Joint Design Research Articles

Thermo-Mechanical Coupled Analysis of Electric Vehicle Drive Shafts

With the growing concerns over global warming and abnormal weather patterns, the development of eco-friendly technologies has emerged as a critical research area in the transportation industry. In particular, the global automotive market, one of the most widely used sectors, has witnessed a surge in research on electric vehicles (EVs) in line with these trends. Compared to traditional internal combustion engine vehicles, EVs require components with high strength and durability to achieve optimal performance. This study focuses on the development of a constant velocity (CV) joint, a critical component for reliably transmitting the maximum output of an electric vehicle motor. Unlike conventional numerical methods, the proposed thermo-mechanical coupled analysis simultaneously accounts for thermal and mechanical interactions, providing more realistic operational performance predictions. This analysis, conducted using the thermal modules of Ls-Dyna and ANSYS Mechanical, effectively simulated field operation scenarios. Prototype testing under simulated conditions showed a 6% discrepancy compared to numerical predictions, validating the high accuracy and reliability of the proposed method. This robust thermo-mechanical coupled analysis is expected to improve the durability and reliability of CV joint designs, advancing electric vehicle component development.

Generative Design Method for Single-Layer Spatial Grid Structural Joints

Single-layer spatial grid joints are crucial to structural safety, with commonly used welded hollow spherical joints and cast steel joints. However, these traditional joints face limitations, including a rigid design, excessive weight, and susceptibility to stress concentration. As engineering practices advance, these joints struggle to meet modern requirements. This paper introduces a generative method for designing rigid joints in single-layer spatial grid structures, based on Audze space-filling criteria. The method’s mathematical formulation is presented, followed by developing novel joint configurations by exploring various cross-sectional forms, retention mass, and geometric elements, while considering bending moments. A comparative analysis of static properties between the new and traditional joints shows promising results. The generative approach demonstrates significant innovation, producing lightweight, aesthetically pleasing, and structurally efficient joints. Compared to conventional welded hollow spherical joints, the new joints exhibit a 57% reduction in self-weight, a 51% decrease in maximum equivalent stress, and a 24% reduction in maximum displacement. This method enables versatile and optimized joint design for single-layer spatial grid structures, offering enhanced strength, safety, and aesthetic appeal.

Study of Generative Design Using Autodesk Fusion 360

Abstract: This study explores the use of generative design in Autodesk Fusion 360 for improving knuckle joint design. By applying generative design principles, we created optimized designs specifically for additive manufacturing, which showed a significant reduction in von Mises stress compared to conventional designs. These results highlight the ability of generative design to develop structures that are more efficient and better suited for specific manufacturing processes. Overall, our findings suggest that generative design can optimize knuckle joints by lowering stress, reducing weight through careful material selection, and improving stiffness, offering valuable benefits for mechanical applications.

Full-scale testing of the bending behaviour of UHPC gravity–grouted sleeve–prestressed anchor joints in assembled frame tunnels

Joints are weak parts of a prefabricated tunnel frame structure, and the joint bending resistance is a crucial factor controlling the deformation and bearing capacity of the tunnel structure. This study proposes a joint with dual anchoring of ultrahigh-performance concrete (UHPC) gravity-grouted sleeves and prestressed steel reinforcement. The material strain, opening amount, deflection, stiffness, rotation angle, and ductility of the grouted sleeve-prestressed anchor joint and grouted sleeve joint types were tested through full-scale bending tests, and with the help of noncontact measurement technology, the dynamic process of joint bending failure was captured. In addition, the finite element method was used to evaluate the influences of the prestressing magnitude and the position of the prestressing steel bars on the bending performance of the joints. The results indicate that the damage to the concrete joint is concentrated at the top of the joint and that the damage to the top surface of the joint concrete is distributed in an "m" shape, indicating that the damage to the concrete in the area between the sleeves is relatively extensive. Owing to the turning points of grouting material fracture and joint yielding, the joint bending process clearly shows a three-stage change. The grouted sleeve-prestressed anchor joint exhibits greater bending stiffness than the grouted sleeve joint does, and the slip of the grouting material in the sleeve is smaller. Prestressing plays a key role in enhancing the bearing capacity and deformation resistance of joints. Considering that excessive prestress may increase the brittleness of the structure, the prestress of the grouted sleeve-prestressed anchor joint is recommended to be 200 kN. This study provides theoretical support for the joint design and construction of prefabricated tunnel frame structures.

