Calculation Method Research Articles

Reduced-order method for nuclear reactor primary circuit calculation

Reduced-order method for nuclear reactor primary circuit calculation

Base joint hysteresis model for reinforced concrete assembly columns with post-pouring area

In response to the problem of uncontrollable grouting quality of traditional grouting sleeves in the connection between prefabricated components, a column base joint with post pouring area connected by grouting sleeves (PCGS) is proposed. Both the sleeve and post pouring area could cause differences in hysteresis characteristics between prefabricated and cast-in-place components. In order to investigate the hysteresis model of PCGS column base joint, the cyclic load tests and finite element parametric analysis of PCGS column base joint were conducted. The theoretical calculation method for load and displacement of PCGS column base joint at yield, peak, and ultimate characteristic points was established based on equivalent rectangular stress and plastic hinge length in joint area. The average ratios of theoretical calculations to test results for load and displacement at the above three characteristic points are 0.997, 0.983, and 0.983, and 1.020, 1.041, and 0.970, respectively, indicating that the theoretical calculation method can accurately predict the strength and deformation of PCGS column base joint. The dimensionless skeleton curve model with double broken lines in the elastic and strengthening stages, and exponential function in descending stage has been established based on the test and simulated results. The degradation behavior of unloading stiffness and bearing capacity was quantitatively described using the regression fitting method, and the hysteresis rule was defined. The established hysteresis model can effectively reflect the strength and stiffness degradation under cyclic loading, which can provide guidance for the elastic-plastic seismic response analysis of PCGS column base joint.

Retrospective assessment of HDR brachytherapy dose calculation methods in locally advanced cervical cancer patients: AcurosBV vs. AAPM TG43 formalism.

This retrospective analysis was completed to investigate the use of a model-based dose calculation algorithm (MBDCA) AcurosBV, for use in HDR BT treatments for locally advanced cervical cancer treated with tandem and ovoid applicators with interstitial needles. A cohort of 32 patients receiving post-EBRT HDR brachytherapy boost with a prescription dose of 5.5Gy × 5 fractions to the high-risk clinical target volume (CTVHR) were selected for this study. For standard TG43 dose calculation, applicators were manually digitized on the planning images, while for AcurosBV calculations, solid renderings of Titanium Fletcher Suite Delclos (FSD) applicators included in BrachyVision were matched to those used clinically and Ti needles were manually digitized. The dose was recalculated using Varian's AcurosBV 13.5 and dose-to-medium-in-medium (Dm,m) was reported. EQD2 values for targets and organs at risk were compared between dose calculation formalisms. D90% and D98% values were reported for the high and intermediate-risk CTVs, and values were reported for OARs including bladder, rectum, sigmoid, bowel, and vagina. Due to variability within the patient cohort, the dosimetric impact of AcurosBV was investigated corresponding to planning image modality (CT vs. CBCT), presence of Ti needles, and contrast within vaginal balloons used to stabilize implants. AcurosBV showed lower dosimetric values for all plans compared to TG43. The average±standard deviation of dosimetric reduction in D90% was 4.33±0.09% for CTVHR and 4.12±0.09% for CTVIR. The reduction to OARs was: 4.99±0.15% for bladder, 7.87±0.16% for rectum, 5.79±0.17% for sigmoid, 6.91±0.14% for bowel, and 4.55±0.14% for vagina. AcurosBV should be utilized for HDR BT GYN cases, treated with tandem and ovoid applicators, with high degrees of heterogeneity and calculated in tandem with TG43.

Roll force prediction using hybrid genetic algorithm with semi-supervised support vector regression

Roll force prediction plays a significant role in rolling schedule and optimization. For a specific steel grade, the roll force can be determined by the aid of several factors: rolling speed, initial thickness, ratio of thickness reduction, the starting temperature of the strip, and the friction coefficient in the contact region. Roll force prediction mathematical models are sometimes rare and inaccurate. This paper presents a new approach to predict roll separating force using semi-supervised support vector regression (SSSVR). The parameters affecting the sensitivity of the SSSVR were optimized using the genetic algorithm to maximize the r-squared accuracy score. The intelligent system is evaluated using two quality metrics: the root mean square error (RMSE) and the mean absolute error calculated between the measured force from the industrial rolling field and the predicted force using the proposed system from one side, and the measured force and the calculated force from another side. Obtained results show the improvement while using the intelligent predictive system. The reduction in RMSE was achieved by the proposed system by 66.9% and 32.1% for oval and round shape passes, respectively in comparison to the conventional calculation method.

