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The existence of large deposit of crude oil in the Nigerian Niger-Delta accords the region a strategic position in the country’s economy. However, activities associated with the oil and gas industry have resulted in extensive and in some instances indelible damages on the ecosystems. The destructive effect of hydrocarbon on bionetwork necessitated this study that aimed at evaluating the potential of adopting microbial and biosurfactant technology as tools for bioremediation. The research involved gas chromatography monitoring of hydrocarbon degradation in polluted soil, microbiological/molecular identification of hydrocarbon degraders and the evaluation of biosurfactant production by indigenous bacteria. The performance of four treatments involving; co-treatment with mixed bacterial consortium and close-to-nature surfactants (Bioversal QF and Bioversal UK), treatments with mixed bacteria culture, single bacteria culture and treatment with close-to-nature surfactants only were evaluated for the mineralization of hydrocarbons contained in 500g of 2% crude oil contaminated soil supplemented with NaH₂PO*₄2HO₂, KHP₂O₄ and NHC₄l as nutrient sources over a period of 20 weeks. Six indigenous biosurfactant producing and/or hydrocarbon degrading bacteria strains were isolated namely: Pseudomonas aeruginosa, Bacillus sp, Achromobacter sp, Stenotrophonas sp, Lysinibacillus sp. and Delftia sp. Molecular characterization of sequenced polymerase chain reaction products of these cultured bacteria using Nucleotide Basic Local Alignment Search Tool confirmed close relationships ranging from 98.83% to 100% with those on the NCBI databank. Co-treatment with mixed bacteria culture and Bioversal UK/Bioversal QF yielded synergetic impact that enhanced 73.35% and 71.52% degradation of total petroleum hydrocarbon respectively. Treatments with close-to-nature surfactants and with mix bacterial culture recorded 53.61% and 54.58%. The use of single bacteria strains resulted in the mineralization of 46% - 62.26% total petroleum hydrocarbon while their use as a consortium yielded 54%. Liquid chromatography-Mass spectrometry assessment of extracellular polymeric substances produced by cultured bacteria strains indicated the presence of rhamnolipids (L-rhamnosyl-3-hydroxydecanoyl-3-hydroxydecanoic acid with a mass of 504.654 Da) and lipopeptides (2-(Hydroxymethyl) phenyl 6-O-palmitoyl-β-D-glucopyranoside with a mass of 524.687 Da). Extracellular polymeric substances produced yielded emulsion index ranging from 70.70% to 75% and 39% to 65% with crude oil and heptane respectively. EPS yields ranging from 1.34 g/ml to 1.5 g/ml were recorded.
Today, urban conservation scholarship calls for case studies that problematise universal conservation principles in local planning circumstances, particularly in countries from which modern conservation has not originated. In this series of workshops, we discuss singularities of urban conservation and the protection of historic urban areas with local experts who have been directly involved in processes of putting conservation policy documents into practice. We discuss how the planned goals of conservation projects are influenced by unplanned factors such as war, economic and political instability, inter-organisational conflicts, and natural hazards. The discussed cases represent cities with non-western cultural backgrounds that are geographically and culturally interconnected. By discussing urban conservation issues in Ankara, Baghdad, Tehran, Shiraz, Yazd, Kerman, Herat, and Mumbai, we aim to reflect on the functionality of mainstream conservation approaches in local conditions. The speakers share their local insight into obstacles of realising the international conservation models under rapidly changing natural and socio-political conditions. The workshops' moderators are outstanding young academics who have a deep understanding of the discussed issues and have co-planned the sessions with the speakers. This series of events is cooperatively organised by the Chair Urban Management and the DFG Training Group 1913, "Cultural and Technological Significance of Historic Buildings" in the framework of the DFG project, Assembling Iran's Urban Heritage Conservation Policy and Practice: Problematised in Tehran.
Machine learning is a field that has been the object of study of many researchers around the globe during the last decades. Very often to solve machine learning challenges like classification problems for example, one needs to train an artificial neural network. To train this network a certain loss function has to be minimized. There is a ubiquitous approach to achieve this which consists of using variants of the stochastic gradient descent combined with the backpropagation algorithm. In our work, we aimed at testing a rather non-conventional scheme consisting of making use of the solvers a software called AMPL offers.