Analysis of the Influence of Adhesive, Geometry, and Manufacturing Processes on Mixed Mode Stress Ratio in Single Lap Shear Adhesive Joint Structures of Aluminum and Composite Plates

In aircraft structures, composite plate joints often present significant challenges. Mechanical fastenings such as pins, bolts, or rivets require holes to be drilled in the plates, which reduces the strength of the laminate due to stress concentrations around the hole edges. These joints frequently become sources of structural failure in aircraft. Therefore, the design of composite plate joints is crucial to maintain structural integrity. Adhesive joints offer several advantages over mechanical joints, including the ability to join two different materials, more uniform stress distribution along the joint, and reduced weight since no bolts or rivets are needed. The most common adhesive joint design is the Single Lap Joint (SLJ), which is popular due to its simple geometry and high structural efficiency. However, the main drawback of the SLJ is load eccentricity, which leads to secondary bending and undesirable normal stresses along the adhesive edges. The hypothesis of this study is that SLJ conditions with optimal shear strength can be achieved through the right combination of adhesive type, bond surface preparation, and joint configuration. This study analyzes the influence of various adhesive materials, joint designs, and manufacturing methods using numerical modeling methods, validated with analytical approaches and ASTM standard testing. Numerical modeling is conducted using the finite element method with a cohesive zone model (CZM) approach to examine stress distribution in various cases, such as the impact of geometry, adhesive thickness, and joint length. The normal and shear stress distribution along the joint is found to significantly affect the strength of the SLJ, highlighting the importance of careful design and material selection in these applications.

Multiple-Input Multiple-Output Synthetic Aperture Radar Waveform and Filter Design in the Presence of Uncertain Interference Environment

Multiple-input multiple-output synthetic aperture radar (MIMO-SAR) anti-jamming waveform design relies on accurate prior information about the interference. However, it is difficult to obtain accurate prior knowledge about uncertain intermittent sampling repeater jamming (ISRJ), leading to a severe decline in the detection performance of MIMO-SAR systems. Therefore, this article studies the robust joint design problem of MIMO radar transmit waveform and filter against uncertain ISRJ. We characterize two categories of uncertain interference, including sample length uncertainty and sample-time uncertainty, modeled as Gaussian distribution in different range bins. Based on the uncertain interference model, we formulate the maximizing SINR as a figure of merit, which is a non-convex quadratic optimization problem under specific waveform constraints. Based on the alternating direction method of multipliers (ADMM) framework, a novel joint design algorithm of waveform and filter is proposed. In order to improve the convergence performance of ADMM, the difference in convex functions (DC) programming is applied to the ADMM iterations framework to solve the problem of waveform energy inequality constraint. Finally, numerical results demonstrate the effectiveness and robustness of the proposed method, compared to the existing methods that utilize deterministic interference models in the uncertain ISRJ environment. Moreover, the spaceborne SAR real scene imaging simulations are conducted to evaluate the anti-ISRJ performance.

Joint Design and Pricing Problem for Symbiotic Bioethanol Supply Chain Network: Model and Resolution Approach

To fight climate change, the Province of Quebec, Canada, has set targets to reduce greenhouse gas emissions by reducing fossil fuel consumption and integrating biofuel content into gasoline and diesel fuel. Motivated by a real-world case study, this paper presents a novel distributed decision model for designing a symbiotic supply chain network and supporting pricing decisions. A distributed decision-making problem is formulated as a game theoretic approach considering a Stackelberg–Nash equilibrium. A novel mathematical model is proposed to support the decisions of four actors: corn farms, processing depots, pig farms, and biorefineries. In addition to the configuration of a biofuel-based industrial symbiosis, the model offers the possibility of setting purchase prices and supply levels for biomass (corn stover supplied by farms), as well as determining sales prices and production levels for the main product (the cellulosic sugar used for the bioethanol production) and a coproduct (pig feed sold to pig farmers). A three-step optimization process involving the user is proposed to address the computational challenges posed by large design problem instances. The case study of the Province of Quebec is used to evaluate the performance of the proposed resolution approach.

