Search results for ""Verlag G. Mainz""

Big data raises new opportunities for deep insights and supporting decision-making. To seize these opportunities, methods that derive useful knowledge from large amounts of data are needed. Such methods can help meet urgent challenges in many fields. An urgent challenge for energy systems is the necessary transformation towards sustainability to mitigate climate change. One crucial aspect of this challenge is a permanent optimal operation of energy systems. In principle, mathematical optimization can best determine the optimal operation of energy systems. However, manual model generation and operational optimization of energy systems are time-consuming and can thus prevent an application of mathematical optimization in practice. This thesis presents methods that use measured data to automatically generate mathematical models of energy systems to tackle the challenge of time-consuming model generations. Additionally, methods are presented that accelerate the operational optimization

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The audio bandwidth of digital landline and mobile telephone networks is still mostly restricted to 200 Hz to 3.4 kHz. This is due to compatibility requirements during the transition phase from analogue to digital transmission technology. The resulting characteristic telephone speech is widely accepted, but the intelligibility of syllables is only 91%.Meanwhile, improved coding standards for so-called HD voice or Wideband Speech have been developed which are gradually being introduced into the networks. They support an audio frequency bandwidth of 50 Hz to 7.0 kHz with significantly increased audio quality and speech intelligibility. For a very long time however, new HD-telephones and old narrowband telephones have to co-exist. If an HD-terminal is connected over a narrowband link to an old telephone, the improved coding scheme cannot be used.In this thesis, signal processing concepts are developed for improving audio quality and intelligibility of narrowband speech by

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In recent years, the conversion of CO2 to basic chemicals with one carbon atom (C1-chemicals) such as methane and methanol has gained increasing interest. The major motivation for the utilization of CO2 is the reduction of global warming and fossil depletion impacts. However, these reductions are not guaranteed because all C1-chemicals require hydrogen besides the abundantly available CO2. Thus, the goal of this thesis is the life cycle assessment of CO2-based C1-chemicals (methane, methanol, carbon monoxide and formic acid). The assessment is based on a system-wide perspective, which means that for limited resources such as renewable electricity also the utilization of the limited resources is in other processes is considered.First of all, the CO2-based processes are compared to fossil-based processes for C1-chemicals. Formic acid has the highest potential to reduce global warming and fossil depletion impacts followed by carbon monoxide, methanol and methane. Even if hydroge

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The emerging interest on the application of vacuum interrupter (VI) in medium and even high-voltage application has led to increase of comprehensive and fundamental research on VIs. Application of these interrupters is however hindered by limitation of interrupting capability, when high-current anode phenomena occur.The goal of the work is to investigate the high-current anode phenomena using spectroscopic methods se well as electrical measurements. Different current waveforms, i.e. AC and DC pulses are applied. Moreover, the impact of vacuum interrupter properties, e.g. electrode diameter and geometries, contact materials, opening time and opening speed on the formation of high-current anode phenomena are investigated.The results reveal that the threshold current of the high-current anode formation is dominated by the current in case of high-frequency pulsed, whereas in case of pulsed DC, it is controlled by transferred charge.Along with typical and already kno

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This thesis studies the congestion problem at the Medium Access Control (MAC) layer of the IEEE 802.11p system in highway scenarios using an analytical approach. Using the Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) protocol, the IEEE 802.11p system suffers from the hidden station problem. This thesis provides formal definitions for the hidden station condition and the hidden station problem and develops an analytical methodology for CSMA protocols to investigate the interaction between stations in mutual channel sensing range and hidden to each other. Analytical models are developed for broadcast communication using the generic CSMA protocol and the IEEE 802.11p MAC protocol with a one-dimensional (1-D) homogeneous network topology. Simulation studies prove the accuracy of the models in analyzing the reliability performance and the efficiency performance of CSMA broadcast communication with hidden stations.The performance of Cooperative Awareness Message (CAM

