Weather Files Research Articles

Os efeitos das mudanças climáticas nas condições de conforto térmico urbano

Climate change is a global reality, leading to consequences for both the natural and urban environment. These changes and their implications can be perceived in features such as ecological cycles, in the economic status of a country, or on the well-being and physical integrity of a population. Hence, this study aimed to analyse the effects of climate change on urban thermal comfort and the physiological limits of a population in a tropical city, applying the Physiological Equivalent Temperature (PET) index and correlating it to the local wet-bulb temperature. The method adopted consists of four stages: (1) assembling weather files for future scenarios; (2) setting up scenarios for computational simulations; (3) choosing the most adequate urban thermal comfort index; and (4) selecting a risk parameter to evaluate human health risk. The results show that the presumed urban temperatures, considering 2050 and 2080 scenarios as parameters, can cause serious damage to inhabitants’ health, given the frequency of high temperatures recorded in some months of the year. Accordingly, it is clear that there is a need for balance between the temperature variables and relative air humidity is required, striving for better comfort conditions, as well as improving users' permanence in external environments.

THE IDEALIZED AND THE REALISTIC VALIDATION STUDIES OF BUILDING SIMULATION MODELS IN GHANA

ABSTRACT The research is based on the premise that in order for a building energy model to contribute to a sustainable energy future, the model’s accuracy must be ensured in order for the model’s results to be trusted. Therefore, validation processes in continuing Ghanaian building performance studies are outlined. The process started with long-term monitoring of low-rise, multi-storey and test cells structures. Combined with weather data from meteorological offices, reliance on synthetic weather files and local measurements, appropriate matching periods of weather data and measurements were used to simulate indoor parameters. Further, the simulated and measured data were in good agreement in terms of regression values (r2of 0.53–0.96). Energy use bills were used to validate energy loads of a multi-story building which resulted in a difference of 0.09% between the simulated and billed data. Furthermore, an approach of using the Coefficient of Variance for Root Mean Square Error (CV (RMSE)) was also presented. Considering the range of the regression values which could be due to the difficulty in the validating process; one can confidently rely on the outcome to predict building performance. Sampled challenges are the potential of synthetic weather files to overlook microclimatic conditions such as urban heat island effects; difficulty in predicting internal loads as comprehensive monitoring devices are lacking, e.g., occupancy sensors to monitor the actual number of people present at a time and their behaviour within spaces; system performance values which are known to decline with time, therefore, affecting measured versus simulated values; most firms not keeping energy bills and their unwillingness to provide the information to researchers; etc. The validated models can be used as scientific-based data and analysis to inform building designers decisions to reduce the economic and environmental burden in Ghana.

Data-driven, long-term prediction of building performance under climate change: Building energy demand and BIPV energy generation analysis across Turkey

This research presents a methodological framework for lifetime energy demand and PV energy generation predictions for a given building considering the CC impacts through multivariate regression models. As a case study, a hypothetical office building in Turkey was selected. An existing linear morphing methodology was utilized to generate future weather files for all 81 cities in Turkey. For each year and city, corresponding weather metrics were calculated, and heating/cooling demand and PV energy generation values were computed through building energy simulations. Obtained data were used to develop two sets of multivariate regression models: (i) models to predict future weather metrics and (ii) models to predict future energy demand and generation. These models allowed lifetime energy demand and generation analysis (including associated GWP and cost) of the building considering CC impacts using only the current weather metrics of its location. For a lifetime of 60 years, considering CC impacts yielded substantially higher cooling (averaging at +0.5 MWh/m2 in the warmest region) and lower heating loads (averaging at −0.4 MWh/m2 in the coldest region). For Turkey, the carbon intensity and the unit cost of cooling are much higher than those of heating. Therefore, the shift from heating to cooling has significant consequences in lifetime GWP and cost values (averaging +212 kg CO2-eq/m2 and +27 $/m2, respectively, for the warmest region), emphasizing the importance of the decarbonization of the energy sector. The impact of CC on PV energy generation was limited (all-city average of +0.02 MWh/m2 for the building lifetime). Our regression-based approach can be further expanded to include not only various building parameters and types, but also supply-demand matching potentials.

