This Thesis deals with an innovative approach to the design of ground-source heat pump systems (GSHP), based on performance optimization during the entire operational life. Both design and management strategies are taken into account in order to find the optimal level of exploitation of the ground source, minimizing a proper performance index. The proposed method takes into account all the macro-systems governing the energy balance of the GSHP, namely: building thermal energy loads, efficiencies of the heat pump unit and back-up systems, and thermal response of the ground source. For each of them, suitable simulation models are presented and discussed. A rigorous mathematical formulation of the optimal design problem is provided, together with a specific resolution technique. In this regard, we also propose a statistically based evaluation methodology in order to analyze the soundness of the results of the optimization procedure. The main results of the proposed design and optimization methodology are: thermal capacities of heat pump and back-up generators, length and number of ground heat exchangers and the optimal load share between GSHP and back-up systems (control strategy). If installation costs and energy prices are taken into account, investment figures are also an output. We show how a proper synergy among GSHP and back-up generators leads to notable energetic and economic benefits, ensuring higher energetic performances, lower installation costs, and a sustainable exploitation of the ground-source. The proposed methodology can be conveniently applied to numerous professional, political, economic, and research activities. In this Thesis, we present two case studies. The first one refers to a typical professional design case, showing both the energetic and economic benefits achievable through the illustrated procedure with respect to traditional design methods. The second one illustrates as the proposed methodology can be applied to investigate the technological room for improvement of GSHP technology: in other words, we figure out the subsystem on which technological development should be focused, the expected benefits and some hints about a possible strategy for research activities.
The problem of energy quality control in buildings was officially recognised for the first time at a European level in the EEC directive no. 93/76 of 1993. This directive represented the formal act of an undertaking to promote actions that would lead to a reduction in global carbon dioxide (CO2)emissions. Article 2 of this directive established that states should carry out programmes concerning the energy certification of buildings, which were consistent in the description of their energy parameters, so as to allow future users of a building to know and understand its energy efficiency. Italy acknowledged this directive, along with the subsequent European directive 2002/91/CE on energy efficiency in the building industry, with the Legislative Decree 192 of 2005.
Energy consumption in the building sector is responsible for 36% of the energy use worldwide (corresponding to 39% of the total energy-related CO2 emissions), while at the European level the building sector accounts for a share of the total energy consumption comprised between 25% and 40% (corresponding to about 35% of the overall CO2 emissions throughout Europe). Concerning the Italian context, instead, such figures stand at about 40% and 17.5% for the energy consumption and for the CO2 emissions, respectively. In light of this, much attention has been paid, at global, European and single countries (national) levels on the important aspects regarding the reduction of energy consumption and the related decrease of greenhouse gases emissions in order to improve the environmental performance and the resilience of the building sector, both by the political and legislative bodies and by the scientific community. Despite the effort spent in putting into effect such actions, in recent years, the energy consumption in the building sector has experienced an increase, particularly in Italy. That is why more exertion in advancing the current measures and finding new innovative strategies to improve energy efficiency and resilience of buildings are of paramount importance. The research work carried out during the PhD course, and presented in this doctoral thesis, arises precisely from this context and from the desire to contribute to the question. To this end, strategies and solutions aimed at improving the energy efficiency, environmental performance and resilience of buildings, were assessed in detail by means of both experimental and modeling approaches. Accordingly, a number of case studies were designed and conducted to estimate how the adoption of some proposed interventions could impact the energy consumption, the indoor thermal comfort and contribute to the reduction of the CO2 emissions of buildings. In doing this, two important aspects influencing the afore-mentioned strategies and solutions were also considered, namely, the effect of the climatic conditions characterizeing the considered sites and the spatial scale at which they are applied, from the single building to a wider group of them, and how such perspective may influence the surrounding areas. The outcomes of the carried-out work put in evidence how accurate planning, construction and management of buildings, according to the peculiarities of the sites in which they are located, can contribute to reduce the energy and environmental burden of the building sector and at the same time help in the enhancement of urban resilience. Proper solution sets can, in fact, enable the building resilience against the outdoor stresses and simultaneously guarantee a regenerative indoor environment.
