Actual Rate Research Articles

Direct yaw moment control of eight-wheeled distributed drive electric vehicles based on super-twisting sliding mode control

This paper proposed a novel direct yaw moment control (DYC) system to enhance vehicle stability and handling performance in various driving conditions and overcome the chattering problem of traditional sliding mode control. Accordingly, a DYC strategy is developed for eight-wheeled DDEVs by utilizing a super-twisting sliding mode (STSM) algorithm. Initially, a three-degrees-of-freedom model, nonlinear tire model, and motor model are established for vehicles. Subsequently, the reference yaw rate is obtained based on the reference model of the vehicle to serve as a control target. The DYC strategy is then established using the error between the actual yaw rate and the reference yaw rate as the input. Moreover, a traditional sliding mode (SM) controller is developed to enhance vehicle stability. A second-order SM controller is designed by incorporating a STSM control algorithm to address the chattering problem associated with traditional SM controllers. The algorithm adaptively adjusts the sliding surface and controls the gains based on the dynamic state of the vehicle. The effectiveness of the proposed control strategy is validated via hardware-in-the-loop simulations.

Probabilistic corrosion hazard maps for reinforced concrete infrastructure in coastal regions

The development of probabilistic corrosion hazard maps for reinforced concrete infrastructure exposed to airborne chlorides in coastal regions is addressed in the present work, with special attention to bridges. The methodology developed in this study consists of three steps. Initially, spatial distribution, construction year, and main features of the existing infrastructure are examined together with the general characteristics of the study area. The second step deals with the elaboration of relevant environmental data, including the direction and height of sea waves, sea salinity, temperature, relative humidity, rainfall, speed and direction of wind, and chloride deposition rates. Corrosion hazard maps are obtained next, wherein the corrosion current density is selected as an intensity measure. Particularly, they are elaborated for an assigned probability of exceedance given the exposure time window and concrete mixture. The presented methodology is applied to develop probabilistic corrosion hazard maps for reinforced concrete bridges exposed to the marine atmosphere at Oahu Island (Hawaii, United States). For this case-study, it is also discussed the correlation between the actual condition rating of the existing concrete bridges and the estimated corrosion hazard levels.

Analysis of Affecting Variables Actual Inflation Rate at Indonesia

The discussion in this empirical study is to find out what variables can influence the achievement of the actual inflation rate variable in Indonesia in the last ten years. The writer considers that achieving the actual inflation rate targeted by a Central Bank is not simply related to supply and demand imbalances for primary goods alone, but more broadly than that related to dynamic micro and macroeconomic conditions. The writer initially suspected that variables such as the inflation target rate, previous inflation rate, loan interest rate, and gross domestic product had a significant influence on fluctuations in the actual inflation rate in Indonesia. After statistical tests were carried out using the secondary data in the form of the rates of the four independent variables and the actual inflation rate in Indonesia as the dependent variable every year for the last ten years it’s found that only the loan interest rate had a significant and positive effect on the actual inflation rate in Indonesia. which means that the higher the loan interest rate will also increase the actual inflation rate. The three other variables tested in this empirical study, namely the inflation target rate, the previous inflation rate, and the gross domestic product rate, did not have a significant effect.

Experiments on capacitance based liquid flow meter with parallel channels used in two-phase

A new flow meter has been proposed to measure liquid mass flow rate in a two-phase system. Irrespective of the input flow, the proposed system transforms incoming stream into laminar stratified flow. This configuration offers a promising avenue for assessing liquid flow rates in a two-phase system by leveraging measurements of liquid column height. Extensive performance assessments have been conducted for different vapour and liquid flows. Since the fluid properties are taken into consideration for designing the system, the temperature dependence on the performance of the flow meter also has been studied. The outcome of these studies has yielded a robust correlation between the actual liquid flow rate and the value deduced from the observed liquid column height. The correlation developed between the actual liquid flow rate and that determined from the height of fluid was accurate with an error of ± 3.8 %. It is also found that this flow meter is capable enough to determine the changes in flow conditions with temperature and would provide flow measurements within an error of ± 4 %. This novel two-phase flow meter not only advances the precision of liquid mass flow rate measurements but also demonstrates its adaptability in accommodating changing flow conditions, particularly those driven by temperature dynamics. The findings presented herein underscore the potential of this innovative flow meter as a reliable tool for accurate flow rate determination in diverse industrial applications such as cryogenics, superconductivity, etc.

