摘要：
The existence of multiple cracks accelerates chloride ion penetration within damaged concrete, substantially shortening the lifespan of the structure. Therefore, this paper conducts an in-depth analysis of chloride migration mechanisms in cracked concrete subjected to multiple cracks under drying-wetting cycles. Firstly, a series of accelerated chloride diffusion experiments were conducted on prestressed concrete beams subjected to multiple cracks. The analysis examines how crack width, depth, and density affect chloride concentration distribution. Then, a chloride diffusion coefficient prediction model incorporating the effects of multiple cracks was established using the crack interaction function and verified through experimental data. Finally, this paper explored the distribution patterns of chloride concentration and convection zones in concrete subjected to multiple cracks under various environmental conditions. The experimental results showed that crack width exerts the strongest effect on chloride diffusion, followed by crack depth, while crack density has the smallest impact. At the same depth of diffusion, the chloride concentration in concrete specimens with crack width of 0.3 mm increased by 45 % and 25 % on average compared with those with crack width of 0.1 mm and 0.2 mm, respectively. The dry-wet time ratio and initial moisture saturation significantly affect chloride concentration distribution, with the depth of the convection zone showing a negative correlation with initial moisture saturation.
The existence of multiple cracks accelerates chloride ion penetration within damaged concrete, substantially shortening the lifespan of the structure. Therefore, this paper conducts an in-depth analysis of chloride migration mechanisms in cracked concrete subjected to multiple cracks under drying-wetting cycles. Firstly, a series of accelerated chloride diffusion experiments were conducted on prestressed concrete beams subjected to multiple cracks. The analysis examines how crack width, depth, and density affect chloride concentration distribution. Then, a chloride diffusion coefficient prediction model incorporating the effects of multiple cracks was established using the crack interaction function and verified through experimental data. Finally, this paper explored the distribution patterns of chloride concentration and convection zones in concrete subjected to multiple cracks under various environmental conditions. The experimental results showed that crack width exerts the strongest effect on chloride diffusion, followed by crack depth, while crack density has the smallest impact. At the same depth of diffusion, the chloride concentration in concrete specimens with crack width of 0.3 mm increased by 45 % and 25 % on average compared with those with crack width of 0.1 mm and 0.2 mm, respectively. The dry-wet time ratio and initial moisture saturation significantly affect chloride concentration distribution, with the depth of the convection zone showing a negative correlation with initial moisture saturation.
作者机构：
[Cheng, Xiaokang; Xiao, Junyi; Peng, Jianxin; Zhang, Jianren] Changsha Univ Sci & Technol, Sch Civil Engn, Key Lab Bridge Engn Safety Control, Dept Educ, Changsha 410114, Hunan, Peoples R China.;[Xiao, Junyi] Guangzhou Vocat Coll Technol & Business, Sch Emergency Technol, Guangzhou 511442, Guangdong, Peoples R China.;[Yang, Yiming] Hunan City Univ, Sch Civil Engn, Yiyang 413000, Hunan, Peoples R China.;[Dong, You] Hong Kong Polytech Univ, Dept Civil & Environm Engn, Hong Kong 999077, Peoples R China.
通讯机构：
[Peng, JX ] C;[Yang, YM ] H;Changsha Univ Sci & Technol, Sch Civil Engn, Key Lab Bridge Engn Safety Control, Dept Educ, Changsha 410114, Hunan, Peoples R China.;Hunan City Univ, Sch Civil Engn, Yiyang 413000, Hunan, Peoples R China.
关键词：
Post-tensioned concrete structures;Chloride wet-dry environment;Performance degradation;Concrete creep;Prestress loss
摘要：
The shrinkage, creep of concrete, and relaxation of prestressing tendons lead to prestress loss in prestressed concrete (PC) structures under conventional environments. The prestress loss of PC structures is also affected by corrosive environments resulting from alternating wet and dry. Therefore, a new model for predicting prestress loss under alternating damp and dry chloride environments is proposed. The model considers the coupled effects of corrosion on concrete creep and the remaining cross-sectional area of steel reinforcement/prestressing tendons. A 300-day experimental study is conducted on a series of post-tensioned prestressed concrete beams subjected to a cyclic wet-dry corrosive environment to discuss prestress loss. The effectiveness of the model is verified through experimental results. The results indicate that the existing codes underestimate the long-term prestress loss of PC structures in corrosive environments. The proposed model can accurately predict the long-term prestress loss of PC beams. Compared with conventional environments, the creep coefficient of concrete under a dry-wet alternating corrosive environment increases by 15 %, resulting in a 12.4 % increase in the long-term prestress loss of the structure.
