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Construction and demolition waste (DW) generation information has been recognized as a tool for providing useful information for waste management. Recently, numerous researchers have actively utilized artificial intelligence technology to establish accurate waste generation information. This study investigated the development of machine learning predictive models that can achieve predictive performance on small datasets composed of categorical variables. To this end, the random forest (RF) and gradient boosting machine (GBM) algorithms were adopted. To develop the models, 690 building datasets were established using data preprocessing and standardization. Hyperparameter tuning was performed to develop the RF and GBM models. The model performances were evaluated using the leave-one-out cross-validation technique. The study demonstrated that, for small datasets comprising mainly categorical variables, the bagging technique (RF) predictions were more stable and accurate than those of the boosting technique (GBM). However, GBM models demonstrated excellent predictive performance in some DW predictive models. Furthermore, the RF and GBM predictive models demonstrated significantly differing performance across different types of DW. Certain RF and GBM models demonstrated relatively low predictive performance. However, the remaining predictive models all demonstrated excellent predictive performance at R2 values > 0.6, and R values > 0.8. Such differences are mainly because of the characteristics of features applied to model development; we expect the application of additional features to improve the performance of the predictive models. The 11 DW predictive models developed in this study will be useful for establishing detailed DW management strategies.
Gi-Wook Cha; Hyeun-Jun Moon; Young-Chan Kim. Comparison of Random Forest and Gradient Boosting Machine Models for Predicting Demolition Waste Based on Small Datasets and Categorical Variables. International Journal of Environmental Research and Public Health 2021, 18, 8530 .
AMA StyleGi-Wook Cha, Hyeun-Jun Moon, Young-Chan Kim. Comparison of Random Forest and Gradient Boosting Machine Models for Predicting Demolition Waste Based on Small Datasets and Categorical Variables. International Journal of Environmental Research and Public Health. 2021; 18 (16):8530.
Chicago/Turabian StyleGi-Wook Cha; Hyeun-Jun Moon; Young-Chan Kim. 2021. "Comparison of Random Forest and Gradient Boosting Machine Models for Predicting Demolition Waste Based on Small Datasets and Categorical Variables." International Journal of Environmental Research and Public Health 18, no. 16: 8530.
Maintaining a pleasant indoor environment with low energy consumption is important for healthy and comfortable living in buildings. In previous studies, we proposed the integrated comfort control (ICC) algorithm, which integrates several indoor environmental control devices, including an air conditioner, a ventilation system, and a humidifier. The ICC algorithm is operated by simple on/off control to maintain indoor temperature and relative humidity within a defined comfort range. This simple control method can cause inefficient building operation because it does not reflect the changes in indoor–outdoor environmental conditions and the status of the control devices. To overcome this limitation, we suggest the artificial intelligence integrated comfort control (AI2CC) algorithm using a double deep Q-network(DDQN), which uses a data-driven approach to find the optimal control of several environmental control devices to maintain thermal comfort with low energy consumption. The suggested AI2CC showed a good ability to learn how to operate devices optimally to improve indoor thermal comfort while reducing energy consumption. Compared to the previous approach (ICC), the AI2CC reduced energy consumption by 14.8%, increased the comfort ratio by 6.4%, and decreased the time to reach the comfort zone by 54.1 min.
Sun-Ho Kim; Young-Ran Yoon; Jeong-Won Kim; Hyeun-Jun Moon. Novel Integrated and Optimal Control of Indoor Environmental Devices for Thermal Comfort Using Double Deep Q-Network. Atmosphere 2021, 12, 629 .
AMA StyleSun-Ho Kim, Young-Ran Yoon, Jeong-Won Kim, Hyeun-Jun Moon. Novel Integrated and Optimal Control of Indoor Environmental Devices for Thermal Comfort Using Double Deep Q-Network. Atmosphere. 2021; 12 (5):629.
