Air-conditioning And Mechanical Ventilation Research Articles

3D reconstruction of semantic-rich digital twins for ACMV monitoring and anomaly detection via scan-to-BIM and time-series data integration

Current research in air-conditioning and mechanical ventilation (ACMV) operation focuses on isolated sub-processes and analytical models. Digital twins, as digital replicas of assets, processes, or systems in the built environment, enable facilities manager (FM) to gain insights into the physical features of space, equipment performance, and energy efficiency. This study presents the 3D reconstruction of semantic-rich digital twins, which encompasses conditional and machine learning-enabled monitoring with 3D geometric models, for ACMV modeling and operation. The proposed framework involves a hybrid rule-based and data-driven approach to forecast the performance of indoor environment and identify potential anomalies throughout ACMV operation. Following this, a scan-to-BIM process is undertaken, with the aid of Simultaneous Localization and Mapping algorithms, to semi-automatically generate the as-built geometric models. Lastly, semantic enrichment of BIM is performed by incorporating time-series data from the rule-based and data-driven approach with 3D geometric models. The proposed approach supports the reconstruction of content-aware and semantic-rich digital twins, which utilize sensor-derived time-series data and 3D geometric models, to conduct advanced analysis for intelligent ACMV operation towards energy efficiency and occupant comfort.

Study of Energy Performance in Malaysian Public Hospital using Power Query

In 2016, the Ministry of Health (MOH), Malaysia, initiated a sustainable program that includes activities for sustainable energy management at all 145 buildings under the MOH. The focus of the sustainable energy management program is to target these buildings to reduce their annual energy consumption by 10% by 2018. The target implementation of a sustainable energy management program includes achieving 3-star EMGS certification within 5 years. By December 2022, 135 have achieved two-star certification with the requirement to achieve at least 5% energy consumption savings. By 2019, the 118 buildings that embarked on EMGS certification had achieved 22.62% energy consumption savings. District and specialist hospitals achieved 23%–24% savings in 2019. The largest energy consumption in MOH buildings is for room cooling, which is contributed by air conditioning and mechanical ventilation (ACMV) equipment. The implementation of a sustainable energy management program has contributed to energy cost savings of RM21 million per year to MOH energy bills in 2019.

Expertise-based systematic guidelines for chiller retrofitting in healthcare facilities

Air Conditioning and Mechanical Ventilation (ACMV) generally consume more than half of the energy consumption in commercial buildings in a tropical region. In healthcare facilities, the ACMV systems must comply with the following crucial parameters: indoor air quality, which greatly impacts the thermal comfort of occupants, as well as pressure regime regulations and standards, particularly in critical areas. Due to the high cost of operating the ACMV system, many health facilities in Malaysia have embarked on energy efficiency initiatives. Many have replaced their chillers with magnetic-bearing chiller compressors to benefit from cost reduction. However, despite the replacement, it was found that not all healthcare facilities benefited fully from improved air condition systems other than the higher chillers' coefficient of performance obtained from the new installation. The paper's main contribution is to offer a comprehensive and systematic guideline for facility managers to evaluate healthcare facilities ACMV systems and provides solutions that match the healthcare facilities ventilation requirements standards in making effective decision before embarking chiller retrofitting. The proposed guideline is based on the experience and observation of the expertise through energy auditing of the ACMV system and chiller retrofitting evaluation at the healthcare facilities in Malaysia. It may contribute towards more cost-effective management of ACMV system at healthcare facilities in Malaysia while assisting facility managers on chiller retrofitting decision making. More importantly, the guideline has the potential to support sustainable performance of the ACMV system.