The Relationship Between Popularization of Higher Education and Unemployment Rate in China

As a result of the reform and opening, as the Chinese government and society have paid more attention to education, the popularization of education has gradually taken shape, followed by a more complex social structural population, traditional calculations of unemployment rate and gross enrollment rate. The method is no longer suitable for todays social situation. This article is based on Martintrow's three-stage theory of higher education, and the formula used frequently by China's National Bureau of Statistics to calculate urban jobless rates. Assuming the actual unemployment rate calculation formula, regression analysis shows that the higher the degree of higher education, the unemployment rate will also increase accordingly. Government macro-control, the expansion of vocational education, filling the professional labor force gap currently present in society, appropriately regulating the percentage of the population receiving higher education, elevating the status of vocational education, eradicating preconceived notions previously held against vocational education, etc. are all ways that educational development can be accomplished. There were a number of macro and micro control measures developed.

Long-term continuous monitoring of methane emissions at an oil and gas facility using a multi-open-path laser dispersion spectrometer

A method for methane emissions monitoring at industrial facility level was developed based on a high precision multi-open-path laser dispersion spectrometer combined with Bayesian analysis algorithms using Monte Carlo Markov Chain (MCMC) inference. From the methane path-averaged concentrations spatially distributed over the facility under study, together with the wind vector, the analysis allows detection, localization and quantification of fugitive methane emissions. This paper describes the very first long term (3 months), continuous (24 h/7 days) deployment of this monitoring system at an operational gas processing and distribution facility. The continuous monitoring system, made of the combination of the open-path high-precision (<10 ppb) methane concentration analyser and the data analysis method, was evaluated with controlled releases of methane of about 5 kg/h for short periods of time (30–60 min). Quantification was successful, with actual emission rates lying well within the quoted uncertainty ranges. Source localisation was found to lack accuracy, with biases of 30–50 m in the direction of the line of sight of the spectrometer, due to the short duration of the controlled releases, the limited wind vector diversity, and complications from air flows around buildings not accounted for by the transport model. Using longer-term data from the deployment, the MCMC algorithm led to the identification of unexpected low intensity persistent sources (<1 kg/h) at the site. Localisation of persistent sources was mostly successful at equipment level (within ~20 m) as confirmed by a subsequent survey with an optical gas imaging (OGI) camera. Quantification of these individual sources was challenging owing to their low intensity, but a consistent estimate of the total methane emission from the facility could be derived using two different inference approaches. These results represent a stepping stone in the development of continuous monitoring systems for methane emissions, pivotal in driving greenhouse gas reduction from industrial facilities. The demonstrated continuous monitoring system gives promising performance in early detection of unexpected emissions and quantification of potentially time-varying emissions from an entire facility.

Research on the construction and verification of evaluation model for borehole collapse in gas extraction

