Mitsuyoshi Akiyama 1, Dan M. Frangopol 2, Hiroshi Matsuzaki 3

1. Waseda University, Shinjuku-ku, TOKYO, Japan

2. Lehigh University, Bethlehem, PA, USA

3. Tokyo Institute of Technology, Tokyo, Japan

Despite extensive research into the life-cycle performance assessment of structures and infrastructure systems, numerous unresolved issues still demand further investigation. One of the primary challenges is the inherent uncertainty associated with the physical parameters involved in these assessments. These parameters can vary significantly and are often unpredictable, making it essential to predict long-term structural performance using probabilistic concepts and methodologies. This probabilistic approach provides a more robust and reliable forecast of how structures will behave over time. To effectively address these challenges, it is crucial to establish and continuously refine life-cycle reliability assessment methodologies.

 The purpose of this Mini-Symposium is to gather and discuss cutting-edge research papers that focus on advanced computational and experimental techniques for evaluating the life-cycle performance of aging structures, particularly those exposed to aggressive environments. In such settings, structures are subjected to a variety of environmental and mechanical stressors that accelerate deterioration, thus shortening their service life and increasing the overall life-cycle cost associated with maintenance and repair.
This Mini-Symposium will cover the latest theoretical and practical advancements in the assessment and prediction of future performance for existing structures. It will delve into various strategies for maintaining and strengthening these structures, aiming to ensure their safety, mitigate risks, and enhance their resilience. Key topics include the development of long-term deterioration models for structural performance, cutting-edge techniques for visual inspection and structural health monitoring, and life-cycle analysis based on reliability approaches. Furthermore, it will address the methods for updating the reliability of existing structures by integrating inspection results and will explore the application of machine learning techniques in life-cycle performance assessment. Research involving both laboratory and field experiments on aging structures will also be a significant focus.

Fabio Biondini 1, Dan M. Frangopol 2
1. Department of Civil and Environmental Engineering, Politecnico di Milano, Milan, Italy

2. Department of Civil and Environmental Engineering, ATLSS Center, Lehigh University, Bethlehem, PA, United States

Structural systems, due to their inherent vulnerability, are at risk from aging, fatigue and deterioration processes due to aggressive chemical attacks and other physical damage mechanisms. The detrimental effects of these phenomena can lead over time to unsatisfactory structural performance under service loadings or accidental actions and extreme events, such as natural hazards and man-made disasters. The exposure to combined effects of discrete and continuous damaging events pose a major challenge to the field of structural engineering. The classical time-invariant structural design criteria and methodologies need to be revised to account for a proper modeling of the structural system over its entire life-cycle by taking into account the effects of deterioration processes, time-variant loadings, and maintenance and repair interventions under uncertainty. Despite these needs and recent research advances, life-cycle concepts are not yet explicitly addressed in structural design codes. Moreover, the level of structural performance is generally specified with reference to structural safety and reliability. However, when aging and deterioration are considered, the evaluation of the system performance should account for additional probabilistic indicators aimed to provide a comprehensive description of the life-cycle structural resources, such us redundancy, robustness and resilience. Based on these considerations and following the successful events organized at IALCCE2016, IALCCE2018, IALCCE 2020, and IALCCE 2023, the purpose of this IALCCE2025 Mini-Symposium is to present principles, concepts, methods, and strategies for measuring and evaluating the life-cycle risk, reliability, redundancy, robustness and resilience of deteriorating structural systems under multiple hazards, with emphasis on the interaction between seismic and environmental hazards.

Fangjie Chen 1, Yew-Chin Koay2, Estela Oliari Garcez 1, Sachinthani Ayesha Karunarathna 1, Rackel San Nicolas 1
1. Arup, Hawthorn, VIC, Australia

2. Major Road Projects Victoria, Melbourne

The mini symposium on "Fundamental, Innovation, and Implementation of Low Carbon Concrete Materials on Infrastructure Projects" aims to address critical advancements and applications in sustainable construction practices. With the increasing global emphasis on reducing carbon footprints, the construction industry is at the forefront of adopting innovative materials and methods to achieve sustainability goals.

This symposium brings together leading experts, policymakers, engineers and industry stakeholders to discuss the latest research and development in low carbon concrete materials, focusing on their practical implementation in infrastructure projects. The symposium covers a range of topics including the investigation of geopolymer concrete, development of calcined clay concrete, and applications of recycled concrete aggregates. Additionally, the symposium explores the utilization of recycled glass fines, advancements in ultra-high performance concrete, the use of GFRP fibre reinforced polymer bars, and the incorporation of recycled crumb rubber into concrete mixes.

The symposium highlights the importance of these materials in reducing environmental impact and enhancing the durability and performance of concrete structures. Attendees will gain insights into current research directions and innovative methods being developed to address sustainability challenges in the construction sector.

