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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.
In recent years, lightweight materials, such as polymer composite materials (PNCs) have been studied and developed due to their excellent physical and chemical properties. Structures composed of these composite materials are widely used in aerospace engineering structures, automotive components, and electrical devices. The excellent and outstanding mechanical, thermal, and electrical properties of Carbon nanotube (CNT) make it an ideal filler to strengthen polymer materials’ comparable properties. The heat transfer of composite materials has very promising engineering applications in many fields, especially in electronic devices and energy storage equipment. It is essential in high-energy density systems since electronic components need heat dissipation functionality. Or in other words, in electronic devices the generated heat should ideally be dissipated by light and small heat sinks.
Polymeric composites consist of fillers embedded in a polymer matrix, the first ones will significantly affect the overall (macroscopic) performance of the material. There are many common carbon-based fillers such as single-walled carbon nanotubes (SWCNT), multi-walled carbon nanotubes (MWCNT), carbon nanobuds (CNB), fullerene, and graphene. Additives inside the matrix have become a popular subject for researchers. Some extraordinary characters, such as high-performance load, lightweight design, excellent chemical resistance, easy processing, and heat transfer, make the design of polymeric nanotube composites (PNCs) flexible. Due to the reinforcing effects with different fillers on composite materials, it has a higher degree of freedom and can be designed for the structure according to specific applications’ needs. As already stated, our research focus will be on SWCNT enhanced PNCs. Since experiments are timeconsuming, sometimes expensive and cannot shed light into phenomena taking place for instance at the interfaces/interphases of composites, they are often complemented through theoretical and computational analysis.
While most studies are based on deterministic approaches, there is a comparatively lower number of stochastic methods accounting for uncertainties in the input parameters. In deterministic models, the output of the model is fully determined by the parameter values and the initial conditions. However, uncertainties in the input parameters such as aspect ratio, volume fraction, thermal properties of fiber and matrix need to be taken into account for reliable predictions. In this research, a stochastic multiscale method is provided to study the influence of numerous uncertain input parameters on the thermal conductivity of the composite. Therefore, a hierarchical multi-scale method based on computational homogenization is presented in to predict the macroscopic thermal conductivity based on the fine-scale structure. In order to study the inner mechanism, we use the finite element method and employ surrogate models to conduct a Global Sensitivity Analysis (GSA). The SA is performed in order to quantify the influence of the conductivity of the fiber, matrix, Kapitza resistance, volume fraction and aspect ratio on the macroscopic conductivity. Therefore, we compute first-order and total-effect sensitivity indices with different surrogate models.
As stochastic multiscale models are computational expensive, surrogate approaches are commonly exploited. With the emergence of high performance computing and artificial intelligence, machine learning has become a popular modeling tool for numerous applications. Machine learning (ML) is commonly used in regression and maps data through specific rules with algorithms to build input and output models. They are particularly useful for nonlinear input-output relationships when sufficient data is available. ML has also been used in the design of new materials and multiscale analysis. For instance, Artificial neural networks and integrated learning seem to be ideally for such a task. They can theoretically simulate any non-linear relationship through the connection of neurons. Mapping relationships are employed to carry out data-driven simulations of inputs and outputs in stochastic modeling.
This research aims to develop a stochastic multi-scale computational models of PNCs in heat transfer. Multi-scale stochastic modeling with uncertainty analysis and machine learning methods consist of the following components:
-Uncertainty Analysis. A surrogate based global sensitivity analysis is coupled with a hierarchical multi-scale method employing computational homogenization. The effect of the conductivity of the fibers and the matrix, the Kapitza resistance, volume fraction and aspect ratio on the ’macroscopic’ conductivity of the composite is systematically studied. All selected surrogate models yield consistently the conclusions that the most influential input parameters are the aspect ratio followed by the volume fraction. The Kapitza Resistance has no significant effect on the thermal conductivity of the PNCs. The most accurate surrogate model in terms of the R2 value is the moving least square (MLS).
-Hybrid Machine Learning Algorithms. A combination of artificial neural network (ANN) and particle swarm optimization (PSO) is applied to estimate the relationship between variable input and output parameters. The ANN is used for modeling the composite while PSO improves the prediction performance through an optimized global minimum search. The thermal conductivity of the fibers and the matrix, the kapitza resistance, volume fraction and aspect ratio are selected as input parameters. The output is the macroscopic (homogenized) thermal conductivity of the composite. The results show that the PSO significantly improves the predictive ability of this hybrid intelligent algorithm, which outperforms traditional neural networks.