Multi-objective optimization for active IRS-aided multi-group multicast systems with energy harvesting, integrated sensing and communication

In this paper, we utilize an active intelligent reflecting surface (IRS) to assist wireless systems with multiple functionalities, including multi-group (MG) multicast (MC) transmission, integrated sensing and communication (ISAC) and wireless energy harvesting. Specifically, a multi-antenna base station (BS) simultaneously transmits communication signals to MG MC users and sensing signals towards targets, while other users can harvest energy from the received radio frequency signals. We formulate the joint design of the BS transmit precoders (TPs) and the IRS reflection coefficients (RCs) as multi-objective optimization problems (MOOPs) in which the objective functions of the sum rate maximization (SRM) and sum harvested energy maximization (SHEM) are considered under the constraints of transmit power at the BS, amplitude and power amplifications at the active IRS, minimum achievable rate of communication users (CUs), minimum harvested energy of energy harvesting users (EHUs), and beamforming pattern similarity for sensing. To tackle the nonconvexity characteristics of the formulated design problems, we leverage alternating optimization (AO) frameworks to decompose the original problems into subproblems. In the subproblems, we seek appropriate surrogate functions by following majorization–minimization (MaMi) techniques to convert the subproblems into convex ones. Then, iterative algorithms are developed to obtain the optimal BS TPs and IRS RCs. The numerical simulations are carried out to validate the effectiveness of the proposed methods. The numerical results also reveal useful insights in the tradeoffs between the performance metrics and demonstrate the superior performance of systems with an active IRS in comparison with those without an IRS or with a passive IRS.

Compression-shear capacity of circumferential joint with dowel in shield tunnel: From experiments to analytical solution

Dislocations of circumferential joints are commonly prevalent in shield tunnels. Generally, the displacement space of bolt in rigid segment joint is very small. When the dislocation of the circumferential joint is large, plastic deformation of the bolts or concrete crushing is inevitable, which will affect the service life of the shield tunnel. The flexibility of the joint can be achieved by embedding in a dowel, which can reduce the damage of the segment joint during the misalignment of the circumferential joint. However, the addition of the dowel changes the structure of the circumferential joint. At present, the shear bearing capacity of the circumferential joint, affecting the design, safety verification, and service performance evaluation, cannot be accurately calculated through the existing mechanical models. Therefore, the envelope curves of the shear bearing capacity of the circumferential joint with dowel were investigated in this paper. Firstly, a series of shear resistance experiments were conducted to clarify the failure characteristics of the circumferential joint with the dowel. Subsequently, based on the experimental results, several shear mechanical calculation models for the circumferential joint were proposed. And the analytical method for the envelope curves between axial force (N) and shear force (Q) was derived. Finally, the accuracy of the analytical method was verified, and corresponding optimization methods to improve the bearing performance of the circumferential joint were proposed. The research results indicate that the circumferential joint with dowel has both concrete shear stage and steel rebars shear stage. The N-Q envelope curves is determined by the combination of concrete, connectors (including the dowel and the bolt), and steel rebars, and the leading factor can be clarified by the proposed method. A constructive conclusion has been found that the optimization design of the circumferential joint must consider the axial force in order to effectively improve its shear bearing performance. The research results can serve the joint optimization, load-bearing verification during design process, and the physical model in big data analysis during the operation and maintenance of the shield tunnel.

Experimental and numerical analysis of geometry on joint strength in GFRP-aluminum alloy adhesive joints

Enhancing the bonding strength between composites and metals is one of the urgent challenges that needs to be addressed. One of the methods to improve the strength of adhesive joints is to change the geometry of the joints. In this paper, four different types of aluminum alloy sleeves were developed by designing grooves with varying angles and shapes. Glass fiber reinforced polymer rods were adhesively bonded to these sleeves, resulting in the preparation of five different types of adhesive joints, including a conventional structure. The mechanical performance and failure mechanisms of these joints were analyzed experimentally and numerically. The results indicate that, compared to conventional adhesive joints, the load-bearing capacity of the four designed adhesive joints has been significantly improved, with a maximum increase of 49.6% and a minimum increase of 35.6%. The axial angle of the groove structures designed within the joint is a factor that influences the ultimate load capacity of the joint. Furthermore, the shear stress in the adhesive layer is identified as the primary cause of adhesive layer failure. The designed mechanical interlocking structures can not only increase the interfacial bonding force between the adhesive layer and the substrate but also delay the complete failure of the adhesive layer, thereby improving the load-bearing strength of the joint. This work is expected to provide new insights for the design of composite and metal joints.

