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Im Rahmen der Dissertation ist ein analytisches Berechnungsverfahren zur Ermittlung der Kapazität in lichtsignalgeregelten Zufahrten mit zusätzlichen Aufstellstreifen bei gleichzeitiger Freigabezeit entwickelt worden, dass sich durch folgende Eigenschaften auszeichnet:
a) einfaches Berechnungsverfahren – Ansatz eines einfachen linearen Berechnungsansatzes, der auf den Grundzusammenhängen des Verkehrsablaufs in lichtsignalgeregelten Zufahrten aufbaut,
b) breites Anwendungsgebiet – Berechnungsverfahren kann in Zufahrten mit bis zu zwei zusätzlichen Aufstellstreifen angewendet werden,
c) hohe Genauigkeit – Im Rahmen eines direkten Vergleichs konnte u. a.
gezeigt werden, dass mit dem hergeleiteten analytischen Berechnungsverfahren genauere Kapazitätswerte ermittelt werden können, als mit dem Berechnungsverfahren nach HBS 2015.
This dissertation is devoted to the theoretical development and experimental laboratory verification of a new damage localization method: The state projection estimation error (SP2E). This method is based on the subspace identification of mechanical structures, Krein space based H-infinity estimation and oblique projections. To explain method SP2E, several theories are discussed and laboratory experiments have been conducted and analysed.
A fundamental approach of structural dynamics is outlined first by explaining mechanical systems based on first principles. Following that, a fundamentally different approach, subspace identification, is comprehensively explained. While both theories, first principle and subspace identification based mechanical systems, may be seen as widespread methods, barely known and new techniques follow up. Therefore, the indefinite quadratic estimation theory is explained. Based on a Popov function approach, this leads to the Krein space based H-infinity theory. Subsequently, a new method for damage identification, namely SP2E, is proposed. Here, the introduction of a difference process, the analysis by its average process power and the application of oblique projections is discussed in depth.
Finally, the new method is verified in laboratory experiments. Therefore, the identification of a laboratory structure at Leipzig University of Applied Sciences is elaborated. Then structural alterations are experimentally applied, which were localized by SP2E afterwards. In the end four experimental sensitivity studies are shown and discussed. For each measurement series the structural alteration was increased, which was successfully tracked by SP2E. The experimental results are plausible and in accordance with the developed theories. By repeating these experiments, the applicability of SP2E for damage localization is experimentally proven.
Nanostructured materials are extensively applied in many fields of material science for new industrial applications, particularly in the automotive, aerospace industry due to their exceptional physical and mechanical properties. Experimental testing of nanomaterials is expensive, timeconsuming,challenging and sometimes unfeasible. Therefore,computational simulations have been employed as alternative method to predict macroscopic material properties. The behavior of polymeric nanocomposites (PNCs) are highly complex.
The origins of macroscopic material properties reside in the properties and interactions taking place on finer scales. It is therefore essential to use multiscale modeling strategy to properly account for all large length and time scales associated with these material systems, which across many orders of magnitude. Numerous multiscale models of PNCs have been established, however, most of them connect only two scales. There are a few multiscale models for PNCs bridging four length scales (nano-, micro-, meso- and macro-scales). In addition, nanomaterials are stochastic in nature and the prediction of macroscopic mechanical properties are influenced by many factors such as fine-scale features. The predicted mechanical properties obtained by traditional approaches significantly deviate from the measured values in experiments due to neglecting uncertainty of material features. This discrepancy is indicated that the effective macroscopic properties of materials are highly sensitive to various sources of uncertainty, such as loading and boundary conditions and material characteristics, etc., while very few stochastic multiscale models for PNCs have been developed. Therefore, it is essential to construct PNC models within the framework of stochastic modeling and quantify the stochastic effect of the input parameters on the macroscopic mechanical properties of those materials.
This study aims to develop computational models at four length scales (nano-, micro-, meso- and macro-scales) and hierarchical upscaling approaches bridging length scales from nano- to macro-scales. A framework for uncertainty quantification (UQ) applied to predict the mechanical properties
of the PNCs in dependence of material features at different scales is studied. Sensitivity and uncertainty analysis are of great helps in quantifying the effect of input parameters, considering both main and interaction effects, on the mechanical properties of the PNCs. To achieve this major
goal, the following tasks are carried out:
At nano-scale, molecular dynamics (MD) were used to investigate deformation mechanism of glassy amorphous polyethylene (PE) in dependence of temperature and strain rate. Steered molecular dynamics (SMD)were also employed to investigate interfacial characteristic of the PNCs.