Creation and application of future typical weather files in the evaluation of indoor overheating in free-floating buildings

Expected Global warming and heatwaves coupled with the urban heat island effect (UHI) can overheat indoor environments of free-floating buildings in temperate climate regions. Overheating assessment requires practitioners to use appropriate climate data and suitable measurement indices. The aim of this article is first, to propose a practical approach to generate yearly and typical ready-to-use future typical weather datasets (FTWY) using high-resolution Regional Climate Model (RCM) data from Coordinated Regional Climate Downscaling Experiment (CORDEX), and second, investigate the potential of FTWYs in the assessment of indoor overheating, considering UHI effect.To achieve these objectives, three dynamically downscaled (DDS) FTWYs generated from RCMs (IPSL-SMHI, CNRM-ALADIN, MPI-REMO) were compared with one statistically downscaled (ESD) FTWY from Meteonorm, and observed heatwave weather data of 2003. Comparative analysis was performed in two stages: comparison of monthly statistical distribution of climate variables, and analysis of heatwave presence. Urban weather generator (UWG) was used to project UHI effect on two weather files for two buildings, and three overheating measurement indices were used to exploit results. Comparative analysis of weather files show that temperature in a FTWY in the medium future (2040–2070) is likely not as intense as the heatwave of 2003 for Nantes. Results also confirm that it is better to use two weather files, and at least two overheating indices to obtain reliable outputs. This study also revealed that indoor overheating is not limited to densely built areas where impact of UHI is highest; buildings located in sparsely built neighbourhoods are also at risk.

Impact of climate change on Helicoverpa armigera voltinism in different Agro-Climatic Zones of India

The Gram pod borer, Helicoverpa armigera (Noctuidae: Lepidoptera) is a cosmopolitan agricultural insect pest that prefers to feed on plant’s protein biomolecules. Out of different density-independent factors, surface air temperature majorly affects the incidence and damage of the H. armigera on the crops. Early prediction of H. armigera generations (voltinism) in future climate years perhaps prevent additional damage in various crops and improve the farmers preparedness. In this study, future climate data that is temperature obtained for eleven Agro-Climatic Zones (ACZs) of India under four Representative Concentration Pathways (RCPs) scenarios in different climate years (2010, 2030, 2050, 2070, 2090) using weather file generator MarkSim web application. The accumulation of Growing Degree-days (GDD) by H. armigera at eleven ACZs in each climate year under different RCP scenarios was estimated using temperature data. The mean surface air temperature is predicted to 0.51 °C, 1.03 °C, 1.57 °C and 2.1 °C in climate years 2030, 2050, 2070 and 2090, which escalated annual H. armigera Gen. to 12.88, 13.33, 13.79 and 14.23, respectively over the baseline climate year 2010. Likewise, under RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 scenarios H. armigera Gen. is predicted to 12.86, 13.29, 13.23 and 13.97 per annum with mean surface air temperatures 27.4 °C, 27.92 °C, 27.86 °C and 28.72 °C, respectively. The Eastern Coastal Plains and Hills Zone (ACZ 11) across climate years and RCPs has experienced a considerable increase in mean surface air temperature minimum (25.22 °C) and maximum (34.61 °C), which likely favor the GDD accumulation (6319.91) and the Genrations (14.97) in H. armigera. Therefore, the Eastern Coastal Plains and Hills Zone of India could be identified as H. armigera risk zone in near future. The present predictions in various ACZs of India may be significant in planning H. armigera management.

Projected climate data for building design: barriers to use

Building professionals’ use of historical weather data in performance analysis and design is an insufficient response to the impacts of a changing climate. Existing standards, laws and conventions in the US (and elsewhere) reinforce the use of typical weather files derived from historical data. Although projected climate data are readily available from reliable sources, significant barriers prevent adoption. These include a lack of consensus on the <em>methodology</em> for creating climate data for buildings based on climate models; a lack of a publicly available <em>platform</em> for providing climate projections for use in a <em>format</em> suitable for building analysis; a lack of consensus on a <em>standardized framework</em> for communicating results of simulation with long-term climate data projections; andliability concerns with using projection data. A coordinated response to these challenges is necessary across building design disciplines to ensure widespread adoption. Professional institutions, codes and standards organizations, and national governments have a key role to ensure that buildings created today are fit for climatic conditions in 20, 50, and 100 years’ time. <em><strong>Policy relevance</strong></em> Codes and standards for buildings and infrastructure need rethinking to account for adaptation to climate change, including the protection of real estate investments. Concerted action from professional and standards-setting bodies is required to standardize and make available projected climate data that can be used for building design and analysis. The use of these data and resultant analyses must be standardized in an industry-wide, sanctioned framework to address concerns around liability, misuse and transparency.

