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This study investigates the fitting techniques for notch fatigue curves, seeking a more reliable method to predict the lifespan of welded structures.

Building on the fatigue test results of butt and cruciform joints, this research delves into the selection of fitting methods for the notch fatigue curve of welded joints. Both empirical formula and finite element methods (FEMs) were employed to assess the notch stress concentration factor at the toe and root of the two types of welded joints. Considering the mean stress correction and weld misalignment coefficients, the notch fatigue life curves were established using both direct and indirect methods.

An engineering example was employed to discern the differences between the direct and indirect approaches. The findings highlight the enhanced reliability of the indirect method for fitting the fatigue life curve.

While the notch stress approach is extensively adopted due to its accurate prediction of component fatigue life, most scholars have overlooked the importance of its curve fitting methods. Existing literature scantily addresses the establishment of these curves. This paper offers a focused examination of fatigue curve fitting techniques, delivering valuable perspectives on method selection.

Due to its inexpensive production costs, low stress concentration and maintenance-friendliness, the adhesive bonded pipe joint is frequently utilized for pipe connection. However, further theoretical analysis is needed to understand the debonding failure mechanism of such bonded pipe joints under axial tension.

In this study, based on the bi-linear cohesive zone model, the integrated closed-form solutions were derived by considering the axial stiffness ratio and failure stage to determine the relative interfacial slip, interfacial shear stress and relationship of tension–displacement in the bonded pipe joint.

Additionally, solutions for the critical bonded length and the ultimate load capacity were put forth. Besides, the numerical study was conducted to verify the theoretical solutions regarding the load–displacement relationship. The interfacial shear stress distribution at different failure stages was presented to understand the interfacial shear stress transmission and debonding process. The effect of bonded length on the ultimate load and ductility of pipe joints was also discussed.

The findings in this study can give a reference for the design of bonded pipe joints in their actual engineering applications.

Central to the entire discipline of construction safety management is the concept of construction accidents. Although distinctive progress has been made in safety management applications over the last decades, construction industry still accounts for a considerable percentage of all workplace fatalities across the world. This study aims to predict occupational accident outcomes based on national data using machine learning (ML) methods coupled with several resampling strategies.

Occupational accident dataset recorded in Turkey was collected. To deal with the class imbalance issue between the number of nonfatal and fatal accidents, the dataset was pre-processed with random under-sampling (RUS), random over-sampling (ROS) and synthetic minority over-sampling technique (SMOTE). In addition, random forest (RF), Naïve Bayes (NB), K-Nearest neighbor (KNN) and artificial neural networks (ANNs) were employed as ML methods to predict accident outcomes.

The results highlighted that the RF outperformed other methods when the dataset was preprocessed with RUS. The permutation importance results obtained through the RF exhibited that the number of past accidents in the company, worker's age, material used, number of workers in the company, accident year, and time of the accident were the most significant attributes.

The proposed framework can be used in construction sites on a monthly-basis to detect workers who have a high probability to experience fatal accidents, which can be a valuable decision-making input for safety professionals to reduce the number of fatal accidents.

Practitioners and occupational health and safety (OHS) departments of construction firms can focus on the most important attributes identified by analysis results to enhance the workers' quality of life and well-being.

The literature on accident outcome predictions is limited in terms of dealing with imbalanced dataset through integrated resampling techniques and ML methods in the construction safety domain. A novel utilization plan was proposed and enhanced by the analysis results.

The purpose of this paper is to achieve the multi-objective optimization design of novel tubular switched reluctance motor (TSRM).

First, the structure and initial dimensions of TSRM are obtained based on design criteria and requirements. Second, the sensitivity analysis rules, process and results of TSRM are performed. Third, three optimization objectives are determined by the average electromagnetic force, smoothing coefficient and copper loss ratio. The analytic hierarchy process-entropy method-a technique for order preference by similarity to an ideal solution-grey relation analysis comprehensive evaluation algorithm is used to optimize TSRM. Finally, a prototype is manufactured, a hardware platform is built and static and dynamic experimental validations are carried out.

The sensitivity analysis reveals that parameters significantly impact the performance of TSRM. The results of multi-objective optimization show that the average electromagnetic force and smoothing coefficient after optimization are better than before, and the copper loss ratio reduces slightly. The experimental and simulated results of TSRM are consistent, which verifies the accuracy of TSRM.