Chicago/Turabian StyleSun-Ho Kim; Young-Ran Yoon; Jeong-Won Kim; Hyeun-Jun Moon. 2021. "Novel Integrated and Optimal Control of Indoor Environmental Devices for Thermal Comfort Using Double Deep Q-Network." Atmosphere 12, no. 5: 629.
Recently, artificial intelligence (AI) technologies have been employed to predict construction and demolition (C&D) waste generation. However, most studies have used machine learning models with continuous data input variables, applying algorithms, such as artificial neural networks, adaptive neuro-fuzzy inference systems, support vector machines, linear regression analysis, decision trees, and genetic algorithms. Therefore, machine learning algorithms may not perform as well when applied to categorical data. This article uses machine learning algorithms to predict C&D waste generation from a dataset, as a way to improve the accuracy of waste management in C&D facilities. These datasets include categorical (e.g., region, building structure, building use, wall material, and roofing material), and continuous data (particularly, gloss floor area), and a random forest (RF) algorithm was used. Results indicate that RF is an adequate machine learning algorithm for a small dataset consisting of categorical data, and even with a small dataset, an adequate prediction model can be developed. Despite the small dataset, the predictive performance according to the demolition waste (DW) type was R (Pearson’s correlation coefficient) = 0.691–0.871, R2 (coefficient of determination) = 0.554–0.800, showing stable prediction performance. High prediction performance was observed using three (for mortar), five (for other DW types), or six (for concrete) input variables. This study is significant because the proposed RF model can predict DW generation using a small amount of data. Additionally, it demonstrates the possibility of applying AI to multi-purpose DW management.
Gi-Wook Cha; Hyeun Jun Moon; Young-Min Kim; Won-Hwa Hong; Jung-Ha Hwang; Won-Jun Park; Young-Chan Kim. Development of a Prediction Model for Demolition Waste Generation Using a Random Forest Algorithm Based on Small DataSets. International Journal of Environmental Research and Public Health 2020, 17, 6997 .
AMA StyleGi-Wook Cha, Hyeun Jun Moon, Young-Min Kim, Won-Hwa Hong, Jung-Ha Hwang, Won-Jun Park, Young-Chan Kim. Development of a Prediction Model for Demolition Waste Generation Using a Random Forest Algorithm Based on Small DataSets. International Journal of Environmental Research and Public Health. 2020; 17 (19):6997.
Chicago/Turabian StyleGi-Wook Cha; Hyeun Jun Moon; Young-Min Kim; Won-Hwa Hong; Jung-Ha Hwang; Won-Jun Park; Young-Chan Kim. 2020. "Development of a Prediction Model for Demolition Waste Generation Using a Random Forest Algorithm Based on Small DataSets." International Journal of Environmental Research and Public Health 17, no. 19: 6997.
This study presents a multi-objective parametric design tool for four-axis surround-type movable shading device using solar position tracking in Seoul, South Korea. In order to explore large numbers of possible forms of shades, generic algorithms are utilized with real-time simulation of the performative criteria such as solar radiation, daylight glare probability (DGP), and solar shielding rate on window surface. This study outlines a workflow using a multi-objective engine called Octopus that runs within Grasshopper 3D, a parametric design tool, in addition to environmental performance simulation plug-in Ladybug. The workflow utilizes a performance-based design tool, which allows the designer to explore, sort, and filter solutions, and visually compare alternative solutions in terms of energy saving and indoor daylight quality in order to determine the optimal form of shade changing its shape every one hour. The result of deriving and analyzing the optimal shade shape through the genetic algorithm proposed in this study is as follows: On the one hand, on the summer solstice, shade shapes with shielding areas of almost 100% should be derived to achieve the most effective reduction of the direct solar radiation. The proposed movable shading device reduced direct solar radiation by 52.40% and 57.20% in the south- and east-facing windows, respectively. On the other hand, in winter when solar heat gain is important, the absence of sunshade is optimal in terms of heating load. However, in order to improve the indoor light environment, it is confirmed that it is possible to derive a certain shape of sunshade according to the sun’s trajectory. On the winter solstice, the problem of glare arises from 10:00 to 15:00 in the south and 10:00 in the east. Therefore, the proposed four-axis movable shading device can be configured to have a minimum protrusion length satisfying DGP less than 0.35 in winter.
