Search Results (1,449)

Research on industrialised building (IB) adoption has extensively documented technical, organisational and market barriers but has paid less attention to how responsibility for addressing them is organised. The purpose of this study is to examine how responsibility, trust and actor-positioned risk are constructed in Australian practitioner accounts of IB adoption. A critical discourse analysis of interviews with 23 practitioners provides the primary empirical evidence. A secondary corpus of English-language YouTube comments provides a bounded contrast with public discourse. Responsibility-void discourse was most evident around shared functions including training, certification, inspection, industry coordination and design-to-delivery integration. Trust helped interpret why some firms sought greater control over functions they considered insufficiently assured externally, while risk differentiated the delivery, compliance, capital and purchase-related forms of exposure described across the two corpora. The analysis also identified distinct information conditions, including knowledge-infrastructure absence and bounded cases of strategic opacity and interoperability failure. The illustrative public corpus foregrounded purchase conditions, tenure and category credibility, whereas practitioner accounts focused on institutional delivery and coordination. The study develops a framework for responsibility in IB adoption that distinguishes fragmented responsibility, responsibility shifting and responsibility voids. It conceptualises ownership as accountable coordination of work distributed across actors, reframing persistent adoption barriers as problems of institutional organisation, coordination and follow-through. Full article

In this study, the hydrogen embrittlement (HE) susceptibility and hydrogen-induced cracking behavior of X70 pipeline steel were investigated in CH₄–H₂ mixed-gas environments containing 5–20% H₂ at a total pressure of 7 MPa. Slow strain rate tensile tests, thermal desorption spectroscopy, fractography, and electron backscatter diffraction (EBSD) were employed to correlate hydrogen uptake, mechanical degradation, fracture morphology, and crack evolution. The results showed that increasing the hydrogen fraction progressively deteriorated the mechanical performance of X70 pipeline steel, as evidenced by reductions in tensile strength and elongation. This degradation was accompanied by a fracture-mode transition from micro-void coalescence to quasi-cleavage fracture. More importantly, EBSD analysis revealed a hydrogen-content-dependent change in the role of the heterogeneous microstructure. At relatively low hydrogen fractions, fine-grained regions and microstructural heterogeneity acted as effective barriers to hydrogen-induced crack propagation. However, at higher hydrogen fractions, this intrinsic crack-arresting capability was substantially weakened. Newly formed cracks were observed to initiate ahead of pre-existing cracks and propagate preferentially along grain boundaries, with limited local plastic deformation. These findings demonstrate that the increased HE susceptibility of X70 pipeline steel under high-H₂ mixed-gas conditions is associated with the progressive loss of the crack-arresting resistance provided by its heterogeneous microstructure. Full article

This study investigates the influence of controlled fiber orientation on the mechanical and microstructural properties of cellulose excelsior fiber cementitious composites with an excelsior content of 75% by volume. Two different sets of composites were fabricated. In one set, no effort was made to orient the fibers, while in the other set fibers were preferentially aligned through manual placement and compressive consolidation. The mechanical performance, including elastic modulus and flexural strength, was evaluated. The internal structure, specifically porosity and 3D fiber orientation, was quantified using X-ray Computed Tomography (XCT) and subsequent 3D image analysis. The results demonstrate that the composites with aligned fibers exhibited a 20% higher bulk density and a significantly lower porosity (5.1%) compared to the non-aligned composites (9.0%), representing a 43% reduction in void volume. Further image analysis showed distinct differences in fiber orientation relative to the axis of the specimen. These different distributions led to a 120% increase in elastic modulus and a 58% increase in flexural strength. These results demonstrate how, within limits, the mechanical properties of the composite system can be controlled to meet application demands. Full article

