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Faculty / Organisational entity
- Kaiserslautern - Fachbereich Mathematik (278)
- Kaiserslautern - Fachbereich Informatik (218)
- Kaiserslautern - Fachbereich Maschinenbau und Verfahrenstechnik (143)
- Kaiserslautern - Fachbereich Chemie (79)
- Kaiserslautern - Fachbereich Elektrotechnik und Informationstechnik (64)
- Kaiserslautern - Fachbereich Biologie (53)
- Kaiserslautern - Fachbereich Sozialwissenschaften (26)
- Landau - Fachbereich Natur- und Umweltwissenschaften (22)
- Kaiserslautern - Fachbereich Wirtschaftswissenschaften (19)
- Kaiserslautern - Fachbereich Physik (9)
Weak memory consistency models capture the outcomes of concurrent
programs that appear in practice and yet cannot be explained by thread
interleavings. Such outcomes pose two major challenges to formal
methods. First, establishing that a memory model satisfies its
intended properties (e.g., supports a certain compilation scheme) is
extremely error-prone: most proposed language models were initially
broken and required multiple iterations to achieve soundness. Second,
weak memory models make verification of concurrent programs much
harder, as a result of which there are no scalable verification
techniques beyond a few that target very simple models.
This thesis presents solutions to both of these problems.
First, it shows that the relevant metatheory of weak memory
models can be effectively decided (sparing years of manual proof
efforts), and presents Kater, a tool that can answer metatheoretic
queries in a matter of seconds. Second, it presents GenMC, the first
(and only) scalable stateless model checker that is parametric in the
choice of the memory model, often improving the prior state of the art
by orders of magnitude.
This thesis outlines the development of thermoplastic-graphite based plate heat exchangers from material screening to operation including performance evaluation and fouling investi-gations. Polypropylene and polyphenylene sulfide as matrix and graphite as filler were cho-sen as feedstock materials, as they possess a low density and excellent corrosion resistance at a comparatively low price.
For the purpose of material screening, custom-made polymer composite plates with a plate thickness of 1-2 mm and a filler content of up to 80 wt.% were investigated for their thermal and mechanical suitability with regard to their use in plate heat exchangers. Three-point flexural tests show that the loading of polypropylene with graphite leads to mechanical prop-erties that allow the composites to be applied as corrugated heat exchanger plates. The simu-lated maximum overpressure is greater than 7 bar, depending on the wall thickness. The thermal conductivity of the composites was increased by a factor of 12.5 compared to pure polypropylene, resulting in thermal conductivities of up to 2.74 W/mK.
The fabrication of the developed corrugated heat exchanger plates, with a thickness between 0.85 mm and 2.5 mm and a heat transfer surface area of 11.13·10-3 m² was carried out via processes that can be automized, namely extrusion and embossing. With the manufactured plate heat exchanger, overall heat transfer coefficients are determined over a wide range of operating conditions (Re = 200 - 1600), which are used to validate a plate heat exchanger model and consequently to compare the composites with conventional materials. The em-bossing, which seems to result in a shift of the internal graphite structure, leads to a further improvement of the thermal conductivity by 7-20 %, in addition to the impact of the filler. With low plate thicknesses, overall heat transfer coefficients of up to 1850 W/m²K could be obtained. Considering the low density of the manufactured thermal plates, this ensures com-parable performance with metallic materials over a wide range of process conditions (Re = 200 - 4000).
The fouling kinetics and amount of calcium sulfate and calcium carbonate, respectively, on different polypropylene/graphite composites in a flat plate heat exchanger and the developed chevron type plate heat exchanger are determined and compared to the reference material stainless steel. For a straight evaluation of the fouling susceptibility of the materials the for-mation of bubbles on the materials is considered by optical imaging or excluded by a degas-ser. The results are interpreted using surface free energy and roughness of the surfaces. The results show that if bubble formation is avoided, the polymer composites have a very low fouling tendency compared to stainless steel, which is attributed to the low surface free ener-gies of approximately 25 mN/m. This is particularly the case when turbulent flows are pre-sent, as is in plate heat exchangers or when sandblasted specimen are used. Sandblasting also continues to increase heat transfer compared to untreated samples by increasing thermal conductivity and creating local turbulences. Depending on the test conditions, the fouling resistance formed on the stainless steel surface is an order of magnitude greater than on the flat plate polymer composites. In addition, the fouling layers adhere only weakly to the com-posites, which indicates an easy cleaning in place after the formation of deposits. The fouling investigations in the plate heat exchanger reveal sensitivity to calcium sulfate fouling, how-ever, CFD simulations indicate that this is due to flow maldistribution and not the actual pol-ymer composite materials.
Plant-specific factors affecting short-range attraction and oviposition of European grapevine moths
(2024)
The spread of pests and pathogens is increasingly intensified by climate change and globalization. Two of the most serious insect pests threating European viticulture are the European grape berry moth, Eupoecilia ambiguella (Hübner) and the European grapevine moth Lobesia botrana (Denis & Schiffermüller). Larvae feed on fructiferous organs of grapevine Vitis vinifera, resulting in high yield and quality losses. Under the aspects of integrated pest management, insecticide measures are only reasonable when other control strategies become ineffective. In order to support the development of novel decision support system for the application of insecticides, the aim of this thesis was to decipher plant-specific factors, which affect the short-range attraction and oviposition of L. botrana and E. ambiguella.
The focus was set on the visual, volatile, tactile and gustatory stimuli provided by their host plant after settlement. The use of artificial surfaces as model plant showed that oviposition of both species is affected by the color, the shape and the texture of the oviposition site. To explain a susceptibility of certain grapevine cultivars and phenological stages of the berries to egg infestations, we analysed and compared the chemical composition of the epicuticular waxes of the berry surface as well as the volatile organic compounds emitted by the berries. Thereby it turned out that the attractiveness to wax extracts decreased during ripening of the berries, highlighting a preference of earlier phenological stages of the berries for oviposition. In addition, grapevine cultivars exhibited variations in their volatile composition. The principle components perceived by female’s antennae could not explain the differentiation between cultivars, suggesting volatiles do not trigger orientation to certain cultivars. Furthermore, a method was developed to measure real-time behavioural response of female moths to volatiles. The setup allowed to quantify the orientation to a volatile source as well as movements of the antennae and ovipositor. They could be linked to the olfactory and gustatory perception of volatiles during the evaluation of suitable host plants for oviposition. In addition, the risk of potential alternative host plants in the vicinity of the vineyard was investigated. This confirmed that L. botrana in particular prefers the stimuli provided by some plants to those of grapevine. Overall, the results suggest that during oviposition, volatiles emitted by the plants and the composition of the plant surface are the most important factors for host plant differentiation.
