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In the time of increased awareness about the environment problems by the public opinion and also intensive international efforts to reduce emissions of greenhouse gases, as well increase of the generation of electrical energy to facilitate industrial growth, the conference offers broad contribution towards achieving the goals of diversification and sustainable development.
Focus of the student conference is to promote the discussion of views from scientists and students from Wroclaw University of Technology, Technical University of Ostrava and Brandenburg University of Technology Cottbus-Senftenberg.
The conference offers prominent academics and industrial practitioners from all over the world the forum for discussion about the future of electrical energy and environmental issues and presents a base for identifying directions for continuation of research.
In the time of increased awareness about the environment problems by the public opinion and also intensive international efforts to reduce emissions of greenhouse gases, as well increase of the generation of electrical energy to facilitate industrial growth, the conference offers broad contribution towards achieving the goals of diversification and sustainable development.
Focus of the student conference is to promote the discussion of views from scientists and students from Wroclaw University of Technology, Technical University of Ostrava and Brandenburg University of Technology Cottbus-Senftenberg.
The conference offers prominent academics and industrial practitioners from all over the world the forum for discussion about the future of electrical energy and environmental issues and presents a base for identifying directions for continuation of research.
Tax effects on asset prices
(2018)
In this dissertation I treat questions of asset pricing under the presence of taxes. I present four published articles. The first three articles are concerned with topics of company valuation when debt is risky. The first article analyzes the applicable discount rate for the valuation of tax savings in a simple setting without taxes on cancelled debt. The article concludes that the discount rate of tax savings is the same as the one for interest payments. Other than frequently assumed, this discount rate is not necessarily the same as the discount rate for debt as a whole. With the prioritization of interest or principal payments in case of losses on debt payments, the discount rates on interest payments and of tax savings are regularly different from the one for the overall debt issue. Only a pro rata distribution of losses on principal and interest payments generally leads to equal discount rates for interest payments, principal payments, and, therefore, also for debt payments as a whole. The second article continues to look at the valuation of tax savings. It differentiates the case with and the one without the taxation of cancelled debt. For both cases, the article derives equations for the value of tax savings as well as for risk-adjusted discount rates and WACC-like equations. A major finding is that the previous corporate finance literature on this topic usually makes the implicit assumption that cancelled debt is taxed. In this case valuation equations have a simple form since they are independent from the distribution of losses between interest and principal payments. Without the taxation of cancelled debt, the distribution of losses on interest and principal payments becomes important for the valuation procedures and a differentiation between cases such as interest prioritization, principal prioritization and pro rata loss distribution is necessary. The third article uses the findings of the first two articles and constructs equations for a de- and re-levering procedure using the expected return equations from the mean-variance CAPM. It extends the regularly used procedure that uses the assumption of risk-free debt to simple settings with risky debt. The forth article looks at two economies, which differ only with respect to taxation - one features taxes on capital gains and one does not. The analysis leads to several extensions on prior findings on the question of the conditions under which asset prices are the same in both economies. The article provides sufficient conditions for unchanged prices for the case of a zero risk-free rate, which entails that all agents consume exactly the same in each state. Without a zero risk-free rate, prices are the same in both economies with exponential utility and normal returns and with linear marginal utility.
