Energy and Built Environment最新文献

At present, thermal conductivity is usually taken as a constant value in the calculation of building energy consumption and load. However, in the actual use of building materials, they are exposed to the environment with continuously changing temperature and relative humidity. The thermal conductivity of materials will inevitably change with temperature and humidity, leading to deviations in the estimation of energy consumption in the building. Therefore, in this study, variations in the thermal conductivity of eight common building insulation materials (glass wool, rock wool, silica aerogel blanket, expanded polystyrene, extruded polystyrene, phenolic foam, foam ceramic and foam glass) with temperature (in the range of 20–60 °C) and relative humidity (in the range of 0–100%) were studied by experimental methods. The results show that the thermal conductivity of these common building insulation materials increased approximately linearly with increasing temperature with maximum growth rates from 3.9 to 22.7% in the examined temperature range. Due to the structural characteristics of materials, the increasing thermal conductivity of different materials varies depending on the relative humidity. The maximum growth rates of thermal conductivity with humidity ranged from 8.2 to 186.7%. In addition, the principles of selection of building insulation materials in different humidity regions were given. The research results of this paper aim to provide basic data for the accurate value of thermal conductivity of building insulation materials and for the calculation of energy consumption.

The thermal comfort of frail people has to be considered carefully, mainly because of the high thermal sensitivity of this population and the negative influences that unsatisfactory thermal conditions have on their health. Most existing thermal comfort works have been conducted under steady-state, uniform thermal environments, with far fewer being performed in dynamic and non-uniform thermal environments, and even less for frail people. This study aimed at assessing the thermal responses of frail people under transient and non-uniform thermal environments, using a thermal manikin and a climatic test cell. Thermal responses were investigated and discussed in both genders. The analysis of variance showed a significant difference in thermal comfort and thermal sensation between females and males over time, under hot exposure. Under cold exposure, results showed a significant difference in thermal sensation between females and males over time, but no significant difference was observed in term of thermal comfort. Analysis revealed also significant differences in the dynamic thermal sensation between the sexes under cold exposure, while results confirmed that there is no significant difference in the dynamic thermal sensation between sexes under hot exposure.

Direct air capture (DAC) is one of the most potential technologies to mitigate CO₂ emission. Adsorption technology is recognized as a promising CO₂ capture method in view of its desirable characteristics including reusability of adsorbents and low capital investment. To further improve thermal performance, evaporation/condensation heat of vapor compression refrigeration (VCR) cycle in air condition system of buildings is adopted for adsorption/desorption process of DAC. Thermal performance of a 4-step temperature swing adsorption process (TSA) is analyzed at various adsorption/desorption temperatures by using different adsorbents. Analysis on Coefficient of Performance (COP) of VCR cycle is also conducted in search for a balance between adsorbent and refrigerant. Taking both real working capacity and COP into consideration, Mg-MOF-74&R134a is the best choice for more amounts of CO₂. Real working capacity of Mg-MOF-74 is up to 0.38 mol•kg⁻¹ at 70 °C, which is twice as much as that of zeolite 13X. While zeolite 13X&R134a shows the best performance of two cycles in view of exergy efficiency and COP, which could reach 81.9% and 7.21, respectively, at 35 °C. These matches will provide some guidelines for the practical application of the combination of DAC with heating, ventilation and air conditioning (HVAC).

Household electricity demand has substantial impacts on local grid operation, energy storage and the energy performance of buildings. Hourly demand data at district or urban level helps stakeholders understand the demand patterns from a granular time scale and provides robust evidence in energy management. However, such type of data is often expensive and time-consuming to collect, process and integrate. Decisions built upon smart meter data have to deal with challenges of privacy and security in the whole process. Incomplete data due to confidentiality concerns or system failure can further increase the difficulty of modeling and optimization. In addition, methods using historical data to make predictions can largely vary depending on data quality, local building environment, and dynamic factors. Considering these challenges, this paper proposes a statistical method to generate hourly electricity demand data for large-scale single-family buildings by decomposing time series data and recombining them into synthetics. The proposed method used public data to capture seasonality and the distribution of residuals that fulfill statistical characteristics. A reference building was used to provide empirical parameter settings and validations for the studied buildings. An illustrative case in a city of Sweden using only annual total demand was presented for deploying the proposed method. The results showed that the proposed method can mimic reality well and represent a high level of similarity to the real data. The average monthly error for the best month reached 15.9% and the best one was below 10% among 11 tested months. Less than 0.6% improper synthetic values were found in the studied region.

The philosophy of building energy management is going through a paradigm change from traditional, often inefficient, user-controlled systems to one that is centrally automated with the aid of IoT-enabled technologies. In this context, occupants’ perceived control and building automation may seem to be in conflict. The inquiry of this study is rooted in a proposition that while building automation and centralized control systems are assumed to provide indoor comfort and conserve energy use, limiting occupants’ control over their work environment may result in dissatisfaction, and in turn decrease productivity. For assessing this hypothesis, data from the post-occupancy evaluation survey of a smart building in a university in Australia was used to analyze the relationships between perceived control, satisfaction, and perceived productivity. Using structural equation modeling, we have found a positive direct effect of occupants’ perceived control on overall satisfaction with their working area. Meanwhile, perceived control exerts an influence on perceived productivity through satisfaction. Furthermore, a field experiment conducted in the same building revealed the potential impact that occupant controllability can have on energy saving. We changed the default light settings from automatic on-and-off to manual-on and automatic-off, letting occupants choose themselves whether to switch the light on or not. Interestingly, about half of the participants usually kept the lights off, preferring daylight in their rooms. This also resulted in a reduction in lighting electricity use by 17.8% without any upfront investment and major technical modification. These findings emphasize the important role of perceived control on occupant satisfaction and productivity, as well as on the energy-saving potential of the user-in-the-loop automation of buildings.