High-speed railway track–bridge systems (HSRTBSs) in near-fault high-seismicity regions face combined threats from pulse-type seismic excitations, vertical earthquake components and track defects, which may trigger structural damage and deterioration of track regularity. This paper establishes refined OpenSEES coupled numerical models for a typical 32 m simply supported girder bridge equipped with CRTS II slab ballastless track, considering both conventional spherical steel bearings and friction pendulum bearings (FPBs). Nonlinear time-history analyses are performed with near-fault pulse-like and far-field non-pulse ground motions to explore the influences of peak ground acceleration (PGA), vertical-to-horizontal acceleration ratio (αVH), and CA mortar void length. The results demonstrate hierarchical controlling effects of these parameters. PGA dominates the overall seismic response; sliding layer damage follows the sensitivity sequence PGA > αVH > CA mortar void, whereas post-earthquake traffic capacity degradation obeys PGA > CA mortar void > αVH. Near-fault pulse-like ground motions produce more severe structural damage compared with far-field inputs. FPB isolation yields a maximum pier-top seismic reduction ratio of 86.73% and effectively mitigates structural deformation, but cannot eliminate track irregularity originating from CA mortar void defects. Conditional on the 0.2 g seismic level and the given structural configuration adopted in this study, αVH = 0.65 and the 1.95 m critical CA mortar void length for longitudinal track constraint failure can serve as reference values, though they are not universally applicable for all track–bridge systems. This work provides insights for seismic design, CA mortar defect remediation and post-earthquake traffic assessment of near-fault isolated HSRTBSs. Full article

Desert highways have long been subjected to aeolian sand hazards, and sand accumulation on the pavement significantly weakens the surface texture and deteriorates skid resistance, which has become one of the core contributing factors to traffic accidents on desert road sections. Current research predominantly focuses on the attenuation law of the macroscopic friction coefficient of sand-covered pavements; however, the quantitative correlation mechanism between three-dimensional micro-texture characteristics and skid resistance has not been sufficiently revealed, and there is a lack of high-precision skid resistance prediction methods under multi-condition coupling scenarios. To address the above research deficiencies, this paper takes the asphalt pavement in the Tengger Desert region as the research object. A handheld three-dimensional texture scanning system was employed to acquire the three-dimensional pavement morphology parameters under different sand coverages, and the sideway force coefficient (SFC) was synchronously measured under the corresponding conditions. Through Pearson correlation analysis and dual multiple comparison correction using the FDR-BH and Bonferroni methods, the core influencing indicators were identified. Subsequently, a skid resistance prediction model based on a BP neural network optimized by the particle swarm optimization (PSO) algorithm was constructed and horizontally compared and validated with LSTM and PSO-SVM models. The research results show the following: ① under dry conditions, the root mean square height ($S_q$), peak density ($S_{pd}$), arithmetic mean peak curvature ($S_{pc}$), valley void volume ($V_{vv}$), root mean square slope ($S_{dq}$), and developed interfacial area ratio ($S_{dr}$) are significantly linearly correlated with the SFC, among which $S_q$, $S_{pd}$, $S_{pc}$, and $V_{vv}$ are the core controlling indicators, with the absolute values of their correlation coefficients all exceeding 0.73, and ② the constructed PSO-BP prediction model achieved a coefficient of determination $R^2$ of 0.86093 on the test set, and its prediction accuracy and generalization ability are both superior to those of the LSTM and PSO-SVM models, enabling it to effectively characterize the nonlinear mapping relationship between multiple texture parameters and skid resistance. This study can provide theoretical support and a technical basis for skid resistance evaluation, sand accumulation disaster warning, and scientific maintenance decision-making for desert highways. Full article

SBS-modified asphalt is widely used in high-grade pavements for its excellent rutting and fatigue resistance; however, how its friction behavior evolves under submerged conditions with surface distress remains poorly understood. To address this gap, we developed a rubber–asphalt friction tester to characterize quasi-static rubber–asphalt friction under submerged conditions with three typical distresses: pothole, crack, and surface void. Our results show that friction increases with roughness, load, and water temperature, but degrades progressively under cyclic loading. Among the three distresses, surface void offers the most stable friction performance, whereas pothole exhibits the largest friction loss under repeated loading, identifying them as high-priority repair targets. The positive temperature–friction correlation further implies that wet-skid risks are higher at lower temperatures, providing a basis for seasonal maintenance scheduling. Three-dimensional wear analysis reveals distinct mechanisms: pothole causes localized deep-pit wear, while surface void generates uniform roughening, explaining their contrasting durability. These findings directly support distress prioritization, friction-performance evaluation, and maintenance planning for SBS-modified pavements in rainy environments. Full article