In July 2013, the Italian photovoltaic (PV) support policies changed the feed-in tariff (FIT) mechanism and turned to a tax credits program, which is currently in force. The aim of this paper is to investigate how such a radical change has influenced the electricity demand coverage of the PV systems installed in urban contexts. A methodology, which connects the economic assessment to a detailed architectural and energy suitability analysis, was applied to some case studies to analyse the relationships between the physical parameters related to multi-storey buildings (roof shapes, number of floors and area of flats) and the most relevant economic and financial features affecting the viability of rooftop PV systems. The study, which considers only the electricity produced by the PV systems that are economically profitable, highlighted that the tax credits scheme is even more effective in covering the electrical consumption of densely urbanised Italian city districts. The results, which are significantly influenced by the latitude of the analysed districts, underline the opportunity for governments to adopt PV promoting policies that are more sensitive to the amount of solar energy available in the different regions of their national territory.
Although many centuries have passed, in many ancient theatres evocative theatrical performances still take place, especially during summer. Greek and Latin architects care for equilibrium of proportions offers not only an intense quality of view but also a high quality acoustics. In our study we did an analysis both theoretical and experimental of the acoustic parameters of the ancient theaters of Syracuse, Segesta, and Akrai, in Sicily and the theater of Bulla Regia, in Jendouba (Tunisia), it was only simulated, because of the inability to reach the scene for reasons due to the political turmoil. A measurement session was carried out by our team in the framework of a wide research project on ancient theatres acoustics in the modern use. From data recorded "room criteria" parameters have been evaluated together with spectral analysis in order to gain deeper information on the acoustic field. Main results are compared to data collected during the team experience in the past years.
La tesi di dottorato si colloca all'interno di un lavoro di ricerca realizzato nell'ambito del Progetto PRIN 2015 (Progetto di Rilevante Interesse Nazionale) che ha visto per 36 mesi la collaborazione di dodici università Italiane, allo scopo di realizzare un network di ricerca per la riqualificazione del parco edilizio esistente in ottica nZEB (nearly zero energy buildings). Gli studi, le sperimentazioni e i progetti pilota di edifici ad alta efficienza energetica sono importanti al fine di accelerare i processi verso la realizzazione di edifici autosufficienti, fornendo esempi ed esperienze pratiche sulle prestazioni, le tecnologie, i costi, e dove possibile le esperienze degli utenti. Inoltre, l'adozione di sistemi ibridi di energia in grado di combinare combustibili fossili con fonti di energia rinnovabile è considerata una valida soluzione per il risparmio di energia primaria negli edifici. Sulla scia del contesto energetico, la ricerca si inserisce in un quadro procedurale in corso di sviluppo nei ultimi anni, identificato come Building Information Modelling (BIM), che implica una gestione informativa e una digitalizzazione automatica dell'edificio. La pubblicazione della UNI 11337 avvenuta nel gennaio del 2017, e la serie ISO 19650 avvenuta nel mese di dicembre 2018, stabiliscono i primi passi da rispettare per supportare tutte le parti nel raggiungimento dei propri obiettivi qualitativi ed economici, fissando l'obbligo di utilizzo del BIM per le opere pubbliche e private. Il tema prevede un insieme di tecnologie, processi e politiche che consentono a più parti interessate di progettare, costruire e gestire in modo collaborativo un immobile. Su questi aspetti, la creazione, la manipolazione e l'analisi dei dati, rappresentano il ruolo predominante per far fronte ai cambiamenti di innovazione tecnologica. Nel presente elaborato si vuole dimostrare l'efficacia in termini di trasparenza del dato proveniente da una modellazione parametrica BIM, fino alla simulazione in un software energetico, la successiva gestione del dato in un database PostgreSQL, e la visualizzazione semplificata in un sistema geo referenziato Cesium. La ricerca è stata portata avanti su tre casi applicativi di differente entità, il caso Test (base) per l'approccio al tema, il caso semplice per la verifica della procedura e il caso complesso, dotato di sistema impiantistico avanzato. L'impianto ibrido investigato all'interno dell'ultimo caso studio contribuisce a sostenere l'approccio orientato alla riduzione delle emissioni di CO2 e al risparmio in termini di energia primaria, il quale, unito alle nuove tecnologie procedurali contribuisce al raggiungimento di un futuro più sostenibile e autosufficiente. Per dimostrare le possibilità offerte dall'innovazione sono state considerate due tipi analisi, la simulazione energetica e di illuminamento, e due formati di interscambio, il file gbxml e il file IFC. Alla fine di questa prima fase sono state valutate le risposte sia dal punto di vista di trasmissione del dato che di validità delle simulazioni. Successivamente, i dati geometrici sono stati referenziati in un sistema geo-spaziale e, insieme alle informazioni energetiche, sono stati ospitati e manipolati all'interno di un Database gestionale in grado di archiviare le fonti e interrogarle per mezzo di servizi WEB.
