Maintenance Resources Research Articles

Integrated operation and maintenance optimization for high-speed train fleets considering passenger flow

A joint optimization model of maintenance and operation of high-speed train fleets is established with the optimization objective of minimizing the total costs, considering dynamic passenger flow and maintenance resources. A new maintenance strategy CCPM (Coordinating Conflicts Preventive Maintenance) is proposed to optimize the problem. The effectiveness of the model and the strategy are verified by numerical examples. The comparison between the strategy in the paper and the existing approach proves that the new strategy is more effective and shows the importance of considering dynamic passenger flow. The model and the strategy provide decision support for the actual high-speed trains operation and maintenance program. This study also offers new ideas to the subsequent research on preventive maintenance of high-speed trains.

Effect of psychological empowerment on human resource management with the mediating role of emotional engagement in employees of selected sport federations

The purpose of this research was to investigate the effect of psychological empowerment on human resource retention in selected sports federations, with the role of emotional commitment as a mediating factor. A cross-sectional study was carried out. The statistical population of the study (270 employees) was all official staff of five selected federations (wrestling, volleyball, taekwondo, soccer and swimming). Based on the Morgan table, 175 individuals were selected as the statistical sample. In order to assess the studied variables, Spritzer's psychological empowerment questionnaire (1995), Allen and Meyer Commitment Measurement Questionnaire (1991), and Kaident’s staff retention questionnaire (2009) were used. The reliability of the questionnaires was 0.89, 0.87, and 0.84, respectively. In order to analyze the data, descriptive and inferential statistics (Kolmogorov Smirnov, Pearson Correlation Coefficient, Path Analysis Model) were used. The results showed that there is a statistically significant positive correlation between psychological empowerment and human resources maintenance (0.56). Emotional commitment with an impact factor of 0.35 plays a mediating role in relation to psychological empowerment in human resource retention. Therefore, the officials of sports federations can improve the maintenance of human resources by establishing a complete and desirable psychological empowerment and paying attention to the concept of emotional intelligence at the organization level.

Penilaian IT Governance dalam Manajemen Risiko IT Menggunakan Metode Quantitative dan Qualitative Risk Analysis

IT Governance is the structure of process relationships that guide and control an organization to achieve its vision and mission by adding value that will balance risks with IT and its processes. The analytical method used in this research is quantitative and qualitative risk analysis. The Quantitative Risk Analysis (QRA) approach focuses on analyzing the maintenance of IT resources to find risk factors that need serious consideration and treatment. For the qualitative risk analysis method, NIST SP 800-30 is used to analyze the various threat and risk attributes to provide guidelines for managing IT installations at XYZ Campus. Based on the QRA risk assessment, Internal HR who has access to the server is calculated as the highest potential campus loss. This can be seen in the risk aspect where losses caused by Internal HR who play the role of server admins have the greatest potential for losses. Qualitative assessment of risk management finds sources of threats with high risk are Internal HR and IT Infrastructure Systems. This level of risk can be detected during the hazard source classification process. The presentation of all risk analysis results can provide risk recommendations that will be communicated to campus IT management. To then be able to assist the campus in making a decision that includes policies, procedures, budgets, system operations, and change management.

Building strength for the long haul toward liberation: What psychology can contribute to the resilience of communities targeted by state-sanctioned violence.

State-sanctioned violence (SSV) has resounding effects on entire populations, and marginalized communities have long persisted in the work toward liberation despite continued SSV. This paper aims to bridge the gap between the vast scholarship on resilience and the practical challenge of sustaining and thriving in communities targeted by SSV. We use the theoretical frame of the Transconceptual Model of Empowerment and Resilience (TMER) to articulate the process of resilience and the resources that support it: maintenance, efficacy, skills, knowledge, and community resources. As a practical frame, we ground our application of the model in the experiences of the first two authors in their own communities. Centering examples from the Black Lives Matter movement and the CeCe McDonald Support Committee, we use our theoretical and practical frames to explore the scholarship on resilience relevant to resisting SSV, and we identify mechanisms for supporting community stakeholders' efforts to move toward liberation from SSV. We discuss implications for future research and activism, and we include a toolkit with suggested strategies as an appendix for psychologists, activists, and community stakeholders to consider as they work to facilitate community resilience and build a society free from SSV.

