An event-triggered collaborative neurodynamic approach to distributed global optimization

In this paper, we propose an event-triggered collaborative neurodynamic approach to distributed global optimization in the presence of nonconvexity. We design a projection neural network group consisting of multiple projection neural networks coupled via a communication network. We prove the convergence of the projection neural network group to Karush-Kuhn-Tucker points of a given global optimization problem. To reduce communication bandwidth consumption, we adopt an event-triggered mechanism to liaise with other neural networks in the group with the Zeno behavior being precluded. We employ multiple projection neural network groups for scattered searches and re-initialize their states using a meta-heuristic rule in the collaborative neurodynamic optimization framework. In addition, we apply the collaborative neurodynamic approach for distributed optimal chiller loading in a heating, ventilation, and air conditioning system.

Energy efficient ventilation and indoor air quality in the context of COVID-19 - A systematic review

New COVID-19 ventilation guidelines have resulted in higher energy consumption to maintain indoor air quality (IAQ), and energy efficiency has become a secondary concern. Despite the significance of the studies conducted on COVID-19 ventilation requirements, a comprehensive investigation of the associated energy challenges has not been discussed. This study aims to present a critical systematic review of the Coronavirus viral spreading risk mitigation through ventilation systems (VS) and its relation to energy use. COVID-19 heating, ventilation and air conditioning (HVAC)-related countermeasures proposed by industry professionals have been reviewed and their influence on operating VS and energy consumption have also been discussed. A critical review analysis was then conducted on publications from 2020 to 2022. Four research questions (RQs) have been selected for this review concerning i) maturity of the existing literature, ii) building types and occupancy profile, iii) ventilation types and effective control strategies and iv) challenges and related causes. The results reveal that employing HVAC auxiliary equipment is mostly effective and increased fresh air supply is the most significant challenge associated with increased energy consumption due to maintaining IAQ. Future studies should focus on novel approaches toward solving the apparently conflicting objectives of minimizing energy consumption and maximizing IAQ. Also, effective ventilation control strategies should be assessed in various buildings with different occupancy densities. The implications of this study can be useful for future development of this topic not only to enhance the energy efficiency of the VS but also to enable more resiliency and health in buildings.

Improving the Efficiency of Fan Coil Units in Hotel Buildings through Deep-Learning-Based Fault Detection

Optimizing the performance of heating, ventilation, and air-conditioning (HVAC) systems is critical in today's energy-conscious world. Fan coil units (FCUs) play a critical role in providing comfort in various environments as an important component of HVAC systems. However, FCUs often experience failures that affect their efficiency and increase their energy consumption. In this context, deep learning (DL)-based fault detection offers a promising solution. By detecting faults early and preventing system failures, the efficiency of FCUs can be improved. This paper explores DL models as fault detectors for FCUs to enable smarter and more energy-efficient hotel buildings. We tested three contemporary DL modeling approaches: convolutional neural network (CNN), long short-term memory network (LSTM), and a combination of CNN and gated recurrent unit (GRU). The random forest model (RF) was additionally developed as a baseline benchmark. The fault detectors were tested on a real-world dataset obtained from the sensory measurement system installed in a hotel and additionally supplemented with simulated data via a physical model developed in TRNSYS. Three representative FCU faults, namely, a stuck valve, a reduction in airflow, and an FCU outage, were simulated with a much larger dataset than is typically utilized in similar studies. The results showed that the hybrid model, integrating CNN and GRU, performed best for all three observed faults. DL-based fault detectors outperformed the baseline RF model, confirming these solutions as viable components for energy-efficient hotels.

A Review of Data-Driven Approaches and Techniques for Fault Detection and Diagnosis in HVAC Systems

Heating, ventilation, and air conditioning (HVAC) systems are a popular research topic because buildings' energy is mostly used for heating and/or cooling. These systems heavily rely on sensory measurements and typically make an integral part of the smart building concept. As such, they require the implementation of fault detection and diagnosis (FDD) methodologies, which should assist users in maintaining comfort while consuming minimal energy. Despite the fact that FDD approaches are a well-researched subject, not just for improving the operation of HVAC systems but also for a wider range of systems in industrial processes, there is a lack of application in commercial buildings due to their complexity and low transferability. The aim of this review paper is to present and systematize cutting-edge FDD methodologies, encompassing approaches and special techniques that can be applied in HVAC systems, as well as to provide best-practice heuristics for researchers and solution developers in this domain. While the literature analysis targets the FDD perspective, the main focus is put on the data-driven approach, which covers commonly used models and data pre-processing techniques in the field. Data-driven techniques and FDD solutions based on them, which are most commonly used in recent HVAC research, form the backbone of our study, while alternative FDD approaches are also presented and classified to properly contextualize and round out the review.

