Substructuring approache in state space models for dynamic system parameters identification

In the recent decade, the request for structural health monitoring expertise increased exponentially in the United States. The aging issues that most of the transportation structures are experiencing can put in serious jeopardy the economic system of a region as well as of a country. At the same time, the monitoring of structures is a central topic of discussion in Europe, where the preservation of historical buildings has been addressed over the last four centuries. More recently, various concerns arose about security performance of civil structures after tragic events such the 9/11 or the 2011 Japan earthquake: engineers looks for a design able to resist exceptional loadings due to earthquakes, hurricanes and terrorist attacks. After events of such a kind, the assessment of the remaining life of the structure is at least as important as the initial performance design. Consequently, it appears very clear that the introduction of reliable and accessible damage assessment techniques is crucial for the localization of issues and for a correct and immediate rehabilitation. The System Identification is a branch of the more general Control Theory. In Civil Engineering, this field addresses the techniques needed to find mechanical characteristics as the stiffness or the mass starting from the signals captured by sensors. The objective of the Dynamic Structural Identification (DSI) is to define, starting from experimental measurements, the modal fundamental parameters of a generic structure in order to characterize, via a mathematical model, the dynamic behavior. The knowledge of these parameters is helpful in the Model Updating procedure, that permits to define corrected theoretical models through experimental validation. The main aim of this technique is to minimize the differences between the theoretical model results and in situ measurements of dynamic data. Therefore, the new model becomes a very effective control practice when it comes to rehabilitation of structures or damage assessment. The instrumentation of a whole structure is an unfeasible procedure sometimes because of the high cost involved or, sometimes, because it’s not possible to physically reach each point of the structure. Therefore, numerous scholars have been trying to address this problem. In general two are the main involved methods. Since the limited number of sensors, in a first case, it’s possible to gather time histories only for some locations, then to move the instruments to another location and replay the procedure. Otherwise, if the number of sensors is enough and the structure does not present a complicate geometry, it’s usually sufficient to detect only the principal first modes. This two problems are well presented in the works of Balsamo [1] for the application to a simple system and Jun [2] for the analysis of system with a limited number of sensors. Once the system identification has been carried, it is possible to access the actual system characteristics. A frequent practice is to create an updated FEM model and assess whether the structure fulfills or not the requested functions. Once again the objective of this work is to present a general methodology to analyze big structure using a limited number of instrumentation and at the same time, obtaining the most information about an identified structure without recalling methodologies of difficult interpretation. A general framework of the state space identification procedure via OKID/ERA algorithm is developed and implemented in Matlab. Then, some simple examples are proposed to highlight the principal characteristics and advantage of this methodology. A new algebraic manipulation for a prolific use of substructuring results is developed and implemented.

Stationary states in random walks on networks

In this thesis we dealt with the problem of describing a transportation network in which the objects in movement were subject to both finite transportation capacity and finite accomodation capacity. The movements across such a system are realistically of a simultaneous nature which poses some challenges when formulating a mathematical description. We tried to derive such a general modellization from one posed on a simplified problem based on asyncronicity in particle transitions. We did so considering one-step processes based on the assumption that the system could be describable through discrete time Markov processes with finite state space. After describing the pre-established dynamics in terms of master equations we determined stationary states for the considered processes. Numerical simulations then led to the conclusion that a general system naturally evolves toward a congestion state when its particle transition simultaneously and we consider one single constraint in the form of network node capacity. Moreover the congested nodes of a system tend to be located in adjacent spots in the network, thus forming local clusters of congested nodes.

Programmazione ad Agenti e Pianificazione: AgentSpeak(PL) come caso di studio

In questa tesi si discutono inizialmente i concetti chiave di agente e sistema multi-agente e si descrivono in ogni dettaglio il linguaggio di programmazione AgentSpeak(L) e la piattaforma Jason, fornendo le basi per poter programmare con il paradigma AOP. Lo scopo centrale di questa tesi è quello di estendere il modello di pianificazione dell’interprete di AgentSpeak(L), considerato come caso specifico, con un approccio che può essere integrato in qualsiasi linguaggio di programmazione ad agenti. Si espone un’evoluzione di AgentSpeak(L) in AgentSpeak(PL), ossia la creazione ed esecuzione di piani automatici in caso di fallimento attraverso l'uso di un algoritmo di planning state-space. L'approccio integrativo modifica il Ciclo di Reasoning di Jason proponendo in fase di pianificazione automatica un riuso di piani già esistenti, atto a favorire la riduzione di tempi e costi nel long-term in un sistema multi-agente. Nel primo capitolo si discute della nozione di agente e delle sue caratteristiche principali mentre nel secondo capitolo come avviene la vera e propria programmazione con AgentSpeak(L). Avendo approfondito questi argomenti base, il terzo capitolo è incentrato sull’interprete Jason e il quarto su una migliore estensione dell'interprete, in grado di superare i limiti migliorando le performance nel tempo. Si delineano infine alcune considerazioni e ringraziamenti nel quinto e ultimo capitolo. Viene proposta con scrittura di carattere divulgativo e non ambiguo.