Urban Sustainable Development Index: a geospatial approach to add Tree Cover to HDI in São Paulo City

Human Development Index (HDI) has become an important tool to measure the basics aspects of human quality of living, being based on educational, economic and longevity dimensions. Over the years, criticism about the absence of an environmental dimension has emerged together with the need for knowledge about sustainable development at a local scale. For these reasons, this paper proposes a new approach for HDI, the Urban Sustainable Development Index (USDI), adding a Tree Cover indicator based on the most accepted criteria of 30% of tree cover to provide high quality of life and kept the balance between the other three dimensions of HDI. The normalized and weighted proposed index showed to be a promising alternative to complement existing sustainable indices impractical at local scale, mainly because they are based on carbon emission measurements. A Tree Cover indicator is more comprehensive, assessing greenhouse gases sequestration, heat islands attenuation, flora preservation, sustenance of fauna habitat, mitigation of extreme weather events and maintenance of water resources and soil stability. The case study in São Paulo city indicated that the transition from HDI to USDI resulted in a negative variation of almost 0.12, mostly in city central regions, and an increase up to 0.08 in peripherical regions - revealing how powerful can be geospatial analysis at a local scale, considering that USDI differs from the spatial distribution of HDI, valuing the importance of a sustainable urban index.

Managing Forbs Preferred by Greater Sage-Grouse and Soil Moisture in Mesic Meadows with Short-Duration Grazing

Mesic meadows provide valuable water and forage resources for wildlife and livestock in the arid western United States. Greater sage-grouse (Centrocercus urophasianus), a species of conservation concern, rely on these habitats because they support forb species of high importance to broods during late brood rearing. Because mesic meadows comprise a small fraction of the landscape, identifying grazing strategies compatible with maintenance and production of mesic resources is vital to balancing livestock production with suitable conditions for sage-grouse. We evaluated relationships between short-duration grazing treatments and habitat components important to sage-grouse in mesic meadows. In 2019 and 2020, we implemented short-duration (16 d) grazing treatments that varied by season (Early: early June; Late: early August) and intensity (control: 0%, moderate: 30−40%, high: 70−80% relative use). We evaluated cover and biomass percentages of high importance forbs (HIF), soil moisture, and noxious weed cover before and after grazing and again after pasture regrowth (Early: ≈13 wk, Late: ≈6 wk). Short-duration treatments did not reduce HIF cover or biomass. Early-season (P = 0.018) and high-intensity (P = 0.04) grazing increased HIF cover during the pregrazing sample period from 2019 to 2020, suggesting positive effects of these treatments on HIF cover during the pregrazing sample period. Postgrazing HIF cover and biomass percentages remained similar across treatments. Percentages of HIF biomass after regrowth were greater (P = 0.04) in early-season than late-season treatments in 2020. Seasonal declines in soil moisture from pregrazing to regrowth sample periods were greater (P < 0.001) in early-season treatments than late-season treatments but not associated with grazing intensity (P = 0.60). Cover of noxious weeds remained unchanged under short-duration treatments. Our study emphasizes the potential of early-season, high-intensity grazing to increase HIF cover and biomass for brood-rearing sage-grouse in mesic meadows over short time intervals.

Internal Control and Enterprise Green Innovation

Green innovation has become an important support to promote the strategic goals of peak carbon dioxide emission and high-quality economic development. This paper systematically examines whether internal control can effectively drive enterprise green innovation and achieve the “win–win” result of enterprise economic development and environmental protection. We found that internal control can significantly improve the green innovation level of enterprises, which is mainly reflected in the mandatory disclosure stage of internal control information and the other four elements of internal control, except the control environment. The mechanism test found that internal control can promote green innovation by reducing enterprise risks, alleviating agency conflicts, relieving financing constraints, and improving the rationality of innovation investment. The heterogeneity test found that the promotion effect of internal control on green innovation is more significant in large enterprises and private enterprises; internal control can effectively supervise the maintenance of relationship resources, and relationship resources positively regulate the promotion effect of internal control on green innovation; excessive executive power will weaken the internal control supervision and punishment of executives, and weaken the positive effect between internal control and green innovation; internal control can improve the utilization rate of government subsidies, and government subsidies positively regulate the positive effect of internal control on green innovation. The research conclusions enrich the market-oriented research on the driving factors of enterprise green innovation, and provide empirical evidence for enhancing the competitiveness of enterprise green innovation and achieving carbon neutrality.

