Air Quality and Comfort Characterisation within an Electric Vehicle Cabin in Heating and Cooling Operations

This work is aimed at the experimental characterisation of air quality and thermal profile within an electric vehicle cabin, measuring at the same time the HVAC system energy consumption. Pollutant concentrations in the vehicle cabin are measured by means of a low-cost system of sensors. The effects of the HVAC system configuration, such as fresh-air and recirculation mode, on cabin air quality, are discussed. It is shown that the PM concentrations observed in recirculation mode are lower than those in fresh-air mode, while VOC concentrations are generally higher in recirculation than in fresh-air mode. The energy consumption is compared in different configurations of the HVAC system. The novelty of this work is the combined measurement of important comfort parameters such as air temperature distribution and air quality within the vehicle, together with the real time energy consumption of the HVAC system. A wider concept of comfort is enabled, based on the use of low-cost sensors in the automotive field.

Energy-Efficient Retrofit Measures to Achieve Nearly Zero Energy Buildings

Considering the 2021 IPCC report that justly attributes our deteriorating climatic condition to human doing, the need to develop nearly zero energy building (nZEB) practices is gaining urgency. However, rather than the typical focus on developing greenfield net-zero initiatives, retrofitting underperforming buildings could create significant scale climate positive impacts faster. The chapter accordingly discusses energy-efficient retrofitting methods under three categorical sectors—visual comfort (daylight-based zoning, shadings); thermal comfort and ventilation (solar radiation-based zoning, central atrium plus interior openings, insulation, and window replacement); energy consumption (efficient lighting system, and controllers, material and HVAC system optimization, PV panels as the renewable energy source). This chapter further substantiates these theoretical underpinnings with an implemented design scheme—an educational building within a cold semiarid climatic condition—to showcase the on-ground impact of these retrofitting strategies in reducing the energy used for heating and cooling and lighting purposes.

Energy-Optimal Structures of HVAC System for Cleanrooms as a Function of Key Constant Parameters and External Climate

This article presents approximating relations defining energy-optimal structures of the HVAC (Heating, Ventilation, Air Conditioning) system for cleanrooms as a function of key constant parameters and energy-optimal control algorithms for various options of heat recovery and external climates. The annual unit primary energy demand of the HVAC system for thermodynamic air treatment was adopted as the objective function. Research was performed for wide representative variability ranges of key constant parameters: cleanliness class—Cs (ISO5÷ISO8), unit cooling loads —q˙j (100 ÷ 500) W/m2 and percentage of outdoor air—αo (5 ÷ 100)%. HVAC systems are described with vectors x¯ with coordinates defined by constant parameters and decision variables, and the results are presented in the form of approximating functions illustrating zones of energy-optimal structures of the HVAC system x¯* = f (Cs, q˙j, αo). In the optimization procedure, the type of heat recovery as an element of optimal structures of the HVAC system and algorithms of energy-optimal control were defined based on an objective function and simulation models. It was proven that using heat recovery is profitable only for HVAC systems without recirculation and with internal recirculation (savings of 5 ÷ 66%, depending on the type of heat recovery and the climate), while it is not profitable (or generates losses) for HVAC systems with external recirculation or external and internal recirculation at the same time.

Technologies Of Sustainability in Large Banks Buildings

Achieving energy efficiency is a very important step of applying the concepts of sustainability, this will reduce the financial costs that coming from energy consumption for the purposes of operating HVAC system so this concept will give a great effect on the environment and the economic aspects. Bank buildings are represented of the financial strength of the country, as they have a strong and direct impact on the reality of society and urban reality, and these buildings often consume a large amount of energy for cooling and heating purposes in the hot and dry climate of Iraq, so the research problem is focus on the knowledge deficiency of the importance of the role of technologies of sustainability in advancing the banking work at the design and performance level. Therefore, the aim of research was to find the knowledge aspects of designing the external envelope of the banking building in a sustainable manner that contributes to achieving energy efficiency and reducing the negative impact of banking buildings on the environment, as a result technique of sustainability and technological developments have led to the change and innovation in designing an advanced environment in banking buildings, such as achieving communication in the work environment in addition to providing comfort to the occupants in it, and this will lead to improved performance and production.

