Numerical investigations on axial compression performance of square coral aggregate concrete-filled duplex stainless steel tube columns

Pullulan-based semi-interpenetrating network hydrogel sensor for artificial intelligence-driven pressure recognition.

Local compression performance of steel-reinforced concrete-filled square stainless steel tubular columns

Axial compressive performance of CFDST stub columns using HSS and UHSC

Experimental and analytical studies on the axial compressive performance of steel-confined timber composite columns

Abstract Joint compression and encryption algorithms are one of the key candidate technologies for JPEG image processing. However, these methods inevitably impair compression efficiency of JPEG images. To balance protection power and compression performance, a novel JPEG image cryptosystem is proposed based on a complex chaotic map. Specifically, a two dimensional coupled Rastrigin complex hyperchaotic map (2D-CRCCM) is studied as the key generator. Meanwhile, the global and group permutation algorithms are designed to prevent the leakage of sensitive information in the adaptive discrete cosine transform (DCT) domain, namely the alternating current coefficients (ACCs) and direct current components (DCCs). Finally, a lightweight binary stream encryption method is presented to further enhance the data security during the transmission process. Experimental results show that the proposed approach effectively mitigates the risk of sensitive information leakage. It also reduces file size increment, maintains format compatibility, and exhibits linear time complexity in worst-case scenarios. Notably, across most compression ratios, our method yields higher PSNR value than others, and better than standard JPEG compression.

ABSTRACT To investigate rehabilitation methods for damaged inorganic-adhesive bamboo composite (InorgBam) columns and their post-rehabilitation eccentric compressive performance, this study proposed four rehabilitation schemes: Epoxy injection rehabilitation (EIR), CFRP hoop confinement rehabilitation (CHR), CFRP hoop-planar hybrid rehabilitation (CHPR), and CFRP hoop confinement-embedded rebar hybrid rehabilitation (CHRR). Eccentric compression tests were conducted on rehabilitated specimens with two slenderness ratios. The results indicate that: The failure mode of rehabilitated specimens was buckling failure, with bearing capacity recovery coefficients ranging from 0.88 to 1.40. Specimens rehabilitated using the CHRR method achieved the highest bearing capacity recovery ratio. All rehabilitation schemes significantly improved the ductility of damaged columns. The rehabilitated specimens also exhibited notable enhancements in both axial and lateral stiffness, with axial stiffness recovery coefficients ranging from 0.81 to 1.15 and lateral stiffness recovery coefficients ranging from 0.68 to 1.47. Among the four methods, the CHRR method provided the most substantial improvement in column stiffness. Based on experimental results and existing theoretical models, analysis methods were developed for predicting mid-span lateral deflection and eccentric compression bearing capacity of rehabilitated InorgBam columns.

The utilisation of coal gasification ash (CGA) is an important way of reducing carbon dioxide emissions in the construction industry. Regarding columns made using coal gasification ash concrete (CGAC), their compressive performance and compatibility with existing bearing capacity formula are undefined, and existing research on concrete columns fails to address differences in their material systems. In this study, three reinforced concrete columns (RCCs) made with ordinary concrete and nine reinforced columns made with CGAC of three strength grades (C30, C40 and C50) and 20% CGA were fabricated to analyse the influences of eccentricity, concrete strength and concrete type on the columns’ failure modes, load–displacement curves, ductility and other properties. The results showed that, compared with RCCs, the CGAC columns exhibited fewer cracks with a more uniform distribution, along with significantly improved bearing capacity and ductility. The compressive performance of the CGAC columns was further enhanced with an increase in concrete strength. With an increasing in eccentric (60 mm–120 mm), the load-bearing capacity decreased while the deformation capacity increased. Based on the test results, the formula for calculating the ultimate bearing capacity was revised, and the revised formula can be applied to calculate the bearing capacity CGAC columns. The influence of factors such as the reinforcement ratio on the load–moment curve was analysed through a parametric analysis.

