Fitting Parameters Research Articles

On the sensitivity of DEM parameters on pile experiments

AbstractThe discrete element method (DEM) is suitable to investigate problems where large deformations occur especially in granular material. The fitting of reliable DEM parameters is crucial and a challenge which is caused by the high number of DEM parameters and the computational effort. Despite its drawbacks, a trial and error approach is often used for the DEM parameter calibration. The knowledge of the DEM parameter influence on the model response is necessary to improve the calibration and to check whether the experiment is suitable to calibrate specific parameters or not. It is possible to reduce the dimensionality of the optimisation problem by omitting parameters whose influence on the model response is negligibly small. One approach is to perform a global sensitivity analysis based on Sobol’ indices. A frequently used calibration experiment in literature is the pile experiment. The deviation between the experiment and the simulation is evaluated with the angle of repose. In the present paper, an algorithm to determine the angle of repose considering the three-dimensional shape of the heap is discussed. The global sensitivity analysis is performed for two different experimental heap set-ups. To decrease the computational effort of the sensitivity analysis, the model response is approximated with metamodels whose predictability is evaluated using the root mean squared error (RMSE) based on a separate sampling point set.

The dynamics of hybrid-immune and immunodeficient susceptible individuals and the three stages of COVID-19 vaccination

The World Health Organization has disclosed that the hybrid-immune and immunodeficient individuals are two distinct classes of individuals susceptible to the COVID-19 virus. To model this unique characteristics of two distinct categories of susceptible individuals and the dynamics of the three phases of a vaccination program implemented by the World Health Organization in Malaysia, which have not been accounted for in previous studies, a twelve compartmental SSVEIHQR-D epidemiological model was developed. This model aimed to accurately capture the spread of the COVID-19 virus by fitting real-life data to the model and obtaining updated estimates of the reproduction number. The study also focused on assessing current control measures and exploring strategies to eradicate the virus and mitigate future outbreaks. Mathematical analyses of the model included investigations into stability, equilibrium points, the basic reproduction number R0, optimal control strategies, and sensitivity analyses. Estimation and fitting of the model parameters were conducted using daily situation reports from the Ministry of Health of Malaysia. The obtained value of the basic reproduction number, based on fitted parameter values, indicated stability and reflected the current pandemic situation more realistically. Additionally, the herd immunity threshold was calculated and interpreted in the context of the study findings. Finally, practical insights and recommendations derived from the model’s results were provided to inform government agencies, public health organizations, and intervention bodies, aimed at controlling the spread of the COVID-19 virus.

PMT Fluorescence Signal Denoising Processing Based on Wavelet Transform and BP Neural Network

Air is the environmental foundation for human life and production, and its composition changes are closely related to human activities. Sulfur dioxide (SO2) is one of the main atmospheric pollutants, mainly derived from the combustion of fossil fuels. But SO2 is a trace gas in the atmosphere, and its concentration may be less than one part per billion (ppb). This paper is based on the principle of photoluminescence and uses a photomultiplier tube (PMT) as a photoelectric converter to develop a device for real-time detection of SO2 concentration in the atmosphere. This paper focuses on the impact of noise interference on weak electrical signals and uses wavelet transform to denoise the signals. At the same time, considering that the photoelectric system is susceptible to temperature changes, a multi parameter fitting model is constructed, and a BP neural network is used to further process the signal, separating the real data from the original data. Finally, a high-precision and wide-range trace level sulfur dioxide concentration detection device and algorithm were obtained.

Exploring ice Ic nucleation and structural relaxation in supercooled water

Despite intensive research efforts, understanding how water freezes remains an open and relevant question with profound implications. In this study, we examine ice Ic nucleation and water relaxation at the atomic level, employing molecular dynamics (MD) simulations and Classical Nucleation Theory (CNT). Our key findings address the following foundational issues: (i) Routes to cubic ice. Ice Ic seeding liquid water results in equal amounts of ice Ic and Ih structures at T<235K, while ice Ic predominates at T⩾235K along zero isobar. Moreover, ice produced from spontaneous nucleation at T=205-215K is more cubic compared with that grown on ice Ic seeds; (ii) CNT validity. Using MD-generated data, CNT accurately predicts ice nucleation rates without any fitting parameter, thereby bridging the gap between simulations and experiments; (iii) Kinetic crossroads. We determined a kinetic spinodal for high-density water as an intersection of relaxation and nucleation time curves at TKS=199K for a MD sample and TKS=233K for a macroscopic sample, which coincides with the experimental homogenous freezing limit; (iv) Kauzmann conundrum. Finally, we indicated that if the Kauzmann temperature exists, estimated as TK=190K, it might be inaccessible for high-density water due to the kinetic spinodal at a higher temperature, TKS>TK, thus resolving the long-standing entropy paradox. Overall, this research provides valuable insights into fundamental aspects related to water crystallization.