Production, purification and analysis of novel peptide antibiotics from terrestrial cyanobacteria
(2024)
Cyanobacteria are a known source for bioactive compounds, of which several also show antibiotic activity. In regard to the growing number of multi-resistant pathogens, the search for novel antibiotic substances is of great importance and unexploited sources should be explored. So, this thesis initially dealt with the identification of productive strains, especially within the group of the terrestrial cyanobacteria, which are less well studied than marine and freshwater strains. Amongst these, Chroococcidiopsis cubana, an extremely desiccation and radiation tolerant, unicellular cyanobacterium was found to produce an extracellular antimicrobial metabolite effective against the Gram-positive indicator bacterium Micrococcus luteus as well as the pathogenic yeast Candida auris. However, as the sole identification of a productive cyanobacterium is not sufficient for further analysis and a future production scale-up, the second part of this thesis targeted the identification of compound synthesis prerequisites. As a result, a limitation of nitrogen was shown to be the production trigger, a finding that was used for the establishment of a continuous production system. The increased compound formation was then used for purification and analysis steps. As a second approach, in silico identified bacteriocin gene clusters from C. cubana were cloned and heterologously expressed in Escherichia coli. By this, the bacteriocin B135CC was identified as a strong bacteriolytic agent, active predominantly against the Gram-positive strains Staphylococcus aureus and Mycobacterium phlei. The peptide showed no cytotoxic effects against mouse neuroblastoma (N2a-) cells and a high temperature tolerance up to 60 °C. In order to facilitate the whole project, two standard protocols, specifically adapted for the work with cyanobacteria, were established. First, a method for a quick and easy in vivo vitality estimation of phototrophic cells and second, an approach for a high throughput determination of nitrate concentrations in microalgal cultures. Both methods greatly helped to proceed the main objectives of this work, the first one by simplifying the development of suitable cryopreservation protocols for individual cyanobacteria strains and the second one by accelerating the determination of the optimal nitrate concentration for the production of the antimicrobial compound from C. cubana. In the course of this cultivation optimization, the ability of cyanobacteria to utilize organic carbon sources for an accelerated cell growth was examined in greater detail. It could be shown that C. cubana reaches significantly higher growth rates when mixotrophically cultivated with fructose or glucose. Interestingly, this effect was even further enhanced when light intensity was decreased. Under these low-light conditions, phototrophically cultivated C. cubana cells showed a clearly decreased cell growth. This effect might be extremely useful for a quick and economic preparation of precultures.
The ability to sense and respond to different environmental conditions allows living organisms to adapt quickly to their surroundings. In order to use light as a source of information, plants, fungi, and bacteria employ phytochromes. With their ability to detect far-red and red light, phytochromes constitute a major photoreceptor family. Bacterial phytochromes (BphPs) are composed of an apo-phytochrome and an open-chain tetrapyrrole, the chromophore biliverdin IXα, which mediates the photosensory properties. Depending on the photoexcitation and the quality of the incident light, phytochromes interconvert between two photoconvertible parental states: the red light-absorbing Pr-form and the far-red light-absorbing Pfr-form. In contrast to prototypical phytochromes, with a thermal stable Pr ground state, there is a group of bacterial phytochromes that exhibit dark reversion from the Pr- to the Pfr-form. These special proteins are classified as bathy phytochromes and range across different classes of bacteria. Moreover, the majority of BphPs act as sensor histidine kinases in two-component regulatory systems. The light-triggered conformational change results in the autophosphorylation of the histidine kinase domain and the transphosphorylation of an associated response regulator, inducing a cellular response. Spectroscopic analysis utilizing homologously produced protein identified PaBphP, the histidine kinase of the human opportunistic pathogen Pseudomonas aeruginosa, as a bathy phytochrome. Intensive research on PaBphP revealed evidence that the interconversion between its physiological active and inactive states is influenced by light and darkness rather than far-red and red light. In order to conduct a comprehensive systematic analysis, further bacterial phytochromes were investigated regarding their biochemical and spectroscopic behavior, as well as their autokinase activity. In addition to PaBphP, this work employs the bathy phytochromes AtBphP2, AvBphP2, XccBphP from the non-photosynthetic plant pathogens Agrobacterium tumefaciens, Allorhizobium vitis, Xanthomonas campestris, as well as RtBphP2 from the soil bacterium Ramlibacter tataouinensis. All investigated BphPs displayed a bathy-typical behavior by developing a distinct Pr-form under far-red light conditions and undergoing dark reversion to their Pfr-form. Different Pr/Pfr-fractions can be identified among the BphP populations in varying natural light conditions, including red or blue light. The Pr-form is considered as the active form due to autophosphorylation activity in the heterologously produced phytochromes when exposed to light. In the absence of light, associated with the development of the Pfr-form, the phytochromes exhibited disabled or strongly reduced autokinase activity. Additionally, light-triggered phosphorylation was observed for the response regulator PaAlgB, which is linked to the phytochrome of P. aeruginosa. This study presents the first comparative investigation of numerous bathy phytochromes under identical conditions. The work addressed a gap in the literature by providing quantitative correlation between kinase activity and calculated Pr/Pfr-fractions obtained from spectroscopic measurements. The biological role of PaBphP was partially elucidated through phenotypic characterization employing P. aeruginosa mutant and overexpression strains. The generation of a functional model was possible by considering the postulated functions of the other phytochromes found in the literature. In summary, bathy BphPs are hypothesized to modulate bacterial virulence according to the circadian day/night rhythm of their hosts. The pathogens are believed to reduce their virulence during daylight hours to evade immune and defense reactions, while increasing their virulence during the evening and night, enabling more effective infections.