Hongyuan GUO 1, Ruiwei Feng 1, You Dong 1, Dan M. Frangopol 2

1. The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, China

2. Fazlur R. Khan Endowed Chair of Structural Engineering and Architecture, Department of Civil and Environmental Engineering, ATLSS Engineering Research Center, Lehigh University, Bethlehem, Pennsylvania, United States

In an era marked by escalating environmental uncertainties and rapid urbanization, the resilience of civil infrastructure against multiple hazards has become a paramount concern. The increasing frequency and intensity of extreme weather events, such as hurricanes, floods, and wildfires, alongside aging infrastructure and urban densification, highlight the urgent need for a robust framework to assess and enhance infrastructure resilience throughout its life-cycle.

The interdependencies of modern infrastructure systems further compound the potential for cascading failures, where the impact of one event can trigger a series of disruptions across various sectors, including energy, transportation, and water supply. This domino effect can lead to severe economic losses and prolonged recovery periods, underscoring the importance of proactive resilience planning and adaptive response strategies.

Recognizing the complexity of these challenges, this special session is dedicated to exploring the necessity of life-cycle resilience assessment and developing strategies based on resilience to fortify civil infrastructure. Topics for potential contributions include but are not limited to

(1) Methods for integrating multiple hazards across the life-cycle of civil infrastructure;

(2) Life-cycle structural reliability analysis method for civil infrastructure under multiple hazards;

(3) Life-cycle resilience assessment of civil infrastructure under multiple hazards;

(4) Recovery planning and emergency response strategies for civil infrastructure facing multiple hazards; and

(5) Data-driven and AI-informed life-cycle analysis methods for civil infrastructure.

We invite researchers, practitioners, and policymakers to contribute their insights and innovations to this mini-symposium. Together, we aim to advance the understanding and implementation of comprehensive resilience strategies that ensure the sustainability and safety of civil infrastructure in the face of multiple hazards.

Lei Hou 1

1. RMIT University, Melbourne, VIC, Australia

The field of civil engineering is undergoing a transformation through the integration of advanced digital tools. This mini symposium on "Lifecycle Digital Tools for Civil Engineering" will address critical challenges and opportunities presented by these innovations, focusing on their application throughout the lifecycle of civil engineering projects. The importance of these tools lies in their potential to enhance efficiency, accuracy, and sustainability in significant applications such as infrastructure development, urban planning, and environmental management. Current research directions are exploring various methods to solve complex civil engineering problems. Digital twins are being developed for real-time performance monitoring and maintenance. Building Information Modeling (BIM), along with Augmented Reality (AR) and Virtual Reality (VR), is revolutionising design and construction processes. Artificial intelligence (AI) and soft-computing techniques are being employed for predictive analytics and optimisation. Machine learning is enhancing Life Cycle Assessment (LCA) for sustainability. Advances in sensor technology, Internet of Things (IoT), big data, and cloud computing are transforming data collection, connectivity, and analysis. Additionally, robotic and drone-based techniques are offering innovative solutions for inspection and surveying. The scope of this mini symposium includes, and is not limited to: Digital Twins for Performance Monitoring: Enhancing infrastructure performance and maintenance. BIM, AR/VR for Design and Construction: Improving design accuracy and construction efficiency. AI and Soft-Computing Methods: Solutions for predictive analytics and complex problem-solving. Machine Learning in LCA: Impact on sustainable practices. Sensor Technology and IoT: Real-time data collection and connectivity. Big Data and Cloud Computing: Managing and processing engineering data. Robotic and Aviation-Based Techniques: Solutions for inspection, surveying, and construction.

Speakers: TBD

Masaru Kitahara 1, Takeshi Kitahara 2, Hong Hao 3, Jun Li 3, Mark G Stewart 4

1. The University of Tokyo, Tokyo, Japan

2. Kanto Gakuin University, Kanagawa, Japan

3. Curtin University, Perth, Australia

4. University of Newcastle, Sydney, Australia

Structural health monitoring (SHM) aims at condition assessment and service life monitoring of structural systems, often based on the availability of system vibration data. Model updating has been developed as a key technique for SHM, where parameters of the numerical model are updated to tune its prediction close to the measurements. However, uncertainties are inevitable in both the measuring and modeling processes, which leads to the necessity of non-deterministic approaches to quantifying the uncertainties. This Mini-Symposium is dedicated to gathering experts from both academia and industries to showcase the latest development on the uncertainty treatment for model updating and SHM and their practical applications in Civil Engineering. A non-exhaustive list includes stochastic/interval model updating, Online model updating, Data-driven SHM, and Bayesian approaches.