Cameroon’s forest is one of the richest ecosystems in the Congo Basin and in Africa as a whole in terms of its biodiversity. These forest types are currently subjected to multiple categories of threats. By enacting a new forestry law in 1994, the government of Cameroon intended to intensify efforts toward the protection and conservation of this rich biodiversity. This study aimed to compare two forest management systems, a state management system (the case of Takamanda National Park) and a community-based management system (the case of Bimbia- Bonadikombo Community Forest), to determine which management system better conserves and protects the forest against biodiversity loss. The study applied a methodological framework that made use of selected indicators and criteria to evaluate the extent of sustainability of the two forest management systems and challenges faced in implementing them. Both quantitative and qualitative results were realized through the administration of questionnaires, semi-structure interview and in-depth contents analysis of Law No.94-1 of 20th January 1994 that lays down forestry, wildlife and fisheries regulations and the 1996 Environmental Management Law that directs Cameroon’s compliance to the international standard of protecting the environment.Results indicated that community-based system of forest management is a much more sustainable approach of forest management than a state management system. Based on the criterion of cultural values attributed to natural resources in the community-based management zone (Bimbia- Bonadikombo Community Forest), 78.2% of the local communities were more willing to protect biodiversity as opposed to 48.3% from state management zone (Takamanda National Park). This study found that the level of participation in the community-based management system was much more inclusive and transparent. On the other hand, in the state management system, a high level of corruption, lack of transparency, delayed and irregular salaries of forest guards and minimal participation of local communities in forest management decision-making was noted and likely responsible for the ineffectiveness and unsustainable management efforts in this system. The study recommends the adoption and implementation of a more inclusive, transparent and accountable management in the state managed system (Takamada national park), particularly the full involvement of respected Elites, Chiefs and Traditional Councils.
Sophisticated engine knock modeling supports the optimization of the thermal efficiency of spark ignition engines. For this purpose the presented work introduces the resonance theory (Bradley and co-workers, 2002) for three-dimensional Reynolds-Averaged Navier-Stokes (RANS) and for the zero-dimensional Spark Ignition Stochastic Reactor Model (SI-SRM) simulations. Hereby, the auto-ignition in the unburnt gases is investigated directly instead of the resulting pressure fluctuations. Based on the detonation diagram auto-ignition events can be classified to be in acceptable deflagration regime or possibly turn to a harmful developing detonation.
Combustion is modeled using detailed chemistry and formulations for turbulent flame propagation. The use of detailed chemistry caters for the prediction of physical and chemical properties, such as the octane rating, C:H:O-ratio or dilution. For both models, the laminar flame speed is retrieved from surrogate specific look-up tables compiled using the reaction mechanism for Ethanol containing Toluene Reference Fuels by Seidel (2017). In the fresh gas zone, the scheme is used for auto-ignition prediction. For this purpose, the G-equation coupled with a Well-Stirred-Reactor model is applied in RANS. In analogy, in the SI-SRM the combustion is modeled using a two zone model with stochastic mixing between the particles.
RANS is used to develop the knock classification methodology and to analyze in detail location, size and shape of the auto-ignition kernels. RANS estimates the ensemble average of the process and therefore cannot reproduce a developing detonation. Hence, Large Eddy Simulation (LES) is used to verify the methodology. Studies using wide ranges of surrogates with different octane rating and cycle-to-cycle variations are carried out using the computationally efficient SI-SRM. Cyclic variations are predicted based on stochastic mixing, stochastic heat transfer to the wall, varying exhaust gas recirculation composition and imposed probability density functions for the inflammation time and the scaling of the mixing time retrieved from RANS.
The methodology is verified for spark timing and octane rating. It is shown that the surrogate formulation has an important impact on knock prediction.
RANS is suitable to predict the mean strength of auto-ignition in the unburnt gas if the thermodynamic and chemical state of the ignition kernel is analyzed instead of the pressure gradients. The probability of the transition to knocking combustion can be determined. Good agreement between RANS and SI-SRM are obtained. The combination of both tools gives insights of local effects using RANS and the distribution of auto-ignition in the whole pressure range of an operating point using SI-SRM with reasonable computationally cost for development purposes.
