1,721,013 research outputs found
Applicazione di nuove tecnologie per il monitoraggio di ambienti marino-costieri
Full text linkIn my PhD project, two low cost detection systems have been tested: a marine one to acquire high resolution data in the bathymetric range between 0 and -10m and, a terrestrial to acquire high resolution data on the beaches. High resolution Side Scan Sonar data acquisition strategies have been developed in shallow water (-5 and -2.5m), capable of communicate integrating data acquired with non-oceanographic systems (Georadar “G.P.R.”). These integrations allowed us to study the emerged shallow and deep submerged areas, and to create very detailed cartographies of the seabed of the Alghero bay, of the Bay of Porto Conte (De Luca et al., 2018) and of the some areas of the Asinara island. In addition to the Side Scan Sonar and the Remote Operated Vehicle (ROV), the classic satellite detection systems have been used as well as high resolution images acquired with drones (UAVs). This latest technology, simple to use and very cheap, allows the creation of aerial photographs of marine areas close to the coast, where the oceanographic instruments, at the moment are unable to acquire data (depth less than 2.5 m). The information acquired made possible to evaluate the state of thePosidonia oceanicaseagrass, the coastal dynamics present in the Alghero harbour and to characterize two temporary storage sites used for the accumulation of the banquettes ofPosidonia oceanica. The coast of Alghero has a unique peculiarity in Sardinian realm, that is; the accumulations of Posidonia leaves. These per year are about 3000 m3, mostly concentrated in the beaches of San Giovanni, Maria Pia and Punta Negra. The large accumulations of leaves are a problem for the recreational use of the beach. The formed banquettes can frequently reach one meter in height, occasionally exceeding two meters. CurrentlyPosidonia oceanica(both leaves and banquettes) is moved by tractors and stored in temporary accumulation sites located near the beaches. For this reason, an action plan was prepared for the dismantling of the temporary storage sites of San Giovanni and Villa Segni. This was aimed to recover as much sand as possible the beach. The Ground Penetrating Radar (G.P.R.) was used to obtain information on the subsurface deposits in the San Giovanni are, to better correct management of thePosidoniaaccumulated leaves.The area has a surface layer composed of 10 to 50 cm ofPosidoniaresidues mixed with sand, overlying about 3 meters of sand. Between the layers, some wastes with an expiry date or production date were found, useful for stratigraphic dating. These analyses allowed us to establish that the temporary storage areas are not a dump sites and that an accurate managing of them could reclaim sand to the beaches
Runway surface friction characteristics assessment for Lamezia Terme airfield pavement management system
No full textThe main objective of this paper was to explore the relationship between runway friction and traffic data useful for the APMS of Lamezia Terme Airport (IATA: SUF, ICAO: LICA), located near Lamezia Terme in the Calabria region in southern Italy. Its IATA airport code SUF originates from Sant'Eufemia, the part of Lamezia Terme which the airport is closest to. The infrastructure is the most important Calabrian airport and is under continuous development. In the last few years, the number of passengers using the airport has risen enormously (more than 1.9 ml passengers in 2010), as have traffic and handling activities.
The performance models proposed here are useful in predicting the decay of a runway's pavement surface characteristics. The results were obtained from a large number of experimental evaluations over the last nine years. The main model obtained in the study makes it possible to predict the decay curve as a function of aircraft structure, load and passages
ANALISI DEGLI INCIDENTI STRADALI SULLE STRADE APPARTENENTI ALLA RETE SECONDARIA: IL CASO DI STUDIO SULLA VIABILITÀ MINORE DELLA RETE DELLA PROVINCIA DI SALERNO
No full textNel contributo vengono illustrati i risultati
di uno studio sull'incidentalità condotto sulla rete
secondaria della provincia di Salerno nel triennio
2003-2005. In particolare sono stati analizzati i
tronchi della rete caratterizzati da un TGM inferiore
a 1000 veicoli/giorno. I dati di base adoperati nello
studio, oltre che gli incidenti occorsi nei tronchi
analizzati, riguardano la geometria, il traffico e le
condizioni ambientali. In buona parte questi dati
sono stati forniti dalla Provincia di Salerno; per le
parti, ove sono risultate necessarie integrazioni alle
informazioni disponibili negli archivi della Provincia,
sono stati effettuati opportuni e specifici rilievi.