Jie J Li 1, Rajeev R Roychand 1, Mohammad M Saberian 1, Shannon S Kilmartin-Lynch 2

1. RMIT University, Melbourne, VIC, Australia

2. Civil Enngineering, Monash University, Melbourne, Vic, Australia

Description:

Climate change due to greenhouse gas emissions poses a major global issue. The cement industry significantly contributes to this problem, responsible for around 5–7% of worldwide greenhouse gas emissions. Additionally, the ongoing extraction of vital natural resources by the cement, concrete, and pavement sectors to satisfy growing infrastructure demands presents a long-term sustainability challenge. Consequently, efforts to reduce the carbon footprints of the construction industry and push it towards a carbon-neutral and sustainable sector have been intensely pursued. This transformation process now actively includes conserving natural resources and recycling waste materials, aligning with the global goal of a closed-loop circular economy. Numerous innovations have emerged in creating eco-friendly cement concrete, enhancing sustainability and supporting the circular economy. Furthermore, advancements in pavement technology and road geotechnics are increasingly embracing sustainable methods and materials.

This mini-symposium is designed to unite specialists in innovative, low-carbon concrete and pavement, fostering discussions on the latest advancements in these fields. The objective is to create a platform that addresses a broad spectrum of topics, emphasising the distinct aspects that enhance our comprehension of sustainable construction and pavement materials. Attendees will explore current research and practical applications in infrastructure projects.

Topics for potential contributions include, but are not limited to:

• Carbon sequestration from various waste streams in cement concrete

• Development of zero cement composites

• Development of low carbon footprint cement composites and pavements

• Recycling of various waste materials for the replacement of cement and/or aggregates

• Physicochemical and microstructure studies of the blended cement/concrete composites

• Pavement geotechnics using sustainable materials

  Speakers:
  Dr. Rajeev Roychand (RMIT)
  Dr. Mohammad Saberian (RMIT)
  A/Prof. Shannon Kilmartin-Lynch (Monash University)
  Macedon Ranges Shire Council (TBD)
  Hiway Stabilizer  (TBD)
  Hanson  (TBD)
  Bild Group (TBD)

Airong Chen 1, Mitsuyoshi Akiyama 2, Fabio Biondini 3, Yong Yuan 1, Xin Ruan 1, Rujin Ma 1

1. College of Civil Engineering, Tongji Univerisity, Shanghai, China

2. Department of Civil and Environmental Engineering, Waseda University, Tokyo, Japan

3. Department of Civil and Environmental Engineering, Politecnico di Milano, Milan, Italy

The increasing frequency and severity of natural hazards pose significant threats to infrastructure systems worldwide. This Mini Symposium aims to address the critical need for multi-hazard resilience assessment of infrastructure, encompassing a range of natural and anthropogenic threats such as earthquakes, floods, hurricanes, and terrorist attacks. The symposium will bring together leading researchers and practitioners to discuss the latest methodologies and technologies in assessing and enhancing the resilience of infrastructure systems.

Current research in this field is focused on developing comprehensive assessment frameworks that integrate various hazard models, performance metrics, and resilience indicators. Methods such as probabilistic risk assessment, simulation modeling, and resilience optimization are being advanced to better predict and mitigate the impacts of multi-hazard events. The symposium will cover these cutting-edge approaches, highlighting case studies and practical applications.

Túlio Bittencourt 1, Rui Calçada 2, Diogo Ribeiro 3, Hermes Carvalho 4, Marcos Massao 1, Pedro Montenegro 2

1. Universidade de São Paulo, São Paulo

2. Faculdade de Engenharia da Universidade do Porto, Porto

3. Instituto Superior de Engenharia do Porto, Porto

4. Universidade Federal de Minas Gerais, Belo Horizonte

In recent years, important investments have been made in the construction of new railway lines, as well as in the rehabilitation and upgrading of existing lines. Many of these lines include a significant number of bridges, viaducts and other critical infrastructures whose operational and safety conditions have to be preserved by the infrastructure managers during life cycle. Recent scientific and technological advancements have enabled a more efficient structural condition assessment of railway bridges, mainly through the implementation of intelligent strategies for the inspection, monitoring, maintenance and risk management. Within the framework outlined above, this special session aims to bring together from across the world the latest research studies, findings and achievements with regard to the smart condition assessment of railway bridges. Theoretical, experimental and computational investigations (or a combination of these) are welcome. Expected papers will cover various topics related to: structural integrity; structural condition assessment; digital twins; model calibration and validation; structural health monitoring; new sensors and technologies (photogrammetry, laser scanning, drones, wireless); computer vision techniques; automated damage identification; remote inspection strategies; BrIM (Bridge Information Modelling); Big Data; Artificial Intelligence (supervised and unsupervised learning); augmented reality; virtual reality; disaster risk reduction; emergency management and intelligent asset management.

