Parameter ambiguity, particularly the representative length denoting the overall scale of the frozen wall, frequently impedes the development of analytical models for artificial ground freezing. This study proposes a quantitative methodology for determining using numerical simulations. After validating the coupled thermo-hydraulic solver against laboratory experiments, we conducted a parametric study of 12 pipe layouts under varying groundwater velocities. The results showed that the critical flow velocity decreased with the number of pipes owing to the hydraulic dam-up effect. Subsequently, a multiple linear regression model was used to predict as a function of the total wall length, pipe density, and their interactions. This analysis revealed that a higher pipe density significantly improved the hydraulic robustness of longer frozen walls. The predictive model achieved a high coefficient of determination of 0.9771. By transforming from a vague assumption into a predictable parameter for high-permeability soils, this study bridges numerical simulations and analytical models to enhance engineering design reliability.
{"title":"Determining representative length in analytical model for artificial ground freezing: A numerical study","authors":"Shun Kikuchi , Hirotaka Saito , Masato Oishi , Kunio Watanabe , Yusuke Yabuchi","doi":"10.1016/j.coldregions.2026.104842","DOIUrl":"10.1016/j.coldregions.2026.104842","url":null,"abstract":"<div><div>Parameter ambiguity, particularly the representative length <span><math><mi>l</mi></math></span> denoting the overall scale of the frozen wall, frequently impedes the development of analytical models for artificial ground freezing. This study proposes a quantitative methodology for determining <span><math><mi>l</mi></math></span> using numerical simulations. After validating the coupled thermo-hydraulic solver against laboratory experiments, we conducted a parametric study of 12 pipe layouts under varying groundwater velocities. The results showed that the critical flow velocity decreased with the number of pipes owing to the hydraulic dam-up effect. Subsequently, a multiple linear regression model was used to predict <span><math><mi>l</mi></math></span> as a function of the total wall length, pipe density, and their interactions. This analysis revealed that a higher pipe density significantly improved the hydraulic robustness of longer frozen walls. The predictive model achieved a high coefficient of determination of 0.9771. By transforming <span><math><mi>l</mi></math></span> from a vague assumption into a predictable parameter for high-permeability soils, this study bridges numerical simulations and analytical models to enhance engineering design reliability.</div></div>","PeriodicalId":10522,"journal":{"name":"Cold Regions Science and Technology","volume":"245 ","pages":"Article 104842"},"PeriodicalIF":3.8,"publicationDate":"2026-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146075305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-25DOI: 10.1016/j.coldregions.2026.104847
Hamza Asif, Muhammad S. Virk, Jan-Arne Pettersen, Pourya Pourhejazy
Despite the vast economic (e.g., tourism) and environmental advantages (e.g., clean transportation) of gondola lifts, there is a lack of a comprehensive reference about ice accretion, ice detection, and mitigation solutions for safe operations of gondola infrastructure. This paper presents a state-of-the-art scientific literature review drawn from synergetic applications (e.g., power transmission lines, railways, bridges, and aviation structures) to investigate and identify the scientific technological knowledge gaps. An overview of gondola system components along with their operations, as well as the system components' design and safety standards, is provided to discuss the potential impacts of icing on gondola infrastructure. The literature review revealed a lack of comprehensive scientific studies explicitly addressing ice accretion on gondola systems. Insights from the comparable applications and discussion with the gondola operators indicate that ice accretion can pose significant safety risks and potential structural failures. Using opinion and critical reasoning from experts, some existing suitable ice detection and mitigation techniques are listed and mapped to critical gondola components with the potential for practical implementation. Several directions for future research are also identified to contribute to this underexplored field of research.