-Stochastic Integrated Machine Learning. A stochastic integrated machine learning based multiscale approach for the prediction of the macroscopic thermal conductivity in PNCs is developed. Seven types of machine learning models are exploited in this research, namely Multivariate Adaptive Regression Splines (MARS), Support Vector Machine (SVM), Regression Tree (RT), Bagging Tree (Bag), Random Forest (RF), Gradient Boosting Machine (GBM) and Cubist. They are used as components of stochastic modeling to construct the relationship between the variable of the inputs’ uncertainty and the macroscopic thermal conductivity of PNCs. Particle Swarm Optimization (PSO) is used for hyper-parameter tuning to find the global optimal values leading to a significant reduction in the computational cost. The advantages and disadvantages of various methods are also analyzed in terms of computing time and model complexity to finally give a recommendation for the applicability of different models.
Heutige Methoden zur Soll-Spezifikation von Bauleistungen (Kostenermittlung und zeitliche Ablaufplanung) gehen von einer abstrahierten und vereinfachten Betrachtung der Zusammenhänge bei Bauprojekten aus. Leistungsverzeichnisse, Kostenermittlungen und Bauzeitpläne orientieren sich nur indirekt an der Geometrie des Bauwerks und der Baustelle. Die dabei verwendeten Medien wie Papier, 2D-Dateien, digitale Leistungsbeschreibungen oder 3D-Darstellungen lassen die Suche nach Informationen auf der Baustelle zu einem zeitaufwändigen und in Anbetracht existierender Medientechnologien ineffizienten Prozess werden. Interaktive virtuelle Umgebungen erlauben die Auflösung starrer Zusammenhänge durch interaktive Eingriffe des Anwenders und visualisieren komplexe bauproduktionstechnische Vorgänge. Das Konzept der visuellen interaktiven Simulation der Bauproduktion sieht vor, die Soll-Spezifikation anhand eines interaktiven 3D-Modells zu entwickeln, um räumliche Veränderungen und parallele Prozesse auf der virtuellen Baustelle im Rahmen der Entscheidungsfindung zum Bauablauf besser berücksichtigen zu können. Verlangt man einen hohen Grad an Interaktivität mit dem 3D-Modell, dann bieten sich Computerspieltechnologien sehr gut zu Verifikationszwecken an. Die visuelle interaktive Simulation der Bauproduktion ist damit als eine 3D-modellbasierte Methode der Prozessmodellierung zu verstehen, die Entscheidungen als Input benötigt und die Kostenermittlung sowie die zeitliche Ablaufplanung als Output liefert.
The reduction of the cement clinker content is an important prerequisite for the improvement of the CO2-footprint of concrete. Nevertheless, the durability of such concretes must be sufficient to guarantee a satisfactory service life of structures. Salt frost scaling resistance is a critical factor in this regard, as it is often diminished at increased clinker substitution rates. Furthermore, only insufficient long-term experience for such concretes exists. A high salt frost scaling resistance thus cannot be achieved by applying only descriptive criteria, such as the concrete composition. It is therefore to be expected, that in the long term a performance based service life prediction will replace the descriptive concept.
To achieve the important goal of clinker reduction for concretes also in cold and temperate climates it is important to understand the underlying mechanisms for salt frost scaling. However, conflicting damage theories dominate the current State of the Art. It was consequently derived as the goal of this thesis to evaluate existing damage theories and to examine them experimentally. It was found that only two theories have the potential to describe the salt frost attack satisfactorily – the glue spall theory and the cryogenic suction theory.
The glue spall theory attributes the surface scaling to the interaction of an external ice layer with the concrete surface. Only when moderate amounts of deicing salt are present in the test solution the resulting mechanical properties of the ice can cause scaling. However, the results in this thesis indicate that severe scaling also occurs at deicing salt levels, at which the ice is much too soft to damage concrete. Thus, the inability of the glue spall theory to account for all aspects of salt frost scaling was shown.
The cryogenic suction theory is based on the eutectic behavior of salt solutions, which consist of two phases – water ice and liquid brine – between the freezing point and the eutectic temperature. The liquid brine acts as an additional moisture reservoir, which facilitates the growth of ice lenses in the surface layer of the concrete. The experiments in this thesis confirmed, that the ice formation in hardened cement paste increases due to the suction of brine at sub-zero temperatures. The extent of additional ice formation was influenced mainly by the porosity and by the chloride binding capacity of the hardened cement paste.
