Numerical modeling on the short-term response of fiber-reinforced concrete round panels

Fiber-reinforced concrete is a composite material consisting of discrete, discontinuous, and uniformly distributed fibers in plain concrete primarily used to enhance the tensile properties of the concrete. FRC performance depends upon the fiber, interface, and matrix properties. The use of fiber-reinforced concrete has been increasing substantially in the past few years in different fields of the construction industry such as ground-level application in sidewalks and building floors, tunnel lining, aircraft parking, runways, slope stabilization, etc. Many experiments have been performed to observe the short-term and long-term mechanical behavior of fiber-reinforced concrete in the last decade and numerous numerical models have been formulated to accurately capture the response of fiber-reinforced concrete. The main purpose of this dissertation is to numerically calibrate the short-term response of the concrete and fiber parameters in mesoscale for the three-point bending test and cube compression test in the MARS framework which is based on the lattice discrete particle model (LDPM) and later validate the same parameters for the round panels. LDPM is the most validated theory in mesoscale theories for concrete. Different seeds representing the different orientations of concrete and fiber particles are simulated to produce the mean numerical response. The result of numerical simulation shows that the lattice discrete particle model for fiber-reinforced concrete can capture results of experimental tests on the behavior of fiber-reinforced concrete to a great extent.

Implementation of a non ground meta interpreter for defeasible logic

Human reasoning is a fascinating and complex cognitive process that can be applied in different research areas such as philosophy, psychology, laws and financial. Unfortunately, developing supporting software (to those different areas) able to cope such as complex reasoning it’s difficult and requires a suitable logic abstract formalism. In this thesis we aim to develop a program, that has the job to evaluate a theory (a set of rules) w.r.t. a Goal, and provide some results such as “The Goal is derivable from the KB5 (of the theory)”. In order to achieve this goal we need to analyse different logics and choose the one that best meets our needs. In logic, usually, we try to determine if a given conclusion is logically implied by a set of assumptions T (theory). However, when we deal with programming logic we need an efficient algorithm in order to find such implications. In this work we use a logic rather similar to human logic. Indeed, human reasoning requires an extension of the first order logic able to reach a conclusion depending on not definitely true6 premises belonging to a incomplete set of knowledge. Thus, we implemented a defeasible logic7 framework able to manipulate defeasible rules. Defeasible logic is a non-monotonic logic designed for efficient defeasible reasoning by Nute (see Chapter 2). Those kind of applications are useful in laws area especially if they offer an implementation of an argumentation framework that provides a formal modelling of game. Roughly speaking, let the theory is the set of laws, a keyclaim is the conclusion that one of the party wants to prove (and the other one wants to defeat) and adding dynamic assertion of rules, namely, facts putted forward by the parties, then, we can play an argumentative challenge between two players and decide if the conclusion is provable or not depending on the different strategies performed by the players. Implementing a game model requires one more meta-interpreter able to evaluate the defeasible logic framework; indeed, according to Göedel theorem (see on page 127), we cannot evaluate the meaning of a language using the tools provided by the language itself, but we need a meta-language able to manipulate the object language8. Thus, rather than a simple meta-interpreter, we propose a Meta-level containing different Meta-evaluators. The former has been explained above, the second one is needed to perform the game model, and the last one will be used to change game execution and tree derivation strategies.

Sea level trends in the Mediterranean from tide gauges and satellite altimetry

Sea level variation is one of the parameters directly related to climate change. Monitoring sea level rise is an important scientific issue since many populated areas of the world and megacities are located in low-lying regions. At present, sea level is measured by means of two techniques: the tide gauges and the satellite radar altimetry. Tide gauges measure sea-level relatively to a ground benchmark, hence, their measurements are directly affected by vertical ground motions. Satellite radar altimetry measures sea-level relative to a geocentric reference and are not affected by vertical land motions. In this study, the linear relative sea level trends of 35 tide gauge stations distributed across the Mediterranean Sea have been computed over the period 1993-2014. In order to extract the real sea-level variation, the vertical land motion has been estimated using the observations of available GPS stations and removed from the tide gauges records. These GPS-corrected trends have then been compared with satellite altimetry measurements over the same time interval (AVISO data set). A further comparison has been performed, over the period 1993-2013, using the CCI satellite altimetry data set which has been generated using an updated modeling. The absolute sea level trends obtained from satellite altimetry and GPS-corrected tide gauge data are mostly consistent, meaning that GPS data have provided reliable corrections for most of the sites. The trend values range between +2.5 and +4 mm/yr almost everywhere in the Mediterranean area, the largest trends were found in the Northern Adriatic Sea and in the Aegean. These results are in agreement with estimates of the global mean sea level rise over the last two decades. Where GPS data were not available, information on the vertical land motion deduced from the differences between absolute and relative trends are in agreement with the results of other studies.

New assessments of global sea level rise from tide gauges

Estimates of global sea-level change rates based on observations from Tide Gauges (TGs) show a long-term global mean sea-level rise (GMSLR) of 1÷2 mm/yr for the 20th century. The considerable scatter in these estimates is mainly attributable to the uneven distribution of the TG sites and to several physical phenomena that cause local sea level to deviate from the global mean, or to affect the TG record through land subsidence or uplift. The main cause of vertical ground motion on a regional space scale is the response of the Earth to past ice loads, called Glacial Isostatic Adjustment (GIA), which is often modelled and corrected for. In this work, a simple average approach was used to revisit two past estimates based on small sets of long, high-quality TG records in view of the longer record available, employing a newer GIA model (ICE-6G) from Peltier et al. [2015]. The value of GMSLR obtained from both sets is (1.5±0.4) mm/yr. In addition, a much larger set of TGs was used to estimate the contemporary (post 1993) GMSLR using satellite estimates from Cazenave et al. [2018] as a benchmark, in an attempt to understand how a simple average approach could perform for larger sets. The resulting estimate of (3.4÷3.5)±0.2 mm/yr (depending on the GIA correction applied) is comparable to the satellite result of (3.1±0.3) mm/yr.