To improve the precision prevention of gas extraction borehole deformation and collapse, it is an important prerequisite to achieve precise monitoring of boreholes. This work is based on distributed optical fiber monitoring and Brillouin Optical Time Domain Analysis Technique (BOTDA). We carried out simulation and validation experiments of borehole plugging with different particle size ratios, constructed a mathematical model for calculating the plugging rate (denoted by ω) of boreholes, and put forward a new methodology for accurate monitoring and evaluation of gas extraction boreholes. The experimental results show that there is a linear relationship between the strain of optical fiber (denoted by ε), the accumulation mass of the simulated coal samples (denoted by m), and the deformation collapse of the borehole. And a mathematical model for calculating the plugging rate of boreholes with more universality has been built by introducing the ratio, volumetric, and strain correction coefficients (denoted by φ, β, and γ). Based on the verification experiment, it was found that the change in the actual and theoretical plugging rates is consistent. With the increase in the ratio of medium coal (2.0–5.0 cm), the plugging rate error decreases first and then increases. The maximum errors are −18.36 % and 19.04 %, but the plugging rate results are still within the middle boundaries of the collapsed boreholes (29.31 % to 75.07 %) and have a neglected effect on the stage classification. Inevitable errors in model construction and actual accumulation errors are two important factors contributing to errors in mathematical models. Taking ω as 0 %, 27.71+40.05·rord.-2%, 74.50+14.13·rord.-2%, and ε limit value 143.77·φ·γ με as the critical value to distinguish the primary, middle, and late periods of borehole collapse. In this work, a new technology of borehole monitoring and evaluation with plugging rate and strain critical value as evaluation indexes is proposed, which can provide a reference for accurate monitoring of drainage boreholes and gas prevention.

Aftershock forecasts based on incomplete earthquake catalogues: ETASI model application to the 2023 SE Türkiye earthquake sequence

SUMMARY The epidemic-type aftershock sequence (ETAS) model is the state-of-the-art approach for modelling short-term earthquake clustering and is preferable for short-term aftershock forecasting. However, due to the large variability of different earthquake sequences, the model parameters must be adjusted to the local seismicity for accurate forecasting. Such an adjustment based on the first aftershocks is hampered by the incompleteness of earthquake catalogues after a mainshock, which can be explained by a blind period of the seismic networks after each earthquake, during which smaller events with lower magnitudes cannot be detected. Assuming a constant blind time, direct relationships based only on this additional parameter can be established between the actual seismicity rate and magnitude distributions and those that can be detected. The ETAS-incomplete (ETASI) model uses these relationships to estimate the true ETAS parameters and the catalogue incompleteness jointly. In this study, we apply the ETASI model to the SE Türkiye earthquake sequence, consisting of a doublet of M 7.7 and M 7.6 earthquakes that occurred within less than half a day of each other on 6 February 2023. We show that the ETASI model can explain the catalogue incompleteness and fits the observed earthquake numbers and magnitudes well. A pseudo-prospective forecasting experiment shows that the daily number of detectable m ≥ 2 can be well predicted based on minimal and incomplete information from early aftershocks. However, the maximum magnitude (Mmax ) of the next day’s aftershocks would have been overestimated due to the highly variable b value within the sequence. Instead, using the regional b value estimated for 2000–2022 would have well predicted the observed Mmax values.

Al and Autonomous Systems: An Experiment in Industry 5.0 Transformation

Important practical consequences are shown in this experimental study of AI and autonomous systems integration in the context of Industry 5.0. AI optimization of the product manufacturing process resulted in a 35% decrease in the real faulty rate and a significant 20% rise in production rates, reaching an actual rate of 1440 units per hour. The actual defective rate was just 1.3%. Since autonomous robots were introduced, work completion rates have increased by 18%, totaling 2,520 tasks completed, and maintenance expenses have decreased by 9%, amounting to a $450 real cost savings. Furthermore, with an actual faulty rate of 2.6%, the AI-driven quality control method showed an astounding 35% decrease in defective goods. Ultimately, significant 15% energy consumption decrease was accomplished using AI-based energy optimization solutions, translating into real energy savings of 1,500 kWh. These results highlight the real advantages of combining AI and Autonomous Systems in Industry 5.0, such as increased productivity, lower costs, better product quality, and sustainability.

