The aim of this investigation was to determine the applicability and weaknesses of the regional distribution model SimpleBox and to make proposals for improvement. The validation was performed using a scheme of which the main aspects are the division into internal and external validation. With its default values, the regional distribution model represents a generic region, and it is connected with a model which estimates indirect emissions from sewage treatment plants. The examination was carried out using a set of sample substances, the characteristics of which cover a wide range of different physico-chemical properties, use patterns and emissions. These substances were employed in order to enable us to make common statements on the model´s applicability. Altogether, the model complies with its designated purpose to calculate regional background concentrations. A scrutiny of theory did not show serious errors or defects. Regarding sensitivity, it could be shown that the model contains only few parameters with a negligible influence on the results. The comparison with measured results showed a good agreement in many cases. The highest deviations occur if the preliminary estimations of emissions, degradation rates and partition coefficients deliver unrealistic values. Altering the regional default parameters has a lower influence on the modelled results than replacing unrealistic substance properties by better ones. Generally, the model employed is a reasonable compromise between complexity and simplification. For the sewage treatment model, it could be shown that its influence on the predicted concentration is very low and a much simpler model fulfils its purpose in a similar way. It is proposed to improve the model in several ways, e.g. by alternative estimations functions for partition coefficients. But the main focus for future improvements should be on the amelioration of release estimations and substance characteristics.

La croissance en début de cycle des grandes cultures est principalement influencée par la température et la teneur en eau du sol. Nous avons développé un modèle capable de prédire ces variables grâce à l’utilisation de données climatiques largement disponibles. Des analyses de la sensibilité du modèle nous ont permis d’identifier les composants qui contribuent à son incertitude. Après calibration, une erreur moyenne relative de moins de 10 % est constatée pour la température et la teneur en eau à 30 cm de profondeur.Dans des conditions de semis standard en Suisse, l’émergence du maïs a été mieux prédite en utilisant notre température de sol simulée plutôt que la température de l’air, plus couramment utilisée. Ce travail est une application d’un modèle biophysique complexe à un problème agronomique. Les résultats participeront à l’optimisation de l’effort de sélection des variétés tolérantes au froid. Deux pistes de recherche peuvent être considérées pour des futurs travaux: une meilleure modélisation de l’évaporation et une décomposition de l’émergence. / The beginning of crop growth is influenced by soil temperature and water content near the surface. We have developed a model that predicts the local temperature and water content surrounding the seed using easily available meteorological data. Our global sensitivity analysis helped us identify the components of the model with the largest contribution to the output uncertainty. After calibration, the model showed less than 10 % relative error for temperature and water content at 30 cm. In standard sowing conditions in north-western Switzerland, the emergence was better predicted when using our simulated seed bed temperature than air temperature, the classical proxy variable. Combining the emergence model with soil temperature simulation, an accurate prediction of emergence was achieved. This work is an example of applying complex biophysics model for understanding an agronomic problem. The results of this work will participate in optimising breeding efforts for cold-tolerant crop varieties. Future investigations should consider a finer modelling of processes for evaporation and emergence.

The main aim of this dissertation was to develop a computational tool capable of evaluating the influence of aerodynamics on the handling of a vehicle. The methodology it uses is based on the simulation of driving manoeuvres with a single-track model of a vehicle, which was composed with an emphasis on minimizing the amount of necessary input parameters. This simple model, which allows the assessment of the influence of aerodynamics on vehicle dynamic and static driveability, therefore doesn’t require large amount of input data, which makes the acquirement of relevant values easier. The computational model was validated by extensive measurements of two driving manoeuvres defined by ISO norms (step steer input and steady state cornering). As a consequence of unsatisfactory initial validation results, the differences between measurements and simulations were analysed, which led to gradual enhancements of the model with additional inputs to achieve better accuracy of simulations. The final part of the thesis deals with the comparison of influences of individual aerodynamic parameters on vehicle handling and the assessment of overall significance of aerodynamics compared to other factors which were taken into account (tires, mass properties, steering etc.). This thesis was realized in close cooperation with Škoda-Auto.

