Search Results (875)

The preservation of cultural heritage presents persistent challenges due to the heterogeneity of methodologies, data structures, and information requirements involved in heritage projects. While conventional Building Information Modeling (BIM) workflows commonly rely on the Level of Development (LOD), heritage contexts require flexible and requirement-driven approaches to manage both geometric and semantic information according to stakeholder needs. To address these challenges, this study adopts a design-oriented approach that investigates the integration of the Level of Information Need (LOIN) within an OpenBIM-based Historic Building Information Modeling (HBIM) framework. The proposed methodology combines a systematic literature review with a practical case study to develop and implement an interoperable workflow articulating HBIM, Level of Information Need (LOIN), Industry Foundation Classes (IFC), and Information Delivery Specification (IDS). Within this framework, LOIN governs the relevance and granularity of information, while IFC and IDS ensure interoperability, data exchange, and conformity checking. The methodology is applied to a Moroccan heritage case study focusing on the documentation and management of building pathologies, including cracks, humidity, capillary rise, and material degradation. The results demonstrate that the proposed approach overcomes the limitations of LOD by enabling requirement-driven information management, thereby improving pathology documentation and supporting informed decision-making for cultural heritage conservation. Full article

Corrosion of reinforcing steel is a key cause of deterioration in reinforced concrete (RC) structures exposed to coastal environments with chloride presence. The loss of reinforcing steel cross-sectional area, cracking of the concrete cover, and reduction in confinement progressively decrease both strength and ductility of structural elements. This study provides a reproducible, open-access dataset, compiling input parameters and numerical results of the cyclic behaviour of isolated RC columns and RC frames, specifically addressing their nonlinear cyclic response under moderate corrosion (η < 25%), as well as in the non-corroded (baseline) conditions, generated through conventional nonlinear modelling. In terms of modelling, the methodology applies fibre-section modelling for columns and concentrated plastic hinges for beams. Furthermore, the corrosion effects are incorporated by reducing the steel area and ultimate strain, while also accounting for the decrease in compressive strength of the cracked concrete cover. Therefore, the cyclic response is represented by a Pivot-type hysteretic model. It is worth noting that the dataset provides model input information, such as material stress–strain relationships and backbone curves reflecting corrosion-induced deterioration. It also includes structural outputs, such as force–displacement relationships, and envelopes of quasi-static hysteretic cycles for the analyzed columns and frames. Overall, the dataset facilitates the calibration and validation of numerical models for RC structures affected by corrosion. In conclusion, the contribution enhances the reliability of computational simulations and supports the development of predictive tools for structural performance under degradation scenarios. Full article

Sustainable vegetable production requires strategies that optimize yield while conserving water and minimizing resource inputs. This study, conducted at the Horticulture Research Farm near Absaraka, ND, evaluated the performance of several paste-type tomato (Solanum lycopersicum) cultivars under different irrigation strategies in high-tunnel and open-field production systems to identify cultivar and irrigation combinations that support sustainable production. Across seasons and production environments, cultivar significantly influenced marketable yield, fruit number, fruit size, and the proportion of unmarketable fruit, whereas irrigation treatments had limited effects on total and marketable yield. High-yielding cultivars such as ‘Granadero’, ‘Pozzano’, ‘Cauralina’, and ‘Amish Paste’ consistently produced greater marketable yields in both production systems, although ‘Cauralina’ also exhibited higher levels of fruit cracking and unmarketable yield. In high-tunnel production, deficit irrigation strategies based on soil moisture thresholds (10% and 30% management allowable depletion) maintained yields comparable to time-based irrigation, suggesting that water-efficient irrigation scheduling can sustain productivity. In the open field, cultivar responses varied under different irrigation regimes, highlighting the importance of selecting cultivars adapted to water-limited conditions. Fruit quality attributes, including soluble solids content and titratable acidity, were primarily influenced by cultivar rather than irrigation. Overall, the findings demonstrate that cultivar selection combined with water-efficient irrigation management can maintain tomato productivity while reducing water use and production losses. These results support the development of more sustainable tomato production systems that enhance resource-use efficiency, reduce waste from unmarketable fruit, and maintain fruit quality across diverse production environments. Full article

