Energy rating of a water pumping station using multivariate analysis

Among water management policies, the preservation and the saving of energy demand in water supply and treatment systems play key roles. When focusing on energy, the customary metric to determine the performance of water supply systems is linked to the definition of component-based energy indicators. This approach is unfit to account for interactions occurring among system elements or between the system and its environment. On the other hand, the development of information technology has led to the availability of increasing large amount of data, typically gathered from distributed sensor networks in so-called smart grids. In this context, data intensive methodologies address the possibility of using complex network modeling approaches, and advocate the issues related to the interpretation and analysis of large amount of data produced by smart sensor networks. In this perspective, the present work aims to use data intensive techniques in the energy analysis of a water management network. The purpose is to provide new metrics for the energy rating of the system and to be able to provide insights into the dynamics of its operations. The study applies neural network as a tool to predict energy demand, when using flowrate and vibration data as predictor variables

Impact of wind field horizontal resolution on sea waves hindcast around Calabrian coasts

We investigated the impact of wind field enhanced horizontal resolution on sea wind-wave hindcast around the Calabrian coasts, which lie at the southernmost tip of the Italian peninsula. Simulations have been performed using WAM (WAve Model), a third-generation state of the art wave-model. In order to study this topic, we shall discuss two simulations sets. The first set forces WAM by ECMWF (European Centre for Medium-Range Weather Forecasts) surface wind field analysis, used in this paper with a resolution of 0.5◦; whilefor these cond simulation set RAMS (Regional Atmospheric Modelling System) surface wind field forcesWAM. Initial and dynamic boundary conditions for RAMS simulations, which have a 20 km horizontal resolution, are derived from ECMWF analysis. To obtain a reliable statistical data set, integrations have been performed over six months from 1 October 2003 to 31 March 2004. We have evaluated performance comparing the WAM modelled wave heights and directions against data of Wave measuring Buoys (WBs) moored off Cetraro and Crotone. Statistical tests are performed to assess differences between modelled data and measurements and between modelled data sets. Results show better performance for wave height fields when RAMS forces WAM. The best results are obtained for Crotone but differences between simulated and measured wave height distributions are significant at a 99% statistical level. Simulated wave directions are generally good for the model set-up used in this paper and the differences between modelled data sets are minor

Internal combustion engine sensor network analysis using graph modeling

In recent years there has been a rapid development in technologies for smart monitoring applied to many different areas (e.g. building automation, photovoltaic systems, etc.). An intelligent monitoring system employs multiple sensors distributed within a network to extract useful information for decision-making. The management and the analysis of the raw data derived from the sensor network includes a number of specific challenges still unresolved, related to the different communication standards, the heterogeneous structure and the huge volume of data. In this paper we propose to apply a method based on complex network theory, to evaluate the performance of an Internal Combustion Engine. Data are gathered from the OBD sensor subset and from the emission analyzer. The method provides for the graph modeling of the sensor network, where the nodes are represented by the sensors and the edge are evaluated with non-linear statistical correlation functions applied to the time series pairs. The resulting functional graph is then analyzed with the topological metrics of the network, to define characteristic proprieties representing useful indicator for the maintenance and diagnosis

Improvement of Solar and Wind forecasting in southern Italy through a multi-model approach: preliminary results

The improvement of the Solar and Wind short-term forecasting represents a critical goal for the weather prediction community and is of great importance for a better estimation of power production from solar and wind farms. In this work we analyze the performance of two deterministic models operational at ISAC-CNR for the prediction of short-wave irradiance and wind speed, at two experimental sites in southern Italy. A post-processing technique, i.e the multi-model, is adopted to improve the performance of the two mesoscale models. The results show that the multi-model approach produces a significant error reduction with respect to the forecast of each model. The error is reduced up to 20  % of the model errors, depending on the parameter and forecasting time

Implementation of an acoustic stall detection system using near-field diy pressure sensors

In this paper the authors propose the use of an unconventional instrumentation, based on a DIY transducer, to measure the pressure instabilities in a low speed industrial axial fan, with the purpose of rotating stall detection. Rotating stall is an aerodynamic instability with a frequency typically half the rotor frequency, and in slow turbomachines such as industrial fans this frequency has a value even lower than 10 Hz. The authors carried out the pressure measurements using a dynamic transducer and a piezoelectric sensor to provide the measurement base-line. In turbomachinery standard methods, time-resolved pressure measurements use piezoelectric sensors such as microphones in the far field and pressure transducers in the near field. Other classes of sensors, such as electret microphones, May be not suited for pressure measurements, especially in the infrasound region since their cut-off frequency is about 20 Hz. In the present study, the authors compare a low cost and DIY technology to a high precision piezoelectric sensor as alternative technology to stall detection. They implemented and set-up a measurement chain that is the basis of a stall warning system able to identify the rotating stall typical pattern in low speed axial fans. The results have been validated respect to the state of the art of the acoustic control techniques described in literature. The signals acquired using the two technologies are discussed combining spectral analysis and time-domain reconstruction of phase space portraits. The acoustic patterns obtained through the phase space reconstruction shows that the DIY dynamic sensor is a good candidate solution for the rotating stall acoustic analysis

