<p>The design and discovery of novel materials are difficult not only due to expensive and time- consuming calculation and measurements of their properties, but also thanks to the infinite search spaces. With the increasingly abundant data from experiments and simulations, learning from data has the potential of bypassing complex physics-based simulations and experiments and providing fast approximations of the solution. Deep learning models are helpful in the design process that requires prohibitively expensive iterative computations. In addition, as efficient and accurate sur- rogate models, trained deep networks can incorporate techniques, such as sensitivity analysis and active learning, to provide guidance in searching promising candidates. Moreover, deep learning models need to account for the material structural information, such as molecule and atom align- ments, chemical bonds, and grain-level interactions, as it plays an important role in determining the macroscopic properties. In this thesis, we start with developing two standard deep learning model- based materials design frameworks for lithium-ion batteries and thermoelectric materials, and we then investigate the feasibility of standard deep learning models on data with graph-structured in- formation and identify the challenges. Finally, we propose a deep graph operator network that effectively capture the spatial dependency encoded in the graph structure to solve networked dy- namical systems.</p> <p><br></p> <p>In the first half of the thesis, we propose a hybrid convolutional neural network to infer lithium- ion battery microstructure properties, Bruggeman’s exponent and shape factor, given its voltage vs. capacity curves. The trained model accurately predicts the microstructural properties on both experimental and simulation data, and it can readily accelerate the processing-properties- performance and degradation characteristics of the existing and emerging chemistries of lithium- ion batteries. Also, we develop a AI-guided framework to discover and design thermoelectric materials, where we train classifiers based on the materials chemical and structural information embeddings and combine with variance-based sensitivity analysis to suggest candidates and con- duct fast screening.</p> <p><br></p> <p>In the second half of the thesis, we build a data-centric framework with a recurrent neural network-based classifier to achieve traffic incident detection on highway networks. We incorporate weak supervised learning and design labeling functions to create large amount of training data with probabilistic labels. The trained deep ensemble accurately detects incidents with predictive uncertainty. To capture the structural information in the network, we then propose a deep graph operator network that maps the input graph state function to the output graph state function. The proposed model enables resolution-independence and zero-shot transfer, where we do not require a set of fixed sensors to encode the graph trajectory and can use the trained model directly on larger graphs with high accuracy. We utilize the proposed model to solve power grid transient stability prediction and traffic forecasting problems.</p>

No / This paper presents the results of a simulation study of 10 fire tests on restrained steel beam–column assemblies using five different types of joints: fin plate, flexible endplate, flush endplate, web cleat and extended endplate. This paper will provide details of the simulation methodology for achieving numerical stability and faithful representation of detailed structural behaviour, and compare the simulation and experimental results, including joint failure modes, measured beam axial forces and beam mid-span deflections. Good agreement between ABAQUS simulations and experimental observations confirms that the finite element models developed through the ABAQUS/Standard solver are suitable for predicting the structural fire behaviour of restrained structural assemblies with realistic steel joints undergoing different phases of behaviour in fire, including restrained thermal expansion and catenary action in the beams. The validated model may be used to conduct numerical parametric studies to generate theoretical data to help develop detailed understanding of steel joint behaviour and their effects on robustness of steel framed structures in fire.