The shrinkage, creep of concrete, and relaxation of prestressing tendons lead to prestress loss in prestressed concrete (PC) structures under conventional environments. The prestress loss of PC structures is also affected by corrosive environments resulting from alternating wet and dry. Therefore, a new model for predicting prestress loss under alternating damp and dry chloride environments is proposed. The model considers the coupled effects of corrosion on concrete creep and the remaining cross-sectional area of steel reinforcement/prestressing tendons. A 300-day experimental study is conducted on a series of post-tensioned prestressed concrete beams subjected to a cyclic wet-dry corrosive environment to discuss prestress loss. The effectiveness of the model is verified through experimental results. The results indicate that the existing codes underestimate the long-term prestress loss of PC structures in corrosive environments. The proposed model can accurately predict the long-term prestress loss of PC beams. Compared with conventional environments, the creep coefficient of concrete under a dry-wet alternating corrosive environment increases by 15 %, resulting in a 12.4 % increase in the long-term prestress loss of the structure.
期刊：
JOURNAL OF COMPUTING IN CIVIL ENGINEERING,2025年39(3):04025017 ISSN：0887-3801
通讯作者：
Da Hu
作者机构：
[Yongsuo Li] Professor, Hunan Engineering Research Center of Structural Safety and Disaster Prevention for Urban Underground Infrastructure, Hunan City Univ., No. 518, Yingbin East Rd., Yiyang 413000, PR China;[Kai Qi] Master’s Candidate, College of Civil Engineering, Univ. of South China, Henyang, Hunan 421001, PR China;[Xiaoxuan Weng; Ze Tan; Jing Liu] Master’s Candidate, College of Civil Engineering, Hunan City Univ., Yingbin East Rd., Yiyang, Hunan 413000, PR China;[Da Hu] Professor, Hunan Engineering Research Center of Structural Safety and Disaster Prevention for Urban Underground Infrastructure, Hunan City Univ., No. 518, Yingbin East Rd., Yiyang 413000, PR China
通讯机构：
[Da Hu] P;Professor, Hunan Engineering Research Center of Structural Safety and Disaster Prevention for Urban Underground Infrastructure, Hunan City Univ., No. 518, Yingbin East Rd., Yiyang 413000, PR China
关键词：
Prediction of jacking force;Pipe jacking tunnel;Deep-learning;Convolutional neural network;Long-term and short-term memory network
摘要：
The advancement of computer technology has led to the increased utilization of new algorithms, such as machine learning, in various fields including underground engineering. The estimation of jacking force plays a critical role in the construction of rectangular jacked tunnels. Conventional prediction techniques often rely on empirical models and statistical analysis, posing challenges in accurately forecasting the jacking force for intricate tunnel structures. To overcome this obstacle, a method for predicting tunnel jacking force is proposed, which integrates a convolutional neural network (CNN) and long short-term memory network (LSTM). By utilizing geometric and operational parameters as inputs, the CNN extracts data features, which are subsequently inputted into the LSTM network for time-series modeling. This model effectively processes continuous jacking force data by comprehending the complex correlations within the data set, resulting in more precise predictions of future jacking force values. Comparative analysis with traditional methods such as the artificial neural network, single CNN model, and LSTM network demonstrates that the CNN-LSTM model significantly reduces prediction errors in tunnel jacking force estimation, thereby enhancing model accuracy. Consequently, the efficacy of the CNN-LSTM model has been validated, showcasing the benefits of employing deep-learning techniques for predicting jacking force in pipe jacking tunnel construction.
关键词：
Wind loading;wind turbine structure;extended foundation;transient response;response frequency
摘要：
To study the transient response characteristics of wind turbine structures-extended foundations under wind loads in mountainous areas, this paper develops a simplified analytical model based on soil-structure interaction theory. It explores the effects of constraint conditions, wind speed, and foundation shear wave speed on the transient response behavior. By analyzing the time-domain and frequency-domain trends of tower top displacement, foundation horizontal displacement, and foundation rotation angle, the relationship between foundation shear wave speed and the safe wind speed of the wind turbine is clarified. The results indicate that different constraint conditions lead to variations in the calculated resonance frequency, maximum tower top displacement, and acceleration response spectrum. Furthermore, based on the analysis of the tower top acceleration response curve, the influence interval of frequency can be categorized into three distinct ranges: stable range, small influence range, and large influence range. Wind speed primarily influences the vibration amplitudes of the three displacement components, while the overall trend of the time-displacement waveform remains unchanged. The foundation shear wave speed primarily affects the displacement of the foundation itself, exerting a smaller influence on the displacements of the wind turbine structure. Notably, the total displacement at the tower top decreases as the shear wave speed increases. Moreover, the safe wind speed of the wind turbine shows a positive correlation with the foundation shear wave speed, indicating a linear relationship between the two variables.