Ho-Jeong Kim; Chang-Seok Yang; Hyeun Jun Moon. A Study on Multi-Objective Parametric Design Tool for Surround-Type Movable Shading Device. Sustainability 2019, 11, 7096 .
AMA StyleHo-Jeong Kim, Chang-Seok Yang, Hyeun Jun Moon. A Study on Multi-Objective Parametric Design Tool for Surround-Type Movable Shading Device. Sustainability. 2019; 11 (24):7096.
Chicago/Turabian StyleHo-Jeong Kim; Chang-Seok Yang; Hyeun Jun Moon. 2019. "A Study on Multi-Objective Parametric Design Tool for Surround-Type Movable Shading Device." Sustainability 11, no. 24: 7096.
Response scales are widely used to assess the personal experience of sensation and perception in built environments, and have a great impact on the quality of the responses. The purpose of this study was to investigate the effects of response scales on human sensation and perception in moderate indoor environments. Four different response scales were compared under three room temperatures (19.0 °C, 24.5 °C, and 30.0 °C) and five acoustic stimuli (ambient noise, 42 and 61 dBA × water sounds and traffic noise): a bipolar seven-point scale according to ISO 10551:1995, a unipolar 11-point scale according to ISO/TS 15666:2003, these two scales combined for each sensory comfort assessment, and a bipolar visual analogue scale. The degree of relative differentiation based on indoor physical factors made no significant difference across the four response scales. Therefore, the effects of physical factors on human response could be assessed by using any of the four scales tested in this study, with a statistical significance at P < 0.05 in moderate environments. The choice of response scale would depend not only on the type of physical stimulus but also on the question of sensation or perception. The reliability of each response scale was different according to the subjective attributes. The bipolar visual analogue scale was subjectively preferred by the respondents.
Wonyoung Yang; Hyeun Jun Moon; Jin Yong Jeon. Comparison of Response Scales as Measures of Indoor Environmental Perception in Combined Thermal and Acoustic Conditions. Sustainability 2019, 11, 3975 .
AMA StyleWonyoung Yang, Hyeun Jun Moon, Jin Yong Jeon. Comparison of Response Scales as Measures of Indoor Environmental Perception in Combined Thermal and Acoustic Conditions. Sustainability. 2019; 11 (14):3975.
Chicago/Turabian StyleWonyoung Yang; Hyeun Jun Moon; Jin Yong Jeon. 2019. "Comparison of Response Scales as Measures of Indoor Environmental Perception in Combined Thermal and Acoustic Conditions." Sustainability 11, no. 14: 3975.
This study aims to evaluate an optimal operation control scheme for a radiant floor heating system in a residential building to maintain a desired room temperature. Radiant floor heating systems frequently cause overheating—exceeding the set temperature—due to the heat capacity of the flooring material. To mitigate this problem, an optimal operation control scheme is proposed to determine the optimal set temperature for each room. To evaluate the suggested optimal operation scheme, experiments were conducted on a living test bed—two bedrooms. In Bedroom 1, three operation periods with the suggested operation control were implemented and in Bedroom 2, three operation periods with the optimal operation control were implemented, reducing overheating from 4.0 °C to 0.0 °C and 4.5 °C to 0.5 °C, respectively.
S H Kim; Y R Yoon; H J Moon. Improved operation scheme for a radiant floor heating system to reduce overheating. IOP Conference Series: Earth and Environmental Science 2019, 238, 012071 .
AMA StyleS H Kim, Y R Yoon, H J Moon. Improved operation scheme for a radiant floor heating system to reduce overheating. IOP Conference Series: Earth and Environmental Science. 2019; 238 (1):012071.