This thesis is a combined work of understanding the high temperature oxidation chemistry of cycloalkanes viz. methylcyclohexane based on previously developed cyclohexane and extending it to generate the larger n-propylcyclohexane chemical kinetic mechanism. The detailed kinetic reaction mechanism model for the oxidation of 1-hexene previously developed has been added to account for the ring opening of cyclohexane forming 1-hexene. As an update to the publication, preference of allylic H-abstractions from 1-hexene has been taken into account and retro-ene reaction producing propene has been added. The complete model is composed of 329 species and 2065 reactions with 3796 reversible elementary reactions. Further, these models have been validated against different experiments such as shock tubes, jet stirred reactors and laminar flames to cover full range of temperatures, pressures and equivalence ratios making the models comprehensive and was found to be adequate to satisfactorily reproduce the experimental data. The allylic radicals (C₆H₁₁-D1R3) preferred abstractions from 1-hexene improves the C₆H₁₁ profiles in the 1-hexene model. But it also influences the otherwise isomerization path of C₆H1₁₁-D1R6 to CYC₆H₁₁ (Cyclohexyl radical) which would further form cyclohexene (CYC₆H₁₀). It is observed that CYC₆H₁₀ profiles in 1-hexene flames and cyclohexane speciation are over-predicted. The major decomposition pathway of the cycloalkanes is through H-abstractions on the ring. The path which leads towards ring opening to form olefin is observed for cyclohexane and methylcyclohexane but is very low. The fulvene pathway influence on benzene profiles of 1-hexene is obvious but do not seem to affect the cycloalkanes. This infers there are other benzene formation pathways in cycloalkanes. Some possible pathways would be the dehydrogenation of dienes and dehydrogenation of cyclo-olefins.
The provision of nutrients and organic matter to arable soils is critical to facilitate an intensive agriculture and secure long-term soil functionality. Municipal organic waste (MOW) is rich in nutrients and organic matter and its recycling onto agricultural lands presents a promising alternative to conventional fertilizers. In comparison to common aerobic treatment, the application of the biogas technology enables the recovery of both energy and soil amendments. The introduction of a mandatory separate collection in Germany in 2015 reflects the political will to increase MOW recovery rates and facilitates its utilization as feedstock in biogas plants. However, MOW is a challenging feedstock as its composition varies and it is often contaminated with impurities such as plastics and metals. The two-stage anaerobic digestion process with dry fermentation is very robust and offers possibilities for process control so that no extensive MOW pretreatment is required. To close nutrient circles, remaining digestates shall be processed to soil amendments, which can be redistributed to arable land. However, less is known about digestate properties from two-stage digestion of MOW and how they are influenced during the treatment process. Furthermore, only scarce information on nutrient recovery rates and the accumulation of elements during processing is available. Therefore, this thesis investigates the development of digestate properties during anaerobic and subsequent aerobic treatment at laboratory and semi-industrial scale. During a first experiment, changes in nutrient and heavy metal concentration in the solid digestate were monitored during anaerobic treatment of MOW in a two-stage laboratory biogas plant. A second investigation related amendment properties of MOW digestate of one origin to different post-treatment procedures. The impact of drying, composting and sieving on final digestate properties and specifically nutrient availability and heavy metal and carbon elution was evaluated. A third experimental approach investigated total material and substance flows during treatment of source-separated MOW in a semi-industrial scale two-stage biogas plant and subsequent digestate composting including impurities removal.
The main part of the research outlined in this thesis is to develop Deep Learning models for the linguistic interpretation of the visual contents. This part is split into two research problems: interactive region segmentation and captioning, and selective texture labeling. In the first attempt, we proposed a novel hybrid Deep Learning architecture whereby the user is able to specify an arbitrary region of the image that should be highlighted and described. The proposed model alternates the bounding box indications of the standard object localization process with the output of a deep interactive segmentation module to achieve a better understanding of the dense image captioning and improve the object localization accuracy. The idea of the next part is to establish a bidirectional correlation between deep texture representation and its linguistic description via a hybrid CNN-RNN model that enables end-to-end learning of the selective texture labeling. This novel architecture provides new opportunities to describe, search, and also retrieve texture images from their linguistic descriptions. To be able to train such a model, we generated a multi-label texture dataset that covers color, material, and pattern labeling simultaneously. Our contribution to the automatic generation of texture descriptions provides an excellent opportunity to enrich the existing vocabulary of the image captioning. Such a conceptual extension can be used for fine-grained captioning applicable in geology, meteorology and other natural sciences where fine-grained image structures are of importance to understand complicated patterns. Apart from Deep Learning technologies, in the final section of the thesis, we proposed a novel approach to define mathematical morphology on color images. To this end, we converted common RGB-values of the color images into a new biconal color space and then combined two approaches of mathematical morphology to give meaning to the maximum and the minimum of the matrix field data and formulate our novel strategy.
