Abstract available via the hyperlink above

Abstract: The present work evaluates the performance of different decentralized ventilation control strategies in the local Norway climate. Evaluation is performed using a monthly time-step energy analysis and the IDA-ICE simulation tool for a comparative primary energy analysis on the strategy combinations. Primary energy comparison is conducted with respect to a centralized constant air volume system for comparative analysis. The evaluation results show that the representative decentralized ventilation (DV) system has the most significant energy performance. The lower heat recovery efficiency significantly impacts on the ventilation energy of DV system in the cold climate, and the low specific fan power can efficiently be used for zone cooling in summer.
Permalink: https://doi.org/10.1051/e3sconf/202236211005

Abstract: The main objective of this work is to investigate the energy and exergy performance of a solar assisted ground source heat pump for a school building designed according to Norwegian passive house standard. The system is designed in such a way that the solar collector prioritizes to provide heat to the hot water tank and whenever there is excess heat from the solar collector it can be used to charge the ground borehole. A detailed thermodynamic analysis of the system has been carried out in Engineering Equation Solver (EES). Isobutane (R600a), propane (R290), ammonia (R717) and solstice (R1234ze(E)) have been investigated as working fluid for the heat pump. The result revealed that the solar collector and the different working media have affected both the COP and the exergy of the system. Moreover, the mass flow rate of the brine and the length of the borehole affect the performance of the system.
Permalink: https://doi.org/10.1051/e3sconf/202236202002

Abstract: Climate change is expected to significantly affect the interior climate of old, leaky buildings without HVAC systems. As a result, the items of cultural significance that are hosted indoors will experience new ambient conditions, which will affect their degradation. In the current research, the impact of climate change on the biological, mechanical, and chemical degradation of a cabinet and a storage trunk which are made of wood and have paintings on their outer surface is investigated. These two items are found in two different rooms of a historic timber building in Vestfold, Norway. Data from the REMO2015 driven by the global model MPI-ESM-LR are used in order to account for past, present, and future climate conditions. In addition, climate data from ERA5 reanalysis are used in order to assess the accuracy of the MPI-ES-LR_REMO2015 model results. Whole building hygrothermal simulations are employed to calculate the temperature and the relative humidity inside the rooms that host the items of interest. The transient hygrothermal condition and certain characteristics of the timber surfaces are used as inputs in models that describe their degradation. The biological degradation is examined by using i) the updated VTT mould model and ii) the Growing Degree Days (GDD) for temperature and humidity dependant insects. The mechanical deterioration is assessed by the method proposed by Mecklenburg et al. (1998). The concept of the Lifetime Multiplier (LM) is used in order to assess the chemical deterioration of the furniture. Results reveal a significant mechanical degradation risk and a very high chemical deterioration risk. The biodeterioration risk remains at acceptable levels. Moreover, it could be possible that the storage trunk would be damaged by certain insects in the future. It is then suggested that both items should be moved to a room with proper conditions in order to minimize their chemical and mechanical deterioration risk and extend their life span. Finally, the significance of implementing bias correction in the data from climate models is underlined.
Permalink: https://doi.org/10.1051/e3sconf/202236211003

Abstract: Numerous buildings fall short of expectations regarding occupant satisfaction, sustainability, or energy efficiency. In this paper, the performance of buildings in terms of occupant comfort is evaluated using a probabilistic model based on Bayesian networks (BNs). The BN model is founded on an in-depth anal- ysis of satisfaction survey responses and a thorough study of building performance parameters. This study also presents a user-friendly visualization compatible with BIM to simplify data collecting in two case studies from Norway with data from 2019 to 2022. This paper proposes a novel Digital Twin approach for incorporating building information modeling (BIM) with real-time sensor data, occupants’ feedback, a probabilistic model of occupants’ comfort, and HVAC faults detection and prediction that may affect occupants’ comfort. New methods for using BIM as a visualization platform, as well as a pre- dictive maintenance method to detect and anticipate problems in the HVAC system, are also presented. These methods will help decision-makers improve the occupants’ comfort conditions in buildings. However, due to the intricate interaction between numerous equipment and the absence of data integra- tion among FM systems, CMMS, BMS, and BIM data are integrated in this paper into a framework utilizing ontology graphs to generalize the Digital Twin framework so it can be applied to many buildings. The results of this study can aid decision-makers in the facility management sector by offering insight into the aspects that influence occupant comfort, speeding up the process of identifying equipment malfunc- tions, and pointing toward possible solutions.
Permalink: https://doi.org/10.1016/j.enbuild.2022.112732