<p dir="ltr">Energetic materials are substances with considerable amounts of energy that can detonate under shock, pressure, or high temperature conditions, making them acceptable candidates for applications such as explosives, propellants, and fuels. One example of an energetic material is the explosive known as cyclotetramethylene tetranitramine (HMX). When subjected to impact, HMX can undergo thermo-mechanical responses that may lead to deflagration or, in the most severe cases, detonation. Due to the multiscale nature of these phenomena and the varying impact velocity magnitudes, replicating such responses can be challenging or even unattainable in an experimental setting. Consequently, computational models capable of predicting real-world conditions beyond experimental reach are highly valuable to the explosives research community.</p><p dir="ltr">This study continues the work from previous analyses (Duarte 2021) by developing a finite element model of HMX combined with an aluminum rod, predicting damage evolution and dynamic response under shock compression. The impact velocities applied in the model ranged from 0.1 km/s to 0.6 km/s using three different crystal orientations to investigate their corresponding effects. The results indicate that impacting in the direction normal to the HMX plane [110], which exhibited high levels of plastic energy, had the most resistant to cracking near the HMX-aluminum interface. Furthermore, these findings show that elastic energy accumulation is the primary driver in this analysis of crack propagation and bulk damage in HMX crystals.</p><p dir="ltr">Additionally, the HMX and aluminum results were compared against two additional models: a homogeneous HMX sample without discontinuities and an HMX sample with a void in place of the aluminum rod. Comparisons of the models show that the most severe damage field occurs in the void model, while the shock wave accelerated through the aluminum rod but also decelerated significantly in the presence of a void due to wave refraction at traction free boundaries. These results provide another level of understanding into the role of material interfaces and voids in the dynamic response of HMX under shock loading. Experimental validation of these findings is recommended for future studies, assuming the conditions are feasible for testing.</p>

<p dir="ltr">Nature moves small things by chemical energy. Inspired by this, catalytic reactions driven microswimmers have been designed and believed to be promising to help transport drugs and other cargos at microscales. However, decorating the microswimmers with drugs and cargos would make them heavy and hard to move. An alternative solution to this would be designing self-pumping devices that can pump the fluid and things carried by the fluid all together without external resources. In this work, we have presented the first full numerical model of electrochemically-powered self-pumping in the Pt-Au coated polycarbonate membrane reported by Jun and Hess [1]. The simulations demonstrate that autonomous flow in self-pumping membranes is an electro-osmotic flow driven by a self-generated electric field. The injection and consumption of H⁺ on Pt and Au respectively lead to a charge asymmetry and an associated electric field that acts on the electric double layers (EDL) coating the pore walls driving fluid move, i.e. self-electro-osmosis. Key parameters controlling the performance of self-pumping are pore radius and background pH values, as they affect the EDL overlap and ionic strength. Other parameters such as porosity and pore length can both be tuned to find the local optimum for a membrane design. By tuning these parameters, the trade-off between increased ionic current and increased ionic strength could be balanced, contributing to an optimum self-pumping performance. When inclination or deformation occurs in cylindrical pores, the self-pumping flow does not significantly deviate from the trend. Membranes with complicated shape of contracting/expanding pores and cross-linked connecting pores should follow same pattern as cylindrical pores with similar pore size. In addition, if we replace the Pt/Au catalytic pairs by TiO₂/Au photocatalytic pairs, self-pumping membrane could be driven by light. The geometry of pore enhances the light absorption, enabling self-pumping membrane achieving high flow rate at large porosity with relatively large pores. At the end, we provide experimental evidence of self-pumping flow on TiO₂-Au plates as well as self-pumping membrane driven by light.</p>

<p dir="ltr">This thesis delves into the dynamics and driving factors of thermal transport via natural convection, the onset and severity of quiescent cavitation and its impact of auto-injector device performance, and the controlled release of rapidly swelling pharmaceutical tablets. In each of these instances showcases how variations in external conditions or the introduction of new variables can disrupt the equilibrium of fluid systems, leading to complex behaviors. Vertical thermal convection illustrates how temperature gradients induce fluid movement and patterns; cavitation inception focuses on the formation of vapor cavities due to pressure drops within a fluid; and rapid tablet swelling explores the interaction between solid materials and liquids, leading to significant changes in concentration and mass transfer. These studies collectively enhance our understanding of transport dynamics, highlighting pathways to achieve optimal transport and delivery conditions for various industrial and pharmaceutical processes.</p>