Reconstruction of the 3D shape information is a fundamental problem in computer vision. Among different shape recovering technologies, photometric stereo is highlighted for its capability to produce high quality 3D reconstruction. This dissertation generalizes photometric stereo in different aspects towards creating a practical 3D reconstruction. The proposed techniques can be considered as a fundamental support to develop future cameras offering 3D shapes for various applications such as movie and video game industry, medical sciences, virtual reality, automotive driving and etc. The first generalization is developed for addressing specularities in 3D reconstructions and also involving the perspective projection. These attempts lead to remove the limitation of working with diffuse materials and confined projected scenes. We will prove the applicability of our approach using complex scenes like endoscopy images. In the second proposed approach, we will offer a real-time 3D reconstruction of micro-details with a more generalized reflectance model. Moreover, a recurrent optimization network will be provided. These innovations lead to presenting the 3D reconstruction of details which are even invisible to human eyes like micro-prints on the banknote. This information recovery can be used in various areas such as detecting security items on financial documents for fraud detection and also the quality control of any industrial productions including delicate details such as printed circuits. In the third proposed model, we develop a PS reconstruction technique using neural networks for the uncalibrated PS where the light direction is not available. Finally, for the first time, benefiting from deep neural networks and meta heuristic algorithms, we will devise an approach which can deliver high qualified 3D shape from the internet and out-door images, without any pre-necessary knowledge.
For many countries, gasturbine technology is one of the key technologies for the reduction of climate-damaging pollutant emissions. The profitability of such facilities, however, is highly dependent on the price for the utilized fossil fuel, which is why there is a constant need for increased efficiency. The potential of increasing the efficiency of the individual components is basically limited by factors which will reduce operating life. The goal of this thesis is to develop methods for improved automated structural design optimization, which shall be developed on the basis of compressor airfoils. Special attention is payed to avoid the excitation of failure critical eigenmodes by detecting them automatically. This is achieved by introducing a method based on self-organizing neural networks which enables the projection of eigenmodes of arbitrary airfoil geometries onto standard surfaces, thereby making them comparable. Another neural network is applied to identify eigenmodes which have been defined as critical for operating life. The failure rate of such classifiers is significantly reduced by introducing a newly developed initialization method based on principle components. A structural optimization is set up which shifts the eigenfrequency bands of critical modes in such a way that the risk of resonance with engine orders is minimized. In order to ensure practical relevance of optimization results, the structural optimization is coupled with an aerodynamic optimization in a combined process. Conformity between the loaded hot-geometry utilized by the aerodynamic design assessment and the unloaded cold-geometry utilized by the structural design assessment is ensured by using loaded-to-unloaded geometry transformation. Therefor an innovative method is introduced which, other than the established time-consuming iterative approach, uses negative density for a direct transformation taking only a few seconds, hence, making it applicable to optimization. Additionally, in order for the optimal designs to be robust against manufacturing variations, a method is developed which allows to assess the maximum production tolerance of a design from which onwards possible design variations are likely to violate design constraints. In contrast to the usually applied failure rate, the production tolerance is a valid requirement for suppliers w.r.t.~expensive parts produced in low-quantity, and therefore is a more suitable optimization objective.