{"title":"A review of ice accretion, detection, and mitigation methods for the gondola infrastructure application","authors":"Hamza Asif, Muhammad S. Virk, Jan-Arne Pettersen, Pourya Pourhejazy","doi":"10.1016/j.coldregions.2026.104847","DOIUrl":"10.1016/j.coldregions.2026.104847","url":null,"abstract":"<div><div>Despite the vast economic (e.g., tourism) and environmental advantages (e.g., clean transportation) of gondola lifts, there is a lack of a comprehensive reference about ice accretion, ice detection, and mitigation solutions for safe operations of gondola infrastructure. This paper presents a state-of-the-art scientific literature review drawn from synergetic applications (e.g., power transmission lines, railways, bridges, and aviation structures) to investigate and identify the scientific technological knowledge gaps. An overview of gondola system components along with their operations, as well as the system components' design and safety standards, is provided to discuss the potential impacts of icing on gondola infrastructure. The literature review revealed a lack of comprehensive scientific studies explicitly addressing ice accretion on gondola systems. Insights from the comparable applications and discussion with the gondola operators indicate that ice accretion can pose significant safety risks and potential structural failures. Using opinion and critical reasoning from experts, some existing suitable ice detection and mitigation techniques are listed and mapped to critical gondola components with the potential for practical implementation. Several directions for future research are also identified to contribute to this underexplored field of research.</div></div>","PeriodicalId":10522,"journal":{"name":"Cold Regions Science and Technology","volume":"245 ","pages":"Article 104847"},"PeriodicalIF":3.8,"publicationDate":"2026-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146075303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-23DOI: 10.1016/j.coldregions.2026.104845
Ye Zhang, Yufeng Zhan, Hongru Chen, Yongcan Zhu, Long Zhao, Yi Tian
The transmission line icing scenario is complex, with limited samples for different icing types and high sim-ilarity between them. Moreover, there is currently a lack of non-contact methods for identifying icing types. Therefore, this paper proposes a transmission line icing classification algorithm based on BiTex-ResNet34. Firstly, a quantitative analysis of the texture features of icing images is conducted to identify the most significant feature parameters that highlight the mean differences between different icing types, thereby enhancing the discriminability between them. Secondly, the model adopts a dual-branch architecture, with each branch containing a complete ResNet34 convolutional backbone network to parallelly extract both the raw features and texture features of icing images, thereby enhancing the model's feature representation. Finally, the Second-order Feature Fusion Module (SK-FM) module is embedded at different layers of the model's dual-branch architecture. This module integrates second-order features and concatenates the Selective Kernel (SK) attention mechanism to capture the correlations between different icing feature information, thereby improving the model's ability to distinguish between three types of icing: rime, hard rime, and soft rime. Experimental results show that BiTex-ResNet34 can accurately identify the three types of icing—glaze, hard rime, and soft rime—under complex environments, achieving precision, recall, and F1-score of 94.7%, 91.07%, and 92.85%, respectively, providing a new approach for transmission line icing type recognition.
{"title":"Research on transmission line icing classification and recognition algorithm based on BiTex-ResNet34","authors":"Ye Zhang, Yufeng Zhan, Hongru Chen, Yongcan Zhu, Long Zhao, Yi Tian","doi":"10.1016/j.coldregions.2026.104845","DOIUrl":"10.1016/j.coldregions.2026.104845","url":null,"abstract":"<div><div>The transmission line icing scenario is complex, with limited samples for different icing types and high sim-ilarity between them. Moreover, there is currently a lack of non-contact methods for identifying icing types. Therefore, this paper proposes a transmission line icing classification algorithm based on BiTex-ResNet34. Firstly, a quantitative analysis of the texture features of icing images is conducted to identify the most significant feature parameters that highlight the mean differences between different icing types, thereby enhancing the discriminability between them. Secondly, the model adopts a dual-branch architecture, with each branch containing a complete ResNet34 convolutional backbone network to parallelly extract both the raw features and texture features of icing images, thereby enhancing the model's feature representation. Finally, the Second-order Feature Fusion Module (SK-FM) module is embedded at different layers of the model's dual-branch architecture. This module integrates second-order features and concatenates the Selective Kernel (SK) attention mechanism to capture the correlations between different icing feature information, thereby improving the model's ability to distinguish between three types of icing: rime, hard rime, and soft rime. Experimental results show that BiTex-ResNet34 can accurately identify the three types of icing—glaze, hard rime, and soft rime—under complex environments, achieving precision, recall, and F1-score of 94.7%, 91.07%, and 92.85%, respectively, providing a new approach for transmission line icing type recognition.</div></div>","PeriodicalId":10522,"journal":{"name":"Cold Regions Science and Technology","volume":"245 ","pages":"Article 104845"},"PeriodicalIF":3.8,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146075302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-22DOI: 10.1016/j.coldregions.2026.104843
Dongdong Ma , Maoqi Li , Rongrong Zhang , Yizhong Tan