Numerical simulation on structural behavior of FRP profile‐concrete hybrid beams with bolt shear connector

AbstractFRP profile‐concrete hybrid beam, composed of a FRP profile beam, a concrete slab made of normal concrete (NC) or ultra‐high‐performance‐concrete (UHPC), and shear connectors, shows significant potential for employment in large‐span bridges due to its excellent corrosion resistance, lightweight, and easy construction. The structural behavior of such hybrid beam was simulated using a three‐dimensional non‐linear finite element model (FEM) in Abaqus. The Hashin failure model and concrete damage plastic (CDP) model were employed to characterize the progressive failure of FRP, NC, and UHPC, respectively. The FEM considered partial shear connection by utilizing shear load‐slip model and the orthotropic behavior of the FRP profile. The proposed FEM was validated through comparisons with experimental data in terms of load‐midspan deflection curve, load‐end slip curve, and failure modes. A parametric study was subsequently conducted to identify the effects of various factors, including concrete strength, bolt spacing, concrete slab width, concrete slab height, FRP flange and web thickness, and shear span. Based on the results yielded from FEM analysis, the accuracy of the calculation method in Chinese standard (GB‐50608) for predicting the loading capacity of hybrid beams was evaluated and found too conservative.

A Comprehensive and Repeatable Contrast-Enhanced Ultrasound Quantification Approach for Clinical Evaluations of Tumor Blood Flow

Objective The aim of this study is to define a comprehensive and repeatable contrast-enhanced ultrasound (CEUS) imaging protocol and analysis method to quantitatively assess lesional blood flow. Easily repeatable CEUS evaluations are essential for longitudinal treatment monitoring. The quantification method described here aims to provide a structure for future clinical studies. Materials and Methods This retrospective analysis study included liver CEUS studies in 80 patients, 40 of which contained lesions (primarily hepatocellular carcinoma, n = 28). Each patient was given at least 2 injections of a microbubble contrast agent, and 60-second continuous loops were acquired for each injection to enable evaluation of repeatability. For each bolus injection, 1.2 mL of contrast was delivered, whereas continuous, stationary scanning was performed. Automated respiratory gating and motion compensation algorithms dealt with breathing motion. Similar in size regions of interest were drawn around the lesion and liver parenchyma, and time-intensity curves (TICs) with linearized image data were generated. Four bolus transit parameters, rise time (RT), mean transit time (MTT), peak intensity (PI), and area under the curve (AUC), were extracted either directly from the actual TIC data or from a lognormal distribution curve fitted to the TIC. Interinjection repeatability for each parameter was evaluated with coefficient of variation. A 95% confidence interval was calculated for all fitted lognormal distribution curve coefficient of determination (R 2) values, which serves as a data quality metric. One-sample t tests were performed between values obtained from injection pairs and between the fitted lognormal distribution curve and direct extraction from the TIC calculation methods to establish there were no significant differences between injections and measurement precision, respectively. Results Average interinjection coefficient of variation with both the fitted curve and direct calculation of RT and MTT was less than 21%, whereas PI and AUC were less than 40% for lesion and parenchyma regions of interest. The 95% confidence interval for the R 2 value of all fitted lognormal curves was [0.95, 0.96]. The 1-sample t test for interinjection value difference showed no significant differences, indicating there was no relationship between the order of the repeated bolus injections and the resulting parameters. The 1-sample t test between the values from the fitted lognormal distribution curve and the direct extraction from the TIC calculation found no statistically significant differences (α = 0.05) for all perfusion-related parameters except lesion and parenchyma PI and lesion MTT. Conclusions The scanning protocol and analysis method outlined and validated in this study provide easily repeatable quantitative evaluations of lesional blood flow with bolus transit parameters in CEUS data that were not available before. With vital features such as probe stabilization ideally performed with an articulated arm and an automated respiratory gating algorithm, we were able to achieve interinjection repeatability of blood flow parameters that are comparable or surpass levels currently established for clinical 2D CEUS scans. Similar values and interinjection repeatability were achieved between calculations from a fitted curve or directly from the data. This demonstrated not only the strength of the protocol to generate TICs with minimal noise, but also suggests that curve fitting might be avoided for a more standardized approach. Utilizing the imaging protocol and analysis method defined in this study, we aim for this methodology to potentially assist clinicians to assess true perfusion changes for treatment monitoring with CEUS in longitudinal studies.