Towards ultrasensitive SPR-based sensing: self-referencing and detection of single nanoparticles
(2018)
Surface plasmon resonance (SPR) and its extensions, surface plasmon resonance imaging (SPRi) and surface plasmon resonance microscopy (SPRM) both enabling visualization of the sensor surface, belong to classical, indispensable highly sensitive and robust optical (bio)analytical techniques to study affinity processes on a surface. Nevertheless, SPR and SPRi/SPRM undergo a continuous development in regard to the improvement of sensitivity. The main challenge in this direction is attributed to the separation of signals due to the binding of analytes and those due to the bulk effect. The main task of the present thesis was to apply different strategies to improve the performance of SPR sensing. Within this scope, two main objectives were pursued: (1) implementation and realization of a so-called internal referencing towards suppression of the bulk effect leading to an improvement and optimization of the signal-to-noise ratio (SNR) and (2) application of wide-field (WF)-SPRM to detect, to visualize and to characterize single nanoparticles adsorbed to modified surfaces. The first objective of this thesis comprises the realization of three different internal-referencing approaches. In the first approach, a self-referencing effect based on arbitrarily distributed micro-patterned self-assembled monolayer (SAM) containing sensing and referencing spots was realized. Measurements of classical antigen-antibody-interaction resulted in a 10-fold improvement of the SNR by suppression of the bulk effect and the corresponding microfluctuations of the bulk temperature. The application of the second internal-referencing-approach, ionic referencing, acting as an assessment of patterned SAM was realized using electrolytes with a high molar refraction of either anions or cations to micro-patterned SAM combined with WF-SPRM as detecting technology. As a result, successful, unobtrusive visualization and spatial distinction of micro-patterned surfaces was shown. Unlike visualization of micro-scaled surface areas, the application of spatio-temporal referencing in WF-SPRM, as a third type of internal referencing, enables to detect, moreover to visualize and localize, smallest changes in refractive index near/on the sensor surface. In that sense, the second objective of this thesis was dedicated to the application of the WF-SPRM technology combined with spatio-temporal referencing to detect, to visualize, to quantify and to characterize single nanoparticles adsorbed to the sensor surface; here, nanoparticles act as analyte species. Based on a sophisticated image analysis, successful detection and characterization of single nanoparticles in complex media such as wine, juice and sun cream was performed. Besides being a powerful solution for nanoparticles analytics, the WF-SPRM technology represents a base to develop novel, ultra-sensitive and fast (bio)sensing platforms. Within this scope, enzyme-assisted generation of nanoparticles was studied.
PEM water electrolysis is a clean technology for hydrogen production. In spite of its many advantages, the costs of the conventional PEM electrolysis cell makes it commercially less competitive vis-à-vis its peers. An alternative cell design has been proposed which has up to a 25 % costs advantage over the conventional cell. In this alternative cell design, the flow channel plate which bears the most costs in the conventional cell design has been replaced with a 3-D Porous Transport Layer (PTL) structure. It has however, been observed that the conventional cell by far out performs the low cost cell at high current density operations, due to increased mass transport limitation in the later. Industrial and commercial hydrogen production efforts are focused towards high current density operation (> 3 A/cm²), so the alternative cell design must be optimized for mass transport limitation.
PEM water electrolysis is a clean technology for hydrogen production. In spite of its many advantages, the costs of the conventional PEM electrolysis cell makes it commercially less competitive vis-à-vis its peers. An alternative cell design has been proposed which has up to a 25 % costs advantage over the conventional cell. In this alternative cell design, the flow channel plate which bears the most costs in the conventional cell design has been replaced with a 3-D Porous Transport Layer (PTL) structure. It has however, been observed that the conventional cell by far out performs the low cost cell at high current density operations, due to increased mass transport limitation in the later. Industrial and commercial hydrogen production efforts are focused towards high current density operation (> 3 A/cm²), so the alternative cell design must be optimized for mass transport limitation.
This work seeks to understand the source of, and to eliminate the mass transport losses in the alternative cell design to get it performing at least as good as the conventional cell at current densities up to 5 A/cm². A 2-D non-isothermal semi-empirical fully-coupled models of both cell designs have been developed and experimentally validated. The developed validated models were then used as tools to simulate and predict the best operating conditions, design parameters and micro-structural properties of the PTL at which the mass transport issues in the alternate cell will be at its minimum, at high current densities. The models are based on a multi-physics approach in which thermodynamic, electrochemical, thermal and mass transport sub-models are coupled and solved numerically, to predict the cell polarization and individual overpotentials, as well as address heat and water management issues. The most unique aspect of this work however, is the development of own semi-empirical equations for predicting the mass transport overpotential imposed by the gas phase (bubbles) at high current densities. For the very first time, calculated polarization curves up to 5 A/cm² have been validated by own experimental data. The results show that, the temperature and pressure, water flowrate and thickness of the PTL are the critical parameters for mitigating mass transport limitation. It was found that, for the size of the cells studied (25 cm² active area each), when both cells are operating at the same temperature of 60 °C, alternative design will have a comparable performance to the conventional designed cell even at 5 A/cm² current density when; the operating pressure is ≥ 5 bar, the feed water flowrate is ≥ 0.024l/min∙cm², PTL porosity is 50 %, PTL pore size is ≥ 11 µm and PTL thickness is 0.5 mm. At these operating, design and micro-structural conditions, the predicted difference between the polarizations of both cells will be only ~10 mV at 5 A/cm² operating current density.