Med den nuvarande situationen med ökade oroligheter i Europa, bristande elproduktion och en utveckling mot mer elektrifierade samhällen så har ett behov för hållbara energikällor uppstått. Många länder har börjat satsa på små modulära reaktorer (SMR) istället för storskaliga kärnkraftverk då de kan serietillverkas och är enkla att bygga vilket gör dem kostnadseffektiva. Denna studie fokuserade på var den mest optimala placeringen av SMR är inom elområde 4 om man bortser från 17 kap 6a§ miljöbalken. Elområde 4 valdes då det är det elområdet som producerar allra minst och har störst underskott av el. Detta gjordes med hjälp av en multikriterieanalys (MKA) och en efterföljande känslighetsanalys med totalt sex restriktionskriterier och nio faktorer med anvisningar hämtade från svensk lagstiftning, tidigare studier och internationella atomenergiorganet (IAEA). För att bedöma placeringen genomfördes en viktsättning med hjälp av intervjuer och enkäter med fyra olika personer med olika expertisområden inom kärnkraft. För att relatera faktorernas vikter till varandra användes Analytisk Hierarki process (AHP)-metoden vid skapandet av den genomsnittliga viktsättningen. En MKA-karta gjordes för att ta reda på vart den mest optimala platsen är utifrån den genomsnittliga viktsättningen samt en egen karta för de olika experternas egna viktsättningar. Det följdes upp av en känslighetsanalys med en faktor i taget (OAT) metoden och genom att eliminera en faktor i taget för att avgöra ifall den mest optimala platsen ändras och procentuellt hur mycket som arean ändras mellan de olika modellerna. Resultatet visar att den mest optimala platsen att placera en SMR är runtom Barsebäck, där det har stått ett storskaligt kärnkraftverk sedan tidigare. Man kan dra slutsatsen att känslighetsanalysen är robust och att den inte påverkas mycket av förändringar. / With the current situation of increased tension in Europe, inadequate electricity production, and a move towards more electrified societies, there has arisen a need for sustainable energy sources. Many countries have started investing in small modular reactors (SMR) instead of large-scale nuclear power plants as they can be mass-produced and are easy to build, making them cost-effective. This study focused on the most optimal location for SMRs within the fourth electrical bidding zone, disregarding section 17-chapter 6a§ of the Swedish Environmental Code. Bidding zone four was chosen as it produces the least amount of electricity and has the largest deficit. This was done using a multicriteria analysis (MCA) and a subsequent sensitivity analysis with a total of six restriction criteria and nine factors considering guidelines taken from Swedish legislation, previous studies on the subject, and the International Atomic Energy Agency (IAEA). To evaluate the placement interviews and questionnaires with four different people with different areas of expertise in nuclear power were carried out as a basis for the average weighting. The Analytic Hierarchy process (AHP) where used to evaluate the factors relative weights to each other. An average MCA map was made to determine the most optimal location based on the average weighting and a separate map for the different experts' own weightings. This was followed by a sensitivity analysis using one factor at a time (OAT) method, and by eliminating a factor to determine how the most optimal location changes, and the percentage of how much the area changes between the different models. The results show that the most optimal site to place an SMR is around Barsebäck where there was a large-scale nuclear power plant previously. One can conclude that the sensitivity analysis is robust and is not significantly impacted by changes.