A primary methodological constraint in analyzing dynamic damage progression within frozen soil systems arises from experimental limitations in obtaining high-resolution thermal measurements during transient impact loading. To address this challenge, an advanced experimental methodology was developed to synchronously measure the mechanical properties and temperature variation of the measurement points on the surface of frozen soil specimen under impact loading, incorporating a modified split Hopkinson pressure bar (SHPB) coupled with an Infrared Temperature Measurement System (ITMS). In addition, the parameters of the PFC3D model were determined by comparing the simulation and test elevated temperature curves. The elevated temperature field evolution characteristic of frozen soil with various conditions was systematically studied. Moreover, the work-to-heat conversion coefficient (η) of frozen soil was determined by comparing the calculated elevated temperature curves and the simulated results. Finally, the elevated temperature damage mechanism of frozen soil under impact loading was analyzed by revealing the ice-water transformation process. Results demonstrated that the temperature elevation under impact loading showed a gradual and non-uniform progression. The average elevated temperature value of frozen soil increased with the decrease of initial temperature and the increase of strain rate, and its maximum value 1.18 °C was observed under −30 °C initial temperature and 920 s−1 strain rate. The η values of frozen soil ranged from 0.89 to 0.95 spanning a range of subzero temperatures (−10 °C to −30 °C) and strain rates (480 s−1 to 920 s−1). The observed decline in dynamic strength and decreased material brittleness resulting from impact-induced temperature elevation were attributed to three interconnected mechanisms: a progressive reduction in ice crystal content, a concomitant rise in unfrozen water concentration, and the progressive deterioration of interparticle bonding strength throughout thermal loading. The research findings provided significant guidance and served as a valuable reference for practical engineering applications.
{"title":"Study on elevated temperature effect and damage mechanism of frozen soil under impact loading","authors":"Dongdong Ma , Maoqi Li , Rongrong Zhang , Yizhong Tan","doi":"10.1016/j.coldregions.2026.104843","DOIUrl":"10.1016/j.coldregions.2026.104843","url":null,"abstract":"<div><div>A primary methodological constraint in analyzing dynamic damage progression within frozen soil systems arises from experimental limitations in obtaining high-resolution thermal measurements during transient impact loading. To address this challenge, an advanced experimental methodology was developed to synchronously measure the mechanical properties and temperature variation of the measurement points on the surface of frozen soil specimen under impact loading, incorporating a modified split Hopkinson pressure bar (SHPB) coupled with an Infrared Temperature Measurement System (ITMS). In addition, the parameters of the PFC3D model were determined by comparing the simulation and test elevated temperature curves. The elevated temperature field evolution characteristic of frozen soil with various conditions was systematically studied. Moreover, the work-to-heat conversion coefficient (<em>η</em>) of frozen soil was determined by comparing the calculated elevated temperature curves and the simulated results. Finally, the elevated temperature damage mechanism of frozen soil under impact loading was analyzed by revealing the ice-water transformation process. Results demonstrated that the temperature elevation under impact loading showed a gradual and non-uniform progression. The average elevated temperature value of frozen soil increased with the decrease of initial temperature and the increase of strain rate, and its maximum value 1.18 °C was observed under −30 °C initial temperature and 920 s<sup>−1</sup> strain rate. The <em>η</em> values of frozen soil ranged from 0.89 to 0.95 spanning a range of subzero temperatures (−10 °C to −30 °C) and strain rates (480 s<sup>−1</sup> to 920 s<sup>−1</sup>). The observed decline in dynamic strength and decreased material brittleness resulting from impact-induced temperature elevation were attributed to three interconnected mechanisms: a progressive reduction in ice crystal content, a concomitant rise in unfrozen water concentration, and the progressive deterioration of interparticle bonding strength throughout thermal loading. The research findings provided significant guidance and served as a valuable reference for practical engineering applications.</div></div>","PeriodicalId":10522,"journal":{"name":"Cold Regions Science and Technology","volume":"245 ","pages":"Article 104843"},"PeriodicalIF":3.8,"publicationDate":"2026-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146036120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-20DOI: 10.1016/j.coldregions.2026.104844
Taoying Liu, Sisi Wang, Huaheng Li, Mengyuan Cui
The seepage characteristics of geotechnical materials critically affect the stability of engineering structures under rainfall conditions. In cold and high-altitude regions, repeated freeze-thaw (F-T) cycles cause the internal deterioration and damage of engineering rock masses and alter the seepage behavior, leading to frequent instability hazards. To address this issue, a series of F-T tests were conducted on sandstone samples to investigate the evolution of rock's porosity and permeability subjected to different F-T cycles in this paper, combining with the coupled PFC-COMSOL numerical simulations. Moreover, the Dual Permeability Model (DPM) was further employed to simulate the effects on rainwater infiltration behaviors of sandstone treated with F-T cycles. The results show that the porosity of sandstone decreases slowly first and then increases rapidly with the increase of F-T cycles. The permeability exhibits a significant positive correlation with the number of F-T cycles. The peak position of seepage pressure moves deeper into the rock mass with increasing F-T cycles, and the evolution trend of seepage pressure in different seepage media is synchronous. In addition, the influence of F-T cycles on the wetting-front depth is more pronounced than that of rainfall intensity, with an average increase of approximately 30% as the number of cycles rises. During the rainfall infiltration, a dynamic negative correlation between seepage pressure and effective saturation is observed. These test findings demonstrate that F-T cycling significantly modifies the rock pore structure and enhances its infiltration capacity. The study results provide a theoretical reference for the design of protective and drainage systems and for the stability assessment of geotechnical works in alpine and seasonally frozen regions.