Consequently, the cryogenic suction theory plausibly describes the actual generation of scaling, but it has to be expanded by some crucial aspects to represent the salt frost scaling attack completely. The most important aspect is the intensive saturation process, which is ascribed to the so-called micro ice lens pump. Therefore a combined damage theory was proposed, which considers multiple saturation processes. Important aspects of this combined theory were confirmed experimentally.
As a result, the combined damage theory constitutes a good basis to understand the salt frost scaling attack on concrete on a fundamental level. Furthermore, a new approach was identified, to account for the reduced salt frost scaling resistance of concretes with reduced clinker content.
Revisiting vernacular technique: Engineering a low environmental impact earth stabilisation method
(2022)
The major drawbacks of earth as a construction material — such as its low water stability and moderate strength — have led mankind to stabilize earth. Different civilizations developed vernacular techniques mainly focussing on lime, pozzolan or gypsum stabilization. Recently, cement has become the most commonly used additive in earth stabilization as it improves the strength and durability of plain earth. Also, it is a familiar and globally available construction material. However, using cement as an additive reduces the environmental advantages of earth and run counter to global targets regarding the reduction of CO2 emissions. Alternatives to cement stabilization are currently neither efficient enough to reduce its environmental impact nor allow the possibility of obtaining better results than those of cement. As such, this thesis deals with the rediscovery of a reverse engineering approach for a low environmental impact earth stabilization technique, aiming to replace cement in earth stabilization.
The first step in the method consists in a comprehensive review of earth stabilization with regards to earthen building standards and soil classification, which allows us to identify the research gap. The review showed that there is great potential in using other additives which result in similar improvements as those achieved by cement. However, the studies that have been conducted so far either use expansive soils, which are not suitable for earth constructions or artificial pozzolans that indirectly contribute to CO2 emissions. This is the main research gap.
The key concept for the development in the second step of the method is to combine vernacular additives to both improve the strength and durability of plain earth and to reduce the CO2 emissions. Various earth-mixtures were prepared and both development and performance tests were done to investigate the performance of this technique. The laboratory analyses on mix-design have proven a high durability and the results show a remarkable increase in strength performance. Furthermore, a significant reduction in CO2 emissions in comparison to cement stabilization could be shown.
The third step of the method discusses the results drawn from the experimental programme. In addition, the potential of the new earth mixture with regards to its usability in the field of building construction and architectural design is further elaborated on.
The method used in this study is the first of its kind that allows investors to avoid the very time-consuming processes such as finding a suitable source for soil excavation and soil classification. The developed mixture has significant workability and suitability for production of stabilized earthen panels — the very first of its kind. Such a panel is practically feasible, reasonable, and could be integrated into earthen building standards in general and in particular to DIN 18948, which is related to earthen boards and published in 2018.
Das Bauwesen hat sich in den letzten Jahren durch die Globalisierung des Marktes verbunden mit einer verstärkten Nutzung moderner Technologien stark gewandelt. Die Planung und die Durchführung von Bauvorhaben werden zunehmend komplexer und sind mit erhöhten Risiken verbunden. Geld- und Zeitressourcen werden bei einem immer härter werdenden Konkurrenzkampf knapper.
Das Projektmanagement stellt Lösungsansätze bereit, um Bauvorhaben auch unter erschwerten Bedingungen und erhöhten Risiken erfolgreich zum Abschluss zu bringen. Dabei hat ein systematisches Risikomanagement beginnend bei der Projektentwicklung bis zum Projektabschluss eine für den Projekterfolg entscheidende Bedeutung.
Ziel der Arbeit ist es, eine quantitative Risikoerfassung für Projektmanager als professionelle Bauherrenvertretung und die Simulation der Risikoauswirkungen auf den Verlauf eines Projektes während der Planungs- und Bauphase zu ermöglichen. Mit Hilfe eines abstrakten Modells soll eine differenzierte, praxisnahe Simulation durchführbar sein, die die verschiedenen Arten der Leistungs- und Kostenentstehung widerspiegelt. Parallel dazu soll die Beschreibung von Risiken so abstrahiert werden, dass beliebige Risiken quantitativ erfassbar und anschließend ihre Auswirkungen inklusive mögliche Gegenmaßnahmen in das Modell integrierbar sind.
