期刊：
International Journal of Thermal Sciences,2026年220:110367 ISSN：1290-0729
通讯作者：
Chuangang Fan
作者机构：
[Rongwei Bu] School of Transportation, Changsha University of Science and Technology, Changsha 410114, China;[Chuangang Fan; Zengguang Liang; Guanjie Rao] School of Civil Engineering, Central South University, Changsha 410075, China;[Zhenyu Gao] Center for Combinatorics, Nankai University, Tianjin 300071, China;[Wenlong Wang] National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing, 100085, China;[Tong Xu] School of Emergency Management and Safety Engineering, China University of Mining and Technology, Beijing 100083, China
通讯机构：
[Chuangang Fan] S;School of Civil Engineering, Central South University, Changsha 410075, China
摘要：
Polymethyl methacrylate (PMMA) is extensively utilized in the design of various architectural structures, including concave configurations. However, its inherent flammability poses a significant potential fire hazard. Investigation of upward flame spread over concave surfaces has been restricted to flame spread parameters, while the associated burning behaviors have not yet been addressed. In this study, 36 groups of fire experiments were performed on 3 mm thick PMMA with varying curvature (denoted by K , 0.52–2.00 m -1 ) and width ( W , 2.5–15.0 cm). The results reveal that the mass loss rate undergoes an eruptive growth when K ≥ 1.41 m -1 . By introducing a dimensionless parameter Γ , this burning behavior is quantitatively described using a piecewise power-law correlation between Γ and the Grashof number Gr x . The critical occurrence of eruptive burning behavior is identified at Gr x ≈ 3 × 10 7 . For Gr x < 3 × 10 7 , flame convection mode in the pyrolysis zone is governed by natural convection, whereas forced convection becomes gradually dominant when Gr x ≥ 3 × 10 7 . Subsequently, based on this critical threshold, the flame spread model before the occurrence of eruptive phenomenon is developed. This model reflects a power-law relationship between flame spread rate and pyrolysis length, with an average power exponent of 1.24.
Polymethyl methacrylate (PMMA) is extensively utilized in the design of various architectural structures, including concave configurations. However, its inherent flammability poses a significant potential fire hazard. Investigation of upward flame spread over concave surfaces has been restricted to flame spread parameters, while the associated burning behaviors have not yet been addressed. In this study, 36 groups of fire experiments were performed on 3 mm thick PMMA with varying curvature (denoted by K , 0.52–2.00 m -1 ) and width ( W , 2.5–15.0 cm). The results reveal that the mass loss rate undergoes an eruptive growth when K ≥ 1.41 m -1 . By introducing a dimensionless parameter Γ , this burning behavior is quantitatively described using a piecewise power-law correlation between Γ and the Grashof number Gr x . The critical occurrence of eruptive burning behavior is identified at Gr x ≈ 3 × 10 7 . For Gr x < 3 × 10 7 , flame convection mode in the pyrolysis zone is governed by natural convection, whereas forced convection becomes gradually dominant when Gr x ≥ 3 × 10 7 . Subsequently, based on this critical threshold, the flame spread model before the occurrence of eruptive phenomenon is developed. This model reflects a power-law relationship between flame spread rate and pyrolysis length, with an average power exponent of 1.24.
作者：
Runzhou Luo;Xudong Zha*;Hengwu Hu;Bingbing Lei
期刊：
Renewable & Sustainable Energy Reviews,2026年226:116332 ISSN：1364-0321
通讯作者：
Xudong Zha
作者机构：
[Runzhou Luo; Xudong Zha; Hengwu Hu; Bingbing Lei] School of Transportation, Changsha University of Science and Technology, Changsha, China
通讯机构：
[Xudong Zha] S;School of Transportation, Changsha University of Science and Technology, Changsha, China
摘要：
The growing prominence of energy shortages and environmental challenges has intensified global attention toward renewable energy utilization, with an urgent demand for energy transition in the transportation sector. Roads, as one of the important transportation infrastructures, contain a large amount of utilizable mechanical energy, and their energy harvesting technology is currently one of the hotspots in research.This study presents a comprehensive review of road mechanical energy harvesting technologies. First, three categories of road mechanical energy harvesting systems suitable for different application scenarios are summarized and analyzed, including speed bumps, flat-plate, embedded or integrated. Subsequently, from the four technical approaches of hydraulic/pneumatic, electromagnetic, piezoelectric, and TENGs, the principles, methodological frameworks, and research outcomes of various energy harvesting technologies are comprehensively reviewed. The key performance metric of energy output for these four technologies is compared and summarized, along with evaluations of their advantages and disadvantages. Furthermore, the integration and development of road mechanical energy harvesting technologies with smart road systems are introduced. Finally, the key challenges currently hindering the real-world implementations of road mechanical energy harvesting technologies are discussed, including energy harvesting efficiency, material performance, cost and return, regulatory issues, among others. Predictions and recommendations for future development are proposed, aiming to provide assistance for further research and large-scale applications.
The growing prominence of energy shortages and environmental challenges has intensified global attention toward renewable energy utilization, with an urgent demand for energy transition in the transportation sector. Roads, as one of the important transportation infrastructures, contain a large amount of utilizable mechanical energy, and their energy harvesting technology is currently one of the hotspots in research.This study presents a comprehensive review of road mechanical energy harvesting technologies. First, three categories of road mechanical energy harvesting systems suitable for different application scenarios are summarized and analyzed, including speed bumps, flat-plate, embedded or integrated. Subsequently, from the four technical approaches of hydraulic/pneumatic, electromagnetic, piezoelectric, and TENGs, the principles, methodological frameworks, and research outcomes of various energy harvesting technologies are comprehensively reviewed. The key performance metric of energy output for these four technologies is compared and summarized, along with evaluations of their advantages and disadvantages. Furthermore, the integration and development of road mechanical energy harvesting technologies with smart road systems are introduced. Finally, the key challenges currently hindering the real-world implementations of road mechanical energy harvesting technologies are discussed, including energy harvesting efficiency, material performance, cost and return, regulatory issues, among others. Predictions and recommendations for future development are proposed, aiming to provide assistance for further research and large-scale applications.