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The need for artificial intelligence systems that are not only capable of mastering complicated tasks but also of explaining their decisions has massively gained attention over the last years. This also seems to offer opportunities for further interconnecting different approaches to artificial intelligence, such as machine learning and knowledge representation.This work considers the task of learning knowledge bases from agent behavior, with a focus on human-readability, comprehensibility and applications in games. In this context, it will be presented how knowledge can be organized and processed on multiple levels of abstraction, allowing for efficient reasoning and revision. It will be investigated how learning agents can benefit from incorporating the approaches into their learning processes.Examples and applications are provided, e.g., in the context of general video game playing. The most essential approaches are implemented in the InteKRator toolbox and show pote

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Plant virus nanoparticle (VNP) is a useful platform with biocompatibility and versatile monodisperse protein structures that can be engineered with bioactive cues, offering opportunities to functionalize bioinert hydrogels for tissue engineering. The hypothesis in this study was that osteogenesis of human mesenchymal stem cells (hMSCs) and biomineralization could be enhanced by incorporating VNPs, which were engineered with osteogenesis-associated or cell-adhesive peptides, into cell-laden hydrogels. Cellular responses to VNPs were examined in both 2D and 3D cultures, including VNP-cell distribution, cell attachment, morphology, and osteogenesis. VNP-laden agarose or agarose-collagen hydrogels were characterized in terms of release rate, mineralization effect, mechanical properties, and usage as bioink. The results revealed enhanced osteogenic differentiation when cells were cultured on VNP-coated surfaces, and attachment of VNPs to cells as well as at least 84 % of VNP retention we

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In nuclear magnetic resonance (NMR) the demand for compact, low-cost instruments that can substitute expensive superconducting magnets is growing. Although compact NMR devices based on permanent magnets that can resolve 1H chemical shift differences are commercially available, the magnetic field strength of these devices is limited, which sets boundaries to the signal intensity and quality. Hyperpolarization techniques to boost the NMR signal beyond ist thermally given polarization are well known and applied on superconducting magnets. Thus, implementing these methods on compact NMR instruments will be the next step of development to gain an increased signal quality and widen the range of applications for those magnets.One part of this thesis deals with the development of compact magnets for an X-Band Overhauser Dynamic Nuclear Polarization (ODNP) setup and the construction of the hyperpolarization hardware itself. Two concepts of small open-access magnets are presented, simu

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Worldwide heating and cooling demand will rise significantly over the next decades. Adsorption energy systems, namely adsorption chillers and heat pumps, have the potential to provide parts of this demand environmentally friendly by employing solar heat or waste heat.Designing adsorption energy systems is challenging due to the following reasons: (1) intrinsic dynamics, (2) multi-objectiveness, (3) large variety in design parameters, (4) strong influence of control, and (5) a large impact of input parameters such as temperatures. In many studies, these effects have been investigated separately by conducting sensitivity analyses. To explore also the interactions between design, control, and input parameters, a simultaneous optimisation approach is presented and exemplified in this thesis.Key to simultaneous optimisation are fast simulation models which capture the effects of all optimisation parameters. To quickly model new advanced adsorption energy systems, an object-

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Global greenhouse gas emissions significantly accelerate climate change and adversely affect life on earth. To mitigate these effects, greenhouse gas emissions need to be cut-down by significant reductions in primary energy consumption. Primary energy consumption can be reduced by increasing the efficiency of energy supply, which is mainly fixed during the synthesis of energy systems. Optimal synthesis of energy systems can be realized by mathematical optimization, however the solvable problem complexity is limited. In contrast, energy systems encompass highly complex energy conversion technologies and an increasing number of time-varying operation conditions. Thus, the synthesis of real-world energy systems usually result in large-scale optimization problems, which are computationally prohibitive.In this thesis, a solution framework is proposed to enable large-scale synthesis of energy systems. The framework exploits the two-stage character of synthesis problems: the decisio