Chicago/Turabian StyleS H Kim; Y R Yoon; H J Moon. 2019. "Improved operation scheme for a radiant floor heating system to reduce overheating." IOP Conference Series: Earth and Environmental Science 238, no. 1: 012071.
Realistic thermal conditions with various humidity levels have been considered to examine cross-modal effects of noise and thermal conditions on indoor environmental perceptions. Subjective assessments of temperature, humidity and acoustics were conducted with 26 subjects under combined environments of seven thermal conditions (18°C: RH 30, 60%, 24°C: RH 27, 43, 65%, 30°C: RH 30, 60%), two noise types (fan and babble noises) and five noise levels (45, 50, 55, 60, and 65 dBA). Three-minute moderate noise exposure did not affect temperature or humidity sensations. However, temperature and humidity levels affected loudness, annoyance, and acoustic preferences. Men were more sensitive to hot sensations than women, and women were more sensitive to arid sensations than men. Women were more sensitive to noise levels than men. Gender differences were also found in terms of different types of noise. Men were found to be significantly less sensitive to fan noise than women. Even though psychoacoustic parameters were affected by indoor thermal conditions; thermal parameters were not affected by short-term moderate noise. The combined effect of various types of noise and temperature is still unclear, and this will be considered in a future larger cohort study.
Wonyoung Yang; Hyeun Jun Moon; Myung-Jun Kim. Cross-modal effects of noise and thermal conditions on indoor environmental perceptions. The Journal of the Acoustical Society of America 2018, 144, 1977 -1977.
AMA StyleWonyoung Yang, Hyeun Jun Moon, Myung-Jun Kim. Cross-modal effects of noise and thermal conditions on indoor environmental perceptions. The Journal of the Acoustical Society of America. 2018; 144 (3):1977-1977.
Chicago/Turabian StyleWonyoung Yang; Hyeun Jun Moon; Myung-Jun Kim. 2018. "Cross-modal effects of noise and thermal conditions on indoor environmental perceptions." The Journal of the Acoustical Society of America 144, no. 3: 1977-1977.
Wonyoung Yang; Hyeun Jun Moon; Myung-Jun Kim. Perceptual assessment of indoor water sounds over environmental noise through windows. Applied Acoustics 2018, 135, 60 -69.
AMA StyleWonyoung Yang, Hyeun Jun Moon, Myung-Jun Kim. Perceptual assessment of indoor water sounds over environmental noise through windows. Applied Acoustics. 2018; 135 ():60-69.
Chicago/Turabian StyleWonyoung Yang; Hyeun Jun Moon; Myung-Jun Kim. 2018. "Perceptual assessment of indoor water sounds over environmental noise through windows." Applied Acoustics 135, no. : 60-69.
While water sounds have been used for soundscape improvement, little is known about their applicability in indoor environments. In order to investigate the effects of indoor water sounds on noise perception, a simple indoor water fountain system was used to produce water sounds over three different types of indoor intrusive noise (traffic noise, higher frequency dominated noise of a chair scraping the floor above, lower frequency dominated impact noise of a man running on the floor above) and speech in a test laboratory. Intrusive noise perception (annoyance and pleasantness) and speech recognition (KS-MWL-A) were assessed with three water sound levels (40, 50, 60 dBA) at two exposure times (immediate and 50 min) of water sounds by 54 participants. Short-term exposure to indoor water sounds improved the pleasantness of intrusive noise without increasing annoyance except lower frequency dominated impact noise. The increase in exposure time to indoor water sounds did not affect intrusive noise perception and speech recognition. The water to noise ratio significantly affected annoyance and pleasantness of traffic noise only; however, the level of water sounds did not significantly affect intrusive noise perception. Indoor water sounds can be used to improve intrusive noise perception except lower frequency dominated floor impact noise with no adverse effects on speech recognition dependent upon the speech to water sound ratio. Practical application: This simple indoor water fountain can be directly applied to small offices or rooms to improve intrusive noise perception. When the simple fountain produces water sounds in a room, pleasantness of traffic noise throughout window openings or higher frequency dominated noise such as chair scraping noise can be improved without increment of annoyance and decrement of speech recognition. Short-term exposure to indoor water sounds is effective to increase pleasantness of the intrusive noises.