To overcome the limitations of conventional biopolymer films and reduce reliance on petroleum-based plastics, a nacre-inspired film was developed via 3D printing. During printing process, shear-induced alignment of mica flakes was achieved within a sodium alginate/xanthan gum matrix. Additionally, zinc oxide nanoparticles (ZnO NPs) were incorporated to achieve a synergistic reinforcement effect. Structural analysis revealed that the mica flakes within the film exhibited an oriented distribution, with ZnO NPs uniformly embedded in the interlayer voids, and hydrogen bonding assisted in forming a dense network of the components. Performance testing showed that the tensile strength rose from 13.8 MPa to 62.9 MPa. Improvements in water resistance and thermal stability were also observed. Furthermore, the material exhibited outstanding comprehensive protective properties, including a low water vapor permeability value of 7.587 × 10⁻¹¹ g·m/m²·Pa·s, an ultraviolet blocking rate of 99.37% at a wavelength of 280 nm, and the ability to completely inhibit target bacterial strains, while also possessing good biodegradability and recyclability. Shelf-life tests indicated that the film fabricated in this work could notably prolong the shelf life of strawberries. Biocompatibility test results indicated that the film was safe and non-toxic, and showed no significant cytotoxicity. Full article

Out-of-autoclave (OoA) manufacturing of Fiber Metal Laminates (FMLs) remains challenging because their mechanical performance and failure mechanisms are sensitive to processing-induced variations in phase distribution and interfacial bonding quality. Three FML-2/1 configurations (FML/Al-20, FML/Al-40, and FML/Al-60), where the numerical values indicate the exposure time (minutes) of 3003-H14 aluminum to NaOH alkaline etching, were physically characterized after bonding to a basalt fiber-reinforced polymer (BFRP) core to quantify constituent and void volumetric fractions. Based on previously reported differences in interlaminar strength, FML/Al-40 was selected to evaluate tensile behavior at room temperature and high temperature. The average density across all FML configurations was about 2.15 g/cm³, corresponding to a 21% reduction relative to aluminum. Compositional analysis revealed significant differences among configurations in both the complete FML and the renormalized matrix–fiber–void composition of the BFRP core, indicating that surface treatment is associated with changes in internal phase distribution beyond the metallic contribution. At room temperature, FML/Al-40 exhibited an ultimate tensile strength of 262.7 MPa. Relative to this value, tensile strength was retained at 83%, 54%, and 31% at 100, 150, and 200 °C, respectively, demonstrating a progressive reduction in strength with increasing temperature and a corresponding change in the thermomechanical response associated with evolving failure mechanisms. Full article

This research aims to investigate and improve the accuracy of porosity prediction in steel ingot casting by leveraging Thercast finite element simulations. In particular, the study refines the Niyama criterion through additional physical parameters and solidification modeling, aiming to reduce shrinkage porosity and enhance the overall mechanical reliability of cast components. Simulation results reveal that a lower thermal conductivity and faster cooling rates exacerbate shrinkage porosity, while a refined Niyama indicator using explicit solid-fraction weighting, with viscosity, alloy composition, and shrinkage accounted for through the underlying THERCAST material model, improves spatial localization of porosity-prone regions in the investigated case. For the investigated configuration, reducing the cooling rate to around 1.25 K/s decreased the extent of the simulated region classified as porosity-prone relative to the reference case. Furthermore, the analytical porosity–strength relation indicates a material-dependent reduction in strength when the porosity fraction exceeds 2%, underscoring the structural significance of internal voids. This study extends the practical interpretation of the classical Niyama criterion by combining solid-fraction weighting with material-dependent thermophysical inputs, addressing gaps in existing shrinkage porosity models. The approach integrates simulation findings with actual casting defects identified through ultrasonic scanning and metallographic analysis. By merging experimental insights with advanced finite element simulations, foundries can better regulate casting conditions, particularly cooling rates and thermal gradients, to minimize porosity. The refined porosity prediction framework aids in process optimization, improved material utilization, and superior quality assurance of steel ingots. Full article