Abstract: The Passive House building concept has been widely researched concerning its performance, especially aspects like energy consumption and thermal properties. Nevertheless, the design stages still do not present a dynamic thermal comfort predictive process that aids in investigating the design performance. This study focuses on a methodology that calculates summer months peak conditions in a pilot Passive House dwelling in the United Kingdom, based on the natural ventilation plan’s effectiveness in maintaining sufficient airflows. The methodology involves EnergyPlus dynamic simulations, ANSYS computational fluid dynamics simulations, and the Centre for the Built Environment Thermal Comfort Tool. The results showed a spectrum of predicted percentages of people dissatisfied ranging between 13.3−99.2% for different airspeeds, where the majority were of uncomfortable levels. Results also present ranges of thermal comfort parameters individually. The findings may add a comprehensive description to the thermal comfort status during design stages by employing the integrated software combination.
Permalink: https://doi.org/10.13044/j.sdewes.d10.0419

Abstract: This study conducted an experimental analysis of how indoor air quality (IAQ) is influenced by the outdoor air pollutants levels, infiltration rate, and occupants’ behaviours. The impacts of these factors on IAQ were analyzed using onsite measurements and numerical simulations. The results contribute to a better understanding of how to control the Indoor Particulate Level (IPL) for the specific conditions of the studied building. Results showed that occupant behaviour was the primary factor in determining the IPL, significantly changing the number of outdoor particles introduced to the building. Moreover, it was found that the IPL was exponentially correlated to the Outdoor Particulate Level (OPL). Based on numerical simulations, this study concluded that smaller particles do not always have more chance than larger particles of accessing the indoor environment through the building envelope. Meanwhile, a steady-state indoor particle concentration numerical model was established and verified using the 4-fold crossvalidation method. Finally, simulation results identified that the room infiltration rate had a positive linear impact on IAQ if the OPL was under 30 μg/m3 . This is because the increased air exchange rate can help to dilute indoor air pollutants when the outdoor air is relatively clean.
Permalink: https://doi.org/10.1016/j.scitotenv.2022.158026

Abstract: For the last couple of years, the world has faced the global pandemic COVID-19. The viral transmission could occur viadifferent modes like large respiratory droplets, direct contact with contaminated surfaces and airborne microdroplets or aerosol.This work revisits and focuses on human cough, and breathing sequence together with cough in confined spaces. We considerthe Eulerian dispersion medium as a multicomponent ideal gas mixture consisting of oxygen, nitrogen and water vapor andthe Lagrangian dispersed phase of human cough/breathe is modeled as pure liquid water. The unsteady complex flow isresolved with an advanced three-dimensional multiphase flow solver utilizing adaptive mesh refinement (AMR). A simplifiedrectangular block with a rectangular mouth area is considered to mimic human beings to inject exhaled gas and liquid dropletsassociated with cough and or breathing instances. The evaporation model is switched off for the particles of diameter lessthan 5μm to resolve the dynamics of the airborne particles. The results clearly demonstrate the efficacy of the novel approachtoward gaining more knowledge about viral transmission in indoor environments.
Permalink: https://doi.org/10.3384/ecp192035

Abstract: Existing thermal condition and indoor air quality have a big impact on our work performance, comfort, and health in an indoorenvironment. Apart from many other parameters, door motions and human movements play crucial role in mass and thermalexchange affecting safety and/or energy management issues in various situations. An isolation room in a hospital setup, forinstance, helps to protect patients and staff against the risk of infection by airborne pathogens. Another example is cold storageroom facilities, where temperature and moisture control are the key parameters for an optimal operation and energy usage.In this study, we present a transient flow analysis of door motions in indoor environment. The flow physics is resolved bysolving 3D compressible RANS (Reynolds-averaged Navier-Stokes) equations together with the energy and species transportequations and two-equation turbulence models utilizing an overset mesh strategy to address the rigid body motion of doors in arelevant fluid domain involving air and sulfur hexafluoride (SF6). Simulations are performed for three different types of doors,namely a hinged door, a two-way sliding door, and a sliding door considering door opening and closing phases. Transientflow-field data through the door opening area have been processed and a comparative analysis is performed considering themass flux of the constituents, normal velocity, cumulative mass exchange through the different doors.
Permalink: https://doi.org/10.3384/ecp192024

