Engineering Construction Research Articles

The Impact of Renewable Energy on Low Energy Consumption in Civil Engineering Construction

As the main representative of new energy, photovoltaic energy is widely used in civil engineering construction, its purpose is to reduce the energy consumption in the project, there is a deviation in the integration of new energy and civil engineering, and it cannot effectively play its own advantages. Continuously analyze the changes in the energy consumption values of civil engineering. Then, the influencing factors of building energy consumption were introduced, and the covariance matrix was constructed, and the engineering construction benefit was taken as the ultimate goal. When calculating energy consumption, the dual benefits of building benefits are fully considered, and environmental protection and engineering energy consumption are estimated to reduce the error of energy consumption calculation. The results show that new energy can reduce the high energy consumption value in the project, improve the light transmittance, enhance the conversion rate of sunlight, and provide support for the transportation, lighting and thermal insulation of the building, with an increase rate of 10~25%, and the new energy can reduce the cost of civil engineering, with a reduction rate of 19~26%, and improve the economic and social benefits, with an increase of more than 10%. Therefore, new energy can reduce the energy and energy consumption of civil engineering, and expand the scope and application depth of new energy development.

Study on InSAR deformation information extraction and stress state assessment in a railway tunnel in a plateau area

Introduction: The study proposes a method for evaluating stress distribution in high-altitude Tibetan Plateau railway tunnels using high-precision radar satellite time-series interferometric synthetic aperture radar technology.Methods: To effectively monitor and prevent geological hazards during the construction process, this method i employed, as it serves as a component of advanced geological prediction and surrounding rock deformation monitoring technology for high-altitude tunnels, particularly in the Dongelu Tunnel of the China–Tibet Railway. The study utilizes time-series interferometric synthetic aperture radar to obtain deformation information for Dongelu Tunnel area between 2022 and 2023 from Sentinel- 1A orbit images. This quantitatively investigates the upper mountain body and line-of-sight direction along the tunnel. The deformation characteristics are correlated with high-frequency and high-precision automated vertical displacement monitoring results, determining the spatiotemporal distribution of tunnel deformation. In this study, a model that determines the vertical stress state of the Dongelu Tunnel under loading near the entrance and evaluates its health status was established.Results: The results show that the surface deformation of the mountain above the tunnel axis develops slowly and is relatively small, with a maximum vertical deformation rate of 1–3 mm/year. The average stress on the tunnel arch is 5.54 MPa, with a fluctuation range of 0.01 MPa. Temporal Q9 changes in various parts of the tunnel are periodic, with maximum fluctuations observed in December 2022. The study reveals inconsistent surface settlement of the tunnel arch and mountain above it, causing minor vertical stress changes. As the tunnel construction progresses, vertical stress variation shows periodicity because of an initial imbalance in internal stress within the mountain. Stress fluctuations near the tunnel entrance occur during the initial excavation phase, gradually diminishing as the project progresses and internal stress stabilizes.Discussion: The proposed tunnel monitoring and stability assessment method can reduce its impact on engineering construction and provide guidance for advanced geological prediction.

Experimental Study on the Shear Failure Properties and Damage Constitutive Model of Rocks.

In the construction of underground geological engineering, a variety of rocks were often encountered, and the engineering surrounding rocks was prone to shear fracturing. Shear mechanics tests were conducted on a variety of rocks under various joint angles. By studying the shear mechanical characteristics, acoustic emission behavior, and damage degree of the different rock types, we can obtain an insight into their bearing capacity and fracture mechanisms. An obvious inflection point from the elastic to plastic behavior can be observed for the specimens during the process of shear mechanics tests, and the shear behavior was divided into three phases. The acoustic emission signals significantly increased for coal during the second phase, while those of sandstone and shale start to increase during the third phase, which is from the peak point to fracture. The analyses of the shear failure and acoustic emission properties showed that the crack propagation angle increases as the normal stress of rock increases. It was proved that the joint angles and normal stresses of rock could effectively hinder the development of vertical fractures. Based on the shear failure and acoustic emission properties, a constitutive model capable of describing the shear behavior of different types of rocks was developed. This constitutive model can accurately describe the shear fracture properties of the various rocks. The shear failure properties and damage constitutive model of rocks in this study can be used to reduce engineering surrounding rock instability caused by shear.

Artificial Neural Network Model for Predicting Mechanical Strengths of Economical Ultra-High-Performance Concrete Containing Coarse Aggregates: Development and Parametric Analysis.

