Plenary lectures
Abstract of the presentation: An integrated piezoelectric (PZT) and digital image correlation (DIC) monitoring method is developed to conduct real-time damage monitoring and assessment of flexural cracks in polyvinyl alcohol engineered cementitious composite (PVA-ECC) beams. Four-point bending tests are conducted in real-time monitoring conditions, where the DIC system captures the crack propagation while the PZT sensors simultaneously track the crack evolution. Both the wavelet packet decomposition and reconstruction are applied to the signals, and the differences in the amplitude and energy are analyzed. The experimental process is numerically simulated, from which the experimental data is correlated and compared. The combined experimental and numerical study indicates that the PZT-DIC system effectively monitors the development of cracks in the tensile region of PVA-ECC beams in three crack development stages (i.e., from microcrack initiation, to dominant macrocrack formation, and finally to failure). As cracks develop, the amplitude and energy of the received signals decrease significantly. During the three observed stages of crack development, the energy at 20°C received by the specimens decreases by 22.6%, 68.1%, and 59.3%, respectively; while at 150°C, the energy decreases by 33.1%, 63.9%, and 55.8%, respectively; and finally, as the temperature keeps increasing, the number of microcracks decrease, and the flexural resistance capacity deteriorates, leading to brittle fracture. At 150°C, the health index during the microcrack development and main crack formation stages decrease by 13.56% and 24.14%, respectively, when compared to 20°C. At 250°C, the PVA-ECC beams experience the instant brittle fracture. The proposed method effectively identifies the flexural crack damage and quantifies its severity in PVA-ECC beams, demonstrating its potential for widespread application in health monitoring of cement-based composite structures.
Abstract of the presentation: This presentation deals with the application of advanced machine learning techniques in construction and focuses on their role in predicting material strength, wall load-bearing capacity and seismic vulnerability of buildings. Based on the interdisciplinary project "Intelligent Methods for Structures, Elements and Materials", details on the selection and implementation of different ML models — such as regression algorithms, ensemble methods and neural networks — tailored to specific engineering challenges will be explained. The presentation will give an insight into the rationale behind the chosen approaches, the integration of expertise and the practical results achieved, as well as possible limitations and how intelligent systems can improve prediction accuracy and support evidence-based design and safet
Abstract of the presentation: Integrating Artificial Intelligence (AI) into critical infrastructures—such as power grids, water systems, transportation networks, and healthcare facilities—marks a significant advancement in the management and resilience of essential services. AI technologies, in conjunction with smart materials, offer powerful tools for real-time data analysis, predictive maintenance, automated decision-making, and rapid anomaly detection, enabling infrastructure operators to optimize performance, reduce operational costs, and respond swiftly to disruptions. For example, AI-driven predictive analytics can anticipate equipment failures before they occur, while intelligent control systems can dynamically adjust resource allocation in response to fluctuating demand or emerging threats. Despite these benefits, the integration of AI also introduces new complexities and risks. Increased reliance on automated systems can create vulnerabilities to cyberattacks, data breaches, and unintended system behaviors. Furthermore, ethical considerations—such as transparency, accountability, and fairness—must be addressed to ensure public trust and regulatory compliance. The successful integration of AI in critical infrastructures requires a multidisciplinary approach that combines technical innovation with robust governance, continuous risk assessment, and stakeholder collaboration. By carefully balancing innovation with security and ethical oversight, AI can significantly enhance the reliability, efficiency, and adaptability of critical infrastructures, ultimately supporting the safety and well-being of society as a whole.
Abstract of the presentation: The long-term durability of reinforced concrete structures in cold climates is severely compromised by freeze-thaw (F-T) damage. Near-surface mounted (NSM) fiber-reinforced polymer (FRP) bars have been increasingly employed for structural rehabilitation due to their excellent corrosion resistance and mechanical performance. However, the bond performance of the NSM FRP systems under F-T conditions remains a critical concern. This study experimentally investigates the influence of the F-T cycle number, FRP bar type (GFRP and BFRP), and bond length on the bond behavior of NSM FRP bars-concrete interfaces. A total of 18 pull-out specimens were exposed to 0, 50, and 100 F-T cycles. The bond strength, bond stress-slip response, and failure modes were evaluated. Two dominant failure mechanisms were identified: splitting failure in unexposed specimens and pull-out failure after F-T exposure. Results revealed that bond strength decreased with the increase of the bond length, and initially increased but later decreased with the number of F-T cycles. Microstructural analysis showed that epoxy resin softening and interfacial cracking due to F-T cycling led to the degradation at the epoxy resin-concrete interface. The weakening of van der Waals forces and disruption of hydrogen bonds between epoxy and SiO2 were identified as key degradation mechanisms. A modified bond-slip constitutive model was proposed, capturing the interface behavior under different failure modes with high accuracy. The findings support more reliable durability design and assessment of NSM FRP systems in freeze-thaw-prone environments.