An urban thermal tool chain to simulate summer thermal comfort in passive urban buildings

This paper presents a simulation tool chain for the prediction of thermal comfort in passive urban buildings during summer and under heat wave conditions. The tool chain encompasses EnergyPlus building energy model and the Urban Weather Generator and UrbaWind tools to consider the impacts of the urban environment on building loads. This chain of tools is computationally efficient and does not require notable expertise for the simulations. To assess its accuracy, this simulation results are compared to in situ measurements. This paper describes the measurement setup, analyzes the measurement results and reveals a satisfactory model accuracy through a comparison to the measurement data. The average nighttime urban heat island between July and September 2020 reached 2.31 °C in the city of Lyon. Not considering the urban heat island effect (employing rural weather files) in urban thermal simulations could induce a 1 °C bias in indoor air temperature predictions. This could also result in overpredicting the cooling potential of natural ventilation during summer. Key parameters of the simulation accuracy are identified. These are the action schedule of occupants in regard to opening devices (shutters, windows and doors) and the urban boundary layer height at night.

Integrating courtyard microclimate in building performance to mitigate extreme urban heat impacts

• Specific urban microclimates are not considered by building energy simulation tools. • Numerical modelling with multi-nodal outdoor conditions is developed. • The aim is to quantify the benefits of specific microclimates in building performance. • A reference case with a courtyard microclimate was measured, simulated and validated. • Courtyard microclimate mitigates the impact of extreme urban heat in buildings. Extreme heat events are expected to occur more often as a consequence of climate change. This paper quantifies the impact of urban climate on building performance and evaluates the benefits of specific microclimates, such as inner courtyards, to mitigate extreme heat impacts. A reference case study associated with two outdoor weather conditions, an inner courtyard and a local urban climate, was measured, simulated and validated in TRNSYS. The validated model was then compared to three building models with a single outdoor weather condition associated with the urban climate, weather data from a rural station and a typical year weather file. The models were evaluated in free-running conditions and with air-conditioning systems. The results show how urban climate can increase indoor discomfort hours by 32% in free-running conditions and demonstrate that courtyard microclimate can almost completely mitigate the impact of urban overheating in buildings, eliminating severe indoor discomfort hours by more than 88%. Moreover, the increase in cooling energy demand due to urban climate was reduced by more than 15% in the case of having air-conditioning systems. The findings manifest the importance of accurate weather data for building simulation and demonstrate how multi-nodal outdoor conditions can enable additional strategies to mitigate climate risks, highlighting urban microclimates as a promising strategy to tackle extreme heat events in buildings and cities.

Analyzing the climate-driven energy demand and carbon emission for a prototype residential nZEB in central Sweden

The changes in climate and the expected extreme climate conditions in the future, given the long life span of the buildings have pushed the design limits. In this study, the changes in primary energy use (PEPET), total energy use and CO2 emission were investigated for a prototype residential building. The building fulfils nearly zero energy building (NZEB) characteristics, imposed by the Swedish building regulations. Different cooling technologies and various typical meteorological year (TMY) climate files assembled for different periods, as well as automatic shading were investigated. The assembled TMY files advocated for the present (2001–2020) and mid-future (2041–2060) period using the CORDEX data. Different cooling methods and set-points (24–28 °C) were defined to evaluate the cooling energy demand changes.It was discovered that the freely available typical climate file fails to cover the induced changes in climate and its extreme implications on the building. The required cooling energy use increased from 1.7 to 5.8 times the freely available climate file, when using the projected TMY and the extreme climate files.Addition of automatic shading system reduced cooling energy up to 75% within the studied cooling methods and set-points. Moreover PEPET and CO2 emission also decreased for the studied cooling methods, climate and weather files.

The effect of increasing surface cover vegetation on urban microclimate and energy demand for building heating and cooling

The study examines the potential effects of adding vegetation to an urban neighborhood in Tel Aviv on the microclimate, and subsequently on the potential for cooling by night ventilation and on energy consumption for heating and air conditioning. Computer simulation was employed to first generate modified weather files that account for urban effects of location, surface cover and density in different building configurations. These files were then used to assess the climatic cooling potential (CCP) by night ventilation and as inputs for detailed computer simulation of building energy performance. The microclimate model simulation indicates that elevated urban night-time temperatures will increase summer cooling loads relative to the reference rural site, but this penalty will be more than offset by reduced winter heating loads, resulting in a net decrease of between 2 and 7% in electricity use for heating and cooling (depending on building characteristics). The main impact of the urban heat island in this case is the reduction in the potential for cooling by night ventilation, which is almost completely absent in the summer months. Consequently, the urban climate of Tel Aviv may increase the prevalence of air conditioning use and will make buildings more vulnerable to potential loss of electric power in case of shortages or blackouts during episodes of extreme heat. Implementing a strategy of extensive planting, so that a green surface fraction of 0.5 is obtained, results in a mean annual temperature reduction of about 0.3 °C and an energy saving relative to the current condition of about 2–3%.