Ultra-high-performance concrete with coarse aggregates (UHPC-CA) has the advantages of high strength, strong shrinkage resistance and a lower production cost, presenting a broad application prospect in civil engineering construction. In view of the difficulty in establishing a mathematical model to accurately predict the mechanical properties of UHPC-CA, the back-propagation artificial neural network (BP-ANN) method is used to fully consider the various influential factors of the compressive strength (CS) and flexural strength (FS) of UHPC-CA in this paper. By taking the content of cement (C), silica fume (SF), slag, fly ash (FA), coarse aggregate (CA), steel fiber, the water-binder ratio (w/b), the sand rate (SR), the cement type (CT), and the curing method (CM) as input variables, and the CS and FS of UHPC-CA as output objectives, the BP-ANN model with three layers has been well-trained, validated and tested with 220 experimental data in the studies published in the literature. Four evaluating indicators including the determination coefficient (R2), the root mean square error (RMSE), the mean absolute percentage error (MAPE), and the integral absolute error (IAE) were used to evaluate the prediction accuracy of the BP-ANN model. A parametric study for the various influential factors on the CS and FS of UHPC-CA was conducted using the BP-ANN model and the corresponding influential mechanisms were analyzed. Finally, the inclusion levels for the CA, steel fiber, and the dimensionless parameters of the W/B and sand rate were recommended to obtain the optimal strength of UHPC-CA.

An overview of potential excavation compensation method for tunnelling in deep rock engineering

The complicated geological environment of deep rocks poses new challenges to tunnel and mining engineering. Some thorny disasters such as large deformation of soft rock and rockburst are becoming more and more prominent. However, the classic tunnelling methods represented by the mine tunnelling method and the new Austrian tunnelling method are generally unsatisfactory in addressing these issues due to the limited self-stability of surrounding rock mass. Therefore, the excavation compensation method (ECM) with the core of active stress compensation has been proposed and applied in practical engineering construction to solve the above problems. After extensive engineering practice, the theoretical foundation, key technologies, and construction system of ECM have been established and improved. This article provides a comprehensive overview of this novel tunnelling method. In addition, its controlling effects on surrounding rock are demonstrated by two typical engineering examples. It could provide some new ideas and references for the development of future tunnelling technology.

The Hysteresis Behavior of Steel Beam–Column Joint with the Load Bearing-Energy Dissipation Connection for Converter Station Building

Prefabricated converter station building has been gradually applied in the field of power engineering construction due to the advantages of standardized design, high construction efficiency, and quality control. The beam–column joint is the essential constitutive part to ensure structural integrity and reliable force transmission for the prefabricated structure. In this paper, a novel load bearing-energy dissipation connection is proposed and applied to the beam–column joint to improve seismic performance and seismic resilience. Pseudo-static tests were conducted on the beam–column joint with the load bearing-energy dissipation connection, and the test results demonstrated that the tested beam–column joints developed with similar failure modes, and the damage was concentrated in the load bearing-energy dissipation connection while the beam and column remained elastic. The beam–column joint with the load bearing-energy dissipation connection had stable hysteresis behavior, with favorable bearing capacity and energy dissipation behavior. A shorter slip length and a larger bolt distance could lead to better stress development and enhance the bearing capacity, while the slip length barely affected the ductile behavior. Moreover, a finite element model was established and validated to extend the parametric study to provide a preliminary understanding of the mechanical mechanism of the proposed beam–column joint with the load bearing-energy dissipation connection. It was confirmed that the load–-deformation behavior was greatly affected by the slip length, but the slip length barely affected the initial stiffness. The width of the sliding steel fuse influenced the bearing capacity and the degradation behavior. A wider width could lead to a higher bearing capacity and improve the degradation behavior. Based on the analysis of the stress development and stress distribution corresponding to different feature points, it was concluded that the use of bearing-energy dissipation improved the stress development in the framing components and achieved damage concentration.