The causation dilemma in ESG research

&lt;abstract&gt; &lt;p&gt;The ESG literature suggests that the relationship between a firm's environmental, social, and governance (ESG) performance and a firm's financial performance is positive, but the causal link between these two variables is ambiguous. The results in this study mirrored that sentiment of the ESG literature; thus, the purpose of this article is to frame the causal ambiguity in ESG research that accounts for ambiguous conclusions in ESG literature. This study found that firms with complete Bloomberg ESG ratings had higher abnormal returns than firms without complete ESG ratings, but the actual rating did not correlate with abnormal returns. Similarly, this study found that firms with higher ESG disclosure scores (regardless of whether the disclosures were good or bad) were associated with higher abnormal returns, which further illustrates the ambiguity and suggests transparency as a clarifying factor. While much of the literature notes challenges in ESG research, this study is one of the first that frames the confusing causal link between ESG performance and financial performance as the key conclusion of the study.&lt;/p&gt; &lt;/abstract&gt;

Full-flow surface defect identification method based on spot scanning scattering for unpatterned wafer

As the critical dimensions of semiconductor manufacturing processes gradually decrease, the requirements for production yield management become increasingly stringent. During the manufacturing process, there are many different types of defects, such as micron-sized particles, millimeter-sized scratches, etc. Multiple categories and different scales bring great challenges to the detection and identification of defects. This paper provides a full-flow surface defect identification method based on spot scanning scattering for unpatterned wafers. First, an adaptive threshold method with dynamic kernel windows is used to perform line-by-line scanning inspection of the wafer Mercator image. The 3σ decision strategy is used to avoid the impact of defects on background estimation and to improve detection sensitivity. After morphological processing, connected domain analysis is performed to obtain the defect mask, and feature information such as the shape, size, and distribution of the defect is extracted. Finally, the defect identification is performed by rules based binning, and the identified defects are converted into wafer polar coordinate image for display and analysis. In the experiments, the proposed method is used to identify micron-scale particles as well as large scratches on the millimeter scale for SiC wafers. Relative to the actual production rate requirement of 20 wafers per hour, the analysis time for a 6-inch wafer is 24.4 s, which can meet the requirement. Meanwhile, the test results illustrate the effectiveness of the method. The proposed method is recommended for early-stage defect detection and identification of unpatterned wafers.

Photosynthetic adaptation mechanisms of waterlogged wheat (Triticum aestivum) at flowering under exogenous nitric oxide donor application

AbstractThe effects of nitric oxide (NO) on the photosynthetic adaptation mechanisms of wheat plants in waterlogging during the flowering stage are poorly understood. Field and pot experiments using two cultivars were conducted with three treatments: waterlogging (WL), waterlogging plus NO donor sodium nitroprusside (WLsnp), and adequate water (CK). The results indicated that the WLsnp and CK treatments exhibited significantly higher 1000‐kernel weight and yield than the WL treatment because of high photosynthetic potential(P&lt;0.05). We found that the photosynthetic performance, including photosynthetic rate (Pn), stomatal conductance (gs), mesophyll conductance (gm), carbon dioxide concentration at the carboxylation site (Cc), maximum carboxylation rate (Vcmax), maximum electron transfer rate (Jmax), actual electron transfer rate (J), actual PSII efficiency (ΦPSII) and potential maximum efficiency in PSII (Fv/Fm), was significantly improved in the WLsnp treatment compared to the WL treatment, both during waterlogging and after de‐waterlogging. Little difference was observed in the photosynthetic performance between the WLsnp and CK treatments during waterlogging for cultivar YM15 and after de‐waterlogging for cultivar YM24. Further analysis indicated that gs, gm and J were identified as key physiological indicators that synergistically regulate Pn of waterlogged wheat plants. Overall, the improvement of wheat's waterlogging resistance capacity after spraying NO is mainly related to high gs, great gm, and high J.

