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Abstract Due to the limited hydrophobic properties of porcelain insulators, applying anti-pollution flashover coatings is crucial to enhance their functionality. This research outlines a classification system for assessing contamination levels on 22 kV porcelain insulators, both with and without coatings. It synthesizes six classification criteria derived through both numerical simulations and experimental studies to effectively gauge contamination severity. The study examined insulators treated with Room Temperature Vulcanizing (RTV) silicone under three different conditions: uncoated, partially coated, and fully coated. Additionally, the research assessed the effects of humidity on these polluted insulators to understand environmental impacts on their performance. The criteria, which are the flashover voltage (x1), fifth to third harmonics of leakage current (x2), maximum electric field (x3), total harmonic index (x4), insulation resistance (x5) and dielectric loss (x6), were proposed for evaluating the insulator’s string condition. The finite element method (FEM) was used to simulate an electric field. Then, based on the proposed criteria, the performances of the Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Multi-layer Perceptron (MLP) have been trained and compared to classify polluted insulator conditions with and without coating. The established criteria facilitate precise monitoring of the condition of high-voltage insulators, ensuring quick and effective responses that support the stability of the electrical power system.

This work introduces a wideband metamaterial (MM) absorber designed to operate effectively across a wide reception angle and be polarization-insensitive within ISM band (2.4 GHz) applications. The proposed absorber unit cell comprises four copper sectors loaded with lumped resistors and a full copper ground plane hosted onto two FR4 substrates. Furthermore, an air layer suspended between the ground plane and a FR4 substrate is applied to achieve wideband absorption. In addition, the simulation results show that particular design factors, such as lumped resistors and unit cell geometry, can be optimized to improve the efficiency of the absorber. The simulations demonstrate that the proposed absorber achieves a wideband absorption, exceeding 90%, over a broad frequency range from 1.94 GHz to 2.98 GHz. The designed absorber was fabricated and tested, and the simulation and measurement results were agreed well.

Environmental monitoring for the detection and regulation of toxic gases is of paramount importance. This study proposes the modeling and fabrication of MEMS devices based on the standard Polysilicon Multi-Users MEMS Process (PolyMUMPs) for acetone gas detection. Titanium dioxide ( $TiO_{2}$ ) nanoparticles has been incorporated onto the top sensor’s surface, amplifying its detection sensitivity. The study delves into Electrothermal mechanisms that has integrated with the embedded microheater to induce thermal forces. This enhancement significantly improves the acetone gas detection capabilities of the device with high sensitivity and low detection limit. Results include the displacement amplitude of the uncoated PolyMUMPs sensor, with exploration of the coated device’s behavior under different heating voltages. Electrothermal actuation is employed, and the output voltage is measured using an MS3110 universal capacitive readout circuit. Comparisons of uncoated and coated devices has been investigated, demonstrating the influence of the sensing material that improve the detection performance. This investigation delves into the impact of varying coating thickness on the PolyMUMPs sensor’s performance. The mass sensitivity of the device is found to be 3.8574 mHz/pg, while the detection limit indicates that the device can detect up to 44 part per billion (ppb) at resonance frequency of 7.627 kHz.

The aim of this work is to model the influence of uneven contamination distribution under various humidity on the pollution flashover voltage of 11 kV porcelain insulator disc. Four scenarios of contamination distribution were proposed to test the sample under various severities of contamination simulated by salt deposit density (SDD). Series flashover experiments on contaminated insulators were performed under various conditions. The voltage of flashover under clean condition was appointed as a reference value for analyzing the effect of pollution. Based on the percentage value of breakdown voltage of the contaminated insulator to the clean insulator, the conditions of the tested sample are classified into three categories namely normal (55–60%), caution (45–54 %) and severe (35–44%). In the experimental tests, the uneven contamination area dimension was taken into consideration. An artificial neural network (ANN), derived from experiment results was used as a tool to predict the flashover voltage. The ANN method is built with five inputs related to the geometry of the sample and pollution factors while the flashover voltage was set as the model's output. The results showed that the distribution of pollutants according to the presented scenario has a significant impact on the performance of the flashover voltage. In addition, the error value between the experiment outcomes and the prediction system appeared to be less than 6%. This suggests that the proposed ANN model can be an effective tool in forecasting the insulators’ flashover voltage under test.

