Modellazione edilizia e simulazione energetica per le analisi delle prestazioni e la progettazione integrata delle cantine aziendali

Il presente studio si colloca nell’ambito di una ricerca il cui obiettivo è la formulazione di criteri progettuali finalizzati alla ottimizzazione delle prestazioni energetiche delle cantine di aziende vitivinicole con dimensioni produttive medio-piccole. Nello specifico la ricerca si pone l’obiettivo di individuare degli indicatori che possano valutare l’influenza che le principali variabili progettuali hanno sul fabbisogno energetico dell’edificio e sull’andamento delle temperature all’interno dei locali di conservazione ed invecchiamento del vino. Tali indicatori forniscono informazioni sulla prestazione energetica dell’edificio e sull’idoneità dei locali non climatizzati finalizzata alla conservazione del vino Essendo la progettazione una complessa attività multidisciplinare, la ricerca ha previsto l’ideazione di un programma di calcolo in grado di gestire ed elaborare dati provenienti da diversi ambiti (ingegneristici, architettonici, delle produzioni agroindustriali, ecc.), e di restituire risultati sintetici attraverso indicatori allo scopo individuati. Il programma è stato applicato su un caso-studio aziendale rappresentativo del settore produttivo. Sono stati vagliati gli effetti di due modalità di vendemmia e di quattro soluzioni architettoniche differenti. Le soluzioni edilizie derivano dalla combinazione di diversi isolamenti termici e dalla presenza o meno di locali interrati. Per le analisi sul caso-studio ci si è avvalsi di simulazioni energetiche in regime dinamico, supportate e validate da campagne di monitoraggio termico e meteorologico all’interno dell’azienda oggetto di studio. I risultati ottenuti hanno evidenziato come il programma di calcolo concepito nell’ambito di questo studio individui le criticità dell’edificio in termini energetici e di “benessere termico” del vino e consenta una iterativa revisione delle variabili progettuale indagate. Esso quindi risulta essere uno strumento informatizzato di valutazione a supporto della progettazione, finalizzato ad una ottimizzazione del processo progettuale in grado di coniugare, in maniera integrata, gli obiettivi della qualità del prodotto, della efficienza produttiva e della sostenibilità economica ed ambientale.

Miglioramento delle performance termiche e energetiche degli edifici rurali: valutazione del retrofit di locali per la conservazione del vino su casi studio

Il presente studio si colloca all’interno di una ricerca più ampia volta alla definizione di criteri progettuali finalizzati all’ottimizzazione delle prestazioni energetiche delle cantine di aziende vitivinicole, di dimensioni produttive medio - piccole. Nello specifico la ricerca riguarda la riqualificazione di fabbricati rurali esistenti di modeste dimensioni, da convertire a magazzini per la conservazione del vino in bottiglia. Lo studio si pone come obiettivo la definizione di criteri di analisi per la valutazione di interventi di retrofit di tali fabbricati, volto sia al miglioramento delle prestazioni energetiche dell’involucro edilizio, sia alla riduzione del fabbisogno energetico legato al funzionamento di eventuali impianti di controllo termico. La ricerca è stata condotta mediante l’utilizzo del software di simulazione termica Energy Plus, per ottenere i valori simulati di temperatura interna relativi ai diversi scenari migliorativi ipotizzati, e mediante la successiva definizione di indicatori che esplicitino l’influenza delle principali variabili progettuali sull’andamento delle temperature interne dei locali di conservazione e sul fabbisogno energetico del fabbricato necessario a garantire l’intervallo di temperatura di comfort del vino. Tra tutti gli interventi possibili per il miglioramento della prestazione energetica degli edifici, quelli analizzati in questo studio prevedono l’aggiunta di un isolamento a cappotto delle pareti esterne, l’isolamento della copertura e l’aggiunta di una struttura ombreggiante vegetale esterna. I risultati ottenuti danno una prima indicazione sugli interventi più efficaci in termini di miglioramento energetico e mettono in luce l’utilità del criterio proposto nell’evidenziare le criticità degli interventi migliorativi ipotizzati. Il metodo definito nella presente ricerca risulta quindi un valido strumento di valutazione a supporto della progettazione degli interventi di retrofit dei fabbricati rurali da convertire a magazzini per la conservazione del vino.

Enabling Human Centric Smart Campuses via Edge Computing and Connected Objects

Early definitions of Smart Building focused almost entirely on the technology aspect and did not suggest user interaction at all. Indeed, today we would attribute it more to the concept of the automated building. In this sense, control of comfort conditions inside buildings is a problem that is being well investigated, since it has a direct effect on users’ productivity and an indirect effect on energy saving. Therefore, from the users’ perspective, a typical environment can be considered comfortable, if it’s capable of providing adequate thermal comfort, visual comfort and indoor air quality conditions and acoustic comfort. In the last years, the scientific community has dealt with many challenges, especially from a technological point of view. For instance, smart sensing devices, the internet, and communication technologies have enabled a new paradigm called Edge computing that brings computation and data storage closer to the location where it is needed, to improve response times and save bandwidth. This has allowed us to improve services, sustainability and decision making. Many solutions have been implemented such as smart classrooms, controlling the thermal condition of the building, monitoring HVAC data for energy-efficient of the campus and so forth. Though these projects provide to the realization of smart campus, a framework for smart campus is yet to be determined. These new technologies have also introduced new research challenges: within this thesis work, some of the principal open challenges will be faced, proposing a new conceptual framework, technologies and tools to move forward the actual implementation of smart campuses. Keeping in mind, several problems known in the literature have been investigated: the occupancy detection, noise monitoring for acoustic comfort, context awareness inside the building, wayfinding indoor, strategic deployment for air quality and books preserving.