摘要：
To study the evolution of the rheological properties of warm mix asphalt (WMA) and its mastic viscoelastic drive prediction model, different dosages of Sasobit (S) and Evotherm 3G (G) WMA were prepared. The temperature sensitivity, high temperature deformation resistance, and low temperature viscoelastic properties of the two WMA were analyzed using a bonding material high and low temperature performance test. By combining the Refatus and Burgers models, the optimal dosage of the two warm mixes (S and G) was determined to be 4.0 % and 0.6 %, respectively. The prediction accuracy of three micromechanical models, including Hashin and Buttlar, for the high temperature performance of mastic was compared through the particle reinforcement theory system. The results showed that the warm mix additives significantly improved the high temperature stability performance of the asphalt, reduced the temperature sensitivity of the asphalt, and the Refatus model parameter a was decreased by 9.15 % and 1.0 % for B-S-4 and B-G-0.6 (denoting 4 % S and 0.6 % G added to the SBS modified asphalt, respectively). The creep deformation of WMA was smaller than that of the asphalt in the original samples, and the warm mix additives effectively improved the low temperature cracking resistance of asphalt. The Buttlar model optimally predicted the high temperature performance in the mastic (71 °C/29 °C correlation coefficient R 2 = 0.991/0.917), and the adsorption of mineral powders with SBS modified asphalt was superior to that of the base asphalt. At the same time, the warming agent had a detrimental effect on the asphalt adsorption. The results provide a theoretical basis for predicting WMA mastic’s multiscale performance and for designing sustainable pavement materials.
To study the evolution of the rheological properties of warm mix asphalt (WMA) and its mastic viscoelastic drive prediction model, different dosages of Sasobit (S) and Evotherm 3G (G) WMA were prepared. The temperature sensitivity, high temperature deformation resistance, and low temperature viscoelastic properties of the two WMA were analyzed using a bonding material high and low temperature performance test. By combining the Refatus and Burgers models, the optimal dosage of the two warm mixes (S and G) was determined to be 4.0 % and 0.6 %, respectively. The prediction accuracy of three micromechanical models, including Hashin and Buttlar, for the high temperature performance of mastic was compared through the particle reinforcement theory system. The results showed that the warm mix additives significantly improved the high temperature stability performance of the asphalt, reduced the temperature sensitivity of the asphalt, and the Refatus model parameter a was decreased by 9.15 % and 1.0 % for B-S-4 and B-G-0.6 (denoting 4 % S and 0.6 % G added to the SBS modified asphalt, respectively). The creep deformation of WMA was smaller than that of the asphalt in the original samples, and the warm mix additives effectively improved the low temperature cracking resistance of asphalt. The Buttlar model optimally predicted the high temperature performance in the mastic (71 °C/29 °C correlation coefficient R 2 = 0.991/0.917), and the adsorption of mineral powders with SBS modified asphalt was superior to that of the base asphalt. At the same time, the warming agent had a detrimental effect on the asphalt adsorption. The results provide a theoretical basis for predicting WMA mastic’s multiscale performance and for designing sustainable pavement materials.
作者机构：
School of Civil Engineering, Changsha University, Changsha, 410022, PR China;Hunan Provincial Key Laboratory for Big Data Smart Application of Natural Disaster Risks Survey of Highway Engineering, Changsha University, Changsha, 410022, PR China;[Wu Gaoqiao] School of Traffic and Transportation Engineering, Changsha University of Science and Technology, Changsha, 410022, PR China;School of Civil Engineering and Architecture, Guangxi University, Nanning, 530004, PR China;State Key Laboratory of Featured Metal Materials and Life-cycle Safety for Composite Structures, Guangxi University, Nanning, 530004, PR China
通讯机构：
[Yao Xiao] S;School of Civil Engineering and Architecture, Guangxi University, Nanning, 530004, PR China<&wdkj&>State Key Laboratory of Featured Metal Materials and Life-cycle Safety for Composite Structures, Guangxi University, Nanning, 530004, PR China
摘要：
This research presents a novel approach to addressing plane strain stability problems in rock masses, obeying the generalized Hoek-Brown failure criterion. The methodology integrates upper bound (UB) finite element limit analysis (FELA) with power cone programming (PCP) techniques. To achieve significantly enhanced UB results, quadratic velocity elements are employed for the discretization of the kinematic theorem. Within the UB formulation, the generalized Hoek-Brown (GHB) yield criterion is represented through a series of linear constraints and two conic constraints—specifically, a quadratic cone and a power cone. This allows the GHB yield criterion to be articulated in its original form without the need for smoothing the yield surface. Three classic examples have been analyzed to verify the feasibility of the proposed method. Comprehensive comparisons between the newly obtained results and existing results from several related references demonstrate that the new method is highly efficient in terms of computation time and capable of generating highly accurate upper bounds when combined with an appropriate mesh adaptivity procedure.
This research presents a novel approach to addressing plane strain stability problems in rock masses, obeying the generalized Hoek-Brown failure criterion. The methodology integrates upper bound (UB) finite element limit analysis (FELA) with power cone programming (PCP) techniques. To achieve significantly enhanced UB results, quadratic velocity elements are employed for the discretization of the kinematic theorem. Within the UB formulation, the generalized Hoek-Brown (GHB) yield criterion is represented through a series of linear constraints and two conic constraints—specifically, a quadratic cone and a power cone. This allows the GHB yield criterion to be articulated in its original form without the need for smoothing the yield surface. Three classic examples have been analyzed to verify the feasibility of the proposed method. Comprehensive comparisons between the newly obtained results and existing results from several related references demonstrate that the new method is highly efficient in terms of computation time and capable of generating highly accurate upper bounds when combined with an appropriate mesh adaptivity procedure.