Functional structures as well as materials provided by nature have always been a great source of inspiration for new technologies. Adapting and improving the discovered concepts, however, demands a detailed understanding of their working principles, while employing natural materials for fabrication tasks requires suitable functionalization and modification.
In this thesis, the white scales of the beetle Cyphochilus are examined in order to reveal unknown aspects of their light transport properties. In addition, the monomer of the material they are made of is utilized for 3D microfabrication.
White beetle scales have been fascinating scientists for more than a decade because they display brilliant whiteness despite their small thickness and the low refractive index contrast. Their optical properties arise from highly efficient light scattering within the disordered intra-scale network structure.
To gain a better understanding of the scattering properties, several previous studies have investigated the light transport and its connection to the structural anisotropy with the aid of diffusion theory. While this framework allows to relate the light scattering to macroscopic transport properties, an accurate determination of the effective refractive index of the structure is required. Due to its simplicity, the Maxwell-Garnett mixing rule is frequently used for this task, although its constraint to particle and feature sizes much smaller than the wavelength is clearly violated for the scales.
To provide a correct calculation of the effective refractive index, here, finite-difference time-domain simulations are used to systematically examine the impact of size effects on the effective refractive index. Deploying this simulation approach, the Maxwell-Garnett mixing rule is shown to break down for large particles. In contrast, it is found that a quadratic polynomial function describes the effective refractive index in close approximation, while its coefficients can be obtained from an empirical linear function. As a result, a simple mixing rule is reported that unambiguously surpasses classical mixing rules when composite media containing large feature sizes are considered. This is important not only for the accurate description of white beetle scales, but also for other turbid media, such as biological tissues in opto-biomedical diagnostics.
Describing light transport by means of diffusion theory moreover neglects any coherent effects, such as interference. Hence, their impact on the generation of brilliant whiteness is currently unknown. To shed a light on their role, spatial- and time-resolved light scattering spectromicroscopy is applied to investigate the scales and a model structure of them based on disordered Bragg stacks. For both structures the occurrence of weakly localized photonic modes, i.e., closed scattering loops, is observed, which is further verified in accompanying simulations. As shown in this thesis, leakage from these random photonic modes contributes at least 20% to the overall reflected light. This reveals the importance of coherent effects for a complete description of the underlying light transport properties; an aspect that is entirely missing in the purely diffusive transport presumed so far. Identifying the importance of weak localization for the generation of brilliant whiteness paves the way to further enhance the design of efficient optical scattering media, an issue that recently drawn great attention.
Unlike their plant-based counterparts, rigid carbohydrates, such as chitin, are currently unavailable for 3D microfabrication via direct laser writing, despite their great significance in the animal kingdom for the construction of functional microstructures. To overcome this gap, the monomeric unit of chitin, N-acetyl-D-glucosamine, is here functionalized to serve as a photo-crosslinkable monomer in a non-hydrogel photoresist. Since all previous photoresists based on animal carbohydrates are in the form of hydrogel formulations, a new group of photoresists is established for direct laser writing.
Moreover, it is exhibited that the sensitization effect, previously used only in the context of UV curing, can be successfully transferred to direct laser writing to increase the maximum writing speed. This effect is based on the beneficial combination of two photoinitiators.
In this, one photoinitiator is an efficient crosslinking agent for the monomer used, but a rather poor two-photon absorber. The other photoinitiator (called sensitizer) possesses, conversely, a much higher two-photon absorption coefficient at the applied wavelength but is not well suited as a crosslinking agent. In combination, the energy absorbed by the sensitizer is passed to the photoinitiator, resulting in the formation of radicals needed to start the polymerization. As this greatly increases the rate at which the photoinitiator is radicalized, resists containing a photoinitiator and a sensitizer are shown to outperform resists containing only one of the components. Deploying the sensitization effect in direct laser writing therefore offers a simple way to individually tune the crosslinking ability and the two-photon absorption properties by combining existing compounds, compared to the costly chemical synthesis of novel, customized photoinitiators.
In contrast to motorbike tyres, whose friction during cornering has to be as high as possible, the desired effect in skiing is the opposite, that of low friction. The reduced friction between skis and ice or snow is made possible by a film of meltwater that forms as a function of friction power. To support this friction mechanism, skis are waxed with different waxes in both hobby and professional sports, depending on a variety of conditions. Waxes with fluorine additives show best performance in most conditions, corresponding to the lowest friction coefficients. However, for health and environmental reasons, the International Ski Federation (FIS) and the Biathlon Un-ion (IBU) have imposed a complete ban on fluorine additives at all FIS races and IBU events with effect from the 2023/2024 season. As a result, wax manufacturers are required to develop and extensively test fluorine-free waxes in order to remain competitive.
Traditional tests take place either indoors or outdoors in the field. Athletes, who complete a particular distance and whose time is measured, also note the impres-sions that the prepared skis provide to the skiers. The time and cost involved in nu-merous individual tests is a drawback, and the presence of only a single type of snow in the hall or field, air resistance, changing environmental conditions and var-iations in the athlete's movement, limit the depth of information. For the need of re-ducing the time-consuming procedure of indoor and outdoor tests, a tribometer of-fers a solution where friction measurements can be performed on a laboratory scale. Due to the consistent adjustable conditions such as temperature, speed and load applied to the friction partners, scientific studies can be carried out with reduced dis-turbance variables. At present, the tribometric results of laboratory instruments for predicting friction values do not translate into application in practice. The reasons for this are the compromises that have to be made in the design of the tribometers.