<p dir="ltr">This thesis focuses on the study of wave propagation in architected material systems. Specifically of interest is wave propagation in topologically interlocking material (TIM) systems made of tetrahedra and bio-inspired blocks. TIM systems are assemblies of composed of blocks in which the block geometry constrains blocks in place. Individual blocks can only be removed by disassembling the system. This interlocking of block geometry allows these systems to bear loads without the need for adhesives. Overall, load bearing is affected by block geometry, contact interaction, and assembly architecture. Wavefronts and wave velocities are computed using an explicit finite element code. Wave propagation is investigated first in a row of interlocking tetrahedra, then in 3D planar TIM systems of tetrahedra and bio-inspired scutoid blocks.</p><p dir="ltr">The propagation of linear traveling waves through a row of interlocking tetrahedra is demonstrated by the use of finite element simulations. The wave velocity was found to be independent of wave amplitude for ideal contact conditions but dependent on impact velocity for an exponential pressure-overclosure relationship between surfaces. For a frictionless, constant contact stiffness model, the effective wave velocity is about 50% of the 1D material wave speed. In the presence of friction, the wave velocity increases to about 80% of the 1D material wave speed. The wave velocity is attributed to wave-guiding set by the geometry of the tetrahedra. The wave velocity is further modulated by the rocking motion of the tetrahedra about an axis perpendicular to the wave propagation direction. The rocking motion is affected by friction and is reduced as friction is increased. Experimental results on wave propagation in a row of 3D-printed triangular prisms demonstrate pulse-like voltage versus time wave responses. With rough and tacky surfaces, the velocity of the linear traveling waves is measured as approximately 20% the 1D material wave speed. For smooth and low friction surface conditions, significantly higher wave velocities are measured. Similarly, reducing the number of contact surfaces by fusing pairs of building blocks also results in higher measured wave velocities. Experiments on rectangular prisms lack the wave-guiding geometry and provide a reference configuration. Finite element models are used to gain detailed insight into the wave propagation process. Wave-guide models are defined to predict wave speeds based on the effective path of wave propagation. The proposed models closely predict measured and computed wave speeds for the tetrahedra and triangular prisms.</p><p dir="ltr">Scutoids are prism-like shapes containing lateral vertices between two parallel polygonal surfaces. With the lateral vertices at the midplane, scutoid blocks can be periodically and densely packed. Scutoid-based planar arrays are demonstrated to behave mechanically as TIM systems. Under quasi-static transverse loads, assembly properties (stiffness, strength, toughness) match or exceed those of the corresponding tetrahedra-based TIM systems. The scutoid-based TIM systems have unique chiral characteristics. Chirality is attributed to the combination of building block and assembly symmetry. Chirality leads to asymmetric internal load transfer patterns resulting in unbalanced in-plane reaction forces and reaction moments. Experiments confirm the computational findings. Under transverse indentation, these systems have nonlinear force-displacement responses and measurable torque responses.</p><p dir="ltr">Wave propagation following transverse impact on planar arrays of interlocking tetrahedra and scutoids is investigated. Unique wave speed and wavefront development are demonstrated to occur in these systems. The 1D material wave speed emerges as the limiting wave speed of the TIM systems, rather than the dilatational wave speed. In tetrahedra assemblies, waves propagate with a velocity of approximately 25% of the 1D material wave speed. The wave velocity is attributed to wave-guiding from the interlocking tetrahedra geometry. Tetrahedra are not perfectly space-filling and block-to-block interactions are not limited to one direction. In the scutoid assemblies, waves propagate at velocities between 80% and 90% of the 1D material wave speed. These velocities are along directions associated with dominant load paths. The wave velocities in the scutoid-based TIM systems approach the 1D material wave speed as the contact surfaces are substantially orthogonal to the assembly surface. In comparison to monolithic plates, wavefronts develop with significant spatial non-uniformity. Wave patterns exhibit the symmetry or asymmetry also observed in the quasi-static response. Overall, contact surface orientation, block geometry, and assembly architecture affect wave velocity and wavefront development.</p>

The Habitable Worlds Telescope Starshade is an occulting disk that orbits in tandem with a telescope that occludes and diffuses the light from stars to observe the relatively dim exoplanets in orbit around them. It achieves this in part with tailored petals that diffuse light to soften the light from the star. Due to the relative sizes of the star and the planet, NASA considers the shape stability of the Starshade's petals to be a Key Technology Gap. The Starshade is developed to be a deployable composite structure that folds on itself to fit within modern rockets. Due to the nature of satellite launches, Starshade will sit in the stowed configuration for multiple years, during which the viscoelastic material properties of the materials that consist of the Starshade will deform in the structure and take an unknown time to recover fully. Thus, the need arises to understand Starshade's viscoelastic behavior through recovery after fully deploying. Starshade's Petals consists of a sandwich composite structure where multiple composite edges are joined together using a significantly less stiff adhesive that is comparably thicker than the individual Carbon Fiber Reinforced Plastic layers that consist of the composite edge. This could cause traditional modeling approaches to not fully capture the potential modes of relaxation in the structure, so a diagnostic model, referred to as the Phoenix Edge, is developed to compare different modeling techniques. After modeling techniques are validated against each other, they are applied to the NI2 Petal to predict the viscoelastic structural response through 6 months of recovery after three years of stowage in a furled configuration.