作者机构：
[Tao Chen; Huiyun Wu; Yujie Huang; Juan Xie] School of Transportation, Changsha University of Science and Technology, Changsha 410114, China;National Engineering Laboratory of Highway Maintenance Technology, Changsha University of Science and Technology, Changsha 410114, China;[Junwei Xiang] Zhongda Intelligent Technology Co., Ltd., Changsha 410006, China;[Shuihui Wu] Zhenjiang Yuehui New Materials Co., Ltd., Zhenjiang 212000, China;[Pu Zhao] Oceanpower Industrial Co., Ltd., Shenzhen 518040, China
通讯机构：
[Hui Wang] S;School of Transportation, Changsha University of Science and Technology, Changsha 410114, China<&wdkj&>National Engineering Laboratory of Highway Maintenance Technology, Changsha University of Science and Technology, Changsha 410114, China
摘要：
Although rubber asphalt and its mixtures demonstrate excellent road performance, they release unpleasant and harmful fumes during production, mixing, and construction. This paper examines the various applications of asphalt deodorizers, assesses the deodorization efficacy of deodorant-rubber asphalt evaluated by two quantitative indexes, and proposed the application scope of various deodorizers in engineering. The key innovations were as follows: Response surface methodology (RSM) was used to research the primary pollutants in the fumes, the hydrogen sulfide and particulate matter. Meanwhile, the optimal combination for deodorant-rubber asphalts was determined. In addition, various microscopic analysis methods, including PY-GC-MS, FTIR, FM, and element analyzer, were used to analyze three kinds of deodorant-rubber asphalt and reveal their deodorization mechanisms. The results showed that the granular deodorizer inhibits hydrogen and carbon release, lowers sulfur-containing emissions by binding with sulfides, and prevents hydrocarbon reactions at high temperatures. The powder deodorizer restricts the release of hydrogen and sulfur through physical adsorption. The oil-based deodorizer reduces hydrogen volatilization by up to 83.56 % and masks some odors when nitrogenous organic substances act catalytically. Under optimal conditions, the granular deodorizer is most effective in suppressing H 2 S(57.3 %). Regarding the suppression of particulate matter, the oil-based deodorizer has the most significant impact (28.7 %).
Although rubber asphalt and its mixtures demonstrate excellent road performance, they release unpleasant and harmful fumes during production, mixing, and construction. This paper examines the various applications of asphalt deodorizers, assesses the deodorization efficacy of deodorant-rubber asphalt evaluated by two quantitative indexes, and proposed the application scope of various deodorizers in engineering. The key innovations were as follows: Response surface methodology (RSM) was used to research the primary pollutants in the fumes, the hydrogen sulfide and particulate matter. Meanwhile, the optimal combination for deodorant-rubber asphalts was determined. In addition, various microscopic analysis methods, including PY-GC-MS, FTIR, FM, and element analyzer, were used to analyze three kinds of deodorant-rubber asphalt and reveal their deodorization mechanisms. The results showed that the granular deodorizer inhibits hydrogen and carbon release, lowers sulfur-containing emissions by binding with sulfides, and prevents hydrocarbon reactions at high temperatures. The powder deodorizer restricts the release of hydrogen and sulfur through physical adsorption. The oil-based deodorizer reduces hydrogen volatilization by up to 83.56 % and masks some odors when nitrogenous organic substances act catalytically. Under optimal conditions, the granular deodorizer is most effective in suppressing H 2 S(57.3 %). Regarding the suppression of particulate matter, the oil-based deodorizer has the most significant impact (28.7 %).
期刊：
Geotextiles and Geomembranes,2026年54(1):99-114 ISSN：0266-1144
通讯作者：
Ling Zhang
作者机构：
College of Civil Engineering, Hunan University, Changsha, 410082, China;Key Laboratory of Building Safety and Energy Efficiency of the Ministry of Education, Hunan University, Changsha, 410082, China;National Center for International Research Collaboration in Building Safety and Environment, Hunan University, Changsha, 410082, China;[Shao Yue] School of Transportation, Changsha University of Science and Technology, Changsha, 410114, Hunan, China;[Xiaocong Cai; Ling Zhang; Zijian Yang; Jinpeng Tan] College of Civil Engineering, Hunan University, Changsha, 410082, China<&wdkj&>Key Laboratory of Building Safety and Energy Efficiency of the Ministry of Education, Hunan University, Changsha, 410082, China<&wdkj&>National Center for International Research Collaboration in Building Safety and Environment, Hunan University, Changsha, 410082, China
通讯机构：
[Ling Zhang] C;College of Civil Engineering, Hunan University, Changsha, 410082, China<&wdkj&>Key Laboratory of Building Safety and Energy Efficiency of the Ministry of Education, Hunan University, Changsha, 410082, China<&wdkj&>National Center for International Research Collaboration in Building Safety and Environment, Hunan University, Changsha, 410082, China
摘要：
Geogrid-encased stone columns (GESCs) have shown notable potential in improving performance, thereby reducing the seismic failure probability ( P F ) of soil. This research proposes a limit equilibrium-based formulation for predicting the ultimate seismic bearing capacity ( q u ) of GESC composite foundations. Subsequently, a fragility analysis framework is developed based on the bearing capacity formula to quantify P F . The fragility analysis incorporates machine learning to evaluate the influence of tensile strength ( T ), column diameter ( D c ), column and soil strength parameters ( φ c , c c , φ s , and c s ), shear strength utilization ratio ( n ), area replacement ratio ( m ), vertical load demand ( P v ), footing width ( B ), footing embedded depth ( h 0 ), and seismic coefficients ( k h and k v ). Results demonstrate that encasement substantially enhances q u and reduces earthquake-induced settlements. The fragility function demonstrates a critical behavioral transition at n ≈ 0.5. P F decreases with increasing T , m , φ c , c c , φ s , c s , B , and h 0 , but increases with k v , D c , and P v . The significant impact and indeterminacy of soil properties suggest P F shall be reduced by selecting the controllable parameters (e.g., T and D c ). Larger B improves load diffusion, and increased h 0 maximizes vertical effective stress. Large D c delays confinement mobilization, potentially reducing the reinforcement effectiveness and increasing the failure risk.
Geogrid-encased stone columns (GESCs) have shown notable potential in improving performance, thereby reducing the seismic failure probability ( P F ) of soil. This research proposes a limit equilibrium-based formulation for predicting the ultimate seismic bearing capacity ( q u ) of GESC composite foundations. Subsequently, a fragility analysis framework is developed based on the bearing capacity formula to quantify P F . The fragility analysis incorporates machine learning to evaluate the influence of tensile strength ( T ), column diameter ( D c ), column and soil strength parameters ( φ c , c c , φ s , and c s ), shear strength utilization ratio ( n ), area replacement ratio ( m ), vertical load demand ( P v ), footing width ( B ), footing embedded depth ( h 0 ), and seismic coefficients ( k h and k v ). Results demonstrate that encasement substantially enhances q u and reduces earthquake-induced settlements. The fragility function demonstrates a critical behavioral transition at n ≈ 0.5. P F decreases with increasing T , m , φ c , c c , φ s , c s , B , and h 0 , but increases with k v , D c , and P v . The significant impact and indeterminacy of soil properties suggest P F shall be reduced by selecting the controllable parameters (e.g., T and D c ). Larger B improves load diffusion, and increased h 0 maximizes vertical effective stress. Large D c delays confinement mobilization, potentially reducing the reinforcement effectiveness and increasing the failure risk.