Abstract: The current Norwegian building code (TEK 17) requires the new residential buildings to have balanced ventilation with heat recovery, in addition to the strict regulations regarding thermal performance and airtightness of the fabric. During the cold winters in the South-East part of the country, the moisture content in the air outdoors is very low and results in a dry climate indoors as well. This study investigates in-situ the moisture excess indoors (Δv) in a series of urban residential apartments that have been built according to TEK 17. In particular, air temperature and relative humidity have been measured in six locations/rooms in each of the monitored apartments. Variations in moisture production as well as in ventilation rates have resulted in different moisture excess levels. The findings reveal that the current practice limits moisture excess and have led to an overall reduction of Δv compared to results found in similar studies performed two decades ago. 90th percentiles of Δv have been calculated as below 2 g/m3 in all types of rooms, while in bathrooms it has been 2.6 g/m3. The relative humidity (RH) has been respectively below 30%, with bathrooms being the only exception with RH just over this level. The results from a survey among the occupants showed that most of them complain about fatigue, difficulty in concentrating and a head that feels heavy. In addition, dust and too high air temperature have been identified as the main problems of the indoor environment.
Permalink: https://doi.org/10.34641/clima.2022.293

Abstract: Sustainable urban dwellings are built space-efficient, and open-plan kitchens have increasingly become the norm. A study of newer building projects has shown that the kitchen space is in the inner area of the apartment with limited options for forced window airing, leaving the job of removing cooking emissions to the kitchen hood or general ventilation. One of the aims of our study is to measure exposure from actual cooking in modern apartments, as preparations for further advanced studies. To achieve this, particle number concentrations (>0.3 μm) are measured for three typical Norwegian meals with different ventilation rates at three locations in the kitchen lab. The kitchen setup is comparable to the EN 61591:2019 standard with an area of approximately 30 m2 and a height of 2.7 m. The measurements show that the meals and cooking procedures developed are reasonably repeatable. Most of the particles are in the range 0.3-2.5 μm. The meal producing the lowest numbers of particles is the vegetarian pasta Bolognese, while taco and fried salmon which required both higher cooking temperature and contained more fat resulted in a much higher number of particles. The peak for particle number concentration was more than 40% lower for the vegetarian meal. Turning on the kitchen hood at medium setting (286 m3/h) drastically reduced the particle number concentrations, however, the Norwegian requirement of 108 m3/h (low) resulted in a 58% reduction for the taco meal.
Permalink: https://doi.org/10.34641/clima.2022.52

Abstract: Sustainable urban development results in more space and energy-efficient apartments. Open plan solutions are becoming more common, and the market is exploring new configurations and ventilation solutions for the kitchen in direction of the design and minimize space for ductwork. Cooking is an important aspect of human life and is considered one of the major sources of particle emissions. The cooking method, the type of cuisine, and the type of kitchen hood are some of the factors that will influence this. In Norway, the minimum requirement for general kitchen exhaust is 36 m3/h, with a minimum additional forced ventilation by the kitchen hood of 108 m3/h. However, these requirements might not be sufficient to mitigate the exposure from cooking. Electricity is the main heating source, traditionally with hot plate, today mainly induction or ceramic cooktop. In this work, we aim to investigate representative Norwegian cooking habits, typical meals and set up a procedure for cooking in the laboratory to perform intensive exposure studies. A survey has been performed to identify the type and usage of kitchen hoods in different living situations as well as typical Norwegian meals. A total of 336 people responded to the survey, of which 111 provided answers to a few additional questions. More than 60% of the respondents belonged in the age groups 30 – 60 years old and 92% owned their dwelling. Wall-mounted kitchen hoods were found in the majority of the homes, and almost 4% had downdraft. Only 12% of the homes had recirculating hoods. 76% of the respondents used the kitchen hood during cooking. The Norwegians mainly cook or fry their food, while deep-frying is not common. For the question related to what meal is most often cooked, the categories of food that were most mentioned were pasta dishes, taco, meat, fish, boiled potatoes, and chicken. Based on this we developed the cooking procedure for three different test meals suitable for exposure studies.
Permalink: https://doi.org/10.34641/clima.2022.54