[ES] La predicción del comportamiento de los pesticidas liberados en el ambiente es necesaria para anticipar y por ende minimizar sus efectos adversos. La contaminación por pesticidas en las aguas subterráneas puede suceder a través de la deriva, la escorrentía superficial o el flujo subsuperficial. Se han desarrollado varios modelos para predecir el comportamiento, movilidad y persistencia de los pesticidas. Sin embargo, el número de estos modelos aplicados a aguas subterráneas es muy reducido, ya que usualmente solo se aplican a masas de agua superficiales. Además, los pocos estudios realizados en masas de agua subterráneas son limitados y no logran reflejar todas las variables que pueden influir en la contaminación por pesticidas. Es necesario integrar en el modelo procesos clave como el crecimiento de los cultivos, la aplicación de pesticidas, los procesos de transformación y las prácticas de gestión de los campos. Por tanto, la modelación en aguas subterráneas requiere tener en cuenta parámetros como las propiedades del suelo y las características químicas del pesticida (solubilidad, coeficiente de degradación etc.). Además, también debe integrar variables que son cambiantes en el espacio y en el tiempo, como características hidrológicas, fenología de los cultivos y variables climáticas como temperatura, precipitación, evaporación, viento y radiación solar. El movimiento de pesticidas en las aguas superficiales y subterráneas es una preocupación ambiental creciente debido a la contaminación causada por la aplicación intensiva de pesticidas en la agricultura y otras actividades antropogénicas. Estos compuestos reducen la calidad del agua y producen efectos perjudiciales en los ecosistemas y la salud humana, lo que justifica el interés que tiene su modelado en las reservas de agua subterráneas para poder realizar una gestión ambiental adecuada y adoptar medidas preventivas. En esta tesis se aborda la modelación matemática de cinco pesticidas (Bromacil, Terbutilazina, Atrazina, Desetil-Terbutilazina y Terbumeton) en la Demarcación Hidro-gráfica del Júcar (DHJ) que ocupa una superficie de más de 40 000 km2 con una población superior a los cinco millones de personas. Para ello, se utilizó el software PRZM5 (Pesticide Root Zone Model, versión 5) desarrollado por la Agencia Medioambiental de Estados Unidos (EPA). Mediante la aplicación de PRZM5 se simuló el destino y transporte de pesticidas en la zona no saturada de los acuíferos. El modelo se ha utilizado para estimar las concentraciones diarias de pesticidas de 72 pozos de la DHJ. En estas masas de agua subterránea se han encontrado valores de concentración de plaguicidas superiores al valor Máximo de Concentración Permitido (MCP) establecido por la Legislación Española. Estos resultados proporcionan un primer paso crucial para el desarrollo de la evaluación del riesgo de plaguicidas en la DHJ. A partir de estos resultados obtenidos se realizaron un conjunto de mapas de riesgo de contaminación, para tener una mejor perspectiva de la evolución temporal de los pesticidas en las masas de agua subterránea de la DHJ. La distribución espacial de los pesticidas corresponde a zonas mayoritariamente dedicadas a la agricultura de regadío. Por tanto, se puede concluir que la cantidad de pesticida aplicada en los cultivos es el factor más importante que influye en la concentración de pesticida en las masas de agua subterránea. Además, otras variables que afectan son el tipo de suelo, la profundidad del acuífero, características hidro-meteorológicas, y el índice de persistencia de los pesticidas. Este trabajo ejemplifica que la aplicación del modelado matemático es una herramienta válida para el análisis y predicción del destino y transporte de pesticidas en los suelos y en las aguas subterráneas, por lo que su incorporación