BUILDING ENVELOPE RETROFIT FOR ENERGY SAVINGS IN MALAYSIAN GOVERNMENT HIGH-RISE OFFICES: A CALIBRATED ENERGY SIMULATION

With over a third of global energy used for building construction and operation, an optimum design for building envelopes is essential to improve the energy performance of the existing buildings. This study revealed that typical government high-rise office buildings in Malaysia have an average Building Energy Intensity (BEI) of 161 kWh/m2/year before any upgrading works on the air-conditioning and mechanical ventilation (ACMV) systems were conducted. This value is higher than the recommended value in Green Building Index (GBI) for commercial office buildings (150 kWh/m2/year) and the Economic Planning Unit (EPU) standard for public buildings (140 kWh/m2/year). Therefore, this study employed a case study approach combined with calibrated computer simulation to determine the optimal building envelope retrofit strategies and identify the three levels of interventions (minor, moderate and major levels) with corresponding energy reduction. A validated model representing a typical existing government high-rise office building in Malaysia was chosen as the base case model for energy evaluation studies. The effectiveness of each level of intervention and its energy retrofit measures (ERMs) were evaluated compared to the actual electricity bills. The results showed that all levels of interventions provided between 4% to 7% savings in annual energy consumption. The proposed interventions demonstrated compliance with the BEI benchmark margins of the GBI and EPU standard, namely 116 kWh/m2/year (minor intervention level), 113 kWh/m2/year (moderate intervention level), and 110 kWh/m2/year (major intervention level).

Transactive control of air-conditioning systems in buildings for participation in Singapore’s Demand Response market through load curtailment

Air-conditioning and mechanical ventilation (ACMV) systems account for significant electrical demand within buildings. These systems have large thermal time constants and can be utilized as thermal energy storage. This paper is focused on participation of commercial buildings in Singapore’s Demand Response (DR) programme through curtailment in electricity demand of ACMV systems for financial incentive and power grid benefits. A novel Transactive Energy-based virtual market is proposed for a building where multiple air-conditioning zone agents transact to purchase conditioned-air from central ACMV system. These zone agents consider forecasts of occupancy and outdoor temperatures to submit bids for conditioned-air corresponding to increasing electricity market prices, using a novel dynamic programming approach to utilize the temporal flexibility in cooling demand through pre-cooling. ACMV electricity demand bid is calculated based on net conditioned-air bids by using existing accurate building models in whole-building energy modeling (BEM) platforms corresponding to increasing electricity prices for submission to DR market. Case studies are performed in MATLAB–EnergyPlus co-simulation environment on a benchmark five-zone building model representing a small office building. Results show that the proposed control is effective in providing curtailment of ACMV electricity demand for DR according to real Singapore market price signals, while respecting occupants’ thermal comfort preferences and up to 56% reduction in ACMV electrical power demand is possible for 1 h. Further, revenue analysis shows that DR market participation incentive from 1 h participation would be higher than energy costs for ACMV operation for the entire day, which makes the DR market participation commercially lucrative.

Review of Automation and Energy Monitoring System for Air-Conditioning and Mechanical Ventilation (ACMV) in Building Malaysia

Buildings and their components such as ventilation, air conditioning (VAC), and lighting account for most of the energy use in Malaysia.The control system of a building reduces energy usage based on numerous criteria such as luminance or daylight and occupancy by reducing the running duration of the VAC and lamp.As a result, the need for further energy-efficient buildings should be emphasized, given the country's high energy consumption, which puts it at risk of global warming.Energy demand considerably exceeds supply, prompting the installation of increasingly rigorous energy saving measures. Thus, this study conducts a literature analysis on Building Management Systems (BMS) with the goal of integrating building automation systems into new buildings and retrofitting older buildings to make them automation ready.The focus of the building automation market is on increasing user comfort while cutting running expenses.Examining the role of BMSs in improving the energy use of a building's electromechanical systems and emphasizing their superior cost-cutting capabilities in both operations and maintenance would inspire stakeholders and facility owners to embrace automation (residential, commercial, and industrial).The current concept may be incorporated into a single platform for monitoring and controlling multiple pieces of equipment in the future.