摘要：
Reasonable prediction of chloride concentration in the interfacial zone of precast and cast-in-place concrete structures is crucial for assessing the durability of such structures. In this paper, the machine learning-based deterministic model is first proposed to predict the chloride concentration in the interfacial zone using seven machine learning methods. Then, an uncertainty prediction model of chloride concentration in the interfacial zone is developed considering the aleatory uncertainty of input parameters and epistemic uncertainty of model itself. Finally, the effectiveness of the proposed prediction model is validated by using the collected database containing 2505 sets of data. The research results indicate that the deep neural network (DNN) model performs the best in predicting chloride concentration in the interfacial zone among the seven machine learning (ML) models, achieving an R 2 value as high as 0.9847. The proposed uncertainty prediction method not only demonstrates high prediction accuracy but also effectively accounts for uncertainty in the prediction process. The obtained prediction interval coverage probability (PICP) of the proposed method reaches to 0.9457 for the collected database. Moreover, rising dropout rate can improve the interval coverage at the expense of interval clarity, but the overall prediction performance still improves. Additionally, the prediction performance of uncertainty model for chloride concentration in interfacial zone is more sensitive to epistemic uncertainty than aleatory uncertainty in this case study.
Reasonable prediction of chloride concentration in the interfacial zone of precast and cast-in-place concrete structures is crucial for assessing the durability of such structures. In this paper, the machine learning-based deterministic model is first proposed to predict the chloride concentration in the interfacial zone using seven machine learning methods. Then, an uncertainty prediction model of chloride concentration in the interfacial zone is developed considering the aleatory uncertainty of input parameters and epistemic uncertainty of model itself. Finally, the effectiveness of the proposed prediction model is validated by using the collected database containing 2505 sets of data. The research results indicate that the deep neural network (DNN) model performs the best in predicting chloride concentration in the interfacial zone among the seven machine learning (ML) models, achieving an R 2 value as high as 0.9847. The proposed uncertainty prediction method not only demonstrates high prediction accuracy but also effectively accounts for uncertainty in the prediction process. The obtained prediction interval coverage probability (PICP) of the proposed method reaches to 0.9457 for the collected database. Moreover, rising dropout rate can improve the interval coverage at the expense of interval clarity, but the overall prediction performance still improves. Additionally, the prediction performance of uncertainty model for chloride concentration in interfacial zone is more sensitive to epistemic uncertainty than aleatory uncertainty in this case study.
摘要：
To investigate the dynamic characteristics and safe operation speed threshold of metro train passing through curved bridge (CB) considering resilient wheels, the mechanical connection characteristics of rim and web are discussed firstly. Based on the train-track-bridge interaction theory, the coupled dynamic model of metro train-CB considering resilient wheels is established. Then, the vehicle-bridge coupled dynamic characteristics under the excitation of long-short wave track irregularity are researched. Finally, from the perspective of dynamics, the safe operating speed threshold of metro trains passing through curved bridge considering resilient wheels (RW) is discussed. Results show that the vertical wheel-rail force of RW is reduced, but the lateral wheel-rail force is amplified compared with the solid wheels (SW). The vertical vibration acceleration of the wheel is reduced, but the lateral vibration acceleration is increased. It is recommended that the speed of metro trains running on curved bridge is not more than 60km/h. The vehicle-bridge coupling dynamic response is aggravated with the speed and load of metro train. The vibration of the inner side of the curved bridge is greater than that of the outer side, and the vibration reduction effect of the RW on the inner side is more significant than that on the outer side. The RW has a vibration absorption effect on the wheel-rail vertical and the vibration of the curved bridge force within 40-140Hz.