With the increased aircraft volume and lifetime cost, the performance of the honeycomb sandwich structure needs to be further improved. This paper innovatively proposes a method for adjusting the strength of multi-layer honeycomb sandwich structures within a limited space. Based on the existing technology, structural innovations have been made, expanding the application of honeycomb structures. Through 3D printing technology, the material composition and mechanical properties of the middle panel can be precisely controlled, enabling flexible design of the performance of honeycomb sandwich structures. Compared with traditional manufacturing methods, it has significant advantages. Compression experiments were carried out on different samples by a universal testing machine. The influence of the strength of the middle panel on the compression performance, energy absorption performance, and transverse dimension of the honeycomb sandwich structure was analyzed and verified by theory. The morphology of the honeycomb core, panel, and interface state after compression was observed by an electron microscope. The failure mechanism was analyzed, and the accurate platform endpoint was obtained by solving the image slope. The results show that with the increase of the strength of the middle panel, the compression performance and energy absorption capacity of the honeycomb sandwich structure decreases gradually in the yield stage. In contrast, the compression performance increases gradually in the rapid climbing stage, and the transverse size decreases gradually. By changing the strength of the middle panel, the average compressive stress in the yield stage can be increased by 7.69%, the energy absorption capacity can be increased by 18.11%, the compressive stress can be increased by 23.12%, and the transverse dimension can be decreased by 3.66% when the strain is 0.545. The above research provides a theoretical basis for improving the compression performance and energy absorption capacity of honeycomb multi-layer structures.

Study on the axial compression performance and residual load-bearing capacity of coal gangue concrete columns after high temperature exposure

Strategic heat treatment for tailored room- and high-temperature properties in a high Nb–TiAl alloy

The CPR compression matrix: relationship among depth, recoil, and rate.

Transferring large volumes of high-resolution images during wind turbine inspections introduces a bottleneck in assessing and detecting severe defects. Efficient coding must preserve high fidelity in blade regions while aggressively compressing the background. In this work, we propose an end-to-end deep learning framework that jointly performs segmentation and dual-mode (lossy and lossless) compression. The segmentation module accurately identifies the blade region, after which our region-of-interest (ROI) compressor encodes it at superior quality compared to the rest of the image. Unlike conventional ROI schemes that merely allocate more bits to salient areas, our framework integrates: 1) a robust segmentation network (BU-Netv2+P) with a CRF-regularized loss for precise blade localization; 2) a hyperprior-based autoencoder optimized for lossy compression; and 3) an extended bits-back coder with hierarchical models for fully lossless blade reconstruction. Furthermore, our ROI framework removes the sequential dependency in bits-back coding by reusing background-coded bits, enabling parallelized and efficient dual-mode compression. To the best of our knowledge, this is the first fully integrated learning-based ROI codec combining segmentation, lossy, and lossless compression, ensuring that subsequent defect detection is not compromised. Experiments on a large-scale wind turbine dataset demonstrate superior compression performance and efficiency, offering a practical solution for automated inspections.

This study conducts an extensive analysis of the axial compressive performance of rectangular light-gauge steel tube columns filled with expansive self-compacting concrete (ESCC). Thirty-six concrete-filled steel tube (CFST) samples, comprising conventional self-compacting concrete (SCC) and type K expansive cement-based SCC, as well as six hollow control samples, were subjected to monotonic axial loading tests. The experimental program included modifications in steel tube thickness (2mm, 3mm, and 4mm), concrete grade (M30, M40, and M50), and column slenderness ratio to evaluate their impact on structural performance. The use of expansive agents successfully generated self-stress in the concrete core, hence improving the interaction among steel and concrete composites, as validated by strain measurements and analytical models. The ESCC-filled columns demonstrated enhanced confinement effects, delayed the initiation of local buckling,and significant improvements in load-bearing capability, resulting in strength increases of up to 21% compared with their SCC-filled equivalents. Finite element models created in ABAQUS precisely mirrored the experimental behaviour, with prediction discrepancies confined to a 10% margin. Additionally, a revised theoretical model adjusted to incorporate self-stress and confinement effects exhibited a robust association with the empirical results. The performance metrics, including strength enhancement, confinement efficiency, ductility, and concrete contribution, validate the efficiency of expansive self-compacting concrete in refining the structural integrity of CFST columns. The results highlight the promise of expansive self-compacting concrete as a pivotal material innovation for enhancing the reliability and load-bearing capacity of light-gauge steel-concrete composite columns.