A rapid determination of wheat flours components based on near infrared spectroscopy and chemometrics

In this work, a rapid and simple analytical method for the quantitative determination of moisture, protein, wet gluten, starch and sedimentation index in the wheat flour was established by the combination of near infrared spectroscopy and chemometrics. The spectra of the 229 wheat flour samples were collected by a portable near infrared fast analyzer. The contents of these components were determined according to the relevant Chinese National Standards, and were taken as the corresponding reference database. Seven spectral pretreatment methods were employed to eliminate the optical interference from background and other noise information. The best result was obtained with FD+SG(15, 3)+MC method for moisture, protein, wet gluten and sedimentation index, FD+SG(15, 2)+MC method was more suitable for starch. The principal component numbers (PCs) were also optimized to obtain a superior model effect. Furthermore, partial least squares (PLS) and multiple linear regression (MLR) modeling methods were used to quantify the content of the components. When using FD+SG(15, 3)+MC pretreatment, all the PLS model parameters were significantly better than the MLR model. Both the predicted values and the reference values showed superior linear relationship within the calibration range. Moreover, the absolute error of the predicted values and their corresponding reference values in the PLS model were within their confidence intervals, respectively. The relative errors for moisture, protein, wet gluten and starch fluctuated little, only sedimentation index fluctuated greatly. The actual prediction correct rate of moisture, protein, wet gluten, starch and sedimentation index were 96.8%, 96.8%, 90.3%, 100.0% and 80.6%, respectively, which indicated the prediction was excellent.

Nonparametric bootstrap methods for hypothesis testing in the event of double-censored data

&lt;abstract&gt;&lt;p&gt;This paper illustrated how nonparametric bootstrap methods for double-censored data can be used to conduct some hypothesis tests, such as quartiles' hypothesis tests. Through simulation studies, the smoothed bootstrap (SB) method performed better results than Efron's method in most scenarios, particularly for small datasets. The SB method provided smaller discrepancies between the actual and nominal error rates.&lt;/p&gt;&lt;/abstract&gt;

A quantum digital signature protocol with state preparation error tolerance

&lt;sec&gt;The quantum digital signature (QDS) has attracted much attention as it ensures the nonrepudiation, unforgeability, and transferability of signature messages based on information-theoretic security. Amiri et al. (&lt;ext-link ext-link-type="uri" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="https://doi.org/10.1103/PhysRevA.93.032325"&gt;&lt;i&gt;Phys. Rev. A&lt;/i&gt; &lt;b&gt;93&lt;/b&gt; 032325&lt;/ext-link&gt;) proposed the first practical QDS protocol based on orthogonal coding, which has realized information-theoretic security and become the mainstream paradigm in QDS research. The procedure of QDS involves two essential stages, the one is the distribution stage, in which Alice-Bob and Alice-Charlie individually utilize the three-intensity decoy-state quantum key distribution protocol but without error correction or privacy amplification, namely, key-generation protocol, to generate correlated bit strings, the other is the messaging stage, in which Alice transmits signature messages to the two recipients.&lt;/sec&gt;&lt;sec&gt;However, previous theoretical and experimental studies both overlooked the modulation errors that may be introduced in the state preparation process due to the imperfections in modulator devices. Under the traditional framework of GLLP analysis method, these errors will significantly reduce the actual signature rates. Therefore, we propose a state-preparation-error tolerant QDS and use parameter analysis to characterize the state preparation error to make the simulation analysis more realistic. In addition, we analyze the signature rates of the present scheme by using the three-intensity decoy-state method.&lt;/sec&gt;&lt;sec&gt;Compared with previous QDS protocols, our protocol almost shows no performance degradation under practical state preparation errors and exhibits a maximum transmission distance around 180 km. Furthermore, state preparation errors do not have a significant influence on the bit error rate induced by normal communication between the legitimate users or the one produced by an eavesdropper. These results prove that the method proposed in this paper has excellent robustness against state preparation errors and it can achieve much higher signature rates and signature distances than other standard methods. Besides, signature rates are basically unchanged under different total pulse numbers, which shows that our protocol also has good robustness against the finite-size effect. Additionally, in the key generation process, our method is only required to prepare three quantum states, which will reduce the difficulty of experiment realizations.&lt;/sec&gt;&lt;sec&gt;Furthermore, the proposed method can also be combined with the measurement-device-independent QDS protocol and the twin-field QDS protocol to further increase the security level of QDS protocol. Therefore, our work will provide an important reference value for realizing the practical application of QDS in the future.&lt;/sec&gt;