Analytical model for cyclic behavior of cold-formed steel bolted connection frames considering local buckling

Cold-formed steel (CFS) structures are increasingly popular in the construction industry due to their high strength-to-weight ratio, ease of fabrication, and cost-effectiveness. This study focuses on the development of a detailed mathematical model to accurately simulate the cyclic behavior of CFS moment-resisting bolted connection frames, particularly considering the local buckling of connected frames. Bolted joints are preferred in thin-walled CFS structures over welded joints due to their ease of installation and adaptability in seismic design, relying on slip and bearing mechanisms of bolts to accommodate inelastic deformations and dissipate energy during seismic events. The proposed model incorporates these mechanisms and validates them against experimental data and refined finite element analyses. Significant findings highlight the importance of the balanced number and arrangement of bolts in preventing excessive bolt slip and premature buckling. This research provides a robust analytical tool for optimizing bolted joint designs in CFS bolted connection frames, contributing to safer and more resilient CFS structures in seismic regions. The model’s computational efficiency further enhances its practicality for engineers and researchers.

Loading mechanism of timber screw–adhesive composite joint

The impact of carbon emission and other pollution generated by the construction industry on the natural environment and ecosystems is immeasurable. Wood, as a renewable building material with excellent performance, is a practical solution for future low-carbon buildings. Current screwed wood connections have good ductility, but the initial stiffness is relatively low. In this paper, composite wood connections with screw and adhesive were proposed and investigated. Static loading tests were conducted to screwed connections and composite connection specimens. The failure modes of different connection types, as well as the effects of adhesive type and adhesive connection area on the joint bearing capacity are discussed. The results show that the yield load and ultimate load of the composite joint made with the existing adhesive increased by up to 169% and 222%, respectively, compared with the screw connection. At the same time, the influence of curing time and bonding should also be taken into consideration. This study provides a foundation for wood joint design and promotes the sustainable development of the building industry.

Effectiveness of Ankle-Foot Orthoses for Patients with Weakness of the Plantarflexors and Dorsiflexors: Biomechanical Comparison of Different Orthotic Concepts

Abstract Introduction Weakness of plantarflexor and dorsiflexor muscles is a complex individual condition and can result in pathological gait, such as crouch gait or knee hyperextension. Affected patients can be supported with ankle-foot orthoses (AFOs) to improve gait and safety. Objective This study aims to compare three orthotic ankle joint designs in AFOs for patients with muscle weakness in the plantarflexors and/or dorsiflexors: a conventional hinged ankle joint with rigid stops (CAJ), a jointless orthosis (JLO), and a reactive-dynamic ankle joint with adjustable spring modules (RDA). Study Design Seven patients with plantarflexor and/or dorsiflexor muscle weakness tested three orthosis configurations in randomized order during a single session. Methods Biomechanical gait analysis was performed during standing and walking on level ground and up and down 10° slopes. The main outcomes were ground reaction forces, joint angles, moments, and power at the ankle, knee, and hip joints. Mean values of outcome measures for patients and values of an able-bodied control group were compared with nonparametric analyses of variance and pairwise post hoc tests. Results Throughout all motion tasks, statistically significant differences (P < 0.05) were predominantly found in ankle and knee joint kinematics between RDA and CAJ, as well as between JLO and CAJ, whereas only few differences were found between RDA and JLO. Conclusions For this patient group, RDA enabled the most physiological gait, with outcomes measure values closest to those of the able-bodied control group, and the best perception of support for an active lifestyle and physically demanding activities. In less physically demanding situations, such as short walking distances and even surfaces, JLO also showed sufficient support for physiological gait and may be an adequate orthosis for patients living with supportive infrastructure or a more sedentary lifestyle. CAJ restricted physiological movements, showed the highest deviations from the values of the able-bodied controls in most activities, and provides the least comfort for patients in the tested situations. Clinical Relevance Statement Determining the best possible orthotic care and support for different patient groups is essential to enable independence, safety, and comfort during activities of daily living based on individual requirements.