Model predictive control for integrated control of air-conditioning and mechanical ventilation, lighting and shading systems

Modern buildings are increasingly automated and often equipped with multiple building services (e.g., air-conditioning and mechanical ventilation (ACMV), dynamic shading, dimmable lighting). These systems are conventionally controlled individually without considering their interactions, affecting the building’s overall energy inefficiency and occupant comfort. A model predictive control (MPC) system that features a multi-objective MPC scheme to enable coordinated control of multiple building services for overall optimized energy efficiency, indoor thermal and visual comfort, as well as a hybrid model for predicting indoor visual comfort and lighting power is proposed. The MPC system was implemented in a test facility having two identical, side-by-side experimental cells to facilitate comparison with a building management system (BMS) employing conventional reactive feedback control. The MPC system coordinated the control of the ACMV, dynamic façade and automated dimmable lighting systems in one cell while the BMS controlled the building services in the other cell in a conventional manner. The MPC side achieved 15.1–20.7% electricity consumption reduction, as compared to the BMS side. Simultaneously, the MPC system improved indoor thermal comfort by maintaining the room within the comfortable range (−0.5 < predicted mean vote < 0.5) for 98.3% of the time, up from 91.8% of the time on the BMS side. Visual comfort, measured by indoor daylight glare probability (DGP) and horizontal illuminance level at work plane height, was maintained for the entire test period on the MPC side, improving from having visual comfort for 94.5% and 85.7% of the time, respectively, on the BMS side.

Thermal comfort prediction of air-conditioned and passively cooled engineering testing centres in a higher educational institution using CFD

PurposeThe purpose of this paper is to analyse the thermal environment of two engineering testing centres cooled via different means using computational fluid dynamics (CFD), focussing on the indoor temperature and air movement. This computational technique has been used in the analysis of thermal environment in buildings where the profiles of thermal comfort parameters, such as air temperature and velocity, are studied.Design/methodology/approachA pilot survey was conducted at two engineering testing centres – a passively cooled workshop and an air-conditioned laboratory. Electronic sensors were used in addition to building design documentation to collect the required information for the CFD model–based prediction of air temperature and velocity distribution patterns for the laboratory and workshop. In the models, both laboratory and workshop were presumed to be fully occupied. The predictions were then compared to empirical data that were obtained from field measurements. Operative temperature and predicted mean vote (PMV)–predicted percentage dissatisfied (PPD) indices were calculated in each case in order to predict thermal comfort levels.FindingsThe simulated results indicated that the mean air temperatures of 21.5°C and 32.4°C in the laboratory and workshop, respectively, were in excess of the recommended thermal comfort ranges specified in MS1525, a local energy efficiency guideline for non-residential buildings. However, air velocities above 0.3 m/s were predicted in the two testing facilities, which would be acceptable to most occupants. Based on the calculated PMV derived from the CFD predictions, the thermal sensation of users of the air-conditioned laboratory was predicted as −1.7 where a “slightly cool” thermal experience would prevail, but machinery operators in the workshop would find their thermal environment too warm with an overall sensation score of 2.4. A comparison of the simulated and empirical results showed that the air temperatures were in good agreement with a percentage of difference below 2%. However, the level of correlation was not replicated for the air velocity results, owing to uncertainties in the selected boundary conditions, which was due to limitations in the measuring instrumentation used.Research limitations/implicationsDue to the varying designs, the simulated results of this study are only applicable to laboratory and workshop facilities located in the tropics.Practical implicationsThe results of this study will enable building services and air-conditioning engineers, especially those who are in charge of the air-conditioning and mechanical ventilation (ACMV) system design and maintenance to have a better understanding of the thermal environment and comfort conditions in the testing facilities, leading to a more effective technical and managerial planning for an optimised thermal comfort management. The method of this work can be extended to the development of CFD models for other testing facilities in educational institutions.Social implicationsThe findings of this work are particularly useful for both industry and academia as the indoor environment of real engineering testing facilities were simulated and analysed. Students and staff in the higher educational institutions would benefit from the improved thermal comfort conditions in these facilities.Originality/valueFor the time being, CFD studies have been carried out to evaluate thermal comfort conditions in various building spaces. However, the information of thermal comfort in the engineering testing centres, of particular those in the hot–humid region are scantily available. The outcomes of this simulation work showed the usefulness of CFD in assisting the management of such facilities not only in the design of efficient ACMV systems but also in enhancing indoor thermal comfort.

