Search

Supplemental Material, sj-pdf-1-lrt-10.1177_14771535211046521 for Lighting conditions in physiotherapy centres: A comparative field study by L Zaniboni, M Sarey Khanie, G Pernigotto, J Toftum, A Gasparella and BW Olesen in Lighting Research & Technology

All research studies based either on analytical and numerical simulations or on testing facilities under controlled or monitored external conditions require some simplifications with respect to the real physical phenomena. The simplification level has to be accurately defined since it introduces some boundaries to the achievable results and to the possibility to generalize the research findings. In particular, this last aspect is very important: once the model complexity is chosen, the desired number of cases can be determined. As a rule, the more complex a model, the larger the sample required to get statistically significant results. In building simulations, we can distinguish two kinds of analyses: the studies aimed to analyze the building performance (e.g., the kind of glazing with the best energy performance in a certain climate, the optimum insulation thickness, the most convenient refurbishment approach) and those focused on building modelling, methods and assumptions (e.g., weather inputs, solar radiation and sky luminance models or algorithms for the calculation of heat transfer through the opaque envelope). As concerns the first group, when the focus is on existing buildings, the sample has to be representative of the building stock possible variability – especially when reference buildings are not available or their characteristics are not completely suitable for inferential statistics. For new building solutions or technologies, instead, proper samples are needed for their evaluation. In the second case, as well, proper building configurations have to be determined and they strongly depend on the researchers’ aims: for instance, the set for the assessment of energy balance models can be different from those for the evaluation of thermal-hygrometric or visual comfort models. In this work, we propose a method to manage the complexity of variables involved in building simulation studies and to identify groups of simplified building models – “shoe-box building models” – or domains of relevant variables suitable to have statistically significant results. The method is applied as an example to the definition of an appropriate set of configurations for the comparison of TRNSYS and EnergyPlus and to the analysis of the discrepancies of six output quantities, i.e., monthly energy needs, hourly peak loads and time of occurrences of hourly peak loads – both heating and cooling. A set of candidate variables describing the building envelope characteristics are studied for each comparison and those more significant are selected for further analyses by means of statistical screening methods (specifically, Spearman’s rank correlation coefficient). Six different short lists of significant buildings variables are then defined for detailed and extensive statistical studies with a full factorial analysis (or equivalent approaches): while in the preliminary study attention is paid in particular to the main effects with a monthly time-discretization of the outputs, the detailed analyses aim at investigating the interactions between the different variables, with shorter time-discretization and focus on the most interesting quantities with respect to the research targets.

The interest in energy refurbishment has grown up in the last few years, since noticeable energy savings can be achieved through energy saving measures (ESM) applied to the existing building stock. In this respect, one of the best opportunities to promote the energy renovation of the existing building is to define cost-effective solutions. The recast of the European energy performance of building directive (EPBD-recast) and the Commission Delegated Regulation EU 244/2012 underline the necessity to define “energy performance level which leads to the lowest cost during the estimated economic life-cycle” of a building. The choice of the optimal solution addresses the problem of optimizing two or more conflicting goals such as the net present value (NPV) and the achievable energy performance. For this reason multi-objective optimizations are often applied to building energy simulation. However, the higher capabilities in calculating detailed outputs imply more complex and detailed inputs. In this regard, the representativeness of weather inputs is crucial to ensure the reliability of energy simulation results. In fact, the length of the multi-year weather data series and the methodology used for the typical month selection largely influence the results of the reference year development process. Although this topic has been widely discussed in the literature, little is yet known about the robustness of the optimal solutions obtained from multi-objective optimization analysis to the variation of the quality of the weather data used. This information could also be relevant to understand if the optimal solution obtained with historical weather data could be undermined by future climate changes. Aiming to provide objective confidence levels of the multi-objective optimization analyses, in this work we investigate the extent to which the weather data used for building energy simulations can affect the optimal solutions. With this purpose, several MOO are carried out both with multi-years energy simulations and with the test reference years. In particular, the adopted test reference year was developed according to EN ISO 15927-4:2005 starting from the hourly weather data collected in the meteorological station of Trento, in northern Italy. Different lengths of data series were adopted in order to model the different levels of data availability. Furthermore, semi-detached houses penthouses and intermediate flat in multi-story buildings are analyzed with the purpose of broaden the representativeness of the conclusions.