Pelatihan Pembuatan Beton bagi Siswa SMK N 3 Semarang

<div align="justify"><p><em>Concrete is a solid mixture that hardens, consisting of components such as cement, sand, gravel, and water that are mixed. Civil engineering construction is related to concrete, including the construction of roads, buildings, dams, houses, and irrigation channels. Considering the importance of knowledge related to concrete, students of SMK N 3 Semarang who are majoring in construction engineering and housing need to be well informed. Many vocational high school students are still unaware of the proper process of making concrete that meets the desired quality standards. Students of SMKN 3 Semarang, who are expected to be able to work immediately after completing their studies, need to be equipped with knowledge about the concrete-making process. The purpose of this activity is to improve the knowledge of SMKN 3 Semarang students regarding the quality of concrete materials, the making of K-225 quality concrete, and the value of the concrete slump test. The PkM team from Universitas Semarang conducted training on making concrete for SMK N 3 Semarang students using discussion methods and laboratory practice. As a result of this training, the majority of students understand the process of making concrete in terms of material quality, K-225 concrete mix design, and slump test testing.</em></p></div>

Joint probability analysis and mapping of typhoon-induced wind, wave, and surge hazards along southeast China

The southeastern coastal region of China frequently faces typhoon attacks, posing significant threats to its ever-growing infrastructure. Quantifying multiple typhoon-induced hazards in terms of wind, wave, and surge would provide valuable data to support structural design, risk assessments, and disaster mitigation. This study simulated the evolution of wave and surge driven by typhoon wind fields using the SWAN + ADCIRC coupling model, generating extreme samples of wind speed, significant wave height, and surge height. Trivariate joint probability distributions were established at six typical coastal stations (Hong Kong, Xiamen, Fuzhou, Wenzhou, Zhoushan, and Shanghai) based on optimal copula functions. Using the environmental contour and conditional return period methods, appropriate combinations of design environmental loads were analyzed for a specific return period. The results revealed two reasonable combination types for the 100-year design period. One involves the combination of the 100-year dominant variable value computed using a univariate probability distribution, with two 20-year secondary variable values calculated using the second conditional return period. The second combination selects a variable group corresponding to the maximum value of the dominant variable on the environmental surface. These methods and findings were further extended to the entire computational area to develop hazard maps covering the Southeast Sea area of China. The hazard maps show that the design values of significant wave height increase with distance from the coast. In contrast, the spatial distribution of surge presents the opposite pattern. This study provides a novel perspective on structural design values subjected to multiple disasters and offers a reference for offshore engineering construction in the sea area of southeast China.

Assessing the Impact of Climate Comfort on Labor Productivity in Hydropower Engineering Construction in Southwest China

Labor productivity exerts a significant influence on the construction cycle and investment in hydropower projects. Consequently, it is a crucial factor in the estimation of the cost of hydropower project construction. The mechanisms that are modulated by subjective factors have been extensively studied. However, the assessment of labor productivity in objective environments with regular changes is usually considered using a single factor, especially in special environments where the influence of environmental factors is of greater concern. As the most extensive region of China’s water-energy resources, the Southwest region has a lengthy tradition of using altitude or oxygen as an inherent criterion for the assessment of labor productivity. However, the applicability of inherent standards is limited. Therefore, we tried to assess the spatial and temporal changes in labor productivity based on the changes in meteorological conditions in Southwest China, employing climate comfort indicators in this study. The result identified five distinct regions of climate change in Southwest China (R-I to R-V). In particular, there is minimal variation in labor productivity as assessed by climate comfort indicators and the elevation between R-I and R-II. R-III and R-IV are influenced by oxygen, temperature, and humidity, while R-V is affected by a multitude of factors. Our findings indicate that temporal and spatial variations in meteorological conditions can result in up to a threefold difference in productivity at the same altitude in different regions. Importantly, our study provides valuable theoretical insights for engineering project management. In particular, it can be concluded that altitude is not a reliable indicator for evaluating labor productivity in high-altitude construction.

Study on dynamic mechanical properties and microscopic damage mechanisms of granite after dynamic triaxial compression and thermal treatment

As underground mining operations gradually extend deeper, the conditions for orebody occurrence become increasingly complex, and various geological disasters occur frequently. Rock masses are prone to different degrees and types of damage, making it impractical to continue using intact rock as a reference. To study the dynamic mechanical properties of damaged rock under actual conditions, this study subjected granite samples to impact and high-temperature damage. Detailed observations were made of the samples' surface morphology and microstructure before and after damage, and the patterns of damage changes were investigated. Subsequently, uniaxial compression tests at different loading rates were conducted on the damaged samples. By calculating the loading rate effect sensitivity, it was found that as the damage increased, the rate effect gradually diminished. In addition, this study also summarized the influence of damage and loading rate on the macroscopic failure characteristics of the samples. The novelty of this study lies in focusing on damaged rock, which more closely resembles the actual rock conditions encountered in most underground mining operations today. This research can provide a reference for stability assessment and safe construction in deep mining rock engineering and offers important insights into the feasibility of non-explosive extraction of damaged rock.