Quantification of Viable Bioaerosol Emanation from an ACMV System and its Impact on Indoor Bioaerosol Pollution

Viable bioaerosol can deposit and multiply in air-conditioning and mechanical ventilation (ACMV) systems, eventually entering indoor environments after these systems are operated and contributing to indoor pollution. We propose a method for identifying and quantifying the emanation of viable bioaerosol from an ACMV system and its impact on indoor pollution through surface and air sampling followed by analysis using a material-balance model. Adopting this method, we investigated the contribution of viable bioaerosol from an ACMV system to the indoor pollution in an air-conditioned room located in Singapore. The system, which emanated viable bacteria and viable fungi at the rates of 2.4 CFU s–1 and 3.9 CFU s–1, respectively, was the largest source of indoor viable bacteria and the second largest source of indoor viable fungi (exceeded only by the outdoor fungi introduced through mechanical ventilation) in the air. Potentially pathogenic bioaerosol species in the genera of Staphylococcus, Moraxella and Aspergillus were also identified in the ACMV system. In particular, Moraxella osloensis, the most likely genus to originate from occupants, was found to accumulate in the ACMV system, indicating the potential effect of this system’s cleanliness on indoor pollution. Our method can be used as a tool for analysing the potential sources of indoor bioaerosol and supporting the development of effective control measures for bioaerosol emanation from ACMV systems.

Experimental study of model predictive control for an air-conditioning system with dedicated outdoor air system

Using separate cooling coils for sensible and latent loads provide extra control flexibility to optimise the energy efficiency and comfort in air-conditioning and mechanical ventilation (ACMV) systems. A popular implementation of such technology is dedicated outdoor air system (DOAS)-assisted separate sensible and latent cooling (SSLC) systems. However, a sophisticated control technique is needed to coordinate the control of multiple cooling coils in such systems. This paper presents a novel model predictive control (MPC) developed for a DOAS-assisted SSLC system. The MPC adopts a linear state-space model that captures building thermodynamics, thermal comfort and ACMV for building response prediction and optimization. Subsequently, a multi-objective cost function is employed to optimize energy use and thermal comfort while fulfilling constraints of predicted mean vote (PMV) (-0.5, 0.5) and relative humidity (0%, 65%) in buildings. The performance of the MPC for controlling a conventional single-coil air-handling unit (AHU) system and a DOAS-assisted SSLC system is experimentally investigated and compared to a conventional feedback-control-based building management system (BMS). The MPC system achieved 18% and 20% electricity savings for the single-coil AHU and DOAS-assisted SSLC, respectively, as compared to the BMS controlled single-coil AHU. Furthermore, indoor thermal comfort is significantly improved, compared to the BMS. DOAS-assisted SSLC is shown to be advantageous compared to single-coil AHU to achieve better indoor environment in terms of thermal comfort and humidity, when both systems are controlled by MPC.

Computation of zone-level ventilation requirement based on actual occupancy, plug and lighting load information

This paper presents a case study to compare the zone-level actual supplied ventilation rate with minimum required ventilation rate for a typical variable air volume (VAV) operation. The minimum required ventilation rate was computed using zone-level actual occupancy, plug and lighting load data. Two different algorithms were adopted to collect the actual zone-level occupancy information using camera-based technology which are (a) area-based occupancy counting and (b) row-based occupancy counting. Similarly, zone-level Plug, lighting and air-conditioning and mechanical ventilation (ACMV) system-related energy data were taken from the energy submeters and BTU meters. The median values of actual supplied ventilation rates are 0.16, 0.14, 0.14 and 0.12 m3/s for the classroom, computer room, open office and closed office, respectively. For the same zone, the computed minimum required ventilation rates are 0.10, 0.09, 0.10 and 0.08 m3/s, respectively. This case study shows that except during evening classes in classroom and computer room, the actual ventilation supplied is much more than the minimum required ventilation. These over and under ventilation scenarios have been identified as an indicator for energy wastage and poor indoor environmental quality, respectively.

