Characteristics Of Joints Research Articles

Changes of bone and articular cartilage in broilers with femoral head necrosis

Femoral head necrosis (FHN) in broilers is a common leg disorder in intensive poultry farming, giving rise to poor animal health and welfare. Abnormal mechanical stress in the hip joint is a risk factor for FHN, and articular cartilage is attracting increasing attention as a cushion and lubrication structure for the joint. In the present study, broilers aged 3 to 4 wk with FHN were divided into femoral head separation (FHS) and femoral head separation with growth plate lacerations (FHSL) groups, with normal broilers as control. The features of the hip joint, bone, and cartilage were assessed in FHN progression using devices including computed tomography (CT), atomic force microscope (AFM), and transmission electron microscopy (TEM). Broilers with FHN demonstrated decreased bone mechanical properties, narrow joint space, and thickened femoral head stellate structures. Notably, abnormal cartilage morphology was observed in FHN-affected broilers, characterized by increased cartilage thickness and rough cartilage surfaces. In addition, as FHN developed, cartilage surface friction and friction coefficient dramatically increased, while cartilage modulus and stiffness decreased. The ultramicro-damage occurred in chondrocytes and the extracellular matrix (ECM) of cartilage. Cell disintegration, abnormal mitochondrial accumulation, and oxidative stress damage were observed in chondrocytes. A notable decline in cartilage collagen content was observed in ECM during the initial stages of FHN, accompanied by a pronounced reduction in collagen fiber diameter and proteoglycan content as FHN progressed. Furthermore, the noticeable loosening of the collagen fiber structure and the appearance of type I collagen were noted in cartilage. In conclusion, there was a progressive decrease in bone quality and multifaceted damage of cartilage in the femoral head, which was closely linked to the severity of FHN in broilers.

Influence of material position and tool axis offset on the stir zone material flow and joint integrity of friction stir welded dissimilar AA5083 and AA7050 alloys

The present investigation aims to establish the influence of tool axis offset and the relative position of materials on the stir zone (SZ) material flow and joint characteristics of friction stir (FS) butt welded dissimilar AA5083-H111 and AA7050-T7651 aluminium alloys. The FS welding trials were conducted by systematically varying the tool axis offset from zero to 1 mm, with an increment of 0.25 mm, to both the advancing side (AS) and retreating side (RS) of the joint by keeping AA7050 and AA5083 alloys at the AS and RS of the joint, respectively. The welding speed, tool rotational speed, axial force and tool tilt angle were held constant. The results showed that for the given relative position of the alloys, the tool axis offset has significant influence on the SZ material flow pattern and the evolution of microstructure in the joint zone. The microhardness has a heterogeneous distribution across the joint and it is found to be sensitive to the tool axis offset. The highest hardness values are observed for the joints FS welded at 1 mm tool axis offset to the AS and the lowest for the joints welded at 1 mm tool axis offset to the RS of the joint. The joint fabricated at 0.5 mm tool axis offset to the AS has exhibited the highest joint strength of 303 MPa (joint efficiency of 98.4 %). Also, within the limits of tool axis offset experimented, the joint integrity is less sensitive to the variation of tool axis offset to both the AS and RS of the joint. The softening of the HAZ on the weaker AA5083 alloy side (for high heat generation cases) and the weakening of the SZ towards the bottom (for low heat generation cases) are the main factors limiting the joint strength. The studies showed that in FSW of dissimilar 5xxx and 7xxx alloys, appropriate selection of tool axis offset and relative position of the alloys are critical for producing joints with excellent joint efficiency.

Exploration of the behavior and evolution features of beam-column joints with T-stub using the structural strain energy method

Based on the structural strain energy method, the work behavior of four T-stub connection joints under cyclic loading is analyzed to visualize their working behavior and failure evolution. The experimental strain data are modeled as generalized strain energy density (GSED) to characterize the structural stress state and the corresponding characteristic parameters, and the Mann-Kendall (M-K) criterion is formulated to determine the performance characteristic points (P and Q) of the joint Mj-Ej curves and to derive the starting point of structural continuity damage. Then, by analyzing the parameters of the joint working state (strain, deformation, joint energy dissipation, connection stiffness, bolt force and pry force), the trends of the joint stressing state curves before and after the critical loading are reflected. Finally, the feature point data interpolation (EDI) method is introduced to effectively expand the joint test data, visualize the change process of the strain/stress field, and deeply reveal the mechanical response mechanism and evolutionary degradation law behind it. The contribution of the above work is to quantitatively identify the P and Q characteristic points in the changing trend of the joint working state, to reveal the mechanical mechanism and the failure degradation law from the perspective of energy evolution, and to visualize the mutation of the field data before and after the P/Q using the EDI method, which is a generalized method that can be applied to the other progressive failure structures.