Quantitative Evaluation of Liquid Permeability in Cracked Oilwell Cement Sheaths

Summary Understanding the consequences of cracking in oilwell cement sheaths is crucial to evaluating the leakage scenarios that can lead to sustained casing pressure. However, the theoretical equations commonly used to estimate flows and permeabilities tend to overestimate actual flow rates through cracks, primarily due to the omission of key factors such as crack tortuosity, surface roughness, and self-healing processes. Therefore, experimental methods are required to quantify the influence of these factors and define “empirical reduction factors.” Because each material exhibits its own unique effects on flow behavior, empirical reduction factors must be determined for each specific material, including oilwell cement. This paper presents a comprehensive procedure for systematically measuring flows, determining permeabilities, and evaluating self-healing processes in deliberately cracked cement specimens with controlled crack widths. The procedure considers pressure gradients and crack widths relevant to oilwell conditions aiming to contribute to the development of more accurate models and simulations for cemented oil wells.

Joint optimization of two-dimensional warranty period and maintenance strategy considering availability and cost constraints

Abstract Warranty can improve customer satisfaction and increase product sales, but it will bring additional economic burden to manufacturers, so making reasonable warranty decisions is particularly important. The current research focuses more on the interests of manufacturers, while there is less attention paid to indicators that consumers are concerned about, such as system availability. To solve this problem, a joint optimization model of the two-dimensional warranty period and preventive maintenance (PM) strategy considering availability and cost constraints was established. Based on the failure dependence analysis of multi-component systems, the actual failure rate function is constructed by using the failure dependence coefficient matrix. Based on the comprehensive consideration of imperfect PM and minimum maintenance, the two-dimensional warranty cost model and system availability model are established, respectively. Aiming at maximum availability and considering the warranty cost budget constraint, a joint optimization model of the two-dimensional warranty period and PM strategy was built, and a model-solving algorithm combining grid search and binary search was introduced. The effectiveness of the model is verified by the case analysis, and the necessity of the PM strategy and considering failure dependence are reflected in the model comparative analysis and parameter sensitivity analysis. Finally, reasonable suggestions are put forward for manufacturers’ warranty decisions through the result analysis.

Multi-stage hydraulic fracturing simulation methodology at the wells of the gas condensate field X

The purpose of this work is to select the optimal method for multi-stage hydraulic fracturing simulation at the wells of a large gas condensate field X in conditions of low-permeability reservoirs and potential risk of condensate loss in the near bottomhole zone with a decrease in reservoir pressure. At the moment, there are many ways to simulate hydraulic fracturing, each of which is characterized by its advantages and disadvantages. For specific simulation conditions, it is necessary to choose the most optimal method of hydraulic fracturing simulation, which allows you to correctly simulate all the effects that are expected during development. Within the framework of the current work, the most common numerical methods of hydraulic fracturing simulation were described in abstract, their advantages and disadvantages for specific conditions of field X were reflected. Special attention was paid to the comparison of hydraulic fracturing simulation techniques using virtual perforations and local grid refinement, since these techniques are the most common ways to set hydraulic fracturing in existing hydrodynamic simulators. Scenario calculations were carried out, which made it possible to determine the limits of applicability of various methods, compare the correctness of reproducing downhole effects, quantify the deviation of the calculation results of different methods from the reference calculation. In addition, in the course of the work, various features of the application of the hydraulic fracturing simulation through local grid refinement were described, which were revealed experimentally. As a result, for multi-stage hydraulic fracturing simulation was used a method in which the cells with hydraulic fracturing are logarithmically chopped relative to the original grid. This method allows to simulate the actual rate of decline in well productivity in conditions of low reservoir permeability, and also allows to simulate in the hydrodynamic model the effect of condensate precipitation in the near bottomhole zone and the subsequent decrease in gas productivity.