Reducing Virus Transmission from Heating, Ventilation, and Air Conditioning Systems of Urban Subways

Transmission via virus-carrying aerosols inside enclosed spaces is an important transmission mode for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), as supported by growing evidence. The urban subway is one of the most commonly used enclosed spaces. The subway is a utilitarian and low-cost transit system in today’s society. However, studies are yet to demonstrate patterns of viral transmission in subway heating, ventilation, and air conditioning (HVAC) systems. To fill this gap, we performed a computational investigation of the airflow (and the associated aerosol transmission) in an urban subway cabin equipped with an HVAC system. We employed a transport equation for aerosol concentration, which was added to the basic buoyant solver to resolve aerosol transmission inside the subway cabin. This was achieved by considering the thermal, turbulence, and induced ventilation flow effects. Using the aerosol encounter probability over sampling lines crossing the passenger breathing zones, we can detect the highest infection risk zones inside the urban subway under different settings. We proposed a novel HVAC system that can impede aerosol spread, both vertically and horizontally, inside the cabin. In the conventional model, the maximum aerosol encounter probability from an infected individual breathing near the fresh-air ducts was equal to 15%. This decreased to 0.36% in the proposed HVAC model. Overall, using the proposed HVAC system for urban subways decreased the mean value of the aerosol encounter probability by approximately 79% compared to that for the conventional system.

Enhancing Indoor Air Quality and Tackling COVID - 19 Virus

Objective/Scope One of the main concerns of Oil & Gas Plants and associated Buildings is how to improve indoor air quality (IAQ) and tackling viruses. IAQ can be affected, or may become under high risk by some of nearby gases, microbial contaminates or energy stressor that affect the HSE condition. This paper presents the main factors that been considered to provide practical solutions to achieve high IAQ and tackling viruses (such as COVID-19). Methods, Procedures, Process IAQ refers to the air quality within and around the plants/buildings. IAQ can usually be affected, or may become under high risk by nearby gases, particulates, microbial contaminates or any mass that affect 100% HSE. Inadequate air quality in building will increase the risk and impact on transferring viruses to people (such as COVID and Flue) and equipment performance (such as equipment failure, components corrosion and short circuits on control board). Survey and data was recorded to evaluate air quality performance in atmosphere instead of assuming it. Accordingly, the impact of inadequate IAQ was studied and evaluated. Results, Observations & Conclusions The international standard set a good IAQ in respect of gas concentration and human who works inside buildings in a way that less than 50% people should not detect any odor, 25% should not experience discomfort, 10% should not suffer from mucosal irritation and 5% should not experience annoyance. Study concluded that inadequate IAQ inside the building will affect people performance/health and installed equipment performance. In addition, improper HVAC system operation will be become breeding site for odor causing mold and bacteria, specifically on cooling coil. Hence, several technics were studied to improve IAQ, by installing Ultraviolet (UV) light to stop growing bacterial inside the HVAC system, installing chemical filter in air intakes to remove atmospheric dust, gases and bacteria by 100%, upgrading filtration efficiency to MERV-13 or highest achievable to capture at least 75 – 95% of airborne particles between 0.3 and 1.0 micron, increase outdoor air ventilation and temperature/humidity control. The performance of HVAC system and quality of air inside building were monitored by simulating IAQ based on ISO 16890, filters life cycle, energy consumption, and the results were found 100% satisfactory and provided solutions that are now successfully implemented in all new and some of the existing buildings. Novel/Additive Information There are several buildings with similar issues and these approach/technics now being adopted in new constructed/existing buildings to protect human and asset integrity, which will support ADNOC Way by sustaining safe environment operation, lower health risk, reduce of equipment failure, reduce maintenance cost and 100% HSE. There are numbers of occupied buildings across the world were surrounded by aggressive gases/pollution with poor IAQ and above approaches it can be followed to realize larger benefits.

Hybrid Random Forest and Support Vector Machine Modeling for HVAC Fault Detection and Diagnosis

The malfunctioning of the heating, ventilating, and air conditioning (HVAC) system is considered to be one of the main challenges in modern buildings. Due to the complexity of the building management system (BMS) with operational data input from a large number of sensors used in HVAC system, the faults can be very difficult to detect in the early stage. While numerous fault detection and diagnosis (FDD) methods with the use of statistical modeling and machine learning have revealed prominent results in recent years, early detection remains a challenging task since many current approaches are unfeasible for diagnosing some HVAC faults and have accuracy performance issues. In view of this, this study presents a novel hybrid FDD approach by combining random forest (RF) and support vector machine (SVM) classifiers for the application of FDD for the HVAC system. Experimental results demonstrate that our proposed hybrid random forest–support vector machine (HRF–SVM) outperforms other methods with higher prediction accuracy (98%), despite that the fault symptoms were insignificant. Furthermore, the proposed framework can reduce the significant number of sensors required and work well with the small number of faulty training data samples available in real-world applications.