Joint Design of Pilot Power and Phase Shifts in RIS-Aided Cell-Free Massive MIMO URLLC Systems

Joint Design of Pilot Power and Phase Shifts in RIS-Aided Cell-Free Massive MIMO URLLC Systems

Experimental investigation and analytical modeling of steel falsework systems

This research paper presents a comprehensive experimental program aimed at investigating the behavior and capacity of steel falsework systems, with a specific focus on two popular systems, Ringlock and Cuplock. The primary objective of this study is to provide a thorough understanding of the mechanical properties exhibited by falsework systems and to develop accurate analytical models for their design. To achieve this goal, a series of full-scale tests were conducted on various joint configurations to examine their capacities and deformation characteristics. The obtained experimental results are meticulously analyzed and compared against existing design codes. Emphasis is placed on the behavior of falsework systems, highlighting the significance of precise joint design and analysis. Based on the findings, it is recommended to employ an equivalent length factor for different loading scenarios. For internal verticals, a factor of 0.95 is suggested, while edge verticals range from 1.50 to 1.73, and corner verticals reach a factor of 2.04. In the case of one-lift verticals under edge loading conditions, an effective length factor of 1.31 is proposed. Furthermore, a proposed stiffness four-linear model is introduced, which accurately captures the semi-rigid behavior of these joints for both Ringlock and Cuplock systems. To validate the experimental results and ensure their reliability, a finite element model was developed using the proposed four-linear model for joints. The comparison between the experimental and numerical results demonstrates excellent agreement and a perfect match, further reinforcing the validity of the experimental findings. By providing a comprehensive understanding of the mechanical properties and behavior of falsework systems, this study contributes to the development of accurate analytical models for their design. The proposed equivalent length factors and stiffness four-linear models offer practical insights for designers and engineers working with Ringlock and Cuplock systems.

Influence of Column–Base Connections on Seismic Behavior of Single-Story Steel Buildings

This study focuses on assessing the seismic performance of existing single-story steel buildings used as industrial buildings. This research aims to provide a systematic procedure for evaluating the seismic response of a single-story strategic building and properly accounting for the behavior of the column–base joints. Through meticulous data collection, advanced numerical modeling, and pushover analyses, this study highlights the significant impact of column–base joint behavior on the overall seismic performance of industrial buildings. The findings reveal that while single-story steel buildings show a satisfactory seismic performance in terms of lateral resistance and stiffness in the longitudinal direction, deficiencies in the joint design can strongly impact the performance in the transversal direction. This study emphasizes the necessity of incorporating joint flexibility into numerical analyses to accurately assess structural behavior. In conclusion, a precise assessment of the base joints provides insights for informing retrofitting strategies.

ANN prediction of mode I fracture energy in epoxy adhesive joints: Adherend, adhesive, and strain rate effects

In this investigation, the mode I fracture behavior of an epoxy adhesive joint has been investigated to probe the combined effects of adherend Young's modulus and thickness, strain rate, and adhesive length. Experimental fracture testing was conducted on double-cantilever beam (DCB) specimens under three various strain rate thresholds, namely, quasi-static (0.0005 s−1), low (0.015 s−1), and intermediate (0.5 s−1). The specimens were constructed with varying adherend materials (i.e., copper, aluminum), thickness (12–20 mm), and adhesive lengths (25–75 mm). The fracture load was measured in each experiment, and the critical strain energy release rate, JCi, was calculated via a finite element analysis (FEA) in each case. Results with a 95 % confidence interval showed adherend thickness had a negligible effect within the investigated range (p-value = 0.462). JCi was significantly impacted by adhesive length (p-value = 0.009) and two other investigated parameters (p-values = 0.000). The development of artificial neural networks (ANNs) with Levenberg-Marquardt (LM) led to the prediction of JCi based on the examined parameters. With a mean absolute percentage error (MAPE) of 8.9 % and a mean squared error (MSE) of 683 J2/m4 on unseen test data, the ANN model built in this study was able to predict the JCi in epoxy adhesive joints, indicating its potential to produce an accurate prediction for JCi in epoxy adhesive joints. This work offers insights for precise fracture behavior prediction under mode I stress conditions as well as some helpful information that can be utilized to optimize adhesive joint design.

