Modeling, characterization and microalgal cultivation in an airlift panel photobioreactors.

Microalgae cultures are attracting great attentions in many industrial applications. However, one of the technical challenges is to cut down the capital and operational costs of microalgae production systems, with special difficulty in reactor design and scale-up. The thesis work open with an overview on the microalgae cultures as a possible answer to solve some of the upcoming planet issues and their applications in several fields. After the work offers a general outline on the state of the art of microalgae culture systems, taking a special look to the enclosed photobioreactors (PBRs). The overall objective of this study is to advance the knowledge of PBRs design and lead to innovative large scale processes of microalgae cultivation. An airlift flat panel photobioreactor was designed, modeled and experimentally characterized. The gas holdup, liquid flow velocity and oxygen mass transfer of the reactor were experimentally determined and mathematically modeled, and the performance of the reactor was tested by cultivation of microalgae. The model predicted data correlated well with experimental data, and the high concentration of suspension cell culture could be achieved with controlled conditions. The reactor was inoculated with the algal strain Scenedesmus obliquus sp. first and with Chlorella sp. later and sparged with air. The reactor was operated in batch mode and daily monitored for pH, temperature, and biomass concentration and activity. The productivity of the novel device was determined, suggesting the proposed design can be effectively and economically used in carbon dioxide mitigation technologies and in the production of algal biomass for biofuel and other bioproducts. Those research results favored the possibility of scaling the reactor up into industrial scales based on the models employed, and the potential advantages and disadvantages were discussed for this novel industrial design.

Dynamic characterisation of four nine-story large-panel R.C. buildings in Bishkek (Kyrgyzstan): A comparison between experimental ambient vibration analysis and numerical finite element modeling

With the outlook of improving seismic vulnerability assessment for the city of Bishkek (Kyrgyzstan), the global dynamic behaviour of four nine-storey r.c. large-panel buildings in elastic regime is studied. The four buildings were built during the Soviet era within a serial production system. Since they all belong to the same series, they have very similar geometries both in plan and in height. Firstly, ambient vibration measurements are performed in the four buildings. The data analysis composed of discrete Fourier transform, modal analysis (frequency domain decomposition) and deconvolution interferometry, yields the modal characteristics and an estimate of the linear impulse response function for the structures of the four buildings. Then, finite element models are set up for all four buildings and the results of the numerical modal analysis are compared with the experimental ones. The numerical models are finally calibrated considering the first three global modes and their results match the experimental ones with an error of less then 20%.

Metodi strumentali per l'analisi della frazione volatile in oli di oliva vergini come supporto al panel test

L’olio di oliva è tra i prodotti alimentari principali della dieta mediterranea e possiede delle caratteristiche salutistiche, compositive e sensoriali peculiari. La qualità e la genuinità dell’olio di oliva vergine sono valutate sia mediante determinazioni analitiche chimiche e strumentali, sia attraverso l’analisi sensoriale. Quest’ultima, realizzata con il metodo del panel test, è tra i metodi ufficiali per la classificazione degli oli di oliva vergini nelle tre categorie commerciali extra vergine, vergine e lampante. Tuttavia, l’analisi sensoriale presenta dei limiti legati, in particolare, al numero elevato di campioni di olio da analizzare rispetto alle capacità di lavoro dei panel. Negli ultimi anni è aumentata, così, la necessità di sviluppare e validare metodi analitici strumentali che, pre-classificando gli oli in esame, siano di supporto al panel test e possano ridurre il numero di campioni da sottoporre ad analisi sensoriale. In questo elaborato di tesi sono state prese in considerazione due diverse tecniche analitiche, la gas cromatografica accoppiata alla spettrometria a mobilità ionica (HS-GC-IMS) e la flash gas cromatografia (FGC E-nose), entrambe impiegate per la valutazione della frazione volatile dell’olio di oliva, responsabile degli attributi olfattivi del prodotto. Utilizzando i risultati ottenuti applicando queste due tecniche, mediante analisi multivariata, è stato possibile stimare la categoria merceologica di ogni campione appartenente ad un set di 52 oli di oliva vergini, classificandoli con un determinato livello di probabilità. Entrambe le metodiche analitiche sono già state utilizzate e valutate in precedenti studi; con la sperimentazione effettuata nell’ambito di questa tesi è stato possibile confermare l’efficacia dei modelli di stima che possono essere impiegati con finalità di screening in supporto al panel test, nell’ottica di renderli sempre più robusti ed affidabili per la classificazione degli oli di oliva vergini.