For decades, there has been a distinction between fast, volatile and slow, non-volatile memory technologies in the storage hierarchy of computer systems. While volatile memories offer a byte addressable interface, persistence was limited to slower, block-oriented media. As a consequence, processing and storing information implies copying data from the persistent storage to volatile memory and vice versa.
In recent years, a new memory technology which is both byte-addressable and non-volatile has been announced: Non-Volatile Random Access Memory (NVRAM). Its unique combination of features allows processing of information exactly at the location where it is stored permanently, thereby eliminating the need for copies. Without the need to create and manage copies, data can be processed significantly faster.
The processing of persistent information can be disrupted by failures, like crashes. When changes are only partially performed, data might be left in an inconsistent state. Such a situation can be avoided by creating a copy before starting to change data. That backup is restored when a failure has been detected. Such a procedure relies on a highly specific order of its operations, because the backup can only be disposed after all changes have been carried out successfully. Since NVRAM removes the need for accessing block-oriented media, it removes a major bottleneck in the processing of persistent information, especially when only small amounts of data are modified. As a result, controlling the order of operations dominates the processing performance.
This thesis analyses transactional mechanisms for data on NVRAM which can guarantee that sequences of operations are either carried out as one unit or not at all. The idea is based on creating backups, as sketched above. Existing approaches for the traditional storage hierarchy use separate memory locations for backup and modified data. In a first step, the costs of applying existing procedures to NVRAM are identified. Afterwards, a novel approach which couples the versions tighter in space is presented. Enabled by the unique properties of NVRAM, this new approach is able to reduce the costs of ordering. The processing of persistent data can thereby be sped up significantly.
The chemical and electronic structure of hybrid organometallic (CH₃NH₃PbI₍₃₋ₓ₎Clₓ) and inorganic (CsSnBr₃) perovskite materials on compact TiO₂ (c-TiO₂) is studied using x-ray and electron based spectroscopic techniques. The morphology and local elemental composition of CH₃NH₃PbI₍₃₋ₓ₎Clₓ, used as absorbers in PV devices, defining the film quality and influencing the performance of respective solar cells is studied in detail by using photoemission electron microscopy (PEEM). An incomplete coverage, with holes reaching down to the c-TiO₂ was revealed; three different topological regions with different degrees of coverage and chemical composition were identified. Depending on the degree of coverage a variation in I oxidation and the formation of Pb⁰ in the vicinity of the c-TiO₂ is found. The valence band maxima (VBM) derived from experimental data for the perovskite and c-TiO₂, combined with information from literature on spiro-MeOTAD suggests an energy level alignment resulting in an excellent charge selectivity at the absorber/spiro-MeOTAD and absorber/c-TiO₂ interfaces respectively. Further, the derived energy level alignment indicates a large recombination barrier (~2 eV), preventing shunts due to direct contact between c-TiO₂ and spiro-MeOTAD in the pin-holes.
In-situ ambient pressure hard x-ray photoelectron spectroscopy (AP-HAXPES) studies of 60 and 300 nm CH₃NH₃PbI₍₃₋ₓ₎Clₓ have been performed under varies conditions (i.e. vacuum/water and dark/UV light) to gain insight into the degradation mechanism responsible for the short lifetime of the absorber. The 60 nm perovskite forms Pb⁰ in water vapor (non-defined illumination) in presence of x-rays. The 300 nm perovskite sample shows a complex behavior under illumination/dark. In water vapor/dark the perovskite dissolves into its organic (MAI) and inorganic (PbI₂) components. Under illumination PbI₂ further decomposes to Pb⁰ induced by UV light and x-rays.