Analyzing urban green adaptation opportunities: concepts, approaches, & strategies for existing neighborhoods

Over the last decades, the growing evidence of human-caused climate change has raised awareness of the consequences of exceeding global temperature by 2˚C. This awareness has led to a contemporary approach to the conceptualization and management of green adaptation policies in spatial planning. This thesis aims to develop a comprehensive methodology for assessing the adaptability of existing neighborhoods to green strategies. The reliability of the proposed method is examined in the cities of Bologna and Imola and proved to be applicable in other geoghraphical locations. This thesis integrates three key themes of conceptual and implementation principles for urban green adaptation. This thesis initially defines methods for narrowing uncertainties in urban planning energy forecasting modeling by exploring the roles of integrated energy planning. The second is by exploring green retrofitting strategies in building, this thesis examines the effects of various energy-saving factors in roofing scenarios including a green roof, rooftop greenhouse, and insolated roof. Lastly, this thesis analyzes green strategies in urban spaces to enhance thermal comfort through facing urban heat exposure related to urban heat island effects. The roles of integrated energy policies and green strategic thinking are discussed to highlight various aspects of green adaptation on the neighborhood scale. This thesis develops approaches by which cities can face the challenges of current green urban planning and connect the conceptual and practical aspects of green spatial planning. Another point that this thesis highlight is that due to the interdependency of individuals and places, it is difficult to assure whether all the adaptation policies on a large scale are enhancing the resiliency of the neighborhood or they are simply shuffling the vulnerability through the individuals and places. Besides, it asserts that neglecting to reflect on these reallocations of the effects generates serious complications, and will result in long-term dysfunctional consequences.

Urban air quality: new high-resolution modeling approaches and forecasting tools for citizens

Air pollution is one of the greatest health risks in the world. At the same time, the strong correlation with climate change, as well as with Urban Heat Island and Heat Waves, make more intense the effects of all these phenomena. A good air quality and high levels of thermal comfort are the big goals to be reached in urban areas in coming years. Air quality forecast help decision makers to improve air quality and public health strategies, mitigating the occurrence of acute air pollution episodes. Air quality forecasting approaches combine an ensemble of models to provide forecasts from global to regional air pollution and downscaling for selected countries and regions. The development of models dedicated to urban air quality issues requires a good set of data regarding the urban morphology and building material characteristics. Only few examples of air quality forecast system at urban scale exist in the literature and often they are limited to selected cities. This thesis develops by setting up a methodology for the development of a forecasting tool. The forecasting tool can be adapted to all cities and uses a new parametrization for vegetated areas. The parametrization method, based on aerodynamic parameters, produce the urban spatially varying roughness. At the core of the forecasting tool there is a dispersion model (urban scale) used in forecasting mode, and the meteorological and background concentration forecasts provided by two regional numerical weather forecasting models. The tool produces the 1-day spatial forecast of NO2, PM10, O3 concentration, the air temperature, the air humidity and BLQ-Air index values. The tool is automatized to run every day, the maps produced are displayed on the e-Globus platform, updated every day. The results obtained indicate that the forecasting output were in good agreement with the observed measurements.

Thermal and air quality modeling of an electric vehicle cabin with low-cost sensors and reinforcement learning

The design process of any electric vehicle system has to be oriented towards the best energy efficiency, together with the constraint of maintaining comfort in the vehicle cabin. Main aim of this study is to research the best thermal management solution in terms of HVAC efficiency without compromising occupant’s comfort and internal air quality. An Arduino controlled Low Cost System of Sensors was developed and compared against reference instrumentation (average R-squared of 0.92) and then used to characterise the vehicle cabin in real parking and driving conditions trials. Data on the energy use of the HVAC was retrieved from the car On-Board Diagnostic port. Energy savings using recirculation can reach 30 %, but pollutants concentration in the cabin builds up in this operating mode. Moreover, the temperature profile appeared strongly nonuniform with air temperature differences up to 10° C. Optimisation methods often require a high number of runs to find the optimal configuration of the system. Fast models proved to be beneficial for these task, while CFD-1D model are usually slower despite the higher level of detail provided. In this work, the collected dataset was used to train a fast ML model of both cabin and HVAC using linear regression. Average scaled RMSE over all trials is 0.4 %, while computation time is 0.0077 ms for each second of simulated time on a laptop computer. Finally, a reinforcement learning environment was built in OpenAI and Stable-Baselines3 using the built-in Proximal Policy Optimisation algorithm to update the policy and seek for the best compromise between comfort, air quality and energy reward terms. The learning curves show an oscillating behaviour overall, with only 2 experiments behaving as expected even if too slow. This result leaves large room for improvement, ranging from the reward function engineering to the expansion of the ML model.