Graduate Research Symposium 2023
Design Technology
Time: 12:00PM – 13:40 PM
Venue: Seminar Barrel Room, SDE3 Floor4
Reviewers: Rudi Stouffs
Speakers:
SHUYANG LI
URBAN DIGITAL TWINS FOR REFINED BUILDING ENERGY SIMULATION: OCCUPANCY, INTERIOR SPACE, AND MICROCLIMATE
Abstract: To achieve sustainable cities, it is necessary for urban planning stakeholders and architects to understand and estimate building energy consumption in the early design stage. However, the building energy simulation faces challenges in accuracy and efficiency, especially when the study scope is enlarged to the district scale and urban scale. Therefore, we need to determine the key parameters which may cause significant deviation in simulation results and how these parameters affect the building energy simulation, then calibrate the simulation results and simplify the simulation process.
Previous studies have revealed the impact of building height, building footprint, shading, window-to-wall ratio, façade material, air-conditioning system parameters (set point, operation, coefficient of performance) on the building energy consumption. CEA and UBEM.IO used these data as inputs to energy simulations at the district and urban scale, but the simulation results’ accuracy is still unsatisfactory. Some studies pointed out that the lack of reliable occupancy data may lead to inaccurate predictions of the electricity consumption of appliances and equipment. In addition, some studies indicated that oversimplifying the individual buildings as a thermal zone for energy simulation affects the accuracy.
Occupancy and microclimate data as a type of dynamic information is an important part of the urbandigital twin framework. Detailed building information beyond the LOD2 (Level of Detail) is also urgently needed for upgrading the urban digital twin. Therefore, this study focuses on understanding and analysing the impact of occupancy, interior space, and microclimate on energy consumption from the digital twin perspective, aiming to improve the accuracy of urban building energy modelling.
LU YIJUN
OPTIMIZATION OF VERTICAL AGRIVOLTAIC FAÇADE SYSTEM
Abstract: Climate change has been recognized as one of the most significant challenges in cities worldwide. With greater importance placed on energy and food security, attention has been directed to optimizing urban surfaces in cityscapes as spaces for production. Concurrently, most cities suffer from the Urban Heat Island (UHI) effect due to the loss of green spaces and increased built-up areas. Vertical greenery has been shown to be an effective countermeasure against UHI. Building façades offer significantly larger areas compared to roof spaces for harvesting solar energy and greenery installation. However, very few previous studies have developed the integration of vertical greenery and photovoltaic panels. The research aims to bridge this knowledge gap by developing and evaluating a prototype that showcases the potential benefits and feasibility of this integrated approach.
Using a novel double-skin Productive Façade (PF) system, this study quantifies the microclimate metrics between greenery and PV self-shading on building facades. The study will involve conducting field experiments and simulations simultaneously in order to establish a comprehensive microclimate model. Aside from assessing the optimized energy and food production on building facades, the study also aims to investigate the UHI effect as a potential environmental benefit. These experiments emphasize the crucial significance of the positioning of vegetation and the design of photovoltaic (PV) arrangements on building facades, as they would influence urban environments as well as energy and food production.
MERVE ESMEBASI
ENHANCING OFFICE ENVIRONMENTS: BIOPHILIC DESIGN AND ADAPTIVE ACOUSTIC COMFORT PERSPECTIVE IN MITIGATION OF ROAD TRAFFIC NOISE ANNOYANCE
Abstract: The impact of indoor greenery and operable windows on the annoyance stemming from road traffic noise within office spaces is the focal point of this research. While noise mitigation studies related to urban landscapes in residential areas have been conducted in the past, there remains a conspicuous knowledge gap concerning the effects of indoor greenery in office settings. In this study, a structural equation model is employed to meticulously examine the cause-and-effect relationships associated with noise perception. Assessments across thirty-two combinations of greenery levels, window conditions, and traffic noise, spanning four different sound pressure levels that range from 50 dBA to 65 dBA are conducted. In the quest to shed light on noise perception, various perceptual attributes such as pleasantness, eventfulness, appropriateness, preference, and visual aesthetics are considered by the model. The results of the investigation unveiled a relationship between traffic noise levels and visual perception, underscoring the existence of a two-way interaction between auditory and visual perceptions.
This highlights the potential benefits of integrating biophilic design principles into the development of office spaces, where the goal is to create environments that are not only visually pleasing but also acoustically comfortable. Moreover, the study brought to the forefront the constructive influence of open windows on the perceived appropriateness of traffic noise, ultimately resulting in reduced levels of annoyance. This research aims to provide insights into the domain of establishing adaptive acoustic comfort in naturally ventilated office spaces.
LI HUI
RESEARCH ON VIBRATION PREDICTION METHOD OF FLOOR IMPACT SOUND
Abstract: Impact sound insulation is a significant part in acoustic field. At present, the common test method is to tap the ground with a standard source in the sound source room and test the sound pressure level of the room in the reception room downstairs. In such a test process, the limitation is that the background noise in the source room and the receiving room must be very low. This is easy to achieve in laboratory tests, but in field tests, the test conditions are often very complex, and it is likely to fail meeting the test environment requirements.
By analyzing the transmission principle of the floor impact sound, it can be found that for thereceiving room, the sound source is the ceiling affected by the impact. If we can predict the noise in the receiving room by measuring the vibration of the floor after the impact, the limitations of existing test methods could be broke. In some existing studies, the transfer matrix method (TMM) is usually used to predict the noise caused by vibration. This is a model based on the physical transfer process, which will not be able to avoid the problem that the transfer coefficient between media could not be calculated accurately.
In this study, the floor vibration and receiving room noise level in the floor impact test will be measured and collected. Then, using pure mathematics method of artificial neural network, the trusted interface transfer coefficient is obtained. Then using TMM method, a better prediction model of floor impact sound could be established. This means that a new method of measuring the sound of floor impact has been established breaking the background noise limit for the test environment.