Dilan Robert 1, Jayantha Kodikara 2, Pat Rajeev 3

1. RMIT University, Melbourne, DEFAULT, Australia

2. Civil Engineering, Monash University, Melbourne, VIC, Australia

3. Civil Engineering, Swinburne University, Melbourne, VIC, Australia

Overview: This mini-symposium will explore the crucial role pipelines play in transporting energy, water and providing essential services, focusing on the challenges faced by both onshore and offshore pipelines. Topics will include failure mechanisms, condition assessment, and renewal strategies for water, stormwater, sewer, gas, and petroleum pipelines. Special attention will be given to the effects of ground conditions, climate change, and emerging technologies such as smart sensing and digital twins. 

Objective: This mini-symposium aims to bring together industry professionals, researchers, and policymakers to discuss the latest advancements and strategies in pipeline engineering and asset management. By addressing critical issues such as failure prediction, corrosion protection, and the impact of climate change, the symposium seeks to enhance pipeline infrastructure's safety, efficiency, and sustainability. Participants will have the opportunity to share knowledge, exchange ideas, and collaborate on developing practical solutions to the challenges faced by the pipeline industry.

Key topics

(a) Water pipelines

• Failure mechanisms of buried water pipelines and failure hot spots

• Proximal and intrusive condition assessment of buried water pipelines

• Failure prediction and prevention

• Renewal strategies of deteriorated water pipelines, including trenchless lining

• Design of new pipelines

(c) Stormwater and sewer pipelines

• Condition assessment

• Failure prediction and prevention

• Renewal

(b) Gas and petroleum pipelines

• Critical pipelines affected by problematic ground, e.g., reactive soil, fault lines and mine subsidence

• Reticulation pipelines

• Cathodic and corrosion protection

(c) Offshore pipelines

• Upheaval buckling of offshore pipelines

• Pipelines vulnerable for underwater hazards

• On-bottom stability of offshore pipelines

(d) Other 

• Contributions to net zero initiatives via pipeline engineering and asset management

• Hydrogen transmission via pipelines

• Engineering backfill for corrosion protection and reducing environmental footprint

• Smart sensing for pipelines

• Climate change effects on buried pipelines

• Digital twin development for buried pipelines

Alfred A Strauss 1, Dan M Frangopol 2

1. BOKU University, Vienna, AUSTRIA, Austria

2. Lehigh University, Bethlehem

Civil engineers are facing the challenge of managing aging infrastructure under tight budgetary as well as operational constraints. A qualified assessment of new and existing structures is essential to optimally allocate the limited resources available for asset management. A profound knowledge on the condition of a structure is the necessary basis for deciding on actions which can be taken to guarantee a safe use and operation of the structure within the planned technical lifetime or for prolonging the technical lifetime of the structure. There have been significant advances in the development of technologies for Structural Health Monitoring (SHM), however such technologies are at present only limited integrated in the assessment of existing structures.

This Mini-Symposium (MS) addresses the problem of decision making in the management of deteriorating infrastructure. Such decision making should consider all relevant uncertainties, and exploiting the potential for profound knowledge on the structural condition as provided by SHM technologies. In particular this MS will focus on (1) developing a framework that allows assessing existing structures by means of a decision making tool that takes into account monitoring information and (2) determining and optimizing the value of monitoring over the lifetime of structures.

Guowen Yao 1, 2, Yang Tang 1, 2, Xuanbo He 1, 2, Liuyang Ma 1, 2, Guiping Zeng 1, 2

1. School of Civil Engineering, Chongqing Jiaotong University, Chongqing, China

2. State Key Laboratory of Mountain Bridge and Tunnel Engineering, Chongqing Jiaotong University, Chongqing, China

In order to alleviate the corrosion problem of bridge cable wires, based on the mechanism of impressed current cathodic protection (ICCP) of the three-electrode system, the ICCP corrosion test of galvanized steel wire was carried out by applying load at the end of the steel wire using a constant load device to study the protection effect of different protection potentials on steel wire under different constant load levels. According to the steel wire corrosion process macro and microscopic damage patterns, corrosion rate, open circuit potential, the constitutive relationship and other mechanical property indexes, to explore the ICCP protection voltage threshold and bridge cable wires ICCP mechanism. The study shows that: ICCP can effectively delay the corrosion rate of steel wire, and effectively enhance the ductility of steel wire, the corrosion effect of steel wire within the threshold is positively correlated with the output of the protection potential; when the protection potential is less than -1.3V, the steel wire brittle fracture indicator is obvious, and the steel wire may be overprotection of precipitation of hydrogen reaction and affect its mechanical properties; with the development of the corrosion process, the steel wire surface zinc plating depletion, the role of ICCP gradually sufficient, and thus produce a stable corrosion protection effect on the iron substrate.