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Most industrial processes for producing bulk and fine chemicals are transition metal catalyzed. Toxicity and high cost of platinum group metals are triggering the current search for sustainable catalysts. In this regard, nontoxic and earth-abundant alkali metals could become attractive alternatives. They are the most electropositive elements of the periodic table. With a single s electron in the valence shell and a low ionization enthalpy they easily form M+ ions. The vacant, low-energy orbital of the M+ ion is capable of accepting an electron pair. This Lewis acidic property can be utilized in molecular catalysis. Since alkali metal compounds easily dimerize, oligomerize or even polymerize (Scheme A.1-1), suitable ligands are crucial for the isolation of defined metal complexes in their monomeric form.

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Mobile phones as well as tablets are omnipresent and belong to everyday life. Today audiovisual communication takes place at different locations and in a large variety of acoustic environments. In consequence, the intelligibility as well as the quality of speech may significantly be degraded by ambient background noise. In order to improve speech intelligibility and to ensure a convenient communication with high audio quality, speech enhancement techniques are required. In this thesis all critical components contributing to the enhancement of the up-link signal are addressed: signal capturing at the acoustic front-end with a new near field beamformer new codebook based speech and noise estimation procedure generating and exploiting reliability information, and actual noise reduction exploiting spectral dependencies of human speech.For the acoustic front-end of the digital processing chain a novel concept for the filter optimization of a near field beamfor

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This thesis presents systematic extensions of the continuous-molecular targeting framework for the integrated design of working fluids and ORC processes. In the first step of the proposed method, a simultaneous optimization of working fluid and process allows for the identification of an optimal hypothetical working fluid. The second step of the method is used to search for real working fluids that lead to similar performance.

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In 2007 the International Telecommunication Union, Radiocommunication Sector (ITU-R) published evaluation guidelines for future mobile broadband radio networks including a minimal VoIP capacity that the IEEE 802.16m WiMAX system had to meet, proven by system level simulation. These evaluation guidelines are the foundation of this work that shows that relayenhanced 4G networks do not only meet the requirements but exceed them by far. The key-requirement for packet based VoIP services that has been set in the evaluation guidelines demands that the end-to-end packet delay of at least 98% of user data traffic stays below 50 ms.Since 2011 proposals of ComNets to implement relays into mobile radio networks to increase system capacity are part of all 4G systems (LTE and WiMAX). This work investigates the voice over IP (VoIP) capacity of the relay-enhanced WiMAX system by system simulation. The work presents a modular approach that has been developed by my colleagues and myself to im

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In this thesis, two novel synthesis methodologies are proposed to facilitate the use of optimization for efficient and reliable DESS synthesis, thus making optimization accessible for practitioners: The automated superstructure-based and the superstructurefree synthesis methodology. The proposed methodologies avoid both the a priori definition of a superstructure and the manual definition of many technology-specific replacement rules while accounting for the major characteristics inherent to DESS synthesis problems. The superstructure-based framework (chapter 4) relies on an algorithm for automated superstructure-generation. The method employs a successive superstructure expansion and optimization strategy that continuously increases the number of units included in the superstructure until the optimal solution is identified. The superstructure-free approach (chapter 5) combines evolutionary optimization and deterministic optimization for simultaneous alternatives generation and opti

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The global demand for cooling increases and poses a challenge for the stability of electrical grids and the emission targets. Thermally-driven adsorption chillers can meet this challenge by substituting electricity with thermal energy. However, although adsorption chillers are primarily driven by thermal energy, practical experience shows that the electricity savings often hardly compensate the electricity demand of the auxiliaries, such as pumps and fans. Thus, smart systems integration is crucial. Systems integration of adsorption chillers is challenging due to several features: (1) intrinsic dynamics; (2) close interaction between various system components; and (3) strong coupling of design, control, and operating conditions. These features lead to a variety of degrees of freedom, which make it difficult to use simple design and control rules for systems integration.To move towards optimal systems integration of adsorption chillers, this thesis provides appropriate models