RIS-aided integrated sensing and communication: Beamforming design and antenna selection

This work considers an integrated sensing and communication system, where a reconfigurable intelligent surface (RIS) is utilized to manage interference and radar signals. The sensors are attached to the RIS to sense multiple targets. A joint design of the base station transmit beamforming and RIS phase shift matrix is proposed to minimize total interference and maximize the worst received signal power at the RIS sensors. Due to highly coupled transmit beamforming and RIS phase matrices, the optimization problem is decoupled into two subproblems and solved iteratively by semidefinite programming and a manifold-based Riemannian steepest descent algorithm. We further design energy-aware beamforming to eliminate the interference induced by radar probing signals. Antenna selection with the ℓ0 norm is introduced to exclude redundant antennas while maintaining the sufficient multiple beams for multiple users and targets with minimized required antennas. Due to the nonconvexity of the ℓ0-norm, we relax the number of active transmit antennas as a weighted ℓ1-norm and employ a concave approximation for the constraint on the radar beampattern. Numerical results illustrate that the proposed algorithms can effectively reduce interference and strengthen the received signal power for radar sensing, achieving mutual benefit for communication and sensing performance.

Joint Design of Altitude and Channel Statistics Based Energy Beamforming for UAV-Enabled Wireless Energy Transfer

In recent years, UAV-enabled wireless energy transfer (WET) has attracted significant attention for its ability to provide ground devices with efficient and stable power by flexibly navigating three-dimensional (3D) space and utilizing favorable line-of-sight (LoS) channels. At the same time, energy beamforming utilizing multiple antennas, in which energy beams are focused toward devices in desirable directions, has been highlighted as a key technology for substantially enhancing radio frequency (RF)-based WET efficiency. Despite its significant utility, energy beamforming has not been studied in the context of UAV-enabled WET system design. In this paper, we propose the joint design of UAV altitude and channel statistics based energy beamforming to minimize the overall charging time required for all energy-harvesting devices (EHDs) to meet their energy demands while reducing the additional resources and costs associated with channel estimation. Unlike previous works, in which only the LoS dominant channel without small-scale fading was considered, we adopt a more general air-to-ground (A2G) Rician fading channel, where the LoS probability as well as the Rician factor is dependent on the UAV altitude. To tackle this highly nonconvex and nonlinear design problem, we first examine the scenario of a single EHD, drawing insights by deriving an optimal energy beamforming solution in closed form. We then devise efficient methods for jointly designing altitude and energy beamforming in scenarios with multiple EHDs. Our numerical results demonstrate that the proposed joint design considerably reduces the overall charging time while significantly lowering the computational complexity compared to conventional methods.

Resource Allocation in UAV-D2D Networks: A Scalable Heterogeneous Multi-Agent Deep Reinforcement Learning Approach

In unmanned aerial vehicle (UAV)-assisted device-to-device (D2D) caching networks, the uncertainty from unpredictable content demands and variable user positions poses a significant challenge for traditional optimization methods, often making them impractical. Multi-agent deep reinforcement learning (MADRL) offers significant advantages in optimizing multi-agent system decisions and serves as an effective and practical alternative. However, its application in large-scale dynamic environments is severely limited by the curse of dimensionality and communication overhead. To resolve this problem, we develop a scalable heterogeneous multi-agent mean-field actor-critic (SH-MAMFAC) framework. The framework treats ground users (GUs) and UAVs as distinct agents and designs cooperative rewards to convert the resource allocation problem into a fully cooperative game, enhancing global network performance. We also implement a mixed-action mapping strategy to handle discrete and continuous action spaces. A mean-field MADRL framework is introduced to minimize individual agent training loads while enhancing total cache hit probability (CHP). The simulation results show that our algorithm improves CHP and reduces transmission delay. A comparative analysis with existing mainstream deep reinforcement learning (DRL) algorithms shows that SH-MAMFAC significantly reduces training time and maintains high CHP as GU count grows. Additionally, by comparing with SH-MAMFAC variants that do not include trajectory optimization or power control, the proposed joint design scheme significantly reduces transmission delay.