Oxid uraničitý (UO2) je v současnosti nejčastěji používaným materiálem jakožto palivo v komerčních jaderných reaktorech. Největší nevýhodou UO2 je jeho velmi nízká tepelná vodivost, a protože se při štěpení UO2 v jaderném reaktoru vytváří velké množství tepla, vzniká v UO2 peletě velký teplotní gradient. Tento teplotní gradient způsobuje vznik velkého tepelného napětí uvnitř pelety, což následně vede k tvorbě trhlin. Tyto trhliny napomáhají k šíření štěpných plynů při vysoké míře vyhoření paliva. Tvorba trhlin a zvýšený vývin štěpného plynu posléze vede ke značnému snížení odolnosti jaderného paliva. Tato práce se zabývá problematikou zvyšování tepelné vodivosti jaderného paliva na modelu materiálu (CeO2). V této práci jsou studovány podobnosti chování CeO2 a UO2 při konvenčním slinováním a při „spark plasma sintering.“ Způsob jak zvýšit tepelnou vodivost použitý v této práci je včlenění vysoce tepelně vodivého materiálu, karbidu křemíku (SiC), do struktury CeO2 pelet. Od karbidu křemíku je očekáváno, že zvýší tok tepla z jádra pelety, a tím zvýší tepelnou vodivost CeO2. V této práci je také porovnávána podobnost chování SiC v CeO2 matrici s chováním SiC v UO2, které bylo popsáno v literatuře.

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<p>The research effort addressed important gaps in the modeling to simulate Urban Air Mobility (UAM) operations and couple optimization analyses for vehicle design, fleet allocations, and operational choices for next generation urban travel. Urban Air Mobility is expected to be a \$1 trillion dollar industry by 2040, but operators and designers have limited models and tools to estimate fleet performance, cost metrics, emissions performance, and profit for a given concept under future concepts of operations. A review of the literature reveals 14 modeling gaps related to infrastructure, operations, airspace, vehicles, and customers. In addition, the UAM industry requires better understanding of how operational choices may impact vehicle design and fleet allocations in a market with significant economic barriers and infrastructure needs. To address those needs, this effort proposed alternatives to address modeling challenges and develop studies to evaluate UAM vehicle concepts and concepts of operations in ways once not possible using the enhanced modeling tools. The research findings revealed that modeling coupled design/fleet and operational choices can affect daily profitability potential by 2-4\times\, for piloted and autonomous operations and affect the fleet size from between 12-50 vehicles across small, medium, and large metropolitan areas. The modeling capability provided by the improvements in UAM operations simulations and accessing vehicle and fleet metrics enables future studies to address UAM in a holistic manner. The increased capability could benefit the UAM community and inform future operations and concepts of operations in preparation for ubiquitous operations.</p>

Cyclist underreporting of lower severity and single cyclist collisions to police results in the underestimation of the societal costs of lower severity and single cyclist collisions [1], [2]. Prevention strategies for these types of collisions are becoming a popular area of research, and video-based approaches have obvious potential for these cases, allowing for detailed analyses of underreported lower severity and single cyclist falls. Video-based studies have been used to investigate site-specific cyclist safety issues such as railway crossings [3 ]. They have also been used for near-collision or near-miss incidents and Surrogate Measures of Safety (SMoS), e.g., [4]. A recent Irish study has identified the most common collision configurations and factors with the inclusion of unreported cases [5]. Findings indicate that falls involving interactions with light rail tram tracks are common in Dublin; they were the most common infrastructural collision partner in this study and a contributing factor in 23% of single cyclist collisions (ibid.), supplementing international findings [6], [7]. Furthermore, along with increasing popularity of cycling, many new light rail systems are being implemented across Europe as part of a broader move towards sustainable transport [8]. Accordingly, further investigation is required to avoid potential conflicts. Therefore, this study aims to use video-based assessment to correlate fall risk with trajectories and crossing angles. [From: Introductiojn]

The purpose of this study was to qualitatively examine the possible formation of surrogate families within Ugandan schools to provide a context for positive development experiences, especially for orphans who lack positive development opportunities provided by parents. The sample for this study consisted of 66 Ugandan Secondary School students from eight schools in the Mukono district of Uganda. This study found a potentially widespread family formation pattern between students and their teachers/coaches. More than 75% of students self-identified their teacher and/or coach as family. The results provide insight concerning why orphans and vulnerable children are forming surrogate families with staff members at school. Teachers and coaches were able to offer the students positive developmental assets and were therefore identified as family.

