Microscopic Simulation Research Articles

Multi-scale study on the crack resistance and energy dissipation mechanism of modified rubberized concrete

This study investigates the impact of rubber aggregates with different particle sizes, volume proportions, and pretreatment methods on the crack resistance and energy dissipation properties of rubberized concrete (RuC). The mechanisms of crack resistance and energy consumption are analyzed from macroscopic, mesoscopic, and microscopic perspectives using static and dynamic performance tests, digital image correlation (DIC), and scanning electron microscopy (SEM). These techniques reveal changes in crack patterns, interface transition zones, and pore characteristics. The findings demonstrate that rubber aggregates significantly slow crack propagation and enhance damping energy dissipation, with the volume content of rubber being the most critical factor. The inclusion of rubber aggregates introduces "cavity defects" into the concrete structure, which accounts for RuC's reduced strength compared to standard concrete while highlighting its advantages in vibration reduction and energy absorption. These insights are essential for advancing research on material modifications and microscopic numerical simulations, contributing to reduced carbon emissions.

Synergy of chelating agents and surfactants on the wettability and pore structure of coal dust: Experimental study and molecular simulation

To reduce the hazards of coal dust pollution to miner health and the environment, and to realize efficient wetting and settling of coal dust, this paper evaluates the wettability of tetrasodium glutamate diacetate (GLDA)–aliphatic alcohol polyoxyethylene ether sodium sulfate (AES), hereafter termed G–A, by selecting the surfactant through macroscopic experiments and microscopic simulations. With the help of molecular simulation to study the synergistic mechanism of the surfactants and chelating agents, the functional group changes and mesoscopic modification of coal dust particles were evaluated in combination with characterization experiments. Comprehensive analysis showed that the G-A solution had the best wettability with a low surface tension of 22.77 mN/m, the diffusion rate of the solution increased to 1.25°/s, and the contact angle with the coal dust decreased to 18° within 12 s. After infiltration, the median particle size of coal dust reached 38.140 μm, which increased by 148 %. The pores and slits on the surface of the coal dust particles are further increased, providing surfactants with more extensive adsorption sites, and the proportion of hydrophilic groups on the surface of coal increased by 8.42 %, with the consequent improvement of wettability. This study provides a theoretical basis for the research and development of more environmentally friendly and efficient dust reducing agents in the field of spray dust reduction.

Remarkable chlorobenzene absorption by carboxylic acid based deep eutectic solvents

A novel purification technology for the absorption of chlorobenzene (CB) using carboxylic acid based deep eutectic solvents (DESs) as absorbents was proposed and systematically investigated, combining experiments with microscopic molecular simulations. A series of newly designed DESs synthesized and evaluated for their CB absorption performance, revealing that DESs with quaternary phosphonate as hydrogen bond acceptors (HBAs) and long-chain fatty acid-based hydrogen bond donors (HBDs) exhibit remarkable CB absorption performance. Additionally, it illustrated that both the structure and acidity of HBD significantly impact the absorption capacity. Consequently, the DES comprising tetrabutylphosphonium chloride ([P4444][Cl]) and decanoic acid (DecA) with molar ratio of 1:2 was identified as the possessing optimal absorbent. Notably, after undergoing five cycles of absorption–desorption processes, the CB absorption capacity in [P4444][Cl]-DceA (1:2) was almost maintained at approximately 467 mg/g (Henry’s law constant of 4.90Pa m3/mol) at 30 °C. NMR characterization revealed no chemical bonding between [P4444][Cl]-DceA and CB, indicating that it’s a physical absorption process. Finally, the interaction mechanism was elucidated by COSMO-RS model, quantum chemical calculations and wave function analysis. This work fills the gap of CB removal by DES absorption and proves that DES is a promising green solvent for the removal of chlorinated volatile organic compounds.