This work reviews the existing tribometers for their operating conditions and con-firms the need for a scientific method of characterising different waxes. In order to fill the gap between friction results obtained in laboratory tests which cannot yet be used in the selection of waxes, and traditional field tests, this thesis is dedicated to the methodical design and manufacture of a linear tribometer capable of measuring friction between a ski base made of UHMWPE (ultra high molecular weight polyeth-ylene) and an ice sample. The tribometer provides for the first time results that allow differentiating be-tween different modified waxes with regard to their running performance. Friction-influencing factors such as speed, temperature and the surface pressure below the ski base can be adjusted within the range relevant for ski sports. Furthermore, the laboratory-scale test stand, which is located in a cold chamber, is capable of ac-commodating not only typical ski jumping base lengths and widths, but also cross-country and alpine ski bases. To verify the tribometer, a ski base is treated with three waxes of different fluorine content and measured comparatively. With a minimum of 95% confidence, the friction differences between the tested waxes depending on their fluorine content is validated and proven at the end of this work.
Pervasive human impacts rapidly change freshwater biodiversity. Frequently recorded exceedances of regulatory acceptable thresholds by pesticide concentrations suggest that pesticide pollution is a relevant contributor to broad-scale trends in freshwater biodiversity. A more precise pre-release Ecological Risk Assessment (ERA) might increase its protectiveness, consequently reducing the likelihood of unacceptable effects on the environment. European ERA currently neglects possible differences in sensitivity between exposed ecosystems. If the taxonomic composition of assemblages would differ systematically among certain types of ecosystems, so might their sensitivity toward pesticides. In that case, a single regulatory threshold would be over- or underprotective.
In this thesis, we evaluate (1) whether the assemblage composition of macroinvertebrates, diatoms, fishes, and aquatic macrophytes differs systematically between the types of a European river typology system, and (2) whether these taxonomical differences engender differences in sensitivity toward pesticides. While a selection of ecoregions is available for Europe, only a single typology system that classifies individual river segments is available at this spatial scale - the Broad River Types (BRT).
In the first two papers of this thesis, we compiled and prepared large databases of macroinvertebrate (paper one), diatom, fish, and aquatic macrophyte (paper two) occurrences throughout Europe to evaluate whether assemblages are more similar within than among BRT types. Additionally, we compared its performance to that of different ecoregion systems. We employed multiple tests to evaluate the performances, two of which were also designed in the studies. All typology systems failed to reach common quality thresholds for the evaluated metrics for most taxa. Nonetheless, performance differed markedly between typology systems and taxa, with the BRT often performing worst. We showed that currently available, European freshwater typology systems are not well suited to capture differences in biotic communities and suggest several possible amelioration.
In the third study, we evaluated whether ecologically meaningful differences in sensitivity exist between BRT types. To this end, we predicted the sensitivity of macroinvertebrate assemblages across Europe toward Atrazine, copper, and Imidacloprid using a hierarchical species sensitivity distribution model. The predicted assemblage sensitives differed only marginally between BRT types. The largest difference between
median river type sensitivities was a factor of 2.6, which is far below the assessment factor suggested for such models (6), as well as the factor of variation commonly observed between toxicity tests of the same species-compound pair (7.5 for copper). Our results don’t support the notion that a type-specific ERA might improve the accuracy of thresholds. However, in addition to the taxonomic composition the bioavailability of chemicals, the interaction with other stressors, and the sensitivity of a given species might differ between river types.
Mechanistic disease spread models for different vector borne diseases have been studied from the 19th century. The relevance of mathematical modeling and numerical simulation of disease spread is increasing nowadays. This thesis focuses on the compartmental models of the vector-borne diseases that are also transmitted directly among humans. An example of such an arboviral disease that falls under this category is the Zika Virus disease. The study begins with a compartmental SIRUV model and its mathematical analysis. The non-trivial relationship between the basic reproduction number obtained through two methods have been discussed. The analytical results that are mathematically proven for this model are numerically verified. Another SIRUV model is presented by considering a different formulation of the model parameters and the newly obtained model is shown to be clearly incorporating the dependence on the ratio of mosquito population size to human population size in the disease spread. In order to incorporate the spatial as well as temporal dynamics of the disease spread, a meta-population model based on the SIRUV model was developed. The space domain under consideration are divided into patches which may denote mutually exclusive spatial entities like administrative areas, districts, provinces, cities, states or even countries. The research focused only on the short term movements or commuting behavior of humans across the patches. This is incorportated in the multi-patch meta-population model using a matrix of residence time fractions of humans in each patches. Mathematically simplified analytical results are deduced by which it is shown that, for an exemplary scenario that is numerically studied, the multi-patch model also admits the threshold properties that the single patch SIRUV model holds. The relevance of commuting behavior of humans in the disease spread has been presented using the numerical results from this model. The local and non-local commuting are incorporated into the meta-population model in a numerical example. Later, a PDE model is developed from the multi-patch model.
Cancer, a complex and multifaceted disease, continues to challenge the boundaries of biomedical research. In this dissertation, we explore the complexity of cancer genesis, employing multiscale modeling, abstract mathematical concepts such as stability analysis, and numerical simulations as powerful tools to decipher its underlying mechanisms. Through a series of comprehensive studies, we mainly investigate the cell cycle dynamics, the delicate balance between quiescence and proliferation, the impact of mutations, and the co-evolution of healthy and cancer stem cell lineages. The introductory chapter provides a comprehensive overview of cancer and the critical importance of understanding its underlying mechanisms. Additionally, it establishes the foundation by elucidating key definitions and presenting various modeling perspectives to address the cancer genesis. Next, cell cycle dynamics have been explored, revealing the temporal oscillatory dynamics that govern the progression of cells through the cell cycle.
The first half of the thesis investigates the cell cycle dynamics and evolution of cancer stem cell lineages by incorporating feedback regulation mechanisms. Thereby, the pivotal role of feedback loops in driving the expansion of cancer stem cells has been thoroughly studied, offering new perspectives on cancer progression. Furthermore, the mathematical rigor of the model has been addressed by deriving wellposedness conditions, thereby strengthening the reliability of our findings and conclusions. Then, expanding our modeling scope, we explore the interplay between quiescent and proliferating cell populations, shedding light on the importance of their equilibrium in cancer biology. The models developed in this context offer potential avenues for targeted cancer therapies, addressing perspective cell populations critical for cancer progression. The second half of the thesis focuses on multiscale modeling of proliferating and quiescent cell populations incorporating cell cycle dynamics and the extension thereof with mutation acquisition. Following rigorous mathematical analysis, the wellposedness of the proposed modeling frameworks have been studied along with steady-state solutions and stability criteria.