Optimal selective maintenance scheduling for series–parallel systems based on energy efficiency optimization

With the industry sustainable development and increasing awareness of energy conservation, many manufacturing enterprises prefer to develop the operation and maintenance (O&M) with high production throughput and low energy consumption. In reality, many manufacturing systems are required to conduct a sequence of predefined missions with finite breaks between any two consecutive missions. To successfully complete the next mission production, maintenance actions are arranged and performed on machines during each scheduled break. In this paper, an energy-oriented selective maintenance policy (ESMP) for series–parallel systems is investigated. At each break, multiple maintenance actions with different impacts on machine degradation are available under limited maintenance resources. To obtain the throughput-and-energy based maintenance scheme, we first model the system energy efficiency based on system throughput and energy consumption. Then, we integer the energy efficiency modeling, production throughout analysis, and selective maintenance scheduling into an optimization model. And the model objective is to find the appropriate maintenance action for each machine at each break subject to cost and duration constraints. Numerical examples have been addressed to demonstrate the performance and adaptability of our proposed ESMP in long-term selective maintenance scheduling. Finally, a comparative analysis with traditional reliability-oriented policy shows the significant improvement of energy efficiency.

A Text Mining Framework for Analyzing Change Impact and Maintenance Effort of Software Bug Reports

Software practitioners often strive to achieve a “bug-free” software, though, it is a myth. Software Bug Categorization (SBC) models, which assigns levels (viz. “low”, “moderate” or “high”) to a software bug aid effective bug management. They assist in allocation of proper maintenance resources for bug elimination to improve software quality. This study proposes the development of SBC models that allocate levels on the basis of three software bug aspects i.e., maintenance effort required to correct a bug, its change impact and the combined effect of both of these. In order to develop SBC models, we use text mining approach, which extracts relevant features from bug descriptions and relates these features with different software bug levels. The results of the study indicate that the categorization of software bugs in accordance with maintenance effort and change impact is possible. Furthermore, the combined approach SBC models were also found to be effective.

A deep reinforcement learning assisted simulated annealing algorithm for a maintenance planning problem

Maintenance planning aims to improve the reliability of assets, prevent the occurrence of asset failures, and reduce maintenance costs associated with downtime of assets and maintenance resources (such as spare parts and workforce). Thus, effective maintenance planning is instrumental in ensuring high asset availability with the minimum cost. Nevertheless, to find such optimal planning is a nontrivial task due to the (i) complex and usually nonlinear inter-relationship between different planning decisions (e.g., inventory level and workforce capacity), and (ii) stochastic nature of the system (e.g., random failures of parts installed in assets). To alleviate these challenges, we study a joint maintenance planning problem by considering several decisions simultaneously, including workforce planning, workforce training, and spare parts inventory management. We develop a hybrid solution algorithm (DRLSA\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mathcal {DRLSA}$$\\end{document}) that is a combination of Double Deep Q-Network based Deep Reinforcement Learning (DRL) and Simulated Annealing (SA) algorithms. In each episode of the proposed algorithm, the best solution found by DRL is delivered to SA to be used as an initial solution, and the best solution of SA is delivered to DRL to be used as the initial state. Different from the traditional SA algorithms where neighborhood structures are selected only randomly, the DRL part of DRLSA\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mathcal {DRLSA}$$\\end{document} learns to choose the best neighborhood structure to use based on experience gained from previous episodes. We compare the performance of the proposed solution algorithm with several well-known meta-heuristic algorithms, including Simulated Annealing, Genetic Algorithm (GA), and Variable Neighborhood Search (VNS). Further, we also develop a Machine Learning (ML) algorithm (i.e., K-Median) as another benchmark in which different properties of spare parts (e.g., failure rates, holding costs, and repair rates) are used as clustering features for the ML algorithm. Our study reveals that the DRLSA\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mathcal {DRLSA}$$\\end{document} finds the optimal solutions for relatively small-size instances, and it has the potential to outperform traditional meta-heuristic and ML algorithms.