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The accurate prediction of reaction kinetics data, e.g., reaction rate constants, for the microgel synthesis is highly desired because its usage in model-based design approaches promises the development of more specialized microgels and enables new applications. The complexity and the diversity of the microgel synthesis, however, often prevent experimental approaches but depict challenges for prediction approaches, as well. Therefore, this thesis analyzes a wide range of aspects relevant for the microgel synthesis individually and proposes prediction strategies for each.Here, the focus is on three main aspects: (i) The prediction of reaction kinetics in homogenous liquid reaction environments by combining high-level density functional theory and COSMO-RS, (ii) improving the property prediction of ionic species by applying the Cluster-Continuum approach and analyzing the uncertainty of the reference data, and (iii) enabling the kinetics prediction for inhomogeneous reaction en

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In the last decades, CH activation became an increasingly powerful tool for CC bond formation. It provided a valid alternative to conventional cross coupling reactions with maximised atom- and step-economy for synthetic reactions. Even though a lot of great advances have been made, some challenges in CH activations remain. CH bonds are highly stable (110 kcal/mol), often harsh reaction conditions are needed to break the bond and form a new CC compound. Furthermore, regioselectivity has been proven to be a difficult issue since a number of CH bonds are present in organic molecules. Also, chemoselectivity still remains a difficulty to overcome in CH activation reactions. Many groups focus their research on developing mild reaction conditions that proceed at ambient temperature, neutral conditions and in absence of strong oxidants or reductants.[1b] By choosing milder reaction conditions also problems of selectivity can be managed. In general, the catalytic cycle of CH activation react

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Diffusion is the rate-limiting mass transport step in many (bio)chemical processes. Diffusion data is therefore necessary to design unit operations, e.g., extraction. However, diffusion data on multicomponent mixtures in liquids are scarce, as diffusion measurements are intrinsically time-consuming and laborious. Also, several measurements are required for one diffusion coefficient matrix in a multicomponent mixture.Microfluidics promises to reduce experiment time and experimental effort, while Raman spectroscopy reduces the number of necessary experiments for multicomponent mixtures. To reduce the measurement effort for diffusion coefficients in multicomponent mixtures, microfluidics and Raman microspectroscopy were combined in this work for the first time for the measurement of diffusion coefficient matrices in multicomponent mixtures: Two liquids of different concentrations co-flow in parallel in a microfluidic H-cell, while changes of concentration due to diffusion are qu

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Sensors for stray-field nuclear magnetic resonance (NMR) have been employed to measure tangible cultural heritage since they were first conceived. Although NMR is a method with inherently low sensitivity and requires larger amounts of time than many other techniques, it is non-destructive and grants access to spin densities and relaxation times, physical quantities which are exclusive to the method. This thesis describes theory, instrumentation, and applications of unilateral NMR in the field of cultural heritage.The detection zone of an NMR-MOUSE, a sensor developed and maintained by past and present members of the group of Professor Blümich, is mapped through back-projection for the first time. Traditionally, the signal arising from the detection volume was averaged over multiple scans until the signal response was satisfactory. In this work, an algorithm is proposed to improve the signal-to-noise ratio in magnetization decays as a method of post processing an output, which

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Today humanity faces a challenge: Global warming that is caused by emissions of CO2. To reduce CO2 emissions, usage of CO2 as a renewable carbon source has gained attention. In particular, the CO2-based synthesis of formic acid has been intensively studied, since in addition to utilizingCO2, formic acid could also act as chemical storage of fluctuating renewable energy. Developing such storage is paramount for any renewable energy system due to the fluctuating occurrence of e.g. wind. However, for the CO2-based formic acid synthesis, only a few processes have been developed. Thus, novel formic acid synthesis processes are developed in this thesis. The development considers process structure and solvents, as well as formic acid derivatives due to the unfavorable equilibrium of the CO2-based formic acid synthesis.Firstly, a process is developed for the formic acid synthesis with the widely investigated solvent dimethyl sulfoxide (DMSO). The work identifies that DMSO has an azeo