Anhand zweier Beispiele werden die unterschiedlichen Einsatzmöglichkeiten der quantitativen Erfassung von Projektrisiken und der anschließenden Simulation ihrer Auswirkungen aufgezeigt. Bei dem ersten Beispiel, einem realen, bereits abgeschlossenen Schieneninfrastrukturprojekt, wird die Wirksamkeit einer vorbeugenden Maßnahme gegen ein Projektrisiko untersucht. Im zweiten Beispiel wird ein Planspielansatz zur praxisnahen Aus- und Weiterbildung von Projektmanagern entwickelt. Inhalt des Planspiels ist die Planung und Errichtung eines privatfinanzierten, öffentlichen Repräsentationsbaus mit teilweiser Fremdnutzung.
Due to the development of new technologies and materials, optimized bridge design has recently gained more attention. The aim is to reduce the bridge components materials and the CO2 emission from the cement manufacturing process. Thus, most long-span bridges are designed to be with high flexibility, low structural damping, and longer and slender spans. Such designs lead, however, to aeroelastic challenges. Moreover, the consideration of both the structural and aeroelastic behavior in bridges leads to contradictory solutions as the structural constraints lead to deck prototypes with high depth which provide high inertia to material volume ratios. On the other hand, considering solely the aerodynamic requirements, slender airfoil-shaped bridge box girders are recommended since they prevent vortex shedding and exhibit minimum drag. Within this framework comes this study which provides approaches to find optimal bridge deck cross-sections while considering the aerodynamic effects. Shape optimization of deck cross-section is usually formulated to minimize the amount of material by finding adequate parameters such as the depth, the height, and the thickness and while ensuring the overall stability of the structure by the application of some constraints. Codes and studies have been implemented to analyze the wind phenomena and the structural responses towards bridge deck cross-sections where simplifications have been adopted due to the complexity and the uniqueness of such components besides the difficulty of obtaining a final model of the aerodynamic behavior. In this thesis, two main perspectives have been studied; the first is fully deterministic and presents a novel framework on generating optimal aerodynamic shapes for streamlined and trapezoidal cross-sections based on the meta-modeling approach. Single and multi-objective optimizations were both carried out and a Pareto Front is generated. The performance of the optimal designs is checked afterwards. In the second part, a new strategy based on Reliability-Based Design Optimization (RBDO) to mitigate the vortex-induced vibration (VIV) on the Trans-Tokyo Bay bridge is proposed. Small changes in the leading and trailing edges are presented and uncertainties are considered in the structural system. Probabilistic constraints based on polynomial regression are evaluated and the problem is solved while applying the Reliability Index Approach (RIA) and the Performance Measure Approach (PMA). The results obtained in the first part showed that the aspect ratio has a significant effect on the aerodynamic behavior where deeper cross-sections have lower resistance against flutter and should be avoided. In the second part, the adopted RBDO approach succeeded to mitigate the VIV, and it is proven that designs with narrow or prolonged bottom-base length and featuring an abrupt surface change in the leading and trailing edges can lead to high vertical vibration amplitude. It is expected that this research will help engineers with the selections of the adequate deck cross-section layout, and encourage researchers to apply concepts of optimization regarding this field and develop the presented approaches for further studies.
Mitigating Risks of Corruption in Construction: A theoretical rationale for BIM adoption in Ethiopia
(2021)
This PhD thesis sets out to investigate the potentials of Building Information Modeling (BIM) to mitigate risks of corruption in the Ethiopian public construction sector. The wide-ranging capabilities and promises of BIM have led to the strong perception among researchers and practitioners that it is an indispensable technology. Consequently, it has become the frequent subject of science and research. Meanwhile, many countries, especially the developed ones, have committed themselves to applying the technology extensively. Increasing productivity is the most common and frequently cited reason for that.
However, both technology developers and adopters are oblivious to the potentials of BIM in addressing critical challenges in the construction sector, such as corruption. This particularly would be significant in developing countries like Ethiopia, where its problems and effects are acute. Studies reveal that bribery and corruption have long pervaded the construction industry worldwide. The complex and fragmented nature of the sector provides an environment for corruption. The Ethiopian construction sector is not immune from this epidemic reality. In fact, it is regarded as one of the most vulnerable sectors owing to varying socio-economic and political factors. Since 2015, Ethiopia has started adopting BIM, yet without clear goals and strategies. As a result, the potential of BIM for combating concrete problems of the sector remains untapped. To this end, this dissertation does pioneering work by showing how collaboration and coordination features of the technology contribute to minimizing the opportunities for corruption. Tracing loopholes, otherwise, would remain complex and ineffective in the traditional documentation processes.