[pt] Este trabalho propõe uma metodologia para a otimização de forma de estruturas geometricamente não-lineares. O objetivo desta metodologia é evitar os problemas de instabilidade apresentados por estruturas otimizadas de acordo com a formulação clássica. Ela foi implementada para problemas bidimensionais e os resultados obtidos na otimização de diferentes estruturas demonstraram o seu sucesso. Utilizando-se conceitos de modelagem geométrica, a forma da estrutura é defini-da através das curvas de seu contorno. Assim, a representação paramétrica de curvas e a definição destas em função de um conjunto de pontos de interpolação (pontos-chave) são discutidas detalhadamente. A ênfase é dada à interpolação através de B-splines,devido a sua grande flexibilidade. O problema de otimização é definido com base no modelo geométrico e as variáveis de projeto são as coordenadas dos pontos-chave. A simetria da estrutura é garantida através da ligação de variáveis. A estrutura é analisada através de elementos isoparametricos planos. Assim, antes de realizar a análise, é necessário discretizar a estrutura em um conjunto de elementos finitos. Para realizar esta tarefa foram implementados diferentes algoritmos de geração de malhas, tanto estruturadas quanto não-estruturadas. O método de Newton-Raphson é utilizado pa- ra determinar a configuração de equilíbrio e diferentes métodos podem ser aplicados para determinar os pontos críticos. Devido aos problemas de convergência apresentados pelos métodos diretos para a determinação dos pontos crticos, um método semi-direto foi desenvolvido neste trabalho. Os resultados obtidos na análise de diferentes exemplos mostraram a adequação dos elementos finitos e dos métodos numéricos implementados. Os algoritmos de programação matemática utilizados neste trabalho precisam dos gradientes da função objetivo e das restrições, que são calculadas com base nos gradientes das respostas da estrutura. Partindo-se de equações gerais válidas para quaisquer elementos,foram desenvolvidas expressões analíticas que permitem o cálculo exato das sensibilidades de elementos finitos isoparamétricos formulados através do procedimento Lagrangiano Total. O desenvolvimento e a implementação de expressões semelhantes para elementos mais complexos é uma tarefa bastante árdua. Por outro lado, o método das diferenças fi- nitas é simples e genérico, mas muito caro computacionalmente. O método semi-analítico mantémm as vantagens da utilização de diferenças finitas e possui um custo computacional baixo, porém pode apresentar sérios problemas de preciso. Devido a estes motivos, foi desenvolvido neste trabalho um procedimento para melhorar a qualidade das sensibilidades semi-analíticas de estruturas geometricamente não-lineares. O procedimento é baseado na diferenciação exata dos movimentos de corpo rígido do elemento utilizado. Os resultados numéricos obtidos demonstraram a sua eficácia. / [en] This work presents a methodology for shape optimization of geometrically nonlinear structures. The main purpose is to avoid the stability problems generated by optimization based on linear behavior. The methodology was implemented for two-dimensional problems, and several structures were successfully optimized. Using geometrical modeling concepts, the shape of the structure is defined by its boundary curves. Therefore, parametric representation and curve definition by a set of key points are discussed in detail. Due to its flexibility in shape definition, particular attention is given to interpolation using B- splines. The optimization problem is defined based on the geometrical model and the design variables are the positions of key points. Design variable linking can be applied to enforce symmetry.The structure it is analyzed using plane isoparametric elements. Thus, is necessary to perform the discretization of the structure in a set of finite elements. Different algorithms were implemented to generate structured or unstructured finite element meshes. The standard Newton-Raphson method is applied to find the equilibrium configuration, and different methods can be used to evaluate critical points. Due to the convergence problems presented by direct methods, a new semi-direct method was developed. The