{"title":"Evolution of seepage characteristics in frozen-thawed sandstone: Insights from coupled PFC-COMSOL simulations","authors":"Taoying Liu, Sisi Wang, Huaheng Li, Mengyuan Cui","doi":"10.1016/j.coldregions.2026.104844","DOIUrl":"10.1016/j.coldregions.2026.104844","url":null,"abstract":"<div><div>The seepage characteristics of geotechnical materials critically affect the stability of engineering structures under rainfall conditions. In cold and high-altitude regions, repeated freeze-thaw (F-T) cycles cause the internal deterioration and damage of engineering rock masses and alter the seepage behavior, leading to frequent instability hazards. To address this issue, a series of F-T tests were conducted on sandstone samples to investigate the evolution of rock's porosity and permeability subjected to different F-T cycles in this paper, combining with the coupled PFC-COMSOL numerical simulations. Moreover, the Dual Permeability Model (DPM) was further employed to simulate the effects on rainwater infiltration behaviors of sandstone treated with F-T cycles. The results show that the porosity of sandstone decreases slowly first and then increases rapidly with the increase of F-T cycles. The permeability exhibits a significant positive correlation with the number of F-T cycles. The peak position of seepage pressure moves deeper into the rock mass with increasing F-T cycles, and the evolution trend of seepage pressure in different seepage media is synchronous. In addition, the influence of F-T cycles on the wetting-front depth is more pronounced than that of rainfall intensity, with an average increase of approximately 30% as the number of cycles rises. During the rainfall infiltration, a dynamic negative correlation between seepage pressure and effective saturation is observed. These test findings demonstrate that F-T cycling significantly modifies the rock pore structure and enhances its infiltration capacity. The study results provide a theoretical reference for the design of protective and drainage systems and for the stability assessment of geotechnical works in alpine and seasonally frozen regions.</div></div>","PeriodicalId":10522,"journal":{"name":"Cold Regions Science and Technology","volume":"245 ","pages":"Article 104844"},"PeriodicalIF":3.8,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146075304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-19DOI: 10.1016/j.coldregions.2026.104832
Yong Wook Lee , Mingjian Wu , Tae J. Kwon
Adverse winter weather significantly compromises driving safety and mobility in regions such as Canada and the northern United States. This study addresses these challenges by utilizing stationary Road Weather Information Systems (RWIS) equipped with cameras. These images capture complex scenes, making automated road surface condition (RSC) classification systems particularly challenging. Unlike previous studies that required manual cropping of main road pavement, we applied convolutional neural networks (CNNs) directly to full stationary RWIS imagery to validate their effectiveness and generalizability for real-world winter road maintenance (WRM) applications. Our study focused on four key aspects: (1) rigorously validating CNN performance on stationary RWIS images without manual cropping, (2) systematically analyzing the influence of camera angles using explainable artificial intelligence (XAI) techniques, (3) evaluating the effect of image resolution on model accuracy, and (4) exploring data-quantity trade-offs, including the impact of adding or removing camera feeds, to develop robust and deployable CNN models. The developed CNN achieved excellent performance metrics, all exceeding 98%. Our findings indicate that optimizing camera orientation substantially enhances the model's focus on relevant features that align with human interpretation. Reducing background complexity and increasing road captures from different perspectives further enhanced model focus. Furthermore, increasing image resolution up to 224 × 224 improved performance, although gains were marginal beyond this point while computational costs rose substantially. This comprehensive evaluation demonstrates the high potential of using stationary RWIS imagery for RSC classification with CNNs, suggesting significant improvements in WRM efficiency and traffic safety during winter.