Multistage Optimization toward a Nearly Net Zero Energy Building Due to Climate Change

Climate change is one of the major problems of the planet. The atmosphere is overloaded with carbon dioxide caused by fossil fuels that are burned for energy. Almost 40 percent of the total energy worldwide is used by the building sector, which comes from non-renewable sources and contributes up to 30% of annual greenhouse gas emissions globally. The building sector in Iran accounts for 33.8% of Iran’s total energy usage. Within the building sector, the energy consumption of Iranian educational buildings is 2.5 times higher than educational buildings in developed countries. One of the most effective ways of reducing global energy consumption and greenhouse gas emissions is retrofitting existing buildings. This study aims to investigate whether a particular energy-optimized design under the present climate conditions would respond effectively to future climate change. This can help designers make a better decision on an optimal model, which can remain optimal over the years based on climate change. For methodological purposes, multistage optimization was used to retrofit an existing educational building. Specifically, the non-dominated sorting genetic algorithm (NSGA-II) was chosen to minimize the cooling and heating load, as well as consider investment costs for present and future weather files, using the jEPlus tool. Furthermore, the TOPSIS method was used to identify the best set of retrofit measures. For this purpose, a four-story educational building in Tehran was modeled on Design Builder software v7.0.0.116 as a case study to provide a better understanding for researchers of how to effectively retrofit a building to achieve a nearly zero energy building considering climate change. The results show that the optimized solution for the present weather file does not remain the optimized solution in 2080. Moreover, it is shown that to have an optimized building in regard to future weather files, the model should be designed for the future weather conditions. This study shows that if the building becomes optimized using the present weather file the total energy consumption will be reduced by 65.14% and 86.18% if using the future weather file. These two figures are obtained by implementing active and passive measures and show the priority of using the future weather file for designers. Using PV panels also, this building is capable of becoming a nearly net zero building, which would produce about 90% of its own energy demands.

Effect of Climate Change and Occupant Behaviour on the Environmental Impact of the Heating and Cooling Systems of a Real Apartment. A Parametric Study through Life Cycle Assessment

Climate change has a strong influence on the energy consumption of buildings, affecting both the heating and cooling demand in the actual and future scenario. In this paper, a life cycle assessment (LCA) was performed to evaluate the influence of both the occupant behaviour and the climate change on the environmental impact of the heating and cooling systems of an apartment located in southern Italy. The analysis was conducted using IPCC GWP and ReCiPe indicators as well as the Ecoinvent database. The influence of occupant behaviour was included in the analysis considering different usage profiles during the operational phase, while the effect of climate change was considered by varying the weather file every thirty years. The adoption of the real usage profiles showed that the impact of the systems was highly influenced by the occupant behaviour. In particular, the environmental impact of the heating system appeared more influenced by the operation hours, while that of the cooling system was more affected by the natural ventilation schedules. Furthermore, the influence of climate change demonstrated that more attention has to be dedicated to the cooling demand that in the future years will play an ever-greater role in the energy consumption of buildings.

Dynamic modeling of future climatic and technological trends on life cycle global warming impacts and occupant satisfaction in US office buildings

Dynamic modeling of building performance is essential for understanding how current buildings will respond to projected changes in environmental conditions, and how these responses will in turn affect building occupants. Additionally, expected shifts in background energy systems will change the carbon intensity of energy delivered to buildings, while shifts in atmospheric composition will alter the global warming potential of each greenhouse gas. This paper models these three dynamic systems simultaneously to determine which projected shifts will have the largest influence on global warming impacts and occupant satisfaction metrics throughout the use phase of an office building prototype model in different climate zones of the United States. The median of RCP8.5 and RCP4.5 climate scenarios were used to morph local weather files to simulate the electricity and natural gas needed to meet heating and cooling loads in each location, as well as thermal comfort and daylighting metrics. These RCPs were also used to estimate shifts in the global warming potential factors for CO2, CH4, and N2O. Projected shifts in the electricity generation mix and upgrades to transmissions and distribution infrastructure in each region were used to estimate future carbon intensity factors for building site energy use. Compared to the baseline results, decarbonization of the electricity grid results in the largest shift in building operational GHG emissions, far outweighing emissions increases due to higher cooling loads. Shifts in ambient temperatures and direct and diffuse radiation had heterogeneous effects on occupant comfort, particularly in Boston across different seasons and orientations. Understanding how building performance is expected to respond to complex future trends will assist in designing adaptive buildings that take advantage of projected changes.