摘要：
Reasonable assessment of flexural capacity and reliability is an important prerequisite for ensuring the normal use of corroded prestressed concrete (PC) structures. In this paper, a theory-informed deep neural network (TIDNN)-based model is first developed to predict the flexural capacity of corroded PC beams. Then, a TIDNN-based time-dependent reliability analysis method is proposed considering the aleatory uncertainty of input parameters and the epistemic uncertainty of model. In addition, the effectiveness of the proposed prediction method of flexural capacity is validated by using the collected database, and a simple case analysis of corroded PC beam is used to illustrate the application of the proposed reliability assessment approach. The research results indicate that the prediction performance of the proposed TIDNN method for predicting flexural capacity is significantly better than the deep neural network (DNN), radial basis function (RBF) neural network, and the physics-based prediction model. The proposed uncertainty prediction method of flexural capacity has high accuracy and coverage ability, and the coverage rate for the collected database is 97.37 %. Moreover, the cumulative failure probability is more sensitive to aleatory uncertainty than epistemic uncertainty. Additionally, the cumulative failure probability increases with the rising dropout rate, and the magnitude of this increase gradually intensifies.
Reasonable assessment of flexural capacity and reliability is an important prerequisite for ensuring the normal use of corroded prestressed concrete (PC) structures. In this paper, a theory-informed deep neural network (TIDNN)-based model is first developed to predict the flexural capacity of corroded PC beams. Then, a TIDNN-based time-dependent reliability analysis method is proposed considering the aleatory uncertainty of input parameters and the epistemic uncertainty of model. In addition, the effectiveness of the proposed prediction method of flexural capacity is validated by using the collected database, and a simple case analysis of corroded PC beam is used to illustrate the application of the proposed reliability assessment approach. The research results indicate that the prediction performance of the proposed TIDNN method for predicting flexural capacity is significantly better than the deep neural network (DNN), radial basis function (RBF) neural network, and the physics-based prediction model. The proposed uncertainty prediction method of flexural capacity has high accuracy and coverage ability, and the coverage rate for the collected database is 97.37 %. Moreover, the cumulative failure probability is more sensitive to aleatory uncertainty than epistemic uncertainty. Additionally, the cumulative failure probability increases with the rising dropout rate, and the magnitude of this increase gradually intensifies.
摘要：
The stability control of roadway surrounding rock is a hot issue in coal mining, it is of great significance to study the characteristics of surrounding rock and damage evolution mechanism under the influence of roadway excavation and mining disturbance. The RMT-150 testing machine was used to carry out the triaxial loading-unloading-uniaxial reloading mechanical characteristics test of the white sandstone specimen, the physical properties and mechanical response characteristics of the rock under different unloading points are analyzed systematically. Through monitoring the AE characteristics during rock loading, it was found that there is a close internal connection between AE and rock mechanical response. Based on the Weibull distribution function, the progressive damage evolution equation of rock was constructed, and the damage evolution law of rock under different unloading points was discussed, and the relationship between compressive strength and damage factor D of rock at different unloading points was analyzed. The results show that with an increasing degree of initial damage, the elastic modulus, deformation modulus and compressive strength of rock decrease nonlinearly, while the wave velocity and volume density first increase and then decrease; With an increasing initial damage degree, the failure modes of the rock vary during the uniaxial reloading process, it is manifested that high damage rock is ductile failure and low damage rock is brittle-ductile failure. The correlation between the acoustic emission amplitude and stress-strain curve is strong. The scale parameter m value can have an influence on the rock damage rate, when the morphological parameter epsilon 0 remains unchanged, as the scale parameter m value increases, the curve rotates counterclockwise around one certain point A; The initial damage degree of the rock under different unloading points is different. The higher the unloading point, the greater the initial damage degree, and the smaller the uniaxial compressive strength of the damaged rock. The model can predict the stability of the rock to some extent.
作者机构：
[Li, Liuxi; Zhou, Yi; Zhou, Dequan; Zhou, Y] Changsha Univ Sci & Technol, Coll Civil Engn, Changsha 410114, Peoples R China.;[Li, Liuxi; Zhou, Yi; Deng, Chao; Zhou, Y] Hunan City Univ, Hunan Engn Res Ctr Struct Safety & Disaster Preven, Yiyang 413000, Peoples R China.;[Zhou, Yi; Deng, Chao; Zhou, Y; Tan, Qundong] Hunan City Univ, Coll Civil Engn, Yiyang 413000, Peoples R China.;[Yan, Wenqin] Cent South Univ, Sch Geosci & Infophys, Changsha 410083, Peoples R China.
通讯机构：
[Deng, C] H;[Zhou, Y ] C;Changsha Univ Sci & Technol, Coll Civil Engn, Changsha 410114, Peoples R China.;Hunan City Univ, Hunan Engn Res Ctr Struct Safety & Disaster Preven, Yiyang 413000, Peoples R China.;Hunan City Univ, Coll Civil Engn, Yiyang 413000, Peoples R China.