Does the selection of the fracture model affect the calculation of the permeability of a rock mass?

The permeability of a rock mass is an indispensable and significant parameter for the construction of rock engineering. Since most fractures are buried in the rock mass, accurately assessing the permeability of the rock mass has posed a challenge to scholars in the field. The discrete fracture network (DFN) is recognized as an effective method for calculating the permeability of rock masses. However, the impact of the fracture model on permeability calculations is neglected during the construction of DFNs. This study uses the FracMan software to conduct a series of numerical simulation experiments, demonstrating that the selection of the fracture model significantly influences permeability calculations. Furthermore, we investigate the effects of constructing different circular DFNs based on trace information from various sampling windows. The results indicate that relying solely on a circular DFN derived from a single sampling window to calculate permeability is unreliable, and we reveal the fundamental laws of how DFNs constructed based on different fracture models influence the permeability assessment of rock masses. Therefore, integrating multi-source information from rock mass outcrops and boreholes, in conjunction with selecting an appropriate fracture model for constructing DFNs, is crucial for accurate permeability calculations of rock masses.

Risk early warning model of tunnel engineering based on computer vision and CNN

Abstract Safety management in tunnel construction is important to ensure the safety of construction personnel and equipment. This paper proposes a tunnel engineering risk early warning model based on computer vision and convolutional neural network (CNN), aiming at realizing real-time monitoring and risk early warning of the construction site using modern image processing technology and deep learning algorithm. Many image data of tunnel engineering construction sites were collected, and the data were preprocessed and marked. Then, the paper designs a depth CNN model for feature extraction and risk identification of construction site images. Through the performance evaluation of the model on the training set and test set, the effectiveness and feasibility of the model in risk early warning are verified. The experimental results show that the proposed model achieves high accuracy, recall, and F1 score on the test set, which is superior to the traditional method based on image features and artificial rules. At the same time, we analyzed the prediction results of the model on the actual construction site images. We found that the model can effectively identify different risk factors and has strong generalization ability and practicability. To sum up, this study provides a new technical means and solution for the safety management of tunnel engineering, which has important theoretical and practical significance.

A study on civil engineering construction simulation technology based on artificial intelligence for civil buildings

Abstract This research delves into utilizing Artificial Intelligence (AI) in civil engineering, specifically construction simulations. The primary objective is to reconcile the discrepancies between conventional structural analysis techniques and the actual performance of structures. By integrating AI technologies—neural networks, cellular automata, and support vector machines— with data mining, this research proposes a novel approach for simulating civil building constructions. Traditional methods, often constrained by underlying assumptions, fail to capture the complex behaviors of engineering structures accurately. The developed AI simulation framework utilizes experimental and on-site data to construct digital models, enabling precise prediction of structural behaviors without the limitations of traditional assumptions. Results indicate that AI-enhanced simulations can significantly improve the accuracy of structural analysis, demonstrating potential for wider application in civil engineering. This advancement promises to enhance the predictability, efficiency, and safety of civil constructions, marking a significant step forward in the field.

Research on the evaluation method of whole process engineering consulting service modes based on uncertain multiple-attribute group decision-making

With the continuous development of the economy and society, the engineering construction industry has experienced rapid growth, and higher requirements have been put forward for engineering consulting services. Currently, most engineering consulting service enterprises in China only provide relevant consulting services for engineering construction at a certain stage, lacking overall planning and overall control over the entire lifecycle of engineering construction. In order to improve the scientific level of fixed assets investment decision-making and construction management, it is of great value to explore professional engineering consulting services covering the whole process of project construction in the project decision-making stage and implementation stage to achieve the optimization of project quality and economic benefits. The whole process engineering consulting service modes (ECSM) evaluation is a multiple-attribute group decision-making (MAGDM). Recently, the TODIM technique and MACONT technique was created to put forward MAGDM. The interval neutrosophic sets (INSs) are created as a tool for managing fuzzy information during the whole process ECSM evaluation. In this work, the interval neutrosophic number TODIM-MACONT (INN-TODIM-MACONT) technique is created to put forward the MAGDM under INSs. Finally, a numerical analysis for whole process ECSM evaluation is given to validate the proposed technique. The main contributions are outlined: (1) the TODIM and MACONT technique was enhanced under INSs; (2) Information Entropy is created to conduct the weight information under INSs. (3) the INN-TODIM-MACONT technique is created to implement the MAGDM under INSs; (4) a numerical example for whole process ECSM evaluation and some comparative analysis is created to verify the INN-TODIM-MACONT technique.