Investigating a Toolchain from Trajectory Recording to Resimulation

The growing variety of transportation options and increasing traffic congestion pose new challenges for road safety. As a result, there is an intensified focus on developing automated driving features and assistance systems aimed at minimizing accidents caused by human errors. The creation of these systems requires a substantial amount of testing kilometers, with estimates suggesting that around 2.1 billion kilometers would be necessary to ensure that each situation pertinent to the driving function is encountered at least once with a probability of 50%. This paper advances the microscopic simulation of traffic scenarios beyond linear patterns, utilizing the open-source environment openPASS. It addresses the research question of whether existing microscopic simulations are able to realistically represent non-linear traffic scenarios. A comprehensive toolchain integrates simulation with video recordings and laser scans. The study compares recorded traffic flow data with simulations at a T-junction, assessing the realism of vehicle models and trajectory representation. Three scenarios are analyzed, considering vehicles and pedestrians. The 3D geometry of the scene was captured with a laser scanner, enabling the mapping of recorded video data onto a geo-referenced environment. Object trajectories were extracted using an ’Regions with Convolutional Neural Networks features’ object detector. While openPASS simulated vehicle and pedestrian behaviors effectively, limitations in trajectory variability and reaction times were observed. These findings highlight the need for more realistic behavior models. This research emphasizes the necessity for improvements to accommodate complex driving behaviors and pedestrian dynamics.

A Microscopic Experimental Study on the Dominant Flow Channels of Water Flooding in Ultra-High Water Cut Reservoirs

The water drive reservoir in Shengli Oilfield has entered a stage of ultra-high water cut development, forming an advantageous flow channel for the water drive, resulting in the inefficient and ineffective circulation of injected water. Therefore, the distribution characteristics of water drive flow channels and their controlled residual oil in ultra-high water cut reservoirs are of great significance for treating water drive dominant flow channels and utilizing discontinuous residual oil. Through microscopic physical simulation of water flooding, color mixing recognition and image analysis technology were used to visualize the evolution characteristics of water flooding seepage channels and their changes during the control process. Research has shown that during the ultra-high water content period, the shrinkage of the water drive seepage channel forms a dominant seepage channel, forming a “seepage barrier” at the boundary of the dominant seepage channel, and dividing the affected area into the water drive dominant seepage zone and the seepage stagnation zone. The advantage of water flooding is that the oil displacement efficiency in the permeable zone is as high as 80.5%, and the remaining oil is highly dispersed. The water phase is almost a single-phase flow, revealing the reason for high water consumption in this stage. The remaining oil outside the affected area and within the stagnant flow zone accounts for 89.8% of the remaining oil, which has the potential to further improve oil recovery in the later stage of ultra-high water cut. For the first time, the redundancy index was proposed to quantitatively evaluate the control effect of liquid extraction and liquid flow direction on the dominant flow channels in water flooding. Experimental data showed that both liquid extraction and liquid flow direction can regulate the dominant flow channels in water flooding and improve oil recovery under certain conditions. Microscopic physical simulation experiments were conducted through the transformation of well network form in the later stage of ultra-high water content, which showed that the synergistic effect of liquid extraction and liquid flow direction can significantly improve the oil recovery effect, with an oil recovery rate of 68.02%, deepening the understanding of improving oil recovery rate in the later stage of ultra-high water content.

Coordinated Ramp Metering Considering the Dynamics of Mixed-Autonomy Traffic

The introduction of connected autonomous vehicles may bring opportunities and challenges to traditional traffic control instruments, like ramp metering. This paper starts by constructing the fundamental diagram for mixed-autonomy traffic based on the car-following behaviors of both connected autonomous vehicles and human-driven vehicles. Then, analyses are performed on the main factors that influence the critical velocity, critical density, and road capacity under mixed-autonomy traffic. Two methods named COE-HERO and TRLCRM are developed to support the implementations of coordinated ramp metering for freeways with mixed-autonomy traffic. The COE-HERO method enhances the HERO method by incorporating a critical occupancy estimation module. Both COE-HERO and TRLCRM consider dynamic traffic flow parameters of mixed-autonomy traffic. The TRLCRM method is a reinforcement learning-based approach with a two-stage training framework, enabling it to adapt to varying mixed-autonomy demand scenarios. Extensive microscopic simulations show that the learning-based TRLCRM method can effectively alleviate bottleneck congestion and is robust to deal with various traffic scenarios. The COE-HERO method performs better than the HERO method, indicating the necessity of critical occupancy estimation in the implementations of coordinated ramp metering.

Experiment and Simulation Study on the Adsorption Interaction between a Fluorescent Tracer and a Montmorillonite Crystal in Drilling Fluid.