A Physics-based Model Assisted by Machine-Learning for Sodium-ion Batteries with both Liquid and Solid Electrolytes

In the absence of experimental data of fully developed hierarchical 3D sodium solid-state batteries, we developed an improved continuum model by relying on Machine Learning-assisted parameter fitting to uncover the intrinsic material properties that can be transferred into different battery models. The electrochemical system simulated has sodium metal P2-type Na2/3[Ni1/3Fe1/12Mn7/12]O2 (NNFMO) as the cathode material, paired with two types of electrolytes viz, the organic liquid electrolyte and a solid polymer electrolyte. We implemented a 1D continuum model in COMSOL to suit both liquid and solid electrolytes, then used a Gaussian Process Regressor to fit and evaluate the electrochemical parameters in both battery systems. To enhance the generalizability of our model, the liquid cell and solid cell models share the same OCV input for the cathode materials. The resulting parameters are well aligned with their physical meaning and literature values. The continuum model is then used to understand the effect of increasing the thickness of the cathode and current density by analyzing the cathode utilization, and the overpotentials arising from transport and charge transfer. This 1D model and the parameter set are ready to be used in a 3D battery architecture design.

Comparative Analysis of Adaptive Changes in Immunoendocrine and Physiological Responses to High-Intensity Sprint Interval Training with Progressive and Nonprogressive Loads in Young Wrestlers.

The objective of this study was to explore the effects of a 7-week short sprint interval training (SSIT) with differing in programming volume-loads including progressive (P-SSIT) and nonprogressive (NP-SSIT) approaches on the immunoendocrine, physical fitness attributes and physiological parameters in male wrestlers during the pre-season. Thirty young freestyle wrestlers at the collegiate national-level were included in the study and were divided into three groups: P-SSIT (n = 10), NP-SSIT (n = 10), and an active control group (n = 10). The wrestlers engaged in their specific wrestling training three days weekly, while the P-SSIT and NP-SSIT groups underwent a 7-week SSIT, with scheduling in either progressed or nonprogressed volume-based overloads, three times per week. Before and after the intervention, various aspects of physical fitness (such as 20-m sprint, 4×9-m shuttle run, and maximal strength) and physiological parameters (including cardiorespiratory fitness and anaerobic power output), as well as immunoendocrine responses (such as immunoglobulin-A, testosterone, and cortisol) were measured. Following the training intervention, the control group did not show any significant changes in the variable measured; however, both the P-SSIT and NP-SSIT groups experienced significant improvements (p = 0.001) in physical fitness attributes and physiological parameters with effect sizes ranging from small to very large, and also more adaptive responses compared with control group (p < 0.05). In addition, there were no statistically significant changes observed among the P-SSIT and NP-SSIT groups in terms of immunoendocrine response to training, and physical fitness, as well as physiological parameters (p > 0.05). In conclusion, neither the progressed nor nonprogressed approaches of SSIT demonstrated superior effects on adaptations compared to one another. Therefore, it is recommended for strength and conditioning coaches in wrestling to incorporate both P-SSIT and NP-SSIT into their annual training plan, especially during the pre-season phase, to maximize the physical fitness and physiological parameters of their wrestlers while minimizing changes in immunoendocrine responses.

The Correlation between Body Composition and Physical Fitness Parameters in High Theological School Students

