Probabilistic design of coastal structures

Malliouri, Dimitra I.; Μαλλιούρη, Δήμητρα Ι.

dc.contributor.author	Malliouri, Dimitra I.	en
dc.contributor.author	Μαλλιούρη, Δήμητρα Ι.	el
dc.date.accessioned	2020-12-01T12:45:58Z
dc.date.available	2020-12-01T12:45:58Z
dc.date.issued	2020-12-01
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/52134
dc.identifier.uri	http://dx.doi.org/10.26240/heal.ntua.19832
dc.rights	Default License
dc.subject	Short-crested waves	en
dc.subject	Short-term wave statistics	en
dc.subject	Long-term wave statistics	en
dc.subject	Failure probability	en
dc.subject	Rubble mound breakwaters	en
dc.title	Probabilistic design of coastal structures	en
dc.title.alternative	Πιθανοτικός σχεδιασμός παράκτιων έργων	el
dc.contributor.department	ΕΡΓΑΣΤΗΡΙΟ ΛΙΜΕΝΙΚΩΝ ΕΡΓΩΝ	el
heal.type	doctoralThesis
heal.generalDescription	I would also like to acknowledge DHI for freely providing me with the software license of MIKE 21 for educational purposes as a part of my thesis, Hellenic Centre for Marine Research (POSEIDON system) and Puertos del Estado for kindly providing me with wave and sea level measurements.	en
heal.classification	Ocean Engineering	en
heal.classification	Coastal Engineering	en
heal.language	en
heal.access	free
heal.recordProvider	ntua	el
heal.publicationDate	2020-10-09
heal.abstract	Nowadays, more and more researchers and engineers have realized that coastal structures should be designed to meet predefined safety and performance levels, i.e. the reliability level. This can be accomplished by implementing a thorough methodology able to assess accurately the reliability level of a coastal structure, i.e. the probability of failure during its design operating lifetime. The latter should be equal or lower than a predefined allowable failure probability that depends on the consequence class of the structure’s failure. However, due to the lack of long-term environmental data (i.e. measurements, observations, etc.) at the coastal structures’ location (commonly in intermediate waters), there is a difficulty in estimating the long-term probabilistic representation of environmental parameters at this location, which is vital for the design of these structures. Besides, since more than one parameter play a significant role in coastal structure’s stability, the necessity to develop a multivariate methodology, able to assess accurately a coastal structure’s failure probability within its design lifetime via the use of the environmental parameters’ joint probability distribution, is derived. Therefore, the research in the present thesis has been motivated by the abovementioned needs of reliability analysis of coastal structures. Particularly, an overall probabilistic methodology for reliability assessment of coastal structures under wave action is described, which starts from the step of wave data collection referring usually to deep waters, and ends to the estimation of failure probability of coastal structures during their design Lifetime. In an intermediate step, a statistical linear wave propagation model that integrates short- with long-term wave statistics from deep to intermediate waters has been developed and applied. This is a wave model that uses the long-term wave statistics in deep waters as input data, and via the use of the short-term wave statistics for each sea state in deep waters, estimates the long-term wave statistics in shallower waters. Specifically, by using i) data/measurements of significant wave height Hs, mean wave period Tm, and mean wave direction θm e.g. obtained from an oceanographic buoy in deep waters, ii) the dimensionless short-term images by Memos and Tzanis in deep waters, iii) a theoretical expression for wave directionality adjusted in a statistical individual wave analysis, and iv) a modification of Battjes approach, the short-term joint distribution of individual wave height H, period T, and direction θ for every sea state or storm event could be produced in deep waters. Then, the short- and the long-term joint distribution of H, T, θ could be estimated in intermediate waters, as well as the long-term joint probability density function (pdf) of Hs, Tm, θm, by considering linear wave transformations of each individual wave, as waves propagate from the open sea towards shallower waters. The capability of the statistical linear wave propagation model to produce properly the short-term wave statistics in deep and intermediate waters has been investigated via comparisons of its results with measurements in deep waters and the results of a commercial, and well-known for its accuracy, Boussinesq wave propagation model from deep to intermediate waters, respectively. As for the deep water short-term wave statistics considered by the model, it was shown that the joint pdf of individual wave period T and wave height H of a real sea state could be well represented by using the dimensionless probabilistic images by Memos and Tzanis. The latter refer to nonlinear deep water sea waves. Referring to intermediate waters’ short-term wave statistics considered by the model, comparisons between the linear wave propagation model and the nonlinear Boussinesq-type model showed good agreement in most of the intermediate water depths examined for both normal and oblique incidence. At the shallower intermediate water depth tested, the results of the two models differed more significantly than in deeper intermediate water depths. Therefore, as it was expected and has been already mentioned, the linear model adopted could cover the deeper and medium zone of intermediate waters and thus could be used for many engineering design purposes. Also, it is noteworthy that a thorough probabilistic methodology is presented, aiming at estimating the reliability of coastal structures, such as rubble mound breakwaters during their lifetime, based on the probabilistic representation of load environmental and resistance variables. One of the innovative points and main objectives of this study is the estimation of the failure probability of a coastal structure based on the long-term wave climate at the structure’s location, usually met in intermediate waters, using wave observations or measurements in deeper waters. This task is accomplished by applying the abovementioned wave propagation statistical model in order that the joint probability density function of all random load variables be estimated at the structure’s location. Moreover, two thorough probabilistic methodologies, i.e. the event-based extreme value analysis and the reliability analysis applied on all sea conditions, are presented, aiming at estimating the reliability of coastal structures, such as rubble mound breakwaters during their lifetime, based on the probabilistic representation of load environmental and resistance variables. Also, their pros and cons with respect to their outputs and constraints are discussed. The main differences between the two approaches are focused on the fact that the two methods estimate different types of failure probabilities. The first method estimates the failure probability in the sample of exreme events, and the second one the failure probability in the total sample of data. The latter can be translated as the percentage of the structure’s lifetime that the structure will be in a failure situation, which can be efficiently incorporated into a risk analysis with consideration of social and economic costs. The fully probabilistic reliability analysis, applied on all sea conditions, is recommended for reliability and design purposes of coastal structures, when the period of measurements or of data used is close to the lifetime of the structure. In other cases, the extreme event-based method could be used for the design of a coastal structure (e.g. ULS), considering however its cons, and the second method for the operation of the structure (e.g. SLS). In short, the problem of assessing failure probability of coastal structures was presented and attempted to be solved by giving application examples, flowcharts, and mathematical equations that describe the procedure, focusing on the case of rubble mound breakwaters.	en
heal.advisorName	Tsoukala, Vasiliki
heal.committeeMemberName	Tsoukala, Vasiliki	en
heal.committeeMemberName	Memos, Constantine	en
heal.committeeMemberName	Soukissian, Takvor	en
heal.committeeMemberName	Karambas, Theophanis	en
heal.committeeMemberName	Galanis, Georgios	en
heal.committeeMemberName	Katsardi, Vasiliki	en
heal.committeeMemberName	Sørensen, John Dalsgaard	en
heal.academicPublisher	Σχολή Πολιτικών Μηχανικών	el
heal.academicPublisherID	ntua
heal.numberOfPages	334 p.	en
heal.fullTextAvailability	false