The adsorption interaction of oil field tracer in drilling fluid plays a significant role in tracer monitoring (TM) technology in the petroleum industry. In this work, the adsorption performances of Rhodamine B (RhB+) and fluorescein sodium (Fln-) tracers with montmorillonite (MMT) crystal in drilling fluid were investigated by both experimental and simulation methods. For the experimental aspect, the macroscopic results indicate thermodynamic monolayer adsorption by the Langmuir model and kinetic chemical adsorption by the pseudo-second-order (PSO) model. As a result, MMT shows a larger adsorption capacity (qm) for RhB+ than for Fln- with but stronger adsorption spontaneity (ΔrGmθ) for Fln- than for RhB+ with kJ mol-1 < kJ mol-1. Meanwhile, the interaction rate (k2) of Fln- was shown to be faster than that of RhB+ with . For simulation insight, MMT shows much higher system stability (E) for Fln- than for RhB+ with and . Meanwhile, the microscopic simulation results reveal configuration changes and site distinctions for RhB+ and Fln- interactions with the MMT crystal. The different adsorption responses were explained by proposing an interaction mechanism of force dominance and position orientation. Specifically, Fln- was deduced to interact with metal (Al, Ca) and metalloid (Si) elements in the MMT crystal interlayer by "upright-insertion" orientation while RhB+ was deduced to interact with oxygen atoms on the MMT crystal surface by a "flat-lying" orientation. Hydrogen bonds, the electrostatic interaction, and the coordination effect were revealed to dominate for the interaction of tracer adsorption. This work provides both performance and mechanism investigation of fluorescent tracer adsorption interaction with the MMT crystal in drilling fluid, which is of great significance in reservoir exploitation.

Measurement and analysis of heterogeneous road transport parameters using Smart Traffic Analyzer and SUMO Simulator:An experimental approach

The main objective of research work is to study the characteristics of heterogeneous road transport environment & compare its dynamic parameters with the performance metrics measurement in terms of error rate & accuracy for vehicle count and classification using Smart Traffic Analyzer (STA) and SUMO Traffic Simulator. SUMO GUI is a simple tool for microscopic traffic simulation and helps to obtain vehicle dynamic parameters in the easiest way. Experimental research is also carried out by capturing live traffic video at study area of four way intersection road and analyzed through STA. The outcome results from SUMO and STA explicit overall accuracy of 96.63 %, and 95.62 % for vehicle count with the error rate of 3.35% & 4.37%. Similarly for vehicle classification, it provides the overall accuracy of 97.21% and 83.01% with the error rate of 2.78% & 16.97% respectively.

Machine-Learning Methods Estimating Flights’ Hidden Parameters for the Prediction of KPIs

Complex microscopic simulation models of strategic Air Traffic Management (ATM) performance assessment and decision-making are hindered by several factors. One of the most important is the existence of hidden parameters—such as aircraft take-off weight (TOW) and the selected cost index (CI)—which, if known, would allow for more effective performance modeling methodologies for assessing Key Performance Indicators (KPIs) at various levels of abstraction/detail, e.g., system-wide, or at the level of individual flights. This research proposes a data-driven methodology for the estimation of flights’ hidden parameters combining mechanistic and advanced Artificial Intelligence/Machine Learning (AI/ML) models. Aiming at microsimulation models, our goal is to study the effect of these estimations on the prediction of flights’ KPIs. In so doing, we propose a novel methodology according to which data-driven methods are trained given optimal trajectories (produced by mechanistic models) corresponding to known hidden parameter values, with the aim of predicting hidden parameters’ values of unseen trajectories. The results show that estimations of hidden parameters support the accurate prediction of KPIs regarding the efficiency of flights: fuel consumption, gate-to-gate time and distance flown.

Experimental and molecular dynamic simulation studies of landfill contaminated groundwater remediation by graphene oxide coated zeolite