Previous research findings support the claim that physical activity (PA) and maturation result in changes in physical fitness (PF) and body composition (BC) parameters. Fitness assessment tests are especially important for monitoring the health of adolescents. The purpose of this study was to find the correlation between BC and PF parameters in studnts enrolled in High Theological School in Niš. Thirty-seven male students living in boarding schools were included in the participant sample. The average age of the participants was 17.48±1.48 years. The body composition analyser Omron BF 511 (Omron, Tokyo, Japan), was used to measure the BC values. A modified Eufitmos testing protocol was determined to evaluate PF parameters such as: Progressive aerobic cardiovascular endurance run (Pacer), 1-Mile run (1MR), Push-ups (PU), Handgrip (HG), Standing broad jump (SBJ), 20-Meter run (20mR), Back-saver sit and reach (BSR), and Body mass index (BMI). The results showed that the weight status parameters were highly correlated with each other. Regarding PF parameters, they correlated moderately with each other. The correlation analysis between BC and PF parameters showed that BMI, Fat%, and Muscle% achieved moderate correlations with PACER, VO2max, PU, SBJ, and 20mR, while BW had a significant correlation only with HG and PU. Also, BH had a moderate correlation with VO2max, PACER, SBJ, and HG. The findings indicate a correlation between body composition and physical fitness parameters among theology students. However, a suggestion for further research is to conduct multiple regression analysis, which would reveal the relationship between the overall body composition composite and the fitness of the students, rather than just individually determined parameters.

Effect of solvent depletion on electrokinetic energy conversion in viscoelastic fluids

We analyze the electrokinetic energy conversion from the pressure-driven flow of viscoelastic fluids akin to dilute polymer solutions. In contrast to the previously reported results, we account for the reduced differential capacitance over the interfacial layer and the solvent-mediated non-electrostatic interactions, cumulatively represented in an extended continuum framework. We attribute a physical basis of our consideration from the perspective of the formation of a polymer-depleted layer at the channel interface, where the explicit role of the solvent appears to dictate the electromechanics–hydrodynamics coupling over the interfacial scales. By adapting a “box-model” depicting the alterations in the solvent permittivity across the interfacial layer and accommodating a non-electrostatic interaction coefficient concomitantly, the interfacial electrokinetics are coupled with the bulk flow of the polymer-rich medium using the simplified Phan-Thien–Tanner (sPTT) constitutive model. A closed-form theory is obtained that includes only two fitting parameters, namely, the span of the interfacial layer and the strength of the non-electrostatic interactions. These parameters are estimated from comprehensive molecular simulation data. The results of the investigation are analytically tractable and enable rationalizing the “electrokinetic” implications of the polymer-depleted interfacial layer and the possibility that the electrokinetic parameters can be extracted from measurements obtained from experiments. This paves the way toward optimizing the induced streaming potential for the conversion of hydraulic energy to electrical power in polymeric solutions.

Energy efficient clustering and sink mobility protocol using Improved Dingo and Boosted Beluga Whale Optimization Algorithm for extending network lifetime in WSNs

In Wireless Sensor Networks (WSNs), the potential design challenge of energy efficiency is determined to be handled through the strategies of clustering and routing. The approaches of clustering and routing in WSNs pertain to the problems of Non-deterministic Polynomial (NP)-hard optimization. In this context, swarm intelligence-based algorithms are identified to be suitable and ideal for determining near-optimal and optimal solutions in the search space. On the other hand, APTEEN routing protocol possesses the issues that are related to unnecessary energy drain, ineffective overall network coverage and premature death of certain nodes. To address these issues, an attempt to optimize the APTEEN routing protocol using Dingo Optimization Algorithm (DOA) and Beluga Whale Optimization Algorithm (BWOA) is made in this proposed clustering protocol. With this motivation, Improved Dingo and Boosted Beluga Whale Optimization Algorithm (IDBBWOA) is proposed for determining the optimal cluster head and perform energy-efficient routing to minimized the energy consumption and maximize the lifetime of the network. It specifically used Improved Dingo Optimization Algorithm (IDOA) for attaining cluster head (CH) selection and energy efficient routing through the adoption fitness parameters of Residual Energy, Distance within and between Clusters, Network coverage, Node Degree for maximizing the rate of reliable data dissemination. It also incorporated Boosted Beluga Whale Optimization Algorithm (BBWOA) for determining the optimal points over the sink node can be moved to prevent multi-hop between CHs and the sink nodes, since it is essential for addressing the issue of hot-spot and extends the network lifetime. The simulation results of the proposed IDBBWOA approach revealed its efficacy in improving the mean throughput by 18.92 %, sustaining alive nodes by 34.28 %, and maintaining residual energy by 29.34 %, compared to the benchmarked approaches used for evaluation.