Degree-days (DD) are a climatic indicator that can be used in the assessment and analysis of weather related to energy consumption of buildings. Essentially, degree-days are a summation of the differences between the outdoor temperature and some reference (or base) temperature over a specific time period. In literature, different method can be used for determining the DD value and generally the choice depends on the availability of climatic data of each location. In this paper, after a review and comparison of the most common approaches used to determine DD, the Italian procedure was deeply analyzed. The application of Italian technical rules is based on weather data calculated on a monthly time series monitored before 1994. The obsolescence of the used weather data leads to an incorrect assessment of energy performances. Taking into account the climatic change that in the last years has affected Italy land, the aim of the paper is to assess the impact of new DD values in calculating energy demand of buildings. For these reasons, in this paper the authors recalculated DD of some Italian cities, considering the average monthly temperatures of the last decade. Data were extracted from Meteonorm 7, one of the most popular software for the statistical processing of climate data. Furthermore, other datasets were generated considering future scenarios defined by IPCC (Intergovernmental Panel on Climate Change). A comparison with the official DD issued by current legislation and new DD recalculated with more recent data highlighted how climate change have affected the calculation of this parameter
Questa ricerca si inserisce nell'ambito della verifica della "sostenibilità ambientale delle realizzazioni antropiche" . Una preliminare fase di studio dei macroscopici aspetti economici, sociali, ambientali globali, ha spinto la mia indagine su un piano via via più intimo, individuando infine nell'uomo, nella sua integrità, l'elemento chiave per una corretta stima dei fenomeni di criticità energetico-ambientale. Procedendo, anche attraverso una fase sperimentale di cooperazione internazionale tra l'Università di Palermo e il mondo delle imprese di piccole comunità locali del Bangladesh, sono giunto alla definizione di SVILUPPO ZERO, che si presenta come una chiave di lettura dei temi (sociali, politici, economici, ambientali) del presente, ma anche, entrando nel merito, come possibile maniera per aiutare a capire e risolvere le nuove dinamiche planetarie della dialettica uomo-uomo, uomo-ambiente. Rispetto al passato, le novità rappresentate dai temi attuali stanno nei processi sociali e ambientali che l'uomo, alla ricerca del suo benessere, ha avviato senza preoccuparsi dei caratteri e degli effetti, per la prima volta nella storia umana, irreversibili. Stando a tutto ciò, SVILUPPO ZERO si presenta come un modello, esempio, di possibile sviluppo. Non unico e rigido, al quale tendere in senso dogmatico, ma flessibile, "liquido", come le nuove dinamiche planetarie e inclusivo. Essendo l'uomo il mattone della sua struttura, l'elemento costruttivo, SVILUPPO ZERO può infiltrarsi e fare da collante in quella maglia di sempre nuove crepe che rischiano di far frantumare il sistema umano e quindi ambientale. Esperimento teorico e pratico, traccia di un progresso partecipativo e condiviso (con ricadute sociali, antropologiche, ambientali) che parte da nuovi sistemi di crescita e benessere, sintesi di contributi e istanze peculiari su una base di equilibrio generale, universale. Questo lavoro è stato presentato in occasione del Terzo Forum Mondiale dello Sviluppo Economico Locale a Torino (EXPOTO 2015). ; SOSTENIBILITA' AMBIENTALE
The aim of this paper is to estimate how the profitability of grid-connected PV (photovoltaic) systems may vary month by month due to the changes in all parameters involved in the economic evaluation (discount rate, PV electricity selling price, inflation rate, price of PV devices etc.). The effects of these variations were investigated for a district of a city in the South Italy (Palermo). The results of the analysis provided the trend of the actual coverage of the district power demand from June 2010 to August 2012. In particular the load match index, which considers the daily energy demand covered by PV systems, ranged from almost 30% to less than 12%, which is less than the value of 17% of the final energy consumption in 2020 from renewable energy sources that Italy is obliged to ensure by the European Union Directive 2009/28/EC. Finally, a sensitivity analysis related to shading and mismatch factors was carried out. If 10% of the solar energy had been shadowed, the load match index would have reduced of 70%. Similarly, if only 40% of electrical production had been used, the load match index would have lowered to an almost null value in January 2012.