We describe the problem of re-balancing a number of units distributed over a geographic area. Each unit consists of a number of components. A value between 0 and 1 describes the current rating of each component. By a piecewise linear function this value is converted into a nominal status assessment. The lowest of the statuses determines the efficiency of a unit, and the highest status its cost. An unbalanced unit has a gap between these two. To re-balance the units, components can be transferred. The goal is to maximize the efficiency of all units. On a secondary level, the cost for the re-balancing should be minimal. We present a mixed-integer nonlinear programming formulation for this problem, which describes the potential movement of components as a multi-commodity flow. The piecewise linear functions needed to obtain the status values are reformulated using inequalities and binary variables. This results in a mixed-integer linear program, and numerical standard solvers are able to compute proven optimal solutions for instances with up to 100 units. We present numerical solutions for a set of test instances and a bi-criteria objective function, and discuss the trade-off between cost and efficiency.
The old city core experienced a long series of modernization process that affected the old urban fabric and the coherence among urban elements. This dissertation tried to explore the intervention methods and the variety of impacts that have been occurred inside the old core . New streets that were added to the city changed the urban space hierarchy in each time. Starting from analyzing the spatial form via exploring the morphology of the city up to analyze the city skyline is the main methodology of this work. The spatial form of the city of Baghdad shows the impacts of multi planning approaches belong to variant master plans which were proposed and achieved to manage the city growth and development. Those impacts were varied and explained in this dissertation based on the change in the city network, city expansion and land use distribution. The old city of Baghdad was analyzed and explained in details in term of investigating the morphological layers for different periods showing the development of Baghdad urban structure by new comparative plans that explain the change between two following morphological periods. The understanding of the transformation in each morphological period was based on the following criteria’s (urban growth, urban space development, urban components and innovations) to provide a comprehensive investigation about the behavior of the urban components. The investigation of the main old and new streets was well assessed showing their structure, building typologies and the role of the urban space typologies along the segments of those streets. The transect analysis method was used by having nine sections through the old city in different areas to understand the transformation in the city of Baghdad and the impacts of the unregulated development process accompanied within the lack of clear urban management method. The development of the city skyline provided a clear interpretation about the impacts of inserting new urban space and building typologies inside the old core. It was so clear that the hypothesis of this dissertation was proved in showing the role of the street hierarchy change (for both pedestrian and car street in different segments) in exploring the mechanism of the conflict among urban components that bring more destruction to the city. The conclusion showed what to avoid in any prospective rehabilitation process and gave the impacts of the previous interventions that shoud not be repeated in the future.
The Lateral-Photovoltage-Scanning-Method (LPS) operates well for Si, Ge and Si_{1–x}–Ge_x for an analysis in defect regions below one part per million, where Secondary Ion Mass Spectroscopy (SIMS) or X-Ray Fluorescence (XRF) signals fall below its detection limit. Although LPS is well established since 1999, it is still poorly investigated. We used a computational simulation finite volume (FVM) approach, solving the van-Roosbroeck equations in three dimensions using a MUltifrontal Massively Parallel sparse direct Solver MUMPS. The signal transport is simulated by solving the Maxwell equations in two dimension for different sample geometries.
It could be shown that a typical LPS-measurement is distorted due to the samples geometry (except cuboid). This distortion can be simulated, understood and recalculated, as discussed for trapezoidal or cylindrical samples. Also using the signal generation simulation of this measurement technique it can be shown, that the measurement signal is convoluted depending on the inherent minority charge carrier life time reducing the local resolution. An investigation of the local resolution were made using a Gaussian function as the convolution function of this method. A comparison of simulations to real measurements was discussed on silicon samples with boron implantation pattern.
In 1955 Tauc already stated that the bulk photovoltaic effect, causative for the LPS measurement set-up, could be used detecting any quantity, which affects the band structure of a semiconductor.As strain is coupled to the conduction and valence band profiles by the deformation potential theory by van-de-Walle, we investigated the possibility to detect strain variations using LPS simulations. For an n-type Si sample with an on-top stressor stripe (silicon-nitride) the strain distribution in Si got calculated by finite elemente simulation (FEM) using solid mechanics module. By directly converting the strain profile to a single conduction and valence band, FVM LPS simulations were performed. It could be shown, that the LPS voltage can be connected to hole traps caused by the conduction and valence band profile. Therefore we can finally conclude, that the LPS measurement set-up is suitable measuring conduction and valence band variations caused by strain.
The geometric accuracy of an incrementally formed part is dependent on the underlying deformation mechanism and the residual stresses induced in the material during forming. This thesis presents new insights into the deformation mechanism and residual stresses of the Single Point Incremental Forming (SPIF) variant of the ISF process. In addition, strategies to control, suppress and adjust the deformation mechanism and residual stresses to increase the geometric accuracy and improve part properties are presented.