Proceeding from this anticipation, this thesis brings up two primary questions: what are areas and risks of corruption in case of the Ethiopian public construction projects; and how could BIM be leveraged to mitigate these risks? To tackle these and other secondary questions, the research employs a mixed-method approach. The selected main research strategies are Survey, Grounded Theory (GT) and Archival Study. First, the author disseminates an online questionnaire among Ethiopian construction engineering professionals to pinpoint areas of vulnerability to corruption. 155 responses are compiled and scrutinized quantitatively. Then, a semi-structured in-depth interview is conducted with 20 senior professionals, primarily to comprehend opportunities for and risks of corruption in those identified highly vulnerable project stages and decision points. At the same time, open interviews (consultations) are held with 14 informants to be aware of state of the construction documentation, BIM and loopholes for corruption in the country. Consequently, these qualitative data are analyzed utilizing the principles of GT, heat/risk mapping and Social Network Analysis (SNA). The risk mapping assists the researcher in the course of prioritizing corruption risks; whilst through SNA, methodically, it is feasible to identify key actors/stakeholders in the corruption venture. Based on the generated research data, the author constructs a [substantive] grounded theory around the elements of corruption in the Ethiopian public construction sector. This theory, later, guides the subsequent strategic proposition of BIM. Finally, 85 public construction related cases are also analyzed systematically to substantiate and confirm previous findings.
By ways of these multiple research endeavors that is based, first and foremost, on the triangulation of qualitative and quantitative data analysis, the author conveys a number of key findings. First, estimations, tender document preparation and evaluation, construction material as well as quality control and additional work orders are found to be the most vulnerable stages in the design, tendering and construction phases respectively. Second, middle management personnel of contractors and clients, aided by brokers, play most critical roles in corrupt transactions within the prevalent corruption network. Third, grand corruption persists in the sector, attributed to the fact that top management and higher officials entertain their overriding power, supported by the lack of project audits and accountability. Contrarily, individuals at operation level utilize intentional and unintentional 'errors’ as an opportunity for corruption.
In light of these findings, two conceptual BIM-based risk mitigation strategies are prescribed: active and passive automation of project audits; and the monitoring of project information throughout projects’ value chain. These propositions are made in reliance on BIM’s present dimensional capabilities and the promises of Integrated Project Delivery (IPD). Moreover, BIM’s synchronous potentials with other technologies such as Information and Communication Technology (ICT), and Radio Frequency technologies are topics which received a treatment. All these arguments form the basis for the main thesis of this dissertation, that BIM is able to mitigate corruption risks in the Ethiopian public construction sector. The discourse on the skepticisms about BIM that would stem from the complex nature of corruption and strategic as well as technological limitations of BIM is also illuminated and complemented by this work. Thus, the thesis uncovers possible research gaps and lays the foundation for further studies.