Wonyoung Yang; Hyeun Jun Moon. Effects of indoor water sounds on intrusive noise perception and speech recognition in rooms. Building Services Engineering Research and Technology 2018, 39, 637 -651.
AMA StyleWonyoung Yang, Hyeun Jun Moon. Effects of indoor water sounds on intrusive noise perception and speech recognition in rooms. Building Services Engineering Research and Technology. 2018; 39 (6):637-651.
Chicago/Turabian StyleWonyoung Yang; Hyeun Jun Moon. 2018. "Effects of indoor water sounds on intrusive noise perception and speech recognition in rooms." Building Services Engineering Research and Technology 39, no. 6: 637-651.
Wonyoung Yang; Sang Ku Park; Hyeun Jun Moon. Local Weather Data Acquisition for Building Energy Performance Analysis. Journal of The Korean Society of Living Environmental System 2017, 24, 769 -776.
AMA StyleWonyoung Yang, Sang Ku Park, Hyeun Jun Moon. Local Weather Data Acquisition for Building Energy Performance Analysis. Journal of The Korean Society of Living Environmental System. 2017; 24 (6):769-776.
Chicago/Turabian StyleWonyoung Yang; Sang Ku Park; Hyeun Jun Moon. 2017. "Local Weather Data Acquisition for Building Energy Performance Analysis." Journal of The Korean Society of Living Environmental System 24, no. 6: 769-776.
Gi-Wook Cha; Hyeun Jun Moon; Ho-Jeong Kim; Won-Hwa Hong; Yong-Kyu Baik. Analysis on the Reduction of Cooling Load and Improvement of Visual Environment by applying a Kinetic Shading Device in Summer. Journal of The Korean Society of Living Environmental System 2017, 24, 810 -823.
AMA StyleGi-Wook Cha, Hyeun Jun Moon, Ho-Jeong Kim, Won-Hwa Hong, Yong-Kyu Baik. Analysis on the Reduction of Cooling Load and Improvement of Visual Environment by applying a Kinetic Shading Device in Summer. Journal of The Korean Society of Living Environmental System. 2017; 24 (6):810-823.
Chicago/Turabian StyleGi-Wook Cha; Hyeun Jun Moon; Ho-Jeong Kim; Won-Hwa Hong; Yong-Kyu Baik. 2017. "Analysis on the Reduction of Cooling Load and Improvement of Visual Environment by applying a Kinetic Shading Device in Summer." Journal of The Korean Society of Living Environmental System 24, no. 6: 810-823.
Gi-Wook Cha; Young-Chan Kim; Hyeun Jun Moon; Won-Hwa Hong. New approach for forecasting demolition waste generation using chi-squared automatic interaction detection (CHAID) method. Journal of Cleaner Production 2017, 168, 375 -385.
AMA StyleGi-Wook Cha, Young-Chan Kim, Hyeun Jun Moon, Won-Hwa Hong. New approach for forecasting demolition waste generation using chi-squared automatic interaction detection (CHAID) method. Journal of Cleaner Production. 2017; 168 ():375-385.
Chicago/Turabian StyleGi-Wook Cha; Young-Chan Kim; Hyeun Jun Moon; Won-Hwa Hong. 2017. "New approach for forecasting demolition waste generation using chi-squared automatic interaction detection (CHAID) method." Journal of Cleaner Production 168, no. : 375-385.