Research on remote reference denoising method based on non-coaxial and non-coplanar tunnel NMR detection

Abstract The limited space within the tunnel constrains the size of the antenna for NMR detection, thereby significantly impacting the signal-to-noise ratio (SNR) of NMR signals. Insufficient SNR data poses substantial challenges to obtaining reliable NMR signals. The paper presents a novel approach to address the challenge of strong background noise in tunnel environments and low SNR data by incorporating the ground multi-channel remote reference denoising method into tunnel NMR advance detection. Specifically designed for narrow tunnels, a multi-channel non-coaxial and non-coplanar remote reference denoising method is proposed. Firstly, the effectiveness of the non-coaxial, non-coplanar remote reference denoising method is verified in the laboratory environment. Secondly, the correlation between the detector antenna and the reference antenna is calculated theoretically to ensure the significant correlation between the detector antenna and the reference antenna. Finally, two processing methods of reference denoising and non-reference denoising are carried out respectively by combining the tunnel detection data. By comparing the inversion results and the engineering construction results, the effectiveness of non-coaxial and non-coplanar remote reference denoising methods in tunnel NMR detection is proved, which provides relevant research support for expanding the application of tunnel NMR detection technology.

Reform and Exploration of Sensor Course Teaching based on OBE Concept and Proteus Simulation

Under the background of promoting the construction of new engineering, this paper aims at the problems existing in the traditional teaching mode of "Sensor Principle and Application" course for the Internet of Things major, based on the OBE concept and Proteus simulation platform, combined with the teaching practice, and carried out reform and exploration on the training objectives, theoretical and practical teaching, teaching methods and achievement evaluation system of this course. The result-oriented, student-centered and mixed online and offline teaching practice shows that the teaching effect of the course has been significantly improved, and the students' engineering practice ability has been enhanced.

Geophysical and Geotechnical Investigation of Building’s Foundation around Crusher area, Lokoja, Kogi state, Nigeria

Integration of geophysical and geotechnical techniques had been utilised to investigate the foundation of a site characterised with building cracks. It was conducted at Muhammadu Buhari Estate, Crusher area in Lokoja, Nigeria, The study aims to delineate geological features responsible for the failure of the building through 2-D resistivity imaging and electromagnetic surveys in conjunction with geotechnical analysis. Seven 2-D electrical resistivity imaging traverse lines, seven electromagnetic profiles were run and seven soil samples were collected and analysed. Each of the sample point were located on each of the 2-D imaging traverse. Traverses 1-7 host samples 1-7 respectively. The findings revealed high conductivity in unstable areas (resistivity ranging from 11-42 Ohm-m, 1-38 Ohm-m, 4-12 Ohm-m, 1-15 Ohm-m, and 11-30 Ohm-m for traverse 1-5, respectively) and low conductivity in stable ones (resistivity ranging from 19-91 Ohm-m and 109-2056 Ohm-m for traverse 6 and 7, respectively) and they occur at near surface to a relatively shallow depths (ranging from 0-6m depth) in all the profile. Geotechnical analysis showed high clay content in the soil, affecting its engineering properties in most of the studied locations. Soil grain oversize data analysis indicated a range between 70.1% and 75.1% for unstable portions (samples 1-5), with an average of 72.22% fines while percentage coarse ranges between 24.9 and 29.9 with an average of 27.78%. Their optimum moisture content ranged from 10.4% to 11.50%, with a mean value of 11.18%. Also, their plastic index averaged at 10.044%, while linear shrinkage varies between 1.79% and 3.60%, with an average of 2.808%. All these are the responsible factors for the soil instability in this axis of the investigated site. But for the stable portions (samples 6 and 7), Soil grain oversize data analysis is between 18.1% and 18.2% with an average of 18.65% fines while percentage coarse range between 81.9 and 80.8 with an average of 81.35%. The optimum moisture content ranged from 10.4% to 11.50%, with a mean value of 11.18%, the optimum moisture content ranged from 11.3% to 12.0%, with a mean of 11.65%, the plastic index equals zero (0), linear shrinkage varies between 5.57% and 5.71%, with an average of 5.64% and all these parameters are responsible for the stability of these two portions. The California Bearing ratio (CBR) results graded the soil samples into different types with the unstable portion characterised with clay, silty clay and sandy clay while the stable portion are classified into well graded sands. The well graded sands are very suitable for the engineering construction and hence the buildings on this portion showed no cracks and failure because of lack of differential settlements unlike that of the unstable portion characterised with cracks due differential settlements that led to structural failure at those sides of the study site. The geophysical results corroborate well with geotechnical results and these highlight the value of combining geophysical and geotechnical techniques to evaluate the integrity of the subsurface, providing information that is essential for designing infrastructure foundations and determining stability.