Zwischen den Jahren 1920 und 1930 kam es an der kalifornischen Küste zu Bauschäden an Brücken und Fahrbahnen, die sich vor allem in einer deutlichen Rissbildung äußerten. Seither werden immer wieder Bauschäden beschrieben, deren Ursache in der Reaktion von Zuschlägen, die „reaktive“ Kieselsäure enthalten, mit der Porenlösung des Betons zu sehen ist. Diese Reaktion wird als Alkali-Kieselsäure Reaktion (AKR) bezeichnet. Seit der ersten Veröffentlichung von Stanton über die „alkali-aggregate reaction“ an opalhaltigen Zuschlägen sind hunderte von Forschungsarbeiten zu diesem Thema durchgeführt und deren Ergebnisse veröffentlicht worden. Trotz eingehender Forschung seit mehr als 8o Jahren ist weder der Mechanismus der AKR vollständig geklärt noch eine eindeutige Voraussage über die Gefährdung von Bauwerken oder Bauteilen mit potentiell AKR-empfindlichen Zuschlägen möglich. Das liegt vor allen Dingen daran, das es sich bei der AKR um eine Reaktion handelt, die aus einer komplexen Abfolge chemischer und physikalischer Prozesse besteht, die in ihrer Gesamtheit zu einer Schädigung von Beton bzw. Betonbauteilen und Bauwerken führen können. Eine geschlossene Beschreibung und Behandlung dieser Reaktion ist nicht möglich, solange keine befriedigende Kenntnis über den Ablauf der einzelnen Schritte vorliegt. Dazu bedarf es grundsätzlicher Untersuchungen der einzelnen chemischen und physikalischen Reaktionsschritte sowie einer möglichst quantitativen Bewertung der verschiedenen Einflussfaktoren. Grundsätzlich gibt es weltweit eine ganze Reihe von Richtlinien und Normen , die dazu verhelfen sollen, Schädigungen an Bauwerken durch AKR zu verhindern. In Deutschland ist das momentan gültige Regelwerk die sogenannte Alkali-Richtlinie des deutschen Ausschusses für Stahlbeton (DAfStb). Sie dient zur Beurteilung von Zuschlag nach DIN 4226 [6, 7, 8] mit alkaliempfindlichen Bestandteilen. Dabei bezieht sich der Teil 2 der Richtlinie auf Zuschläge mit Opalsandstein, Kieselkreide und Flint aus bestimmten Gewinnungsgebieten. Hier wird eine reine Zuschlagprüfung gefordert. Teil 3 der Richtlinie bezieht sich auf präkambrische Grauwacken und andere alkaliempfindliche Gesteine. Gefordert werden hier Prüfungen der Zuschläge selbst sowie Prüfung an Betonbalken und 30er Würfeln in der Nebelkammer. Für die meisten in der Richtlinie genannten Zuschläge bilden die Prüfungen und Vorschriften eine ausreichende Sicherheit, um eine AKR zu vermeiden. Dennoch treten immer wieder Schäden mit Zuschlägen auf, die nach der Alkali-Richtlinie als unempfindlich eingestuft werden müssten. Dabei handelt es sich in der Regel um Schadensfälle, die erst nach mehreren Jahren mit spät reagierenden AKR-empfindlichen Zuschlägen auftreten. Zu diesen Zuschlägen, die gegebenenfalls speziell im Nebelkammertest innerhalb von neun Monaten keine signifikante Dehnung (<0,6mm/m) aufweisen, gehören Stressquarze, Kieselkalk, Granit, Porphyr, Kieselschiefer und Grauwacke. Die vorliegende Arbeit dient speziell der Beurteilung und Einordnung von unterschiedlichen kristallinen Quarzmodifikationen sowie der Ermittlung geeigneter Untersuchungsmethoden für die Beurteilung der AKR-Empfindlichkeit von Quarz.
Metakaolin made from kaolin is used around the world but rarely in Vietnam where abundant deposits of kaolin is found. The first studies of producing metakaolin were conducted with high quality Vietnamese kaolins. The results showed the potential to produce metakaolin, and its effect has on strength development of mortars and concretes. However, utilisation of a low quality kaolin for producing Vietnamese metakaolin has not been studied so far.
The objectives of this study were to produce a good quality metakaolin made from low quality Vietnamese kaolin and to facilitate the utilisation of Vietnamese metakaolin in composite cements.
In order to reach such goals, the optimal thermal conversion of Vietnamese kaolin into metakaolin was carried out by many investigations, and as such the optimal conversion is found using the analysis results of DSC/TGA, XRD and CSI. During the calcination in a range of 500 – 800 oC lasting for 1 – 5 hours, the characterisation of calcinated kaolin was also monitored for mass loss, BET surface, PSD, density as well as the presence of the residual water. It is found to have a well correlation between residual water and BET surface.
The pozzolanic activity of metakaolin was tested by various methods regarding to the saturated lime method, mCh and TGA-CaO method. The results of the study showed which method is the most suitable one to characterise the real activity of metakaolin and can reach the greatest agreement with concrete performance. Furthermore, the pozzolanic activity results tested using methods were also analysed and compared to each other with respect to the BET surface.
The properties of Vietnam metakaolin was established using investigations on water demand, setting time, spread-flowability, and strength. It is concluded that depending on the intended use of composite cement and weather conditions of cure, each Vietnamese metakaolin can be used appropriately to produce (1) a composite cement with a low water demand (2) a high strength of composite cement (3) a composite cement that aims to reduce CO2 emissions and to improve economics of cement products (4) a high performance mortar.
The durability of metakaolin mortar was tested to find the needed metakaolin content against ASR, sulfat and sulfuric acid attacks successfully.