ABSTRACT Graphene oxide (GO) has proven effective in wastewater treatment due to its capability to adsorb heavy metals and organic contaminants. Zeolite is also widely used in contaminant remediation as a reactive material in permeable reactive barrier (PRB). Experimental column flow-through tests were applied in this study to investigate the remediation ability of composite granule-graphene oxide coated zeolite (GOZ) on FA, Pb2+ and NH4 +, from municipal landfill contaminated groundwater. Microscopic characterization and molecular dynamic simulation were carried out in sequence to understand the adsorption process. The results demonstrated that GO significantly enhanced zeolite’s adsorption capacity for Pb2+ and FA by 147.5% and 164.8%, respectively, though NH4 + removal experienced a slight decrease of 25% after GO coating. The ion exchange of Pb2+ resulted in more significant partial collapse compared to NH4 + due to different effective diameter comparing with the channel size of zeolite. However, GO coating relieved the framework deformation by engaging in functional group reactions during Pb2+ adsorption. A recommended surface area coating ratio between 47.0% and 78.4% was identified, as values outside this range may lead to significant GO deformation or inefficient FA adsorption. The GO-zeolite granules displayed significant potential in remediating various contaminants while effectively preventing GO aggregation and zeolite collapse. As technological advancements reduce GO production costs, the economic feasibility of using GOZ in groundwater remediation is increasingly promising.

Do the sparser access points have less impact on arterial traffic? A microscopic simulation-based study

A dynamic microscopic traffic flow simulation within a ring arterial context was developed to investigate the effects of access point spacing on urban arterial flow under a right-in-right-out access management system. The microscopic traffic flow model, centered on car-following and lane-changing behaviors, was established based on vehicle interactions. The car-following aspect encompasses free driving, car-following behavior, and deceleration and braking states while lane-changing considerations include decision-making and acceptable gap assessment. Experimental scenarios account for arterial traffic density, access traffic demand intensity, average access point spacing, and variation coefficient of access point spacing. The traffic flow and speeds within the ring arterial were evaluated across 5040 operational conditions (equating to 5880 simulation hours). The traffic flow trends and speed variations with density across different access spacing scenarios were analyzed. We made an intriguing discovery: the impact on arterial traffic flow increases with larger average access point spacing, challenging conventional traffic planning recommendations that advocate for greater spacing. Additionally, access traffic minimally affects the overall arterial flow when arterial traffic volume is low. By highlighting these critical insights, this study introduces novel considerations for designing and managing access points.

Facile construction of zirconium/iron bimetallic organic frameworks for fluoride efficient removal from aqueous phase: An integrated experimental and theoretical investigation

This work presents the synthesis of Zr/Fe bimetallic organic frameworks (Zr/Fe-UiO-66) with varying compositions via a straightforward solvothermal method, targeting fluoride ions (F−) removal from the aqueous phase. Adsorption experiments elucidated the effect of factors (i.e., adsorbent dosage, initial concentration (C0), temperature, contact time and pH) on fluoride adsorption, and the parameters were optimized. The results show that the Zr/Fe-UiO-66(C) achieved the maximal uptake capacity of 164.4 mg/g, with the conditions of pH = 5.0, T = 298 K, C0 = 190 mg/L. The adsorption behavior of fluoride on Zr/Fe-UiO-66 can be well followed with the pseudo-second-order (PSO) kinetic model and the Sips isotherm model, described as the spontaneous, chemical driven and endothermic process. The adsorption mechanism was comprehensively explained by characterizations and microscopic simulations, such as molecular dynamics methods (MD) and independent gradient model analysis (IGM), which involves the chemical bonding, hydrogen-bond interaction and electrostatic interactions. Furthermore, Zr/Fe-UiO-66(C) exhibited excellent fluoride ion selectivity and superior stability. After 5 cycles of adsorption, Zr/Fe-UiO-66(C) maintained the removal efficiency of 83.4 % for F−. This research provides significant insights into the development of bimetallic metal–organic framework materials and fluoride removal research.

Experimental and molecular dynamics simulation studies on the effect of composite surfactants on the wettability of anthracite coal

In order to improve the wettability of coal bed water injection, the effects of several composite surfactants on the wettability of anthracite coal were investigated. Firstly, the wettability of different composite surfactants on anthracite was analysed by macroscopic experiments (surface tension and settling time) to determine the optimal concentration and optimal ratio of composite surfactants. Secondly, the effects of adsorption of different composite surfactants on the physicochemical properties of the coal dust surface were investigated by mesoscopic experiments (scanning electron microscopy, energy spectrometer analysis, infrared spectroscopy, X-ray electron spectroscopy and zeta potential), and the results showed that the content of hydrophilic functional groups (Si-O-Si, C-O-C, C-O and CO) on the surface of anthracite coal after treatment with the composite surfactant increased significantly, and the surface potential value decreased significantly in absolute value, agglomerated large coal particles would be formed on the coal surface, and the cracks between coal particles were favourable for the penetration of aqueous solution. Finally, the synergistic mechanism of different composite surfactants was analysed from the perspective of microscopic molecular simulation. The results showed that the composite surfactants enhanced the interaction energy of the coal/composite surfactant/water system, improved the relative concentration distribution of the system, and increased the diffusion coefficient of water molecules. The results of the study can provide valuable guidance for the development of new composite surfactants with wetting effect, which has important application value for mine dust control.