Physical activity, sedentary time, and fitness parameters of cardiopulmonary exercise testing: a compositional data analysis among a population-based adult sample

Physical activity, sedentary time, and fitness parameters of cardiopulmonary exercise testing: a compositional data analysis among a population-based adult sample

Establishing rainfall intensity-duration-frequency curves for Baghdad, Iraq using satellite data

Abstract Rainfall intensity-duration-frequency (IDF) curves were generated for Baghdad by utilising three satellite precipitation datasets: Global Satellite Mapping of Precipitation Near Real-Time (GSMaP NRT), gauge-corrected (GSMaP GC) and Global Precipitation Measurement Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG). Maximum annual rainfall data was fitted using several probability distribution methods. The calculated coefficients from the best-fit distribution were used as fitting parameters to generate IDF curves for return periods of 2, 5, 10, 25, 50 and 100 years using the Sherman equation. To address discrepancies between the satellite-derived IDF curves and observed data, bias correction was performed based on the differences. The analysis revealed that the Generalized Extreme Value Distribution model accurately described the hourly rainfall distribution. GSMaP GC exhibited the highest correlation with the observed data, making it the preferred option for generating IDF curves. The study highlighted the importance of gauge correction for satellite rainfall data to minimise the underestimation or overestimation of rainfall. GSMaP GC demonstrated reasonable accuracy in estimating rainfall in Iraq’s mainly arid climate area. By assisting in the creation of efficient methods for dealing with rainstorm events, the created IDF curves are a major step towards advancing sustainable urban stormwater management in the country.

Consequences of Parasitized Prey Provision on the Fitness and Development Parameters of a Solitary Wasp, Rhynchium brunneum brunneum (Vespidae: Eumeninae)

Consequences of Parasitized Prey Provision on the Fitness and Development Parameters of a Solitary Wasp, Rhynchium brunneum brunneum (Vespidae: Eumeninae)

A 3-Month Modified Basketball Exercise Program as a Health-Enhancing Sport Activity for Middle-Aged Individuals.

Recreational team sports have received great acceptance lately, in different populations, indicating encouraging results in health-related quality of life. This study examined the efficacy of a 3-month basketball exercise program on selected indices of health (body mass-BM, body fat-BF, blood pressure-BP), functional capacity (flexibility of lower and upper limbs, balance), and physical fitness (maximum strength of lower limbs, trunk and handgrip, aerobic capacity) in middle-aged individuals. Forty middle-aged individuals (males and females; 40-55 years old) were randomly divided into (a) exercise (EG; n = 20) and (b) control groups (CG; n = 20). The EG followed a 3-month modified basketball exercise program (2 times/week; 24 training units), including different basketball drills with and without the ball (dribbling, passing, pivot, stops, etc.), to improve participants' health and physical fitness. Repeated measures ANOVA showed that the EG significantly increased their flexibility (17.23-74.88%; p < 0.001), static balance (44.76-54.69%; p < 0.001), and strength of lower limbs and trunk (11.67-13.13%; p < 0.001), while reducing BP (7.31-12%; p < 0.001), heart rate and RPE (5.30-34.37%; p < 0.001), and time during time-up-and-go test (-10.91%; p < 0.001). Handgrip strength, BM, and BF did not change following the program in the EG (p > 0.05). In the CG, the above variables remained stable. In conclusion, this program may be used to eliminate the detrimental effects of aging on health, functional capacity, and physical fitness parameters.

Lensed Type Ia Supernova “Encore” at z = 2: The First Instance of Two Multiply Imaged Supernovae in the Same Host Galaxy

A bright (m F150W,AB = 24 mag), z = 1.95 supernova (SN) candidate was discovered in JWST/NIRCam imaging acquired on 2023 November 17. The SN is quintuply imaged as a result of strong gravitational lensing by a foreground galaxy cluster, detected in three locations, and remarkably is the second lensed SN found in the same host galaxy. The previous lensed SN was called “Requiem,” and therefore the new SN is named “Encore.” This makes the MACS J0138.0−2155 cluster the first known system to produce more than one multiply imaged SN. Moreover, both SN Requiem and SN Encore are Type Ia SNe (SNe Ia), making this the most distant case of a galaxy hosting two SNe Ia. Using parametric host fitting, we determine the probability of detecting two SNe Ia in this host galaxy over a ∼10 yr window to be ≈3%. These observations have the potential to yield a Hubble constant (H 0) measurement with ∼10% precision, only the third lensed SN capable of such a result, using the three visible images of the SN. Both SN Requiem and SN Encore have a fourth image that is expected to appear within a few years of ∼2030, providing an unprecedented baseline for time-delay cosmography.

SBMLToolkit.jl: a Julia package for importing SBML into the SciML ecosystem.