A Calculation Method of Bearing Balls Rotational Vectors Based on Binocular Vision Three-Dimensional Coordinates Measurement

The rotational speed vectors of the bearing balls affect their service life and running performance. Observing the actual rotational speed of the ball is a prerequisite for revealing its true motion law and conducting sliding behavior simulation analysis. To address the need for accuracy and real-time measurement of spin angular velocity, which is also under high-frequency and high-speed ball motion conditions, a new measurement method of ball rotation vectors based on a binocular vision system is proposed. Firstly, marker points are laid on the balls, and their three-dimensional (3D) coordinates in the camera coordinate system are calculated in real time using the triangulation principle. Secondly, based on the 3D coordinates before and after the movement of the marker point and the trajectory of the ball, the mathematical model of the spin motion of the ball was established. Finally, based on the ball spin motion model, the three-dimensional vision measurement technology was first applied to the measurement of the bearing ball rotation vector through formula derivation, achieving the analysis of bearing ball rolling and sliding characteristics. Experimental results demonstrate that the visual measurement system with the frame rate of 100 FPS (frames per second) yields a measurement error within ±0.2% over a speed range from 5 to 50 RPM (revolutions per minute), and the maximum measurement errors of spin angular velocity and linear velocity are 0.25°/s and 0.028 mm/s, respectively. The experimental results show that this method has good accuracy and stability in measuring the rotation vector of the ball, providing a reference for bearing balls' rotational speed monitoring and the analysis of the sliding behavior of bearing balls.

A Study on the Breakthrough Pressure of Porous Rock Formations in Gas Storage Reservoirs

Breakthrough pressure of natural gas in rock is an important evaluation parameter in gas reservoir development. In this study, experimental measurements of porosity and permeability of the caprock core were carried out. A digital core model was obtained by body rendering of rock CT (Computed Tomography) slices using Avizo software. Then, the grid model was imported into Fluent software for a numerical simulation of natural gas breakthrough pressure in the core. The innovations of this paper include (1) an accurate calculation method of cap breakthrough pressure based on the VOF method; (2) the method performs a perceptual analysis of average pore radius, wettability, roughness height, and viscosity ratio.

Modeling and Calculation of Limit Magnitude Detection of Orbital Optoelectric Tracking System

In order to evaluate the tracking capability of optoelectric tracking for an orbital target, the limit magnitude detection performance calculation model and its calculation method are studied. Combining the optical signal characteristics of the tracked orbital target, the background, and the CCD noise, the framework of the limit magnitude calculation model of the system for dynamic target detection is constructed. The relationships between the limit magnitude and the signal-to-noise ratio threshold of the optical signal characteristics, the exposure time of the CCD camera, and the dark current of the CCD imaging are studied and analyzed while considering the sunlight illumination condition, so that the calculation function and its change curve are given. The limit magnitude detection capability of the system is verified by the simulated experiment and the synchronized tracking test, and the detection distance maximum error of the model calculation is 3.6 m. The results show that under certain illumination conditions, when the exposure time of the CCD camera is longer and the SNR threshold is lower, the limit magnitude detection performance of the system is better, and the tracking performance of the system is more stable.

Study of the Dynamic Adaptive Calculation Method for River Water Environmental Capacity

Controlling the total amount of river pollutant discharge is an important means of water resource protection and management, and it is also a necessary condition for ensuring the normal functioning of water areas. The total amount of pollutant discharge is closely related to the water environmental capacity (WEC). Shifting from the traditional method of calculating WEC to dynamic analyses and calculations, concerning practical applications, in this paper, a dynamic adaptive calculation method is proposed for the river WEC that considers the changes in adaptive demand and hydrological conditions. In this method, the dynamic WEC is represented by intervals based on dynamic changes in different spatial and temporal scales, various calculation methods, hydrological conditions, and parameters. According to the calculation results for the WEC, a variable interval was formed. Taking the Shaanxi section of the main stream of the Wei River as the research object, with the support of an integrated platform, the dynamic adaptive calculation of the WEC in the Shaanxi section of the Wei River was realized, and a corresponding simulation system was constructed. The verification results show that (1) the dynamic calculation of WEC can be realized by freely combining different model methods and calculation conditions; (2) the WEC is described using a variable interval, which has strong applicability and operability; and (3) the simulation system can quickly adapt to the changing needs of practical applications and provide managers with visual and credible decision support. The research results provide a theoretical basis for river water environment pollution prevention and environmental management decision-making and help in the high-quality development of the river basin.