At mico-scale, we developed an atomistic-based continuum model represented by a representative volume element (RVE) in which the SWNT’s properties and the SWNT/polymer interphase are modeled at nano-scale, the surrounding polymer matrix is modeled by solid elements. Then, a two-parameter model was employed at meso-scale. A hierarchical multiscale approach has been developed to obtain the structure-property relations at one length scale and transfer the effect to the higher length
scales. In particular, we homogenized the RVE into an equivalent fiber.
The equivalent fiber was then employed in a micromechanical analysis (i.e. Mori-Tanaka model) to predict the effective macroscopic properties of the PNC. Furthermore, an averaging homogenization process was also used to obtain the effective stiffness of the PCN at meso-scale.
Stochastic modeling and uncertainty quantification consist of the following ingredients:
- Simple random sampling, Latin hypercube sampling, Sobol’ quasirandom sequences, Iman and Conover’s method (inducing correlation in Latin hypercube sampling) are employed to generate independent and dependent sample data, respectively.
- Surrogate models, such as polynomial regression, moving least squares (MLS), hybrid method combining polynomial regression and MLS, Kriging regression, and penalized spline regression, are employed as an approximation of a mechanical model. The advantage of the surrogate models is the high computational efficiency and robust as they can be constructed from a limited amount of available data.
- Global sensitivity analysis (SA) methods, such as variance-based methods for models with independent and dependent input parameters, Fourier-based techniques for performing variance-based methods and partial derivatives, elementary effects in the context of local SA, are used to quantify the effects of input parameters and their interactions on the mechanical properties of the PNCs. A bootstrap technique is used to assess the robustness of the global SA methods with respect to their performance.
In addition, the probability distribution of mechanical properties are determined by using the probability plot method. The upper and lower bounds of the predicted Young’s modulus according to 95 % prediction intervals were provided.
The above-mentioned methods study on the behaviour of intact materials. Novel numerical methods such as a node-based smoothed extended finite element method (NS-XFEM) and an edge-based smoothed phantom node method (ES-Phantom node) were developed for fracture problems. These methods can be used to account for crack at macro-scale for future works. The predicted mechanical properties were validated and verified. They show good agreement with previous experimental and simulations results.
Die fortschreitende Digitalisierung lässt innovative bauprojekt- und unternehmensinterne Workflows sowie Organisationssysteme entstehen. In diesem Zusammenhang ist die digitale Fortentwicklung durch Building Information Modeling [BIM] als Veränderungsprozess zu definieren, der Organisationsstrukturen nachhaltig umformen wird. BIM ist die führende digitale Arbeitsmethodik im Bauwesen, die entwurfs-, ausführungs- und bauprojektbezogenen Belangen gerecht werden kann. Die deutsche Bauwirtschaft ist im Vergleich zu anderen Branchen jedoch als digital rückständig zu betrachten. Sie ist durch einen Markt gekennzeichnet, an dem kleine und mittelständische Unternehmen [KMU] in hoher Zahl vertreten sind. Aufgrund von Anwendungsunkenntnis der kleinen und mittelständischen Unternehmen fehlt der flächendeckende und durchgängige BIM-Einsatz in Projekten. Mit dem Fokus auf dem Bauprojekt als temporärer Organisation adressiert der vorliegende Forschungsschwerpunkt die Schaffung eines realistischen Abbilds erprobter BIM-Anwendungsfälle in Modellprojekten. Herausgearbeitet werden derzeit bestehende BIM-Herausforderungen für Erstanwender, die die durchgängige BIM-Anwendung in Deutschland bisher hemmen.
Die Forschungsarbeit fokussiert sich auf die Evaluation erfolgskritischer Faktoren [ekF] in BIM-Anwendungsfällen [AWF] im Rahmen einer qualitativen Inhaltsanalyse. Die digitale Transformation birgt strukturrelevante Veränderungsdeterminanten für Organisationen durch die BIM-Anwendung und außerdem Herausforderungen, die in der Anwendungsfallforschung betrachtet werden.