Zora Vrcelj 1, Malindu Sandanayake 1, Achini Peiris 2, Ronja Kraus 3, Yanni Bouras 1, Le Li 1, Ehsan Yaghoubi 1, Robert Haigh 4, Wasantha Pallewela Liyanage 1

1. Victoria University, Footscray Park, VIC, Australia

2. Digital Enablement, AURECON, Melbourne, VIC, Australia

3. Sustainability, Eastern Freeway Burke to Tram Alliance (EBTA), Melbou, VIC, Australia

4. RMIT, Melbourne, VIC, Australia

The proposed mini symposium addresses the critical need for sustainable development practices in the construction and infrastructure sectors. As global demands for eco-friendly and carbon-neutral infrastructures rise, the symposium highlights innovative research and industry applications that aim to meet these sustainability goals effectively.

The symposium will bring together a diverse group of academics and industry professionals who are at the forefront of developing and implementing sustainable technologies in infrastructure projects. The presentations will cover a wide array of topics, including the use of Life Cycle Assessment (LCA) for Environmental Product Declarations (EPD), the integration of digital technologies for material selection, and the application of machine learning in predicting material properties. These areas represent cutting-edge directions in research that not only enhance the sustainability of infrastructure projects but also offer solutions to critical environmental challenges faced by the industry.

Moreover, the symposium will feature innovative research on utilising waste materials such as recycled cardboard and textile fibers in concrete, exploring their potential to transform waste into valuable construction materials. This not only addresses issues of waste management but also contributes to the circular economy in construction practices.

The scope of this mini symposium encompasses both theoretical advancements and practical applications, making it a vital platform for researchers, practitioners, and policymakers. It aims to foster discussions that bridge gaps between research and real-world applications, highlighting collaborative efforts and encouraging the integration of new technologies and methodologies into mainstream construction practices.

This event promises to be a convergence of ideas and expertise, making it an essential venue for those working directly in the field of sustainable infrastructure as well as those engaged in related areas, seeking to apply sustainable principles to broader contexts.

Xiang-Lin Gu 1, Juanhong Liu 2, Shangtong Yang 3, 4

1. Tongji University, Shanghai, China

2. University of Science and Technology Beijing, Beijing, China

3. China University of Mining and Technology, Xuzhou, JIANGSU, China

4. University of Strathclyde, Glasgow, UK

During the whole life service, engineering structures are subjected to long-term environmental deterioration which can sacrifice their performance or even cause premature failures. Research studies in traditional civil engineering structures and infrastructures with regards to their whole life performance have been well documented. However, in the context of low-carbon transition, new structural forms and materials have recently been developed and attracted considerable research interests, while their long-term performance is still a challenging topic. These may include, for example, underground renewable energy storage structures which utilizes new lining composite structures and materials to sustain the large internal pressure, temperature cycles, structural integrity, etc. Meanwhile, big data and machine learning have evidently showed great potential in leveraging the performance evaluation and prediction for engineering structures. New methods in analyzing big data and developing machine learning algorithms in whole life performance of engineering materials and structures will become important.

In this mini symposium, we aim to bring together world-wide expertise and interest in performance evolution and enhancement of engineering materials and structures. In particular, we would like to include research in discovering new environmental deterioration mechanisms in light of low-carbon materials and engineering applications, new analysis methods involving big data and machine learning, new performance enhancement means and techniques for prolonged service life, etc.

Topics for potential contributions include, but are not limited to:

• Deterioration mechanisms of low-carbon construction materials

• Performance degradation of low-carbon engineering structures

• Performance evaluation in emerging fields such as underground energy storage structures, e.g., cavern hydrogen storage, shaft thermal energy storage, etc.

• Advanced methods for prediction of whole service life

• Risk analysis, reliability and stochastic process modelling

• Big data and machine-learning in evaluation of structural performance

• New materials and techniques for prolonged life service of structures

Xuan-Yi Zhang 1, Chao-Huang Cai 1, Yan-Gang Zhao 1, Zhao-Hui Lu 1

1. Beijing University of Technology, Beijing, China

Description:

Ensuring the long-term safety and reliability of structural systems is a critical research challenge on a global scale. Throughout their life cycles, structural systems are vulnerable to deterioration and hazardous loads, both of which introduce significant uncertainties that can be time-dependent and space-dependent. The combination of these factors results in a range of time-space-dependent failure modes. Therefore, employing reliable analysis methods is essential for a comprehensive evaluation of the service performance of structural systems.

This Mini-symposium aims to bring together experts in the field of structural reliability to explore the latest developments in this domain. The goal is to create a forum that covers a diverse array of topics while highlighting the unique characteristics that shape our understanding of structural reliability.