The roles of both the data collection method (including proper classification) and the behavior of workers on the generation of demolition waste (DW) are important. By analyzing the effect of the data collection method used to estimate DW, and by investigating how workers’ behavior can affect the total amount of DW generated during an actual demolition process, it was possible to identify strategies that could improve the prediction of DW. Therefore, this study surveyed demolition waste generation rates (DWGRs) for different types of building by conducting on-site surveys immediately before demolition in order to collect adequate and reliable data. In addition, the effects of DW management strategies and of monitoring the behavior of workers on the actual generation of DW were analyzed. The results showed that when monitoring was implemented, the estimates of DW obtained from the DWGRs that were surveyed immediately before demolition and the actual quantities of DW reported by the demolition contractors had an error rate of 0.63% when the results were compared. Therefore, this study has shown that the proper data collection method (i.e., data were collected immediately before demolition) applied in this paper and monitoring on the demolition site have a significant impact on waste generation.
Gi-Wook Cha; Young-Chan Kim; Hyeun Jun Moon; Won-Hwa Hong. The Effects of Data Collection Method and Monitoring of Workers’ Behavior on the Generation of Demolition Waste. International Journal of Environmental Research and Public Health 2017, 14, 1216 .
AMA StyleGi-Wook Cha, Young-Chan Kim, Hyeun Jun Moon, Won-Hwa Hong. The Effects of Data Collection Method and Monitoring of Workers’ Behavior on the Generation of Demolition Waste. International Journal of Environmental Research and Public Health. 2017; 14 (10):1216.
Chicago/Turabian StyleGi-Wook Cha; Young-Chan Kim; Hyeun Jun Moon; Won-Hwa Hong. 2017. "The Effects of Data Collection Method and Monitoring of Workers’ Behavior on the Generation of Demolition Waste." International Journal of Environmental Research and Public Health 14, no. 10: 1216.
Seung Ho Ryu; Hyeun Jun Moon. Development of an occupancy prediction model using indoor environmental data based on machine learning techniques. Building and Environment 2016, 107, 1 -9.
AMA StyleSeung Ho Ryu, Hyeun Jun Moon. Development of an occupancy prediction model using indoor environmental data based on machine learning techniques. Building and Environment. 2016; 107 ():1-9.
Chicago/Turabian StyleSeung Ho Ryu; Hyeun Jun Moon. 2016. "Development of an occupancy prediction model using indoor environmental data based on machine learning techniques." Building and Environment 107, no. : 1-9.
Jeong Won Kim; Wonyoung Yang; Hyeun Jun Moon. An Integrated Comfort Control with Cooling, Ventilation and Humidification Systems for Thermal Comfort and Low Energy Consumption. Science and Technology for the Built Environment 2016, 23, 264 -276.
AMA StyleJeong Won Kim, Wonyoung Yang, Hyeun Jun Moon. An Integrated Comfort Control with Cooling, Ventilation and Humidification Systems for Thermal Comfort and Low Energy Consumption. Science and Technology for the Built Environment. 2016; 23 (2):264-276.
Chicago/Turabian StyleJeong Won Kim; Wonyoung Yang; Hyeun Jun Moon. 2016. "An Integrated Comfort Control with Cooling, Ventilation and Humidification Systems for Thermal Comfort and Low Energy Consumption." Science and Technology for the Built Environment 23, no. 2: 264-276.
Hyeun Jun Moon; Seung Ho Ryu; Jeong Tai Kim. Investigation of IAQ in Mechanically Ventilated Kindergartens and Elementary Schools in Korea. International Journal of Engineering and Technology 2015, 7, 382 -385.
AMA StyleHyeun Jun Moon, Seung Ho Ryu, Jeong Tai Kim. Investigation of IAQ in Mechanically Ventilated Kindergartens and Elementary Schools in Korea. International Journal of Engineering and Technology. 2015; 7 (5):382-385.
Chicago/Turabian StyleHyeun Jun Moon; Seung Ho Ryu; Jeong Tai Kim. 2015. "Investigation of IAQ in Mechanically Ventilated Kindergartens and Elementary Schools in Korea." International Journal of Engineering and Technology 7, no. 5: 382-385.