In a nutshell, this thesis represents a significant stride in our understanding of cancer genesis, providing a comprehensive view of the complex interplay between cell cycle dynamics, quiescence, proliferation, mutation acquisition, and cancer stem cells. The journey towards conquering cancer is far from over. However, this research provides valuable insights and directions for future investigation, bringing us closer to the ultimate goal of mitigating the impact of this formidable disease.
In this thesis, material removal mechanisms in grinding are investigated considering a gritworkpiece interaction as well as a grinding-wheel workpiece interaction. In grit-workpiece interaction in a micrometer scale, single grit scratch experiments were performed to investigate material removal mechanism in grinding namely rubbing, plowing, and cutting. Experiments performed were analyzed based on material removal, process forces and specific energy. A finite element model is developed to simulate a single-grit scratch process. As part of the development of the finite element scratch model a 2D and 3D model is developed. A 2D model is utilized to test
material parameters and test various mesh discretizational approaches. A 3D model undertaking the tested material parameters from the 2D model is developed and is tested against experimental results for various mesh discretization. The simulation model is validated based on process forces and ground topography from experiments. The model is also further scaled to simulate multiple grit-workpiece interaction validated against experimental results. As a final step, simulation models are developed to simulate material removal, due to the interaction of grinding wheel and workpiece. A developed virtual grinding wheel topographical model is employed to display
an approach, to upscale a grinding process from grit-workpiece interaction to wheel-workpiece
interaction. In conclusion, practical conclusions drawn and scope for future studies are derived
based on the developed simulation models.
Climate change will have severe consequences on Eastern Boundary Upwelling Systems (EBUS). They host the largest fisheries in the world supporting the life of millions of people due to their tremendous primary production. Therefore, it is of utmost importance to better understand predicted impacts like alternating upwelling intensities and light impediment on the structure and the trophic role of protistan plankton communities as they form the basis of the food web. Numerical models estimate the intensification of the frequency in eddy formation. These ocean features are of particular importance due to their influence on the distribution and diversity of plankton communities and the access to resources, which are still not well understood even to the present day. My PhD thesis entails two subjects conducted during large-scaled cooperation projects REEBUS (Role of Eddies in Eastern Boundary Upwelling Systems) and CUSCO (Coastal Upwelling System in a Changing Ocean).
Subject I of my study was conducted within the multidisciplinary framework REEBUS to investigate the influence of eddies on the biological carbon pump in the Canary Current System (CanCS). More specifically, the aim was to find out how mesoscale cyclonic eddies affect the regional diversity, structure, and trophic role of protistan plankton communities in a subtropical oligotrophic oceanic offshore region.
Samples were taken during the M156 and M160 cruises in the Atlantic Ocean around Cape Verde during July and December 2019, respectively. Three eddies with varying ages of emergence and three water layers (deep chlorophyll maximum DCM, right beneath the DCM and oxygen minimum zone OMZ) were sampled. Additional stations without eddy perturbation were analyzed as references. The effect of oceanic mesoscale cyclonic eddies on protistan plankton communities was analyzed by implementing three approaches. (i) V9 18S rRNA gene amplicons were examined to analyze the diversity and structure of the plankton communities and to infer their role in the biological carbon pump. (ii) By assigning functional traits to taxonomically assigned eDNA sequences, functional richness and ecological strategies (ES) were determined. (iii) Grazing experiments were conducted to assess abundance and carbon transfer from prokaryotes to phagotrophic protists.
All three eddies examined in this study differed in their ASV abundance, diversity, and taxonomic composition with the most pronounced differences in the DCM. Dinoflagellates were the most abundant taxa in all three depth layers. Other dominating taxa were radiolarians, Discoba and haptophytes. The trait-approach could only assign ~15% of all ASVs and revealed in general a relatively high functional richness. But no unique ES was determined within a specific eddy. This indicates pronounced functional redundancy, which is recognized to be correlated with ecosystem resilience and robustness by providing a degree of buffering capacity in the face of biodiversity loss. Elevated microbial abundances as well as bacterivory were clearly associated to mesoscale eddy features, albeit with remarkable seasonal fluctuations. Since eddy activity is expected to increase on a global scale in future climate change scenarios, cyclonic eddies could counteract climate change by enhancing carbon sequestration to abyssal depths. The findings demonstrate that cyclonic eddies are unique, heterogeneous, and abundant ecosystems with trapped water masses in which characteristic protistan plankton develop as the eddies age and migrate westward into subtropical oligotrophic offshore waters. Therefore, eddies influence regional protistan plankton diversity qualitatively and quantitatively.
Subject II of my PhD project contributed to the CUSCO field campaign to identify the influence of varying upwelling intensities in combination with distinct light treatments on the whole food web structure and carbon pump in the Humboldt Current System (HCS) off Peru. To accomplish such a task, eight offshore-mesocosms were deployed and two light scenarios (low light, LL; high light, HL) were created by darkening half of the mesocosms. Upwelling was simulated by injecting distinct proportions (0%, 15%, 30% and 45%) of collected deep-water (DW) into each of the moored mesocosms. My aim was to examine the changes in diversity, structure, and trophic role of protistan plankton communities for the induced manipulations by analyzing the V9 18S rRNA gene amplicons and performing short-term grazing experiments.
The upwelling simulations induced a significant increase in alpha diversity under both light conditions. In austral summer, reflected by HL conditions, a generally higher alpha diversity was recorded compared to the austral winter simulation, instigated by LL treatment. Significant alterations of the protistan plankton community structure could likewise be observed. Diatoms were associated to increased levels of DW addition in the mimicked austral winter situation. Under nutrient depletion, chlorophytes exhibited high relative abundances in the simulated austral winter scenario. Dinoflagellates dominated the austral summer condition in all upwelling simulations. Tendencies of reduced unicellular eukaryotes and increased prokaryotic abundances were determined under light impediment. Protistan-mediated mortality of prokaryotes also decreased by ~30% in the mimicked austral winter scenario.
