1,720,985 research outputs found
SUSTAINABILITY INDICATORS FOR BUILDINGS: NETWORK ANALYSIS AND VISUALIZATION
Full text linkNowadays rating systems to assess the sustainability of the built environment are available worldwide. The idea that a rating system based on indicators and a sustainability score can guarantee architectural quality, reliability, energy efficiency, economic convenience and finally a sustainability label, produces an increased value of the building on the real estate market giving an "aura" of advanced product to the building itself. It is well known that different rating systems can give a different sustainability score because similar areas of evaluation in different rating systems are not equal in term of indicators' weight. Moreover, the continuous updating of the rating systems tries to include in the assessment procedures a tailored vision coming from field experience. The building rating systems were born in the last 15 years (i. e. 1998-2004), while rating systems for urban districts are more recent (2009-2012). The paper provides a survey on the more influential and worldwide diffused rating systems, highlighting the differences in terms of organization and relationship between evaluation areas and comparing existing rating schemes with recent EU research projects and initiatives such as the "Common European framework for Sustainable Building Assessment" (CESBA) framework. The paper aims to report the preliminary analysis on the similarities and differences among rating systems, towards a harmonization of sustainability practices to be applied to new and existing buildings. A network analysis and visualization tool has been applied to show the structural analogies among rating systems through an innovative methodological approach which aims to enable a further development in this field by linking more directly these tools with computational tools used in the building lifecycle
TUNING ENERGY PERFORMANCE SIMULATION ON BEHAVIOURAL VARIABILITY WITH INVERSE MODELLING: THE CASE OF SMART CAMPUS BUILDING
Full text linkIn order to establish a reliable model of occupants' interactions with indoor environment, a method accounting for stochastic factors is used. The result is no more a "single value" for the system performance, but a probability to fulfil a certain performance over time. In this way, occupant behaviour is not deterministic (e.g. the opening of windows when indoor temperature exceeds a threshold value) but coupled with a probability to perform an action.The proposed approach is built upon continuous measurements of both indoor environmental parameters and external climate conditions along with the behaviour of the building occupants (such as window opening, thermostat radiator valve, set point temperatures, occupancy sensors, etc.), performed in a sufficient number of areas and rooms representing different interaction zones in the case study. The monitoring period can range from medium (i.e. one week better if repeated in different seasons) to long-term periods (i.e. a year). The simple measurement of time series of physical quantities (such as relative humidity, temperature, pollutant concentrations, luminance, etc.) generates huge amounts of data that can be hard to "translate" directly into a behavioural model. In order to overcome these barriers, different suitable models can be defined using statistical techniques such as logistic regression and Markov chains.The various occupancy profiles are then inserted into the chosen dynamic simulation software. A monitoring and control scheme that detects users' occupancy, lighting levels, temperature, humidity, CO2 and manages HVAC system settings has been designed and installed. This system has been design to enable a faster "as-built" energy model calibration, using data from commissioning and early occupancy phases.Therefore, the actual measurement in the building will give the possibility of extracting useful information to calibrate the building energy model with a probabilistic behavioural model fitted to real metered data through inverse modelling
PREDICTION OF USERS' BEHAVIOUR PATTERNS IMPACT ON ENERGY PERFORMANCE OF A SOCIAL HOUSING IN CREMONA, ITALY
Full text linkSocial housing is a crucial challenge of European cities, facing the pressing need to provide accommodation for an increasing and changing population with new family models. Functionality, adaptability and quality of living are fundamental topics in social housing. Economic constraints concur to shape the size of apartments and construction choices in the design phase. Further, energy efficiency is a key factor for long-term economic sustainability by reducing running cost in the operation phase. The availability of calibrated energy models is fundamental to perform effective energy management during building lifespan and the ability to investigate users' behaviour by means of physical-statistical models is fundamental to improve current design and operation practices.The case study presented is a social housing located in Cremona, Italy, built by a Social Fund engaged in retrofit interventions on existing social housing and new construction. The variability of energy use, resulting from different occupancy, appliances, ventilation patterns and comfort settings has been investigated by means of simulations. Behavioural patterns are inherently dependent on age, number of components of the family, comfort preferences and activities (i.e. appliances and lighting use). Further, possible occupants' aggregations are constrained by size and flexibility of the architectural layout of residential units (e.g. number of users, change in ability due to ageing, etc.). The results are presented in a graphical way (i.e. energy demand vs outdoor temperature), enabling statistical correlation among energy demand and physical parameters assumed in different simulation scenarios, which can be used for model calibration in the operation phase (for energy management purposes). The results show the large variability of energy performance in different scenarios and the large difference with respect to standard assumptions, highlighting the benefits of parametric behavioural simulation to obtain realistic data for techno-economic assessments
Nomograph for rapid technical and economic assessment of solar thermal systems for DHW production
No full textDifferent types of tools, software and empirical methods to size and assess the performance of solar thermal systems are available today. A quick and easy-to-use graphical tool is proposed here. It is based on a single diagram, called a nomograph, which embeds technical and economic information, allowing the optimisation of the size and performance of a solar thermal system starting from the main input parameters, such as the specific costs of the system and the auxiliary fuel. The optimal surfaces are calculated as a function of the fuel cost through several regressions made on data from the application of the F-Chart method for a set of system configurations. The authors have found good correlations among these two parameters for given collectors types, climates and fuel costs
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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