Using PERT to Optimise the Completion Time of Air-Conditioning and Mechanical Ventilation (ACMV) Project

An air-conditioning and mechanical ventilation (ACMV) construction project involved many interrelated construction activities with varying durations and multiple dependencies. This paper focuses on the development of a best possible project planning and scheduling technique that can help the project manager to manage and complete the ACMV project in optimal time. The program evaluation and review technique (PERT) is used in this research. The PERT technique helps to determine the probabilities of various stages of the project by specified deadlines and identify the activities on the critical path that have high potential for causing delays in the project completion time. The completion times of 72, 76, 79, and 80 weeks were taken for the PERT analysis. Deadline of 72 weeks is the contractual period of the ACMV project as specified in the contract. Completion time of 76 weeks is the critical path of the project as analyzed by the PERT technique. The deadline of 79 weeks is the proposed completion time for the ACMV project whereas 80 weeks are the actual completion date of the project. The PERT analysis revealed that the project completion time of 72 weeks, which is as stated in the contractual completion time, yielded the probability of completion of 2.67% only. This analysis shows that the contractual period is impossible to be achieved and it is an unrealistic time setting. Further negotiation is required including changing or extending of the contractual completion time. The other completion times are able to be achieved but the company may need to face the high penalty costs due to the delays in completion time.

A feedforward neural network based indoor-climate control framework for thermal comfort and energy saving in buildings

Building air-conditioning and mechanical ventilation (ACMV) systems are responsible for significant energy consumption and yet, dissatisfaction with the thermal environment is prevalent among the occupants, revealing a widespread disparity between energy-efficiency and indoor thermal-comfort in buildings. This paper presents an indoor-climate control framework that bridges this gap between energy and comfort. The framework comprises two main components: a thermal-comfort prediction model, and an optimization algorithm termed as the optimal air temperature (OAT) algorithm; they collectively act as an intelligent mediator between the occupant and the ACMV system. Firstly, the ACMV energy consumption is modelled as a function of air temperature, and three operating frequencies of cooling components using a feedforward neural network. Secondly, the thermal-comfort prediction model predicts the thermal state index (TSI: Cool-Discomfort/Comfort/Warm-Discomfort). Thirdly, depending on the predicted TSI, the OAT algorithm locates the optimal operating state such that Comfort state is achieved using the minimum ACMV energy consumption. Proposed framework exhibits an energy saving potential of 36.5%. It is found that 25 °C is the ideal air temperature for desired comfort with minimum energy expense in the tropical buildings. Additionally, six different TSI predictive models including two general and four personal comfort models are implemented to validate the framework. The study is substantiated with extensive real human experiments in controlled thermal environment. The proposed method is scalable for its applicability with any comfort-prediction model, and adaptive for its data-driven architecture. It exhibits the potential to achieve both occupant-comfort and energy-saving through integration with the Internet-of-Things for realizing comfort-energy balanced buildings.

