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Your search keyword '"Ascione, Fabrizio"' showing total 6 results
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6 results on '"Ascione, Fabrizio"'

2. List of contributors

Author

Abuseif, Majed, primary, Afroditi, Synnefa, additional, Aghamohammadi, Nasrin, additional, Anna, Mavrogianni, additional, Ascione, Fabrizio, additional, Bartesaghi Koc, Carlos, additional, Bertoldi, Paolo, additional, Bianco, Nicola, additional, Boemi, Sofia Natalia, additional, Fabiani, Claudia, additional, Ferguson, Lauren, additional, Ghaffarianhoseini, Ali, additional, Ghaffarianhoseini, Amirhosein, additional, González-Trevizo, M.E., additional, Jamei, Elmira, additional, Manniti, Giacomo, additional, Martilli, Alberto, additional, Martínez-Torres, K.E., additional, Mastellone, Margherita, additional, Pigliautile, Ilaria, additional, Pisello, Anna Laura, additional, Ramakreshnan, Logaraj, additional, Rincón-Martínez, J.C., additional, Santamouris, Mattheos, additional, Takebayashi, Hideki, additional, Tariello, Francesco, additional, Treville, Aldo, additional, Ulpiani, Giulia, additional, Vanoli, Giuseppe Peter, additional, Vasilakopoulou, Konstantina, additional, Vetters, Nadja, additional, and Yenneti, Komali, additional

Published
2024
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4. List of Contributors

Author

Aguilar-Castro, Karla Maria, primary, Alev, Üllar, additional, Aparicio, Xabier, additional, Arumägi, Endrik, additional, Ascione, Fabrizio, additional, Babin, Mihajlo, additional, Bianco, Nicola, additional, Burman, Esfand, additional, Calzada, Jaume Roset, additional, Corgnati, Stefano Paolo, additional, Cotana, Franco, additional, D’Oca, Simona, additional, De Masi, Rosa Francesca, additional, De Stasio, Claudio, additional, del Portillo, Luis Alfonso, additional, Erić, Miloš, additional, Erkoreka, Aitor, additional, Fabrizio, Enrico, additional, Ferrara, Maria, additional, Fokaides, Paris A., additional, Hernández-Pérez, Iván, additional, Holopainen, Riikka, additional, Jelle, Bjørn Petter, additional, Johnsson, Filip, additional, Kalamees, Targo, additional, Kalnæs, Simen Edsjø, additional, Koch, David, additional, Kuusk, Kalle, additional, Kylili, Angeliki, additional, Macías-Melo, Edgar Vicente, additional, Martin, Koldobika, additional, Mata, Érika, additional, Matic, Dubravka, additional, Mauro, Gerardo Maria, additional, Monetti, Valentina, additional, Mumovic, Dejan, additional, Pacheco-Torgal, Fernando, additional, Paiho, Satu, additional, Paya-Marin, Miguel Ángel, additional, Pisello, Anna Laura, additional, Rosso, Federica, additional, Sahito, Anwer Ali, additional, Scognamiglio, Alessandra, additional, Shaikh, Faheemullah, additional, Shaikh, Pervez Hameed, additional, Stocker, Emanuel, additional, Terés-Zubiaga, Jon, additional, Todorovic, Marija S., additional, Umrani, Zulfiqar, additional, Uqaili, Muhammad Aslam, additional, Vanoli, Giuseppe Peter, additional, and Xamán, Jesús, additional

Published
2017
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5. Thermal comfort prediction in a building category: Artificial neural network generation from calibrated models for a social housing stock in southern Europe

Author

Universidad de Sevilla. Departamento de Construcciones Arquitectónicas I (ETSA), Universidad de Sevilla. TEP130: Arquitectura, Patrimonio y Sostenibilidad: Acústica, Iluminación, Óptica y Energía, Universidad de Sevilla, Escandón Ramírez, Rocío, Ascione, Fabrizio, Bianco, Nicola, Mauro, Gerardo Maria, Suárez, Rafael, Sendra, Juan J., Universidad de Sevilla. Departamento de Construcciones Arquitectónicas I (ETSA), Universidad de Sevilla. TEP130: Arquitectura, Patrimonio y Sostenibilidad: Acústica, Iluminación, Óptica y Energía, Universidad de Sevilla, Escandón Ramírez, Rocío, Ascione, Fabrizio, Bianco, Nicola, Mauro, Gerardo Maria, Suárez, Rafael, and Sendra, Juan J.

Abstract

A significant part of the housing stock in southern Europe is obsolete and in need of extensive retrofitting to improve its energy performance and thermal comfort. However, before adequate retrofit measures can be proposed for this housing stock, the characterization of current building performance is fundamental. Although the simulation tools frequently used and widely accepted by the scientific community ensure accurate results, these require high computational times. The main aim of this paper is the development of a surrogate model to speed up the thermal comfort prediction for any member of a building category, ensuring high reliability by testing the entire simulation process with real data measured in-situ. To this end, an artificial neural network (ANN) is generated under MATLAB® environment using the data obtained from EnergyPlus simulations for linear-type social housing multi-family buildings in southern Spain, which were constructed in the post-war period. The developed ANN provides a regression coefficient between simulation targets and ANN outputs of 0.96, with a relative error between monitored and simulated data below 9%. A further result is that the building category characterization shows a general lack of suitable indoor thermal comfort conditions, thereby showing the great need for effective retrofit strategies.

Published
2019

6. A coupled numerical approach on museum air conditioning: Energy and fluid-dynamic analysis

Author

Alfonso Capozzoli, Laura Bellia, Fabrizio Ascione, Ascione, Fabrizio, Bellia, Laura, and A., Capozzoli

Subjects
Desiccant, Diffusion (acoustics), Engineering, Management, Monitoring, Policy and Law, Computational fluid dynamics, law.invention, HVAC system, law, Energy saving, HVAC, Relative humidity, Simulation, business.industry, HVAC systems, Museums, CFD, Mechanical Engineering, Thermal comfort, Air diffusers, Building and Construction, General Energy, Air conditioning, Ventilation (architecture), business, BEPS, Marine engineering
Abstract

In the museum environment, the temporal stability and the spatial uniformity of the indoor microclimatic parameters are necessary primarily for the correct artwork conservation and then for the occupant thermal comfort. Therefore, a HVAC system is usually necessary. This paper above all emphasizes the integration of Building Energy Performance Simulation (BEPS) and Computational Fluid Dynamics (CFD) codes. This coupled numerical approach can provide accurate information about both the HVAC system energy request and the indoor microclimatic control (temporal and spatial distribution of the parameters). Then, a case study concerning a typical museum exhibition room is examined. The annual energy request for three types of all-air system, as well as the temporal variation of indoor temperature and relative humidity, is evaluated by means of a BEPS code. Energy savings can be obtained using a system with desiccant wheel (11%) or enthalpy wheel (9%), compared to the base system. As regards indoor relative humidity control, this is more critical for summer conditions, and the best performance is obtained by the system with desiccant wheel. Then, the spatial microclimatic control is analyzed by means of a CFD analysis, for various thermal load conditions and different air diffusion xequipments. The best performances are obtained by using the swirling (vortex) diffusers; also the perimetrical stripes of slot diffusers show satisfactory performances. Finally, in order to evaluate the ability of air diffusion equipments to assure good ventilation effectiveness, an analysis of the mean age of air is carried out too.

Published
2013

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