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During the last 25 years, most of the communication systems have been converted to purely digital technology, although the transmitted content mostly is analog by nature. The principal advantages of digital communication are compression by source encoding, bit error protection by channel coding and robust transmission over noisy channels by appropriate modulation. Digital systems are usually designed for worst case channel conditions. However, often the channel quality is much better, which is not reflected in an improved end-to-end transmission quality due to inevitable quantization noise produced by the source encoder.In this thesis, the focus is set on systems which: are not purely digital anymore benefit from increasing channel qualities and avoid the saturation effect using discrete-time, continuous-amplitude techniques.In the first part, purely analog, i.e., discrete-time and continuous-amplitude transmission systems are considered with line

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Reaction models are important for many engineering tasks, such as the optimization of internal combustion engines or production lines in the chemical industry. The automated reaction space exploration method ChemTraYzer attempts to alleviate the often time-consuming reaction model development process. ChemTraYzer uses reactive Molecular Dynamics (rMD) simulations to find the underlying reactions of the reaction process. Coupling the rMD output to quantum-mechanical reoptimizations of reactant, product and transition state (TS) geometries and to transition state theory, allows ChemTraYzer to produce kinetic and thermochemical data with the low uncertainties,which are required for many reaction model applications. In this thesis, I address two major issues of the ChemTraYzer method. First, I introduce two acceleration techniques for the rMD simulations, the pressure-accelerated Dynamics (pAD) and ChemTraYzer-Temperature-Accelerated Dynamics (ChemTraYzer-TAD) methods, to extend the app

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Climate change mitigation requires a reduction of greenhouse gas (GHG) emissions. The main emitter of GHG emissions is the energy sector, which today is based on fossil fuels. To mitigate climate change, we need to transform the energy systems to low-carbon technologies. For this purpose, new energy system designs are required along with appropriate operational strategies. In principle, these new designs and operational strategies can be identified best using mathematical optimization. However, low-carbon technologies impose challenges in solving and assessing the resulting optimization problems.Low-carbon technologies are volatile, which increase the complexity of optimal synthesis and operation. To cope with the complexity of operational optimization, we develop a time-series decomposition method. The method decomposes the complex, time-coupled operational problem into smaller subproblems, while still providing feasible, near-optimal solutions. For the increased complexity

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Nuclear Magnetic Resonance (NMR) techniques have proliferated in many fields of science and technology like bio-sensing, chemical reaction monitoring and material characterization. Since the inception of NMR as an analytical tool, improving the sensitivity by increasing the field strength has been the primary development goal. However, in order to reduce cost and environmental impact, the trend to miniaturized NMR devices and its diverse application fields enjoys increasing interest. The first part of this thesis introduces novel insights into low-power rf-excitation, which is one crucial aspect for enabling further development in this direction, by employing Frank sequences. Based on experimental data, a detailed evidence of the power savings by excitation in the linear regime is given aiming at future elimination of the rf-amplifier from the NMR spectrometer so as to allow further mobility improvements. Selective excitation by colored Frank-sequence is reported, which bears promis

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The synthesis of energy systems is a complex task, since a plethora of conditions needs to be regarded during decision making. Thus, mathematical optimization is an excellent tool to accomplish this task and to identify an optimal system design. However, energy system synthesis is intrinsically uncertain, since the availability of components is inherently uncertain as well as the input parameters, such as energy demands. As a result, neglecting uncertainties might lead to a lack of energy supply. An insufficient energy supply possibly causes both high unexpected costs and environmental damage. Thus, uncertainties need to be regarded during optimization of energy systems. At the same time, sustainability is a further major aspect in the synthesis of energy systems. To regard sustainability performance, multiple decision criteria, such as economic, environmental, and social criteria, need to be taken into account. For this purpose, employing multi-objective optimization is perfectly s