The findings indicate that the microbial loop is a more relevant factor in the structure of the food web in austral summer and is more focused on the utilization of diatoms in austral winter in the HCS off Peru. It was evident that distinct light intensities coupled with multiple upwelling scenarios could lead to alterations in biochemical cycles, trophic interactions, and ecosystem services. Considering the threat of climate change, the predicted relocation of EBUS could limit primary production and lengthen the food web structure with severe socio-economic consequences.
Mixed Isogeometric Methods for Hodge–Laplace Problems induced by Second-Order Hilbert Complexes
(2024)
Partial differential equations (PDEs) play a crucial role in mathematics and physics to describe numerous physical processes. In numerical computations within the scope of PDE problems, the transition from classical to weak solutions is often meaningful. The latter may not precisely satisfy the original PDE, but they fulfill a weak variational formulation, which, in turn, is suitable for the discretization concept of Finite Elements (FE). A central concept in this context is the
well-posed problem. A class of PDE problems for which not only well-posedness statements but also suitable weak formulations are known are the so-called abstract Hodge–Laplace problems. These can be derived from Hilbert complexes and constitute a central aspect of the Finite Element Exterior Calculus (FEEC).
This thesis addresses the discretization of mixed formulations of Hodge-Laplace problems, focusing on two key aspects. Firstly, we utilize Isogeometric Analysis (IGA) as a specific paradigm for discretization, combining geometric representations with Non-Uniform Rational B-Splines (NURBS) and Finite Element discretizations.
Secondly, we primarily concentrate on mixed formulations exhibiting a saddle-point structure and generated from Hilbert complexes with second-order derivative operators. We go beyond the well-known case of the classical de Rham
complex, considering complexes such as the Hessian or elasticity complex. The BGG (Bernstein–Gelfand–Gelfand) method is employed to define and examine these second-order complexes. The main results include proofs of discrete well-posedness and a priori error estimates for two different discretization approaches. One approach demonstrates, through the introduction of a Lagrange multiplier, how the so-called isogeometric discrete differential forms can be reused.
A second method addresses the question of how standard NURBS basis functions, through a modification of the mixed formulation, can also lead to convergent procedures. Numerical tests and examples, conducted using MATLAB and the open-source software GeoPDEs, illustrate the theoretical findings. Our primary application extends to linear elasticity theory, extensively
discussing mixed methods with and without strong symmetry of the stress tensor.
The work demonstrates the potential of IGA in numerical computations, particularly in the challenging scenario of second-order Hilbert complexes. It also provides insights into how IGA and FEEC can be meaningfully combined, even for non-de Rham complexes.
The aim of this thesis is to introduce an equilibrium insurance market model and study its properties and possible applications in risk class management.
First, an insurance market model based on an equilibrium approach is developed. Depending on the premium, the insured will choose the amount of coverage they buy in order to maximize their expected utility. The behavior of the insurer in different market regimes is then compared. While the premiums in markets with perfect competition are calculated in order to make no profit at all, insurers try to maximize their margins in a monopolistic market.
In markets modeled in this way several phenomena become evident. Perhaps the most important one is the so-called push-out effect. When customers with different attributes are insured together, insurance might become so expensive for one type of customers that those agents are better off with buying no insurance at all. The push-out effect was already shown for theoretical examples in the literature. We present a comprehensive analysis of the equilibrium insurance market model and the push-out effect for different insurance products such as life, health and disability insurance contracts using real-life data from different sources. In a concluding chapter we formulate indicators when a push-out can be expected and when not.
Machine learning regression approaches such as neural networks have gained vast popularity in recent years. The exponential growth of computing power has enabled larger and more evolved networks that can perform increasingly complex tasks. In our feasibility study about the use of neural networks in the regression of equilibrium insurance premiums it is shown that this regression is quite robust and the risk of overfitting can almost be excluded -- as long as the regression is performed on at least a few thousand data points.
Grouping customers of different risk types into contracts is important for the stability and the robustness of an insurance market. This motivates the study of the optimal assignment of risk classes into contracts, also known as rating classes. We provide a theoretical framework that makes use of techniques from different mathematical fields such as non-linear optimization, convex analysis, herding theory, game theory and combinatorics. In addition, we are able to show that the market specifications have a large impact on the optimal allocation of risk classes to contracts by the insurer. However, there does not need to be an optimal risk class assignment for each of these specifications.
To address this issue, we present two different approaches, one more theoretical and another that can easily be implemented in practice. An extension of our model to markets with capacity constraints rounds off the topic and extends the applicability of our approach.
Understanding human crowd behaviour has been an intriguing topic of interdisciplinary research in recent decades. Modelling of crowd dynamics using differential equations is an indispensable approach to unraveling the various complex dynamics involved in such interacting particle systems. Numerical simulation of pedestrian crowd via these mathematical models allows us to study different realistic scenarios beyond the limitations of studies via controlled experiments.
In this thesis, the main objective is to understand and analyse the dynamics in a domain shared by both pedestrians and moving obstacles. We model pedestrian motion by combining the social force concept with the idea of optimal path computation. This leads to a system of ordinary differential equations governing the dynamics of individual pedestrians via the interaction forces (social forces) between them. Additionally, a non-local force term involving the optimal path and desired velocity governs the pedestrian trajectory. The optimal path computation involves solving a time-independent Eikonal equation, which is coupled to the system of ODEs. A hydrodynamic model is developed from this microscopic model via the mean-field limit.