摘要：
La-BiO 2-x composite photocatalyst was successfully synthesized through a single-step hydrothermal strategy. The introduction of La 3+ into the BiO 2-x lattice replaces the Bi 3+ in the BiO 2-x lattice, resulting in a new defect level and oxygen vacancies (V o ) generation. The ·O 2 − generated in the surface of V o , which was converted into singlet oxygen ( 1 O 2 ) with the transformation of Bi 5+ to Bi 3+ . Upon visible (near-infrared) light irradiation, the removal rates of tetracycline (TC), oxytetracycline (OTC), and levofloxacin (LEV) by trace 5 % La-BiO 2-x (0.1 g/L) reached 84.18 % (55.56 %), 78.85 % and 70.12 %, respectively. The Toxicity Estimation Software Tool (T.E.S.T) based on Quantitative Structure-Activity Relationship (QSAR) models illustrated that the biological toxicity of TC intermediates can be eliminated by 5 % La-BiO 2-x . The green bean germination rates in 5 % La-BiO 2-x treated TC solution was close to that in the tap water (100.0 %). The inorganic anion and humic acid (HA) exhibited almost no influence on the degradation of TC in lake water and river water. This study enhances the comprehension of biological toxicity elimination in antibiotics degradation process, providing the possibilities for actual applications of La-BiO 2-x .
La-BiO 2-x composite photocatalyst was successfully synthesized through a single-step hydrothermal strategy. The introduction of La 3+ into the BiO 2-x lattice replaces the Bi 3+ in the BiO 2-x lattice, resulting in a new defect level and oxygen vacancies (V o ) generation. The ·O 2 − generated in the surface of V o , which was converted into singlet oxygen ( 1 O 2 ) with the transformation of Bi 5+ to Bi 3+ . Upon visible (near-infrared) light irradiation, the removal rates of tetracycline (TC), oxytetracycline (OTC), and levofloxacin (LEV) by trace 5 % La-BiO 2-x (0.1 g/L) reached 84.18 % (55.56 %), 78.85 % and 70.12 %, respectively. The Toxicity Estimation Software Tool (T.E.S.T) based on Quantitative Structure-Activity Relationship (QSAR) models illustrated that the biological toxicity of TC intermediates can be eliminated by 5 % La-BiO 2-x . The green bean germination rates in 5 % La-BiO 2-x treated TC solution was close to that in the tap water (100.0 %). The inorganic anion and humic acid (HA) exhibited almost no influence on the degradation of TC in lake water and river water. This study enhances the comprehension of biological toxicity elimination in antibiotics degradation process, providing the possibilities for actual applications of La-BiO 2-x .
通讯机构：
[Zhou, CJ ] G;Guangzhou Univ, Sch Civil Engn & Transportat, Guangzhou 510006, Peoples R China.
关键词：
urban rail transit ridership;land use;temporal heterogeneity;panel data analysis;transit-oriented development
摘要：
Understanding how land use affects urban rail transit (URT) ridership is essential for facilitating URT usage. While previous studies have explored the way that land use impacts URT ridership, few have figured out how this impact evolves over time. Utilizing URT turnstile and land use data in Beijing, we employed panel data analysis methods to verify the existence of the temporal heterogeneity of the impact and capture this temporal heterogeneity. The results identified time-varying impacts of land use on the URT boarding and alighting trips on weekdays and non-weekdays and also demonstrated the rationality of the mixed effects time-varying coefficient panel data (TVC-P) model in capturing this temporal heterogeneity accurately. The TVC-P model revealed how land use density appealed to URT commuting during weekday morning peak times, and how it triggered the generation of URT commutes during the weekday evening rush hours. The land use diversity promoted URT trips over an extended period on non-weekdays. Additionally, the study identified the time-varying impacts of specific land use on URT ridership. These insights provide both theoretical and empirical support for developing policies and actions that improve the efficiency of transportation systems and foster alignment between land use and transport.
摘要：
Hot mix asphalt mixture is considered the ideal approach to reuse waste plastics in high-value applications because of its very high amount of usage in highway construction. However, the differences in polarity and density between polymers and asphalt lead to polymer coalescence and therefore the poor storage stability of modified asphalt. These challenges are exalted when recycling commingled plastics. This study introduced an innovative compatibilization strategy and mechanism for co-stabilizing commingled plastics and pyrolyzed rubber in asphalt. Commingled plastics were first grafted with maleic anhydride for surface activation, followed by reactive kneading with pyrolyzed rubber and crosslinking agent to form an integrated thermoplastic elastomer (ITPE) for asphalt modification. The mechanical, thermal, and interfacial behaviors of the ITPE were evaluated through tensile testing, thermogravimetric analysis, and scanning electron microscopy. The storage stability and rheological properties of the modified binder blends were evaluated through the cigar tube test and dynamic shear rheometer testing. Results demonstrated a successful formation of imide bonds in the ITPE, which can improve the strength, ductility, and thermal stability of rubber-plastic composites. Appropriate utilization of crosslinking agents can improve both rutting and fatigue resistance of ITPE-modified asphalt with good storage stability because of the co-existence of rigid plastic and soft rubbery regimes and the formation of a crosslink network. However, excessive content of crosslinker led to severe phase separation and reduced storage stability of modified binder blends. Extra crosslinker tended to float in asphalt because of its low density and caused an excessive formation of the crosslink network in the top section of the asphalt.
