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The accelerated urbanization has led to increasing tension on urban land use. In this context, more and more slender high-rise buildings are being built worldwide in pursuit of better economic benefits. However, these structures are susceptible to wind excitation due to their lower first natural frequency. Different passive, semi-active, and active damping systems have been developed to reduce wind-induced structural vibration. Among them, the tuned mass dampers are widely used and proved as a very effective method in practice. However, this system requires a large additional damping mass. This also causes additional reinforcement, which increases the cost and carbon footprint. A huge space near the top story of the building is needed for the installation. In this research, a novel system named distributed-Multiple Tuned Facade Damping (d-MTFD) system is proposed by using specially designed parallel moveable Double-Skin Facade (DSF) outer skin as damping mass. These moveable facade elements can be installed on the upper stories of the high-rise building. Smooth-running guide rail systems are used to achieve the parallel moveability. Multi-objective optimization based on the Genetic Algorithm (GA) is applied to reduce the maximum top floor acceleration (Objective I) and to reduce the maximum facade relative displacement (Objective II) simultaneously. The optimization results for the passive and semi-active systems are presented in the form of the Pareto front. The trade-off between these selected two competing optimization objectives is observed. This approach was first validated in a simulation using a 306 m tall reference building for a wind speed of 13.5 m/s at 10 m above ground level with a return period of 10 years. Acceptable peak accelerations at the top story for hotel use and a maximum facade relative displacement of less than ±0.5 m could be achieved for the benchmark building with the d-MTFD system. For semi-active control, the variable damping coefficient can be achieved by using stepper motors in generator mode. The electrical damping coefficient can be continuously adjusted by the developed power electronics. In addition, electrical energy can be generated and stored in a battery. A full-scale prototype with one parallel moveable facade element was built. Based on the prototype, the functionality of the semi-active control using a stepper motor and its energy harvesting performance was tested by applying Hardware-in-the-Loop (HiL) simulations. Greybox system identification was used to estimate some parameters (spring stiffness, friction, etc.) in the connection. The accurate system identification results ensure further validation using HiL simulations. The HiL simulations successfully demonstrated the feasibility of a self-powered semi-active d-MTFD system.
Process-based hydrological models, which simulate nitrogen load from its sources to the receiving waterbody, play an important role in supporting catchment management. The reliability of those models, such as the representative model SWAT used in this study, is determined by a sound calibration and the analysis of the prediction uncertainty. The multi-objective calibration approach prevails the classic single-objective calibration on the spatial parameterization of specific processes. However, the requirement of additional observations and practical procedures limits its application. Moreover, the prediction uncertainty of nitrogen load is inevitable and should also be quantified. This study is a scientific contribution to catchment management by overcoming the challenge with a systematic, well-founded concept of multi-objective calibration and uncertainty analysis for nitrogen load simulation in data-scarce catchments. The concept is tested and proofed by its practical applicability on the Yuan River Catchment (YRC) in China and leads to a generalized, recommended procedure for catchment management application as valuable progress in this field.
The study proposed to apply three groups of objectives, multi-site, multi-objective-function, and multi-metric. The applicability and the advantages of two multi-objective calibration approaches, Euclidean Distance and Non-Dominated Sorting Genetic Algorithm-II were analyzed. To quantify the prediction uncertainty, the study proposed to use the simulations with the highest or the lowest percent bias to represent the uncertainty band of the nitrogen load from the critical source areas (CSAs) and to the stream. The data-scarcity of the YRC was overcome by metrics obtained from open-access satellite-based datasets and metrics extracted from the existing discharge observations. Results show that multi-objective calibration has ensured the model’s better performance in terms of the spatial parameterization, the magnitude of the output time-series and the water balance components, in comparison to single-objective calibration. The predicted CSAs showed that 50% of the total nitrogen (TN) loading to the stream was from 26.3% to 37.1% of the area in the YRC. Meanwhile, over 50% of those TN were from the paddy field. Recommendations for application go to the multi-objective calibration considering all three groups of objectives. Approaches to obtain multi-metric objectives in the YRC are also applicable for catchments with data-scarcity. Recommendations for nitrogen management in the YRC is to emphasize the CSAs identified, especially the paddy field.
Auf dem Gebiet der Prozessintegration und automatisierten Optimierung von Bauteilen nimmt die Triebwerksindustrie eine Vorreiterrolle ein. Insbesondere die aerodynamische Optimierung von Triebwerksschaufeln kann, dank umfangreicher Forschungs- und Entwicklungsarbeit, seit einiger Zeit als Stand der Technik bezeichnet werden. Auf diese Art ist es möglich, trotz kürzer werdender Entwicklungszeiten immer effizientere Schaufeln zu entwerfen, die ihren Beitrag zur notwendigen Reduktion der im Triebwerk produzierten CO2-Emission liefern. Ein wichtiger Schritt beim Schaufelentwurf ist die automatisierte Mehrkriterien-Optimierung einzelner Schaufelsektionen. Hierfür sind geeignete Profilparametrisierungen notwendig, die einerseits genügend Entwurfsfreiheiten bieten, andererseits ohne manuelle Nachbearbeitung sinnvolle Profile liefern. In der vorliegenden Arbeit werden daher drei grundsätzlich verschiedene Möglichkeiten zur automatisierten parametrischen Schaufelprofilerzeugung entwickelt. Im Unterschied zu den meisten bisher vorhandenen Parametrisierungen ist allen drei Methoden gemein, dass die entstandenen Profile stets krümmungsstetig sind. Lediglich beim Übergang zur kreisförmigen Hinterkante wird Tangentenstetigkeit als ausreichend angesehen. Durch diese Vorgehensweise können, anders als vorher, sehr günstige Geschwindigkeitsverläufe an Saug- und Druckseite ohne Überhöhungen an der Vorderkante erreicht werden. Innerhalb eines auf einem Hochleistungs-Rechen-Cluster parallelisierten Mehrkriterien-Optimierungsprozesses, in dem beispielhaft der Mittelschnitt eines Stators einer Hochdruckverdichterstufe aerodynamisch optimiert wird, werden die drei Methoden anschließend miteinander verglichen. Es kann gezeigt werden, dass alle drei Parametrisierungen zu Profilen führen, die bezüglich ihrer aerodynamischen Verluste deutlich besser sind als ein manuell entworfenes Referenzprofil.