Abstract of the presentation: To enhance the ductility of high-strength concrete-filled high-strength square steel tubes (HCFHSSTs), the imbedding of high-strength spirals (HSS) within HCFHSSTs is proposed. This study aims to evaluate the performance of high-strength spiral-confined high-strength concrete-filled high-strength square steel tube (HSS-CHCFHSST) columns under axial compression. A series of tests were conducted on axially compressed HSS-CHCFHSST columns. The strengths of concrete was 90 MPa. The highest yield strength of steel tubes and spirals were 818 MPa and 1561MPa, respectively. The experimental results demonstrated that the HSS deforms and ultimately fails during testing following the column of HSS-CHCFHSST with a slenderness ratio of less than 27.71 reaches its peak load. The working mechanism and parameters of the HSS-CHCFHSST columns were analyzed numerically. The results indicate that after the peak load, the HSS effectively confined the core concrete, increasing its stress. The HSS-CHCFHSST column exhibited a higher axial compressive capacity and ductility than an equivalent HCFHSST column using a thick tube. Considering the significant contribution of the core concrete confined by HSS to the load-bearing capacity of HSS-CHCFHSST columns under axial compressive conditions, a comprehensive equation was formulated for the precise calculation of their axial compression capacity. The strength matching guideline of HSS in HSS-CHCFHSST columns was established. Furthermore, taking steel tube and concrete as a composite material, the calculation equations were proposed for use in the composite stress-strain curve for HSS-CHCFHSST columns under axial compression based on the experimental and numerical analysis results.
Abstract of the presentation: This presentation investigates how collaborative, technology enhanced and data-driven research, based on a comprehensive approach, can contribute to earth-quake preparedness and response.
The first part discusses the use of ICT tools and smartphone applications which deliver real-time data, to support efficient earthquake response. These tools en-hance situational awareness by delivering reliable earthquake damage assessment (buildings, landslides and liquefactions included), thus leading to efficient plan-ning of both preventive and response actions.
The second part emphasizes the vital role of public engagement-particularly in schools-in enhancing resilience. It demonstrates how scientific knowledge can be converted into actions which can promote a culture of preparedness among citi-zens while at the same time, improving their response capacity.
The final section discusses the deployment of low-cost monitoring devices in ur-ban areas, which provide continuous data streams related to both ground motion and building response, thus supporting a more precise, data-driven understanding of seismic risk.
The overall approach presented is based on the results of two successfully com-pleted, EU co-funded projects, the “Rapid Earthquake Danage Assessment con-sortium” (REDACt) and the “Earthquake Resilient Schools” (EReS), and offers a model for improving existing practices, placing data-driven information to sup-port competent authorities and the Public, at the core of earthquake risk mitigation actions.
Abstract of the presentation: The keynote speech discusses the main features of a novel Computerized Upper Bound Limit Analysis approach aimed at the accurate prediction of the ultimate limit state behavior of historical masonry structures exhbiting high geometric complexity. Particular attention is given to the estimation of the seismic vulnerability.
The approach bases on a full 3D discretization of the masonry structure, which allows plastic dissipation exclusively at the interface between contiguous elements. After the derivation of a standard linear programming problem to predict collapse multiplier, active failure mechanism and -from the dual problem- internal stress distribution at failure, an efficient iterative procedure is discussed to simulate the problem in case of interfaces purely frictional.
