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This study aims to investigate the effect of countersunk rivet head dimensions on the fatigue performance of the riveted specimens of 2024-T3 alloy.

The relationship between rivet head dimensions and fatigue behavior was investigated by finite element method and fatigue test. The fatigue fracture of the specimens was analyzed by scanning electron microscopy.

A change of the rivet head dimensions will cause a change in the stress concentration and residual normal stress, the stress concentration near the rivet hole causes the fatigue crack source to be located on the straight section of the countersunk rivet hole and the residual normal stress can effectively restrain the initiation and expansion of fatigue cracks. The fatigue cycle will cause the rivet holes to produce different degrees of surface wear.

The fatigue life of the specimens with the height of the rivet head of 2.28 mm and 2.00 mm are similar, but the specimens with the height of the rivet head of 1.72 mm were far higher than the other specimens.

Additive manufacturing (AM) is growing economically because of its cost-effective design flexibility. However, it faces challenges such as interlaminar weaknesses and reduced strength because of product anisotropy. Therefore, the purpose of this study is to develop a methodology that integrates design for additive manufacturing (AM) principles with fused filament fabrication (FFF) to address these challenges, thereby enhancing product reliability and strength.

Developed through case analysis and literature review, this methodology focuses on design methodology for AM (DFAM) principles applied to FFF for high mechanical performance applications. A DFAM database is constructed to identify common requirements and establish design rules, validated through a case study.

Existing DFAM approaches often lack failure theory integration, especially in FFF, emphasizing mechanical characterizations over predictive failure analysis in functional parts. This methodology addresses this gap by enhancing product reliability through failure prediction in high-performance FFF applications.

While some DFAM methods exist for high-performance FFF, they are often specific cases. Existing DFAM methodologies typically apply broadly across AM processes without a specific focus on failure theories in functional parts. This methodology integrates FFF with a failure theory approach to strengthen product reliability in high-performance applications.

This study aims to improve the stability and obstacle surmounting ability of the traditional wall-climbing robot on the surface of the ship, a wheel-track composite magnetic adsorption wall-climbing robot is proposed in this paper.

The robot adopts a front and rear obstacle-crossing mechanism to achieve a smooth crossover. The robot is composed of two passive obstacle-crossing mechanisms and a frame, which is composed of two obstacle-crossing magnetic wheels and a set of tracks. The obstacle-crossing is realized by the telescopic expansion of the obstacle-crossing mechanism. Three static failure models are established to determine the minimum adsorption force for the robot to achieve stable motion. The Halbach array is used to construct the track magnetic circuit, and the influence of gap, contact area and magnet thickness on the adsorption force is analyzed by parameter simulation.

The prototype was designed and manufactured by the authors for static failure and obstacle crossing tests. The prototype test results show that the robot can cross the obstacle of 10 mm height under the condition of 20 kg load.

A new structure of wall-climbing robot is proposed and verified. According to the test results, the wall-climbing robot can stably climb over the obstacle of 10 mm height under the condition of 20 kg load, which provides a new idea for future robot design.

This study compares the fatigue performance and biocompatibility of as-built and chemically etched Ti-6Al-4V alloys in TPMS-gyroid and stochastic structures fabricated via Powder Bed Fusion Laser Beam (PBF-LB). This study aims to understand how complex lattice structures and post-manufacturing treatment, particularly chemical etching, affect the mechanical properties, surface morphology, fatigue resistance and biocompatibility of these metamaterials for biomedical applications.

Selective Laser Melting (SLM) technology was used to fabricate TPMS-gyroid and Voronoi stochastic designs with three different relative densities (0.2, 0.3 and 0.4) in Ti-6Al-4V ELI alloy. The as-built samples underwent a chemical etching process to enhance surface quality. Mechanical characterization included static compression and dynamic fatigue testing, complemented by scanning electron microscopy (SEM) for surface and failure analysis. The biocompatibility of the samples was assessed through in-vitro cell viability assays using the Alamar Blue assay and cell proliferation studies.

Chemical etching significantly improves the surface morphology, mechanical properties and fatigue resistance of both TPMS-gyroid and stochastic structures. Gyroid structures demonstrated superior mechanical performance and fatigue resistance compared to stochastic structures, with etching providing more pronounced benefits in these aspects. In-vitro biocompatibility tests showed high cytocompatibility for both as-built and etched samples, with etched samples exhibiting notably improved cell viability. The study also highlights the importance of design and post-processing in optimizing the performance of Ti64 components for biomedical applications.