The European Union is moving towards a sustainable, decarbonized, and circular economy. It has identified seven key value chains in which to intervene, with the battery and vehicle value chain being one of them. Thus, actions and strategies for the sustainability of batteries need to be developed. Since Life Cycle Assessment (LCA) is a strategic tool for evaluating environmental sustainability, this paper investigates its application to two configurations of a sodium–nickel chloride cell (planar and tubular), focusing on the active material and the anode, with the purpose of identifying the configuration characterized by the lowest environmental impacts. The results, based on a "from cradle to gate" approach, showed that the tubular cell performs better for all environmental impact categories measured except for particulate matter, acidification, and resource depletion. With nickel being the main contributor to these impact categories, future sustainable strategies need to be oriented towards the reduction/recovery of this material or the use of nickel coming from a more sustainable supply chain. The original contribution of the paper is twofold: (1) It enriches the number of case studies of LCAs applied to sodium/nickel chloride cells, adding to the few studies on these types of cells that can be found in the existing scientific literature. (2) The results identify the environmental hot spots (cell configuration and materials used) for improving the environmental footprint of batteries made from sodium/nickel chloride cells.
The LIFE+ Programme is the European Union's funding instrument for the environment. The general objective of LIFE+ is to contribute to the implementation, updating and development of EU environmental policy and legislation by co-financing pilot or demonstration projects with European added value. In the framework of LIFE+, the project "Forwarding demonstrative ACTions On a Regional and local scale (FACTOR20) to reach EU targets of the European Plan 20/20/20" was founded by European Commission. FACTOR20 is aimed to define a set of tools to support the planning of regional and national policies for the reduction of greenhouse gas emissions and for the reduction of energy consumption. The knowledge of the existing building allow to quantify energy consumption of an urban area and to highlight what are the main energy problems on which to intervene. One of these tools is the definition of a new building regulation schema that identifies the best practices to improve the energy efficiency, to reduce the GHG emissions and to promote the use of RES. The authors, in order to assess the applicability and the effectiveness of some key actions proposed in the new building regulation plan schema, have performed a detailed dynamic analysis of energy consumptions related to typical building structures strongly representative of Sicilian context. The simulations, carried out by using TRNSYS17, have permitted to assess the actual energy consumptions and then to compare the new energy performances induced by the application of some key retrofit actions. In this way it was possible to identify which retrofit action is more convenient from the point of view of energy and environmental; also the designer have an indication to the designer on the priorities of retrofit actions.