The deformation mechanism of the ISF process is investigated. A novel methodology is developed to split the plastic energy dissipation during the SPIF process as a contributions of energies from dominant deformation modes. It is found that the dominant deformation mode can be bending, shear or membrane stretching, depending on the selected values of the process parameters. By controlling the contribution of each deformation mechanism, the outcome of the SPIF process can be designed for maximum geometric accuracy within the constraints of process time and formability.
The build-up of the residual stresses in the SPIF process is investigated and a relation between the geometric accuracy and the residual stresses under changing process parameters is developed. The wall angle parameter has the highest influence on residual stresses. Moreover, the intensity and the magnitude of the residual stresses can be controlled by adjusting the process parameters.
A direct approach based on post-forming Stress Relief Annealing (SRA) is developed to suppress residual stresses and increase geometric accuracy. In this regard, a modular tooling set-up is designed to perform the SRA under partial constraint. For maximum efficiency, optimal SRA parameters are determined. Two parts with practical significance are incrementally formed and subsequently stress relief annealed. A considerable increase in the geometric accuracy is observed with SRA in comparison to the parts without SRA.
In the last part of this thesis, the very first approach is presented to generate a target distribution of high magnitude residual stresses in the ISF process for improving the mechanical properties. The desired residual stresses are generated in the conventionally formed disc springs in the surface treatment approach. In an integrated forming approach, the forming of the disc springs and the desired residual stresses are generated in a single step. Mechanical properties of the disc springs are better for both approaches in comparison to conventional disc springs. Hence, a targeted generation and distribution of the residual stresses to improve the mechanical properties is possible.
Reproducibility of simulation experiments is still a significant challenge and has attracted considerable attention in recent years. One cause of this situation is bad habits of the scientific community. Many results are published without data or source code, and only a textual description of the simulation set-up is provided. Other causes are: no complete simulation set-up, no proper output data analysis and inconsistency of published data, which makes it impossible to compare results.
The progress of computational modelling, amount of data and complexity of models requires designing experiments in such a way that ensures reproducibility. A textual description does not provide all the needed details. A computer code is more reliable than a textual description. It is the precise specification that describes a simulation configuration, model, etc. When computer code, data, models and all parameters are provided, the simulation results become reproducible.
The main goal of this thesis is to develop a tool that ensures reproducibility and efficient execution of simulation experiments, often involving many individual simulation runs. The tool should support a wide range of application scenarios, where the typical scenario is simulation of biochemical reaction networks, which are represented as (coloured) Petri nets interpreted in the stochastic, continuous or hybrid paradigm. The model to be simulated can be given in various formats, including SBML.
The result is a command line tool called Spike, which can be used for various scenarios, including benchmarking, simulation of adaptive models and parameter optimization. It builds on a human-readable configuration script SPC, supporting the efficient specification of multiple model configurations as well as multiple simulator configurations in a single configuration file.
The dissertation covers the physical, design, simulation and measurement aspects of extremely high Q precision oscillators for space applications. Existing design approaches and methods are evaluated, and it is shown that only physically complete models can deliver a good agreement between theory and experiments. A prototype was built showing very good phase noise and stability.
Motivated by computing functionals of high-dimensional, potentially metastable diffusion processes, this thesis studies robustness issues appearing in the numerical approximation of expectation values and their gradients. A major challenge being high variances of corresponding estimators, we investigate importance sampling of stochastic processes for improving statistical properties and provide novel nonasymptotic bounds on the relative error of corresponding estimators depending on deviations from optimality. Numerical strategies that aim to come close to those optimal sampling strategies can be encompassed in the framework of path space measures, and minimizing suitable divergences between those measures suggests a variational formulation that can be addressed in the spirit of machine learning. A key observation is that while several natural choices of divergences have the same unique minimizer, their finite sample properties differ vastly. We provide the novel log-variance divergence, which turns out to have favorable robustness properties that we investigate theoretically and apply in the context of path space measures as well as in the context of densities, for instance offering promising applications in Bayesian variational inference.
Aiming for optimal importance sampling of diffusions is (more or less) equivalent to solving Hamilton-Jacobi- Bellman PDEs and it turns out that our numerical methods can be equally applied for the approximation of rather general high-dimensional semi-linear PDEs. Motivated by stochastic representations of elliptic and parabolic boundary value problems we refine variational methods based on backward SDEs and provide the novel diffusion loss, which can be related to other state-of-the-art attempts, while offering certain numerical advantages.