numerical results show the suitability of the finite elements and numerical methods implemented in the present work.The mathematical programming algorithms used in this work require the evaluation of design sensitivities in order to compute the search direction of the optimization process.Using basic sensitivity equations, which are independent from the particular element, analytical expressions were developed for the sensitivity computation of isoparametric elements formulated according to the Total Lagrangian approach. Applying the analytical method for more complex elements is very cumbersome and error prone. On the other hand, the finite difference method is simple and generic, but its computational cost is prohibitive. The semi-analytical method preserves the advantages of the use of finite differences and has a low computational cost, but presents severe accuracy problems. Hence, a method based on the exact differentiation of the rigid body motions was developed in this work to improve the accuracy of the semi- analytical sensitivities of geometrically nonlinear structures. The numerical examples show that this method eliminates the abnormal errors presented by the semi- analytical sensitivities. / [es] Este trabajo propone una metodología para la optimización de forma de extructuras geométricamente no lineares. EL objetivo de esta metodología es evitar los problemas de inestabilidad que presentan las extructuras optimizadas de acuerdo con la formulación clásica. Ella fue implementada para problemas bidimensionales y los resultados obtenidos en la optimización de diferentes extructuras demuestran su éxito. Utilizando conceptos de modelaje geométrica, la forma de la extructura se define a través de las curvas de contorno. Así, la representación paramétrica de curvas y su definición en función de un conjunto de puntos de interpolación (puntos clave) son discutidas detalladamente. Se le da especial a la interpolación a través de B splines,debido a su gran flexibilidad. El problema de optimización se define con base en el modelo geométrico y las variables de proyecto son las coordenadas de los puntos clave. La simetría de la extructura se garante a través de la llamada de variables. La extructura se analiza a través de elementos isoparamétricos planos. Antes de realizar el análisis, es necesario discretizar la extructura en un conjunto de elementos finitos. Para realizar esta tarea fueron implementados diferentes algoritmos de generación de mallas, tanto extructuradas como no extructuradas. EL método de Newton Raphson es utilizado para determinar la configuración de equilibrio y pueden ser aplicados diferentes métodos para determinar los puntos críticos. Debido a los problemas de convergencia presentados por los métodos directos para la determinación de los puntos crticos, se desarrolló un método semidirecto. Los resultados obtenidos en el análisis de diferentes ejemplos muestran la adque los elementos finitos los métodos numéricos implementados son adequados Los algoritmos de programación matemática utilizados en este trabajo necesitan los gradientes de la función objetivo y de las restricciones, que son calculadas con base en los gradientes de las respuestas de la extructura. Partiendo de las ecuaciones generales válidas para cualesquiera elementos, fueron desarrolladas expresiones analíticas que permiten el cálculo exacto de las sensibilidades de elementos finitos isoparamétricos formulados a través del procedimiento Lagrangiano Total. EL desarrollo y la implementación de expresiones semejantes para elementos más complexos es una tarea bastante árdua. Por otro lado, el método de las diferencias finitas es simple y genérico, pero muy caro computacionalmente. EL método semianalítico mantiene las ventajas de la utilización de diferencias finitas y posee un costo computacional bajo, pero puede presentar serios problemas de precisión. Es por ello que se desarrolló en este trabajo un procedimiento para mejorar la calidad de las sensibilidades semianalíticas de extructuras geométricamente no lineares. EL procedimiento tiene como base la diferenciación exacta de los movimentos de cuerpo rígido del elemento utilizado. Los resultados numéricos obtenidos demuestran su eficacia.