To consider the interaction with moving obstacles in the domain, we model a set of kinematic equations for the obstacle motion. Two kinds of obstacles are considered - "passive", which move in their predefined trajectories and have only a one-way interaction with pedestrians, and "dynamic", which have a feedback interaction with pedestrians and have their trajectories changing dynamically. The coupled model of pedestrians and obstacles is used to discern pedestrian collision avoidance behaviour in different computational scenarios in a long rectangular domain. We observe that pedestrians avoid collisions through route choice strategies that involve changes in speed and path. We extend this model to consider the interaction between pedestrians and vehicular traffic. We appropriately model the interactions of vehicles, following lane traffic, based on the car-following approach. We observe how the deceleration and braking mechanism of vehicles is executed at pedestrian crossings depending on the right of way on the roads.
As a second objective, we study the disease contagion in moving crowds. We consider the influence of the crowd motion in a complex dynamical environment on the course of infection of pedestrians. A hydrodynamic model for multi-group pedestrian flow is derived from the kinetic equations based on a social force model. It is coupled along with an Eikonal equation to a non-local SEIS contagion model for disease spread. Here, apart from the description of local contacts, the influence of contact times has also been modelled. We observe that the nature of the flow and the geometry of the domain lead to changes in density which affect the contact time and, consequently, the rate of spread of infection.
Finally, the social force model is compared to a variable speed based rational behaviour pedestrian model. We derive a hierarchy of the heuristics-based model from microscopic to macroscopic scales and numerically investigate these models in different density scenarios. Various numerical test cases are considered, including uni- and bi-directional flows and scenarios with and without obstacles. We observe that in low-density scenarios, collision avoidance forces arising from the behavioural heuristics give valid results. Whereas in high-density scenarios, repulsive force terms are essential.
The numerical simulations of all the models are carried out using a mesh-free particle method based on least square approximations. The meshfree numerical framework provides an efficient and elegant way to handle complex geometric situations involving boundaries and stationary or moving obstacles.
Lubricated tribological contact processes are important in both nature and in many technical applications. Fluid lubricants play an important role in contact processes, e.g. they reduce friction and cool the contact zone. The fundamentals of lubricated contact processes on the atomistic scale are, however, today not fully understood. A lubricated contact process is defined here as a process, where two solid bodies that are in close proximity and eventually in parts in direct contact, carry out a relative motion, whereat the remaining volume is submersed by a fluid lubricant. Such lubricated contact processes are difficult to examine experimentally. Atomistic simulations are an attractive alternative for investigating the fundamentals of such processes. In this work, molecular dynamics simulations were used for studying different elementary processes of lubricated tribological contacts. A simplified, yet realistic simulation setup was developed in this work for that purpose using classical force fields. In particular, the two solid bodies were fully submersed in the fluid lubricant such that the squeeze-out was realistically modeled. The velocity of the relative motion of the two solid bodies was imposed as a boundary condition. Two types of cases were considered in this work: i) a model system based on synthetic model substances, which enables a direct, but generic, investigation of molecular interaction features on the contact process; and ii) real substance systems, where the force fields describe specific real substances. Using the model system i), also the reproducibility of the findings obtained from the computer experiments was critically assessed. In most cases, also the dry reference case was studied. Both mechanical and thermodynamic properties were studied -- focusing on the influence of lubrication. The following properties were studied: The contact forces, the coefficient of friction, the dislocation behavior in the solid, the chip formation and the formation of the groove, the squeeze-out behavior of the fluid in the contact zone, the local temperature and the energy balance of the system, the adsorption of fluid particles on the solid surfaces, as well as the formation of a tribofilm. Systematic studies were carried out for elucidating the influence of the wetting behavior, the influence of the molecular architecture of the lubricant, and the influence of the lubrication gap height on the contact process. As expected, the presence of a fluid lubricant reduces the temperature in the vicinity of the contact zone. The presence of the lubricant is, moreover, found to have a significant influence on the friction and on the energy balance of the process. The presence of a lubricant reduces the coefficient of friction compared to a dry case in the starting phase of a contact process, while lubricant molecules remain in the contact zone between the two solid bodies. This is a result of an increased normal and slightly decreased tangential force in the starting phase. When the fluid molecules are squeezed out with ongoing contact time and the contact zone is essentially dry, the coefficient of friction is increased by the presence of a fluid compared to a dry case. This is attributed to an imprinting of individual fluid particles into the solid surface, which is energetically unfavorable. By studying the contact process in a wide range of gap height, the entire range of the Stribeck curve is obtained from the molecular simulations. Thereby, the three main lubrication regimes of the Stribeck curve and their transition regions are covered, namely boundary lubrication (significant elastic and plastic deformation of the substrate), mixed lubrication (adsorbed fluid layers dominate the process), and hydrodynamic lubrication (shear flow is set up between the surface and the asperity). The atomistic effects in the different lubrication regimes are elucidated. Notably, the formation of a tribofilm is observed, in which lubricant molecules are immersed into the metal surface. The formation of a tribofilm is found to have important consequences for the contact process. The work done by the relative motion is found to mainly dissipate and thereby heat up the system. Only a minor part of the work causes plastic deformation. Finally, the assumptions, simplifications, and approximations applied in the simulations are critically discussed, which highlights possible future work.
Reactive absorption with amines is the most important technique for the removal of CO2
from gas streams, e.g. from flue gas, natural gas or off-gas from the cement industry.
In this work a rigorous simulation model for the absorption and desorption of CO2 with
an amine-containing solvent is validated using data from pilot plants of various sizes.
This model was then coupled with a detailed simulation of a coal-fired power plant.
The power generation efficiency drop with CO2 capture was determined and process
parameters in the power plant and separation process were optimized. It was shown
that the high energy demand of CO2 separation significantly reduces power generation
efficiencies, which underlines the need for improvements. This can be achieved by better
solvents or by advanced process designs. In this work such improved CO2 separation
processes are described and evaluated by detailed simulation studies.
In order to develop detailed rigorous simulation models for reactive absorption with novel
solvent systems, a precise knowledge of the liquid phase reaction kinetics is necessary.
There are well established techniques for measuring species distributions in equilibirated
aqueous amine solutions by NMR spectrosopy. However, the existing NMR techniques
cannot be used for monitoring fast reactions in these solutions. Therefore, in this work
a novel temperature-controlled micro-reactor NMR probe head was developed which
enables studying reaction kinetics with time constants in the range of seconds.