Modeling outdoor thermal comfort along cycling routes at varying levels of physical accuracy to predict bike ridership in Cambridge, MA

The Universal Thermal Climate Index (UTCI) has been linked to outdoor activity patterns and used to evaluate the effectiveness of urban interventions to improve thermal comfort. This study investigates how simulating the urban environment at increasing levels of physical accuracy impacts UTCI values along three cycling routes in Cambridge, Massachusetts. Baseline UTCI values are estimated using a local weather file, and the following increments in physical accuracy are considered: wind-scaling, shading from buildings, shading and cooling from trees, computational fluid dynamics simulations for wind speeds, and simulated surface temperatures. With bike ridership data from Bluebikes, Boston's bike-sharing program, the relationship between bike ridership patterns and UTCI values along each route is studied. Supervised machine learning models are applied to predict bike ridership based on UTCI and other predictors.UTCI simulation results show that incorporating the various increments of accuracy influences hourly UTCI values at urban areas and exposed areas differently. Incorporating local wind speeds is especially impactful for urban areas. The statistical models trained to predict hourly bike trip counts based on UTCI and other demand and weather predictors achieved a root-mean-squared error of 1.06 trips. 47% of predictions were correct, and an additional 42% of predictions were off by 1 trip.This study demonstrates the importance of spatial refinement in simulating UTCI, and motivates future research into efficient simulation methods or rules-of-thumb for deriving spatial-temporal UTCI values. Future work into building a robust predictive model would motivate the design of thermally comfortable environments for human-powered transportation in cities.

Heat exposure during a power outage: A simulation study of residences across the metro Phoenix area

In the wake of growing concern for climate change, heat waves and their potential health effects (McGeehin and Mirabelli, 2001) [37] have become a recurring phenomenon (Beniston, 2004; Fouillet et al., 2006) [8,21]. Extreme heat events in the USA are responsible for more deaths as compared to other weather events such as hurricanes, lightning, tornadoes and floods (Luber and McGeehin, 2008) [33]. Heat exposure in buildings has risen due to global warming in conjunction with other factors like urbanization and associated heat island effects (Kolokotroni et al., 2012) [25], lack of thermal mass (Lomas and Porritt, 2017a) [31], exposure to solar insolation on higher stories, absence of window shading, overcrowding and envelope properties exacerbate the overheating inside the dwellings (Vellei et al., 2017). [45]. Stone et al. (2021) [43] provides a macro view of the indoor environments in buildings due to the concurrent event of power outage during heat wave in face of climate change. This paper builds on the previous publication and provides a detailed view of modeling methodology, building physics that explains the sources/sinks of heat and entails a detailed evaluation of the current building stock for the low to moderate income residences in the city of Phoenix, Arizona in terms of their thermal performance. Finite Element models of building stock were simulated using MATLAB for microclimate weather files of Phoenix generated by Weather Research and Forecasting (WRF) simulation. Significant differences in temperature were noted in same building archetypes in different pockets of the city indicating the role of urbanization in aggravating the impact of heat wave. Dwellings with high thermal mass are found to be much more resilient to high ambient temperatures as compared to code compliant residences with basements being the coolest zones in all prototypes.

Selecting extreme weather file to assess overheating in residential building

Climate change is great challenge for current and newly built buildings. Nowadays, TMY weather file can be easily generated following the IPCC scenarios. Nevertheless, since these data are extrapolated with stochastic model from monthly mean values, they do not show a real pattern and do not include extreme events like heatwaves. In order to get more representative data, we propose in this work a methodology to select real measured files from a large database in light of heatwaves and climate change. This methodology is applied to the city of Lyon, for which 26 years of weather data are available. Three measured weather files projected for the time periods 2020, 2050 and 2080 are selected. These files are used in building thermal simulation of residential building with low or high thermal inertia. Summer overheating is analysed through two different comfort indicators: adaptative comfort and Givoni chart. Results indicates that summer overheating risk is obviously increased with future weather files. When compared to usual TMY files, this risk is also enhanced by using weather file including extreme events like heatwaves. Last, we note that discomfort is mainly encountered during this extreme events.