{"title":"Integrating convolutional neural networks and explainable AI for enhanced winter road surface conditions classification using stationary RWIS imagery","authors":"Yong Wook Lee , Mingjian Wu , Tae J. Kwon","doi":"10.1016/j.coldregions.2026.104832","DOIUrl":"10.1016/j.coldregions.2026.104832","url":null,"abstract":"<div><div>Adverse winter weather significantly compromises driving safety and mobility in regions such as Canada and the northern United States. This study addresses these challenges by utilizing stationary Road Weather Information Systems (RWIS) equipped with cameras. These images capture complex scenes, making automated road surface condition (RSC) classification systems particularly challenging. Unlike previous studies that required manual cropping of main road pavement, we applied convolutional neural networks (CNNs) directly to full stationary RWIS imagery to validate their effectiveness and generalizability for real-world winter road maintenance (WRM) applications. Our study focused on four key aspects: (1) rigorously validating CNN performance on stationary RWIS images without manual cropping, (2) systematically analyzing the influence of camera angles using explainable artificial intelligence (XAI) techniques, (3) evaluating the effect of image resolution on model accuracy, and (4) exploring data-quantity trade-offs, including the impact of adding or removing camera feeds, to develop robust and deployable CNN models. The developed CNN achieved excellent performance metrics, all exceeding 98%. Our findings indicate that optimizing camera orientation substantially enhances the model's focus on relevant features that align with human interpretation. Reducing background complexity and increasing road captures from different perspectives further enhanced model focus. Furthermore, increasing image resolution up to 224 × 224 improved performance, although gains were marginal beyond this point while computational costs rose substantially. This comprehensive evaluation demonstrates the high potential of using stationary RWIS imagery for RSC classification with CNNs, suggesting significant improvements in WRM efficiency and traffic safety during winter.</div></div>","PeriodicalId":10522,"journal":{"name":"Cold Regions Science and Technology","volume":"245 ","pages":"Article 104832"},"PeriodicalIF":3.8,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146036118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-17DOI: 10.1016/j.coldregions.2026.104831
Francine Hematang , Jonni Marwa , Anton Sinery , Meliza Worabai , Dominggas Renwarin , Evelin Tanur , Obed Lense , Dina Arung Padang , Alexander Rumatora , Elieser Sirami , Ana Tampang , Christian Imburi , Petrus Dimara
Climate change continues to occur, so that the chrysosphere ecosystem has been heavily affected. This study aimed to investigate changes of glacier area in Puncak Jaya in response to ongoing global climate change issue. Landsat 2–9 satellite image series was used to see the dynamics of glacier change using digitized on-screen method. An important finding is that the tropical glaciers of Papua will survive until 2024, but melt and disappear faster than researchers previously predicted. Results showed that the glacier area has decreased by 7.28 km2 (97%) in over 44 years. In 1980, Puncak Jaya and Idenburg glaciers covered 7.46 km2 and then decreased to 0.19 km2 in 2024. Research also shows that only two glaciers remain, while four others Ngga Pilimsit Glacier, Meren Glacier, Southwall Hanging Glacier and West Northwall Firn Glacier have disappeared. In 2024, the Carstensz Glacier covered 0.050 km2 and the East Firn Northwall Glacier 0.136 km2. Another important finding is that the East Firn Northwall Glacier is predicted to disappear faster in 2028–2029 than the Carstensz Glacier in 2029–2030. In the future, it will be necessary to collect all the information from the field, estimate the impact on the ecosystem if the glacier completely disappears, and find out why East Northwall Firn Glacier melts faster than Carstensz Glacier.