The refurbishment of the building stock is a key strategy towards the achievement of the climate and energy goals of the European Union. This study aims at evaluating the energy and environmental impacts associated with retrofitting a residential apartment to improve its vertical envelope thermal insulation. Two insulation materials, stone wool and cellulose fibers, are compared. The life cycle assessment methodology is applied assuming 1 m2 of retrofitted vertical envelope as functional unit. Moreover, to estimate the net energy and environmental benefits achievable in the retrofitted scenario compared with the non‐retrofitted one, a second analysis is performed in which the system boundaries are expanded to include the building operational phase, and 1 m2 of walkable floor per year is assumed as reference. The results show that the use of cellulose fibers involve lower impacts in most of the assessed categories compared to stone wool, except for abiotic resource depletion. In detail, the use of cellulose fibers allows to reduce the impact on climate change up to 20% and the consumption of primary energy up to 10%. The evaluation of the net energy and environmental benefits shows the effectiveness of the retrofit energy policies.
The Confederate Graves Survey Archive of the Texas Division, Sons of Confederate Veterans consists of surveys of cemeteries throughout Texas, and portions of Oklahoma and New Mexico. The surveys document the interment of Confederate States of America military veterans. United States of America (Union) veterans, as well as able-bodied men at the time of the Civil War, are also documented. 13 boxes entitled "Grave Surveys" contain grave surveys listed county-by-county, 3 boxes of "Unit Files" list surveyed individuals by their military unit. Finally, 17 boxes contain "Veteran Files" that document each veteran by name in "last name, first name, middle initial" format. An index that cross-references each of the collection series (Grave Surveys, Unit Files, and Veteran Files) is included, as are institutions to surveyors on how and what to document while conducting surveys. ; North Belton Cemetery #001, Belton, Bell County, Texas | Veterans Interred: Hiatt, Marion F.
The research activity carried out during the three years of the PhD course attended, at the Engineering Department of the University of Palermo, was aimed at the identification of an alternative predictive model able to solve the traditional building thermal balance in a simple but reliable way, speeding up any first phase of energy planning. Nowadays, worldwide directives aimed at reducing energy consumptions and environmental impacts have focused the attention of the scientific community on improving energy efficiency in the building sector. The reduction of energy consumption and CO2 emissions for heating and cooling needs of buildings is an important challenge for the European Union, because the buildings sector contributes up to 36% of the global CO2 emissions [1] and up to 40% of total primary energy consumptions [2]. Despite the ambitious goals set by the Energy Performance of Buildings Directive (EPBD) at the European level [1], which states that, by 2020, all new buildings and existing buildings undergoing major refurbishments will have to be Nearly Zero Energy Buildings (NZEB) [3,4], the critical challenge remains the improvement of the efficiency when upgrading the existing building stock to standards of the NZEB level [5]. The improvement of the energy efficiency of buildings and their operational energy usage should be estimated early in the design phase to guarantee a reduction in energy consumption, so buildings can be as sustainable as possible [6]. While a newly constructed NZEB can employ the "state of the art" of available efficient technologies and design practices, the optimization of existing buildings requires better efforts [7]. One way or the other, the identification of the best energy retrofit actions or the choice of a better technological solution to plan a building is not so simple. It has become one of the main objectives of several research studies, which require deep knowledge in the field of the building energy balance. The building thermal balance includes all sources and sinks of energy, as well as all energy that flows through its envelope. More in detail, the energy demand in buildings depends on the combination of several parameters, such as climate, envelope features, occupant behaviour and intended use. Indeed, the assessment of building energy performance requires substantial input data describing structures, environmental conditions [8], thermo-physical properties of the envelope, geometry, control strategies, and several other parameters. From the first design phases designers and researchers, which are trying to respect the prescriptions of the EPBD directive and to simultaneously ensure the thermal comfort of the occupants, must optimize all possible aspects that represent the key points in the building energy balance. As will be shown in Chapter A, the literature offers highly numerous complex and simplified resolution approaches [9]. Some are based on knowledge of the building thermal balance and on the resolution of physical equations; others are based on cumulated building data and on implementations of forecast models developed by machine-learning techniques [10]. Several numerical approaches are most widespread; these have undergone testing and implementing in specialised software tools such as DOE-2 [11], Energy Plus [12], TRNSYS [13] and ESP-r [14]. Such building modelling software can be employed in several ways on different scales; they can be simplified [15,16] or detailed