Abstract: Pre-dehumidification time (τpre) and pre-dehumidification energy consumption (Epre) play important roles in preventing the condensation of moisture on the floors of rooms that use a radiant floor cooling (RFC) system. However, there are few theoretical or experimental studies that focus on these two important quantities. In this study, an artificial neural network (ANN) was used to predict condensation risk for the integration of RFC systems with mixed ventilation (MV), stratum ventilation (SV), and displacement ventilation (DV) systems. A genetic algorithm-back-propagation (GA-BP) neural network model was established to predict τpre and Epre. Both training data and validation data were obtained from tests in a computational fluid dynamics (CFD) simulation. The results show that the established GA-BP model can predict τpre and Epre well. The coefficient of determination (R2) of τpre and of Epre were, respectively, 0.973 and 0.956. For an RFC system integrated with an MV, SV, or DV system, the lowest values of τpre and Epre were with the DV system, 23.1 s and 0.237 kWh, respectively, for a 67.5 m3 room. Therefore, the best pre-dehumidification effect was with integration of the DV and RFC systems. This study showed that an ANN-based method can be used for predictive control for condensation prevention in RFC systems. It also provides a novel and effective method by which to assess the pre-dehumidification control of radiant floor surfaces.
Permalink: https://doi.org/10.1016/j.enbenv.2022.08.004

Abstract: Collaboration between different actors is key to successful projects within the architecture, engineering, and construction (AEC) industry. Virtual Reality (VR) combined with Building Information Models (BIM) is an effective visualisation tool that may aid a team’s communication and collaboration. Civil engineering students at Oslo Metropolitan University are encouraged to use such tools, available to them in a dedicated digital collaboration room dubbed the ‘Little Big Room’ (LBR) along with computers and large touchscreens. This paper explores how the tools in the LBR are utilised by three student groups working on a project and how the students view them, discussed through the theoretical lens of the technology acceptance model. The aim is to suggest how students’ utilisation of the technology can be facilitated to improve their learning experiences in collaborative projects. The students were satisfied with using the LBR. However, the full potential of VR was not utilised, such as the option to evaluate the size of the rooms and lighting conditions, something they only realised in hindsight, as not all students perceived VR as sufficiently useful for the tasks given. Changing the criteria of the task or increased focus on the students’ first introduction to VR might facilitate increased utilisation of VR as a professional tool.
Permalink: https://doi.org/10.35199/EPDE.2022.41

Abstract: An ever-increasing challenge of global warming and climate change is the issue of overheating in buildings. Several studies have developed numerous passive strategies to lessen the effects of overheating and reduce cooling energy consumption. For instance, thermal mass stores the thermal energy, which locks the heat away and prevents overheating. However, this must be discharged daily to ensure it can be used to store heat again. This discharging of heat can be achieved by night ventilation. The purpose of this research is to investigate the use of thermal mass and night ventilation in different climate conditions in China to minimise overheating in buildings under future climate conditions in 2050s and 2080s with four different greenhouse gas (GHG) emission scenarios. An office space model was employed to run full-year dynamic building simulations using Energyplus to simulate each thermal mass configuration in five cities (Guangzhou, Kunming, Shanghai, Beijing and Harbin) across China with varying climatic conditions. The study enabled the thermal mass configuration to be optimised for each specific climate and with the integrated night ventilation. The results highlighted night ventilation’s vital role in decreasing overheating. The impact of night ventilation was found to reduce overheating hours by up to 60%. The method and results presented in this research can provide means for formulating strategies to combat overheating and to be incorporated into the regulations of buildings in China.
Permalink: https://doi.org/10.1016/j.clet.2022.100534

Abstract: This study investigates approaches to evaluate prediction and correlation how significantly mechanical and natural ventilation rate and local weather conditions affect the actual ventilation performance of a residential building using Artificial Neural Network (ANN) algorithms: Feedforward networks and Layer recurrent neural networks. In order to evaluate the ventilation performance in a residential building, an impact factor was determined for these measured datasets. This study selected two residential apartments in Switzerland and measured indoor carbon dioxide concentration and volatile organic compound levels, façade opening ratio, mechanical ventilation rates, and indoor temperature and humidity ratio between July 2019 and June 2020. The results described that ANN models illustrate performance in predicting ventilation performance and indoor air quality using mechanical and natural ventilation systems in a residential apartment. Both algorithms have presented relatively lower average error rates, 3.36– 6.12 % in the analysis results. The results presented that the two ANN models using the Levenberg-Marquardt Back Propagation (LMBP) algorithm have good agreements with actual data measured. The accuracy differences were 0.18-1.89 for the average error rates, 0.13–0.78 for the Coefficient of Variation of the Root Mean Square Error (CVRMSE) and 0.07–0.35 for the Normalized Mean Bias Error (NMBE). Through impact factor analysis, mechanical ventilation system mainly dominates the impact of indoor ventilation performance, and other surrounding environments also had significantly affected the residential building. However, the natural ventilation system has limitations to largely influence the ventilation performance in the building because occupants have difficulties adjusting ventilation rates in extreme weather conditions or early morning and nighttime. And these elements could not affect indoor air quality independently. These ANN methods are helpful in analyzing input parameters how each element factor can influence indoor air quality in a residential building. The proposed ANN methods can utilize to predict the performance as reliable approaches.
Permalink: https://doi.org/10.1016/j.scs.2022.103981