Pervious concrete must balance mechanical capacity with interconnected voids required for drainage. A three-factor, three-level Box–Behnken design examined fly ash (FA; 10–20%), metakaolin (MK; 5–15%), and nano-silica (NS; 0.5–1.5%) at a fixed total binder content of 380 kg/m³. Compressive strength, water-accessible open porosity, and the apparent permeability coefficient ranged from 16.80 to 28.20 MPa, 14.07 to 24.50%, and 2.20 to 7.29 mm/s, respectively. Quadratic models for compressive strength and the apparent permeability coefficient were statistically adequate (R² = 0.9907 and 0.9861); the porosity model showed significant lack of fit. The porosity model was retained only for local trend interpretation and excluded from optimization. In a researcher-defined design scenario that maximized strength while targeting an apparent permeability coefficient of 3.00 mm/s, desirability analysis selected a model-predicted compromise solution containing 14.038% FA, 12.556% MK, and 1.483% NS, with a predicted compressive strength and an apparent permeability coefficient of 28.233 MPa and 3.000 mm/s. The NS factor was close to the upper boundary, and the solution was not experimentally validated. Selected single-field SEM observations illustrated local differences among M5, M7, and M12, while selected-area EDS sum spectra provided only local elemental composition information. The results indicate potential for future pavement evaluation after independent validation, multi-field microstructural analysis, durability testing, and economic assessment. Full article

Fused filament fabrication (FFF) has become an important additive manufacturing technique for producing functional polymer-composite components. The tensile performance of carbon fiber-reinforced polyethylene terephthalate glycol (PETG/CF) fabricated by FFF depends on multiple printing parameters. This study presents an integrated experimental and predictive framework for investigating the effects of extrusion temperature, printing speed, layer height, infill pattern, and infill density on the tensile strength of PETG/CF containing 15 wt.% carbon fiber. A mixed-level Taguchi L36 orthogonal array was employed, comprising 36 experimental runs with three independently printed specimens per run, resulting in 108 ASTM D638 Type V specimens. Analysis of variance showed that the printing speed had the largest contribution to tensile strength (20.51%), followed by layer height (18.29%). The highest tensile strength of 33.225 MPa was obtained using grid infill, 60% infill density, 270 °C extrusion temperature with 40 mm/s printing speed, and 0.3 mm layer height. An artificial neural network (ANN) was developed for the tensile-strength prediction, achieving R = 0.9801, R² = 0.9569, and MAPE = 1.52% for the overall dataset. Scanning electron microscopy qualitatively revealed bead-interface defects, fiber pullout, and localized void-like features. The proposed framework provides a systematic approach for evaluating process-parameter effects and predicting tensile strength within the investigated PETG/CF parameter domain. Full article

Background: Three-dimensional printing (3DP) is rapidly advancing personalised medicine, yet systematic performance comparison with conventional manufacturing remains limited, particularly for plant-based formulations. Methods: This study compared tablets containing plant-based APIs (cannabidiol, apigenin, and luteolin) produced via conventional hot moulding and semi-solid extrusion (SSE) 3DP. The formulations were evaluated for physicochemical, mechanical, rheological, structural, and drug-release properties. Results: Both manufacturing methods produced tablets with comparable dimensions and mass; however, pronounced formulation-dependent differences were observed in mechanical strength, rheology, and microstructure. The molecular modelling predictions were consistent with the experimental findings. Agar–pectin exhibited the strongest predicted polymer–polymer and polymer–API interactions, including multiple hydrogen bonds, and formed a comparatively dense and cohesive matrix associated with slower API release. In contrast, the weaker interactions predicted for gelatine–pectin were associated with a less cohesive and more porous matrix that facilitated medium penetration, API diffusion, and drug release. SSE printlets generally exhibited greater porosity and more heterogeneous internal architectures than moulded tablets, resulting in enhanced drug release of approximately 95%. Micro-CT analysis provided important structural confirmation; API incorporation increased the void volume of gelatine–pectin printlets from 1.15% to 8.77%, demonstrating that disruption of polymer interactions contributed to pore formation and enhanced molecular diffusion. The observed release behaviour correlated with predicted molecular interactions and experimentally observed microstructural features, where increased porosity and weaker polymer–API interactions facilitated enhanced drug diffusion. Conclusions: Overall, SSE-3DP outperformed conventional moulding, demonstrating superior tunability and performance. This work provides a mechanistically informed strategy for designing plant-based, personalised natural products using 3DP technologies. Full article