On this basis, modern solvent systems for CO2 absorption can be characterized and
the scale-up of separation process for future plants can be accompanied using rigorous
process simulation.
Distributed Optimization of Constraint-Coupled Systems via Approximations of the Dual Function
(2024)
This thesis deals with the distributed optimization of constraint-coupled systems. This problem class is often encountered in systems consisting of multiple individual subsystems, which are coupled through shared limited resources. The goal is to optimize each subsystem in a distributed manner while still ensuring that system-wide constraints are satisfied. By introducing dual variables for the system-wide constraints the system-wide problem can be decomposed into individual subproblems. These resulting subproblems can then be coordinated by iteratively adapting the dual variables. This thesis presents two new algorithms that exploit the properties of the dual optimization problem. Both algorithms compute a quadratic surrogate function of the dual function in each iteration, which is optimized to adapt the dual variables. The Quadratically Approximated Dual Ascent (QADA) algorithm computes the surrogate function by solving a regression problem, while the Quasi-Newton Dual Ascent (QNDA) algorithm updates the surrogate function iteratively via a quasi-Newton scheme. Both algorithms employ cutting planes to take the nonsmoothness of the dual function into account. The proposed algorithms are compared to algorithms from the literature on a large number of different benchmark problems, showing superior performance in most cases. In addition to general convex and mixed-integer optimization problems, dual decomposition-based distributed optimization is applied to distributed model predictive control and distributed K-means clustering problems.
Since their introduction, robots have primarily influenced the industrial world, providing new opportunities and challenges for humans and machinery. With the introduction of lightweight robots and mobile robot platforms, the field of robot applications has been expanded, diversified, and brought closer to society. The increased degree of digitalization and the personalization of goods and products require an enhanced and flexible robot deployment by operating several multi-robot systems along production processes, industrial applications, assembly and packaging lines, transport systems, etc.
Efficient and safe robot operation relies on successful task planning followed by the computation and execution of task-performing motion trajectories. This thesis addresses these issues by developing, implementing, and validating optimization-based methods for task and trajectory planning in robotics, considering certain optimality and performance criteria. The focus is mainly on the time optimality of the presented approaches with respect to both execution and computation time without compromising safe robot use.
Driven by a systematic approach, the basis for the algorithm development is established first by modeling the kinematics and dynamics of the considered robots and identifying required dynamic parameters. In a further step, time-optimal task and trajectory planning algorithms for a single robotic arm are developed. Initially, a hierarchical approach is introduced consisting of two decoupled optimization-based control policies, a binary problem for task planning, and a continuous model predictive trajectory planning problem. The two layers of the hierarchical structure are then merged into a monolithic layer, resulting in a hybrid structure in the form of a mixed-integer optimization problem for inherent task and trajectory planning.
Motivated by a multi-robot deployment, the hierarchical control structure for time-optimal task and trajectory planning is extended for the case of a two-arm robotic system with highly overlapping operational spaces, leading to challenging robot motions with high inter-robot collision potential. To this end, a novel predictive approach for collision avoidance is proposed based on a continuous approximation of the robot geometry, resulting in a nonlinear optimization problem capable of online applications with real-time requirements. Towards a mobile and flexible robot platform, a model predictive path-following controller for an omnidirectional mobile robot is introduced. Here, a time-minimal approach is also applied, which consists of the robot following a given parameterized path as accurately as possible and at maximum speed.
The performance of the proposed algorithms and methods is experimentally analyzed and validated under real conditions on robot demonstrators. Implementation details, including the resulting hardware and software architecture, are presented, followed by a detailed description of the results. Concrete and industry-oriented demonstrators for integrating robotic arms in existing manual processes and the indoor navigation of a mobile robot complete the work.
Aflatoxins, a group of mycotoxins produced by various mold species within the genus Aspergillus, have been extensively investigated for their potential to contaminate food and feed, rendering them unfit for consumption. Nevertheless, the role of aflatoxins as environmental contaminants in soil, which represents their natural habitat, remains a relatively unexplored area in aflatoxin research. This knowledge gap can be attributed, in part, to the methodological challenges associated with detecting aflatoxins in soil. The main objective of this PhD project was to develop and validate an analytical method that allows monitoring of aflatoxins in soil, and scrutinize the mechanisms and extent of occurrence of aflatoxins in soil, the processes governing their dissipation, and their impact on the soil microbiome and associated soil functions. By utilizing an efficient extraction solvent mixture comprising acetonitrile and water, coupled with an ultrasonication step, recoveries of 78% to 92% were achieved, enabling reliable determination of trace levels in soil ranging from 0.5 to 20 µg kg-1. However, in a field trial conducted in a high-risk model region for aflatoxin contamination in Sub-Saharan Africa, no aflatoxins were detected using this procedure, underscoring the complexities of field monitoring. These challenges encompassed rapid degradation, spatial heterogeneity, and seasonal fluctuations in aflatoxin occurrence. Degradation experiments revealed the importance of microbial and photochemical processes in the dissipation of aflatoxins in soil with half-lives of 20 - 65 days. The rate of dissipation was found to be influenced by soil properties, most notably soil texture and the initial concentration of aflatoxins in the soil. An exposure study provided evidence that aflatoxins do not pose a substantial threat to the soil microbiome, encompassing microbial biomass, activity, and catabolic functionality. This was particularly evident in clayey soils, where the toxicity of aflatoxins diminished significantly due to their strong binding to clay minerals. However, several critical questions remain unanswered, emphasizing the necessity for further research to attain a more comprehensive understanding of the ecological importance of aflatoxins. Future research should prioritize the challenges associated with field monitoring of aflatoxins, elucidate the mechanisms responsible for the dissipation of aflatoxins in soil during microbial and photochemical degradation, and investigate the ecological consequences of aflatoxins in regions heavily affected by aflatoxins, taking into account the interactions between aflatoxins and environmental and anthropogenic stressors. Addressing these questions contributes to a comprehensive understanding of the environmental impact of aflatoxins in soil, ultimately contributing to more effective strategies for aflatoxin management in agriculture.