Weather and indoor climate in Greenland

To make a hygrothermal assessment of a building construction, e.g. wall or roof, weather files as well as information on indoor moisture load are needed, however only to some extent available for Greenlandic conditions. This paper describes a project that had a twofold aim: 1) create weather files for four different cities in Greenland in a simple way, 2) determine the typical moisture load in a Greenlandic dwelling to see if the international standard ISO 13788 is applicable in Greenland when describing indoor moisture load. The four chosen cities are placed at the west coast of Greenland. Hourly weather data of 10 years for the four cities were obtained from the meteorological institutes of Denmark and Greenland, from this a reference year with hourly values was created for each city. The paper also describes how incomplete data was treated. Five dwellings were chosen in each city to assess the indoor moisture load. Temperature and relative humidity were measured hourly in living rooms of these dwellings. Furthermore, outdoor temperature and relative humidity were measured in the four cities. The moisture load in the dwellings were scattered in humidity class 1-4, similar to what has been measured in Danish dwellings, consequently ISO 13788 may be applicable in Greenland.

Evaluation of Multiyear Weather Data Effects on Hygrothermal Building Energy Simulations Using WUFI Plus

Transient building energy simulations are powerful design tools that are used for the estimation of HVAC demands and internal hygrothermal conditions of buildings. These calculations are commonly performed using a (often dated) typical meteorological year, generated from past weather measurements excluding extreme weather conditions. In this paper the results of multiyear building simulations performed considering coupled Heat and Moisture Transfer (HMT) in building materials are presented. A simple building is simulated in the city of Udine (Italy) using a weather record of 25 years. Performing a multiyear simulation allows to obtain a distribution of results instead of a single number for each variable. The small therm climate change is shown to influence thermal demands and internal conditions with multiyear effects. From this results it is possible to conclude that weather records used as weather files have to be periodically updated and that moisture transfer is relevant in energy and comfort calculations. Moreover, the simulations are performed using the software WUFI Plus and it is shown that using a thermal model for the building envelope could be a non negligible simplification for the comfort related calculations.

Computational Approach in Investigating Surface and Site Radiation in the Early Phase of Designing Two-Story Wooden House in Orio District, Kitakyushu, Japan

ABSTRACT Along with the rise of awareness in implementing the environmentally conscious urban design, the classical process in approaching urban environmental analysis should be shifted to the performance-based considerations. In architecture and urban design, the tools developed recently holds promise to assist the decision-making process in the early phase of designing. Thus, the further performance of the intended architecture project, particularly related to energy consumption and its environmental impact, can be nearly accurately predicted. Although many studies contain the computer design process for analyzing urban energy performance, the Multi-Objective Optimization (MOO) process in the sub-tropical climate of Japan has not been widely used. This research investigates hypothetically the surface and site radiation in the early phase of designing a two-level wooden house in Orio District, Kitakyushu, Japan, through parametric and generative algorithm. The research designed to map the best possible design solution of free-form loft-twisted structure through iterating design variables related to design elements such as building orientation, base radius, twisting and scaling factor and the angle of the roof slope. The optimization targeting the minimum quantity of solar radiation both for the site and the building surface affected by the geometry. The simulation uses an EPW file of Shimonoseki as the input weather file and being scheduled for fitting the period in the extreme hot week during the summertime. The findings are successful to produce a design with better performance compared to the benchmark model even though with insignificant improvement.

Multiyear hygrothermal performance simulation of historic building envelopes

The objective of this work is to quantify the effects of the short-term climate change with a multiyear (MY) approach on the results of the heat and moisture transfer simulations of an historic building located in Udine (Italy) and to evaluate if a single year simulation could be representative of the results obtained with the MY. The hygrothermal performance and the moisture related risk are evaluated for a brick wall with and without insulation, with a MY of 25 years and with three single years selected form the MY. The software DELPHIN is used for the simulations and the damage indicators are calculated using simplified methods (number of days with unfavourable conditions). Depending on the damage considered, the years have different effects on the studied wall. The simulations that use the MY weather file allow to obtain more accurate results than using one-year simulations, but the effort and time required for the interpretation of the simulation results could be not acceptable. It is then shown that the choice of a representative weather file is crucial to the results of the risk analysis and that considering more than one weather file is necessary to obtain representative results for different damages mechanisms.