Optical fibers play a vital role in modern telecommunication systems and networks. An optical fiber link imposes some linear and nonlinear distortions on the propagating light-wave signal due to the inherent dispersive nature and nonlinear behavior of the fiber. These distortions impede the increasing demand for higher data rate transmission over longer distances. Developing efficient and computationally non-expensive digital signal processing (DSP) techniques to effectively compensate for the fiber impairments is therefore essential and of preeminent importance. This thesis proposes two DSP-based approaches for mitigating the induced distortions in short-reach and long-haul fiber-optic communication systems. The first approach introduces a powerful digital nonlinear feed-forward equalizer (NFFE), exploiting multilayer artificial neural network (ANN). The proposed ANN-NFFE mitigates nonlinear impairments of short-haul optical fiber communication systems, arising due to the nonlinearity introduced by direct photo-detection. In a direct detection system, the detection process is nonlinear due to the fact that the photo-current is proportional to the absolute square of the electric field intensity. The proposed equalizer provides the most efficient computational cost with high equalization performance. Its performance is comparable to the benchmark compensation performance achieved by maximum-likelihood sequence estimator. The equalizer trains an ANN to act as a nonlinear filter whose impulse response removes the intersymbol interference (ISI) distortions of the optical channel. Owing to the proposed extensive training of the equalizer, it achieves the ultimate performance limit of any feed-forward equalizer. The performance and efficiency of the equalizer are investigated by applying it to various practical short-reach fiber-optic transmission system scenarios. These scenarios are extracted from practical metro/media access networks and data center applications. The obtained results show that the ANN-NFFE compensates for the received BER degradation and significantly increases the tolerance to the chromatic dispersion distortion. The second approach is devoted for blindly combating impairments of long-haul fiber-optic systems and networks. A novel adjoint sensitivity analysis (ASA) approach for the nonlinear Schrödinger equation (NLSE) is proposed. The NLSE describes the light-wave propagation in optical fiber communication systems. The proposed ASA approach significantly accelerates the sensitivity calculations in any fiber-optic design problem. Using only one extra adjoint system simulation, all the sensitivities of a general objective function with respect to all fiber design parameters are estimated. We provide a full description of the solution to the derived adjoint problem. The accuracy and efficiency of our proposed algorithm are investigated through a comparison with the accurate but computationally expensive central finite-differences (CFD) approach. Numerical simulation results show that the proposed ASA algorithm has the same accuracy as the CFD approach but with a much lower computational cost. Moreover, we propose an efficient, robust, and accelerated adaptive digital back propagation (A-DBP) method based on adjoint optimization technique. Provided that the total transmission distance is known, the proposed A-DBP algorithm blindly compensates for the linear and nonlinear distortions of point-to-point long-reach optical fiber transmission systems or multi-point optical fiber transmission networks, without knowing the launch power and channel parameters. The NLSE-based ASA approach is extended for the sensitivity analysis of general multi-span DBP model. A modified split-step Fourier scheme method is introduced to solve the adjoint problem, and a complete analysis of its computational complexity is studied. An adjoint-based optimization (ABO) technique is introduced to significantly accelerate the parameters extraction of the A-DBP. The ABO algorithm utilizes a sequential quadratic programming (SQP) technique coupled with the extended ASA algorithm to rapidly solve the A-DBP training problem and optimize the design parameters using minimum overhead of extra system simulations. Regardless of the number of A-DBP design parameters, the derivatives of the training objective function with respect to all parameters are estimated using only one extra adjoint system simulation per optimization iterate. This is contrasted with the traditional finite-difference (FD)-based optimization methods whose sensitivity analysis calculations cost per iterate scales linearly with the number of parameters. The robustness, performance, and efficiency of the proposed A-DBP algorithm are demonstrated through applying it to mitigate the distortions of a 4-span optical fiber communication system scenario. Our results show that the proposed A-DBP achieves the optimal compensation performance obtained using an ideal fine-mesh DBP scheme utilizing the correct channel parameters. Compared to A-DBPs trained using SQP algorithms based on forward, backward, and central FD approaches, the proposed ABO algorithm trains the A-DBP with 2.02 times faster than the backward/forward FD-based optimizers, and with 3.63 times faster than the more accurate CFD-based optimizer. The achieved gain further increases as the number of design parameters increases. A coarse-mesh A-DBP with less number of spans is also adopted to significantly reduce the computational complexity, achieving compensation performance higher than that obtained using the coarse-mesh DBP with full number of spans. / Thesis / Doctor of Philosophy (PhD) / This thesis proposes two powerful and computationally efficient digital signal processing (DSP)-based techniques, namely, artificial neural network nonlinear feed forward equalizer (ANN-NFFE) and adaptive digital back propagation (A-DBP) equalizer, for mitigating the induced distortions in short-reach and long-haul fiber-optic communication systems, respectively. The ANN-NFFE combats nonlinear impairments of direct-detected short-haul optical fiber communication systems, achieving compensation performance comparable to the benchmark performance obtained using maximum-likelihood sequence estimator with much lower computational cost. A novel adjoint sensitivity analysis (ASA) approach is proposed to significantly accelerate sensitivity analyses of fiber-optic design problems. The A-DBP exploits a gradient-based optimization method coupled with the ASA algorithm to blindly compensate for the distortions of coherent-detected fiber-optic communication systems and networks, utilizing the minimum possible overhead of performed system simulations. The robustness and efficiency of the proposed equalizers are demonstrated using numerical simulations of varied examples extracted from practical optical fiber communication systems scenarios.