气候变化不断发生，使温圈生态系统受到严重影响。本研究旨在探讨punak Jaya冰川面积的变化对全球气候变化问题的响应。利用Landsat 2-9卫星图像序列，采用数字化屏幕显示方法观察冰川变化动态。一项重要的发现是，巴布亚的热带冰川将存活到2024年，但融化和消失的速度比研究人员先前预测的要快。结果表明：44年来冰川面积减少了7.28 km2 (97%)；1980年，Puncak Jaya和Idenburg冰川覆盖面积为7.46 km2, 2024年减少至0.19 km2。研究还表明，只有两个冰川仍然存在，而其他四个冰川，阿嘎皮利姆斯特冰川，梅伦冰川，南墙悬挂冰川和西北墙芬冰川已经消失。2024年，Carstensz冰川覆盖面积为0.050 km2， East Firn Northwall冰川覆盖面积为0.136 km2。另一个重要的发现是，预计2028-2029年东芬-诺斯沃尔冰川的消失速度将超过2029-2030年卡斯滕斯冰川的消失速度。在未来，有必要收集所有来自现场的信息，估计冰川完全消失对生态系统的影响，并找出为什么东北壁芬冰川比卡斯滕斯冰川融化得更快。
{"title":"Rapid retreat of tropical glaciers in Puncak Jaya, Papua: Four decades of change observed from Landsat Imagery, 1980–2024","authors":"Francine Hematang , Jonni Marwa , Anton Sinery , Meliza Worabai , Dominggas Renwarin , Evelin Tanur , Obed Lense , Dina Arung Padang , Alexander Rumatora , Elieser Sirami , Ana Tampang , Christian Imburi , Petrus Dimara","doi":"10.1016/j.coldregions.2026.104831","DOIUrl":"10.1016/j.coldregions.2026.104831","url":null,"abstract":"<div><div>Climate change continues to occur, so that the chrysosphere ecosystem has been heavily affected. This study aimed to investigate changes of glacier area in Puncak Jaya in response to ongoing global climate change issue. Landsat 2–9 satellite image series was used to see the dynamics of glacier change using digitized on-screen method. An important finding is that the tropical glaciers of Papua will survive until 2024, but melt and disappear faster than researchers previously predicted. Results showed that the glacier area has decreased by 7.28 km<sup>2</sup> (97%) in over 44 years. In 1980, Puncak Jaya and Idenburg glaciers covered 7.46 km<sup>2</sup> and then decreased to 0.19 km<sup>2</sup> in 2024. Research also shows that only two glaciers remain, while four others Ngga Pilimsit Glacier, Meren Glacier, Southwall Hanging Glacier and West Northwall Firn Glacier have disappeared. In 2024, the Carstensz Glacier covered 0.050 km<sup>2</sup> and the East Firn Northwall Glacier 0.136 km<sup>2</sup>. Another important finding is that the East Firn Northwall Glacier is predicted to disappear faster in 2028–2029 than the Carstensz Glacier in 2029–2030. In the future, it will be necessary to collect all the information from the field, estimate the impact on the ecosystem if the glacier completely disappears, and find out why East Northwall Firn Glacier melts faster than Carstensz Glacier.</div></div>","PeriodicalId":10522,"journal":{"name":"Cold Regions Science and Technology","volume":"245 ","pages":"Article 104831"},"PeriodicalIF":3.8,"publicationDate":"2026-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146036531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-15DOI: 10.1016/j.coldregions.2026.104830
Huayang Sun , Yanlin Huo , Xiaobing Ma , Xuesi Ji , Zhichao Xu , Zhitao Chen , Yingzi Yang
Early-age frozen damage poses significant challenges to concrete durability and structural integrity in cold-region construction. This study investigates the long-term mechanical properties of early-age frozen sulphoaluminate cement-engineered cementitious composites (SAC-ECC). Mechanical tests, single-fiber pullout tests, micromechanical modeling, and microstructural analyses were conducted to evaluate the effects of pre-curing times and frozen temperatures. The experimental results demonstrated that SAC-ECC with shorter pre-curing times (0.75 h), both compressive and flexural strengths increased as frozen temperatures decreased from 0 °C to −10 °C. In contrast, for SAC-ECC with longer pre-curing times (1.5 h and 3 h), the compressive and flexural strengths were aggravated with decreasing freezing temperatures. In addition, longer pre-curing times and lower frozen temperatures reduced tensile strength but significantly enhanced tensile ductility. For SAC-ECC frozen at −10 °C after 3 h of pre-curing, the tensile strain increased by 92.94% compared with the unfrozen group. Micromechanical and microstructural analyses revealed that for early-frozen SAC-ECC, a shorter pre-curing time improved the pore structure and fiber matrix interface, whereas a longer pre-curing time increased porosity and weakened interfacial bonding. The TOPSIS analysis can effectively balance the mechanical properties and time cost, thus providing valuable guidance for the application of SAC-ECC in cold-region construction.