<p>The document describes the computational framework to optimize spring-driven Autoinjectors. It involves Bayesian Optimization for efficient and cost-effective design of Autoinjectors.</p>

Nowadays, earthquakes are one of the most catastrophic natural events that have a significant human, socio-economic and environmental impact. Besides, based on both observations of damage following recent major/moderate seismic events and numerical/experimental studies, it clearly emerges that critical non-structural components (NSCs) that are ubiquitous to most industrial facilities are particularly and even disproportionately vulnerable to those events. Nonetheless and despite their great importance, seismic provisions for industrial facilities and their process equipment are still based on the classical load-and-resistance factor design (LRFD) approach; a performance-based earthquake engineering (PBEE) approach should, instead, be preferred. Along this vein, in recent years, much research has been devoted to setting computational fragility frameworks for special-risk industrial components and structures. However, within a PBEE perspective, studies have clearly remarked: i) a lack of definition of performance objectives for NSCs; ii) the need for fully comprehensive testing campaigns data on coupling effects between main structures and NSCs. In this respect, this doctorate thesis introduces a computational framework for an efficient and accurate seismic state-dependent fragility analysis; it is based on a combination of data acquired from an extensive experimental shake table test campaign on a full-scale prototype industrial steel frame structure and the most recent surrogate-based UQ forward analysis advancements. Specifically, the framework is applied to a real-world application consisting of seismic shake table tests of a representative industrial multi-storey frame structure equipped with complex process components, carried out at the EUCENTRE facility in Italy, within the European SPIF project: Seismic Performance of Multi-Component Systems in Special Risk Industrial Facilities. The results of this experimental research campaign also aspire to improve the understanding of these complex systems and improve the knowledge of FE modelling techniques. The main goals aim to reduce the huge computational burden and to assess, as well, when the importance of coupling effects between NSCs and the main structure comes into play. Insights provided by innovative monitoring systems were then deployed to develop and validate numerical and analytical models. At the same time, the adoption of Der Kiureghian's stochastic site-based ground motion model (GMM) was deemed necessary to severely excite the process equipment and supplement the scarcity of real records with a specific frequency content capable of enhancing coupling effects. Finally, to assess the seismic risk of NSCs of those special facilities, this thesis introduces state-dependent fragility curves that consider the accumulation of damage effects due to sequential seismic events. To this end, the computational burden was alleviated by adopting polynomial chaos expansion (PCE) surrogate models. More precisely, the dimensionality of a seismic input random vector has been reduced by performing the principal component analysis (PCA) on the experimental realizations. Successively, by bootstrapping on the experimental design, separate PCE coefficients have been determined, yielding a full response sample at each point. Eventually, empirical state-dependent fragility curves were derived.