a la gestión ambiental podría beneficiar a la toma de decisiones sobre los recursos hídricos. / [CA] La predicció del comportament dels pesticides alliberats a l'ambient és necessària per anticipar i per tant minimitzar-ne els efectes adversos. La contaminació per pesticides a les aigües subterrànies pot succeir a través de la deriva, l'escorriment superficial o el flux subsuperficial. S'han desenvolupat diversos models per predir el comportament, la mobilitat i la persistència dels pesticides. Tot i això, el nombre d'aquests models aplicats a aigües subterrànies és molt reduït, ja que usualment només s'apliquen a masses d'aigua superficials. A més, els pocs estudis realitzats en masses d"aigua subterrànies són limitats i no aconsegueixen reflectir totes les variables que poden influir en la contaminació per pesticides. És necessari integrar al model processos clau com el creixement dels cultius, l'aplicació de pesticides, els processos de transformació i les pràctiques de gestió dels camps. Per tant, la modelació en aigües subterrànies requereix tenir en compte paràmetres com les propietats del sòl i les característiques químiques del pesticida (solubilitat, coeficient de degradació, etc.). A més, també ha d'integrar variables que són canviants a l'espai i en el temps, com característiques hidrològiques, fenologia dels cultius i variables climàtiques com temperatura, precipitació, evaporació, vent i radiació solar. El moviment de pesticides a les aigües superficials i subterrànies és una preocupació ambiental creixent a causa de la contaminació causada per l'aplicació intensiva de pesticides a l'agricultura i altres activitats antropogèniques. Aquests compostos redueixen la qualitat de l'aigua i produeixen efectes perjudicials en els ecosistemes i la salut humana, cosa que justifica l'interès que té el modelat a les reserves d'aigua subterrànies per poder fer una gestió ambiental adequada i adoptar mesures preventives. En aquesta tesi s'aborda la modelació matemàtica de cinc pesticides (Bromacil, Terbutilazina, Atrazina, Desetil-Terbutilazina i Terbumeton) a la Demarcació Hidrogràfica del Xúquer (DHJ) que ocupa una superfície de més de 40 000 km2 amb una població superior als cinc milions de persones. Per fer-ho, es va utilitzar el programa PRZM5 (Pesticide Root Zone Model versió 5) desenvolupat per l'Agència Mediambiental dels Estats Units (EPA). Mitjançant l'aplicació de PRZM5 es va simular la destinació i el transport de pesticides a la zona no saturada dels aqüífers. El model s'ha fet servir per estimar les concentracions diàries de pesticides de 72 pous de la DHJ. En aquestes masses d"aigua subterrània s"han trobat valors de concentració de plaguicides superiors al valor Màxim de Concentració Permès (MCP) establert per la Legislació Espanyola. Aquests resultats proporcionen un primer pas crucial per al desenvolupament de l'avaluació del risc de plaguicides a la DHJ. A partir d'aquests resultats obtinguts es van fer un conjunt de mapes de risc de contaminació, per tenir una perspectiva millor de l'evolució temporal dels pesticides en les masses d'aigua subterrània de la DHJ. La distribució espacial dels pesticides correspon a zones dedicades majoritàriament a l'agricultura de regadiu. Per tant, es pot concloure que la quantitat de pesticida aplicada als cultius és el factor més important que influeix en la concentració de pesticida a les masses d'aigua subterrània. A més, altres variables que afecten són el tipus de sòl, la profunditat de l'aqüífer, les característiques hidrometeorològiques i l'índex de persistència dels pesticides. Aquest treball exemplifica que l'aplicació del modelatge matemàtic és una eina vàlida per a l'anàlisi i la predicció de la destinació i el transport de pesticides als sòls i a les aigües subterrànies, per la qual cosa