Evaluation of thermal comfort criteria of an active chilled beam system in tropical climate: A comparative study

Air-conditioning systems are employed to provide thermal comfort inside buildings. Therefore, several air-conditioning and mechanical ventilation (ACMV) systems have been tested and applied in different climates. Chilled beam systems are a new addition to it and have been in the application in Europe and North America since last two decades. In the present study, comparative performance of active chilled beam (ACB) system with conventional fan coil unit (FCU) system has been appraised in regards to thermal comfort for the tropical region of Singapore. Experiments were carried out in a simulated office building with approximately 80% glazed area under real environmental conditions. Room air temperature, air velocity, mean radiant temperature (MRT) and relative humidity which are important thermal comfort parameters were measured in perimeter zone inside the cells and assessed. It was perceived that the ACB system was providing acceptable thermal comfort as per the standard of SS 554. General thermal comfort has been assessed based on an index of PMV-PPD model and graphical method. With regard to the local thermal discomfort: indices of air draught, vertical air temperature difference (VATD) and radiant temperature asymmetry have also been evaluated. The entrance of solar radiation through window façade may have a significant impact on the asymmetry of the radiant field and can enhance thermal discomfort of the occupants. Therefore, in the study radiant temperature asymmetry has been calculated extensively. The results show that ACB system yields satisfactory thermal environment as per ISO 7730 standard and sometimes performs even better than conventional FCU system.

A new demand response algorithm for solar PV intermittency management

This paper presents a new algorithm for managing solar PV intermittency in green buildings using demand response management (DRM) technique. The proposed DRM algorithm utilizes the building air conditioning and mechanical ventilation (ACMV) system to dynamically compensate for the deficit of power generated by solar PV system from its rated capacity. For example, the developed solution will reduce the load demand of the ACMV system equal to the drop of solar generation by controlling the speed of the fan. This will ensure that the amount of power supplied by the grid to the building will remain the same (as before the drop of solar generation) and thus no impact on the grid stability. However, since ACMV system is directly linked to building occupant comfort/health, the proposed solution will also include energy storage management and priority-based load shedding programs to provide support when room temperature (air conditioning) or CO level (ventilation) is above regulatory limit. A thermal model for building temperature variation is developed to test and analyze the proposed algorithm to dynamically manage solar PV fluctuation.

Overcoming Solar PV Intermittency using Demand Response Management in Buildings

Singapore’s National Climate Change Policy is aimed to make energy usage in Singapore more efficient, reduce pollution and expand the nation’s green spaces. Part of the plan is to promote the integration of solar photovoltaics (PVs) on rooftops of high-rise HDB residential and commercial buildings. This initiative contributed to the significant growth in the integration of solar PV systems in the last few years. However, large-scale integration of solar PVs will put at risk the reliability and stability of Singapore’s power system due to its intermittent nature. The intermittency problem of solar PV, typically in the range of minutes, will become very significant in Singapore as the installations of PV systems continue to increase. Conventionally, large energy storage systems are deployed as an energy buffer to compensate for the deficit or surplus of power supplied by solar PV systems. However, the high capital and maintenance costs as well as large space requirement for energy storage systems makes this an unfavorable option for building owners. This paper proposes a solution that utilizes the centrifugal fans in building air conditioning and mechanical ventilation (ACMV) system to dynamically compensate for the deficit or surplus of power supplied by solar PVs. For example, the developed solution will reduce the load demand of fans in the ACMV system equal to the drop of solar generation by controlling the speed of the fan. This will ensure that the amount of power supplied by the grid to the building will remain the same (as before the drop of solar generation) and thus no impact on the grid stability. However, since ACMV system is directly linked to building occupant comfort/health, the proposed solution will also include battery management and priority-based load shedding programs to provide support when room temperature (air conditioning) or CO level (ventilation) is above regulatory limit.

Thermal Analysis for Underground Data Centres in the Tropics

Different with traditional aboveground data centres, underground data centres have attracted increasing attention during recent years due to its inherent geographical advantages such as zero solar heat gain, low ambient temperature, natural geothermal cooling, and solid rock surrounded structures. The energy reduction in air-conditioning and mechanical ventilation (ACMV) system of the underground data centre is even more significant for the tropical regions where air is hot and humid all the year round. However, little study has been conducted to systematically analyse the relationship between the air-conditioning effectiveness and the corresponding energy efficiency. In this work, both energy simulations and computational fluid dynamics (CFD) simulations are conducted to the underground air-conditioning data centres in the tropics. The former one studies the energy consumption and energy efficiency of the whole ACMV system for a data centre. Meanwhile, the latter one studies the corresponding detailed airflow pattern within the data centre room. Optimizations in air management of the ACMV system are also proposed based on the energy and CFD simulation results.