Modeling and Visualization of Coolant Flow in a Fuel Rod Bundle of a Small Modular Reactor

This article presents the results of an experimental study of the coolant flow in a fuel rod bundle of a nuclear reactor fuel assembly of a small modular reactor for a small ground-based nuclear power plant. The aim of the work is to experimentally determine the hydrodynamic characteristics of the coolant flow in a fuel rod bundle of a fuel assembly. For this purpose, experimental studies were conducted in an aerodynamic model that included simulators of fuel elements, burnable absorber rods, spacer grids, a central displacer, and stiffening corners. During the experiments, the water coolant flow was modeled using airflow based on the theory of hydrodynamic similarity. The studies were conducted using the pneumometric method and the contrast agent injection method. The flow structure was visualized by contour plots of axial and tangential velocity, as well as the distribution of the contrast agent. During the experiments, the features of the axial flow were identified, and the structure of the cross-flows of the coolant was determined. The database obtained during the experiments can be used to validate CFD programs, refine the methods of thermal-hydraulic calculation of nuclear reactor cores, and also to justify the design of fuel assemblies.

A review of current practice in the design and analysis of extremely small stepped-wedge cluster randomized trials.

Stepped-wedge cluster randomized trials tend to require fewer clusters than standard parallel-arm designs due to the switches between control and intervention conditions, but there are no recommendations for the minimum number of clusters. Trials randomizing an extremely small number of clusters are not uncommon, but the justification for small numbers of clusters is often unclear and appropriate analysis is often lacking. In addition, stepped-wedge cluster randomized trials are methodologically more complex due to their longitudinal correlation structure, and ignoring the distinct within- and between-period intracluster correlations can underestimate the sample size in small stepped-wedge cluster randomized trials. We conducted a review of published small stepped-wedge cluster randomized trials to understand how and why they are used, and to characterize approaches used in their design and analysis. Electronic searches were used to identify primary reports of full-scale stepped-wedge cluster randomized trials published during the period 2016-2022; the subset that randomized two to six clusters was identified. Two reviewers independently extracted information from each report and any available protocol. Disagreements were resolved through discussion. We identified 61 stepped-wedge cluster randomized trials that randomized two to six clusters: median sample size (Q1-Q3) 1426 (420-7553) participants. Twelve (19.7%) gave some indication that the evaluation was considered a "preliminary" evaluation and 16 (26.2%) recognized the small number of clusters as a limitation. Sixteen (26.2%) provided an explanation for the limited number of clusters: the need to minimize contamination (e.g. by merging adjacent units), limited availability of clusters, and logistical considerations were common explanations. Majority (51, 83.6%) presented sample size or power calculations, but only one assumed distinct within- and between-period intracluster correlations. Few (10, 16.4%) utilized restricted randomization methods; more than half (34, 55.7%) identified baseline imbalances. The most common statistical method for analysis was the generalized linear mixed model (44, 72.1%). Only four trials (6.6%) reported statistical analyses considering small numbers of clusters: one used generalized estimating equations with small-sample correction, two used generalized linear mixed model with small-sample correction, and one used Bayesian analysis. Another eight (13.1%) used fixed-effects regression, the performance of which requires further evaluation under stepped-wedge cluster randomized trials with small numbers of clusters. None used permutation tests or cluster-period level analysis. Methods appropriate for the design and analysis of small stepped-wedge cluster randomized trials have not been widely adopted in practice. Greater awareness is required that the use of standard sample size calculation methods can provide spuriously low numbers of required clusters. Methods such as generalized estimating equations or generalized linear mixed models with small-sample corrections, Bayesian approaches, and permutation tests may be more appropriate for the analysis of small stepped-wedge cluster randomized trials. Future research is needed to establish best practices for stepped-wedge cluster randomized trials with a small number of clusters.

