The construction industry is responsible for 36% of the European Union's greenhouse gas emissions. The main goal of the EU in the last decade has been to boost energy efficiency and expand the use of renewable energy in buildings. Ground-to-air heat exchangers may be a solution to reduce the use of primary energy in buildings from nonrenewable sources. The study in this paper deals with an evaluation of the heating and cooling energy potential of a ground-to-air heat exchanger (GAHE), serving a pilot energy-efficient building in Romania. The research follows a comparison between the experimental behavior of GAHE, evaluated based on measured outlet temperatures for two full years, and theoretical behavior, assessed using two computational models following EN 15241:2007 (Model 1) and EN 16798-5-1:2016 (Model 2). A comparison is made between the energy potential calculated using temperature measurements and the energy potential determined based on calculated outlet temperatures using the two models. The assessment is performed as well for conventional climate corresponding to the building location.

In the last few years, a significant amount of research has focused on learning and modeling personalized thermal preferences to satisfy individuals in buildings. However, there is a disconnection between personal comfort studies and building thermal control research. The objective of this article is to review research studies that integrate personalized thermal preferences into building control systems, and their control performance (in terms of comfort and energy) through either simulation studies or field implementations. Existing studies can be categorized into two main categories, depending on the type of control integration: conventional, reactive (feedback) control and advanced model-based predictive control. A deeper analysis of the degree of integration, number of occupants considered, control setpoint type, and thermal preference aggregation method, leads to a more detailed classification of thermal preference-based control research. In the absence of a general consensus of robust implementation of thermal preference-based control in buildings, this categorization allows a better understanding of current focus, research gaps, and needs for future work.

A new test procedure for determining capture efficiency (CE) of domestic range hoods (ASTM-E3087.18) was used to investigate how the range hood mounting height above a stove influences CE. Previous studies on CE utilized only two heights for a single range hood and a test procedure that did not strictly adhere to ASTM-E3087.18. In the study reported herein, testing was performed in accordance with ASTM-E3087.18 on six range hoods of similar design at three heights. The measured CE values ranged from 42.8–96.2%CE with CE changing by 8.2%CE at worst when varying the height for a specific fan. The influence of mounting height on CE uncertainty, repeatability, reproducibility and variability were also investigated. Lower mounting heights were found to increase CE and reduce uncertainty at the cost of increased variability between repeat tests. In contrast, intermediate mounting heights typically improved variability performance and repeatability/reproducibility. One range hood with vents for re-circulation showed higher uncertainty and more variability, indicating that flow exhausting from these vents can influence CE performance. Thus, it is possible that future ASHRAE/HVI certification standards be written with re-circulating vents sealed off during testing and a specified mounting height to minimize variations in CE caused by varying mounting heights.

Data-driven simulation models can be used for optimal control and decision making in building systems only if they are developed accurately and reliably. An unsolved issue pertains to the data collected from BEMS that generally contain errors owing to sensors, malfunctioning systems, and other unknown reasons. These anomalies generally occur in a multidimensional space and cannot be easily detected. Unfortunately, these anomalies can prevent the simulation model from being accurate, reliable, and scalable. This paper presents an automatic anomaly detection method using a support vector data description (SVDD). The data obtained from a compression chiller in a real office building were classified into raw and filtered datasets based on SVDD. Two artificial neural network (ANN) models were developed (ANNraw and ANNSVDD). Based on the comparison between the two ANNs, the ANNSVDD is found to be better than ANNraw in terms of the model reliability and reproducibility. It is also interesting that the model accuracy differences between the two ANN models are marginal. However, the accuracy of the two ANN models can be improved as long as they are tested against filtered data by SVDD. The improvements in accuracy signify the importance of the elimination of these anomalies.