Polymeric insulators, in particular silicone rubber (SIR) are lightweight, have good hydrophobicity characteristics, and are easy to carry and install. They are commonly used for outdoor insulation in power lines. However, pollution, UV radiation, temperature, discharge, wetness, and stress can cause them to degrade over time, losing their electrical properties. Therefore, evaluating the ageing and degradation of polymeric insulators under different conditions becomes crucial. This paper investigates the ageing effects of the polymeric insulators with differences in pollution, applied voltage, hydrophobicity class, and geometrical structures of insulators. The investigation includes the experimental tests of the insulators’ electrical properties such as leakage current and flashover voltage, after assessing the initial characteristics of insulators based on their age and supply voltage. In addition, the aged polymeric insulator model based on an equivalent circuit model was developed to determine the leakage current and breakdown voltage of aged insulators. Moreover, an artificial neural network model is carried out to predict the critical leakage current and flashover voltage of the insulator under the ageing effect. The experiment results were used to validate the accuracy of the proposed models; with an aggregate error of less than 10%, the proposed models appeared to be satisfactory. These models can serve as a scholarly resource for designing, operating, and maintaining insulators, especially in polluted environments.

Abstract The monitoring of leakage current (LC) and voltage characteristics in transmission line insulators is regarded as a good technique for anticipating the physical state of in-service insulators. In the current work, the temporal and frequency characteristics of LC and voltage under various situations were derived for assessing the health condition of porcelain, glass, and silicone rubber insulators. The contamination severity indicated by soluble deposit density, wetting level (Wt), non-soluble deposit density, and uneven pollution distribution (Pu/PL) were chosen as the environmental factors that impact the insulators. Six criteria were utilized to evaluate the physical state of the insulators, with four of those derived from the LC signal in the time domain, namely, the LC signal peak (C1), the phase shift between applied voltage and LC (C2), the LC signal slope between two consecutive peaks (C3), and the crest factor (C4). The remaining two indices, namely, the total harmonics distribution (C5) and the harmonics ratio indicator (C6), were obtained from the frequency domain of the LC signal. In addition, the flashover voltage index (C7) was also employed. The LC indicators were then classified based on the laboratory test results to reflect the physical state of the insulators. The findings revealed that the proposed indicators had an important impact in determining the physical state of the insulators. Furthermore, a confusion matrix was created for the test and prediction data using the suggested indicators to determine the effectiveness of each indicator.

Optimization becomes more valuable when the optimal variables decision can consider sensitivity analysis. To get optimum results quickly, this study established a synthetic sensitivity analysis and multi-objective optimization approach, which is combined with an energy simulation framework characterized by parallel processing. To discover the final optimal solutions, the optimization procedures were carried out under two scenarios. To investigate the impact of each design variable on the optimization goals in order to select the variables with the greatest impact for inclusion in the final optimization, a sensitivity analysis was carried out. In the first scenario, the link between design variables and objective functions is thoroughly examined, and the ultimate impacts of optimum design variables are examined. The purpose of this study is to look at the effect of thermal envelopes on energy performance for subterranean enclosed spaces in Malaysia's tropics, to determine the best design parameter values for enclosed underground spaces and to introduce suitable variables for thermal comfort and energy performance. The optimization results confirm that while considering two objective functions of thermal and energy performance by using different optimization parameters design that as one of the objectives decreases, the other objective increases. The final optimal solutions showed that, it is possible to decrease the cooling energy for underground spaces, by up to 58.33% of total hours of the year, respectively, while maintaining occupants’ thermal comfort in the acceptable range, by up to 26.84%.

Over the past decades, extensive experimental-based research works have been carried out to investigate the flashover phenomenon on the performance of polluted transmission line insulators. The critical focus has been on developing methods that can determine the safety, reliability, and sustainability of the overall power transmission network based on experimental results obtained from polluted insulators’ flashover voltage tests. In this paper, a systematic review of available scientific works, published as early as the 1990s, for the analysis of pollution flashover voltage, is undertaken. The review mainly focuses on factors influencing the efficiency of transmission line insulators under polluted conditions. Specifically, publication databases utilizing various synonyms and keywords associated with the terms “contaminated insulators” and “flashover voltage test” have been scrutinized. The search has resulted in 1364 articles, from which 97 articles have satisfied the review requirements and have been subsequently analyzed to determine the parameters associated with polluted insulators. Major factors that affect the performance of insulators, including electrical and environmental impacts, are discussed. Variations in factors affecting flashover test development and insulator efficiency are also considered. Overall, the current analysis provides an important insight toward successful evaluations of the health of transmission line insulators and research advancements of electric power transmission line insulators.