Abstract available via the hyperlink above

Abstract: This study was carried out to solve the problem of condensation in radiant floor cooling systems. Computational fluid dynamics simulation and back-propagation neural network prediction were employed to conduct thorough research to predict the effects of the displacement ventilation dehumidification phase in an office building located in Jinan, China. The effects of the air supply temperature (Tas), air supply flow rate (Vas), air supply humidity ratio (Has), floor temperature (Tfloor), initial indoor temperature (Tini) and relative humidity (Hini) on the duration and energy consumption of pre-dehumidification were investigated. The big data show the air dew point temperature (Tad) produced the most significant effect on the pre-dehumidification duration and energy consumption, while Tas would cause the least significant effect. With the decrease of Tad, the pre-dehumidification duration and energy consumption were, respectively, decreased by 59.1% and 44.2%. Furthermore, with the variation of Vas, the energy consumption exhibited a fluctuating trend. This study provides a novel and effective method to assess the pre-dehumidification control of radiant floor surfaces by considering different initial indoor conditions and air supply parameters.
Permalink: https://doi.org/10.1177/1420326X221107110

Abstract: The development of collaborative control strategies for radiant cooling and ventilation systems improves thermal comfort and energy efficiency. This study used the Transient System Simulation (TRNSYS) tool integrated with the parametric simulation manager jEPlus to determine the optimal starting and operation mode of a combined radiant floor cooling (RFC) and ventilation system. The results were validated by an experiment. The optimization process was constrained by the thermal comfort defined by the predicted mean vote (PMV) with the objective of minimizing energy consumption. The results showed that the ventilation system was started 1 h earlier than the RFC system at an initial indoor humidity of 85% to prevent condensation, whereas both systems were started at the same time at 75% in the starting stage. In the operation stage, the self-regulation potential of the RFC system and the adjustment of the cooling capacity of the ventilation system were coordinated to counter dynamic internal heat gains. Moreover, the proportion of the total sensible heat removed by the RFC system to the total sensible heat removed by the ventilation system (Sv/SR) was positively correlated with the total energy consumption. The Sv/SR must be sufficiently high to prevent a large PMV deviation from the comfort zone of −0.5 to 0.5. A collaborative control strategy using the PMV-based model was proposed to adjust the Sv/SR according to the PMV range, resulting in a highly efficient operation and maximum energy savings of 26.2%.
Permalink: https://doi.org/10.1016/j.jobe.2022.104648

Abstract: The Energy Performance Certificate (EPC) for existing dwellings has not been able to promote the renovation rate. The main reasons are associated with the low quality of the assessment and renovation recommendations provided. These are not able to provide the information or confidence needed to undertake a renovation project. So far, neither reports for the EPBD nor studies by researchers have proposed modifications to the model used to assess existing buildings under the EPBD. The present research proposes a procedure to evaluate, design improvements, store and share data on the renovation process of each building. Specifically, the procedure is based on three steps, the first one is to apply simplified measurements on the dwelling, laser scanning and envelope testing. The second stage, using the electricity consumption data, was to calibrate and calculate the thermal properties of the building. Finally, tailor-made recommendations for the whole life cycle of the house are proposed and stored in a database. After an optimisation and life cycle analysis of different measurement packages. The results show that by incorporating currently available tools, such as scanners, smart meters and BIM, a complete building condition profile can be obtained, stored and shared, and renovation measures with their benefits and costs can be realistically proposed. This study is in line with what has been proposed by previous studies, the need to digitise the certification system, to use new technologies and to capture the trust of the users.
Permalink: https://doi.org/10.1016/j.enbuild.2022.112071