Dall'analisi dei dati, effettuata attraverso una
regressione multivariata, è stato ricavato un modello
che consente di stimare l'incidentalità in funzione
del traffico (TGM). Inoltre per rendere più semplice
l'applicazione del modello sono stati costruiti una
serie di abachi che consentono, in modo semplice e
veloce, di stimare l'incidentalità per un prefissato
valore del TGM, per i diversi livelli di tortuosità, di
pendenza e di larghezza della carreggiata
The impact of vehicle movement on exploitation parameters of roads and runways: a short review of the special issue
No full text
Using artificial neural network and multivariate analysis techniques to evaluate road operating conditions
No full textRegional paved roads are low volume roads with a prevalence of heavy traffic. In the world, these roads concern about 80% of the total road network; however, the traffic that affects these roads is about 20%. Since regional roads are characterized by weak demand, budget for their management/maintenance is very low. This produces considerable difficulties in the choice of strategies for maintenance planning and scheduling. For this reason, the recurring topics of research in this field deal with typical roads issues and aim to develop low cost tools and methods. The study proposes a decision support system to evaluate regional paved roads operating condition in relation to the hydrogeological situation. In particular, the system allows to evaluate in a quick and easy manner, the operating
conditions of the road, through low-cost tools (i.e. using low economic resources). This is very useful in the case of LVRs because administrations for these roads have a limited budget. The procedure is developed on a regional paved roads network based on more than 80 roads located in Southern Italy. Data is collected by direct surveys in the field and is integrated with cartography and information available in road agency records. From data analysis, obtained using two different techniques, an easy and quick use procedure is made. In particular, Model 1 is built through multivariate analysis and Model 2 using the artificial neural network (ANN) technique. The results show the validity of the two models in Regional paved roads operating conditions estimation in relation to hydrogeological situations of sites. Both models show good reliability. In particular, the first model (Model 1) is characterized by a high level of significance (p < 0.01) and by a coefficient of determination equal to 0.82. Comparative tests between the second model (Model 2) on which standard tests cannot be performed for obvious reasons, and the first model (Model 1). The results show that the ANN model (model 2), characterized by lower residual, simulates more accurately than the second (Model 1)
Aircraft safety analysis using clustering algorithms
No full textIn recent years, there have been many cost-benefit studies on aviation safety, which deal mainly with economic issues, omitting some strictly technical aspects. This study compares aircraft accidents in relation to the characteristics of the aircraft, environmental conditions, route, and traffic type. The study was
conducted using a database of over 1500 aircraft accidents worldwide, occurring between 1985 and 2010. The data were processed and then aggregated into groups, using cluster analysis based on an algorithm of partition binary ‘Hard c
means.’ For each cluster, the ‘cluster representative’ accident was identified as the average of all the different characteristics of the accident. Moreover, a ‘hazard index’ was defined for each cluster (according to annual movements); using this index, it was possible to establish the dangerousness of each ‘cluster’ in terms of aviation accidents. Obtained results allowed the construction of an easy-to-use predictive model for accidents using multivariate analysis
Utilizzazione di un modello di archivio stradale per lo studio dell’incidentalità mediante Cluster Analysis
No full textQuaderno di.pi.ter n. 86 Università della Calabria Dipartimento di Pianificazione Territoriale, Cosenz
Utilizzazione di un modello di archivio stradale per lo studio dell’incidentalità mediante Cluster Analysis
No full textQuaderno di.pi.ter n. 86 Università della Calabria Dipartimento di Pianificazione Territoriale, Cosenz
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