Forecasting the cryptocurrency exchange rate based on the ranking of expert opinions

To date, most existing cryptocurrency exchanges do not have in their arsenal tools that would allow them to verify and investigate the information disseminated on social networks regarding a particular cryptocurrency. This makes it possible to conduct a relevant research with the subsequent development of a tool that, if used correctly, will provide users with advisory advice on further actions in relation to the cryptocurrency under study in the system. Based on this advice, interested parties will be able to adjust their decisions regarding further financial steps. The basis of most recommender systems is always the need to identify some influencing factors, which are later given certain weights to facilitate and simplify the formulation of further advice for users. In this paper, we study the influence of celebrity publications on the formation of prices for a particular cryptocurrency at a certain point in time. The importance and existence of this influence was previously proven by statistical methods. The purpose of the study is to develop an algorithm for studying the level of influence of posts of each of the selected group of experts in social networks on the cryptocurrency rate. The object of the study is the forecast of cryptocurrency rates. The input data used were the list of experts whose level of influence will be studied, the time interval of the study, the number of posts made by each of the experts in question over the specified period of time, and the actual cryptocurrency rates for the relevant period. The experts were well-known personalities who are either knowledgeable in the field of finance in general and cryptocurrencies in particular, or whose activities are somehow related to a particular cryptocurrency. Research methods. Experts are ranked based on the full probability and Bayesian formulas. Forecasting of cryptocurrency rates in a selected period of time is carried out using the algorithm for forecasting cryptocurrency rates based on expert posts on social networks (AUDSM). To control the accuracy of forecasts, the relative average error is calculated. Recommendations for financial transactions with cryptocurrencies are formed by entering the critical value of the exchange rate and calculating the arithmetic mean of cryptocurrency exchange rates for a specified period of time. Results. As a result of the research, an algorithm has been developed that allows taking into account the impact of the posts of each of the selected ranked group of experts on changes in the rates of a particular cryptocurrency. On the basis of the obtained forecasts, the paper presents a methodology for forming recommendations for financial transactions with them.

Enhancing Indoor Air Quality and Regulatory Compliance: An In-Depth Comparative Study on Ventilation Strategies and Their Impact on SARS-CoV-2 Transmission Risk

Enclosed-space ventilation plays a pivotal role in enhancing indoor air quality (IAQ). Various regulations and guidelines determine minimum fresh air requirements, varying by the application, country, etc. The present study employs real-time indoor CO2 measurements to calculate the actual air change rate (ACH) and models the building’s compliance with Chartered Institution of Building Services Engineers (CIBSE) guidelines to assess its impact on IAQ. The contaminant considered is the SARS-CoV-2 virus with multiple infectors, and the study calculates the virus’s transmission risk under different scenarios. Fresh air is assumed to be provided by mechanical or hybrid ventilation. The results reveal that the current building conditions are unacceptable, showing a significant gap from the recommended guideline rates. Meeting CIBSE recommendations ensures indoor air safety in terms of CO2 concentration. However, in extreme conditions with five infectors, findings show a 14% reduction in mechanical ventilation efficacy. Among the hybrid ventilation scenarios, combining CIBSE rates with natural ventilation, with a 30% door and window opening from the class outset, proves most effective in reducing the virus’s transmission risk, with a 58–70% reduction from the building’s current condition. Furthermore, implementing supplementary measures like air cleaners resulted in an additional 28–50% reduction in transmission risk.