Numerical investigation on indoor environment decontamination after sneezing

More than 320 million people worldwide were affected by SARS-CoV-2 or COVID-19, which already caused more than 5.5 million deaths. COVID-19 spreads through air when an infected person breathes, coughs, or sneezes out droplets containing virus. Emerging variants like Omicron with positivity rate of 16 (highest among others) present a greater risk of virus spread, so all types of indoor environments become critically important. Strategically adopted Heating Ventilation and Air Conditioning (HVAC) approach can significantly reduce the virus spread by early removal of contaminated aerosolized droplets. We modeled different HVAC configurations to characterize the diffusion of contaminated droplets cloud through Computational Fluid Dynamics (CFD) simulations of sneeze in standard hospital room as indoor scenario. Injection of saliva droplets with characteristics of exhaled air from lungs was applied to mimic real sneeze. CFD simulations have been performed for three HVAC configurations at two Air Change per Hour (ACH) rates; 6 and 15 ACH. For the first time, use of air curtain at low flow rate has been examined. Simulations provide high fidelity spatial and temporal droplets cloud diffusion under different HVAC configurations, showing spread in room indoor environment up to 360 s. Over 92% of ejected sneeze mass is removed from room air within seconds while the remaining 8% or less becomes airborne with droplets (<50 μm size) and tends to spread uniformly with regular HVAC configuration. Low-speed air curtain accelerates decontamination by efficiently removing aerosolized 1-50 μm size droplets. Study investigates role of droplets removal mechanisms such as escape, evaporation, and deposition on surfaces. Interestingly, results show presence of contaminated droplets even after 5 min of sneeze, which can be effectively removed using low-speed air curtain. Study finds that high ventilation rate requirements can be optimized to modify earlier and new hospital designs to reduce the spread of airborne disease.

Effects of different air change rates on cleanroom 'in operation' status

The objective of this experimental study is to analyse non-viable and viable particle loads in a pharmaceutical cleanroom under 'in operation' conditions using different air change rates (ACR). Regulatory guidelines give limit values for particles/m³ and colony forming units (CFU)/m³. A widely used ACR is20 h^-1 as this value is recommended by the Food and Drug Administration (FDA) in its guidance for industry for sterile drug products. However, this value may be to high, resulting in increased costs for energy. A typical pharmaceutical cleanroom was used for this study, and operations were simulated with a process unit and two operators in the room. The experiments were conducted twice with four different ACR's and four different types of operator garments, resulting in 32 trials in total. Particle load and CFU's were measured by calibrated particle counters and microbial air samplers. The results give evidence that an ACR of 20 h^-1 is not required. ACR 10 h^-1 is sufficient without compromising the demanded air quality. Furthermore, it was found that regulatory agencies should re-evaluate the expected limits as these currently give a high buffer between the required and actual values, which potentially cover up problems in aseptic manufacturing.

Sustainability of Heating, Ventilation and Air-Conditioning (HVAC) Systems in Buildings-An Overview

Increasing demand on heating, ventilation, and air-conditioning (HVAC) systems and their importance, as the respiratory system of buildings, in developing and spreading various microbial contaminations and diseases with their huge global energy consumption share have forced researchers, industries, and policymakers to focus on improving the sustainability of HVAC systems. Understanding and considering various parameters related to the sustainability of new and existing HVAC systems as the respiratory system of buildings are vital to providing healthy, energy-efficient, and economical options for various building types. However, the greatest opportunities for improving the sustainability of HVAC systems exist at the design stage of new facilities and the retrofitting of existing equipment. Considering the high available percentage of existing HVAC systems globally reveals the importance of their retrofitting. The attempt has been made to gather all important parameters that affect decision-making to select the optimum HVAC system development considerations among the various opportunities that are available for sustainability improvement.

Addressing COVID-19 contagion through the HVAC systems by reviewing indoor airborne nature of infectious microbes: Will an innovative air recirculation concept provide a practical solution?