The air infiltration of buildings is closely related to its indoor and outdoor environment and energy consumption. However, measuring air infiltration of a building under natural conditions is time-consuming, easily affected and expensive, so it's often inferred based on building airtightness in practical engineering. Empirical models can nevertheless make a rapid prediction without building parameters, which are widely applied in practical engineering. At present, most of the existing empirical models take residential buildings as objects, therefore they are difficult to be applied to public buildings. Hence, it is imperative to build an empirical model applicable to public buildings. In this study, the conversion coefficients between the airtightness (air change rate under the pressure difference of 50Pa) and the air infiltration rates under natural conditions of four typical zones of public buildings were analyzed. Firstly, the airtightness of four zones of public buildings in the cold region of China was measured. Secondly, their air infiltration rates under 1800 combined conditions of wind pressure and stack effect pressure were simulated based on the airtightness measured results. Finally, calculation and statistical analysis of the conversion coefficient were carried out based on the measured and simulated results, and the recommended value of conversion coefficient was proposed. Analysis results show that the CC of each zone is significantly affected by outdoor meteorological conditions and varies in a wide range (1# zone: 3.21 to 188.44). It is advised to ignore the extreme data and take the mean value of the CC corresponding to 95% of the data volume as the recommended value (22.2). This study can provide theoretical basis for the formulation of standards for the performance evaluation of building airtightness.

This paper presents a comparative study on the thermal comfort of traditional and contemporary houses in Byblos, Lebanon. With climate change affecting indoor environments and potentially leading to increased energy consumption, achieving optimal thermal comfort is a crucial issue for building research. The study analyzes several environmental parameters and conducts an occupancy survey to assess thermal comfort in both types of houses. The questionnaire used in the survey consists of 46 questions divided into three parts: “Who are you?”, “The environment of your house?”, and “Architectural characteristics of the house.” The results show that traditional houses perform better than contemporary ones in terms of thermal comfort, due to their use of natural and passive methods. However, both types of houses have room for improvement in terms of energy efficiency. This study provides insights into potential solutions for improving indoor thermal comfort while reducing energy consumption in traditional and contemporary houses.

A comparison analysis of the heating properties of the hydronic heating system of bridge decks with external (exchange tubes installed at the bottom of the existing bridge deck with voids inside) or internal (exchange tubes embedded in pavement of the newly built bridge deck) tubes was carried out through field tests. Two heating methods (constant heating power and constant inlet fluid temperature) were used to analyze the heat exchange flux and the temperature increments as well as thermally induced stress of the slab. Numerical simulation was conducted to model the bridge deck heating process to analyze the temperature distribution of the bridge surface. The results shows that the heat exchange flux are the same under the same constant heating powers for the two embedded tube position heating systems; the maximum temperature increment of the bridge deck surface obtained by the external heating system is 0.46 times that obtained by the internal heating system; the maximum thermally induced stress caused by the external heating is 20.4% of the concrete strength (19.1 MPa), which is much higher than that caused by the internal heating under the same heating powers. The thermal efficiencies of the external and internal heating systems are approximately 24.4% and 47.9%, respectively. Under the same constant inlet temperatures, the temperature increment of the bridge deck caused by the external heating is 20.4% of that of the internal heating.

As the world continues to urbanize at an unprecedented rate, the energy demand in cities is rising. Buildings account for over 75% of all the energy consumed in cities and are responsible for over two-thirds of the emissions. Assessment of energy demand in buildings is a highly integrative endeavour, bringing together the interdisciplinary fields of energy and urban studies, along with a host of technical domains namely, geography, engineering, economics, sociology, and planning. In the last decade, several urban building energy modelling tools (UBEMs) have been developed for estimation as well as prediction of energy demand in cities. These models are useful in policymaking as they can evaluate future urban energy scenarios. However, data acquisition for generating the input database for UBEM has been a major challenge. In this review, a comprehensive assessment of the potential of remote sensing and GIS techniques for UBEM has been presented. Firstly, the most common input variables of UBEM have been identified by reviewing recent publications on UBEM and then studies related to the acquisition of data corresponding to these variables have been explored. More than 140 research papers and review articles relevant to remote sensing and GIS applications for building level data extraction in urban areas and UBEM applications have been investigated for this purpose. After going through level of details required for each of the input components of UBEM and studying the possibility of acquiring some of those data using remote sensing, it has been inferred that satellite remote sensing and Unmanned Aerial Vehicles (UAVs) have a strong potential in enhancing the input data space for UBEM but their applicability has been limited. Further, the challenges of the usage of these technologies and the possible solutions have also been presented in this study. It is recommended to utilise the existing methodologies of extracting information from remote sensing and GIS for UBEM, along with newer techniques such as machine learning and artificial intelligence.