Numerical simulations of the acoustic and electrical properties of digital rocks based on tetrahedral unstructured mesh

Abstract Unconventional reservoirs typically exhibit strong heterogeneity leading to a significant scale effect in digital rock physics simulations. To ensure the reliability of the simulation results, improving computational efficiency and increasing sample sizes are crucial. In this study, we present a numerical finite element simulation method for the acoustic and electrical properties of digital rock cores based on tetrahedral unstructured meshes. We calculated the elastic moduli and electrical resistivity of the Fontainebleau sandstone digital rock samples. A comparison was made between the tetrahedral mesh and the traditional voxel-based hexahedral mesh in terms of the accuracy and efficiency of finite element numerical simulations. The results indicate that this numerical simulation method based on the tetrahedral mesh exhibits high accuracy comparable to experimental results, and its computational efficiency is significantly improved compared to the traditional hexahedral mesh method. These findings highlight the advantages of this finite element simulation method in improving the computational scale and efficiency of digital rock simulations. It effectively addresses common computational resource constraints in dealing with large-scale core systems and facilitates better integration with engineering construction, well-logging instrument simulations, and production applications.

Spatial distribution law of landslides and landslide susceptibility assessment in the eastern Himalayan syntaxis region

The eastern Himalayan syntaxis region is located on the eastern edge of the Qinghai–Tibet Plateau, and it is one of the regions with the most intense geological tectonic activity in the world. There have been many large-scale landslides in the eastern Himalayan syntaxis region and the distribution of these landslides is of great significance for the inversion of regional tectonic activity strength, major engineering construction and urban–rural planning. However, no researchers have systematically studied all these landslides of this area. In this study, based on Google Earth satellite imagery, landslides were identified using artificial visual interpretation. Then, we analysed 11 landslide-influencing factors were selected, comprising topographic factors (elevation, slope, aspect, curvature), geological environmental factors (strata, distance to faults, distance to water, distance to roads, normalized difference vegetation index), inducing factors (peak ground acceleration, rainfall), the relationships between the distribution law of landslides and influencing factors. Finally, we used the logistic regression model, the weight of evidence model and the weight of evidence–logistic regression coupled model to evaluate the landslide susceptibility.

Micromechanism insights and constitutive modeling for deformation in a novel high manganese austenitic steel

We explore the mechanical behavior and microstructural evolution of a novel high manganese austenitic steel (HMAS), extensively applied in underground engineering and structural construction. Our investigation focuses on two variants of HMAS, namely HMAS-1.9 and HMAS-10, which exhibit distinct yield strengths and elongation behaviors. Electron backscatter diffraction (EBSD), transmission electron microscopy (TEM) and X-ray diffraction (XRD) were employed to elucidate the evolution of microstructures during plastic deformation. Based on these experimental results, we developed a new phenomenological multiscale constitutive model that captures the mechanical behavior of HMAS, integrating micromechanisms and microstructural evolutions. Optimized with the MATLAB genetic algorithm toolbox, this model was successfully implemented in a uniaxial tensile finite element model (FEM) within ABAQUS, proving its efficacy in predicting both macroscopic flow stress and microstructural evolutions. Our findings highlight the important roles of initial grain size, dislocation density, and twin fraction in determining the mechanical properties of HMAS. Throughout the deformation process, both HMAS variants demonstrate similar plastic deformation behaviors, characterized by comparable rates of increase in dislocation density and twinning fraction, accompanied by a consistent trend of grain refinement. These findings not only deepen our understanding of the complex relationship between microstructure and mechanical properties of the HMAS steel, but also provide an effective multiscale constitutive modeling approach for predicting its deformation behavior.