As the world continues to grapple with the reality of coronavirus disease, global research communities are racing to develop practical solutions to adjust to the new challenges. One such challenge is the control of indoor air quality in the COVID-19 era and beyond. Since COVID-19 became a global pandemic, the "super spread" of the virus has continued to amaze policymakers despite measures put in place by public health officials to sensitize the general public on the need for social distancing, personal hygiene, etc. In this work, we have reviewed the literature to demonstrate, by investigating the historical and present circumstances, that indoor spread of infectious diseases may be assisted by the conditions of the HVAC systems. While little consideration has been given to the possibility of indoor airborne transmission of the virus, the available reports have demonstrated that the virus, with average aerodynamic diameter up to 80-120 nm, is viable as aerosol in indoor atmosphere for more than 3 h, and its spread may be assisted by the HVAC systems. Having reviewed the vulnerability of the conventional ventilation systems, we recommend innovative air circulation concept supported by the use of UVGI in combination with nanoporous air filter to combat the spread of SARS-CoV-2 and other harmful microbes in enclosed spaces.

Presence and variability of culturable bioaerosols in three multi-family apartment buildings with different ventilation systems in the Northeastern US

Bioaerosol concentrations in residential buildings located in the Northeastern US have not been widely studied. Here, in 2011-2015, we studied the presence and seasonal variability of culturable fungi and bacteria in three multi-family apartment buildings and correlated the bioaerosol concentrations with building ventilation system types and environmental parameters. A total of 409 indoor and 86 outdoor samples were taken. Eighty-five percent of investigated apartments had indoor-outdoor (I/O) ratios of culturable fungi below 1, suggesting minimal indoor sources of fungi. In contrast, 56% of the apartments had I/O ratios for culturable bacteria above 1, indicating the prominence of indoor sources of bacteria. Culturable fungi I/O ratios in apartments serviced by central heating, ventilation, and air-conditioning (HVAC) system were lower than those in apartments with window AC. The type of ventilation system did not have a significant effect on the presence of indoor culturable bacteria. A significant positive association was determined between indoor dew point (DP) levels and indoor culturable fungi (P < .001) and bacteria (P < .001), regardless of ventilation type. Also, residents in apartments with central HVAC did not experience extreme DP values. We conclude that building ventilation systems, seasonality, and indoor sources are major factors affecting indoor bioaerosol levels in residential buildings.

Distribution and comparison of bacterial communities in HVAC systems of two university buildings: Implications for indoor air quality and public health

The installation of HVAC systems in building is meant to enhance indoor air quality as well as increase comfort to occupants. However, HVAC systems have also become a vehicle of contamination of indoor air with potentially pathogenic microorganisms. DNA was extracted from ten HVAC filter dust samples collected from two buildings and subjected to high throughput sequencing analysis to determine the bacterial community structure. Further, the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2) software was used to predict the potential functional capabilities of the bacterial communities. Sequencing analysis led to the identification of five major bacterial phyla, including Proteobacteria, Cyanobacteria, Actinobacteria, Firmicutes and Bacteroidetes. At genus level, Mycobacterium, Bacillus, Cupriavidus, Hyphomicrobium and Mesorhizobium were the most dominant. With the exception of the later two bacterial genera, the first three are potential pathogens whose presence in HVAC systems poses a significant public health risk, especially among immunocompromised individuals. Nine pathways associated with antibiotics resistance and bacterial pathogenicity were identified, including polymyxin resistance and peptidoglycan biosynthesis pathways. Further, investigation of the relationship between the detected bacterial meta-communities and predicted potential virulence factors (antibiotic resistance and pathogenic genes) led to the detection of 350 positive associations among 43 core bacteria, 2 pathogenic genes (sitA and uidA) and 14 resistance genes. Overall, the heterogeneous nature of microorganisms found in HVAC systems observed in this study shows that HVAC systems are the origin of airborne infections in indoor environments, and must be periodically cleaned and disinfected to avoid the build-up of pathogens, and the subsequent exposure of human occupants of these pathogens.