For alternative inorganic CsSnBr₃ perovskites, the impact of SnF₂ on the chemical and electronic structure is studied to identify its role for the improved performance of the solar cell. HAXPES and lab-XPS measurements performed on CsSnBr₃ with and without SnF₂ indicate two Sn, Cs, and Br species in all samples, where the second Sn species is attributed to oxidized Sn (Sn⁴⁺). When adding SnF₂ to the precursor solution, the coverage is improved and less Sn⁴⁺ and Cs and Br secondary species can be observed, revealing an oxidation inhibiting effect of SnF₂. Additionally, SnF₂ impacts the electronic structure, enhancing the density of states close to the VBM.
Although GaN HEMTs are regarded as one of the most promising RF power transistor technologies thanks to their high-voltage high-speed characteristics, they are still known to be prone to trapping effects, which hamper achievable output power and linearity. Hence, accurately and efficiently modeling the trapping effects is crucial in nonlinear large-signal modeling for GaN HEMTs.
This work proposes a trap model based on an industry standard large-signal model, named Chalmers model. Instead of a complex nonlinear trap description, only four constant parameters of the proposed trap model need to be determined to accurately describe the significant impacts of the trapping effects, e.g., drain-source current slump, typical kink observed in pulsed I/V characteristics, and degradation of the output power. Moreover, the extraction procedure of the trap model parameters is based on pulsed S-parameter measurements, which allow to freeze traps and isolate the trapping effects from self-heating. The model validity is tested through small- and large-signal model verification procedures. Particularly, it is shown that the use of this trap model enables a dramatical improvement of the large-signal simulation results.
The report “Studio Bagan: Building in Heritage Context” presents an in-depth study of the issue of monument climbing at Bagan, one of Asia’s most important Buddhist sites. Originally built during the 11th to 13th centuries the site comprises more than 3.000 Buddhist monuments ranging from small stupas and temples to monastic complexes and several enormous stucco-covered structures on an area of about 25 square kilometres.
The core concept of the research project that resulted in the report was to work across the disciplines of architectural conservation, heritage studies and design. Thus, the study was conducted by academics of respective fields and master students of World Heritage Studies, architecture and urban planning. The project applied approaches from social sciences as applied in architectural conservation in order to guide the architectural design process. These included values-based approaches for gaining an understanding of the site and of the stakeholders’ needs; heritage impact assessments to identify beneficial (and adverse) characteristics for potential alternative viewing platforms; typology exploration and location analysis through the SWOT process.
Statistical size effect in steel structure and corresponding influence on structural reliability
(2018)
This thesis aims to investigate the statistical size effect in the elasto-plastic material and the corresponding reliability of steel structures. The core idea is that the stochastic material properties are directly embedded in mechanical calculations to develop a more accurate and economical design method for steel structure. Moreover, the results of the experimental investigation with different specimen sizes, whose diameter is limit up to 32 mm, show that the statistical size effect exists in steel structures. This thesis demonstrates finally that the structural reliability is affected by the statistical size effect and the structural safety can be optimized by considering this effect.
Because of the uncertainty and non-uniformity of the microscopic imperfection distribution, the material strength in macroscale presents complex randomness. This study described the randomness of material properties through two different ways: developing a stochastic material model for elasto-plastic material and establishing a discrete random field with a general mathematical program. The proposed stochastic material model is extended to analyze the steel structure with multiaxial stress and is integrated into the commercial FEM software for analysis of the complex structures with stress gradient. The stochastic finite element method is implemented to analyze the response of the 3D structures by a general-purpose FEM program when the random field file is imported into the finite element model.
The uniaxial tensile tests with different specimen sizes and different material are carried out to demonstrate the statistical size effect in steel structures. The results show that the variations of the yield and tensile strength increase with the decreasing specimen volume. Moreover, according to the bending tests, it is obvious that the structural component strength is not only related to the specimen volume, but also the stress distribution. These two proposed simulation methods, which are an extension and supplement to traditional simulation methods, can effectively simulate the statistical size effect for the tensile and flexural components in steel structures.