{"title":"New insight into mechanical evolution and micro-mechanisms of early-age frozen engineered cementitious composites","authors":"Huayang Sun , Yanlin Huo , Xiaobing Ma , Xuesi Ji , Zhichao Xu , Zhitao Chen , Yingzi Yang","doi":"10.1016/j.coldregions.2026.104830","DOIUrl":"10.1016/j.coldregions.2026.104830","url":null,"abstract":"<div><div>Early-age frozen damage poses significant challenges to concrete durability and structural integrity in cold-region construction. This study investigates the long-term mechanical properties of early-age frozen sulphoaluminate cement-engineered cementitious composites (SAC-ECC). Mechanical tests, single-fiber pullout tests, micromechanical modeling, and microstructural analyses were conducted to evaluate the effects of pre-curing times and frozen temperatures. The experimental results demonstrated that SAC-ECC with shorter pre-curing times (0.75 h), both compressive and flexural strengths increased as frozen temperatures decreased from 0 °C to −10 °C. In contrast, for SAC-ECC with longer pre-curing times (1.5 h and 3 h), the compressive and flexural strengths were aggravated with decreasing freezing temperatures. In addition, longer pre-curing times and lower frozen temperatures reduced tensile strength but significantly enhanced tensile ductility. For SAC-ECC frozen at −10 °C after 3 h of pre-curing, the tensile strain increased by 92.94% compared with the unfrozen group. Micromechanical and microstructural analyses revealed that for early-frozen SAC-ECC, a shorter pre-curing time improved the pore structure and fiber matrix interface, whereas a longer pre-curing time increased porosity and weakened interfacial bonding. The TOPSIS analysis can effectively balance the mechanical properties and time cost, thus providing valuable guidance for the application of SAC-ECC in cold-region construction.</div></div>","PeriodicalId":10522,"journal":{"name":"Cold Regions Science and Technology","volume":"245 ","pages":"Article 104830"},"PeriodicalIF":3.8,"publicationDate":"2026-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146036532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Snow avalanches pose a major hazard in mountainous regions, but their sporadic occurrence and remote locations hinder consistent regional monitoring. Automated remote sensing techniques, particularly those using Synthetic Aperture Radar (SAR), offer promising solutions for systematic data collection. However, validating SAR-based avalanche detections remains challenging due to the limited availability of ground truth data, spatial mismatches, temporal inconsistencies between reference datasets, and uncertainties associated with the relatively simple hypotheses underlying detection algorithms. This study assesses the performance and reliability of SAR-based avalanche debris detection across seven massifs in the French Alps over two winter seasons (2017–2018 and early 2020). The SAR-derived detections are evaluated against multiple indicators of avalanche activity, including avalanche inventories, snow cover simulation models, and hazard levels from official French avalanche bulletins. The findings demonstrate that, overall, SAR-based methods effectively capture the spatial and temporal patterns of ground-observed avalanche activity and align well with reported hazard levels, particularly during periods of elevated avalanche risk. Notably, for the Beaufortain massif during the 2020 season, SAR detections achieved a Pearson correlation coefficient of 0.65 with ground-based observations. Nevertheless, performance varies significantly across massifs and seasons, with strong correlations in some areas and weaker associations in others. The topographic characteristics (slope, elevation, aspect) of detected debris also show good agreement with other indicators. Despite inherent biases in each reference dataset, the results highlight the potential of SAR imagery for capturing regional-scale spatiotemporal dynamics of avalanches. While SAR offers valuable insights, detection remains far from perfect, underscoring the continued need for direct field observations and further refinement of detection algorithms to improve accuracy and validation.