The comparative analysis between as-built and etched conditions, alongside considering different lattice designs, provides valuable information for developing advanced biomedical implants. The demonstration of enhanced fatigue resistance and biocompatibility through etching adds significant value to the field of additive manufacturing, suggesting new avenues for designing and post-processing implantable devices.

The purpose of this paper is to propose a new combined finite-discrete element method (FDEM) to analyze the mechanical properties, failure behavior and slope stability of soil rock mixtures (SRM), in which the rocks within the SRM model have shape randomness, size randomness and spatial distribution randomness.

Based on the modeling method of heterogeneous rocks, the SRM numerical model can be built and by adjusting the boundary between soil and rock, an SRM numerical model with any rock content can be obtained. The reliability and robustness of the new modeling method can be verified by uniaxial compression simulation. In addition, this paper investigates the effects of rock topology, rock content, slope height and slope inclination on the stability of SRM slopes.

Investigations of the influences of rock content, slope height and slope inclination of SRM slopes showed that the slope height had little effect on the failure mode. The influences of rock content and slope inclination on the slope failure mode were significant. With increasing rock content and slope dip angle, SRM slopes gradually transitioned from a single shear failure mode to a multi-shear fracture failure mode, and shear fractures showed irregular and bifurcated characteristics in which the cut-off values of rock content and slope inclination were 20% and 80°, respectively.

This paper proposed a new modeling method for SRMs based on FDEM, with rocks having random shapes, sizes and spatial distributions.

Steam explosions are a major safety concern in many modern furnaces. The explosions are sometimes caused by water ingress into the furnace from leaks in its high-pressure (HP) cooling water system, coming into contact with molten matte. To address such safety issues related to steam explosions, risk based inspection (RBI) is suggested in this paper. RBI is presently one of the best-practice methodologies to provide an inspection schedule and ensure the mechanical integrity of pressure vessels. The application of RBIs on furnace HP cooling systems in this work is performed by incorporating the proportional hazards model (PHM) with the RBI approach; the PHM uses real-time condition data to allow dynamic decision-making on inspection and maintenance planning.

To accomplish this, a case study is presented that applies an HP cooling system data with moisture and cumulated feed rate as covariates or condition indicators to compute the probability of failure and the consequence of failure (CoF), which is modelled based on the boiling liquid-expanding vapour explosion (BLEVE) theory.

The benefit of this approach is that the risk assessment introduces real-time condition data in addition to time-based failure information to allow improved dynamic decision-making for inspection and maintenance planning of the HP cooling system. The work presented here comprises the application of the newly proposed methodology in the context of pressure vessels, considering the important challenge of possible explosion accidents due to BLEVE as the CoF calculations.

This paper however aims to optimise the inspection schedule on the HP cooling system, by incorporating PHM into the RBI methodology, as was recently proposed in the literature by Lelo et al. (2022). Moisture and cumulated feed rate are used as covariate. At the end, risk mitigation policy is suggested.

In this paper, the proposed methodology yields a dynamically calculated quantified risk, which emphasised the imperative for mitigating the risk, as well as presents a number of mitigation options, to quantifiably affect such mitigation.

Based on social cognitive theory, this study aims to analyze the impact of fear of failure on entrepreneurs’ growth aspirations, the moderating role of collectivist institutional culture and the differences between emerging and developed countries.

Using the Global Entrepreneurship Monitor and the Global Leadership and Organizational Behavior Effectiveness databases for 27 developed and 15 emerging countries, and Global Leadership and Organizational Behavior Effectiveness, the authors apply multilevel model with individual-level and country-level variables.

The fear of failure has a negative impact on growth aspirations and that impact differs between developed and emerging countries. One of the main conclusions is that collectivist culture mitigates the negative impact of fear of failure on growth aspirations, and that this result is significant only in emerging countries.

The authors introduce a boundary condition for this study’s predictions, showing that in emerging countries, contrary to developed countries, the moderator effect of cultural context contributes to growth aspirations, despite the entrepreneur’s fear of failure.

Adhesive bonding is critical to the effectiveness and structural integrity of 3D printed components. The purpose of this study is to investigate the effect of joint configuration on failure loads to improve the design and performance of single lap joints (SLJs) in 3D printed parts.