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Most statistical methods to design and analyze randomized controlled trials with time-to-event data, and synthesize their results in meta-analyses, use the hazard ratio (HR) as the measure of treatment effect. However, the HR relies on the proportional hazard assumption which is often violated, especially in cancer trials. In addition, the HR might be challenging to interpret and is frequently misinterpreted as a risk ratio (RR). In meta-analysis, conventional methods ignore that HRs are estimated over different time supports when the component trials have different follow-up durations. These issues also pertain to advanced statistical methods, such as network meta-analysis and surrogate endpoints validation. Novel methods that rely on the difference in restricted mean survival times (RMST) would help addressing these issues. In this dissertation, I first developed a Bayesian network meta-analysis model using the difference in RMST. This model synthesizes all the available evidence from multiple time points and treatment comparisons simultaneously through within-study covariance and between-study covariance for the differences in RMST. I proposed an estimator of the within-study covariance and estimated the model under the Bayesian framework. The simulation studies showed adequate performance in terms of mean bias and mean squared error. I illustrated the model on a network of randomized trials of second-line treatments of advanced non-small-cell lung cancer. Second, I introduced a novel two-stage meta-analytical model to evaluate trial-level surrogacy. I measured trial-level surrogacy by the coefficient of determination at multiple time points based on the differences in RMST. The model borrows strength across data available at multiple time points and enables assessing how the strength of surrogacy changes over time. Simulation studies showed that the estimates of coefficients of determination are unbiased and have high precision in almost all of the scenarios we examined. I demonstrated my model in two individual patient data meta-analyses in gastric cancer. Both methods, for network meta-analysis and surrogacy evaluation, have the advantage of not involving extrapolation beyond the observed time support in component trials and of not relying on the proportional hazard assumption. Finally, motivated by the common misinterpretation of the HR as a RR, I investigated the theoretical relationship between the HR and the RR and compared empirically the treatment effects measured by the HR and the RR in a large sample of oncology RCTs. When there is evidence of superiority for experimental group, misinterpreting the HR as the RR leads to overestimating the benefits by about 20%. / 2026-02-08T00:00:00Z

Nature-based solutions (NBS) are promising strategies for protecting vulnerable coasts in the context of climate change, utilizing the coastal protection capabilities of natural ecosystems for engineering applications. The ability of coastal marsh vegetation to attenuate wave energy and prevent coastal erosion has been acknowledged for decades, however, consideration for their use in coastal protection strategies is presently limited, particularly in Canada due to a lack of engineering guidelines and limited available research considering region-specific variables. Physical modelling presents a useful tool for investigating the coastal protection function provided by marsh vegetation in a controlled, repeatable environment, which can ultimately inform the design of nature-based coastal protection strategies. To date, such studies have investigated the influence of plant biophysical parameters (stem flexibility, width, and height) and hydrodynamic conditions (wave height, wave period, and plant submergence) on wave attenuation. These studies have used either live vegetation, requiring full-scale wave testing, or surrogate vegetation, which allows simplified testing at either full- or reduced-scale. Overall, live vegetation studies have been limited in the variety of saltmarsh plants considered, with few studies considering plant species native to the Canadian coastline. Several physical modelling studies have been performed using surrogate plants, however, methods of surrogate development for flexible vegetation or reduced-scale testing are not yet well developed. This thesis aims to address knowledge gaps pertaining to the use of marsh vegetation in coastal protection strategies, particularly through the development of experimental methods with both live and surrogate plants. A full-scale flume study with live vegetation was performed to develop fundamental knowledge of wave-vegetation interactions for Spartina alterniflora and Spartina patens, two salt marsh species native to Canada’s Atlantic coast. S. alterniflora was observed to demonstrate a resistance strategy in response to hydrodynamic forcing, versus the avoidance strategy of S. patens, supporting complementary functioning of the two species if utilized together in coastal protection schemes. Observations of plant properties and stem bending from live plant tests were subsequently applied in the development of a small-scale flume study, which examined wave attenuation associated with a downscaled S. alterniflora meadow in the configuration of a “living dyke” structure. Wave damping induced by surrogate vegetation was observed to be minimal for the tested wave conditions (0.073 m < Hm0 < 0.225 m, 2.0 < Tp < 3.2 s, 1:4 scale) and beach slope (1V:20H), with wave height evolution dominated by wave shoaling and breaking. Several methods were considered for modelling the S. alterniflora meadow at reduced scale, and results demonstrated a sensitivity to surrogate diameter but not flexibility. The development of robust experimental methods for investigating the performance of nature-based coastal infrastructure is essential for the establishment of appropriate design conditions. The scale series approach of this thesis supports such methodological advancements and is expected to make preliminary contributions to design guidance on coastal marsh-based NBS and provide critical direction for future studies.