comprehensively by different methods and numerical approaches [17]. Nevertheless, they are often characterised by a lack of a common language, which constitutes an obstacle for making a suitable choice. It is often more convenient to accelerate the building thermal needs evaluation and use the simplified methods and models. For example, a steady state approach for the evaluation of thermal loads is characterised by a good level of accuracy and low computational costs. However, its main limitation is that some phenomenon, such as the thermal inertia of the building envelope/structure, may be completely neglected. On the other hand, the choice of a more complex solution, such as the dynamic approach, uses very elaborate physical functions to evaluate the energy consumption of buildings. Although these dynamic simulation tools are effective and accurate, they have some practical difficulties such as collecting detailed building data and/or evaluating the proper boundary conditions. The use of these tools normally requires an expert user and a careful calibration of the model and do not provide a generalised response for a group of buildings with the same simulation, because they support a specific answer to a specific problem. Meanwhile the lack of precise input can lead to low-accuracy simulation. Anyway, in all cases it is necessary to be an expert user to implement, solve and evaluate the results, and these phases are not fast and not always immediately provide the correct evaluation, conducting the user to restart the entire procedure. In the field of energy planning, in order to identify energy efficiency actions aimed at a particular context, could be more convenient to speed up the preliminary assessment phase resorting to a simplified model that allows the evaluation of thermal energy demand with a good level of accuracy and without excessive computational cost or user expertise. The aim of this research, conducted during the three years of the PhD studies, is based on the idea of overcoming the limits previously indicated developing a reliable and a simple building energy tool or an evaluation model capable of helping an unskilled user at least in the first evaluation phase. To achieve this purpose, the first part of the research was characterised of an in-depth study of the sector bibliography with the analysis of the most widespread and used methods aimed at solving the thermal balance of buildings. After a brief distinction of the analysed methods in White, Black and Grey Box category, it was possible to highlight the strengths and weaknesses of each one [9]. Based on the analysis of this study, some alternative methods have been investigated. In detail, the idea was to investigate several Black-Box approaches; mainly used to deduce prediction models from a relevant database. This category does not require any information about physical phenomena but are based on a function deduced only by means of sample data connected to each other and which describes the behaviour of a specific system. Therefore, it is fundamental the presence of a suitable and well-set database that characterise the problem, so that the output data are strongly related to one or more input data. The completely absence of this information and the great difficulty in finding data, has led to the creation of a basic energy database which, under certain hypotheses, is representative of a specific building stock. For this reason, in the first step of this research was developed a generic building energy database that in a reliable way, and underlining the main features of the thermal balance, issues information about the energy performances. In detail, two energy building databases representative of a non-residential building-stock located in the European and Italian territory have been created. Starting from a well-known and calibrated Base-Case dynamic model, which simulates the actual behaviour of a non-residential building located in Palermo, it was created an Ideal Building representative of a new non-residential building designed with high energy performances in accordance whit the highest standard requirements of the European Community. Taking into consideration the differences existing in the regulations and technical standards about the building energy performance of various European countries, several detailed dynamic simulation models were developed. Moreover, to consider different climatic characteristics, different locations were evaluated for each country or thermal zone which represent the hottest, the coolest and the mildest climate. The shape factor of buildings, which represents the ratio between the total of the loss surfaces to the gross heated volume of a building, was varied from 0.24 to 0.90. To develop a representative database where the data that identify the building conditions are the inputs of the model linked to an output that describes the energy performances it was decided to develop a parametric simulation. In detail different transmittance values, boundary conditions, construction materials, and energy carriers were chosen and employed to model representative building stocks of European and Italian cities for different climatic zones, weather conditions, and shape factor; all details and the main features are described in Chapter B. These two databases were used to investigated three alternative methods to solve the building thermal balance; these are: • Multi Linear Regression (MLR): identification of some simple correlations that uses well known parameters in every energy diagnosis [18–20]; • Buckingham Method (BM): definition of dimensionless numbers that synthetically describe the relationships between the main