 million cells. We provide a spatially resolved cell type composition of the developing human lung, focusing on spatiotemporal changes in the cell types, such as immune cells, endothelial cells, lymphatic cells, and proliferative cell states. Key findings of the first paper are that the proliferation patterns in the epithelium reveal differences in the elongation of smaller and larger distal and proximal airways and the presence of some immune cells around arteries, highlighting location-function relationships. Additionally, this paper represents the first application of multiplexed imaging on the developing human lung. Paper II aimed to systematically investigate human development in whole embryos by focusing on cell types such as immune and endothelial cells. We analyzed human whole embryo tissues from week 3 to 5 using a 28-plex multiplexed antibody panel. A key finding of the paper is the appearance of liver immune cells as early as week 4 and differences in their marker expression profiles compared to the other immune cells. In Paper III, we proposed a simple and flexible open-source method for visualizing in situ expressions of hundreds of genes, which can be combined with other methods, such as multiplexed imaging. In Paper IV, we explored the spatial dynamics of the developing human heart at the cellular and subcellular levels. In conclusion, this thesis elucidates the spatiotemporal changes during the first trimester of human development by presenting spatial maps of developing organs and whole embryos at various stages. The objective is to illustrate the characteristics of a healthy state, contributing to a better understanding of abnormalities associated with congenital diseases.

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    Spatiotemporal Profiling of Human Development Using Multiplexed Imaging