关键词：
temperature field;long longitudinal slope;finite element;mechanical response
摘要：
With the rapid increase in traffic volume and the number of heavy-duty vehicles, the load on asphalt pavements has increased significantly. Especially on sections with long longitudinal slopes, the internal stress conditions of asphalt pavement have become even more complex. This study aims to investigate the thermal-mechanical coupling behavior of asphalt pavement structures on long longitudinal slopes under the combined influence of temperature fields and moving loads. A pavement temperature field model was developed based on the climatic conditions of Nanning (AAT: 21.8 °C; Tmax: 37 °C; Tmin: 3 °C; AAP: 1453.4 mm). In addition, a three-dimensional finite element model of asphalt pavement structures on long longitudinal slopes was established using finite element software. Variations in pavement mechanical responses were compared under different vehicle axle loads (100-200 kN), slope gradients (0-5%), braking coefficients (0-0.7), and asphalt mixture layer thicknesses (2-8 cm). The results indicate that the pavement structure exhibits a strong capacity for pressure attenuation, with the middle and lower surface layers showing more pronounced stress reduction-up to 40%-significantly greater than the 6.5% observed in the upper surface layer. As the axle load increases from 100 kN to 200 kN, the internal mechanical responses of the pavement show a linear relationship with load magnitude, with an average increase of approximately 29%. In addition, the internal shearing stress of the pavement is more sensitive to changes in slope and braking coefficient; when the slope increases from 0% to 5% and the braking coefficient increases from 0 to 0.7, the shear stress at the bottom of the upper surface layer increases by 12% and 268%, respectively. This study provides guidance for the design of asphalt pavements on long longitudinal slopes. In future designs, special attention should be given to enhancing the shear strength of the surface layer and improving the interlayer bonding performance. In particular, under conditions of steep slopes and frequent heavy vehicle traffic, the thickness and modulus of the upper surface asphalt mixture may be appropriately increased.
摘要：
Background : A ramp is an auxiliary roadway that facilitates the vehicles joining and leaving the main traffic stream of highway. Ramp areas are prone to road crashes because of the merging, diverging, and weaving traffic entering and leaving the highways. Objectives : This study evaluates the differences in injury severity and influencing factors between single- and multi-vehicle crashes at ramp areas, with which the transferability assessment of models across time periods is considered. Method: Separate injury severity models for single- and multi-vehicle crashes are established based on comprehensive crash data from North Carolina State in 2016–2018. Random parameter multinomial logit regression model with heterogeneity in means and variances is adopted to measure the association between crash injury severity and possible influencing factors, with which the effect of unobserved heterogeneity is accounted. In addition, partially constrained and temporal unconstrained modeling approaches are adopted to consider temporally shifting parameters. Results: Results indicate that there are considerable differences in the effects on injury severity between single- and multi-vehicle crashes, after controlling for unobserved heterogeneity and temporal instability. Some variables including aberrant driving, vehicle type, area type, speed limit and crash location are found to be significant only in one type of crash but not in the other. There are opposite effects for the crashes in rural areas on the likelihood of injury between single-vehicle and multi-vehicle crashes. Additionally, temporal transferability and out-of-sample prediction performance for models of single- and multi-vehicle crashes are assessed. Results indicate that remarkable temporal stability and instability coexist. Practical Applications : Findings should shed light on the effective traffic management and control strategies that can mitigate crash and injury risk at highway ramp areas.
Background : A ramp is an auxiliary roadway that facilitates the vehicles joining and leaving the main traffic stream of highway. Ramp areas are prone to road crashes because of the merging, diverging, and weaving traffic entering and leaving the highways. Objectives : This study evaluates the differences in injury severity and influencing factors between single- and multi-vehicle crashes at ramp areas, with which the transferability assessment of models across time periods is considered. Method: Separate injury severity models for single- and multi-vehicle crashes are established based on comprehensive crash data from North Carolina State in 2016–2018. Random parameter multinomial logit regression model with heterogeneity in means and variances is adopted to measure the association between crash injury severity and possible influencing factors, with which the effect of unobserved heterogeneity is accounted. In addition, partially constrained and temporal unconstrained modeling approaches are adopted to consider temporally shifting parameters. Results: Results indicate that there are considerable differences in the effects on injury severity between single- and multi-vehicle crashes, after controlling for unobserved heterogeneity and temporal instability. Some variables including aberrant driving, vehicle type, area type, speed limit and crash location are found to be significant only in one type of crash but not in the other. There are opposite effects for the crashes in rural areas on the likelihood of injury between single-vehicle and multi-vehicle crashes. Additionally, temporal transferability and out-of-sample prediction performance for models of single- and multi-vehicle crashes are assessed. Results indicate that remarkable temporal stability and instability coexist. Practical Applications : Findings should shed light on the effective traffic management and control strategies that can mitigate crash and injury risk at highway ramp areas.
摘要：
This research analyzed the characteristics of aggregate contact chain networks based on complex network theory. The contact chain network was extracted using Digital Image Processing (DIP) technology and Three-Dimensional (3D) reconstruction technology. The change rule of the contact chain network of asphalt mixture was analyzed using the complex network theory. From the results of the analysis, the filling particles existed during the compaction. The 4.75–9.5 mm and 9.5–13.2 mm aggregates may rotate to increase the stability of the skeleton structure. The clustering coefficient of the aggregate increased as the asphalt mixture was compacted, and the aggregate with a small size had a larger clustering coefficient. The distribution of shortest path length in each compaction stage obeyed the Gaussian distribution. The average shortest path length decreased with the increase of the compactness of the specimen, indicating that there was a good correlation between shortest path length and compactness.
This research analyzed the characteristics of aggregate contact chain networks based on complex network theory. The contact chain network was extracted using Digital Image Processing (DIP) technology and Three-Dimensional (3D) reconstruction technology. The change rule of the contact chain network of asphalt mixture was analyzed using the complex network theory. From the results of the analysis, the filling particles existed during the compaction. The 4.75–9.5 mm and 9.5–13.2 mm aggregates may rotate to increase the stability of the skeleton structure. The clustering coefficient of the aggregate increased as the asphalt mixture was compacted, and the aggregate with a small size had a larger clustering coefficient. The distribution of shortest path length in each compaction stage obeyed the Gaussian distribution. The average shortest path length decreased with the increase of the compactness of the specimen, indicating that there was a good correlation between shortest path length and compactness.