关键词：
alkaline activation;cementitious replacement;glass waste valorization;grouting properties;sustainable construction materials
摘要：
Effective recycling and utilization of waste glass is a critical issue that urgently needs to be addressed. This study aims to explore the feasibility of using ground waste glass powder (particle size ≤ 75 μm) as a supplementary cementitious material to partially replace cement in the preparation of low-carbon and environmentally friendly grouting materials. The research systematically evaluates the impact of waste glass powder (WGP) on the fresh properties (particularly the stability and rheological characteristics) of cement-based grouting materials under various conditions, including WGP content (0-40%), the addition of NaOH activator (Na(2)O content of 4%) or not, and water-solid ratio (w/s = 0.5, 0.65, 0.8, 1.0). The results indicate that, in the absence of activator, the addition of WGP generally increases the amount of free liquid exudation in the grout, reducing its stability; however, under low w/s ratios, appropriate amounts of WGP can enhance stability. When the w/s ratio is high and the WGP content is large, the grout stability decreases significantly. The addition of NaOH activator (Na(2)O content of 4%) significantly reduces free liquid exudation, enhancing the stability of the grout, especially when the w/s ratio is less than 1.0. Furthermore, the Herschel-Bulkley Model was experimentally validated to accurately describe the rheological behavior of waste glass-cement slurries, with all R(2) values exceeding 0.99. WGP and alkaline activator have significant effects on the rheological properties of the grout. Although they do not change its flow pattern, they significantly affect shear stress and viscosity. The viscosity of the slurry is influenced by the combined effects of w/s ratio, WGP content, and alkaline activator, with complex interactions among the three. The application of these research findings in the field of grouting engineering not only contributes to significantly reducing glass waste but also promotes the production of sustainable cement-based composites, lowering carbon dioxide emissions by reducing cement usage, and thereby alleviating environmental burdens.
期刊：
International Journal of Structural Stability and Dynamics,2024年 ISSN：0219-4554
通讯作者：
Wang, L
作者机构：
[Wu, Yuexing; Wang, Xinzhong] Hunan City Univ, Sch Civil Engn, Yiyang 413000, Peoples R China.;[Chen, Zhaowei; Wu, Yuexing; Zhou, Jianting] Tunnel Engn Chongqing Jiaotong Univ, State Key Lab Mt Bridge, Chongqing 400074, Peoples R China.;[Zhang, Jinquan] Minist Transport, Res Inst Highways, R China, Beijing 100088, Peoples R China.;[Wang, Lang] Southeast Univ, Sch Civil Engn, Nanjing 211189, Peoples R China.
通讯机构：
[Wang, L ] S;Southeast Univ, Sch Civil Engn, Nanjing 211189, Peoples R China.
关键词：
Long-span cable-stayed bridges;bridge system excitation;train-track-bridge dynamic interaction;mapping relationship
摘要：
Urban rail transit is rapidly evolving, with long-span cable-stayed bridges becoming increasingly popular among engineers because of their adaptability. However, as the operation time of bridges with tracks increases, the combined effects of repeated wheel loads and various bridge system excitations, including temperature changes and shrinkage-creep, gradually alter the alignment of the main beam. Similarly, the track structure on the bridge deck also undergoes vertical displacement, leading to corresponding degradation in rail alignment. This study applies singular function theory and verifies its effectiveness in bridge mechanical analysis. For the steel spring floating plate track cable-stayed bridge system, the mapping relationship between the deformation of the bridge's main beam and the track's deformation under bridge system excitation is derived, integrating singular function theory with the theory of train-track-bridge dynamic interaction. By analyzing the force transfer mechanism of the track-bridge system under system excitation, this research examines the effects of different excitations on the coupled dynamic response of the train-track-bridge. These findings suggest that system excitations increase the dynamic response of the train-track-bridge system, which is crucial for improving the durability and reliability of urban rail transit infrastructure.