In this study, adherends were fabricated using material extrusion 3D printing technology with polyethylene terephthalate glycol (PETG). A toughened methacrylate adhesive was chosen to bond the SLJs after adherend printing. In this study, response surface methodology (RSM) was used to examine the effect of the independent variables of failure load, manufacturing time and mass on the dependent variable of joint configuration; adherend thickness (3.2, 4.0, 4.8, 5.6, 6.4, and 7.2 mm) and overlap lengths (12.7, 25.4, 38.1, and 50.8 mm) of 3D printed PETG SLJs.

The strength of the joints improved significantly with the increase in overlap length and adherend thickness, although the relationship was not linear. The maximum failure load occurred with a thickness of 7.2 mm and an overlap of 50.8 mm, whilst the minimum failure load was determined with a thickness of 3.2 mm and an overlap of 12.7 mm. The RSM findings show that the optimum failure load was achieved with an adherend thickness of 3.6 mm and an overlap length of 37.9 mm for SLJ.

This study provides insight into the optimum failure load for 3D printed SLJs, reducing SLJ production time and mass, producing lightweight structures due to the nature of 3D printing, and increasing the use of these parts in load-bearing applications.

Due to the harsh underground environment in coal mining, the surface of hydraulic support columns corrodes severely, resulting in significant economic losses. Therefore, a highly corrosion-resistant coatings is needed to extend the service life of the columns.

This study aims to compare the corrosion resistance of ST-Cr₃C₂-NiCr (sealed treatment Cr₃C₂-NiCr) coatings with industrially applied chromium plating. The corrosion failure mechanism of the coatings was investigated.

The results demonstrated that the ST-Cr₃C₂-NiCr coatings exhibited excellent corrosion resistance. After sealing treatment, the corrosion potential of Cr₃C₂-NiCr coatings was −0.215 V, and the corrosion current density of Cr₃C₂-NiCr coatings was lower than that of the plated parts.

ST-Cr₃C₂-NiCr coatings prepared by supersonic atmospheric plasma spraying could provide excellent corrosion resistance in the coal industry.

The low porosity and the presence of the NiCr phase were crucial factors contributing to the preferable corrosion resistance exhibited by the ST-Cr₃C₂-NiCr coatings. The corrosive process of the coatings involved layer-by-layer delamination of surface oxide film, sub-surface pitting, formation and degradation of sub-surface passive film, as well as severe block-like delamination.

Total productive maintenance consists of strategies and procedures that aim to guarantee the entire functioning of machines in a production process so that production is not interrupted and no loss of quality in the final product occurs. Planned maintenance is one of the eight pillars of total productive maintenance, a set of tools considered essential to ensure equipment reliability and availability, reduce unplanned stoppage and increase productivity. This study aims to analyze the influence of statistical reliability on the performance of such a pillar.

In this study, we utilized a multi-method approach to rigorously examine the impact of statistical reliability on the planned maintenance pillar within total productive maintenance. Our methodology combined a detailed statistical analysis of maintenance data with advanced reliability modeling, specifically employing Weibull distribution to analyze failure patterns. Additionally, we integrated qualitative insights gathered through semi-structured interviews with the maintenance team, enhancing the depth of our analysis. The case study, conducted in a fertilizer granulation plant, focused on a critical failure in the granulator pillow block bearing, providing a comprehensive perspective on the practical application of statistical reliability within total productive maintenance; and not presupposing statistical reliability is the solution over more effective methods for the case.

Our findings reveal that the integration of statistical reliability within the planned maintenance pillar significantly enhances predictive maintenance capabilities, leading to more accurate forecasts of equipment failure modes. The Weibull analysis of the granulator pillow block bearing indicated a mean time between failures of 191.3 days, providing support for optimizing maintenance schedules. Moreover, the qualitative insights from the maintenance team highlighted the operational benefits of our approach, such as improved resource allocation and the need for specialized training. These results demonstrate the practical impact of statistical reliability in preventing unplanned downtimes and informing strategic decisions in maintenance planning, thereby emphasizing the importance of your work in the field.

In terms of the originality and practicality of this study, we emphasize the significant findings that underscore the positive influence of using statistical reliability in conjunction with the planned maintenance pillar. This approach can be instrumental in designing and enhancing component preventive maintenance plans. Furthermore, it can effectively manage equipment failure modes and monitor their useful life, providing valuable insights for professionals in total productive maintenance.