Risk Assessment of UAV Cyber Range Based on Bayesian–Nash Equilibrium

In order to analyze the choice of the optimal strategy of cyber security attack and defense in the unmanned aerial vehicles’ (UAVs) cyber range, a game model-based UAV cyber range risk assessment method is constructed. Through the attack and defense tree model, the risk assessment method is calculated. The model of attack and defense game with incomplete information is established and the Bayesian–Nash equilibrium of mixed strategy is calculated. The model and method focus on the mutual influence of the actions of both sides and the dynamic change in the confrontation process. According to the calculation methods of different benefits of different strategies selected in the offensive and defensive game, the risk assessment and calculation of the UAV cyber range are carried out based on the probability distribution of the defender’s benefits and the attacker’s optimal strategy selection. An example is given to prove the feasibility and effectiveness of this method.

Future Food Security Challenges in Riau Province, Indonesia

The food crisis is a real problem in various regions around the world, including Indonesia. This phenomenon is influenced by the rate of population growth which is increasing while farmlands are depleting due to the conversion of land into settlements, especially in Riau Province which is experiencing food security threats. Food security projections are made to provide an overview of the future condition of food security in Riau Province to support sustainability. The basic data used are data for 2018 and 2019. The measurement method used is the scenario method and then the availability calculation method according to Minister of Agriculture Regulation Number 43/Permentan/OT.140/7/2010. Meanwhile, the calculation of food needs uses a formula taking into account the average consumption per capita per year from the regional agriculture service multiplied by the population in the year concerned. Then, the projections are measured using the arithmetic population growth formula approach for food availability and the geometric population growth formula for the food needs of the population. The food commodity in Riau Province used in the analysis is rice. The calculation results show that in the future food availability in Riau Province will not be able to meet its food needs. Keywords: availability of rice, rice needs, food security

Improving neural-network-based prediction models for misalignment in off-axis three-mirror anastigmat telescopes

The performance of a telescope system heavily relies on the precise alignment of the mirrors. The off-axis three-mirror anastigmat (TMA) telescope presents unique challenges due to its complex optical design. Each optical element within the off-axis TMA telescope is inherently introduced with theoretical eccentricity and tilt. Furthermore, the incorporation of freeform surfaces and other optical elements with intricate surface features typically leads to low initial alignment accuracy of the optical path. With this low initial alignment accuracy and the noise of the measurements, the prediction of the misalignment of the telescope is getting harder. A fully connected neural network architecture is proposed as a misalignment calculation method for an off-axis TMA telescope system with a freeform surface. Random training data is created by using optical design software. The sensitivity of the mirrors to the wavefront error is quantified and incorporated into the loss function of the neural network to improve prediction accuracy. Adding the noisy measurement samples to the training data creates a noise-immune neural network model. Simulation results show that our model can successfully predict misalignment of the mirrors with noisy measurement values.

Far-field Pattern Analysis Based on Piecewise Aperture Field Integration for Leighton Chajnantor Telescope Antenna under Gravity and Wind Load

The Caltech Submillimeter Observatory telescope will be relocated from Mauna Kea, Hawaii to Chajnantor Plateau, Chile, refurbished there and renamed the Leighton Chajnantor Telescope (LCT). At the new site, the open-air environment, as well as the high altitude, will amplify the influence of gravity and wind load on structural deformation, thus affecting the antenna’s radiation characteristics, which can be characterized by a far-field pattern. To quickly and accurately compensate for the effect of reflector structural deformation on the far-field pattern of LCT’s antenna, we propose a far-field pattern quick calculation method (FPQCM) to analyze the antenna’s radiation characteristics under gravity and various wind loads, which combines the optical path difference calculation method on the aperture plane, the piecewise Zernike polynomial function, and the piecewise aperture field integration method. Through extensive experimental comparisons with the numerical method based on physical optics and physical theory of diffraction, it is validated that the proposed FPQCM significantly reduces the time by more than 100 times for acquiring the far-field patterns while maintaining the accuracy of the main figure of merits at the highest frequency (i.e., 856 GHz). In addition, we analyzed the far-field pattern of the antenna at different zenith angles, gravity, and winds of different strengths and directions by FPQCM, which provided guidance for performing more precise control through an active surface optimization system after LCT resumes operation, thus facilitating the acquisition of higher surface accuracy and better observation effect.

Deep Conformal Supervision: Leveraging Intermediate Features for Robust Uncertainty Quantification.