摘要：
Defects in tunnel linings accelerate structural deterioration, reduce service life, and pose serious safety risks. Existing algorithms for detecting defect signals in ground-penetrating radar (GPR) images often struggle to balance accuracy and efficiency, with limited capacity to extract meaningful features. To address these limitations, this paper proposes a lightweight algorithm, MGD-DETR, for accurate recognition of internal tunnel lining defects, using RT-DETR as the base model. First, a Multi-HGNet backbone feature extraction network is introduced to reduce model size (MS) and enhance dynamic fusion and interaction between feature layers, thereby improving feature extraction. Second, the lightweight convolution module GSConv replaces standard convolution operations to reduce the parameter count. Third, a dual attention module (DAM) is integrated to dynamically adjust spatial and channel feature weights, improving the model’s generalization performance. Five models—RT-DETR, YOLO-LD, YOLOv10, YOLOv11, and SSD—were used for comparative evaluation. Experimental results show that MGD-DETR outperforms the other models across all metrics, achieving a mean average precision (mAP) of 0.834, mean F1 score (mF1) of 0.818, MS of 26.9 M, and frames per second (FPS) of 91.2f/s, enabling fast and accurate recognition of defect signals and facilitate subsequent deployment into tunnel detection mobile devices.
Defects in tunnel linings accelerate structural deterioration, reduce service life, and pose serious safety risks. Existing algorithms for detecting defect signals in ground-penetrating radar (GPR) images often struggle to balance accuracy and efficiency, with limited capacity to extract meaningful features. To address these limitations, this paper proposes a lightweight algorithm, MGD-DETR, for accurate recognition of internal tunnel lining defects, using RT-DETR as the base model. First, a Multi-HGNet backbone feature extraction network is introduced to reduce model size (MS) and enhance dynamic fusion and interaction between feature layers, thereby improving feature extraction. Second, the lightweight convolution module GSConv replaces standard convolution operations to reduce the parameter count. Third, a dual attention module (DAM) is integrated to dynamically adjust spatial and channel feature weights, improving the model’s generalization performance. Five models—RT-DETR, YOLO-LD, YOLOv10, YOLOv11, and SSD—were used for comparative evaluation. Experimental results show that MGD-DETR outperforms the other models across all metrics, achieving a mean average precision (mAP) of 0.834, mean F1 score (mF1) of 0.818, MS of 26.9 M, and frames per second (FPS) of 91.2f/s, enabling fast and accurate recognition of defect signals and facilitate subsequent deployment into tunnel detection mobile devices.
关键词：
Asphalt mixture;Triaxial tensile-compressive state;Calculation model of dynamic modulus;Load response analysis
摘要：
The three-dimensional stiffness characteristic tests of AC-13 asphalt mixture were conducted under varying temperatures, frequencies, and confining pressures using self-developed triaxial testing equipment. The triaxial tensile-compressive modulus of the asphalt mixture was found to be approximately 1.5 times greater than the uniaxial tensile-compressive modulus, and the dynamic modulus ratio of the triaxial tensile-compressive modulus is between 0.65 and 0.85. The nonlinear variation laws in the triaxial tensile-compressive dynamic modulus with decreasing temperature and increasing frequency and confining pressure were revealed. According to the principle of time temperature equivalence, the three-axis and uniaxial tensile-compressive displacement factors were calculated, and the dynamic modulus main curve in the form of a Sigmoidal function was established. Subsequently, according to the correlation of the triaxial tensile-compressive dynamic modulus, a dynamic modulus calculation model with high precision and clear physical meaning and considering the effects of temperature frequency and stress state was developed. Moreover, the model was validated using a large amount of domestic and international dynamic modulus data, and the results showed that the model has high accuracy and good applicability. Finally, the three-dimensional dynamic modulus was applied to a load response analysis of typical semirigid base asphalt pavement. The results indicated that the trend in the change in the deflection obtained using the three-dimensional dynamic modulus and the traditional compression modulus calculation is consistent, gradually decreasing from the center of the wheel load to both sides. The maximum deflection values at the center of the wheel load calculated using the two methods are 9.89 and 8.64 (0.01 mm), respectively. The deviation between the deflection at the load center calculated using the three-dimensional dynamic modulus and the measured value of the full-scale test road Beckman beam is only 3.45%, which represents a significant improvement in accuracy compared to that of linear elastic theory using the compressive modulus. A deviation of 3% to 40% in the response of the transverse tensile strain, longitudinal tensile strain, and maximum shear stress between the two methods should be taken seriously.
作者机构：
[Jiang, Chengfeng; Chen, Haiyan; Li, Chuanchang] Key Laboratory of Renewable Energy Electric-Technology of Hunan Province, School of Energy and Power Engineering, Changsha University of Science and Technology, Changsha, 410114, China;[Sun, Jinwang] School of Transportation, Changsha University of Science and Technology, Changsha, 410114, China;[Liu, Lei; Zhang, Dou] State Key Laboratory of Powder Metallurgy, Central South University, Changsha, 410083, China
通讯机构：
[Haiyan Chen] K;[Dou Zhang] S;State Key Laboratory of Powder Metallurgy, Central South University, Changsha, 410083, China<&wdkj&>Key Laboratory of Renewable Energy Electric-Technology of Hunan Province, School of Energy and Power Engineering, Changsha University of Science and Technology, Changsha, 410114, China
摘要：
Dielectric capacitors are critical for energy storage applications, especially in pulsed power systems, owing to their ultrahigh power density and ultrafast charge/discharge capabilities. Among them, HfO₂-based thin films are particularly promising for micro-energy storage devices. In this work, double-layered Hf₀.₅Zr₀.₅O₂(3 nm)/ZrO₂(12 nm) (HZO3ZO12) films are deposited across a wide temperature range (80–225°C) to systematically investigate their energy storage performance. A machine learning-assisted multi-objective optimization approach is employed to identify the optimal deposition temperature, revealing 128°C as the ideal condition for maximizing energy storage properties. Further thickness optimization based on this deposition temperature is used to enhance the performance, achieving an excellent energy storage density of 113 J/cm³ at an applied electric field of 9.1 MV/cm. This study demonstrates a powerful strategy combining machine learning with experimental design to optimize dielectric capacitors, providing a roadmap for developing high-performance energy storage materials.
Dielectric capacitors are critical for energy storage applications, especially in pulsed power systems, owing to their ultrahigh power density and ultrafast charge/discharge capabilities. Among them, HfO₂-based thin films are particularly promising for micro-energy storage devices. In this work, double-layered Hf₀.₅Zr₀.₅O₂(3 nm)/ZrO₂(12 nm) (HZO3ZO12) films are deposited across a wide temperature range (80–225°C) to systematically investigate their energy storage performance. A machine learning-assisted multi-objective optimization approach is employed to identify the optimal deposition temperature, revealing 128°C as the ideal condition for maximizing energy storage properties. Further thickness optimization based on this deposition temperature is used to enhance the performance, achieving an excellent energy storage density of 113 J/cm³ at an applied electric field of 9.1 MV/cm. This study demonstrates a powerful strategy combining machine learning with experimental design to optimize dielectric capacitors, providing a roadmap for developing high-performance energy storage materials.