{"title":"Can Sentinel-1 reliably provide regional-scale information on avalanche activity","authors":"Suvrat Kaushik , Fatima Karbou , Nicolas Eckert , Léo Viallon-Galinier , Adrien Mauss","doi":"10.1016/j.coldregions.2026.104822","DOIUrl":"10.1016/j.coldregions.2026.104822","url":null,"abstract":"<div><div>Snow avalanches pose a major hazard in mountainous regions, but their sporadic occurrence and remote locations hinder consistent regional monitoring. Automated remote sensing techniques, particularly those using Synthetic Aperture Radar (SAR), offer promising solutions for systematic data collection. However, validating SAR-based avalanche detections remains challenging due to the limited availability of ground truth data, spatial mismatches, temporal inconsistencies between reference datasets, and uncertainties associated with the relatively simple hypotheses underlying detection algorithms. This study assesses the performance and reliability of SAR-based avalanche debris detection across seven massifs in the French Alps over two winter seasons (2017–2018 and early 2020). The SAR-derived detections are evaluated against multiple indicators of avalanche activity, including avalanche inventories, snow cover simulation models, and hazard levels from official French avalanche bulletins. The findings demonstrate that, overall, SAR-based methods effectively capture the spatial and temporal patterns of ground-observed avalanche activity and align well with reported hazard levels, particularly during periods of elevated avalanche risk. Notably, for the Beaufortain massif during the 2020 season, SAR detections achieved a Pearson correlation coefficient of 0.65 with ground-based observations. Nevertheless, performance varies significantly across massifs and seasons, with strong correlations in some areas and weaker associations in others. The topographic characteristics (slope, elevation, aspect) of detected debris also show good agreement with other indicators. Despite inherent biases in each reference dataset, the results highlight the potential of SAR imagery for capturing regional-scale spatiotemporal dynamics of avalanches. While SAR offers valuable insights, detection remains far from perfect, underscoring the continued need for direct field observations and further refinement of detection algorithms to improve accuracy and validation.</div></div>","PeriodicalId":10522,"journal":{"name":"Cold Regions Science and Technology","volume":"245 ","pages":"Article 104822"},"PeriodicalIF":3.8,"publicationDate":"2026-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146036534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-10DOI: 10.1016/j.coldregions.2025.104812
Lars Blatny , David Hamre , Johan Gaume , Peter Gauer , Arthur Mears
Slushflows consist of a mixture of snow, water, and ice and often entrain debris or sediments. The high mobility and high density of the flows make them a considerable natural hazard, endangering settlements and infrastructure. They are most commonly associated with higher latitudes, such as Norway, Iceland, or Alaska, but have also been reported in various other countries, including regions such as the Alps. This paper describes slushflows near Atigun Pass, Alaska, which were well documented in a study for the Alyeska Pipeline Service Company (APSC) in 1982. The information has been privately held and is now being released for research purposes. Moreover, state-of-the-art modeling techniques are introduced and applied to the described slushflows, considering both depth-averaged and depth-resolved (three-dimensional) numerical methods with viscoplastic and elasto-viscoplastic rheological models. The observations and modeling approaches presented in this study provide insights that can improve the understanding and assessment of slushflows and their dynamics.
{"title":"Observations and modeling of slushflows from Atigun Pass, Alaska","authors":"Lars Blatny , David Hamre , Johan Gaume , Peter Gauer , Arthur Mears","doi":"10.1016/j.coldregions.2025.104812","DOIUrl":"10.1016/j.coldregions.2025.104812","url":null,"abstract":"<div><div>Slushflows consist of a mixture of snow, water, and ice and often entrain debris or sediments. The high mobility and high density of the flows make them a considerable natural hazard, endangering settlements and infrastructure. They are most commonly associated with higher latitudes, such as Norway, Iceland, or Alaska, but have also been reported in various other countries, including regions such as the Alps. This paper describes slushflows near Atigun Pass, Alaska, which were well documented in a study for the Alyeska Pipeline Service Company (APSC) in 1982. The information has been privately held and is now being released for research purposes. Moreover, state-of-the-art modeling techniques are introduced and applied to the described slushflows, considering both depth-averaged and depth-resolved (three-dimensional) numerical methods with viscoplastic and elasto-viscoplastic rheological models. The observations and modeling approaches presented in this study provide insights that can improve the understanding and assessment of slushflows and their dynamics.</div></div>","PeriodicalId":10522,"journal":{"name":"Cold Regions Science and Technology","volume":"245 ","pages":"Article 104812"},"PeriodicalIF":3.8,"publicationDate":"2026-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146036119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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