Topics for potential contributions include, but are not limited to:

• Structural reliability and risk assessment

• Time-variant reliability analysis methods

• Dynamic reliability analysis methods

• Advanced stochastic models for structural reliability

• Reliability-based maintenance strategies

• Reliability-based design and optimization methodologies

xiaoping zhong 1, xinyao huang 1

1. Yangzhou University, Yangzhou, JIANGSU, China

 In chloride corrosion environment, steel bar corrosion is one of the main reasons for the degradation of concrete structure durability. In order to improve the long-term performance of concrete structures and extend the service life of concrete structures, the mechanical properties and long-term corrosion behavior of new stainless steel clad rebar were studied using uniaxial tension and electrochemical test methods. The results show that the stainless steel clad rebar combines the excellent properties of stainless steel and carbon steel. The yield strength is improved to varying degrees compared with HRB400E carbon steel bars and solid stainless steel bars. The ductility is smaller than that of solid stainless steel but close to that of HRB400 steel bars. The elastic modulus is slightly lower than that of HRB400E steel bars. Under the action of chloride salt corrosion, stainless steel clad rebar is mainly pitted, and the corrosion products contain more α-FeOOH which makes the rust layer denser than that of HRB400E steel bars. Solid stainless steel bars have the best corrosion resistance, HRB400E has the worst corrosion resistance. And the corrosion resistance of stainless steel clad rebars is between solid stainless steel bars and HRB400E. The yield strength, ultimate strength and elongation after fracture of the corroded stainless steel clad rebars all decrease to varying degrees with the increase of the corrosion rate. Based on experimental research and theoretical analysis, the stress-strain constitutive model of stainless steel clad rebars and the relationship between the strength and elongation after fracture of stainless steel clad rebars after corrosion and the corrosion rate were established.

Weiliang Jin 1

1. Department of Civil Engineering, Zhejiang University, Hangzhou, Zhejiang, China

This Paper aims to explore the degradation of long-term performance and optimized management of concrete structures throughout their entire life cycle under complex environmental conditions and various load effects. Utilizing interdisciplinary knowledge from civil engineering structures, materials, electrochemistry, acoustics, and magnetism, the project has established a time-varying damage constitutive model for concrete materials and components under multiple working conditions. It has also developed a system for analyzing time-varying damage of concrete and steel materials under complex corrosion, fatigue, and creep effects. The limit state equations of concrete component performance based on damage indicators, elucidated the long-term reliability and variable sensitivity of structures are reconstructed based on rust expansion crack width, deflection, and steel fatigue fracture. The methods for analyzing the normal service life of components and predicting the fatigue life of concrete structures are established under single and multiple factor effects. The outcomes of this paper deepen the understanding of the long-term performance of reinforced concrete structures and provide theoretical support and practical methods for ensuring the structures' safety, reliability, and economic continuous operation, thereby holding significant theoretical and practical application value.

The content of this paper includes the following as: (1) Complex model and effect of long-term performance of concrete structures; (2)  Damage index and analysis model of long-term performance of concrete structures; (3) Limit state and life prediction of long-term performance of concrete structures.

The conclusions in this paper are (1) the nonlinear creep mechanism of concrete has been revealed at macro, meso, and micro scales; (2) a time-varying creep damage constitutive model, and a time-varying damage analysis system for both concrete and steel materials under corrosion, fatigue and creep is established; (3) the performance limit state equation of concrete members is reconstructed based on damage index. 

Chunhua Lu 1, Hui Li 1, Siqi Yuan 1

1. Jiangsu University, Jingkou District, JIANGSU PROVINCE, China

To investigate the effect of repeated loads on the flexural load carrying capacity of marine concrete beams suffering from chloride attack, a total of 10 marine concrete beams and 36 concrete cubes were designed for flexural performance test and compressive strength test, respectively. Three damage mechanisms, including repeated loads with a stress level of 0.4, chloride solution dry-wet cycles and coupling action of repeated loading history and chloride solution dry-wet cycles, were applied for concrete beams and cubes. Test results show that the effect of repeated loads on the degradation of compressive strength of concrete is significantly higher than that on the flexural properties of concrete beams, and the corresponding degradation ratio between them is maintained at about 1.5. The effect of chloride solution dry-wet cycles on concrete compressive strength is 1.8 times higher than that on the flexural load capacity of test beams. Combined with the test data proposed in this paper and some existing studies, the coupling impacts of repeated loading and compressive strength loss on the flexural load bearing capacity of marine concrete beams are discussed by comparing with the formula calculations based on Chinese, American and European concrete codes. The analysis shows that the compressive strength loss rate can effectively reflect the degradation of flexural load bearing capacity of marine concrete beams and that there is an exponential relationship between them.