Die Zielstellung ist dreiteilig. Ein entwickeltes BIM-Strukturmodell erfasst die aktuelle Richtlinienarbeit sowie Standardisierung und stellt dadurch den Rahmen notwendiger BIM-Strukturen im Bauprojekt auf. Aus dem Strukturmodell ist ein Modell zur Prüfung von Anwendungsfallrisiken abgeleitet worden. Dieses wird auf gezielt recherchierte BIM-Modellprojekte in Deutschland angewendet, um aus den erfolgskritischen Faktoren der darin praktizierten BIM-Anwendungsfälle eine ekF-Risikomatrix abzuleiten. Daraus geht ein unterstützendes BIM-Anwendungsinstrument in Form von BPMN-Abläufen für KMU hervor. Resultierend aus der Verbindung des BIM-Strukturmodels und der Anwendungsfallanalyse wird in den einzelnen Ablaufübersichten eine Risikoverortung je Anwendungsfall kenntlich gemacht. Unternehmen ohne BIM-Anwendungsexpertise in Bauprojektorganisationen erhalten auf diese Weise einen instrumentellen und niederschwelligen Zugang zu BIM, um die kollaborativen und wirtschaftlichen Vorteile der digitalen Arbeitsmethodik nutzen zu können.
Modell bedarfsorientierter Leistungserbringung im FM auf Grundlage von Sensortechnologien und BIM
(2023)
Während der Digitalisierung im Bauwesen insbesondere im Bereich der Planungs- und Errichtungsphase von Bauwerken immer größere Aufmerksamkeit zuteilwird, ist das digitale Potenzial im Facility Management weit weniger ausgeschöpft, als dies möglich wäre. Vor dem Hintergrund, dass die Bewirtschaftung von Gebäuden jedoch einen wesentlichen Kostenanteil im Lebenszyklus darstellt, ist eine Fokussierung auf digitale Prozesse im Gebäudebetrieb erforderlich. Im Facility Management werden Dienstleistungen häufig verrichtungsorientiert, d. h. nach statischen Intervallen, oder bedarfsorientiert erbracht. Beide Arten der Leistungserbringung weisen Defizite auf, beispielweise weil Tätigkeiten auf Basis definierter Intervalle erbracht werden, ohne dass eine Notwendigkeit besteht oder weil bestehende Bedarfe mangels Möglichkeiten der Bedarfsermittlung nicht identifiziert werden. Speziell die Definition und Ermittlung eines Bedarfs zur Leistungserbringung ist häufig subjektiv geprägt. Auch sind Dienstleister oft nicht in frühen Phasen der Gebäudeplanung involviert und erhalten für ihre Dienstleistungen notwendige Daten und Informationen erst kurz vor Inbetriebnahme des zu betreibenden Gebäudes.
Aktuelle Ansätze des Building Information Modeling (BIM) und die zunehmende Verfügbarkeit von Sensortechnologien in Gebäuden bieten Chancen, die o. g. Defizite zu beheben.
In der vorliegenden Arbeit werden deshalb Datenmodelle und Methoden entwickelt, die mithilfe von BIM-basierten Datenbankstrukturen sowie Auswertungs- und Entscheidungsmethodiken Dienstleistungen der Gebäudebewirtschaftung objektiviert und automatisiert auslösen können. Der Fokus der Arbeit liegt dabei auf dem Facility Service der Reinigungs- und Pflegedienste des infrastrukturellen Facility Managements.