Types of interaction between rocks of Achimov sequence and Bazhenov formation

Many fields in the northeastern part of Surgut oil and gas region were discovered in 1960s-1970s. Currently, because to the development of reserves of large deposits of simple structure the restoration of the resource base and maintenance of the production level of oil and gas producing organizations are the main tasks. Its implementation is possible due to the development of new territories, increasing the depth of prospecting drilling, additional exploration of deposits of complex structure.Residual reserves of deposits in the studied area are confined to Achimov sequence and reservoirs in anomalous section of the Bazhenov formation.The article considers the types of deposits in Achimov sequence with normal and anomalous structure of Bazhenov formation. The author proposes a classification of oil deposits in the fondoform part of clinoforms. This classification clearly shows the possible relationship between Achimov sequence and the underlying bituminous deposits of Bazhenov formation.Some deposits associated with reservoirs in anomalous section of the Bazhenov formation may be missed targets; therefore, additional exploration is required. Since the reservoirs of Achimov sequence and anomalous section of the Bazhenov formation have different properties, it is necessary to differentiate them when planning geological and technological measures to extract oil.

The Utilisation of Educational Resources on Academic Achievement: A Case of Boa Amponsem Senior High School and Dunkwa Senior High Technical School

The study explored the utilisation of educational resources on academic achievement; a case of Boa Amponsem Senior High School and Dunkwa Senior High Technical School. The study used a descriptive research design with a quantitative approach. Census survey procedure was used to select teachers for the study and proportionate random sampling was also used to select students for the study. A questionnaire designed with literature was used to collect data for the study. Frequencies, percentages, descriptive statistics (i.e., mean and standard deviation), and, Pearson product-moment correlation was used to analyse the data that was gathered. The findings of the study revealed that educational resources available at Boa Amponsem Senior High School and Dunkwa Senior Technical School included a well-equipped library, well-equipped laboratory/studio, well-equipped computer lab, adequate classrooms, adequate desks and chairs in the classroom, adequate tables and chairs in the staff room, a school clinic, cafeteria/dining hall, adequate teaching resources, adequate number of offices, reliable water supply, and reliable electricity supply. The study further revealed that there is maximum utilization of educational resources as students and teachers utilize facilities in the laboratory, facilities in the library, facilities in the agriculture/ home science/ computer room, reference books, and textbooks in learning. Again, the findings showed that challenges in the utilisation of educational resources available to Boa Amponsem Senior High School and Dunkwa Senior Technical High School included lack of skills/competencies required for the use, lack of adequate storage facilities, inadequate provision of such educational resources, large class size compared to the availability of educational resources, lack of internet connections to the labs and departments, an inadequate period for practical lessons and teachers have a lot of teaching periods and lack of maintenance of these educational resources. The finding of the study indicated that there was a low/weak positive insignificant correlation between utilisation of educational resources and academic performance of students. Recommendations were made for the provision of more educational resources, ensuring maximum utilisation, and addressing challenges in the utilisation of educational resources.

Physical Resource Management and Maintenance Culture in Nigerian Universities

This paper deals with physical resource management and maintenance culture in Nigerian universities. Physical resource is the resource that can be seen (tangible). Resource management is the proper utilization and management of resources such that they are adequate and efficient for the needs of individuals in an organization. The importance of resource management in universities is to see whether the human resource is over or under-allocated in a particular faculty in the university to avoid wastage. Maintenance culture refers to the measures taken so that materials and resources are maintained properly. Universities refer to institutions of higher learning whereby an individual seeks to further his education after the secondary school level. The absence/ poor maintenance of physical resources in Nigerian universities would undoubtedly lead to a decline in the productivity of the university. This paper is to provide a means of efficient management and maintenance of physical resource in Nigerian universities. The objective of this paper is to proffer solutions to the challenges of effective management and maintenance of physical resources in Nigerian universities. The challenges facing the effective management and maintenance of physical resources in Nigerian universities were provided in this paper to include inadequate funding, inadequate facilities, and misuse of university facilities, amongst others. A conclusion was made and a way forward for the challenges facing the efficient management and maintenance of physical resource in Nigerian universities were provided. This includes the provision of adequate funds, punishment of greedy administrators that covert funds, provision of adequate modern facilities, proper maintenance of physical resource from time to time, amongst others.