Construction of multifunctional building envelopes using vertical greenery walls (VGW) has emerged as a sustainable green technology to improving cooling efficiency. To attaining the desired level of building cooling performance, VGW and overall thermal transfer value (OTTV) of the walls are useful design factors. The study aims to revise the current VGW evaluation, considering the decreased heat flux due to thermal efficiency of wall construction based on OTTV values. To achieve this, OTTV based Building Information Modelling (BIM) simulation method was proposed using Autodesk-Revit and DesignBuilder simulation based on EnergyPlus. Six wall compositions with various OTTV values of south facade for residential buildings located in sub-tropical in cooling season, were evaluated. The findings demonstrate that in the presence of a green system, a good OTTV value of the exterior walls is required for optimal performance, to keep the space within set point of cooling for long time during the cooling season. The comparisons between the bare walls and the VGW have demonstrated a great variation due to the different OTTV reached up to 6.57% and 18.44% reduction in indoor air temperature. The best combination of VGW resulted a maximum of 1.2°C reduction in indoor air temperature, with number of hours (within 28°C or less) were higher by 2506h, representing 85.59% of the overall number of hours (2928h). Overall cooling energy saving is found as 103.3kwh, representing 13.63% of the total of energy saving, and decreased the heat gained by 38.82%, representing 61.51kwh reduction during cooling season compared to base wall.

This work aimed to study the influence of contamination profiles and humidity on flashover electrical characteristics of polluted insulators. Firstly, the flashover tests on cap and pin glass insulators under four pollution levels represented by salinity were conducted. Eight artificial contamination profiles based on the solid layer method have been modeled for the selected insulators. The numerical analysis has been used to determine the insulator electrical characteristics such as potential, electric field, and power dissipation under proposed contamination profiles using finite element methods (FEM). Next, the power dissipation has been simulated with consideration of thermal stress propagation in locations with high power. Finally, flashover voltage gradient tests have been conducted under various humidity and contamination profiles. The values of the flashover voltage gradient due to pollution were determined as the percentage of the value of the flashover voltage gradient in the clean condition which was identified as the reference point. The numerical model indicated that the initiation of arc generally occurs at area in which the electric field and power dissipation is maximum. It was also observed from experimental results that the flashover voltage gradient under different contamination profiles has different values depends on the location and dimension of the pollution region.

The next generation (NG) optical technologies will unveil certain unique features, namely ultra-high data rate, broadband multiple services, scalable bandwidth, and flexible communications for manifold end-users. Among the optical technologies, free space optical (FSO) technology is a key element to achieve free space data transmission according to the requirements of the future technologies, which is due to its cost effective, easy deployment, high bandwidth enabler, and high secured. In this article, we give the overview of the recent progress on FSO technology and the factors that will lead the technology towards ubiquitous application. As part of the review, we provided fundamental concepts across all types of FSO system, including system architecture comprising of single beam and multiple beams. The review is further expanded into the investigation of rain and haze effects toward FSO signal propagation. The final objective that we cover is the scalability of an FSO network via the implementations of hybrid multi-beam FSO system with wavelength division multiplexing (WDM) technology.

This study aims to achieve a balance of daylight availability in the work-plane environments of a fully glazed facade integrated with a light shelf system using an optimization procedure that can assist architects with assessing the daylighting performance of numerous design alternatives, and build-up the optimized design. The approach uses parametric design, simulation modelling, and genetic algorithms. A case study of a typical office is carried out to test and verify the effectiveness of the optimization procedure for a light shelf system. Five parameters of light shelf design are optimized in two solar solstices (June and December) and one equinox in March under the Malaysian sky conditions. The optimization results indicate that the optimal design options of light-shelf parameters have great potential for illuminance improvement. After the optimization, the daylighting performance of useful daylight illuminance compared to reference models is increased respectively with an average value of 15.6% and 4.7% on the 21st of June, and by 17.5% and 5.8% on 21st of March, and by 5.8% and 11.3% on 21st of December. Statistical analysis is achieved to investigate the relationship between the performance metric of the optimal design options and the other cases, the outcomes showed that the regression analysis indicated a high level of reliability as well as different levels of variation coefficients.