la seua incorporació a la gestió ambiental podria beneficiar la presa de decisions sobre els recursos hídrics. / [EN] Predicting the behaviour of pesticides released into the environment is necessary to anticipate and thus minimise their adverse effects. Pesticide contamination in groundwater can occur through drift, surface runoff or subsurface flow. Several models have been developed to predict the behaviour, mobility and persistence of pesticides. However, the number of these models applied to groundwater is very small, as they are usually only applied to surface water bodies. Moreover, the few studies carried out on groundwater bodies are limited and fail to reflect all variables that may influence pesticide contamination. Key processes such as crop growth, pesticide application, transformation processes and field management practices need to be integrated into the model. Groundwater modelling therefore requires taking into account parameters such as soil properties and chemical characteristics of the pesticide (solubility, degradation coefficient, etc.). In addition, it must also integrate variables that are changeable in space and time, such as hydrological characteristics, crop phenology and climatic variables such as temperature, precipitation, evaporation, wind and solar radiation. The movement of pesticides to groundwater bodies is a growing environmental concern due to pollution caused by intensive pesticide application in agriculture and other anthropogenic activities. These compounds reduce water quality and produce detrimental effects on ecosystems and human health, which justifies the interest of modelling them in groundwater reservoirs for proper environmental management and preventive measures. This thesis deals with the mathematical modelling of five pesticides (Bromacil, Terbuthylazine, Atrazine, Desethyl-Terbuthylazine and Terbumeton) in the Júcar River Basin District (DHJ), which covers an area of more than 40,000 km2 with a population of more than five million people. For this purpose, the PRZM5 software (Pesticide Root Zone Model version 5) developed by the US Environmental Protection Agency (EPA) was used. The application of PRZM5 was used to simulate the fate and transport of pesticides in the unsaturated zone of aquifers. The model was used to estimate daily pesticide concentrations from 72 wells in the DHJ. In these groundwater bodies, pesticide concentration values higher than the Maximum Allowable Concentration (MCP) value established by the Spanish Legislation have been found. These results provide a crucial first step for the development of the pesticide risk assessment in the DHJ. Based on these results, a set of contamination risk maps were made, in order to have a better perspective of the temporal evolution of pesticides in the groundwater bodies of the DHJ. The spatial distribution of pesticides corresponds to areas mainly dedicated to irrigated agriculture. It can therefore be concluded that the amount of pesticide applied on crops is the most important factor influencing pesticide concentration in groundwater bodies. In addition, other affecting variables are soil type, aquifer depth, hydro-meteorological characteristics, and the persistence rate of pesticides. This work exemplifies that the application of mathematical modelling is a valid tool for the analysis and prediction of the fate and transport of pesticides in soils and groundwater. Therefore, its incorporation into environmental management could benefit decision-making on water resources. / Pérez Indoval, R. (2023). Modelación matemática de pesticidas en las masas de agua subterránea de la Demarcación Hidrográfica del Júcar [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/194647