Occupancy estimation from environmental parameters using wrapper and hybrid feature selection

Occupancy information is essential to facilitate demand-driven operations of air-conditioning and mechanical ventilation (ACMV) systems. Environmental sensors are increasingly being explored as cost effective and non-intrusive means to obtain the occupancy information. This requires the extraction and selection of useful features from the sensor data. In past works, feature selection has generally been implemented using filter-based approaches. In this work, we introduce the use of wrapper and hybrid feature selection for better occupancy estimation. To achieve a fast computation time, we introduce a ranking-based incremental search in our algorithms, which is more efficient than the exhaustive search used in past works. For wrapper feature selection, we propose the WRANK-ELM, which searches an ordered list of features using the extreme learning machine (ELM) classifier. For hybrid feature selection, we propose the RIG-ELM, which is a filter–wrapper hybrid that uses the relative information gain (RIG) criterion for feature ranking and the ELM for the incremental search. We present experimental results in an office space with a multi-sensory network to validate the proposed algorithms.

Temporarily occupied space with metabolic-rate-initiated thermal overshoots—A case study in railway stations in transition seasons

Temporarily occupied space (TOS) is defined as an air-conditioned space in which most of occupants stay for less than a certain period (e.g., 40 min), such as post offices, supermarkets, bookstores, and banks. The definition mainly emphasizes two aspects: obvious temperature step up/down and short-term exposure periods. Typical TOSs with predominantly temperature-initiated thermal overshoots have been explored in previous studies. Indeed, apart from temperature-initiated thermal overshoots, thermal overshoots can also be initiated by other parameters, such as metabolic rates. In this view, the definition of thermal overshoots was generalized and a case study was conducted at high-speed railway station in China under conditions of transition seasons. The phenomenon of metabolic-rate-initiated thermal overshoots instead of temperature-initiated thermal overshoots was observed and explored, based on objective measurements and subjective questionnaire surveys. The results could optimize the design and operation of air conditioning and mechanical ventilation (ACMV) systems in such TOSs as embodied by railway stations. In addition, the probit analysis method for analyzing neutral temperature ranges instead of neutral temperature points was also discussed.

Application of acoustic agglomeration to enhance air filtration efficiency in air-conditioning and mechanical ventilation (ACMV) systems.

The recent episodes of haze in Southeast Asia have caused some of the worst regional atmospheric pollution ever recorded in history. In order to control the levels of airborne fine particulate matters (PM) indoors, filtration systems providing high PM capturing efficiency are often sought, which inadvertently also results in high airflow resistance (or pressure drop) that increases the energy consumption for air distribution. A pre-conditioning mechanism promoting the formation of particle clusters to enhance PM capturing efficiency without adding flow resistance in the air distribution ductwork could provide an energy-efficient solution. This pre-conditioning mechanism can be fulfilled by acoustic agglomeration, which is a phenomenon that promotes the coagulation of suspended particles by acoustic waves propagating in the fluid medium. This paper discusses the basic mechanisms of acoustic agglomeration along with influencing factors that could affect the agglomeration efficiency. The feasibility to apply acoustic agglomeration to improve filtration in air-conditioning and mechanical ventilation (ACMV) systems is investigated experimentally in a small-scale wind tunnel. Experimental results indicate that this novel application of acoustic pre-conditioning improves the PM2.5 filtration efficiency of the test filters by up to 10% without introducing additional pressure drop. The fan energy savings from not having to switch to a high capturing efficiency filter largely outstrip the additional energy consumed by the acoustics system. This, as a whole, demonstrates potential energy savings from the combined acoustic-enhanced filtration system without compromising on PM capturing efficiency.