In this article, an innovative approach to assess the risk of uniform/non-uniform pollution and wet high voltage glass insulator is proposed. The assessment is based on a new index, named as Rh', which is derived from the 3rd, 5th and 7th harmonics of the leakage current. Two 33 kV strings of cap and pin glass insulators having three units with different profiles are employed to evaluate the risk level, based on measured critical voltage gradient (Ec). Critical voltage stress tests are executed on the contaminated insulators under different ratios of lower to upper surface (J) and wetting rates. Furthermore, the effects of ratio of soluble deposit density (ESDD) to non-soluble deposit density (NSDD) on the flashover occurrence are analyzed. It was found that the insulator profile has significant influences on the likelihood of flashover which is estimated as 38% and 24% for type A and B insulators, respectively. From the results, it can be concluded that the proposed Rh' index is able to predict the risk level of the insulator and the probability of flashover occurrence more accurately than the 5th/3rd index, which is widely published in literature.

SONAR signal processing plays an indispensable role when it comes to parameter estimation of Direction of Arrival (DOA) of acoustic plane waves for closely spaced target exclusively under severe noisy environments. Resolution performance of classical MUSIC and ESPRIT algorithms and other subspace-based algorithms decreases under scenarios like low SNR, smaller number of snapshots and closely spaced targets. In this study, optimization strength of swarm intelligence of Cuckoo Search Algorithm (CSA) is accomplished for viable DOA estimation in different scenarios of underwater environment using a Uniform Linear Array (ULA). Higher resolution for closely spaced targets is achieved using smaller number of snapshots viably with CSA by investigating global minima of the highly nonlinear cost function of ULA. Performance analysis of CSA for different number of targets employing estimation accuracy, higher resolution, variance analysis, frequency distribution of RMSE over the monte Carlo runs and robustness against noise in the presence of additive-white Gaussian measurement noise is achieved. Comparative studies of CSA with Root MUSIC and ESPRIT along with Crammer Rao Bound analysis witnesses better results for estimating DOA parameters which are further endorsed from the results of Monte Carlo simulations.

This paper presents a new investigation to detect various faults within the three-phase star and delta induction motors (IMs) using a frequency response analysis (FRA). In this regard, experimental measurements using FRA are performed on three IMs of ratings 1 HP, 3 HP and 5.5 HP in normal conditions, short-circuit fault (SC) and open-circuit fault (OC) conditions. The SC and OC faults are applied artificially between the turns (Turn-to-Turn), between the coils (Coil-to-Coil) and between the phases (Phase-to-Phase). The obtained measurements show that the star and delta IMs result in dissimilar FRA signatures for the normal and faulty windings. Various statistical indicators are used to quantify the deviations between the normal and faulty FRA signatures. The calculation is performed in three frequency ranges: low, middle and high ones, as the winding parameters including resistive, inductive and capacitive components dominate the frequency characteristics at different frequency ranges. Consequently, it is proposed that the boundaries for the used indicators facilitate fault identification and quantification.

Arsenic occurrence and toxicity records in various industrial effluents have prompted researchers to find cost-effective, quick, and efficient methods for removing arsenic from the environment. Adsorption of As(V) onto dried bacterial biomass is proposed in the current work, which continues a line of previous research. Dried bacterial biomass of WS3 (DBB) has been examined for its potential to remove As(V) ions from aqueous solutions under various conditions. Under optimal conditions, an initial concentration of 7.5 ppm, pH 7, adsorbent dose of 0.5 mg, and contact period of 8 h at 37 °C results in maximum removal of 94%. Similarly, amine, amide, and hydroxyl groups were shown to contribute to As(V) removal by Fourier transform infrared spectroscopy (FTIR), and the adsorption of As(V) in the cell wall of DBB was verified by FESEM-EDX. In addition, equilibrium adsorption findings were analyzed using nonlinear and linear isotherms and kinetics models. The predicted best-fit model was selected by calculating the coefficient of determination (R2). Adsorption parameters representative of the adsorption of As(V) ions onto DBB at R2 values were found to be more easily attained using the nonlinear Langmuir isotherm model (0.95). Moreover, it was discovered that the nonlinear pseudo-second-order rate model using a nonlinear regression technique better predicted experimental data with R2 than the linear model (0.98). The current study verified the nonlinear approach as a suitable way to forecast the optimal adsorption isotherm and kinetic data.