Pinghua Zhu 1, Xintong Chen 1

1. Changzhou university, Changzhou, China

With the concrete buildings reaching the service life. It is an inevitable trend to reuse waste concrete with high efficiency, environmental protection, and low cost. The requirements for recycled aggregate concrete (RAC) are more stringent in continuous harsh environments such as freezing and thawing. Based on the actual requirements of areas severely damaged by freezing and thawing. The strength index (compressive strength and splitting tensile strength) and frost resistance index (mass loss rate and relative dynamic elastic modulus) of RAC with different strength grades (C40, C50, and C60) in the freeze-thaw environment were studied, and the performance index (apparent density, water absorption, crushing value, aggregate output rate, and adhesive mortar content) of the second-generation recycled coarse aggregate (2nd-RCA) were explored. SEM observed the microscopic mechanism of 2nd-RCAs. It was found that the compressive strength of three groups of RACs can be higher than the design value, and C50 was the largest higher than the design value, reaching 8.2%. When the number of freeze-thaw cycles reached 400, the mass loss rate of C60 was the smallest, only 1.12%. With the increase of freeze-thaw cycles, the relative dynamic elastic modulus (RDEM) of RAC with three different strengths decreased, and the RDEM of C60 was the lowest before 100 freeze-thaw cycles. After 350 times, the RDEM of C60 was the highest. According to the performance test of 2nd-RCAs produced by C40, C50, and C60, it is concluded that all three groups of 2nd-RCAs can meet the grade III coarse aggregate standard. The aggregate yield of C50 is up to 84%. This shows that RAC can be recycled in a freeze-thaw environment. Using C40 and C50 in an environment with few freeze-thaw cycles is reasonable. When the freeze-thaw cycles are too much, it is suggested to choose C60 to meet the frost resistance requirements.

Ehsan Yaghoubi 1

1. Victoria University, Footscray, VIC, Australia

This presentation highlights three applied research projects from Victoria University, focusing on sustainable practices in the field of green Infrastructure and Transportation Geotechnics. The research aims to increase the use of recycled aggregates in pavement and geostructure construction through both experimental studies and full-scale trials with field testing and monitoring. The first two projects investigate sustainable blends of recycled materials for backfilling deep trenches, over 1.5 meters deep, in both trafficable and non-trafficable areas. Deep trenches (>1.5 m) pose safety risks, preventing engineers from entering and ensuring proper quality control, which can lead to surface settlement issues. These projects used specialized geotechnical and pavement tests, as well as innovative tests designed to mimic real-life construction and service conditions. The recycled material mixtures were also subjected to environmental testing before being used in full-scale trial sites, which were monitored for about 1.5 years. The third project focused on optimizing asphalt mix design using recycled aggregates through an extensive experimental program with specialized asphalt testing. The optimized asphalt mixture was then used to pave a 60-meter road section in Melbourne, Australia. This road section has been monitored for over 2.5 years to assess its long-term performance. Overall, these projects aim to connect transportation geotechnics theories with practical applications by promoting the use of recycled materials, thereby supporting sustainable construction practices.

Jianghong Mao1, Kun Fang1

1. Sichuan University, Sichuan / Chengdu / Wuhou District, SICHUAN PROVINCE, China

Concrete porosity, pore distribution and morphology are important characteristics of concrete pore characteristics, which have a significant impact on the macroscopic mechanical properties and durability of concrete. This study explores a method of instantaneously reducing the curing air pressure after mixing concrete to change the pore characteristics and avoid introducing variables other than voids. In this study, we observed the rising behavior of air bubbles of different sizes in low-pressure intervention cement slurries. Through the modified drag equation, the air pressure-bubble interaction is determined and expressed by the interaction coefficient Ki. Combining bubble motion theory and experimental evidence, a bubble distribution probability model based on rheological characteristics and air pressure was initially proposed. In addition, the effects of void characteristics on mechanical and durability properties were systematically studied through short-term low-pressure intervention.

Piyal Wasantha Pallewela Liyanage 1 , Sejani Mediliye Gedara 1

1. Victoria University, Melbourne, Victoria, Australia

Waffle raft foundations are popular in Australia for residential structures. These on-ground footing systems feature integrated void spaces, forming a network of internal and edge beams. Typically, expanded polystyrene (EPS) boxes, known as waffle pods, are used as void formers and serve as the formwork for the beams. EPS is a preferred choice due to its cost-effectiveness, lightweight nature, and ease of handling. However, growing environmental concerns regarding the use of EPS in residential foundations have led to the adoption of waffle pods made from more sustainable materials, such as recycled plastic (RP). Despite the increasing popularity of RP waffle pods, the environmental impacts of replacing the EPS with RP have not been comprehensively quantified. Therefore, this study performed a detailed life cycle assessment (LCA) of waffle raft foundations constructed using both EPS and RP pods, considering a cradle-to-cradle system boundary. Various factors were analyzed, including different types of superstructures, site classes, foundation areas, and locations across Australia. Embodied energy and greenhouse gas emissions were used as key attributes of the LCA. Established databases were refered to obtain typical quantities for these attributes. The results indicated areas where the use of EPS and RP can be optimized to minimize embodied energy and greenhouse gas emissions. It should be noted that the analysis used quantities for virgin plastics due to the absence of data for recycled plastics. Overall, this study underscores the importance of comprehensive environmental assessments in guiding the choice of materials for sustainable construction practices.