摘要：
<jats:p>Bamboo contains water-soluble saccharides and carboxylic acid which have an anticoagulation effect on Portland cement, and the anticoagulation ingredients can directly influence the hydration reaction extent. Hydration product varieties and hydration product-bamboo shaving binding interfaces of the Portland cement, and finally the mechanical properties of bamboo cement particle boards. In this paper, bamboo shavings are pretreated by carbonizing treatment, hydro-thermal treatment and alkali treatment; high performance liquid chromatography is adopted to analyze the influences of three different pretreatment methods on contents of water-soluble saccharides and carboxylic acid in the bamboo shavings; a Fourier infrared spectrometer and an X-ray diffractometer are respectively utilized to analyze the characteristic peak changes and crystallization property changes of chemical ingredients of the bamboo shavings before and after the three types of pretreatment. This paper discusses effects of three types of pretreatment methods in eliminating water-soluble saccharides and carboxylic acid in the bamboo shavings. Bamboo Portland cement particle boards was prepared using bamboo shavings, which are pretreated in three ways, and influences and mechanisms of different pretreatment methods on properties of the bamboo Portland cement particle boards were studied. Research indicates that the mechanical properties of the Portland cement particle board prepared from bamboo shavings pretreated with 3 % NaOH solution are superior to requirements of qualified products and superior products specified in the Standard.</jats:p>
作者机构：
[Huang, Yonggang] College of Civil Engineering, Hunan City University, Yiyang, China;China Light Industry Changsha Engineering Co., Ltd., Changsha, China;[Wang, Guiyao] College of Civil Engineering, Changsha University of Science and Technology, Changsha, China;[Fu, Jingliang] China Light Industry Changsha Engineering Co., Ltd., Changsha, China<&wdkj&>College of Civil Engineering, Changsha University of Science and Technology, Changsha, China
通讯机构：
[Yonggang Huang] C;College of Civil Engineering, Hunan City University, Yiyang, China
关键词：
Vetiver root;Root–soil interface;Expansive soil;Pullout test
摘要：
Studying the pullout characteristics of roots can help to gain a deeper understanding of the interaction mechanism between plants and soil, and provide theoretical support and practical guidance for engineering applications. This paper aims to investigate the pulling characteristics of the root–soil interface in expansive soil reinforced by vetiver roots. For this purpose, the study focuses on exploring the correlation between the pullout force (PF) required to extract the roots and the pullout displacement caused by the extraction. The research also examines how the geometry of the roots affects the pulling characteristics of the root–soil using a pullout test. It is found that with increasing root diameter, root length segment (RLS), root volume, and root surface area (RSA), the maximum PF increases. The highest correlation coefficient was found between RSA and maximum PF, which explained 81.4% of the variation in maximum PF. Then, the functional relationship between RLS and PF is established. Using RSA to predict the maximum PF of vetiver root is relatively reasonable. The assessment of PF must consider RSA indicators. The increase in RSA due to a high number of roots results in the improvement of the PF of vetiver root. These findings could assist in enhancing the strength of expansive soils.
作者机构：
[Cai, Jianrong] Hunan City Univ, Sch Civil Engn, Yiyang, Peoples R China.;[Liu, Yang] Lanzhou Jiaotong Univ, Sch Traff & Transportat, Lanzhou, Peoples R China.;[Li, Zhixue] Hunan City Univ, Design & Res Inst Co Ltd, Changsha, Peoples R China.
通讯机构：
[Liu, Y ] L;Lanzhou Jiaotong Univ, Sch Traff & Transportat, Lanzhou, Peoples R China.
摘要：
Rear-end collisions frequently occurred in the entrance zone of expressway tunnel, necessitating enhanced traffic safety through speed guidance. However, existing speed optimization models mainly focus on urban signal-controlled intersections or expressway weaving zones, neglecting research on speed optimization in expressway tunnel entrances. This paper addresses this gap by proposing a framework for a speed guidance model in the entrance zone of expressway tunnels under a mixed traffic environment, comprising both Connected and Autonomous Vehicles (CAVs) and Human-driven Vehicles (HVs). Firstly, a CAV speed optimization model is established based on a shooting heuristic algorithm. The model targets the minimization of the weighted sum of the speed difference between adjacent vehicles and the time taken to reach the tunnel entrance. The model's constraints incorporate safe following distances, speed, and acceleration limits. For HVs, speed trajectories are determined using the Intelligent Driver Model (IDM). The CAV speed optimization model, represented as a mixed-integer nonlinear optimization problem, is solved using A Mathematical Programming Language (AMPL) and the BONMIN solver. Safety performance is evaluated using Time-to-Collision (TTC) and speed standard deviation (SD) metrics. Case study results show a significant decrease in SD as the CAV penetration rate increases, with a 58.38% reduction from 0% to 100%. The impact on SD and mean TTC is most pronounced when the CAV penetration rate is between 0% and 40%, compared to rates above 40%. The minimum TTC values at different CAV penetration rates consistently exceed the safety threshold TTC*, confirming the effectiveness of the proposed control method in enhanced safety. Sensitivity analysis further supports these findings.