The design of safe classrooms of educational buildings for facing contagions and transmission of diseases: A novel approach combining audits, calibrated energy models, building performance (BPS) and computational fluid dynamic (CFD) simulations

The proposed investigation is aimed at providing useful suggestions and guidelines for the renovation of educational buildings, in order to do University classrooms safe and sustainable indoor places, with respect to the 2020 SARS-CoV-2 global pandemic. Classrooms and common spaces have to be thought again, for a new "in-presence" life, after the recent worldwide emergency following the spring 2020 pandemic diffusion of COVID-19. In this paper, starting from a real case study, and thus the architectural and technological refurbishment of an Italian University building (Campobasso, South Italy, cold climate), with the aims of improving the classrooms' quality and safety, a comprehensive approach for the retrofit design is proposed. By taking into account the necessary come back to classrooms starting, hopefully, from the next months (Autumn 2020), experimental studies (monitoring and investigations of the current energy performances) are followed by the coupling of different numerical methods of investigations, and thus building performance simulations, under transient conditions of heat transfer, and computational fluid dynamics studies, to evidence criticalities and potentialities to designers involved in the re-thinking of indoor spaces hosting multiple persons, with quite high occupancy patterns. Both energy impacts, in terms of monthly and annual increase of energy demands due to higher mechanical ventilation, and indoor distribution of microclimatic parameters (i.e., temperature, airspeed, age of air) are here investigated, by proposing new scenarios and evidencing the usefulness of HVAC systems, equipment (e.g., sensible heat recovery, without flows' contamination) and suitability of some strategies for the air distribution systems (ceiling squared and linear slot diffusers) compared to traditional ones.

Structural Risk Factors for Hospital-Acquired Infections in Intensive Care Unit

There are risk factors related to architecture and designing labeled as "structural risk factors," causing hospital-acquired infections (HAIs) which are less highlighted in the literature. Through this communication, we wish to reiterate the importance of structural risk factors such as space surrounding the patient, furniture with focus on construction and finishing materials used, and ventilation systems surrounding the patient as risk factors for HAIs and expect that these find a place in HAI prevention guidelines in the future.

The employment of an earth-to-air heat exchanger as pre-treating unit of an air conditioning system for energy saving: A comparison among different worldwide climatic zones

A great fraction (20-40%) of primary energy is required for building air conditioning, so the use of renewable energy sources is increasing. The geothermal energy for Heating, Ventilating and Air Conditioning (HVAC) systems can be used considering an Earth-to-Air Heat eXchanger (EAHX). This work analyses the performance of an EAHX through a mathematical model (2D), as a function of diameter and length of the air ducts. The problem is solved with finite element method. A case study office building is analyzed. The air conditioning plant is characterized by fan-coil units and primary air; the EAHX is positioned upstream the Air Handling Unit (AHU) to pre-cool/pre-heat the air. The building is virtually placed initially in six Italian cities (different climatic zones according to Italian regulation DPR 412/93) and subsequently in eight worldwide cities according to Köppen climate classification. The following parameters are calculated: air temperature variation and thermal efficiency of the EAHX; the decreasing of cooling and heating capacity of the coils into the AHU. The best results refer to a duct length of 100 m for Ottawa (warm-summer humid continental climate, 65% capacity reduction), the worst ones for Rio de Janeiro (tropical wet and dry climate, maximum 24% reduction).

Development and Characterization of Thermal Flow Sensors for Non-Invasive Measurements in HVAC Systems

We investigated non-invasive flow rate measurements in heating, ventilation, and air conditioning (HVAC) systems utilizing thermal transduction instead of commonly used ultrasonic techniques. The proposed thermal flow transduction comprises two temperature sensors and a heater, all mounted non-invasively on the outer surface of metal-pipes and, therefore, not disturbing the fluid flow inside. One temperature sensor measures the heater temperature, whereas the other one, mounted upstream of the heater, follows the fluid temperature for reference. The temperature difference (i.e., the heater excess temperature) depends on the fluid flow velocity and can be used to derive the mean volume flow inside the pipe. Experimental characterizations were conducted using two sensor prototypes. Beside output characteristics, other main issues such as dynamic behavior and noise density were investigated in detail. Special attention was paid to error compensation allowing measurements within a large range of fluid temperatures. Measurement results confirm the feasibility of this approach, however with some constraints regarding response time.