THU0306 ROLE OF 18-FDG PET/CT IN DIAGNOSIS AND FOLLOW UP OF LARGE VESSELS VASCULITIS

Background:18-FDG PET/CT is a functional imaging method which allows to identify inflammation of vessel walls. The use of PET in large vessels vasculitis(LVV) at disease onset and during follow up is still debate either to confirm clinical remission either to drive the therapy choice. American Society of Nuclear Cardiology (ASNC) recently advanced recommendations aimed to standardize the application of PET in LVV(1).Objectives:The aim of our study was to assess the clinical role of PET performed in patients affected by LVV at the diagnosis and during the follow up.Methods:We retrospectively evaluated PET/CT of 49 patients affected by clinically active LVV according to LVV visual grading (LVG, grading 0-3) and measured the standardized uptake value(SUV) of large vessels. 38 (77,6%) patients were affected by Giant Cells Arteritis and 11(22,4%) by Takayasu Arteritis. 32(65.3%) patients repeated the imaging after a mean follow-up of 11.5±5.4 months.All baseline (T0) and follow up (T1) clinical data of disease activity were collected. Patients were treated according to EULAR LVV management recommendations(2). T0 PET/CT study was performed in patients with a clinically active disease defined by suggestive symptoms/signs and/or high inflammatory markers. The mean disease duration before T1 PET/CT examination was 4 months. T0 PET was performed in 25/49 patients(52%) at the diagnosis of LVV, whereas in 24/49(48%) patients with already diagnosed but active LVV disease.Results:Baseline PET was positive in 21 patients(42.9%). According to ASNC recommendations, 19 patients (38.8%) presented a LVG=3, 2(4.0%) a LVG=2, 6(12.2%) LVG=1 and 22 (44.9%) LVG=0. Patients performing PET at disease onset(75%) had higher LVG score than patients performing PET during the disease course (25%),p=0,002. At T0, aortic, carotid, axillary and subclavian SUV did not correlate with inflammatory markers.Follow up PET/CT studies were performed in 32 patients, 13 (40.6%) with a clinically active disease despite therapy, while 19(59.4%) in clinical remission.Follow up PET was still positive in 8 patients (25%) with a LVG=3, 10 (31.2%) patients presented LVG=1 and 14 (43.8%) LVG=0. T1 PET/CT study showed a significant reduction of SUV values in descending aorta, left and right subclavian arteries, and left and right axillary arteries when compared with first PET/CT study. According to LVG, 12 patients with active PET/CT study at T0 (19 pts) presented a reduction of LVG from score 2 and 3 to grade 1 or 0 (64.2%) at second PET/CT study. Only 3 patients presented an increased LVG score at T1, while in the other 17 patients T1 PET confirmed the previous score. No significant difference was found between LVG scores according with clinical characteristics, but among 8 patients presenting an active T1 PET, 4(50%) were in clinical remission.Conclusion:The use of ASNC recommendations for FDG PET/CT in LVV enables to confirm a metabolically active disease in 40% of patients and in 75% of patients at disease onset, suggesting that post-posing the exam could lead to underrate the real extension of disease. Our data, even if limited, suggest that PET/CT could be crucial in management of patients in clinical remission, detecting patients with still metabolically active LVV. Further prospective studies are necessary to evaluate the role of PET/CT in driving therapeutic strategies.References:[1]Slart R et all - Eur J Nucl Med Mol Imaging, 2018[2]Hellmich et all – Ann Rheum Dis 2018Disclosure of Interests:Laura Gigante: None declared, Dario Bruno: None declared, Vanessa Feudo: None declared, Silvia Laura Bosello Speakers bureau: Abbvie, Pfizer, Boehringer, Lucia Leccisotti: None declared, Alessia Musto: None declared, Pier Giacomo Cerasuolo: None declared, Angelo Zoli: None declared, Alessandro Giordano: None declared, Elisa Gremese Speakers bureau: Abbvie, BMS, Celgene, Jannsen, Lilly, MSD, Novartis, Pfizer, Sandoz, UC