In this paper, only three optimization objectives are selected in the multi-objective optimization process. To improve the performance of TSRM, the heating characteristics, such as iron loss, can be considered as the optimization objective for a more comprehensive analysis of TSRM performance.

A novel motor structure is designed, combining the advantages of the TSRM and the linear motor. The established sensitivity analysis rules are scientific and suitable for the effects of various parameters on motor performance. The proposed multi-objective optimization algorithm is a comprehensive evaluation algorithm. It considers subjective weight and objective weight and fully uses the original data and the relational degree between the optimization objectives.

To obtain better fatigue resistance for marine engineering equipment welded joints in the design stage, the design method of the marine engineering equipment welded joint design stage needs to be studied.

Based on the structural stress theory, a design method of the marine engineering equipment welded joints with better fatigue performance is proposed. The effectiveness of the method is demonstrated through the simulation analysis and fatigue test of typical marine engineering equipment welded joints.

Methods based on the theoretical advantages of structural stress and the principle of ensuring that the welded joint has a low degree of stress concentration.

The design method of marine engineering equipment welded joints proposed in this study provides a set of operable design routes for technicians, which can better meet the needs of engineering applications.

This research aims to study the materials that compose older reinforced concrete bridges which are damaged and degrading to explain the mechanisms and origins of various disorders. Therefore, this work will contribute to providing answers on the capacity of nondestructive evaluation method during the diagnosis. In addition to the characterization of affected structures, it will aim to provide effective solutions for different serious pathologies.

In this context, two bridges located on NH16 and NH21, respectively, were studied in Annaba city (north-east Algeria), specifically in El-Hadjar municipality located in the central industrial zone of Pont-Bouchet. This study makes it possible to make conclusions from the in-depth diagnosis based on disorders exposition causes and mechanical characteristics evolution by non-destructive testing (NDT) tools. Furthermore, solutions are proposed, including conservation maintenance of these degraded structures.

All degradations can be the result of several factors: either human (poor design) or chemical (surface water, wastewater and groundwater quality (acidic or basic)). In addition to other natural causes (geological formations, flood phenomena or climate), NDT tools play a major role in the evaluating mechanical performance of degraded structures (resistance and hardness).

The NDT techniques can be transmitted to civil engineering experts because their training is limited regarding mechanical and structural construction.

NDT tools are the most suitable for in-situ assessing, and the concrete constructions health state, so far from financial problems.

Degraded bridge diagnosis by NDT testing is necessary for a thorough safety evaluation (mechanical performance, strength and deformability), to protect human lives and design durability.

This is an original paper which contains new information at different scales and from special fields, based on an evaluation using NDT tools on real degraded structures. It can be used to improve the knowledge of materials employed in a bridge without performing expensive direct tests or the need for destroying it.

In this study, the application of a novel combined steel curved damper (SCD) and steel plate shear wall (SPSW) system in the 5-, 10- and 15-storey steel moment-resisting frames (SMR) subjected to earthquake excitation has been investigated. The proposed system is called here as the SMR-WD (steel moment resisting–wall damper).

At the beginning of this research, an SMR-W and an SMR-D are separately modeled in ABAQUS software and verified against the available experimental data. After that, three different heights SMR-WD systems (5-, 10- and 15-storey) are designed and simulated. Then, their performances are examined and compared to the corresponding SMR-W under the effects of six actual earthquake records.

The obtained results show that the proposed system increases the mean values of the base shear for 5-, 10- and 15-storey SMR-WD equal to 27, 20.15 and 16.51%, respectively compared to the corresponding SMR-W. Moreover, this system reduces the drift of the floors so that the reduction in the average values of maximum drift for 5-, 10- and 15-storey SMR-WD is equal to 10, 7 and 29%, respectively with respect to the corresponding SMR-W. The results also reveal that the considered system dissipates more energy than SMR-W so that the increase in the mean values of the energy absorption for 5-, 10- and 15-storey SMR-WD is 30.8, 25.6 and 41.3%, respectively when compared to the SMR-W. Furthermore, it is observed that SMR-WD has a positive effect on the seismic performance of the link beams and panel zones of the frames. By increasing the height of the structure in the SMR-WD, the energy dissipation and base shear force increases and the drift of floors decreases. Hereupon, the proposed SMR-WD system is more useful for tall buildings than SMR-W frames.