Julia is a general purpose programming language that was designed for simplifying and accelerating numerical analysis and computational science. In particular the Scientific Machine Learning (SciML) ecosystem of Julia packages includes frameworks for high-performance symbolic-numeric computations. It allows users to automatically enhance high-level descriptions of their models with symbolic preprocessing and automatic sparsification and parallelization of computations. This enables performant solution of differential equations, efficient parameter estimation and methodologies for automated model discovery with neural differential equations and sparse identification of nonlinear dynamics. To give the systems biology community easy access to SciML, we developed SBMLToolkit.jl. SBMLToolkit.jl imports dynamic SBML models into the SciML ecosystem to accelerate model simulation and fitting of kinetic parameters. By providing computational systems biologists with easy access to the open-source Julia ecosystevnm, we hope to catalyze the development of further Julia tools in this domain and the growth of the Julia bioscience community. SBMLToolkit.jl is freely available under the MIT license. The source code is available at https://github.com/SciML/SBMLToolkit.jl.

DDE: Deep Dynamic Epidemiological Modeling for Infectious Illness Development Forecasting in Multi-level Geographic Entities.

Understanding and addressing the dynamics of infectious diseases, such as coronavirus disease 2019, are essential for effectively managing the current situation and developing intervention strategies. Epidemiologists commonly use mathematical models, known as epidemiological equations (EE), to simulate disease spread. However, accurately estimating the parameters of these models can be challenging due to factors like variations in social distancing policies and intervention strategies. In this study, we propose a novel method called deep dynamic epidemiological modeling (DDE) to address these challenges. The DDE method combines the strengths of EE with the capabilities of deep neural networks to improve the accuracy of fitting real-world data. In DDE, we apply neural ordinary differential equations to solve variant-specific equations, ensuring a more precise fit for disease progression in different geographic regions. In the experiment, we tested the performance of the DDE method and other state-of-the-art methods using real-world data from five diverse geographic entities: the USA, Colombia, South Africa, Wuhan in China, and Piedmont in Italy. Compared to the state-of-the-art method, DDE significantly improved accuracy, with an average fitting Pearson coefficient exceeding 0.97 across the five geographic entities. In summary, the DDE method enhances the accuracy of parameter fitting in epidemiological models and provides a foundation for constructing simpler models adaptable to different geographic areas.

An adaptive backstepping control strategy based on radial basis function neural networks for the magnetorheological semi-active suspension

Owing to nonlinear issues such as external disturbances and uncertain parameters within the semi-active suspension system (SASS), the vibration amplitude of the suspension system tends to increase, and the time required for the suspension system to reach a steady-state response is prolonged. Hence, this paper proposes an adaptive backstepping control strategy based on radial basis function neural networks (RBF-NNs). Firstly, the damping force characteristics of the magnetorheological (MR) damper are tested, and the experimental data are utilized for parameters identification and fitting of the Bouc-Wen model. To establish a connection between the controller and the forward model of the MR damper, the forward model of the MR damper, the inverse model of the MR damper, and the model of the MR-SASS are constructed. Secondly, the backstepping controller and the adaptive backstepping controller based on RBF-NNs are designed. The stability and reliability of the closed-loop suspension system are verified through stability analysis using Lyapunov function. Finally, the dynamic characteristics of the passive control, backstepping control, and adaptive backstepping control strategies based on RBF-NNs applied to MR-SASS are analyzed under B-Class road excitation and speed bump road excitation. The acceleration, suspension dynamic deflection, and tire dynamic load are selected as the evaluation indices. The results demonstrate that the adaptive backstepping controller based on RBF-NNs significantly enhances the ride comfort of the SASS.

Improved size effect law (SEL) considering size-dependent fracture process zone (FPZ) for quasi-brittle materials