Abstract: This paper reviews studies on the human thermal plume and its influence on the inhalation exposure to particulate matter in the breathing zone under different conditions. The human thermal plume transports particle pollutants from the floor to the breathing zone, increasing the inhaled particulate matter concentration. The concentration can be four times higher than that in the ambient environment. Studies have reported that the human thermal plume may prevent particulate matter from entering the breathing zone under specific conditions. Indoor airflow patterns significantly affect the dispersion of pollutants, especially in rooms equipped with displacement ventilation at low airflow velocities. It has been shown that the particle concentration is two times lower in the breathing zone of a rotating manikin than a static manikin. Understanding the characteristics and influencing factors of the human thermal plume is crucial to formulate measures to mitigate the inhalation exposure to particulate matter, achieve independent and personalized control of the human microenvironment, and create a healthy, intelligent and energy-saving indoor environment.
Permalink: https://doi.org/10.1177/1420326X221080358

Abstract: Root temperature is an important ecological factor affecting plant growth. A solar greenhouse with an active solar heating system was built in Jinan, in the cold climate zone of northern China. Experiments encompassing the complete cycle of heat collection, heat storage, and heat release were carried out. Using the experimental data, the numerical simulation of soil heat storage with a variable heat flow was executed using the ANSYS (ANSYS Inc., Pittsburgh, PA, USA) Fluent software. Soil temperature fields were studied on typical sunny days and typical cloudy days in the transition season and winter. The solar collector efficiency and coefficient of performance of the system were investigated. The applicability of this active solar soil heating system with soil heat storage for cold areas was evaluated. The results showed that the system effectively maintained suitable ground temperatures to prevent plant growth inhibition caused by low ground temperatures in winter. During the experimental period, the solar collector efficiency was 47% and the system’s coefficient of performance was 67.70. The thermal performance of the system was much better than a traditional energy system. This study showed that this active solar heating system with soil heat storage is an economic and feasible way to increase soil temperatures in solar greenhouses in cold areas.
Permalink: https://doi.org/10.3390/buildings12040405

Abstract: The novel Pulse technique measures the building airtightness in a dynamic approach, involving a low-pressure pressurisation process, typically in 1–10Pa. It is known that the wind effect is one of the main sources of uncertainty for airtightness testing. The literature review revealed that the wind impact on measuring building airtightness has been explored in relation to the steady pressurisation method (i.e., the blower door), while there is limited research investigating the validity of the Pulse measurement under various natural wind conditions. In this study, in total, 423 Pulse tests were performed to measure the building airtightness of a five-bedroom dwelling located at the University of Nottingham, UK, under natural wind conditions. The viability of the Pulse technique for delivering airtightness measurements under different wind conditions was assessed, including the impacts of the wind speed and the wind direction on the Pulse measurements. Based on the measured air leakage rates, the threshold of maximum wind speed that led the Pulse measurements to have repeatability greater than ±10% is 5.0 m/s at 2.2 m above ground level (i.e., approximately equivalent to the meteorological wind speed of 7.9 m/s). On the other hand, the directional wind study showed that at lower wind speeds, the wind direction has a lesser influence on the Pulse measurement than the wind speed itself. Practically, multiple Pulse tests are recommended for minimising the wind impact on building airtightness measurement when adverse wind conditions are present.
Permalink: https://doi.org/10.1016/j.buildenv.2022.108955

Abstract: Radiant cooling systems need optimized control strategies to provide superior comfort while maximizing energy-savings. The field measurement method was used to study the operational control of radiant floor cooling (RFC) with a direct-ground cooling source and displacement ventilation (DV) systems. The control methods for the composite system were proposed based on three factors including floor surface temperature relative to the indoor air dew point temperature, the range of indoor/outdoor air temperature and humidity, and the indoor thermal and humidity loads to be countered. These factors were considered in three typical scenarios: intermittent operation, variable initial temperature and humidity conditions, and sudden increases in indoor heat gain, so that maintaining the operative temperature within 26–27 °C. The system required that precooling time of the RFC was 2.5–3 times the time to achieve 63% of the temperature change for intermittent operation on weekends, while the DV system was started 1–1.5 h before work time when initial indoor air humidity was higher than 75% and indoor air temperature was higher than 26 °C, and supply air flow rate was increased to maximum value under sudden increases in indoor heat gain. The results concluded that dynamic optimal control of the radiant cooling system was achieved.
Permalink: https://doi.org/10.1016/j.energy.2021.122410