For the first time, the application of a novel combined steel curved damper (SCD) and steel plate shear wall (SPSW) system in the 5-, 10- and 15-storey steel moment-resisting frames (SMR) subjected to earthquake excitation has been investigated.

The main objective of this paper is to illustrate an analytical view of different methods of 3D bioprinting, variations, formulations and characteristics of biomaterials. This review also aims to discover all the areas of applications and scopes of further improvement of 3D bioprinters in this era of the Fourth Industrial Revolution.

This paper reviewed a number of papers that carried evaluations of different 3D bioprinting methods with different biomaterials, using different pumps to print 3D scaffolds, living cells, tissue and organs. All the papers and articles are collected from different journals and conference papers from 2014 to 2022.

This paper briefly explains how the concept of a 3D bioprinter was developed from a 3D printer and how it affects the biomedical field and helps to recover the lack of organ donors. It also gives a clear explanation of three basic processes and different strategies of these processes and the criteria of biomaterial selection. This paper gives insights into how 3D bioprinters can be assisted with machine learning to increase their scope of application.

The chosen research approach may limit the generalizability of the research findings. As a result, researchers are encouraged to test the proposed hypotheses further.

This paper includes implications for developing 3D bioprinters, developing biomaterials and increasing the printability of 3D bioprinters.

This paper addresses an identified need by investigating how to enable 3D bioprinting performance.

This study presents finite element (FE) and generalized regression neural network (GRNN) approaches for modeling multiple crack growth problems and predicting crack-growth directions under the influence of multiple crack parameters.

To determine the crack-growth direction in aluminum specimens, multiple crack parameters representing some degree of crack propagation complexity, including crack length, inclination angle, offset and distance, were examined. FE method models were developed for multiple crack growth simulations. To capture the complex relationships among multiple crack-growth variables, GRNN models were developed as nonlinear regression models. Six input variables and one output variable comprising 65 training and 20 test datasets were established.

The FE model could conveniently simulate the crack-growth directions. However, several multiple crack parameters could affect the simulation accuracy. The GRNN offers a reliable method for modeling the growth of multiple cracks. Using 76% of the total dataset, the NN model attained an R2 value of 0.985.

The models are presented for static multiple crack growth problems. No material anisotropy is observed.

In practical crack-growth analyses, the NN approach provides significant benefits and savings.

The proposed GRNN model is simple to develop and accurate. Its performance was superior to that of other NN models. This model is also suitable for modeling multiple crack growths with arbitrary geometries. The proposed GRNN model demonstrates its prediction capability with a simpler learning process, thus producing efficient multiple crack growth predictions and assessments.

In order to make the aperture of spatial deployable antenna larger, this paper proposed the study on a spatial annular tensegrity structure with 100 m large scale, which could be one of the ideal solutions to improve the dimension of the antenna. This study is aiming to figure out the dynamic characteristic of ultra-large annular tensegrity and address the problem of insufficient rigidity with local modes that many ring truss-type deployable antenna structures have faced.

This work is carried out based on the nonlinear dynamic modelling when fully considering the effect of bending and torsion deformation of beams, as well as the pretension of cables. Additionally, the structural stability analysis based on the proposed stability criterion is also presented to evaluate the tensegrity configuration with different distribution of cable groups.

This research results verify that the modified structure with radial ribs could eliminate the effect of the local vibration mode on stiffness and is suitable to meet the requirements of the annular tensegrity structure. Additionally, the calculation results demonstrate that the structural configuration of annular tensegrity with 36 groups of cables which share the nodes with radial ribs is more appropriate to enhance the stiffness and structural stability.

A new large annular tensegrity structure with radial ribs and tensioned cables is proposed. Based on the proposed structural configuration, the positive definiteness of the tangent stiffness matrix is carried out as the criterion of stability and the composition of the analytical expression of the tangent stiffness matrix is analyzed. Four levels of tensegrity structure stability have been carried out and the influence of the structural parameters on the stability and the rigidity has been analyzed. A scaled-down prototype is developed to verify the feasibility of the design of the hoop-column-rib configuration by the deployment and dynamic experiment.