Establishing a mechanistic model to simultaneously capture the descending size effect (DSE) and the change from DSE to the ascending size effect (ASE) remains a challenging issue for quasi-brittle materials. A size-dependent fracture process zone (FPZ) model is proposed and verified by experimental and simulative results. Subsequently, the size effect law (SEL) of unnotched specimens is improved by considering the size-dependent FPZ model, which is termed the improved SEL in this paper. Parametric studies are conducted for a better understanding of the improved SEL. It is found that the underlying mechanism of the DSE and the change from DSE to ASE is the competition between the relative rates of FPZ and specimen size change with respect to specimen size. The ASE is obtained when the relative rate of FPZ change is higher than that of specimen size. Conversely, the DSE is observed. No size effect exists when the relative rate of FPZ change is equal to that of specimen size. Experimental and simulative results are adopted to validate the improved SEL of unnotched specimens. The validation of the improved SEL indicates that the improved SEL not only accurately predicts the DSE, but also correctly captures the change from DSE to ASE. In addition, the size effect of nominal strength with different maximum aggregate size is well captured by the improved SEL. The fitting parameters of the improved SEL lie in the given interval. By comparing the determination coefficients R2 of the SEL, unified size effect law (USEL), and improved SEL, it is found that the R2 of the improved SEL is higher than that of the SEL for the DSE and is close to that of the IUSEL for the change from DSE to ASE. Therefore, it is recommended that engineers and researchers use the improved SEL to describe the DSE and the change from DSE to ASE of unnotched specimens.

Investigating the Creep Damage and Permeability Evolution Mechanism of Phyllite Considering Non-Darcy’s Flow

This study investigates the intricate interplay of hydraulic coupling, creep damage, and permeability evolution mechanisms in phyllite, focusing on their relevance to tunnel engineering design and long-term stability in soft rock formations. To achieve this, conventional triaxial tests were conducted on saturated phyllite specimens under creep-seepage acoustic emission conditions. The results were systematically analyzed to unveil the inherent characteristics of creep deformation, seepage rate evolution, and damage progression in phyllite when subjected to stress–seepage coupling. Furthermore, a permeability model for representative volume element (RVE) was developed based on meso-mechanics principles, considering the distinctive attributes of low-permeability non-Darcy’s flow in rock. Consequently, a novel relationship between effective damage and permeability was established. We determined that seepage pressure induces three key effects on the creep damage mechanism of phyllite samples: (1) It adds to the existing stress through the superposition of osmotic pressure and axial load, (2) it induces tensile expansion stress because of pore water pressure, and (3) it softens the fracture surfaces to some extent. More importantly, this study validates the relationship between effective damage and permeability through the fitting of creep and damage parameters, which were obtained from the test results, and it reveals a square relationship between subsequent damage and permeability under stress conditions. The findings of this study provide a robust theoretical foundation for comprehending the evolution of damage and permeability characteristics during the creep process of rock under seepage conditions. We obtained essential insights and quantitative analyses for comprehending the damage mechanisms in rock creep under hydraulic coupling, which has significant implications for tunnel engineering and long-term rock stability assessments in soft rock environments.

Steady-state two-phase relative permeability measurements in proppant-packed rough-walled fractures

Understanding multiphase flow in fractures filled with minerals and proppants is vital in various subsurface applications. Limited experimental data have led to reliance on correlations lacking physical basis. We conducted experiments to characterize relative permeability in rough-walled fractures packed with unconsolidated porous media. We tested fractures packed with water-wet 40/70 sand (silica) and surface-coated ceramic proppants. Brine and mineral oil were used as the wetting and non-wetting fluid phases, respectively. Steady-state (SS) drainage (non-wetting-phase displacing wetting-phase) and imbibition (wetting-phase displacing non-wetting-phase) tests were performed under a wide range of saturation histories (full-cycle and scanning-curves) to study relative permeability hysteresis of the propped fractures. Every SS drainage or imbibition test consisted of several discrete points at which fluid saturations and the corresponding relative permeability were measured by varying the fractional flow rates of fluids whilst maintaining a constant total flow rate. We analyzed residual non-wetting phase saturations and relative permeability trends to understand two-phase flow behavior in each proppant pack. High-resolution x-ray microtomography was used to understand the pore-scale topology, wettability, and to provide insights about the pore-scale displacement mechanisms involved in this study. The results showed that commonly used models to estimate relative permeabilities of fractures significantly overestimated the SS brine and oil relative permeabilities (denoted as krw and kro) measured in this study. Further analysis unveiled that the kro values during imbibition exceeded their drainage counterparts in both proppants, the ceramic proppant exhibited a lower initial water saturation and a higher end-point kro permeability at the end of the drainage displacement, as well as higher krw across all flooding processes. Updated fitting parameters for a Brooks-Corey-type relative permeability correlation are introduced. This study presents improved insights, extensive experimentally generated relative permeability data, and an updated relative permeability correlation, which can be collectively utilized to reduce uncertainties associated with continuum-scale forecasts of multiphase flow behavior in fractured subsurface formations.