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Whereas tetradentate (OSSO)-type ligands mostly allow for the preparation of mononuclear transition metal complexes, lignads that feature two or more of the structurally related (ONNO)-type subunits may give access to multinuclear heterometallic complexes. +IV, +V and *VI stabilized by tetradentate (OSSO)-type ligands led to the development of a tris(ONNO)-type ligands revealed a new approach toward heterometallic 3d transition metal complexes that resolves the limitations of core/shell template directed synthesis and avoids metal cooperative effects resulting in magnetic interactions of the paramagnetic center and in enhanced catalytic activity in transformations of heterocumulenes with epoxides. This thesis further contributes to the field of mono- and tetranuclear metal complexes stabilized by (OSSO)- or tris(ONNO)-type ligands. Based on these ligands, the stractural, magnetic and electrochemical propeties of various complexes are reported.

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Consequential Life Cycle Assessment (CLCA) aims at capturing the environmental consequences of decisions such as the introduction of a new technology, the implementation of a policy, or the purchase of a product. CLCA combines technical and economic modeling approaches to track the consequences of decisions throughout the economy, considering both technical relationships within industrial production systems and market-mediated effects. However, although CLCA is well defined at a conceptual level, a commonly accepted modeling framework for CLCA is still missing, leading to wide differences in CLCA practice.To promote the systematization of the CLCA approach, this thesis proposes a comprehensive modeling framework for CLCA: the Technology Choice Model (TCM). Compared to existing approaches, TCM captures market-mediated effects in multiple markets at a substantially higher level of technical detail, while systematically considering constraints in factor availability, uncertainty

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For the design and control of chemical processes, models that can accurately describe the physicochemical interactions of the process are needed. However, even with systematic modeling frameworks, the validation of predictive models is time and cost consuming. The generation of experimental data required for model validation often ensues in considerable effort and costs, which can be reduced via optimal experimental design (OED) methods. This thesis addresses the question on how to obtain predictive models for reactive complex chemical processes with the least experimental effort for a given application.The different challenges encountered during modeling complex reactive systems are discussed in Chapter 2. To this end a tutorial is presented for modeling chemical systems exhibiting dynamics on different time scales owing to fast (equilibrium-limited), and slow (kinetically-limited) reactions. The presented systematic modeling approach, complementing existing literature, is b

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In order to increase sustainability of chemical processes, a raw material change from conventional to renewable feedstocks is the key. This opens up numerous novel process concepts. A detailed conceptual design of all of these different pathways is expensive and time-consuming, since the mandatory simulations depend on pre-specified design decisions and commercial simulation software lack robustness. Hence, screening methodologies are required for an initial assessment of the processes. Existing screening methods are restricted to reaction or process design data known in literature, such that the integration of novel pathways requires simulation studies. This is impeded by limited data availability and the lack of profound property models.Process Network Flux Analysis is introduced as an optimization-based screening methodology to accelerate process development and improvement for existing and novel processes. The method systematically integrates reaction data with the select

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Plastics are on the rise to conquer every area of modern human life but lead to increased pollution of nature, enormous oil consumption, and large-scale greenhouse gas emissions. Thus, to avoid climate change above 1.5?C, net-zero greenhouse gas emission plastics are needed by the second half of this century. To reduce the greenhouse gas emissions associated with plastics, three circular technologies can be used: (1) chemical or mechanical recycling, (2) carbon capture and utilization, and (3) biomass utilization. However, current environmental assessments of these circular technologies focus solely on individual or partly combined circular technologies, are limited to regional scopes, and often apply inconsistent methodologies. Thus, it is currently unclear if net-zero emission plastics can actually be achieved with the current set of circular technologies. Furthermore, shifting from the linear to a circular economy is regarded as energy-intensive and costly, hindering strong policy i

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