A series of paradigmatic case studies is reviewed, focusing in particular on building aggregates and churches. A final extension of the approach presented is proposed, which relies in a fast algorithm equipped with a surrogate optimization kernel, to automatically provide that disposition of tie rods that maximizes the load carrying capacity.
as a sustainable resource and comparative analysis among alternative solutions
Abstract of the presentation: The research focused on the experimentation of components made with natural fibres, with the aim of assessing their mechanical performance and potential fields of application. In this context, the study analyzed the physical and mechanical properties of a lime-based mortar reinforced with randomly distributed hemp fibres within the mixture, as well as an FRCM system (Fabric-Reinforced Cementitious Matrix) composed of a lime mortar combined with a hemp fiber mesh. For the fiber reinforced plaster, initial tests included fiber water absorption and workability (flow) of the fresh mixture. Subsequently, mechanical characterization was carried out through flexural and compressive strength tests on specimens. As for the meshes, tensile tests were performed on hemp yarns, followed by compressive strength tests on masonry panels (50x50 cm), both with and without FRCM reinforcement, to evaluate the static benefits provided by the proposed retrofit system. The experimental results highlighted the excellent performance of plasters reinforced with hemp fibres and meshes, confirming their effectiveness as a strengthening system for existing structures.
Other natural fibres, such as coconut and jute, also proved to be valid alternatives to hemp to produce eco-sustainable plasters and blocks. For this reason, a research activity was undertaken on mortar samples reinforced with coconut, jute, and hemp fibers, aiming to evaluate their physical and mechanical properties. Once the optimal mix design was defined for each mixture, experimental laboratory tests were conducted to characterize them. The comparison of the results allowed for the identification of the best-performing material and, consequently, the selection of the most suitable type of natural fibres for the development of the fibre-reinforced mortars investigated in this study.
Abstract of the presentation: Recent developments in microbial applications have demonstrated the efficacy of using microorganisms for bioremediation and wastewater treatment, offering environmentally sustainable and economically viable alternatives to conventional methods. Microorganisms possess the intrinsic ability to metabolize and transform pollutants into non-toxic compounds, enabling low-energy, low-cost processes with minimal waste generation. Anaerobic bacteria, capable of respiration without oxygen by utilizing electron acceptors such as nitrates, sulfates, and metals, play a critical role in degrading nitrogen and sulfur-based contaminants in oxygen-depleted environments. These microbial processes are foundational to Microbial Fuel Cells (MFCs), which convert organic matter into electrical energy through bacteria-assisted electron transfer.
The integration of MFC technology into the building industry holds transformative potential for redefining sustainable urban infrastructure. By harnessing the dual capability of electrogenic bacteria to treat wastewater and generate electricity, MFCs offer a promising pathway toward decentralized energy systems and enhanced environmental performance in buildings. The significant reductions in chemical oxygen demand and measurable power output demonstrated in controlled bioreactor settings underscore their feasibility for real-world application. As buildings evolve into more self-sufficient entities, embedding MFC systems could turn wastewater streams into sources of clean energy, minimizing ecological impact while contributing to the circular economy. With further optimization, this bioelectrochemical innovation may become a cornerstone of green architecture, merging biology and technology to power a smarter, cleaner future.
In this study, heterotrophic microorganisms were employed in MFC bioreactors to investigate biomass generation and electron donation under controlled conditions. Using naturally occurring mediators, the reactors achieved direct electron transfer to the anode. Experimental setups included continuous load, step polarization, and series connection tests to determine optimum electrical output. A reactor with a 50 cc volume and a 5:1 anode-to-cathode ratio produced up to 13 mW (0.3V/44.4mA), supported by a 287.5 cm² unfolded anode surface. Additionally, the bioreactors demonstrated a significant reduction in chemical oxygen demand (COD-Cr) in accordance with ISO 6060, achieving a 96% decrease after 192 hours compared to a 76% reduction in the control sample. These results highlight the dual potential of MFCs for effective wastewater treatment and sustainable energy recovery.
Abstract of the presentation: Multifractal scaling has been identified over the last decades in various natural and/or engineered processes, such as rainfall fields (themselves a tracer in atmospheric turbulence, whose energy dissipation is characterized by scale invariance), or financial markets. Multiplicative cascades have been involved in multifractal modeling both in their canonical form, as generic constructors of multifractal fields, or in microcanonical form, as disaggregation tools capable of preserving the downscaling properties of a measured large-scale field. While more sophisticated forms of cascades have been proposed and used, particularly in higher dimensions, where scale continuity becomes essential, even the simplest one-dimensional discrete-scale canonical cascades are difficult to parameterize. Said difficulty arises from the necessity of obtaining compatible scaling properties between the breakdown coefficients of the measured process, and those of the asymptotic measure generated by the canonical cascade kernel (i.e., its microcanonical reconstruction). The presentation is concerned with some recent results about the functional relationships between the probability distributions involved in the above problem, embedded in a more comprehensive view of multifractal cascades and their applications.