A Thermal Flow Sensor Based on Printed Circuit Technology in Constant Temperature Mode for Various Fluids

We present a thermal flow sensor designed for measuring air as well as water flow velocities in heating, ventilation, and air conditioning (HVAC) systems. The sensor is designed to integrate the flow along the entire diameter of the pipe also quantifying the volume flow rate of the streaming fluid where the calorimetric principle in constant temperature operation is utilized as a readout method. In the constant temperature mode, a controller keeps a specific excess temperature between sensing elements at a constant level resulting in a flow dependent heater voltage. To achieve cost-effective sensors, the fabrication of the transducer is fully based on printed circuit board technology allowing low-cost mass production with different form factors. In addition, 2D-FEM simulations were carried out in order to predict the sensor characteristic of envisaged setups. The simulation enables a fast and easy way to evaluate the sensor’s behaviour in different fluids. The results of the FEM simulations are compared to measurements in real environments, proving the credibility of the model.

Outcome-based ventilation: A framework for assessing performance, health, and energy impacts to inform office building ventilation decisions

This article presents an outcome-based ventilation (OBV) framework, which combines competing ventilation impacts into a monetized loss function ($/occ/h) used to inform ventilation rate decisions. The OBV framework, developed for U.S. offices, considers six outcomes of increasing ventilation: profitable outcomes realized from improvements in occupant work performance and sick leave absenteeism; health outcomes from occupant exposure to outdoor fine particles and ozone; and energy outcomes from electricity and natural gas usage. We used the literature to set low, medium, and high reference values for OBV loss function parameters, and evaluated the framework and outcome-based ventilation rates using a simulated U.S. office stock dataset and a case study in New York City. With parameters for all outcomes set at medium values derived from literature-based central estimates, higher ventilation rates' profitable benefits dominated negative health and energy impacts, and the OBV framework suggested ventilation should be ≥45 L/s/occ, much higher than the baseline ~8.5 L/s/occ rate prescribed by ASHRAE 62.1. Only when combining very low parameter estimates for profitable impacts with very high ones for health and energy impacts were all outcomes on the same order. Even then, however, outcome-based ventilation rates were often twice the baseline rate or more.

Ecological succession of the microbial communities of an air-conditioning cooling coil in the tropics

Air-conditioning systems harbor microorganisms, potentially spreading them to indoor environments. While air and surfaces in air-conditioning systems are periodically sampled as potential sources of indoor microbes, little is known about the dynamics of cooling coil-associated communities and their effect on the downstream airflow. Here, we conducted a 4-week time series sampling to characterize the succession of an air-conditioning duct and cooling coil after cleaning. Using an universal primer pair targeting hypervariable regions of the 16S/18S ribosomal RNA, we observed a community succession for the condensed water, with the most abundant airborne taxon Agaricomycetes fungi dominating the initial phase and Sphingomonas bacteria becoming the most prevalent taxa toward the end of the experiment. Duplicate air samples collected upstream and downstream of the coil suggest that the system does not act as ecological filter or source/sink for specific microbial taxa during the duration of the experiment.

Comparison of methods to evaluate the fungal biomass in heating, ventilation, and air-conditioning (HVAC) dust

Heating, ventilation, and air-conditioning (HVAC) systems contain dust that can be contaminated with fungal spores (molds), which may have harmful effects on the respiratory health of the occupants of a building. HVAC cleaning is often based on visual inspection of the quantity of dust, without taking the mold content into account. The purpose of this study is to propose a method to estimate fungal contamination of dust in HVAC systems. Comparisons of different analytical methods were carried out on dust deposited in a controlled-atmosphere exposure chamber. Sixty samples were analyzed using four methods: culture, direct microscopic spore count (DMSC), β-N-acetylhexosaminidase (NAHA) dosing and qPCR. For each method, the limit of detection, replicability, and repeatability were assessed. The Pearson correlation coefficients between the methods were also evaluated. Depending on the analytical method, mean spore concentrations per 100 cm² of dust ranged from 10,000 to 682,000. Limits of detection varied from 120 to 217,000 spores/100 cm². Replicability and repeatability were between 1 and 15%. Pearson correlation coefficients varied from -0.217 to 0.83. The 18S qPCR showed the best sensitivity and precision, as well as the best correlation with the culture method. PCR targets only molds, and a total count of fungal DNA is obtained. Among the methods, mold DNA amplification by qPCR is the method suggested for estimating the fungal content found in dust of HVAC systems.