Eine umfangreiche Recherche etablierter Normen und Standards sowie öffentlich zugänglicher Leistungsausschreibungen bilden die Grundlage der Definition erforderlicher Informationen zur Leistungserbringung. Die identifizierten statischen Gebäude- und Prozessinformationen werden in einem relationalen Datenbankmodell strukturiert, das nach einer Darstellung von Messgrößen und der Beschreibung des Vorgehens zur Auswahl geeigneter Sensoren für die Erfassung von Bedarfen, um Sensorinformationen erweitert wird. Um Messwerte verschiedener und bereits in Gebäuden existenten Sensoren für die Leistungsauslösung verwenden zu können, erfolgt die Implementierung einer Normierungsmethodik in das Datenbankmodell. Auf diese Weise kann der Bedarf zur Leistungserbringung ausgehend von Grenzwerten ermitteln werden. Auch sind Verknüpfungsmethoden zur Kombination verschiedener Anwendungen in dem Datenbankmodell integriert. Zusätzlich zur direkten Auslösung erforderlicher Aktivitäten ermöglicht das entwickelte Modell eine opportune Auslösung von Leistungen, d. h. eine Leistungserbringung vor dem eigentlich bestehenden Bedarf. Auf diese Weise können tätigkeitsähnliche oder räumlich nah beieinander liegende Tätigkeiten sinnvoll vorzeitig erbracht werden, um für den Dienstleister eine Wegstreckeneinsparung zu ermöglichen. Die Arbeit beschreibt zudem die für die Auswertung, Entscheidungsfindung und Auftragsüberwachung benötigen Algorithmen.
Die Validierung des entwickelten Modells bedarfsorientierter Leistungserbringung erfolgt in einer relationalen Datenbank und zeigt simulativ für unterschiedliche Szenarien des Gebäudebetriebs, dass Bedarfsermittlungen auf Grundlage von Sensortechnologien erfolgen und Leistungen opportun ausgelöst, beauftragt und dokumentiert werden können.
In recent decades, a multitude of concepts and models were developed to understand, assess and predict muscular mechanics in the context of physiological and pathological events.
Most of these models are highly specialized and designed to selectively address fields in, e.g., medicine, sports science, forensics, product design or CGI; their data are often not transferable to other ranges of application. A single universal model, which covers the details of biochemical and neural processes, as well as the development of internal and external force and motion patterns and appearance could not be practical with regard to the diversity of the questions to be investigated and the task to find answers efficiently. With reasonable limitations though, a generalized approach is feasible.
The objective of the work at hand was to develop a model for muscle simulation which covers the phenomenological aspects, and thus is universally applicable in domains where up until now specialized models were utilized. This includes investigations on active and passive motion, structural interaction of muscles within the body and with external elements, for example in crash scenarios, but also research topics like the verification of in vivo experiments and parameter identification. For this purpose, elements for the simulation of incompressible deformations were studied, adapted and implemented into the finite element code SLang. Various anisotropic, visco-elastic muscle models were developed or enhanced. The applicability was demonstrated on the base of several examples, and a general base for the implementation of further material models was developed and elaborated.
Identification of flaws in structures is a critical element in the management of maintenance and quality assurance processes in engineering. Nondestructive testing (NDT) techniques based on a wide range of physical principles have been developed and are used in common practice for structural health monitoring. However, basic NDT techniques are usually limited in their ability to provide the accurate information on locations, dimensions and shapes of flaws. One alternative to extract additional information from the results of NDT is to append it with a computational model that provides detailed analysis of the physical process involved and enables the accurate identification of the flaw parameters. The aim here is to develop the strategies to uniquely identify cracks in two-dimensional 2D) structures under dynamic loadings.
A local NDT technique combined eXtended Finite Element Method (XFEM) with dynamic loading in order to identify the cracks in the structures quickly and accurately is developed in this dissertation. The Newmark-b time integration method with Rayleigh damping is used for the time integration. We apply Nelder-Mead (NM)and Quasi-Newton (QN) methods for identifying the crack tip in plate. The inverse problem is solved iteratively, in which XFEM is used for solving the forward problem in each iteration. For a timeharmonic excitation with a single frequency and a short-duration signal measured along part of the external boundary, the crack is detected through the solution of an inverse time-dependent problem. Compared to the static load, we show that the dynamic loads are more effective for crack detection problems. Moreover, we tested different dynamic loads and find that NM method works more efficient under the harmonic load than the pounding load while the QN method achieves almost the same results for both load types.