Polyneoptera is an assemblage of eleven insect orders comprising the "orthopteroid" insects. It includes familiar insects such as grasshoppers, roaches, termites, earwigs and preying mantises; as well as the more obscure web-spinners, angel insects and ice-crawlers. We present a phylogenetic analysis of the polyneopteran orders based on 18S rDNA, 28S rDNA, Histone 3, and a coded morphology matrix for an extensive sampling of taxa. We investigate the use of congruence between separate datasets as an a priori measure of alignment quality. Our results support the paraphyly of Polyneoptera, the monophyly of Dictyoptera, sister taxon relationships between Embiidina + Phasmatodea and Dermaptera + Zoraptera, and a relatively basal placement of Plecoptera. The analyses also support a sister taxon relationship between the newly described Mantophasmatodea and Grylloblattodea, a small order of cryophilic insects confined to the northwestern Americas and northeastern Asia. This placement coupled with the morphological disparity of the two groups validates the creation of a new order for Mantophasmatodea. Our results also suggest the Direct Optimization (formerly Optimization Alignment) produces alignments that are more predictable across the parameter landscape than alignment via CLUSTAL X, as measured by congruence among independent data partitions. Dense taxon sampling and phylogenetic analysis of six molecular markers (12S, 16S, 18S, 28S, COII, and H3) and morphological data for the order Plecoptera demonstrates that the subordinal groups Arctoperlaria and Antarctoperlaria are monophyletic. Euholognatha and Systellognatha are also monophyletic, with the exception of the genus Megaleuctra which is the basal lineage for the order and deserves recognition as a distinct family (Megaleuctridae). Notonemouridae is strongly supported as a monophyletic clade. Within the Systellognatha Styloperlidae is the basal lineage, followed by Peltoperlidae then Pteronarcyidae, and Perloidea is a strongly supported monophyletic group with Chloroperlidae as sister taxon to Perlidae + Perlodidae. The family Gripopterygidae is strongly supported as paraphyletic. Many Plecoptera (stoneflies) exhibit a pre-mating communication known as "drumming." Species of the genus Isogenoides have complex drumming behavior in which (i) the male calls the female by tapping his abdomen against the substrate, (ii) the female answers with her own distinctive tapping, and (iii) the male responds with a confirmatory series of taps. These drumming patterns are specific to individual species and may vary within a species to form distinct dialects. Phylogenetic analysis for the genus based on six molecular markers (12S, 16S, 18S, 28S, COII, and H3) supports Yugus as its nearest extant relative and I. hansoni as the basal lineage within the genus. Drumming behavioral characters appear to be largely incongruent with the phylogeny.