Despite extensive advancements in Engineered Cementitious Composites (ECCs), mixture design remains predominantly empirical, due to the absence of a quantitative parameter directly linking fiber–matrix interfacial mechanics to strain-hardening performance. This study identifies fiber–matrix interfacial friction as a quantifiable parameter and establishes a micromechanics-guided interfacial regulation framework to enhance the toughness of ECC by regulating fiber failure modes. First, a critical fiber–matrix interfacial frictional stress, (τ₀)_crit, corresponding to the transition between fiber pull-out and fracture, was theoretically derived based on energy dissipation maximization during crack propagation. A back-calculation approach was further developed to determine interfacial frictional stress (τ₀) directly from tensile stress–crack opening responses under single-crack tension, eliminating reliance on single-fiber pull-out testing. Then, τ₀ was tuned toward (τ₀)_crit through interfacial regulation using fly ash. Experimental results demonstrate that the toughness of ECC is maximized when τ₀ approaches (τ₀)_crit, confirming the validity of the proposed toughness enhancement mechanism. The study establishes an explicit mechanistic linkage between interfacial micromechanics and macroscopic strain-hardening performance, providing a predictive and quantitative design pathway that transcends empirical mixture adjustment. Full article

As natural and anthropogenic hazards intensify, improving the performance of reinforced-concrete (RC) infrastructure within a resilience-oriented assessment framework while limiting environmental burdens has become an important challenge for sustainable construction. In this context, this study proposes an OpenBIM-based digital-twin methodology to compare two equivalent RC structural scenarios: a conventional solution and an alternative incorporating unprocessed waste sheep wool fibres into cementitious materials. Using an IFC-based model of a high-rise building, the workflow enables automated extraction of structural quantities and a consistent building-scale assessment of material use, environmental impacts, and circularity indicators. Laboratory evidence from the literature is translated into element-level performance criteria through a dual-factor selection strategy based on key structural properties and secondary indicators related to cracking and post-cracking behaviour. The results show that the wool-fibre alternative enables the incorporation of a relevant amount of waste wool into the structure while causing only negligible increases in embodied energy and carbon emissions relative to the conventional RC scenario. The selected formulations also maintain or improve the governing mechanical and serviceability-related factors, indicating potential benefits in crack control, toughness, and repairability. Overall, this methodology provides a reproducible pathway for linking laboratory-scale material innovation with building-scale digital assessment, supporting more sustainable and performance-aware decision-making in RC construction. Full article

Open-pit mining operations rely heavily on visual inspection to identify indicators of slope instability such as surface cracks. Early identification of these geotechnical hazards enables timely safety interventions to protect both workers and assets in the event of slope failures or landslides. While computer vision (CV) approaches offer a promising avenue for autonomous crack detection, their effectiveness remains constrained by the scarcity of labelled geotechnical datasets. Deep learning (DL)-based models, in particular, require large amounts of representative training data to generalize to unseen conditions; however, collecting such data from operational mine sites is limited by safety, cost, and data confidentiality constraints. To address this challenge, this study proposes a novel hybrid game engine–generative artificial intelligence (AI) framework for large-scale dataset generation without requiring real-world training data. Leveraging a parameterized virtual environment developed in Unreal Engine 5 (UE5), the framework generates realistic images of open-pit surface cracks and enhances their fidelity and diversity using StyleGAN2-ADA. The synthesized datasets were used to train the YOLOv11 real-time object detection model and evaluated on a held-out real-world dataset of open-pit slope imagery to assess the effectiveness of the proposed framework in improving model generalizability under extreme data scarcity. Experimental results demonstrated that models trained using the proposed framework consistently outperformed the UE5 baseline, with average precision (AP) at intersection over union (IoU) thresholds of 0.5 and [0.5:0.95] increasing from 0.792 to 0.922 (+16.4%) and 0.536 to 0.722 (+34.7%), respectively, across the best-performing configurations. These findings demonstrate the effectiveness of hybrid generative AI frameworks in mitigating data scarcity in CV applications and supporting the development of scalable automated slope monitoring systems for improved worker safety and operational efficiency in open-pit mining. Full article