This paper proposes a novel Topological Data Analysis (TDA) pipeline to extract robust structural features from functional near-infrared spectroscopy (fNIRS) signals for the classification of Alzheimer’s Disease (AD) stages. Alzheimer’s disease is increasingly understood as a disconnection syndrome, where the disruption of functional brain networks precedes gross anatomical atrophy. However, traditional graph-theoretic approaches rely on arbitrary connectivity thresholds, which can obscure critical multi-scale topological information, and are sensitive to noise. To address this, our framework leverages Persistent Homology (PH) to analyse the topological evolution of brain networks across a continuous range of scales. By modeling 48-channel hemoglobin concentration time-series as high-dimensional point clouds via Granger causality metrics, we construct filtration sequences of Vietoris–Rips complexes. The resulting topological invariants, including 0—dimensional connected components, 1—dimensional loops, and 2—dimensional voids, are first examined through Persistence Diagrams. For classification, significant H0 and H1 features are converted into Persistence Images using Gaussian kernel smoothing, while H2 features are retained for qualitative topological interpretation. This transformation enables the integration of complex topological features into standard machine learning workflows. Our experimental results were evaluated on a subject-level held-out test set consisting only of original, non-augmented recordings. Data augmentation was applied only to the training set to alleviate class imbalance. The proposed topology-driven feature extraction method achieved 86% accuracy in multi-class diagnosis (NC vs. MCI vs. AD). This study validates the efficacy of TDA as a sophisticated signal processing tool for revealing intrinsic neurodegenerative patterns in hemodynamic data, offering an exploratory methodological proof-of-concept for AD stage classification. Full article

Smart-diaper signals collected during routine care are affected by sensor noise, transmission gaps, variable event durations, and limited labels, making normal voiding (NV) and urinary incontinence (UI) difficult to distinguish using threshold-based detection alone. We developed a label-efficient time-series classification framework based on Context-Aware Temporal Contrastive Coding (CA-TCC) using the resistance ($R_{\mathrm{VAL}}$) channel of a smart-diaper sensor. Recordings from 97 older residents across three long-term care facilities were quality-filtered, aggregated at 3 min intervals, screened for candidate events, and interpolated to fixed-length inputs. CA-TCC was pre-trained on an unlabeled candidate-event pool and adapted using 4877 manually labeled events. The linear-probe, full fine-tuning, and class-aware pseudo-label retraining configurations were evaluated using participant-grouped five-fold cross-validation. The selected semi-supervised configuration achieved $82.12\pm 2.33$% accuracy, $82.12\pm 2.32$% macro-F1, and an AUC of $0.895\pm 0.018$ (mean ± 95% confidence interval), exceeding the strongest classical baseline by 4.80 macro-F1 percentage points. Its macro-F1 increased from $79.22\pm 1.84$% with 1000 labeled events to $81.97\pm 1.82$% with the full labeled set, whereas full fine-tuning showed greater fold-to-fold variability. Aggregated LIME analysis over 300 held-out events did not support localization of the model’s evidence to the event onset. These results indicate that contrastive pre-training can support smart-diaper voiding-pattern classification when labeled data are limited. Full article

Due to advantages such as larger heat transfer area, higher heat transfer efficiency, and greater thermal expansion stress, helical coiled tubes (HCTs) have been widely adopted in heat exchangers in industry, especially for nuclear power plants. The nucleate boiling heat transfer characteristics within an HCT are investigated using a multi-phase CFD boiling framework implemented and evaluated in this study. Based on the requirement of BPG (Best Practice Guideline) for the CFD applied in the nuclear safety analysis, mesh-independent calculations are performed, including of the heat transfer coefficient and wall temperature along the HCT and the void fraction and secondary flow on the cross-section of the HCT. The effects of various bubble dynamic correlations in the boiling model on the predicted results are also considered. Several previous experiments are adopted to assess the present boiling models, showing the feasibility of the present boiling CFD methodology in predicting the average nucleate boiling heat transfer coefficient along the HCT. Compared with the predicted results from the various heat transfer correlations in the subcooled and saturated nucleate boiling regions, this CFD boiling model can assess these correlations applied in HCT as well as assist in the safety analysis of system codes in selecting the appropriate boiling heat transfer correlations. Full article