Current understanding of carbon fiber-reinforced PETG (PETG-CF) honeycomb structures remains limited, with their mechanical properties and failure mechanisms insufficiently characterized across a wide operational temperature range from −20°C to 65°C. This study addresses this knowledge gap by systematically investigating the quasi-static compressive response of regular hexagonal PETG-CF honeycombs. A combined approach of experimental testing and thermo-mechanically coupled numerical simulations was employed. Experimental characterization, complemented by fracture surface analysis using scanning electron microscopy (SEM), revealed pronounced temperature-dependent effects on compressive modulus, specific energy absorption (SEA), and failure modes. The results indicate a clear trend, the compressive modulus decreases from 47.76 MPa at −20°C to 39.84 MPa at 65°C, while the SEA declines by 52.4%, from 1.03 MJ/m 3 to 0.49 MJ/m 3 . Failure modes exhibit strong temperature dependence. Brittle fracture, characterized by matrix cracking and fiber breakage, dominates at low temperatures (−20°C, −10°C, 0°C). At 25°C, a brittle-to-ductile transition occurs, whereas plastic buckling and interfacial debonding become the primary failure mechanisms at higher temperatures (45°C and 65°C). Finite element analysis further elucidates the role of geometric stress concentration zones as consistent initiation sites for failure. Importantly, the evolution of failure is governed by the temperature-dependent plastic deformation capability of the PETG-CF matrix. This work establishes a fundamental link between temperature and the progression from microscopic damage to macroscopic failure, providing a theoretical foundation for the design of lightweight structures operating across broad temperature ranges.

To enhance the protection capability of cement concrete and achieve emission reductions, this article developed a novel bionic concrete structure utilizing steel slag powder (SSP) and ground granulated blast furnace slag (GGBFS) as the primary precursors, inspired by the bionic design of the scale structure of pinecone fish. The effects of various contents in SSP, steel fiber, and bionic structure on dynamic-compressive performance were investigated using the Split Hopkinson Pressure Bar (SHPB) test. Results indicated that the bionic structure exhibited high energy absorption performance, with a 73.1% increase in energy absorption at the maximum strain rate compared to the reference group, which effectively protected the internal structure and minimizes cracking. The predictive formulas for the toughness factor and dynamic increase factor (DIF) of SSP-based UHPGC were proposed. The proposed model for DIF provided valuable guidance for the optimization of bionic structure design and its application.

Recently, cold-formed steel (CFS) structural systems have been increasingly used in building applications due to their lightweight characteristics, ease of fabrication, and efficient construction processes. Among these systems, built-up CFS columns are widely adopted to enhance load-carrying capacity; however, their axial compression behavior and failure mechanisms have not yet been fully clarified. This study aims to investigate the axial compression performance of built-up cold-formed steel columns through a combined experimental and numerical approach. This study investigates the axial compression performance of built-up cold-formed steel columns using a combined experimental and numerical approach. Following the full-scale testing of five different configurations, finite element models were developed in ABAQUS using the obtained material properties. The experimental results were used to validate and calibrate the finite element models, which provided a detailed simulation of the nonlinear structural behavior of the columns. The experimental load–displacement responses were compared with the numerical results to evaluate the accuracy of the finite element models and to identify the axial load-carrying capacity and dominant failure modes of the built-up columns. Furthermore, the tensile pull-out behavior of 3.9 mm diameter self-drilling screws utilized in the built-up column connections was examined through expedient fastener tests to facilitate a more profound understanding of the load transfer mechanism. The results highlight the influence of built-up configuration and connection behavior on the axial compression performance of CFS columns, providing practical insights for improving the design and numerical modeling of screw-connected built-up cold-formed steel column systems.