Morphological characteristics of low-asphalt RAP and influence of its reaction product during combustion heating on regenerated asphalt

To provide reference for regeneration of the finely separated low-asphalt reclaimed asphalt pavement (RAP), the macroscopic and microscopic laboratory testing and quantum chemical simulation were combined. The morphological characteristics of the basalt and limestone low-asphalt RAP were analyzed. The low-asphalt RAP needs to be dried before regeneration, so the reaction mechanism and product of the asphalt film on its surface during drying were clarified. The product influence on the temperature resistance and fatigue performance of the virgin asphalt was studied, so as to consider their mixing during the subsequent regeneration process. Result shows that the gradation of limestone low-asphalt RAP is coarser and particles are slenderer than basalt with the same particle size grade. The 5–10 mm low-asphalt RAP particles are slenderer than those in the 10–20 mm grade. In the drying cylinder, asphalt basically generate no new functional groups below 200℃, while the asphalt film on the low-asphalt RAP surface undergoes pyrolysis to produce carbon black with the particle size around 100μm in the combustion heating area. The most easily oxidation or pyrolysis site in asphalt molecule is the carbon atom connected to the benzene ring. The pyrolysis of asphalt molecules to generate free radicals in the local oxygen deficient environment is the prerequisite for the carbon black formation, and pyrolysis requires higher temperature than oxidation because of its higher energy barrier. As the carbon black content increases, the penetration and ductility of asphalt decrease, the softening point increases, the high-temperature performance is enhanced, the low-temperature performance is weakened, and the fatigue performance is not significantly affected. As the particle size of carbon black increases, the decrease range in penetration, ductility and low-temperature performance of asphalt declines, the increase or improvement range of softening point and high-temperature performance enhanced, while the fatigue performance still shows no significant and regular change.

Microscopic simulation on triaxial compression creep of rockfill based on subcritical crack propagation theory

Over time, natural cracks within particles propagate under tensile stress, leading to the delayed breakage of these particles, which significantly contributes to the time-dependent deformation of rockfill materials. In this study, a delayed strength model for spherical particles with virtual cracks is proposed using subcritical crack propagation theory and validated through indoor single-particle creep tests. Based on the model, particles are represented as ideal spheres in the context of triaxial compression creep simulations for rockfill, with special attention to particle size effects, discreteness, and temporal factors. The combined influence of long-term strength and maximum contact force is crucial in determining the delayed particle breakage. Comparative analysis with indoor triaxial creep tests demonstrates that the Discrete Element Method (DEM) simulations accurately model the creep deformation phenomena related to delayed particle breakage in rockfill. Furthermore, statistical analysis indicates that a minor fraction of delayed particle breakage has a negligible impact on the temporal distribution of the Normalized Maximum Contact Force (NMCF).

Study on viscoelastic properties and rheological properties of SBS modified asphalt for road use with service life

SBS modified asphalt is an important material in the construction of high-grade highway, and its performance changes directly affect the pavement performance. In this study, SBS modified asphalt was extracted from the actual pavement with different service years, and the rheological properties of SBS modified asphalt with different service years were studied by macroscopic test and microscopic molecular dynamics simulation. The macroscopic test results show that the needle penetration value of SBS modified asphalt increases by 50.6 % after two years of service, and the viscosity of SBS modified asphalt increases by 54.8 % after 12 years of service. With the increase of service life, G∗ and G″ of SBS modified asphalt showed an increasing trend, and δ and G’’/G’ showed a decreasing trend. The molecular dynamics simulation results of SBS modified asphalt were consistent with the macroscopic experimental results. The rheological properties of SBS modified asphalt showed a decreasing trend with the service life, and the interfacial energies between SBS modified asphalt and aggregate also showed a decreasing trend. The research in this paper will provide a theoretical basis for the future study of the deterioration law of SBS modified asphalt and the formulation of road maintenance plan.