Earth-based additive manufacturing (AM) combines design flexibility and automation of 3D printing (3DP) with low embodied energy, local availability, and circular economy compatibility of earthen materials. However, the sustainability performance of earth-based AM remains contested, particularly when chemical stabilisers and fibres are introduced to address mechanical and durability limitations. This review examines earth-based AM, focusing on fibre reinforcement, mechanical performance, and environmental impacts. Following PRISMA guidelines, peer-reviewed open-access articles (2015–2025) were identified and analysed using the Web of Science database. The review synthesises findings on material compositions, processing strategies, mechanical behaviour, and life cycle assessments of 3D-printed earthen materials, with particular attention to natural fibres. Results show that fibre reinforcement primarily contributes to crack control, post-peak behaviour, dimensional stability, and printability rather than universal strength enhancement. Compressive strengths range from 1–3 MPa for non-stabilised printed earth to 6–25 MPa for stabilised systems, confirming stabilisation as critical for structural scalability. Environmental assessments reveal that despite low-carbon feedstocks, 3D-printed earth can exhibit higher carbon emissions than conventional earthen techniques due to binder use and energy-intensive printing unless material savings and circular strategies are optimised. Key gaps include heterogeneous testing protocols, limited structural-scale validation, and insufficient techno-economic integration. Full article

Mold infection by Aspergillus and Penicillium spp. in Sithong sweet tamarind (Tamarindus indica L.) during commercial postharvest storage poses quality and food safety risks. However, the current visual detection method, which involves randomly cracking open the pods, is both destructive and laborious. The integration of near-infrared spectroscopy (NIRS) with artificial neural networks (ANN) enables rapid and non-destructive detection while capturing non-linear biochemical–spectral relationships, offering advantages over conventional destructive and linear analytical methods. It was tested as a mold classifier in sweet tamarind pods preserved in commercial ambient conditions (25 °C, 60% relative humidity) for five weeks. Six hundred pods were examined weekly using interactance spectroscopy (800–2500 nm) with six measurement points per pod and four spectral preprocessing methods. The ANN outperformed partial least squares discriminant analysis (PLS-DA) across all storage weeks, peaking at Week 2 with standard normal variate (SNV) preprocessing (prediction accuracy: 85.00%; sensitivity: 0.84; specificity: 0.86; F1-score: 0.85). Advanced tissue degeneration caused spectral heterogeneity, which decreased performance at Week 4 (prediction accuracy: 71.82–76.36%). Principal component loadings identified mold-induced water redistribution and carbohydrate depletion wavelengths at 938, 975–980, and 1035 nm. Week-adaptive calibration is essential for implementation because of the large difference between week-specific model accuracy (up to 85%) and overall storage model accuracy (63.53%). These findings provide a mechanistic underpinning for smaller wavelength-selective sensors and temporally adaptive mold screening systems in commercial tamarind storage. Full article

This study investigates the fracture initiation and propagation mechanisms of continuously reinforced concrete–asphalt (CRC+AC) composite pavements under the synergistic effects of diurnal temperature fluctuations and non-uniform tire loading. A three-dimensional (3D) thermo-mechanical coupled finite element (FE) model was developed, with its underlying mechanical framework validated through laboratory-scale model tests conducted at 20 °C. The experimental results, involving strain monitoring at varying depths, demonstrated a high degree of consistency with numerical predictions in terms of spatial strain distribution, thereby ensuring the model’s reliability in capturing interlayer load-transfer efficiency. Building upon this validated mechanical foundation, numerical simulations were extended to analyze the low-temperature fracture response. The numerical results indicate that the maximum longitudinal and transverse tensile stresses in the asphalt layer are concentrated at the pavement surface, whereas the maximum shear stress occurs at a depth of 2–3 cm near the leading and trailing edges of the wheel load. Under low-temperature gradients, the Mode I stress intensity factor (K_I) at the crack tip exhibits a distinct diurnal opening–closing–reopening pattern, peaking at approximately 220 kPa·m^1/2 during the early morning hours (05:00–06:00). Furthermore, numerical simulations reveal the significant sensitivity of shear-sliding to axle loads; specifically, the peak Mode II stress intensity factor (K_II) increases monotonically from 190 to 230 kPa·m^1/2 as the axle load rises from 10 t to 16 t. Under non-uniform contact pressure, longitudinal cracking is primarily characterized by a mixed Mode I and Mode II mechanism driven by coupled tensile and shear stresses, whereas transverse cracking is dominated by Mode II shear failure. These findings suggest that implementing targeted traffic restrictions for overloaded vehicles during identified high-risk time windows can significantly enhance the structural durability and service life of composite pavements in cold regions. Full article