Finally, it is found by studying the influence of statistical size effect on structural reliability that the strength, which is obtained by small specimens through statistical analysis in the laboratory, is no more accurately applicable to large construction. The reliability theory for the structural safety which exists over the decades can be compared and validated or improved through the embedding the stochastic material properties in the numerical simulation.
The use of renewable energy sources, either off-grid or on-grid to supply electricity, has been done by developed countries since many years ago. Developing countries, for example Indonesia especially east part of Indonesia have recently started this way whereas renewable energy potential for example hydro, PV and wind are abundantly available. The lack of research and data is one of the obstacles to precede the use of renewable energy in this area, meanwhile this area has electricity shortages problem that occurred quite often.
Combined hydro, PV, wind, coal and diesel generators will solve electricity shortages problem in Palu (Indonesia). Integration of Hydro, PV and wind into PALAPAS utility grid will decrease levelized cost of energy from US$ 0.145 per kWh to US$ 0.133 per kWh. Sensitivity analysis against fluctuating fuel cost (from US$ 0.4 per litre to US$ 1.6 per litre) will increase levelized cost of energy before integrating renewable energy into the grid from US$ 0.145 per kWh to US$ 0.455 per kWh and will increase levelized cost of energy after integrating RE into the grid from US$ 0.133 per kWh to US$ 0.403 per kWh.
Repowering grid with integrating hydro, PV and wind will increase power quality especially by using configuration based on homer results. Buses voltage and buses frequency showed better result before, during and after some faults based on Homer simulation results. Voltage spectrum and sinusoidal waveform voltage are showing less distortion after integrating hydro, PV and wind into the grid even with no distortion based on Homer results.
In-stream microbial carbon transformation under opposing stresses - drought and sediment transport
(2018)
The mineralization of organic matter (OM) is an important ecosystem service that has come under pressure because of increased frequency of droughts and higher sediment loads in running waters. In particular, lowland streams in temperate regions may experience reinforced sediment transport through migratory ripples and changes of naturally sorted sand and gravel in streambeds towards sand-dominated, homogenized streambed structure. The impact on microbial carbon (C)-transformation from these changes was the main focus of my doctoral thesis, in particular the impact of (i) periodic mechanical disturbance associated with ripple migration (ii) streambed structure homogenization, and (iii) drought in streambeds with sorted or homogenized sediment structure.
In a set of microcosms, the significance of periodic mechanical disturbances for microbial C-transformation was tested. Thereby, the quantity and quality of the OM in the sandy sediments were varied by the addition of leaves and fish feces to the OM-poor sands. The results revealed that periodic mechanical disturbances resulted in significant decrease in microbial respiration to a low and similar level regardless of OM quality contained in sand.
The importance of the streambed structure (sorted vs homogenized) for C-transformation was tested using set of experimental streams. The focus was on the interaction between benthic and hyporheic microbial processes in C-transformation to better understand the consequences of streambed homogenization on microbial function. The results showed that sediment structure determines connectivity between the benthic and hyporheic zones. The lower water exchange in homogenized streambeds and thereby reduced supply of freshly produced bioavailable OM from the benthic to the hyporheic zone, curtailed microbial respiration in the latter affecting the water quality.
The influence of a drought and rewetting was tested on C-transformation in streambeds with a sorted or homogenized sediment structure using experimental streams where one half of the streams were strongly shaded and the other half moderately shaded. The results showed that streambeds affected by droughts, either with sorted or homogenized sediment structure have a similar microbial activity at the first place controlled by shading, whereas microbial composition during drought and its recovery after rewetting was additionally affected by sediment structure.
Overall, this doctoral thesis showed that in sediment transport– and drought-impacted streambeds (i) ripple migration results in decreased C-transformation regardless of the available quality of OM, (ii) homogenization of sorted sediment structure leads to a decrease in microbial C-transformation in the hyporheic zone, and (iii) interaction between sediment structure and shading alters microbial community composition especially critical for resistance and resilience of C-transformation during drought and rewetting.