Transport in cellular aggregates described by fluctuating hydrodynamics

Biological functionality of cellular aggregates is largely influenced by the activity and displacements of individual constituent cells. From a theoretical perspective this activity can be characterized by hydrodynamic transport coefficients of diffusivity and conductivity. Motivated by the clustering dynamics of bacterial microcolonies we propose a model of active multicellular aggregates and use recently developed macroscopic fluctuation theory to derive a fluctuating hydrodynamics for this model system. Both semianalytic theory and microscopic simulations show that the hydrodynamic transport coefficients are affected by nonequilibrium microscopic parameters and significantly decrease inside of the clusters. We further find that the Einstein relation connecting the transport coefficients and fluctuations breaks down in the parameter regime where the detailed balance is not satisfied. This study offers valuable tools for experimental investigation of hydrodynamic transport in other systems of cellular aggregates such as tumor spheroids and organoids. Published by the American Physical Society 2024

How Connected Cars Could Capture Cloud Dynamics for Solar Forecasting—Evidence from Two Simulation Scenarios

The rapidly increasing share of fluctuating electricity from photovoltaics calls for accurate approaches to estimate cloud motion, the primary source for the varying power supply. While local sensor networks are prominent in targeting forecast horizons too short for image‐based methods, they have minimal spatial coverage. This work presents the first step towards expanding those approaches to spatially scalable sensor networks: With the motivation of using automotive light sensors as a sensor network, two excerpts from a microscopic traffic simulation serve as simulative sensor networks. A fractal‐based cloud shadow pattern passes the sensor network areas with defined velocities and directions, which shall be estimated using the cumulative mean absolute error method. The evaluation results indicate that the more extensive observation areas compensate for the dynamics in the sensor network when compared to a reference work with a static sensor grid. Furthermore, this work shows how the estimates deteriorate with lower vehicle penetration rates (PR) and longer building shadows due to a lower solar elevation angle. At a penetration rate of 40%, the root mean square errors for both sensor networks are still below 5 ms−1. In conclusion, the spatiotemporal characteristics of a vehicle network offer a potential for estimating cloud movements.

Evaluating the environmental benefits of autonomous vehicles in urban intersections: a microscopic simulation approach

This research delves into the environmental and energy implications of incorporating autonomous vehicles (AVs) into urban traffic systems, mainly focusing on emissions and fuel efficiency. The study employed PTV VISSIM simulation software to model a four-leg signalized intersection in Balgat, Ankara, under varying levels of AV integration and driving behaviors. A total of 21 scenarios were simulated, assessing the impact of cautious, normal, aggressive, and platooning AV behaviors on emissions of CO, NOx, and VOCs, as well as fuel consumption, across different traffic signal cycle durations. The results indicate that shorter signal cycle times consistently significantly reduce emissions and fuel consumption, irrespective of AV driving behavior. The most notable improvements were observed in platooning scenarios, attributed to their optimized traffic flow. In contrast, longer cycle times increased emissions and fuel consumption, especially with human-driven and cautious AVs, due to more frequent idling and stop-and-go traffic patterns. This study highlights the importance of refining AV driving algorithms and optimizing signal control systems to reduce environmental impacts and improve fuel efficiency in urban settings, providing crucial insights for advancing sustainable urban mobility and traffic management strategies.

Promoting Sustainable Mobility: A Walkability Analysis for School Zone Safety

Promoting sustainable mobility and planning walkable school zones is a pressing priority, as it involves the movement of Vulnerable Road Users (VRUs), such as children aged 5–19, along with adult companions, parents, and school staff or faculty. If these children have a safe walking experience today, they will grow up to become ambassadors of sustainable mobility. In this study, several school zone areas were considered in the capital city of India, Delhi. To conduct a comprehensive walkability analysis, three distinct methods were employed: a stakeholder survey, an evaluation of existing walkable corridors, and a microscopic simulation using the Social Force Model (SFM). The limited focus on school zone safety issues in developing nations presents a case for studying the specific concerns of the school zone pedestrians, aiming to assess the magnitude of the problem, provide design centric solutions, and pick an efficient solution for implementation. The results highlight the parameters influencing pedestrian safety in school zones and their effect on pedestrian attributes. This research work can be replicated for school zone safety assessments across the world. This study will benefit the policymakers, urban planners, local government agencies, and traffic management professionals by assisting them in evaluating the walkability of school zones and promoting sustainable mobility choices.