Abstract In this study, the mechanical performance of copper tailings‐laden geopolymer concrete‐steel tubular columns under axial compression was investigated to improve the utilization of copper tailings and promote the application of geopolymer concrete in construction engineering. The effects of design parameters, such as concrete strength, section size (i.e., the outer diameter of the column), and steel‐tube thickness, were analyzed in detail. The test results illustrated that the effect of section size on the axial compression performance of the tubular columns was the most significant. After reaching the peak load, all specimens exhibited varying degrees of strength degradation. With the yielding of the steel tubes, bulging initiated at the ends, which gradually shifted toward the middle, ultimately showing a barrel‐shaped failure. The compressive force efficiency, defined as the ratio of average compressive force to ultimate compressive force, ranged from 0.71 to 0.78. The ductility coefficient varied between 13.37 and 31.48, with an average of 19.85, indicating excellent load‐bearing capacity and deformation performance of the specimens. Additionally, the axial compressive load capacity of the tubular columns was predicted based on mainstream codes. The results showed that the Eurocode yielded the best agreement with the experimental results, with the ratio of the predicted to experimental values ranging from 0.899 to 1.185 (average of 1.045). Finally, an established finite element analysis model was applied and the results were compared with the experimental ones. The ratio of the peak experimental load to the simulation results for the specimens ranged from 0.92 to 1.16, thus validating the finite element simulation.

ABSTRACT This study focuses on addressing the challenges of poor integrity and insufficient mechanical properties in carbon fiber honeycomb composites, which arise from weak interlaminar node connections and unequal free/bonded wall thicknesses. These issues are particularly critical in the field of satellite antennas, which require lightweight and high‐load‐bearing structures. To achieve continuous fibers and superior cell integrity in honeycomb materials, a honeycomb core structure with equal thicknesses for free walls and bonded walls was developed via 2.5D interlayer interlocking weaving technology. Honeycomb sandwich structure specimens with honeycomb cell side lengths of 5, 9, and 15 mm and equal‐wall‐thickness were fabricated. Additionally, comparison specimens with unequal wall thickness and 15 mm cell side length were prepared. Out‐of‐plane compression tests were conducted, combined with damage characterization using SEM, 3D profilometer, and high‐definition video capture. A mesoscale‐macroscale damage model was established, demonstrating good agreement between simulation and experimental mechanical responses. Analysis indicates that the small‐cell‐size equal‐wall‐thickness structure exhibits excellent out‐of‐plane compression performance, with a 296.88% strength increase compared to the large‐cell‐size equal‐wall‐thickness specimen. Notably, the equal‐wall‐thickness structure demonstrates a 63.6% strength improvement over the unequal‐wall‐thickness specimen under identical side wall length conditions. Simulation and experimental results reveal that the damage in honeycombs with equal wall thickness originates from microcracks in the matrix, progresses through fiber fracture and cell wall buckling, and ultimately leads to the progressive collapse of the honeycomb cells. This study provides an important theoretical and experimental basis for the design and optimization of high‐performance honeycomb structures.

Auxetic structures, recognized for their lightweight design, auxeticity, and exceptional mechanical properties, have garnered considerable attention from the engineering sector. The auxeticity and associated mechanical traits of these structures depend on the negative Poisson's ratio (NPR) principle. These structures comprise a collection of repetitive unit cells, the size of which is crucial for achieving the desired performance. This study introduces a high-performing auxetic structure based on a unit cell named Mixed Star and optimizes its performance using a hybrid statistical-numerical approach. Considering the length, height, thickness, and inclination of the wall as cell parameters, a detailed test plan was generated through a statistical approach. A series of mixed-star Metamaterial (MSM) structures were modeled according to the Design of Experiment plan, and their mechanical performance, specifically energy absorption, modulus, and strength in compression and bending, was evaluated using a validated FEM model. The collected results were analyzed, revealing key effects along with their nature. In-depth analysis of the findings indicated that the auxetic behavior of the structure is closely associated with the size of its unit cell, highlighting the need for an optimized cell size to enhance structural performance. By applying an appropriate approach, the optimum cell size was determined while considering both compression and flexural loads, resulting in substantial gains in auxeticity and mechanical performance, depending on the response parameter and loading condition. This study emphasizes the potential of a hybrid statistical-numerical approach in optimizing the geometry of NPR structures to achieve superior performance, providing a valuable framework and paving the way forward for future research.