Sweden’s extensive network of over 4,000 railway bridges calls for innovative, data-driven strategies to ensure structural reliability, extend service life, and to meet evolving sustainability goals and increasing load demands. As part of a larger initiative, this study focuses on a comparative evaluation of three widely used life cycle calculation tools. We examined Trafikverket’s Klimatkalkyl (employed by Swedish government agencies), OneClick LCA (prominent in industrial practice), and ORIS Material Intelligence (a commonly applied approach). This comparative study is based on a unique full-scale replica of a 1970s reinforced concrete trough railway bridge, housed indoors at Luleå University of Technology in Luleå and equipped with over 100 sensors (including Fiber Optic Sensing (FOS) and Strain Gauges). This testbed generates up to 2 TB of data daily, serving as a robust foundation for structural health monitoring, life cycle and life costs assessments. By analysing the same bridge through various tools, we highlight how their differing algorithms may lead to variations in environmental impact estimates, resource optimization strategies as well as life cycle cost projections in the future. This study aims to determine the most suitable tool for guiding sustainable infrastructure decisions. It also aims to illustrate how these insights feed into the overarching initiative of a holistic bridge management platform, intended to provide a comprehensive, real-time overview of bridge conditions at both the asset and network levels. At last, this work supports Sweden’s broader transition to circular, climate-resilient infrastructure, equipping decision-makers with the comparative knowledge needed to optimize bridge longevity, minimize environmental impacts.

Water retention capacity of zeolite allows strategic water release to mitigate shrinkage effects of cement-based materials. This study employed molecular dynamics simulations to explore the asymmetric wetting behaviors of corrosive salt solutions within pore models combined with different ZSM-5 facets and C-S-H surfaces. Results demonstrate that compared to the consistent hydrophilic C-S-H surface, variations of the zeolite facets influence the water retention capacity of zeolites and lead to differing degrees of solution transport unevenness. At discontinuous cavities, the solution fills first and the contact angle shows a horizontal trend or hysteresis behavior. Hydroxyl groups at the cavity distal ends then attract water molecules to form a hydrophilic contact angle. The favorable void exposure enables the highest water storage capacity of zeolite (0 0 1) facet, followed by (1 0 0) and (0 1 0) facets. While the continuous (0 1 0) facet shows superior hydrophilicity for rapid solution transport. Transport behaviors are similar for pure water and NaCl, but ion clusters in Na2SO4 solution reduce transmission rates and hinder water entry into zeolite channels. These findings provide an atomic-level perspective of zeolite applications for enhancing water storage and durability in cement-based materials.

Alkali-activated materials (AAMs) exhibit low carbon emissions, environmental sustainability, and excellent performance, making them promising for sustainable development. However, their properties are primarily governed by the gel structures—sodium aluminosilicate hydrate (N-A-S-H) and calcium aluminosilicate hydrate (C-A-S-H)—and the interfacial transition zone (ITZ) formed during their transformation. In this study, reactive molecular dynamics (MD) simulations were employed to investigate the effects of temperature and humid/erosive environments on the interfacial reconstruction, revealing the formation and evolution of chemical bonds within the ITZ. The results show that the ITZ thickness increases significantly from 7.6 Å to 16.3 Å with increasing temperature. Meanwhile, Ca ions in C-A-S-H dominate bonding due to their higher valence, promoting coordination with surface oxygen atoms in N-A-S-H. Under environmental exposure, hydrogen bonding becomes the dominant interfacial interaction, and the ITZ expands from initial 8 Å to 17.4 Å after water infiltration and to 21.7 Å in NaCl solution. In NaCl solution, Na ions preferentially accumulate on the surface of the N-A-S-H gel, whereas Cl ions are primarily distributed within the pore channels. This ion penetration further accelerates interfacial deterioration and degrades the mechanical properties, with the Young’s modulus decreasing by 26.98% and the ultimate tensile strength by 16.13%. Elucidating atomic-scale interfacial reaction mechanisms via MD simulations provides valuable insights for the rational design and optimization of AAMs.

Geopolymers are promising sustainable materials for structural and geotechnical applications. However, their pronounced multiscale structural heterogeneity complicates the direct linkage between atomistic mechanisms and macroscopic mechanical performance. In this study, a hierarchical multiscale molecular dynamics (MD) —peridynamics (PD) framework is developed, in which PD serves as an intermediate bridge connecting MD simulations with experimental observations of geopolymer mechanics. This framework enables the transfer of material characteristics across scales and allows the effects of Si/Al ratio and porosity on mechanical behavior to be systematically evaluated. The simulations indicate that Young’s modulus decreases with increasing Si/Al ratio, while the maximum tensile strength is achieved at a Si/Al ratio of 2. Under zero-porosity conditions, the PD-predicted Young’s modulus closely matches the MD results, whereas in the presence of porosity, the PD predictions fall within the experimental range. These findings demonstrate that PD effectively extends the applicability of MD simulations to the mesoscale and provides a practical multiscale framework for the design and optimization of geopolymers.