Fluid-driven fracture processes are central to the development of subsurface energy systems such as geothermal and hydrocarbon reservoirs. Although phase-field formulations have become a widely used tool for describing fracture initiation and growth, the diffuse representation of cracks makes it difficult to resolve flow behavior accurately inside discrete fracture networks (DFNs) and to represent hydro-mechanical coupling in a sharp-interface sense. This study develops a hybrid-dimensional iterative framework for lubrication-flow simulation in deformable fractured geomaterials. By leveraging phase-field point clouds together with non-conforming discretization schemes for both the solid matrix and fracture domains, the proposed framework enables the dynamic reconstruction of evolving fracture networks. The theoretical formulation and numerical implementation of the coupling strategy are presented in detail. Hydraulic benchmark examples verify the performance of the fluid flow solver under various physical conditions. The classical Sneddon problem and Khristianovic–Geertsma–de Klerk (KGD) model are employed to validate the solid deformation solver, confirming accurate predictions of crack opening displacement and mesh independence in fracture width calculation. Additional simulations with complex pre-existing fracture patterns further demonstrate the applicability of the framework to coupled hydro-mechanical analysis in fractured media. Full article

With the opening of complex service routes, the importance of the service performance of brake pads under long slope braking conditions is increasing. It is necessary to analyze the slope braking adaptability of current brake pad products. This work takes the copper-based powder metallurgy brake pads of a certain in-service high-speed train as the research object and conducts friction and wear behavior tests of the brake pads based on a full-scale brake test bench. Through microscopic observation and damage analysis, the differences in friction and wear behavior of the brake pads under stop braking and slope braking conditions are compared, revealing the wear mechanism and damage evolution characteristics of the brake pads. The results show that under the impact of high speed, high braking force, and severe thermal load in the stop braking conditions, the uneven wear of brake pads is high, and the eccentric wear of friction blocks is affected by both the friction radius and friction direction. The friction surface has a large number and size of damages, and the stability of the friction interface is poor. The brake pad exhibits a composite wear mechanism dominated by abrasive wear and brittle fracture induced exfoliation. In the slope braking condition, under the action of low speed, low braking force, and long-term stable thermal load, the uneven wear of the brake pads is relatively low, the surface damage size is small, and the friction block only has eccentric wear along the friction direction. The brake pad mainly initiates cracks along the interface of the components, which propagate parallel to the friction surface, exhibiting a progressive delamination and flaking exfoliation mechanism with a low wear rate. Although the friction interface of the brake pad is relatively stable under slope braking conditions, the cumulative delamination wear of the brake pads under long-term braking action needs further attention. Full article

This study presents an assessment of forced vibration responses of cracked beam-type aerospace structures using VIbration BehaviouR ANalysis Tool (VIBRANT), a high-fidelity time-marching analysis platform. The methodology captures contact-induced nonlinearities arising when crack surfaces intermittently open and close during vibration, producing time-varying stiffness and damping. Frequency-domain behaviour is extracted from time-domain simulations of beams representing aero-engine blades and wing structures under various crack configurations. Results reveal that a crack-induced nonlinearity is strongly configuration-dependent: only specific combinations of crack depth, position relative to the moment distribution, and excitation amplitude produce detectable nonlinear signatures, whilst other configurations—including cracks representing significant structural compromise—exhibit quasi-linear response that would evade conventional vibration-based detection. The deeper crack configuration activates breathing behaviour at higher forcing levels, leading to rightward resonance frequency shifts and amplitude reductions due to impact and frictional contact damping, whereas the baseline and repositioned crack configurations maintain a quasi-linear response across all forcing levels examined. This configuration-dependent character of the breathing crack nonlinearity—and in particular the conditions under which nonlinear signatures are absent despite active damage—represents a critical finding for structural health monitoring and maintenance planning in aerospace applications. Full article