The probability of occurrence of disperser and pollinator birds in urban riparian forests

Riparian forests are important for their ecological function and provision of services regarding the maintenance of water resources and wild fauna. Paradoxically, it is one of the ecosystems that suffer most from anthropization, especially urbanization. Thus, our objective was to compare the probability of occurrence of pollinating and dispersing species in two areas of riparian forest, where the periurban fragment is inserted in an area with patches of forest remnants and the urban fragment, an area of forest remnant located in a heavily constructed region. From the results obtained, we note that the riparian forest area considered preserved had the highest occurrence of dispersers, while the area inserted in the urban matrix had the highest occurrence of pollinators. In this way, it was possible to observe that the most preserved area showed greater equality between the groups, with a greater number of dispersers. Still, riparian forest isolated by strong urbanization showed that dispersers had a low frequency of occurrence, an essential function in the renewal and continuity of riparian forest in the future.

Influence of Participatory Planning for Project Capacity Building on Sustainability of Community Water Point Projects in Turkana County, Kenya

Existence of institutional framework in form of project operation management committees, advocacy group, technical and maintenance teams and resource mobilization committees improves sustainability of projects after handing over. The objective of this study was to assess the extent to which participatory planning for project capacity building influences sustainability of community water point projects in Turkana central, Turkana County. The target population of the study was 24,025 households of Turkana central constituency. Cochran formula with 95% level of confidence and margin of error of 5% was used to determine the sample size of 384 households. Sample selection was done using proportional quota and convenience sampling techniques. The data was collected using observations, focus group discussions, key informants’ interviews, and semi-structured questionnaire guides. Multiple Regression Analysis using Statistical Package for Social Sciences was used to analyze quantitative data. Framework Analysis and Narrative Analysis techniques were used to investigate qualitative data. Inter-rater reliability was used to measure the level of consistency of data collection instruments and content test was used to test instrument validity. The findings were tabulated, condensed, analyzed, and inferences drawn. Descriptive statistics were computed, and frequencies, percentages, arithmetic mean, and deviations presented. Pearson’s Moment Correlation (r), multiple regression and stepwise regression (R 2 ), F-tests were used to test the hypothesis. The results indicated F (1, 374) =1145.246, p=0.00&lt;0.05, r = .868, R 2 =.754. The study established that, for sustainability of community water point projects to be achieved, detailed plans to develop social capacities of stakeholders is a necessity. Stakeholders should be able to embrace communal objectives for resource management and capacitated enough to propose and develop action plans to achieve those objectives. They should have technical capacity to jointly manage their resources sustainably including ability to monitor resources and impose rules. In the same vein, project stakeholders should be able to develop and manage local institutions with the capacity to distribute costs and benefits impartially among themselves and have a self-motivated community leadership to catalyze demand and mediate disputes where and when needed. Keywords: Project Sustainability, Community Water Points, Participatory Project, Capacity Building, Planning, stakeholders, beneficiaries. DOI: 10.7176/DCS/12-3-02 Publication date: March 31 st 2022

Analisis Efektivitas dan Kontribusi Laba BUMD Terhadap Pendapatan Asli Daerah (PAD) Kota Bandung

This research aims to understand the effectiveness and contribution of BUMD profits to Bandung PAD, as well as the obstacles faced and the efforts made to increase profits. The type of research used is a mixed method. The population of this study is BUMD in Bandung City, and the sampling technique used is a saturated sample. The data types used are the literature data and the subject data. The data sources used are second-hand data and original data. The data analysis techniques in this study include effectiveness analysis and contribution analysis. The results of data analysis show that the effectiveness of the profit of the Bandung City BUMD is still in the ineffective category, with a very minimal contribution. There are obstacles faced by Bandung City BUMD in increasing profits, namely company management, business capital capabilities, asset maintenance, service capabilities, tariffs, and human resources. Efforts are being made by BUMD Bandung City to overcome this and to increase profits, namely by reducing operational costs, developing the use of information technology, maintaining and utilizing assets optimally, providing convenience in service, increasing employee competence.