Ziel dieser Doktorarbeit ist ein mathematisches Modell zu entwickeln, um eine mögliche Ausbreitung des West-Nil-Virus (WNV) in Deutschland zu simulieren und zu bewerten. Das entwickelte Werkzeug soll auch auf eine weitere, durch Zecken übertragene Krankheit, dem Krim-Kongo-Hämorrhagischen Fieber (CCHFV) angewendet werden. Die durch den Klimawandel verursachte globalen Erwärmung unterstützt auch die Verbreitung und Entwicklung verschiedener Vektorpopulationen. Dabei hat eine Temperaturerhöhung einen positiven Einfluss auf den Lebenszyklus des Vektors und die Zunahme der Vektoraktivität. In dieser Arbeit haben wir ein Differentialgleichungsmodell (ODE) entwickelt, um den Einfluss eines regelmäßigen Eintrags von Infektionserregern auf die empfängliche Population unter Berücksichtigung des Temperatureinflusses zu verstehen. Als Ergebnis haben wir einen analytischen Ausdruck der Basisreproduktionszahl und deren Wechselwirkung mit der Temperatur gefunden. Eine Sensitivitätsanalyse zeigt, wie wichtig das Verhältnis der anfälligen Mücken zur lokalen Wirtspopulation ist. Als ein zentrales Ergebnis haben wir den zukünftigen Temperaturverlauf auf Basis der Modellergebnisse des IPCC in unser Modell integriert und Bedingungen gefunden, unter denen es zu einer dauerhaften Etablierung des West-Nil-Virus in Deutschland kommt. Darüber hinaus haben wir die entwickelten mathematischen Modelle verwendet, um verschiedene Szenarien zu untersuchen, unter denen sich CCHFV möglicherweise in einer naiven Population etablieren kann, und wir haben verschiedene Kontrollszenarien mathematisch abgeleitet, um die Belastung von einer Infektion durch Zecken zu bewältigen. / The objective of this thesis is to develop the necessary mathematical model to assess the potential spread of West Nile Virus (WNV) in Germany and employ the developed tool to analyse another tick-borne disease Crimean- Congo Hemorrhagic Fever (CCHFV). Given the backdrop of global warming and the climate change, increasing temperature has benefitted the vector population. The increase in the temperature has a positive influence in the life cycle of the vector and the increase in its activities. In this thesis, we have developed an Ordinary Differential Equation (ODE) model system to understand the influence of the periodic introduction of infectious agents into the local susceptible population while taking account of influence of temperature. As results, we have found an analytic expression of the basic reproduction number and its interplay with the temperature. The sensitivity analysis shows us the importance of the ratio between the susceptible mosquitoes to the local host population. As a central result we have extrapolated the temperature trend under different IPCC conditions and found the condition under which the circulation of West Nile Virus will be permanent in Germany. Furthermore, we have utilised the developed mathematical models to examine different scenarios under which CCHFV can potentially establish in a naive population along with we mathematically derived different control scenarios to manage the burden of tick infection.

The age-cutoff regression discontinuity design (RDD) has emerged as one of the most rigorous quasi-experimental approaches to determining program effects of prekindergarten on literacy and numeracy outcomes for children at kindergarten entry. However, few pre-K meta-analyses have focused attention on validity threats. The current random-effects meta-regression tests the moderating effects of prominent threats to validity, selection bias and sensitivity, on impact estimates generated from age-cutoff regression discontinuity studies from large-scale programs. Results from averaging dependent standardized mean difference effects suggested small positive moderating effects of total attrition and robust 3-month bandwidths on reading effects, but not on math. However, these results were not statistically significant. In contrast, results generated from robust variance estimation yielded a small statistically significant association between total attrition and math effects. These mixed results may warrant further research on prekindergarten evaluation methodology, evaluation estimation methods, and the totality of evidence used to inform policy.

This thesis project aims to advance the modelling of pressure gradient turbulent boundary layers (PG TBLs) and offer new insights into TBLs modelling. Previous analytical studies have explored various mathematical models, but this research introduces an extended unstacked Deep Operator Networks (DeepONets) architecture with double outputs and five branch parameters. The objective is to capture the mean velocity and Reynolds stress of turbulent boundary layers under pressure gradients. Numerical and experimental datasets of PG TBLs were accessed and utilized to train the DeepONets models. These models successfully predicted the mean velocity and Reynolds stress profiles using outer-scaled parameters. The DeepONets effectively learned the operator that describes the desired profiles based on input parameters, which correspond to the development of boundary layer thickness and pressure gradients. To identify the model with the best prediction performance, error statistics and distribution were examined across different configurations and dimensions. Furthermore, the individual and global sensitivity analyses revealed the relationship between input parameters and their influence on modelling PG TBLs with DeepONets.