A global strategy, Multilevel Coordinate Search (MCS) with XFEM (XFEM-MCS) methodology under the dynamic electric load, to detect multiple cracks in 2D piezoelectric plates is proposed in this dissertation. The Newmark-b method is employed for the time integration and in each iteration the forward problem is solved by XFEM for various cracks. The objective functional is minimized by using a global search algorithm MCS. The test problems show that the XFEM-MCS algorithm under the dynamic electric load can be effectively employed for multiple cracks detection in piezoelectric materials, and it proves to be robust in identifying defects in piezoelectric structures. Fiber-reinforced composites (FRCs) are extensively applied in practical engineering since they have high stiffness and strength. Experiments reveal a so-called interphase zone, i.e. the space between the outside interface of the fiber and the inside interface of the matrix. The interphase strength between the fiber and the matrix strongly affects the mechanical properties as a result of the large ratio of interface/volume. For the purpose of understanding the mechanical properties of FRCs with functionally graded interphase (FGI), a closed-form expression of the interface strength between a fiber and a matrix is obtained in this dissertation using a continuum modeling approach according to the ver derWaals (vdW) forces. Based on the interatomic potential, we develop a new modified nonlinear cohesive law, which is applied to study the interface delamination of FRCs with FGI under different loadings. The analytical solutions show that the delamination behavior strongly depends on the interphase thickness, the fiber radius, the Young’s moduli and Poisson’s ratios of the fiber and the matrix. Thermal conductivity is the property of a material to conduct heat. With the development and deep research of 2D materials, especially graphene and molybdenum disulfide (MoS2), the thermal conductivity of 2D materials attracts wide attentions. The thermal conductivity of graphene nanoribbons (GNRs) is found to appear a tendency of decreasing under tensile strain by classical molecular dynamics (MD) simulations. Hence, the strain effects of graphene can play a key role in the continuous tunability and applicability of its thermal conductivity property at nanoscale, and the dissipation of thermal conductivity is an obstacle for the applications of thermal management. Up to now, the thermal conductivity of graphene under shear deformation has not been investigated yet. From a practical point of view, good thermal managements of GNRs have significantly potential applications of future GNR-based thermal nanodevices, which can greatly improve performances of the nanosized devices due to heat dissipations. Meanwhile, graphene is a thin membrane structure, it is also important to understand the wrinkling behavior under shear deformation. MoS2 exists in the stable semiconducting 1H phase (1H-MoS2) while the metallic 1T phase (1T-MoS2) is unstable at ambient conditions. As it’s well known that much attention has been focused on studying the nonlinear optical properties of the 1H-MoS2. In a very recent research, the 1T-type monolayer crystals of TMDCs, MX2 (MoS2, WS2 ...) was reported having an intrinsic in-plane negative Poisson’s ratio. Luckily, nearly at the same time, unprecedented long-term (>3months) air stability of the 1T-MoS2 can be achieved by using the donor lithium hydride (LiH). Therefore, it’s very important to study the thermal conductivity of 1T-MoS2.
The thermal conductivity of graphene under shear strain is systematically studied in this dissertation by MD simulations. The results show that, in contrast to the dramatic decrease of thermal conductivity of graphene under uniaxial tensile, the thermal conductivity of graphene is not sensitive to the shear strain, and the thermal conductivity decreases only 12-16%. The wrinkle evolves when the shear strain is around 5%-10%, but the thermal conductivity barely changes.
The thermal conductivities of single-layer 1H-MoS2(1H-SLMoS2) and single-layer 1T-MoS2 (1T-SLMoS2) with different sample sizes, temperatures and strain rates have been studied systematically in this dissertation. We find that the thermal conductivities of 1H-SLMoS2 and 1T-SLMoS2 in both the armchair and the zigzag directions increase with the increasing of the sample length, while the increase of the width of the sample has minor effect on the thermal conductions of these two structures. The thermal conductivity of 1HSLMoS2 is smaller than that of 1T-SLMoS2 under size effect. Furthermore, the temperature effect results show that the thermal conductivities of both 1H-SLMoS2 and 1T-SLMoS2 decrease with the increasing of the temperature. The thermal conductivities of 1HSLMoS2 and 1T-SLMoS2 are nearly the same (difference <6%) in both of the chiral orientations under corresponding temperatures, especially in the armchair direction (difference <2.8%). Moreover, we find that the strain effects on the thermal conductivity of 1HSLMoS2 and 1T-SLMoS2 are different. More specifically, the thermal conductivity decreases with the increasing tensile strain rate for
1T-SLMoS2, while fluctuates with the growth of the strain for 1HSLMoS2. Finally, we find that the thermal conductivity of same sized 1H-SLMoS2 is similar with that of the strained 1H-SLMoS2 structure.