Seung Ho Ryu; Hyeun Jun Moon; Jeong Tai Kim. Evaluation of the influence of hygric properties of wallpapers on mould growth rates using hygrothermal simulation. Energy and Buildings 2015, 98, 113 -118.
AMA StyleSeung Ho Ryu, Hyeun Jun Moon, Jeong Tai Kim. Evaluation of the influence of hygric properties of wallpapers on mould growth rates using hygrothermal simulation. Energy and Buildings. 2015; 98 ():113-118.
Chicago/Turabian StyleSeung Ho Ryu; Hyeun Jun Moon; Jeong Tai Kim. 2015. "Evaluation of the influence of hygric properties of wallpapers on mould growth rates using hygrothermal simulation." Energy and Buildings 98, no. : 113-118.
Hyeun Jun Moon; Seung Ho Ryu; Jeong Tai Kim. The effect of moisture transportation on energy efficiency and IAQ in residential buildings. Energy and Buildings 2014, 75, 439 -446.
AMA StyleHyeun Jun Moon, Seung Ho Ryu, Jeong Tai Kim. The effect of moisture transportation on energy efficiency and IAQ in residential buildings. Energy and Buildings. 2014; 75 ():439-446.
Chicago/Turabian StyleHyeun Jun Moon; Seung Ho Ryu; Jeong Tai Kim. 2014. "The effect of moisture transportation on energy efficiency and IAQ in residential buildings." Energy and Buildings 75, no. : 439-446.
Sang-Min Kim; Ji-Hyun Lee; Sooyoung Kim; Hyeun Jun Moon; Jinsoo Cho. Determining operation schedules of heat recovery ventilators for optimum energy savings in high-rise residential buildings. Energy and Buildings 2011, 46, 3 -13.
AMA StyleSang-Min Kim, Ji-Hyun Lee, Sooyoung Kim, Hyeun Jun Moon, Jinsoo Cho. Determining operation schedules of heat recovery ventilators for optimum energy savings in high-rise residential buildings. Energy and Buildings. 2011; 46 ():3-13.
Chicago/Turabian StyleSang-Min Kim; Ji-Hyun Lee; Sooyoung Kim; Hyeun Jun Moon; Jinsoo Cho. 2011. "Determining operation schedules of heat recovery ventilators for optimum energy savings in high-rise residential buildings." Energy and Buildings 46, no. : 3-13.
Indoor mould spore concentrations can be predicted by using a mathematical model that accounts for the mechanisms of spore transportation in a building with a mechanical ventilation system. The developed model considers the parameters related to a ventilation system and cleaning activity, and calculates indoor spore concentration, indoor/outdoor ratio, and the amount of deposited spores on interior surfaces in each building case. To get a more realistic outcome, an uncertainty analysis is conducted in the model by considering uncertainties associated with the parameters. The analysis results provide the distribution of spore concentrations as a function of time and give possible ranges of outcome with probability. Thus, a more realistic evaluation is available with the mathematical model. In addition, the identification of dominant parameters that have a major influence on spore transportation is performed using an appropriate parameter screening technique. Based on the identified dominant parameters, recommendations can be made to maintain lower indoor spore concentrations in a specific building case. Application of the spore transportation model under uncertainty in an existing building is described in the paper.
Hyeun Jun Moon. Uncertainty Analysis in Mould Spore Transportation and its Application in an Existing Building. Indoor and Built Environment 2010, 19, 355 -365.
AMA StyleHyeun Jun Moon. Uncertainty Analysis in Mould Spore Transportation and its Application in an Existing Building. Indoor and Built Environment. 2010; 19 (3):355-365.
Chicago/Turabian StyleHyeun Jun Moon. 2010. "Uncertainty Analysis in Mould Spore Transportation and its Application in an Existing Building." Indoor and Built Environment 19, no. 3: 355-365.