The pursuit of better energy performance of buildings led o the recourse to more detailed instruments of analysis, requiring more complex and detailed inputs, such as the hourly weather data. In this work, the representativeness of the test reference year (TRYEN) weather data, recently developed in Italy in accordance with the procedure proposed by EN ISO 15927-4:2005, has been studied evaluating the energy performance – energy needs and peak loads – of a set of different simplified reference buildings by means of TRNSYS simulation code, using both the TRYEN and the TRYEN source multi-year collected weather series for 5 north Italian locations. The results have been analysed by means of both descriptive and inferential statistics. The variability of energy performance has also been correlated with the envelope characteristics, in order to estimate a sensitivity of the different buildings to the weather data variability.

The aim of this work is the energy efficiency assessment of micro cogeneration systems (MCHP) based on biomass gasification for residential application, using a multistage modeling approach. Particular attention has been paid to the optimization of the component assembly, focusing on configurations that allows all the devices operating in their optimal configuration. The gasification stage has been then modeled through an enhanced (i.e., gas¬solid) thermodynamic approach using the CANTERA solver and the Gri¬Mech thermodynamic properties. Several values of temperature and amount of gasifying agent have been taken into account for the simulations. The efficiency of the whole MCHP system has been evaluated supplementing the simulation of the gasification stage with the energy balance of the cogeneration set (i.e., internal combustion engine) and implementing the developed routines in the Matlab¬Simulink environment. In the simulations, the plant is supposed to supply thermal energy to a building considering different scenarios. Dynamic simulation through EnergyPlus software have been performed. The building¬system interactions under different operating and boundary conditions have been assessed. The paper shows the optimal operating conditions and the system size range for residential applications. The gasification¬based micro CHP technology has an high potential and also substantial room for improvement., Proceedings of the 20th European Biomass Conference and Exhibition, 18-22 June 2012, Milan, Italy, pp. 1058-1064

In G. Pernigotto, F. Patuzzi, A. Prada, V. Corrado, & A. Gasparella (Eds.), Building Simulation Applications BSA 2019 (pp. 59���66).

Timber buildings are characterized by a thermal inertia lower than other technological solutions in construction. For this reason, some configurations may lead to higher cooling demand and poorer energy performance in hot climates, such as the Mediterranean ones. Possible improvement interventions often regard additional thermal mass but, if not accurately designed, they can worse significantly structural and seismic perfo rmance of timber buildings - which is of primary importance in many Italian regions. In this framework, the TimBEESt project studied some technological solutions for timber buildings in Light Timber Frame and Cross-Laminated Timber, able to improve the dynamic behaviour of the opaque components without worsening their seismic performance. First, the Italian territory was analysed in order to find classes of climate and seismic solicitations and energy and structural performances of reference LTF and CLT building models were simulated. Then, for each Italian province, specific interventions and improvements were defined and evaluated.

Due to the complexity of the acoustic field in articulated closed spaces, architectural acoustics is often approached as a reverse-engineering problem: criteria, reference values and analysis methods are extrapolated by comparing results from measurements in a set of case studies. Considering the methods and the results of previous works on Italian historical theatres, the present study shows the results of geometrical acoustic (GA) numerical simulations with the aim to attempt a ranking based on the subjective preference theory. The models were calibrated using several room criteria that had been previously measured in the framework of a measurement campaign performed in Italian theatres. The cluster chosen is intended to represent an adequate sample of case studies relative to different capacities and different design approaches, which were first developed in the seventeenth century.