characteristic parameters of the thermal balance [21]; and • Artificial Neural Network (ANN): Application of a specific Artificial Intelligence (AI) to determine the thermal needs of a [22] building. These methods, belonging to the Black-Box category, permit solving a complex problem easier with respect to the White-Box methods because they do not require any information about physical phenomena and expert user skills. Only a small amount of data on well-known parameters that represent the thermal balance of a building is required. The first analysed alternative method was the MLR, described in Chapter C. This approach allowed to develop a simple model that guarantees a quick evaluation of building energy needs [19] and is often used as a predictive tool. It is reliable and, at the same time, easy to use even for a non-expert user since an in-depth knowledge in the use phase is not needed, and computational costs are low. Moreover, the presence of an accurate input analysis guarantees greater speed and simplicity in the data collection phase [23]. The basis for this model is the linear regression among the variables to forecast and two or more explanatory variables. The feasibility and reliability of MLR models is demonstrated by the publication of the main achieved results in international journals. At first, the MLR method was applied on a dataset that considered heating energy consumptions for three configurations of non-residential buildings located in seven European countries. In this way, it was developed a specific equation for each country and three equations that describe each climatic region identified by a cluster analysis; these results were published in [19]. In a second work [18], it was applied the same methodology to a set of data referring to buildings located in the Italian peninsula. In this case, three building analysed configurations, in accordance to Italian legislative requirements regarding the construction of high energy performance buildings, have been employed. The achievement of the generalised results along with a high level of reliability it was achieved by diversifying each individual model according to its climate zone. It was provided an equation for each climate zone along with a unique equation applicable to the entire peninsula, obviously with different degrees of reliability. An improved version of the latest work concerning the Italian case study appeared in the paper published in [20]. The revised model provided an ability to predict the energy needs for both heating and cooling. Furthermore, to simplify the data retrieval phase that is required for the use of the developed MLR tool, an input selection analysis based on the Pearson coefficient has been performed. In this way the explanatory variables, needful for an optimal identification of thermal loads, have been identified. Finally, a comprehensive statistical analysis of errors ensured high reliability. The second analysed alternative method represents an innovative approach in developing a flexible and efficient tool in the building energy forecast framework. This tool predicts the energy performance of a building based some dimensionless parameters implemented through the application of the Buckingham theorem. A detailed description of the methodology and results is discussed in the Chapter D and is also published in [21]. The Buckingham theorem represents a key theorem of the dimensional analysis since it is able to define the dimensionless parameters representing the building balance [24]. These parameters define the relationships between the descriptive variables and the fundamental dimensions. Such a dimensional analysis guarantees that the relationship between physical quantities remains valid, even if there is a variation of the magnitudes of the base units of measurement [25]. The dimensional analysis represents a good model to simplify a problem by means of the dimensional homogeneity and, therefore, the consequent reduction in the number of variables. Therefore, this model works well with different applications such as forecasting, planning, control, diagnostics and monitoring in different sectors. The application of the BM for predicting the energy performance of buildings determined nine ad hoc dimensionless numbers. The identification of a set of criteria and a critical analysis of the results allowed to immediately determine thought the dimensionless numbers and without using any software tool, the heating energy demand with a reliability of over 90%. Furthermore, the validation of the proposed methodology was carried out by comparing the heating energy demand that was calculated by a detailed and accurate dynamic simulation. The last Black-Box examined model was the application of Artificial Neural Networks. The ANNs are the most widely used data mining models, characterised by one of the highest levels of accuracy with respect to other methods but generally have higher computational costs in the developing phase [26]. The design of a neural network, inspired by the behaviour of the human brain, involves the large number of suitably connected nodes (neurons) that, upon applications of simple mathematical operations, influence the learning ability of the network itself [27]. Also in this case, as described in Chapter E, this methodology was applied at the two different energy databases. In [22], the ANN was used to predict the demand for thermal energy linked to the winter climatization of non-residential buildings located in European context, while in another work under review, the ANN was used to determine the heating and cooling energy demand of a representative Italian building stock. The validation of the ANNs