Reduction of energy consumption has increasingly come into sharp focus in the chemical process industry. This is of great value not only for existing plant but also for the development of new processes. Therefore, the challenge for process design engineers to develop an integrated chemical process that simultaneously satisfies economic and environmental objectives has increased considerably. Particularly, multi-objective optimization in the chemical industry has become increasingly popular during the last decade. The main problem lies, in selecting the alternative best design during decision making with multiple and often conflicting objectives. This thesis work presents a methodology for the multi-objective optimization of process design alternatives under economic and environmental objectives and also to establish the linkage between exergy and the environment. Four distillation units design alternatives with increasing level of heat integration were considered. Each design is analysed from exergy, potential environmental impact (PEI) and economic point of view. A non-dominated solution known as the “Pareto optimal solution” is generated for decision making. The thermodynamic efficiency indicates where exergy losses occur. The demand for industrial process heat by means of solar energy has generated much interest because it offers an innovative way to reduce operating cost and improve clean renewable electric power. Concentrated Solar Thermal Power (CSP) can provide solution to global energy problems within a relatively short time and is capable of contributing to carbon dioxide reduction, which is an important step towards zero emissions in the process industries. This work provides an overview of a simulation model to evaluate the environmental and economic performance of two case studies of solar thermal power plants. A methodology is presented to integrate solar thermal power plant into industrial processes and this is then compared with an existing hydrocarbon recovery (HCR) plant that depends on coal as its energy source. The two process design alternatives where simulated using the process simulator Aspen PlusTM. This thesis work also evaluates two types of power plants based on coal. The plants considered provide utility systems such as steam and electrical energy to the process plants. Exergy analysis was performed for each type of plant. The standard PEI calculation procedure has been modified for consideration of specific energy resources or power plants.
Stringent safety and environmental regulations, and competitions have challenged the chemical process industries to bring products to market at low lifecycle costs without compromising on safety and environmental standards. Frequently, a large number of alternatives with different structure design and process alternatives of distillation unit can be found to satisfy the demanded criteria of improvement target. Therefore, a systematic method for the improvement of distillation unit is of the considerable interest in order to evaluate the improvement objectives of design alternatives that include economic, environmental and safety criteria. Accordingly, this thesis presents integrated improvement of distillation unit based on careful and simultaneous evaluation of economic, environmental and safety criteria of the design alternatives. The approach for integrated plant improvement in this paper bears the consequence that economically attractive plant might not be the ultimate criteria as the decision tools to choose the best design, but put this economic criteria in a degree of preference in comparison to other criteria. Then, the evaluation of safety and environmental objectives in one side and total cost objectives in other side should be taken into account as a critical step in the plant improvement scenario. This research proposes a fundamental work on evaluation of economic, safety and economic criteria in distillation technology in an integrated manner. Economic evaluation will be calculated based on total annualized cost calculation. Environmental evaluation relies on the calculation of potential environmental impact associated with generated heat and mass balances generated by process simulation. Safety evaluation will be based on dynamic simulation of the investigated distillation unit during disturbance or non-standard operation as well as inherent safety index calculation. At the end, this thesis proposed a methodology for the improvement of distillation unit based on a framework of multi criteria decision making analysis. An analytic hierarchy process methodology is used to support decision upon the criteria for selection, rate the relative importance of the criteria and its advantages/ disadvantages as well as to combine the ratings to obtain an overall rating for each choice of design improvement. The concept will be applied in an existing plant as case study. It is supposed that the proposed integrated-scenario is applicable to support a decision making in chemical industries that always deal all the time with improvement tasks.
Die Arbeit stellt das prinzipielle Vorgehen der Mehrkriterienoptimierung zunächst an Beispielen des virtuellen Prototyping dar. Die Anwendung von Optimierungsalgorithmen auf Parameteridentifikationsaufgaben führt zu Mehrkriterien-Mehrmodell-Optimierung, bei der unbekannte Systemparameter aus Vergleichen zwischen Messungen und Simulationen durch ein schrittweises Vorgehen auf Basis angepasster Versuche, Teilmodelle und Kriterien ermittelt werden können. Bei der Experiment-gekoppelten Hardware-in-the-Loop Optimierung verursacht die Streuung der Messergebnisse auf Grund des nicht vermeidbaren Messrauschens Probleme bei der Konvergenz der Optimierungsverfahren. Abhilfe schafft hier eine angepsste Funktionswert- und Gradientenberechnung auf Basis eines Approximationsverfahrens. Die Vorteile dieses neu entwickelten Verfahrens sind die Verwendung einer Ansatzfunktion zur Elimination von Messfehlern, die Speicherung aller Messwerte für eine eventuelle Weiterverarbeitung und die damit verbundene Minimierung der Anzahl notwendiger Versuche, sowie das Sicherheitskonzept zur Vermeidung kritischer Versuchszustände durch eine implementierte Schrittweitenbegrenzung.