Trustworthiness is crucial for artificial intelligence (AI) models in clinical settings, and a fundamental aspect of trustworthy AI is uncertainty quantification (UQ). Conformal prediction as a robust uncertainty quantification (UQ) framework has been receiving increasing attention as a valuable tool in improving model trustworthiness. An area of active research is the method of non-conformity score calculation for conformal prediction. We propose deep conformal supervision (DCS), which leverages the intermediate outputs of deep supervision for non-conformity score calculation, via weighted averaging based on the inverse of mean calibration error for each stage. We benchmarked our method on two publicly available datasets focused on medical image classification: a pneumonia chest radiography dataset and a preprocessed version of the 2019 RSNA Intracranial Hemorrhage dataset. Our method achieved mean coverage errors of 16e-4 (CI: 1e-4, 41e-4) and 5e-4 (CI: 1e-4, 10e-4) compared to baseline mean coverage errors of 28e-4 (CI: 2e-4, 64e-4) and 21e-4 (CI: 8e-4, 3e-4) on the two datasets, respectively (p < 0.001 on both datasets). Based on our findings, the baseline results of conformal prediction already exhibit small coverage errors. However, our method shows a significant improvement on coverage error, particularly noticeable in scenarios involving smaller datasets or when considering smaller acceptable error levels, which are crucial in developing UQ frameworks for healthcare AI applications.

Application Practice of SHPB Experimental Technology in "Blasting Engineering" Teaching

The course of "Blasting Engineering" is a highly practical professional course in the field of civil engineering. In order to help students deeply understand and comprehend the propagation and attenuation mechanism of stress waves during rock blasting process, as well as the influence of rock dynamic characteristics on blasting rupture effect, SHPB impact compression experimental technology is introduced into the teaching of "blasting engineering". Firstly, the structure, experimental process, and principles of SHPB equipment were introduced, allowing students to have a better understanding of the experimental principles of SHPB and the theoretical calculation methods of rock dynamic parameters. Then, by combining SHPB experiments with the theoretical course of "Blasting Engineering", the teaching mode can solve students' difficulties in learning blasting theory, exercise their scientific research and exploration abilities, expand their innovative thinking, and cultivate their ability to propose and solve key scientific problems. This helps to unleash students' subjective initiative in conducting experimental research independently and improve teaching effectiveness.

Prediction of rotational bending fatigue life of bearing steel based on damage mechanics

Based on the theory of continuous damage mechanics, this paper proposes a fatigue damage evolution model and numerical calculation method considering the influence of vacuum chemical heat treatment process, and studies the rotational bending fatigue damage analysis and life prediction method of M50NiL bearing steel. Firstly, the constitutive model, fatigue damage evolution equation and material parameter calibration method in the theoretical model are given. Secondly, based on the ABAQUS platform, the damage mechanics-finite element numerical calculation method of fatigue damage analysis considering the influence of hardened layer is realized by writing the UMAT subroutine; then, the rotational bending fatigue test of M50NiL bearing steel treated by vacuum chemical heat treatment of quenching and tempering, carburizing and carbonitriding is carried out, and the influence of heat treatment process on fatigue performance is analyzed; finally, based on the proposed fatigue damage model and numerical calculation method, the rotational bending fatigue life of M50NiL bearing steel is predicted, and the results are compared with the experimental results to verify the correctness of the proposed method.

A Groundwater Quality Index Proposed for Assessment of Groundwater Quality: A Case Study of Quang Tri Province, Central Vietnam

Background: Water quality assessment is a crucial task to manage water sources and control water pollution. The purpose of this study is to develop a Groundwater Quality Index (GWQI) to assess groundwater quality. Methods: The GWQI was developed and functioned by weight (wi) and sub-index (qi) of ten selected water quality parameters. Principal Component Analysis (PCA) was applied to a water quality monitoring data set (year 2016 to 2019, 163 samples) at 27 locations in Quang Tri province, aiming to identify the weight of each parameter. Sub-index linear function was established based on the allowable limits for each parameter defined in the National Technical Regulation on drinking water quality. Multiplicate (GWQIM), additive (GWQIA), and reference (GWQIRef) formulas were used to compute the final GWQI indices. The sensitivity and suitability of the proposed GWQI in water quality evaluation were also tested. Results: Among the three GWQI calculation methods, GWQIM was found to be the most suitable in reflecting groundwater quality in the study area. From 2019 to 2022 (152 samples), in the province, 63.2% of GWQIM values were classified as EXCELLENT or GOOD, 17.1% as POOR, and 19.7% as VERY POOR, or UNFIT FOR DRINKING. Conclusion: This improved GWQI can be applied to assess groundwater quality at local or regional scales.