The sub-divided unit (SDU) is the major type of substandard housing in Hong Kong. This study monitored the microclimatic conditions in eight SDUs for 24 h in summer. The mean CO2 concentration (1012 mg/m3) under natural ventilation was much higher than the outdoor level (∼410 mg/m3), suggesting that ventilation was ineffective in most SDUs. The mean predicted mean vote (PMV) was 1.7 (warm), corresponding to 75% predicted percentage dissatisfied (PPD). None of the SDUs was thermally acceptable (PPD < 20%) at any time in the monitoring period. If the adaptive thermal comfort standard was considered, the acceptable temperature range would be between 23.4 °C and 30.4 °C in operative temperature and the thermally acceptable time would be 47%. Larger openable window size, larger external wall area and poor ventilation significantly contributed to higher maximum indoor air temperature.

A transient multipole method for short-term simulations of ground heat exchangers (GHEs) is presented. The two-dimensional unsteady heat equation over a GHE cross section is separated into two problems: (i) a transient heat equation with homogeneous boundary conditions, and (ii) a steady-state heat equation with nonhomogeneous boundary conditions. An eigenfunction expansion is proposed for the solution of the transient heat equation, where the treatment of boundary conditions is considered by a multipole expansion of the eigenfunctions. A singular value decomposition is applied to extract the eigenvalues of the problem. The solution of the steady-state heat equation is obtained from a multipole expansion. The proposed method is validated against reference results for the evaluation of the eigenvalues and for the steady-state temperature field. The complete transient solution is validated against finite-element analysis simulations. The proposed method is meshless, and its accuracy is only dependent on the evaluation of eigenvalues and on the number of terms in each of the multipole expansions.

This article refers to:Development of a standard capture efficiency test method for residential kitchen ventilation

With an equal mass, nanoparticles (NP) have a higher toxicity than particles with the same chemical composition but with larger surface area. However, the toxicological knowledge concerning NP is still insufficient to establish limit values of exposure. To seek the lowest exposure level, filtration is a simple and effective way to capture particles, including NP. According to ANSI/ASHRAE 52.2 standard, ventilation filters efficiency is tested for particles ranging from 0.3 to 10.0 μm. Performances of entire filters for NP are still very limited and particle size of 300 nm (0.3 μm) is commonly used as the most penetrating particle size (MPPS) for mechanical media. To evaluate the filter performance for NP, five type of filters were investigated to measure their performance for particles smaller than 300 nm including NP. The performance of these filters was evaluated in terms of penetration and pressure drop. Experimental data permit to evaluate the MPPS for these mechanical filters. Nevertheless, 150–500 nm range provides a better estimation of the MPPS in the conditions which were tested. Also, filtration velocity influences efficiency for nanoparticles at 50 nm but no effect was observed for MPPS.

An automotive air conditioning and heat pump (AAC/AHP) system employing refrigerants R134a and R1234yf was developed and tested in cooling and heating operation modes under broad ranges of compressor speed and air inlet temperature conditions. Using test results, various energetic and exergetic performance parameters of the system were evaluated and compared. The R1234yf system provided on average 5.8% lower cooling capacity, 0.2% higher heating capacity, 11.9% lower COP for cooling and 3.6% lower COP for heating relative to the R134a one. Furthermore, the exergetic efficiency of the R1234yf system were on average 17.6% and 14.7% lower compared to the R134a one in cooling and heating modes, respectively. The major contributor to the exergy destruction in the system is the compressor for both refrigerants and operation modes. These results reveal that R1234yf performs better in heating relative to cooling mode, and it can be used as a replacement for R134a in not only AAC but also AHP systems in expense of slightly lower energy effectiveness.

Existing studies have treated variable refrigerant flow (VRF) control as a local control problem where control variables are determined using only local state information. This study investigates an integrated VRF control in which the VRF control actions are determined based on not only local information but also the dynamics of the room it serves. For this purpose, two artificial neural network simulation models were developed: one to predict indoor air temperature of the room and the other to predict the VRF’s compressor power. The ANN simulation models were validated with 192 experiments conducted in an experimental chamber. The results revealed that the integrated control reduced cooling and compressor energy use of the VRF by 21.6% and 13.1%, respectively, compared to the local control. These energy savings were achieved because the integrated control ANN models were aware of the dynamic relationship between the VRF and the target room.