1,721,118 research outputs found
Proprietà termiche delle murature
No full textThe recently revised European standard EN 1745 describes methods for the determination of the thermal conductivity of solid masonry units, mortars, masonry units with formed voids and “composite” masonry units, i.e. masonry unit incorporating additional material in the voids, such as thermal insulation. The determination of the “dry” and “design” thermal conductivity values can be defined based on tabulated data, measurements, calculations or a combination of these. The main novelty of the new version lies in the inclusion of a method for the determination of the thermal design values of composite masonry elements. More details in this article
Manti permeabili per tetti traspiranti
No full textThat the ventilation in the roof effectively fulfils the cooling function of a building is a well-established concept.
However the common opinion associates the working of a
ventilated roof only related to the “chimney effect”, neglecting the
fact that in discontinuous coverings (such as clay tiles coverings),
most of the heat is dispersed by ventilation through the joints of
the tiles, with beneficial effects. This paper reports the results of
several experimental activities in this regard.
We monitored the summer thermal performance of full-scale roofs,
built according to the current requirements of thermal transmittance, with different types of coverings (clay tiles, copper) and
height of air gap (3 cm and 6 cm). Results show that clay tiles
roofs are more effective than copper roofs in cooling the internal
environment, and that in roofs with low thermal transmittance, it
is of little convenience to invest in elevated air gaps.
A tracking smoke test of the air movement into the roofs showed
that most of the air entering into the gaps of clay tiles roofs then
escapes through the joints of the tiles.
Laboratory tests allowed to quantify this airflow and to correlate
it to the amount of heat removed by ventilation in a clay tile roo
Ridurre la sopravvalutazione dei rischi associati a investimenti per l’efficientamento energetico: un approccio “probabilistico” a valutazioni dei costi nel ciclo di vita degli edifici
No full textRidurre la sopravvalutazione dei rischi associati a investimenti per l’efficientamento energetico
No full textOccupant density impact on building maintenance: Data-driven approach for university buildings
Full text linkBuilding maintenance needs in public buildings depend on occupant activities and presence. Research should understand how different types of occupant density patterns can be used to forecast the likelihood of specific kinds of maintenance requests. This research adopts a data-driven approach to evaluate experimental-based correlations between maintenance work orders number (relating to a set of Italian university buildings as a relevant case study) and occupant density, thanks to exceptional conditions due to COVID-19 pandemic, which significantly altered building use. Results offer a power-law-based correlation model, confirming that the reduction of occupant density in the COVID-19 lock-down phases impacted the number and perceived severity, but not the typologies, of maintenance work orders. The retrieved correlation model occupant could be directly used to define and prioritize maintenance strategies given occupant density. Future research could use the model to define outsourcing and contract definitions starting from historical data on maintenance actions
Automated priority assignment of building maintenance tasks using natural language processing and machine learning
No full textBuilding maintenance tasks to solve unpredictable faults typically start with written communications from end-users (e.g.,
emails). Technicians manually translate end-users’ requests in work-orders (WOs) assigning them a priority level and the needed staff typology.
When the number of contemporary requests is too high, these actions can lead to the interruption of critical services and then possible
safety issues. Machine Learning (ML) methods can be trained to automatize this process due to large databases of annotated requests. Nevertheless,
natural language preprocessing is needed to apply ML methods because of the unstructured form of the requests. This work aims to
verify how preprocessing impacts the ability of ML methods to properly assign priority to the requests. The research methodology combines
four different text preprocessing approaches (e.g., symbols and numbers remotion, stop-words remotion, stemming, meaningful words selection)
and five consolidated ML methods to classify WOs according to two different priority scales (binary, 4-classes). Accuracy, recall,
precision, and F1 are calculated for each combination. Tests are performed on a database of about 12,000 end-users’ maintenance requests,
generated for 34 months in 23 university buildings. Results show that strong preprocessing methods, usually performed to increase the effectiveness
of ML, do not significantly improve the accuracy of the predictions. Moreover, they show that four of the five tested ML methods
obtained a higher accuracy for binary classification and for high and mean priority classes of 4-classes classification. This means that ML
methods are especially effective in a preliminary check of the most urgent requests. These results then encourage the use of ML methods
in automatic priority assignment of building maintenance tasks, even if based on natural language unstructured requests. The ML can significantly
speed up the interventions assignment process for the technical staff, thus improving the maintenance process especially in large
and complex buildings organizations
Automatic detection of maintenance requests: Comparison of Human Manual Annotation and Sentiment Analysis techniques
Full text linkIn the building management process, the collection of end-users' maintenance requests is a rich source of information to evaluate occupants' satisfaction and building systems. Computerized Maintenance Management Systems typically collect non-standardized data, difficult to be analyzed. Text mining methodologies can help to extract information from end-users' requests and support priority assignment of decisions. Sentiment Analysis can be applied at this aim, but complexities due to words/sentences orientations/polarities and domains/contexts can reduce its effectiveness. This study compares the ability of different Sentiment Analysis techniques and Human Manual Annotation, considered the gold standard, to automatically define a maintenance severity ranking. About 12,000 requests were collected for 34 months in 23 University buildings. Results show that current Sentiment Analysis techniques seem to limitedly recognize the role of technical words for severity assessment of requests, thus remarking the necessity of novel lexicons in the field of building facility management for automatic maintenance management procedures
Immersive virtual vs real office environments: A validation study for productivity, comfort and behavioural research
Full text linkThe use of Virtual Reality (VR) to enhance research in the building sector is currently emerging, but validation studies are still limited. This work aims to provide a contribution in VR validation on comfort, productivity, and adaptive behaviour research in offices. 104 participants performed one test session in a real or a virtual room, three cognitive tasks and surveys (on immersivity, cybersickness, comfort, and intention of interaction). The validation process was addressed by evaluating the adequacy of VR in representing real-life scenarios and the benchmark of results. Findings confirmed the ecological validity of the model by an excellent sense of presence, graphical satisfaction, involvement, realism and low cybersickness levels. The absence of significant differences between the results on comfort, productivity, and behaviour, collected in the real and virtual settings, supported the criterion validity. Results highlighted the potentialities of applying VR to support a user-centred design and investigations on multi-domain comfort
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