Load tests are one of the most powerful tools for bridge assessment, revealing true system behavior, calibrating models, and building public confidence. However, temperature and thermal gradient effects, especially in sub-arctic climates, pose a significant challenge, as they can dominate the structural response and make performance assessments harder to interpret. This paper addresses this challenge by analyzing a unique dataset from a prestressed concrete bridge, comprising five years of multi-sensor SHM data and a final, controlled load test before its demolition. We present a climate-aware, hybrid-modelling workflow that separates temperature-driven responses from vehicle-induced effects. By systematically normalizing the predicted responses to a defined reference climate, the methodology demonstrates tangible benefits, as reflected in discernible variations in owner-facing performance metrics. Furthermore, an “error vs https://www.w3.org/1998/Math/MathML" display="inline">ΔT ” analysis is proposed to highlight the relationship between thermal gradients and prediction accuracy, offering additional insights into the robustness and applicability of the climate-conditioned model. 

Understanding how organic inhibitors regulate oxide surfaces in acidic environments requires connecting adsorption strength with dynamic interfacial transport. Here, reactive force field molecular dynamics (ReaxFF MD) simulations were used to compare salicylic acid (SA) and cinnamaldehyde (CA) on Cr2O3 passive films in sulfuric acid solution. Adsorption configurations, interfacial water structure, ion distribution, hydrogen bonding, and proton-accessibility descriptors were analyzed at the atomic scale. Both inhibitors chemisorb strongly on Cr2O3, but their protective functions differ substantially. SA anchors through localized carboxyl and hydroxyl coordination, forming a discontinuous and relatively hydrophilic adsorption layer that permits water accumulation and proton access. By contrast, CA adopts a surface-parallel configuration stabilized by aldehyde coordination and extended π-metal interactions, producing a compact hydrophobic layer that depletes interfacial water and suppresses proton approach to surface oxygen sites. The results show that corrosion inhibition is governed not only by adsorption energy but also by molecular planarity, lateral packing, interfacial water exclusion, and suppression of proton transport. This work provides an atomistic design framework for organic inhibitors targeting stainless-steel passive films in acidic sulfate environments.

Railway noise barriers are an essential piece of infrastructure for reducing noise propagation. However, these barriers experience aerodynamic loads generated by high-speed trains, leading to dynamic effects that may compromise their fatigue capacity. The most common structural design for railway noise barriers consists of vertical configurations of posts and panels. However, there have been few dynamic analyses of steel post/wood panel noise barriers under train-induced aerodynamic loads. This study used dynamic finite element analysis to assess the dynamic behavior of such noise barriers. Analysis of a 40-m-long noise barrier model and a triangular simplified load model, the latter of which effectively represented the detailed aerodynamic load, were first used to establish the model and input of the moving load during dynamic simulation. Then, the effects of different parameters on the dynamic response of the noise barrier were evaluated, including the damping ratio, the profile of the steel post, the span length of the panel, the barrier height, and the train speed. Gray relational analysis indicated that barrier height exhibited the highest correlations with the dynamic responses, followed by train speed, post profile, span length, and damping ratio. A reduction in the natural frequency and an increase in the train speed result in a higher peak response and more pronounced fluctuations between the nose and tail waves. The dynamic amplification factor (DAF) was found to be related to both the natural frequency and train speed. A model was proposed showing that the DAF significantly increases as the square of the natural frequency decreases and the cube of the train speed rises.

The pursuit of carbon neutrality has intensified interest in carbon utilization. Understanding the diffusion and adsorption mechanisms of CO2 and H2O within calcium silicate hydrate (C–S–H) is critical for assessing the carbonation durability of cement-based materials. In this study we used molecular dynamics to explore the transport and adsorption of H2O, CO2 fluid, and their mixtures in C–S–H nanopores. Water content was varied based on the fixed CO2 amount (0%, 25%, 50%, 75%, and 100%) to assess its impact on CO2 dynamics behaviors. The results indicate that CO2 exhibited greater mobility and density change compared to H2O which moved slowly. The presence of water suppresses initial CO2 diffusivity, an effect that intensified with increasing water content. CO2 initially undergoes dynamic adsorption–desorption cycles on the C–S–H surface but is progressively displaced as infiltrating water molecules establish a stable hydration layer that blocks further CO2 access to adsorption sites. The cohesive nature of the aqueous solution promotes multilayer-to-monolayer adsorption, whereas CO2 remains more evenly distributed yet exhibits a markedly lower adsorption capacity than water molecules. This study offers an atomic-level perspective of early dynamic behaviors of CO2 and H2O within C–S–H pores and thereby provides insights into the subsequent carbonation phenomena in cementitious systems.

Coral aggregate concrete is a potential alternative to natural aggregate concrete for coastal building structures. Given that coastal structures often experience triaxial stress states, conventional empirical models rely on extensive experimental data, and their limited physical interpretability can hinder reliable prediction of coral aggregate concrete behavior when data are sparse. This study proposes a physics-informed neural networks framework embedding the unified five-parameter or modified unified twin-shear strength theory failure criteria, modified Guo’s piecewise constitutive model, and geometric boundary constraints to enable parameter inversion and stress–strain reconstruction. Conventional triaxial compression tests were conducted on coral aggregate concrete across varying strength grades, coral aggregate replacement rates, and confining pressure ratios. Experimental results show that higher confinement shifts failure from axial splitting to ductile oblique shear, increases peak stress, and alleviates post peak softening. Meanwhile, increased coral aggregate replacement rates intensify structural crushing. The developed framework accurately predicts multiaxial peak stress and reconstructs full stress-strain curves from sparse data. Validations demonstrate excellent predictive accuracy, achieving determination coefficients exceeding 0.97 and mean absolute percentage errors below 5 %. The framework maintains robust accuracy under 20 % data noise. This study provides an efficient and interpretable computational approach for characterizing the nonlinear mechanics of emerging engineering materials.