Verunreinigtes Grundwasser stellt eine ernsthafte Bedrohung für die Trinkwasser-Ressourcen auf der ganzen Welt dar. Verunreinigte Grundwasser können zwar in Brunnen detektiert werden, eine ordnungsgemäße Sanierung ist jedoch häufig nur erfolgreich, wenn die Quelle der Verunreinigung erfasst und entfernt wird. Wenn von Anbeginn eines Sanierungsprojektes ein Schwerpunkt auf die Erkennung und Eingrenzung des Verunreinigungsherdes gelegt wird, kann die Sanierung direkt an dieser Stelle ansetzen und zudem hohe Grundwasser-Sanierungskosten verringert werden. ModBack ist eine Software, die mehrere bestehende Modellierungs-Werkzeuge in einer, ein-fach zu verwendenden, ESRI ArcGIS 10-basierten Schnittstelle vereinigt und hilft mögliche Schadstoffquelle Zonen im Untergrund abzugrenzen. Diese Software ist in Visual Basic 3.5 geschrieben und verwendet ArcObjects Bibliotheken, um die erforderlichen GIS-Anwendungen zu implementieren. Es kann ohne Änderung auf allen Microsoft Windows-basierten PC‘s mit ausreichend RAM und mindestens Microsoft. NET Framework 3.5 verwendet werden. Die Nutzung von ModBack erfordert zusätzliche Installation der folgenden Software: Processing Modflow Pro 7.0 (PMWin), MODPATH, CSTREAM (Bayer-Raich et al., 2003a, Bayer-Raich et al., 2003b, Bayer-Raich et al., 2004), Golden Software Surfer, Microsoft Excel und NAS (eine Software zur Berechnung des natürlichen Schadstoffabbaus). Die grafische Benutzeroberfläche (GUI) von ModBack ist in vier Verfahrensschritte Dateneingabe, Grundwassermodellierung, Partikel Backtracking und Analysen getrennt. Geographischen Eingangsdaten werden für eine geografische Übersicht des Testfeldes benötigt. Sie bestehen meist aus georeferenzierten Informationen des Testfeldes und Informationen zur unterirdischen Grundwasserverunreinigungen. Grundwasseranalysen werden entweder durch konventionelle Probennahme aus Grundwassermessstellen oder durch die Durchführung integraler Pumpversuche an Kontrolleben mit eine bestimmten Konzentration/Zeit- Serie (CT-series) gesammelt. Aus den Pumpversuchen resultierende hydraulische Daten werden zusammen mit allen anderen verfügbaren Informationen zur Erstellung eines grundlegenden Grundwasserströmungsmodells des Testfeldes verwendet. Nachfolgende Backtracking Verfahren, als auch die Berechnung von advektivem Schadstofftransport beziehen sich auf die-ses Strömungsfeld und werden entlang einer zuvor definierten Kontrollebene berechnet. Eine Analyse der Backtracking-Ergebnisse erfolgt innerhalb ModBack. Die potenzielle Quelle von Kontaminationen oder deren Abwesenheit werden basierend auf dem Verfahren nach Jarsjö et al. (2005) bestimmt. Die Länge einer Schadstofffahne kann anhand von Fahnenlängen Statistiken und /oder dem Abbau erster Ordnung Abbau Gleichungen oder Berechnungen auf ortsspezifische hydraulischen und chemischen Parametern beruhen. Ferner ist ein analytisches Instrument enthalten, um die Verteilung der Verunreinigungen über eine Steuerebene zu identifizieren. Alle relevanten Ergebnisse können als Vektordaten in ModBack graphisch dargestellt und gespeichert werden und sind somit kompatibel mit weiteren GIS-Software Produkten. ModBack wurde bereits an Testgebieten in Slowenien und Süddeutschland angewendet, um die möglichen Zonen der Verunreinigungsquelle oder deren Abwesenheit zu begrenzen. Auf dem Testgelände in Süddeutschland sind diese Abgrenzungen vergleichbar mit früheren Untersuchungen vor Ort und unterstützt somit die Funktionalität der Software ModBack. Mit ModBack, steht ein Werkzeug zur Verfügung, die bereits jetzt Um-welt-Beratern, Ingenieuren und Umwelt-Agenturen ermöglicht denkbare Quellen der Verunreinigung bei der Planung der Untersuchungen vor Ort und Sanierungsmaßnahmen abzugrenzen, und hilft Kosten deutlich zu senken.

Thesis (MScEng (Process Engineering))--University of Stellenbosch, 2011. / Please refer to full text to view abstract.