Frequency Response Analysis (FRA) technique has been recognized by worldwide utilities as a matured technology to assess the mechanical integrity of power transformers. While some industrial critical assets such as induction motors have the same construction principle as power transformers, the application of FRA technique to induction motors has not yet been fully explored. This paper presents analogical experimental studies for the application of FRA on power transformers and induction motors. For a consistent analogy, the FRA technique has been employed to detect short and open circuit turns in both appliances, which helps explore a wider scope of the FRA applications on rotating machines. In this regard, experimental FRA measurements are performed on an 11/0.415 kV, 500 kVA, three-phase distribution transformer and a 5.5 HP three-phase induction motor. Several short and open circuit faults are staged on the windings of both tested equipment and the FRA signature is recorded and compared with the reference signature at no fault. To quantify the impact of faults on the FRA signature, several statistical indicators are used and threshold limits for these indicators are proposed to automate the interpretation process. Results reveal a good correlation between the FRA signatures of induction motors and power transformers that attests to the feasibility of using FRA technique to detect various faults within large rotating machines.

Insulator monitoring using leakage current characteristics is essential for predicting an insulator’s health. To evaluate the risk of flashover on the porcelain insulator using leakage current, experimental investigation of leakage current indices was carried out. In the first stage of the experiment, the effect of contamination, insoluble deposit density, wetting rate, and uneven distribution pollution were determined on the porcelain insulator under test. Then, based on the laboratory test results, leakage current information in time and frequency characteristics was extracted and employed as assessment indicators for the insulator’s health. Six indicators, namely, peak current indicator, phase shift indicator, slope indicator, crest factor indicator, total harmonic distortion indicator, and odd harmonics indicator, are introduced in this work. The obtained results indicated that the proposed indicators had a significant role in evaluating the insulator’s health. To evaluate the insulator’s health levels based on the extracted indicator values, this work presents the naïve Bayes technique for the classification and prediction of the insulator’s health. Finally, the confusion matrix for the experimental and prediction results for each indicator was established to determine the appropriateness of each indicator in determining the insulator’s health status.

In this paper, a unique approach based on electrical characteristics observed from measurements of contaminated polymeric insulators was established to calculate the electric field distribution over their surfaces. A case study using two different 33 kV polymeric insulator geometric profiles was performed to highlight the benefits of the proposed modeling approach. The conductance of the pollution layer was tested to establish a nonlinear field-dependent conductivity for pollution modeling. The leakage current (LC) of the polluted insulator was measured in a laboratory under clean and wet conditions. Then, using the finite element method (FEM), the electric field and current density distributions along the insulator were computed. The results showed that the insulators experienced an increase in the electric field (EF) magnitude ranging from 0.3 kV/cm to 3.6 kV/cm for the insulator with similar sheds (type I) and 2.2–4.5 kV/cm for the insulator with alternating sheds (big and small, type II) under the high rain condition with a flow rate of 9 L/h. Meanwhile, the highest electric field under fog was 1.74 kV/cm for the insulator with similar sheds and 2.32 kV/cm for an insulator with alternating sheds. Due to the larger diameter on the big shed and the longer leakage distance on the insulator with alternating sheds, the EF on the insulator with alternating sheds is higher than the EF on the insulator with similar sheds. The proposed modeling and simulation provided a detailed field condition estimation around the insulators. This is critical for forecasting the emergence of dry bands and the commencement of flashover on the surfaces of the insulators.

The industry has widely accepted Frequency Response Analysis (FRA) as a reliable method to detect power transformers mechanical deformations. While the FRA technique has been recommended in recent literature as a potential diagnostic method to detect internal faults within rotating machines, detailed feasibility studies have not been fully addressed yet. This paper investigates the feasibility of using the FRA technique to detect several short circuit faults in the stator winding of three-phase induction motors (TPIMs). In this regard, FRA testing is conducted on two sets of induction motors with various short circuit faults. Investigated faults include short circuits between two phases, short circuit turns within the same phase, phase-to-ground, and phase-to-neutral short circuit. The measured FRA signatures are divided into three frequency ranges: low, medium, and high. Several statistical indicators are employed to quantify the variation between faulty and healthy signatures in each frequency range. Experimental results attest the feasibility of the FRA technique as a diagnostic tool to detect internal faults in rotating machines, such as induction motors.