Quality Assurance Parameters as Predictors of Teachers’ Motivation in Kwara State Public Junior Secondary Schools

The study examined quality assurance parameters as predictors of teachers’ motivation in public junior secondary schools in Kwara State. The study adopted the descriptive survey research design of correlation type. The population for this study comprised 5149 teachers of public junior secondary schools in Kwara State. The sample comprised of 640 teachers selected using the multistage sampling technique. A self-developed and validated research instrument titled “Quality Assurance Parameters and Motivation Questionnaire” (QAPMQ) was used to collect information with a reliability coefficient of 0.85. The result showed that teachers in public junior secondary schools in Kwara State had a moderate level of motivation (52.3%). The further showed that quality assurance parameters are significant predictors of teachers’ motivation (72.6% (Adj. R2= 0.726); and each of the quality assurance parameters of human resource maintenance (Beta= 0.704, t= 25.132) and data management (Beta= 0.366, t= 13.101) had significant predictions to teachers’ motivation, while funding was not significant (Beta= -0.275, t= -9.638) in Kwara State public junior secondary schools. Therefore, it was recommended that Kwara State government should not relent its efforts and continue to work collaboratively with Non-Governmental Organizations (NGOs), philanthropists, and other stakeholders in the education sector to ensure its assurance parameters are continued and appropriately used in stimulating teachers’ motivation in the State public secondary schools.

The Discourse of the Resilience of Hospitals in the Theoretical Context of the Organisation’s Concept of Resilience and Factors

The Discourse of the Resilience of Hospitals in the Theoretical Context of the Organisation’s Concept of Resilience and Factors

A Novel Road Maintenance Prioritisation System Based on Computer Vision and Crowdsourced Reporting

The maintenance of critical infrastructure is a costly necessity that developing countries often struggle to deliver timely repairs. The transport system acts as the arteries of any economy in development, and the formation of potholes on roads can lead to injuries and the loss of lives. Recently, several countries have enabled pothole reporting platforms for their citizens, so that repair work data can be centralised and visible for everyone. Nevertheless, many of these platforms have been interrupted because of the rapid growth of requests made by users. Not only have these platforms failed to filter duplicate or fake reports, but they have also failed to classify their severity, albeit that this information would be key in prioritising repair work and improving the safety of roads. In this work, we aimed to develop a prioritisation system that combines deep learning models and traditional computer vision techniques to automate the analysis of road irregularities reported by citizens. The system consists of three main components. First, we propose a processing pipeline that segments road sections of repair requests with a UNet-based model that integrates a pretrained Resnet34 as the encoder. Second, we assessed the performance of two object detection architectures—EfficientDet and YOLOv5—in the task of road damage localisation and classification. Two public datasets, the Indian Driving Dataset (IDD) and the Road Damage Detection Dataset (RDD2020), were preprocessed and augmented to train and evaluate our segmentation and damage detection models. Third, we applied feature extraction and feature matching to find possible duplicated reports. The combination of these three approaches allowed us to cluster reports according to their location and severity using clustering techniques. The results showed that this approach is a promising direction for authorities to leverage limited road maintenance resources in an impactful and effective way.

Multiscale analysis of tire and asphalt pavement interaction via coupling FEM–DEM simulation

With the aging of roads and the lack of resources for maintenance, a thorough understanding of the interaction between tires and asphalt pavements is crucial to optimize asphalt pavement surface design. Currently, most research on this interaction system is conducted using mesh-based methods in the frame of continuum mechanics, which are insufficient to model the discontinuity behavior of asphalt mixtures during their lifespan. In this study, the Contact Dynamics method is introduced to investigate this interaction system by coupling the finite element method (FEM) and the discrete element method (DEM). FEM is utilized to model the tire and capture the resulting contact stresses on the pavement surface, while DEM is used to model the heterogeneous structure of an asphalt mixture and examine internal mixture responses at the particle scale. Analysis of contact stress distributions for free-rolling and full-braking conditions proves the tire model’s effectiveness. According to particle displacement and force distributions, particles tend to flow along the longitudinal direction and undergo a high tangential contact force under full-braking compared with those under free-rolling, resulting in mixture instability and damage initiation. This study offers an enriching supplement and expansion to mesh-based methods for analyzing pavement surface degradation under tire loads, which can provide insight into pavement surface design.