Hydrogen embrittlement is known to adversely affect the mechanical properties of low-carbon steels used for pipelines and pressure vessels, leading to accelerated crack growth and lowered fracture toughness. To overcome the limitations of surface-based analysis, this study employs X-ray micro-computed tomography (µ-CT) to provide a comprehensive 3D evaluation of the crack evolution. This approach is used to assess hydrogen-assisted crack growth in P355NH compact tension samples from previous fracture mechanical tests and enables a precise quantification of the internal crack path and the crack tip opening angle (CTOA) across the entire specimen thickness as well as the local damage morphology. By integrating these spatial parameters, a deeper understanding of the impact of hydrogen on local fracture mechanisms is achieved, revealing insights that have remained hidden in previous two-dimensional microscopy observations. For instance, µ-CT results clearly demonstrate that the hydrogen-assisted crack propagation is associated with increased void formation and secondary cracking in vicinity of the crack tip. However, it is proposed that the results are superimposed with continuous hydrogen desorption, which implies a need for in situ charging during mechanical loading and an analysis of the hydrogen concentration profile. Both will be the scope of further studies. Full article

Fracture toughness is a very important mechanical attribute that affects the strength of rail steel used in high-speed rail systems. This study tests the measurement uncertainty that comes with measuring the plane strain fracture toughness (K_IC) of R350HT rail steel. We used the Single-Edge Bend (SEB) specimen to do fracture toughness testing. We used the Guide to Expressing Measurement Uncertainty (GUM)-based method to figure out how much uncertainty came from measuring the load, the crack opening displacement (COD), and the specimen’s shape and figuring out the crack length. At a 95% confidence level (k = 2), the combined standard uncertainty was found to be 0.881 MPa·m^1/2, which is the same as an expanded uncertainty of 1.761 MPa·m^1/2. The measured fracture toughness value of 40.59 ± 1.76 MPa·m^1/2 meets the standards for rail steels. The results show how important it is to include measurement uncertainty in conformity assessment methods for safety-critical railway components. They also provide an experimentally proven framework for accurate mechanical property evaluation. Full article

Corn starch (CS)/poly (butylene adipate-co-terephthalate) (PBAT) blends were prepared by extrusion and injection molding processes. The CS content in the blends changed between 0 and 50 wt.% in 10 wt.% steps. Melt flow rates, mechanical properties, thermal stability, melting and crystallization behavior, as well as hydrophilicity of the blends were investigated. Based on these, the degradation properties of PBAT and the blend containing 50 wt.% CS (50%CS/PBAT) in water and open-air storage were comparatively studied via visual appearance observation, Shore hardness testing, and water absorption measurement. The results showed that the melt flow rates and the mechanical properties of the blends, including the tensile strength, tensile modulus, impact strength, and elongation at break, initially increased before decreasing as CS content in the blends increased, while the flexural strength and flexural modulus of the samples increased monotonously. The sample would become more thermal unstable when more CS was used. Besides these, the crystallinity and water contact angle became smaller. Immersion in water would blacken the visual appearances of PBAT and 50%CS/PBAT samples, but cracks could be found much more obviously in the blend than in neat PBAT; both the hardness and the mass of PBAT rose slightly while those of 50%CS/PBAT dropped significantly. An open-air storage would also blacken the visual appearances of PBAT and 50%CS/PBAT, and the hardness of the two samples would be decreased to almost the same extent. The results showed that the incorporation of CS in PBAT had much greater effects on the flow ability, mechanical properties, thermal stability, melt and crystallization behavior, as well as hydrophilicity of the blends. Immersion in water or being placed in air could accelerate the degradation of 50%CS/PBAT much more seriously than PBAT. Compared with PBAT, 50%CS/PBAT was of much lower cost and easier to be degraded, especially in water; it should be an ideal degradable blend for applications in packaging, agricultural mulch, and some other areas. Full article