通讯机构：
[Hu, L ] S;Southwest Jiaotong Univ, Sch Transportat & Logist, Chengdu, Peoples R China.
关键词：
Carsharing services;Carbon emissions;Hybrid electric vehicles;Multiple-objective simulation-optimization;Pareto optimality;MGD-SPSA
摘要：
Hybrid electric vehicles (HEVs) are perceived as transitional products bridging the gap between fueled vehicles and electric vehicles (EVs) because people intuitively believe that EVs are more environmentally friendly than HEVs. But is this perception true in the context of carsharing services (CSSs)? This paper pioneers a general large-scale multi-objective simulation–optimization (MOSO) method to explore the values of deploying HEVs in CSSs. We firstly develop a physically logical simulation model, emulating operations of CSSs and capturing mesoscopic dynamics of shared vehicles in a link-based traffic network. This model adopts an event-driven discrete-event mechanism, enhancing efficiency while maintaining high fidelity. Subsequently, we design a simulation–optimization framework aimed at achieving Pareto optimality by jointly optimizing station capacity, fleet size, and trip pricing. The goal is twofold: to maximize operational profits and to minimize carbon emissions, thereby quantitatively analyzing the potential of shared HEVs (SHEVs). To tackle the high-dimensional MOSO problem, we introduce the multi-objective optimization into stochastic approximation field by proposing a general algorithm that incorporates the multiple gradient descent algorithm with the simultaneous perturbation stochastic approximation algorithm. Furthermore, we derive its analytical expression for bi-objective optimization problems. We theoretically prove and practically demonstrate its strong global convergence. The efficiency of this method was validated through large-scale computational experiments conducted in Chengdu, Sichuan Province, involving 66,710 decision variables. These experiments showcased the method’s superiority over existing MOSO algorithms. Several groups of sensitivity experiments focusing on vehicle types and traffic scenarios reveal some interesting findings. (1) Regardless of the increase in travel distances, SHEVs, which can be viewed as shared EVs (SEVs) without range anxiety (RA), continue to primarily rely on electricity rather than fuel for their operational mileages. This high utilization of electricity results in lower carbon emissions compared to SEVs. (2) Under any traffic condition, the dual-engine feature of SHEVs significantly reduces the number of failed pickups. (3) As travel demand increases, the state of charge for SEVs may rapidly fall below the threshold that triggers RA, whereas SHEVs maintain a more reliable power supply.
Hybrid electric vehicles (HEVs) are perceived as transitional products bridging the gap between fueled vehicles and electric vehicles (EVs) because people intuitively believe that EVs are more environmentally friendly than HEVs. But is this perception true in the context of carsharing services (CSSs)? This paper pioneers a general large-scale multi-objective simulation–optimization (MOSO) method to explore the values of deploying HEVs in CSSs. We firstly develop a physically logical simulation model, emulating operations of CSSs and capturing mesoscopic dynamics of shared vehicles in a link-based traffic network. This model adopts an event-driven discrete-event mechanism, enhancing efficiency while maintaining high fidelity. Subsequently, we design a simulation–optimization framework aimed at achieving Pareto optimality by jointly optimizing station capacity, fleet size, and trip pricing. The goal is twofold: to maximize operational profits and to minimize carbon emissions, thereby quantitatively analyzing the potential of shared HEVs (SHEVs). To tackle the high-dimensional MOSO problem, we introduce the multi-objective optimization into stochastic approximation field by proposing a general algorithm that incorporates the multiple gradient descent algorithm with the simultaneous perturbation stochastic approximation algorithm. Furthermore, we derive its analytical expression for bi-objective optimization problems. We theoretically prove and practically demonstrate its strong global convergence. The efficiency of this method was validated through large-scale computational experiments conducted in Chengdu, Sichuan Province, involving 66,710 decision variables. These experiments showcased the method’s superiority over existing MOSO algorithms. Several groups of sensitivity experiments focusing on vehicle types and traffic scenarios reveal some interesting findings. (1) Regardless of the increase in travel distances, SHEVs, which can be viewed as shared EVs (SEVs) without range anxiety (RA), continue to primarily rely on electricity rather than fuel for their operational mileages. This high utilization of electricity results in lower carbon emissions compared to SEVs. (2) Under any traffic condition, the dual-engine feature of SHEVs significantly reduces the number of failed pickups. (3) As travel demand increases, the state of charge for SEVs may rapidly fall below the threshold that triggers RA, whereas SHEVs maintain a more reliable power supply.
关键词：
Collaborative optimization;signal coordination control;subarea division;traffic flow characteristics analysis;traffic signal control
摘要：
Traditional signal coordination methods face challenges in ensuring efficient traffic flow on long arterials due to urban expansion and complex spatiotemporal variations. However, existing methods struggle to achieve effective signal coordination under complex spatiotemporal variations, and lack methodological framework for universally applicable green wave coordination. To address this, a spatiotemporal partitioning-based green wave trajectory feature coordination optimization model is proposed. First, temporal partitioning is performed using an improved Fisher optimal segmentation method, while spatial subarea division is achieved via an enhanced K-Medoids algorithm. For each subarea, an arterial traffic signal control model is established based on green wave trajectory characteristics. Phase difference coordination equations are then applied to synchronize adjacent subareas. The model is validated on Foshan’s Lvjing Road, with evening peak performance compared against a classical green wave trajectory approach. Results indicate that the proposed model reduces vehicle average delay by 13.18% and the number of stops by 18.05%.
Traditional signal coordination methods face challenges in ensuring efficient traffic flow on long arterials due to urban expansion and complex spatiotemporal variations. However, existing methods struggle to achieve effective signal coordination under complex spatiotemporal variations, and lack methodological framework for universally applicable green wave coordination. To address this, a spatiotemporal partitioning-based green wave trajectory feature coordination optimization model is proposed. First, temporal partitioning is performed using an improved Fisher optimal segmentation method, while spatial subarea division is achieved via an enhanced K-Medoids algorithm. For each subarea, an arterial traffic signal control model is established based on green wave trajectory characteristics. Phase difference coordination equations are then applied to synchronize adjacent subareas. The model is validated on Foshan’s Lvjing Road, with evening peak performance compared against a classical green wave trajectory approach. Results indicate that the proposed model reduces vehicle average delay by 13.18% and the number of stops by 18.05%.
