The online identification of rock damage states is crucial for safety monitoring in geotechnical and mining engineering. By analyzing spatiotemporal evolution patterns of infrared radiation in various rock damage states, we established the first infrared temperature field dataset for rock damage state identification. We then constructed a deep convolutional neural network, RESD-CNN, and performed its training and optimization. Results showed that infrared radiation patterns of different rock samples exhibit similarities. RESD-CNN achieved outstanding performance in identifying rock damage states with metrics of ACC 99.04%, Precision 99.39%, Recall 99.52%, and F1-score 99.46% on the validation set. Generalization tests on datasets of different rock types revealed that RESD-CNN significantly outperformed traditional classification methods, demonstrating the feasibility of infrared radiation technology for intelligent coal rock damage identification. This research provides a crucial foundation for developing online identification and early warning systems for rock damage evolution in engineering.

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A new route towards strong yet ductile metals via architecting heterogeneities in both structure and metastability is presented. Such heterogeneities are generated and manipulated in a standard stainless steel using a heterogeneous phase transformation (het-PT) strategy, in which focused laser patterning is applied to stimulate site-specific phase transformations. The het-PT processed steel contains periodically arranged stripes of strong martensite and ductile austenite with different grain sizes and metastability. The resulting structural heterogeneity leads to a desirable strain gradient and heterogeneous deformation-induced martensitic transformation during deformation, which effectively accommodate strain localization and enhance work hardening capability in the het-PT-processed steel. These unique features result in an enhanced balance between strength and ductility, outperforming both homogeneously ultrafine-grained and coarse-grained counterparts. The het-PT strategy is expected to be applicable to tailoring structural heterogeneity and metastability in other steels and metals.

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Corrosion poses a significant risk to the safety of energy pipelines, while landslide disasters emerge as the primary threat responsible for triggering pipeline failures across mountainous areas. To date, there is limited research focused on the safety of energy pipelines considering the synergistic effect of corrosion and landslides. The present study proposes a finite element (FE)-based model to assess the condition of corroded pipelines under landslides. The effects of corrosion dimensions (length and depth) and location are determined. A novel equation is finally developed to predict the maximum stress and determine the most disadvantageous position for corroded pipelines under various landslide displacements. The results demonstrate that (1) as the landslide progresses, the pipeline’s stress significantly increases; (2) corrosion depth has a more significant impact on the pipeline condition than the corrosion length, and it is positively correlated with the pipe’s stress; (3) the maximum stress exhibits a nonlinear relationship with the landslide-facing position and the corrosion circumferential location; and (4) when the axial position of the corrosion is more than 6.5 m away from the center of the landslide, the location of maximum stress shifts from the corrosion region to the central section of the pipeline within the landslide. This work contributes to helping pipeline owners to understand the applicability of energy pipelines subjected to the combined effects of corrosion and landslides and provides support for future risk assessment efforts in pipeline integrity management.@en

The journal is publishing this Expression of Concern to alert readers while we investigate to determine whether further action is required.

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Vehicle field test can be conducted smoothly because of the automobile-mounted monitoring system and abundant diving data have been collected. Driving data mining is in an urgent need of new thoughts introduced to break through the original technical bottleneck. This paper presented a novel method of symbolic representation in diving data mining and applied the idea of time series symbolization to traffic engineering. The sample data is processed by normalization, dimensionality reduction, discretization, and symbolization based on the three steps of symbolic aggregate approximation (SAX) with driving data characteristics taken into adequate consideration. The results showed that the high-dimensionality miscellaneous driving time series data was rationally converted into highly readable, easy to search and locate symbolic series after semantic encoding, and the main characteristics of time series data was preserved after a substantial reduction of data dimensionality. Finally, the paper demonstrated the positive effects of this method on the analysis of actual vehicle driving safety based on case study, and it explored the application of SAX to speed and acceleration data from driving data set.

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Functionally graded scaffold (FGS) is designed to mimic the morphology, mechanical and biological properties of natural bone closely. Porosity variation strategy between different regions in FGS plays a crucial role in influencing its mechanical and biological performance. A combination of modeling tool and scripting language can effectively enhance the ability to optimize FGS design. This study was aimed at determining the effect of porosity variation strategy on the mechanical performance and permeability of the as-built and as-heat-treated FGSs. Ti-6Al-4V FGSs with sizes of 10 × 10 × 15 mm and diamond lattice structures were designed and fabricated by means of selective laser melting. A wide range of porosities in the FGSs (38–75%) were achieved by applying six different porosity variation strategies. The elastic modulus (3.7–5.7 GPa) and yield strength (27.1–84.7 MPa) of the as-built FGSs were found to vary between the corresponding mechanical properties of cancellous bone and cortical bone. Heat treatment reduced the strengths by 13–56%. Porosity variation strategy strongly affected the deformation behavior and failure mechanisms of the FGSs. The sigmoid function-controlled FGSs showed gradual failure behavior and sample Sigk0.5b8 showed superior overall performance. The results demonstrated that porosity variation strategy is a feasible means for tailor design of FGS.

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