Le Li 1 , Yanni Bouras 1

1. College of Sport, Health and Engineering, Victoria University, Footscray, VIC, Australia

Chloride-induced corrosion is a major factor affecting the durability of reinforced concrete structures, especially those exposed to the marine environment. The concrete's chloride resistance can be improved by partially replacing the cement with silica fume. Thus, silica fume concrete has been widely used to construct coastal structures. To develop a maintenance plan for these coastal structures, the corrosion initiation time of reinforcement silica fume concrete in these coastal structures must be predicted. Also, it is vital to consider the spatial variation of concrete mix design (such as water-to-blinder ratio and silica fume content) and use time-dependent reliability theory for the corrosion initiation time prediction so that the uncertainties in chloride diffusion spatially across concrete and over time can be considered. However, limited studies consider these uncertainties. Therefore, this paper developed a platform that combines the time-dependent reliability analysis and random field theory for corrosion initiation prediction of reinforcement in silica fume concrete coastal structures subjected to chloride attack. The platform simulates the water-to-blinder ratio and silica fume content in concrete coastal structures using random field theory and critical water-to-blinder ratio and silica fume content are selected from the generated random field  Then, various chloride diffusion models are used, in which the chloride concentration at the reinforcement locations over time is modelled as a function of concrete mix design and the silica fume content. Then, time-dependent reliability theory is used to predict the probability of chloride concentration at reinforcement being larger than a threshold value, from which the corrosion initiation time of reinforcement can be predicted.

By applying developed platform to concrete coastal structure, we demonstrate its potential to improve maintenance planning. The working example reveals that neglecting spatial variation of water-to-blinder ratio and silica fume content can lead to underestimating the initiation probability of reinforcement in concrete coastal structures. 

Yanni Bouras 1 , Le Li 1

1. College of Sport, Health and Engineering, Institute of Sustainable Industries and Liveable Cities, Victoria University, Footscray, VIC, Australia

Thermal conductivity is an important material property that significantly influences the energy efficiency of buildings. Cement-based materials, such as mortar and concrete, are valued for their strong insulation properties due to their low thermal conductivity. Supplementary cementitious materials (SCMs) including fly ash and blast furnace slag are being increasingly incorporated into mortar and concrete mixes as part of efforts to reduce the embodied carbon of ordinary Portland cement. Substitution of Ordinary Portland Cement (OPC) with SCMs does however influence the physical, mechanical and durability properties of mortars and concretes. Thermal performance is also impacted by the volume and type of SCM incorporated into the mix design. Hence, careful consideration is required when assessing the thermal performance of low-carbon cement materials, particularly when incorporated into the building fabric.

This paper employs supervised machine-learning algorithms to develop models capable of accurately predicting thermal conductivity of mortar and concrete materials containing high-volumes of fly ash, blast furnace slag and silica fume. Artificial neural networks, decision-tree regression, random forest generation and Gaussian process regression were all considered. The machine-learning models were trained using a large database of over 200 points compiled from experimental results reported in the open literature. The selected input parameters included the mix design variables and the specimen curing conditions. 70% of the dataset was utilised for model training with the remaining 30% employed for model verification. The accuracy of different supervised machine-learning algorithms were compared and discussed. The results demonstrate that machine-learning models can accurately predict thermal conductivity of mortar and concrete materials. Furthermore, a Shapley additive explanation (SHaP) analysis was conducted that analysed the importance of each input variable on prediction of thermal conductivity.

Zhilu Lai 1 , Costas Papadimitriou 2 , Edwin Reynders 3 , Eleni Chatzi 4

1. The Hong Kong University of Science and Technology (HKUST), Guangzhou, China

2. University of Thessaly, Thessaly, Greece

3. KU Leuven, Leuven, Belgium

4. Department of Civil, Environmental and Geomatic Engineering, ETH Zurich, Zurich, ZH, Switzerland

A main goal of vibration-based structural health monitoring and damage identification is to assess structural condition via vibration signatures. In the case of large-scale civil structures, response (output-only) data are typically available, due to difficulties associated with forced excitation of large structures. In order to translate such data, which is often indirect observations of structural condition into interpretable condition/performance indicators, model inference is typically attempted using purely data-driven (black-box), physics-based, or hybrid (grey) models.

This mini-symposium welcomes novel contributions to vibration-based structural health monitoring, damage identification and remaining useful life estimation, using black-box as well as grey and physics-based models. Relevant topics include linear and nonlinear system identification, virtual sensing, parameter, state and input estimation, model discoverer and updating, optimal experiment design, as well as exploration of novel sensing techniques. Contributions related to real-world applications and open datasets are particularly welcome.