期刊：
SAE International Journal of Connected and Automated Vehicles,2025年9(1):1-16 ISSN：2574-0741
作者机构：
[Zhaolei Zhang; Zhizhen Liu; Feng Tang] Changsha University of Science and Technology, China;[Xibin Ding] Changsha University of Science and Technology, School of Transportation Engineering, China
摘要：
The existing variable speed limit (VSL) control strategies rely on variable message signs, leading to slow response times and sensitivity to driver compliance. These methods struggle to adapt to environments where both connected automated vehicles (CAVs) and manual vehicles coexist. This article proposes a VSL control strategy using the deep deterministic policy gradient (DDPG) algorithm to optimize travel time, reduce collision risks, and minimize energy consumption. The algorithm leverages real-time traffic data and prior speed limits to generate new control actions. A reward function is designed within a DDPG-based actor-critic framework to determine optimal speed limits. The proposed strategy was tested in two scenarios and compared against no-control, rule-based control, and DDQN-based control methods. The simulation results indicate that the proposed control strategy outperforms existing approaches in terms of improving TTS (total time spent), enhancing the throughput efficiency of the bottleneck area, and reducing the spatial and temporal extent of traffic congestion. Compared to the suboptimal DDQN-based VSL control, the proposed strategy improves TTS by 9.3% in Scenario 1 and by 11% in Scenario 2. The sensitivity analysis shows that the proposed control strategy improves performance as the penetration rate of CAVs increases. However, when the penetration rate reaches a certain threshold, the potential for further optimization becomes limited. Furthermore, higher time-to-collision (TTC) values, influenced by the reward function r 2, enhance traffic safety.
摘要：
As an emerging environmentally friendly solid waste-based composite foam lightweight soil, saponified slag fly ash (SS-FA) foam lightweight soil has a wide range of application prospects in road engineering. In this paper, the dynamic characteristics of SS-FA foam light soil material were investigated. Dynamic triaxial tests under different cyclic loading conditions were designed to analyze the variation rules of dynamic elastic modulus and damping ratio. The results showed that the stress-strain curve of SS-FA foam lightweight soil can be divided into three stages: elastic stage, plateau stage, and stress yielding stage. Under cyclic dynamic load, with the increase of dynamic stress amplitude, the dynamic elastic modulus of 400–700 kg/m3 samples gradually increased to the maximum, reaching 235.24 MPa, 324.54 MPa, 356.45 MPa, 379.67 MPa, respectively. The damping ratio, on the other hand, shows a tendency to first decrease and then slowly increase to stabilize. The dynamic elastic modulus is positively correlated with density grade, confining pressure and loading frequency. The damping ratio decreases with the increase of density grade and loading frequency, and increases with the increase of confining pressure. The electron microscope test was designed and image processing and data statistics were carried out. Through the grey correlation analysis, the correlation degree between the microstructure parameters of SS-FA foamed lightweight soil and the macroscopic mechanical properties is basically above 0.6, indicating that the two have a significant correlation. A normalized prediction formula model between the dynamic elastic modulus of materials and the conditional parameters was established. The R 2 of the linear fitting of the predicted value is 0.964, indicating that the prediction model has a high degree of fitting and a good prediction effect. The research results revealed the dynamic mechanical properties of foamed lightweight soil, and provided a reference for the application of SS-FA foamed lightweight soil in subgrade engineering.
As an emerging environmentally friendly solid waste-based composite foam lightweight soil, saponified slag fly ash (SS-FA) foam lightweight soil has a wide range of application prospects in road engineering. In this paper, the dynamic characteristics of SS-FA foam light soil material were investigated. Dynamic triaxial tests under different cyclic loading conditions were designed to analyze the variation rules of dynamic elastic modulus and damping ratio. The results showed that the stress-strain curve of SS-FA foam lightweight soil can be divided into three stages: elastic stage, plateau stage, and stress yielding stage. Under cyclic dynamic load, with the increase of dynamic stress amplitude, the dynamic elastic modulus of 400–700 kg/m3 samples gradually increased to the maximum, reaching 235.24 MPa, 324.54 MPa, 356.45 MPa, 379.67 MPa, respectively. The damping ratio, on the other hand, shows a tendency to first decrease and then slowly increase to stabilize. The dynamic elastic modulus is positively correlated with density grade, confining pressure and loading frequency. The damping ratio decreases with the increase of density grade and loading frequency, and increases with the increase of confining pressure. The electron microscope test was designed and image processing and data statistics were carried out. Through the grey correlation analysis, the correlation degree between the microstructure parameters of SS-FA foamed lightweight soil and the macroscopic mechanical properties is basically above 0.6, indicating that the two have a significant correlation. A normalized prediction formula model between the dynamic elastic modulus of materials and the conditional parameters was established. The R 2 of the linear fitting of the predicted value is 0.964, indicating that the prediction model has a high degree of fitting and a good prediction effect. The research results revealed the dynamic mechanical properties of foamed lightweight soil, and provided a reference for the application of SS-FA foamed lightweight soil in subgrade engineering.
通讯机构：
[Hao, W ] C;Changsha Univ Sci & Technol, Sch Traff & Transportat Engn, Changsha 410114, Hunan, Peoples R China.
关键词：
Reliability;Stability analysis;Numerical stability;Thermal stability;Autonomous vehicles;Connected vehicles;Roads;Mathematical models;Pricing;Electronic mail;Connected and autonomous vehicles;travel time reliability;mixed traffic flow
摘要：
Existing studies on traffic flow stability primarily focused on local stability, with little attention given to its extension to the network level, known as network stability. In this paper, a reliability-based equilibrium model in a mixed traffic network including human-driven vehicles and connected and autonomous vehicles is developed to analyze the impact of connected and autonomous vehicles on traffic flow stability. The basic characteristics of the model are first examined on a small network, demonstrating the non-uniqueness of the link flow in the user equilibrium pattern. Then, the model is extended to the case of a general network with Variational Inequality (VI) equations. In addition, a two-level optimization strategy is developed by incorporating the pricing and quantity control strategies to the reliability model. Numerical examples are conducted based on Sioux Falls networks to examine the performance of the proposed models.
