1,721,057 research outputs found
Data-driven fault detection and diagnosis: research and applications for HVAC systems in buildings
Get PDFAzioni per la riduzione dell'impatto ambientale dello smaltimento di rifiuti urbani biodegradabili residuali in discarica
No full textNel rispetto delle direttive europee, un moderno sistema integrato di gestione dei rifiuti
è concepito per intercettare già in fase di raccolta i Rub (Rifiuti urbani biodegradabili),
al fine di valorizzarli, per la gran parte, attraverso il recupero di materia per la produzione
di ammendanti di qualità, sottraendoli ai circuiti di smaltimento dove, se non correttamente
gestiti, sarebbero in grado di esercitare nel tempo il maggiore impatto
sull’ambiente. In Italia, in particolare nelle regioni meridionali, l’aliquota di tale frazione
che sfugge alla raccolta differenziata non può essere ritenuta trascurabile, meritando,
dunque, particolare attenzione nella gestione della fase di smaltimento.
È ormai diffusa [Cossu 2003; Stegmann 2005], infatti, la consapevolezza che i sistemi
per il contenimento delle emissioni, stistemi attualmente in uso nelle discariche
controllate (c.d. dry tomb landfill) secondo quanto previsto dalla normativa vigente,
producano soltanto un prolungamento dei tempi di impatto. Inoltre, è noto che, al termine
del periodo di postesercizio (30 anni dopo la chiusura definitiva dell’impianto,
cfr. immagine seguente), per un periodo non facilmente quantificabile, la pericolosità
dei rifiuti resti quasi immutata: il sito, dunque, può risultare ancora a rischio così da
provocare un impatto ambientale fin troppo elevato per essere considerato tollerabile.
Questo lasso di tempo indeterminato, successivo al post-esercizio, sarebbe, inoltre,
quello a più bassa efficienza dei sistemi per il contenimento delle emissioni inquinanti:
l’integrità delle barriere geosintetiche, l’efficienza della rete drenante e di estrazione del percolato e del biogas, infatti, potrebbero iniziare a diminuire, provocando conseguentemente
un aumento del rischio ambientale associato a emissioni incontrollate di
contaminante. In questa fase i costi per i presidi ambientali o per eventuali interventi di
risanamento non sarebbero più coperti dalla tariffa versata per lo smaltimento (questa,
infatti, copre soltanto i costi di allestimento, esercizio e post-esercizio), ma sarebbero
evidentemente a carico della collettività.
Una gestione sostenibile della frazione organica biodegradabile dei rifiuti solidi urbani
non può non porsi l’obiettivo di ridurre la pericolosità dei rifiuti residuali prima
dello smaltimento in discarica, dove può essere opportuno attuare protocolli gestionali
finalizzati ad accelerare la completa stabilizzazione dei rifiuti, raggiungendo livelli accettabili
di impatto ambientale in tempi brevi e certi
A data analytics-based energy information system (EIS) tool to perform meter-level anomaly detection and diagnosis in buildings
Get PDFRecently, the spread of smart metering infrastructures has enabled the easier collection of building-related data. It has been proven that a proper analysis of such data can bring significant benefits for the characterization of building performance and spotting valuable saving opportunities. More and more researchers worldwide are focused on the development of more robust frameworks of analysis capable of extracting from meter-level data useful information to enhance the process of energy management in buildings, for instance, by detecting inefficiencies or anomalous energy behavior during operation. This paper proposes an innovative anomaly detection and diagnosis (ADD) methodology to automatically detect at whole-building meter level anomalous energy consumption and then perform a diagnosis on the sub-loads responsible for anomalous patterns. The process consists of multiple steps combining data analytics techniques. A set of evolutionary classification trees is developed to discover frequent and infrequent aggregated energy patterns, properly transformed through an adaptive symbolic aggregate approximation (aSAX) process. Then a post-mining analysis based on association rule mining (ARM) is performed to discover the main sub-loads which mostly affect the anomaly detected at the whole-building level. The methodology is developed and tested on monitored data of a medium voltage/low voltage (MV/LV) transformation cabin of a university campus
SURVEY, STRATIGRAPHY OF THE ELEVATIONS, 3D MODELLING FOR THE KNOWLEDGE AND CONSERVATION OF ARCHAEOLOGICAL PARKS: THE CASTLE OF AVELLA
Get PDFThe site of Avella is a precious example of ruined medieval fortification with territorial and landscape values. The width and vulnerability of its masonry remnants require a systematic survey and physical investigation, necessary to any preservation and enhancement strategy planning, so far, not yet extended to the fronts of the fortress and the two walled lines. The understanding of the process, scientifically based, which over time has led the buildings to the present state of fragmentation has the same need. Obtain with expedited methods and customary instruments a photogrammetrically controlled survey, the stratigraphic study of the castle elevations and the processing of a photo-based 3D model is therefore the aim of the paper. Carried out on an interdisciplinary basis, it comes from the extension of the outcomes of a didactic workshop in master’s degree courses in Architectural Survey and Restoration Design, held in 2018. The surveying procedure with the drone proved to be the most suitable, also for the possibility of an expeditious and cheaper measurement phase compared to other surveying methods. The results comprise the fortress georeferenced ortho-photomosaic and its photo-based 3D model, then exported both as a point cloud and a 3D mesh. The workshop also implemented topography and terrestrial photogrammetry procedures, such as to be compared with the previous one
Recognition and classification of typical load profiles in buildings with non-intrusive learning approach
Get PDFThe recent increasing spread of Advanced Metering Infrastructure (AMI) has enabled the collection of a huge amount of building related-data which can be exploited by both energy suppliers and users to gain insight on energy consumption patterns. In this context, data analytics-based methodologies can play a key role for performing advanced characterization, benchmarking and classification of buildings according to their typical energy use in the time domain. Traditionally, energy customers are classified according to their building end-use category. However, buildings belonging to the same category can exhibit very different energy patterns making ineffective this kind of a-priori categorization. For this reason, load profiling frameworks have been developed in the last decade to identify homogenous groups of buildings with similar daily energy profiles. The present study proposes a non-intrusive customer classification process, which does not use as predictive attributes in-field load monitoring data for the classification of unknown customers, but rather monthly energy bills and additional information on customers’ habits collected by means of a phone survey. The proposed classification process is developed by analysing hourly energy consumption data of 114 electrical customers of an Italian Energy Provider. The representative daily load profiles are grouped using the “Follow the Leader” clustering algorithm and a globally optimal decision tree is employed to build a supervised classification model. The model, compared to a baseline recursive partitioning tree, leads to an increase of accuracy of about 6%. Eventually, the procedure exploits energy bill data also for estimating the magnitude of typical load profiles
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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