was carried out by using a set of data corresponding to 15% of the initial set which were not used to train the ANNs. The obtained good results (determination coefficient values higher than 0.95 and Mean Absolute Percentage Error lower than 10%) show the suitability of the calculation model based on the use of adaptive systems for the evaluation of energy performance of buildings. Simultaneously, a deep analysis of the investigated problem, underlines how to determine the thermal behaviour of a building trough Black-Box models, particular attention must be paid to the choice of an accurate climate database that along with thermophysical characteristics, strongly influence the thermal behaviour of a building [9]. In detail, to develop a predictive model of thermal needs, it is also necessary to pay close attention to the climate aspects. In the literature, many studies use the degree day (DD) to predict building energy demand, but this assessment, through the use of a climatic index, is correct only if its determination is a function of the same weather data used for the model implementation. Otherwise, the predictive model is generally affected by a greater evaluation error; all these aspects are deeply discussed analysing a specific Italian case study in Chapter F, and the main results are published in [8]. The results achieved during the three years of PhD research, make it possible to affirm that each model can be used to solve thermal building balance by knowing merely a few parameters representative of the analysed problem. Nonetheless, some questions may be asked: Which of these models can be identified as the most efficient solution? Is it possible to compare the performances of these models? Is it possible to choose the most efficient model based on some specific phase in the evaluation? To attempt to answer these questions, during the research period it was decided to compare the three selected alternative models by applying a Multi Criteria Analysis (MCA), that explicitly evaluates multiple criteria in decision-making. It is a useful decision support tool to apply to many complex decisions by choosing among several alternatives. The idea rising thanks to the scientific collaboration with the VGTU University of Vilnius, Lithuanian, in the person of Prof. A. Kaklauskas and Prof. L. Tupènaitè, experts in the field of multi-criteria analysis. At the first time a multi-criteria procedure was applied to determine the most efficient alternative model among some resolution procedures of a building's energy balance. This application required extra effort in defining the criteria and identifying a team of experts. To apply the MCA, it was necessary to identify the salient phases of the evaluation procedure to explain the most sensitive criteria for acquiring conscious, truthful answers that only a pool of experts in the field can provide. Details of this work were carried out during the period of one-month research in Vilnius, from April to May 2019, where it was possible to improve the application of the Multiple Criteria Complex Proportional Evaluation (COPRAS) method for identifying the most efficient predictive tool to evaluate building thermal needs. These results are collected in Chapter G and the main results are explained in a paper under review in the Journal "Energy" from September. The identification of the most efficient alternative model to solve the building energy balance through the application of a specific MCA, allowed to deepen the identified methodology and improve research. In particular, the most efficient alternative resolution model was the subject of the research that took place during the research period at the RWTH in Aachen University, Germany with Prof. M. Traverso, Head of the INaB Department, from September 2018 to March 2019. The experience in the field of LCA and the possibility of identifying the environmental impacts linked to the building system, has led the research to investigate neural networks for a dual and simultaneous environmental-energy analysis. The results confirm that the application of ANNs is a good alternative model for solving the energy and environmental balance of a building and for ensuring the development of reliable decision support tools that can be used by non-expert users. ANNs can be improved by upgrading the training database and choosing the network structure and learning algorithm. The results of this research are collected in Chapter H and published in [28].
The present study verifies the thermo hygrometric comfort conditions in subjects of a university library users, evaluating the differences and peculiarities in the data collected at the measurement campaign. Particularities of the investigation is the period studied concerning the time frame of the Middle season, which is not expected to power the air conditioning systems. Based on assumptions on the thermal resistance of clothing in the spring and the metabolic type of subjects, the environmental parameters were monitored in some work position in the reading hall in the library of the Faculty of Medicine and Surgery of the University of Palermo. The article presents analyses of the measured data correlating the passive structure behavior and the variation of the internal temperature increases caused by the occupants and by the external temperature gradient. These results are compared with the limits and the guidelines provided by legislation for the main variables measured and derived, and which constitute the essential support to test the tolerability of the occupiers against the thermal environment with which they interact. Keywords: PMV PPD Indexes, Thermo-hygrometric comfort, acceptability classes.