The current work contributes an estimate of the time-frequency characteristics of a leakage current in assessing the health condition of a polluted polymeric insulator. A 33 kV polymer insulator string was subjected to a series of laboratory tests under a range of environmental conditions, including pollution, wetting rate (WR), non-soluble deposit density (NSDD), and non-uniform distribution pollution (FT/B). The temporal and frequency features of the leakage current were then extracted and used as assessment indicators for insulator conditions based on laboratory test findings. Two indices were generated from the leakage current waveform in the time domain: the curve slope index (F1), which is determined by measuring the inclination of the curve between two successive time peaks of the leakage current, and the crest factor indicator (F2). The frequency domain of the leakage current signal was used to calculate the other two indices. These are the odd harmonic indicators derived from the odd frequency harmonics of the leakage current up to the 9th component (F3) and the 5th to 3rd harmonics ratio (F4). The findings showed that the suggested indicators were capable of evaluating insulator conditions. Finally, the confusion matrix for the experimental and prediction results obtained with the proposed indices was used to assess which indicator performed the best. Therefore, the analysis suggests an alternative and effective method for estimating the health condition of a polluted insulator through leakage current characteristics obtained in the time and frequency domains.

In-depth understanding of the pollution problems such as dry bands and the polymeric aging process requires better determination of electric field strength and its distribution over the polymeric surface. To determine the electric field distribution over the insulator surface, this research proposes utilizing a novel approach model based on nonlinear electrical characteristics derived from experimental results for polluted polymer insulators. A case study was carried out for a typical 11 kV polymeric insulator to underline the merits of this new modeling approach. The developments of the proposed pollution model and the subsequent computational works are described in detail. The study is divided into two main stages; laboratory measurements and computer simulations. In the first stage, layer conductance tests were carried out to develop nonlinear field-dependent conductivity for the pollution modeling. In the second part, equipotential and electric field distributions along the leakage were computed using the finite element method (FEM). Comparative field studies showed that the simulation using the proposed dynamic pollution model results in more detailed and realistic field profiles around insulators. This may be useful to predict the formation of dry bands and the initiation of electrical discharges on the polymeric surface.

Due to the constant need to enhance water supply sources, water operators are searching for solutions to maintain water quality through leakage protection. The capability to monitor the day-to-day water supply management is one of the most significant operational challenges for water companies. These companies are looking for ways to predict how to improve their supply operations in order to remain competitive, given the rising demand. This work focuses on the mathematical modeling of water flow and losses through leak openings in the smart pipe system. The research introduces smart mathematical models that water companies may use to predict water flow, losses, and performance, thereby allowing issues and challenges to be effectively managed. So far, most of the modeling work in water operations has been based on empirical data rather than mathematically described process relationships, which is addressed in this study. Moreover, partial submersion had a power relationship, but a total immersion was more likely to have a linear power relationship. It was discovered in the experiment that the laminar flows had Reynolds numbers smaller than 2000. However, when testing with transitional flows, Reynolds numbers were in the range of 2000 to 4000. Furthermore, tests with turbulent flow revealed that the Reynolds number was more than 4000. Consequently, the main loss in a 30 mm diameter pipe was 0.25 m, whereas it was 0.01 m in a 20 mm diameter pipe. However, the fitting pipe had a minor loss of 0.005 m, whereas the bending pipe had a loss of 0.015 m. Consequently, mathematical models are required to describe, forecast, and regulate the complex relationships between water flow and losses, which is a concept that water supply companies are familiar with. Therefore, these models can assist in designing and operating water processes, allowing for improved day-to-day performance management.

This study focused on enhancing the balance between sufficient daylighting and heat mitigation in lecture halls, set within the challenging hot-arid climate of Saudi Arabia, through the optimization of window designs and the incorporation of light-shelves. To achieve this, a combination of in-detail Parametric Sensitivity Analyses (PSA) was performed in the first stage to find the best configuration of windows, while a multi-objective optimization (MOO) strategy was applied in the second stage considering multiple objectives in each stage. Before running both analyses, the simulation model was validated by field measurement. The optimization results show that the optimal window configurations obtained through PSA and MOO offer significant potential for improving daylighting performance, energy efficiency and comfort. In terms of the overall best solutions from PSA and MOO, the PSA demonstrated substantial improvements, with Useful Daylight Illuminance (UDI) rising by 46.31% to 55.36%, glare decreasing by 52.17% to 82.61% and Energy Use Intensity (EUI) improving by 0.89% to 2.63%. Additionally, MOO solutions yielded even more significant enhancements, increasing UDI by 43.58% to 58.37%, reducing glare by 95% to 100% and enhancing EUI by 1.81% to 3.88%. This has resulted in a more evenly distributed and efficient daylighting throughout the space. [ABSTRACT FROM AUTHOR]