Erratum to: An Experimental Study of the Effects of Filling Degree on Shear Behavior and Acoustic Emission Characteristics of Kaolinite-Filled Granite Joints

Erratum to: An Experimental Study of the Effects of Filling Degree on Shear Behavior and Acoustic Emission Characteristics of Kaolinite-Filled Granite Joints

Automatic defect detection for electrofusion joints of high-density polyethylene via spatial sequence to sequence attention neural network

High-density polyethylene pipelines have been widely used in various industries owing to their inherent advantages, such as resistance to harsh environments. However, a variety of defects are caused by welding process such as electrofusion technology. Therefore, detecting defects is necessary to guarantee welding quality and safety. The existing methods of detecting defects mainly neglect the internal spatial characteristics and depend on many rules. In this paper, detecting defect is regarded as a sequence labelling problem, and a novel spatial sequence to sequence attentive neural network is proposed to automatically identification defects via the natural spatial features of electrofusion joint. The proposed network utilizes the relative position between the neighbour resistance wire and possible defect to generate the vector representation, and expands the vectors through multivariate Gaussian probability distribution to highlight the vital sequence features related to defect. Self-attention is employed to capture the prominent distinguishing information between normal resistance wire and possible defect. The experimental results on the actual dataset collecting from electrofusion joints of high-density polyethylene illustrate that expanded vector is useful to focus on crucial features and self-attention promotes the identification ability of the proposed network, achieving the F1-score of 92.28 %.

Study on Shear Mechanical Characteristics of Rock Joints Under Different Anchorage Lengths

Study on Shear Mechanical Characteristics of Rock Joints Under Different Anchorage Lengths

Study on the failure mechanism and mechanical properties of multi-layer hole-drilled self-piercing riveted three-layer steel/aluminum hybrid joints

To promote the application of the three-layer steel/aluminum hybrid sheet in the lightweight vehicle body, the multi-layer hole-drilled self-piercing riveting (MH-SPR) process is proposed. This paper aims to investigate the failure mechanism and mechanical properties of three-layer MH-SPR joints and explore the effects of overlap type and pre-drilled layer on forming quality, mechanical properties, failure modes, and fracture characteristics of the three-layer MH-SPR joint in detail. Three overlap types (e.g., type A, type B, and type C) and three pre-drilled layers (e.g., J0, J1, and J2) are designed for the experimental study and the shear experiments and full-field strain measurements are carried out. The results show that the pre-drilled layer can improve SPR joinability and reduce the peak force and energy consumption during the riveting process. Overlap types A and C can increase the peak force of the joint and type C can simultaneously enhance the peak force and energy absorption of the joint. The increase in the pre-drilled layer can increase the peak force and energy absorption of the joint. The overlap types and pre-drilled layers change the failure modes of the joints, which include five types of failure modes: middle sheet tearing, top sheet tearing, rivet fracture, interlock failure, and mixed failure. Full-field strain analysis shows that the overlap type improves the mechanical properties of the joints by altering the deformation mode of the steel sheet. This work provides a theoretical basis for expanding the industrial practice of the MH-SPR process and improving the joined quality of the three-layer joint.

Intelligent ankle–foot prosthesis based on human structure and motion bionics

The ankle–foot prosthesis aims to compensate for the missing motor functions by fitting the motion characteristics of the human ankle, which contributes to enabling the lower-limb amputees to take care of themselves and improve mobility in daily life. To address the problems of poor bionic motion of the ankle–foot prosthesis and the lack of natural interaction among the patient, prosthesis, and the environment, we developed a complex reverse-rolling conjugate joint based on the human ankle–foot structure and motion characteristics, the rolling joint was used to simulate the rolling-sliding characteristics of the knee joint. Meanwhile, we established a segmental dynamics model of the prosthesis in the stance phase, and the prosthetic structure parameters were obtained with the optimal prosthetic structure dimensions and driving force. In addition, a carbon fiber energy-storage foot was designed based on the human foot profile, and the dynamic response of its elastic strain energy at different thicknesses was simulated and analyzed. Finally, we integrated a bionic ankle–foot prosthesis and experiments were conducted to verify the bionic nature of the prosthetic joint motion and the energy-storage characteristics of the carbon fiber prosthetic foot. The proposed ankle–foot prosthesis provides ambulation support to assist amputees in returning to social life normally and has the potential to help improve clinical viability to reduce medical rehabilitation costs.

Multi‐scale skeleton simplification graph convolutional network for skeleton‐based action recognition

AbstractHuman action recognition based on graph convolutional networks (GCNs) is one of the hotspots in computer vision. However, previous methods generally rely on handcrafted graph, which limits the effectiveness of the model in characterising the connections between indirectly connected joints. The limitation leads to weakened connections when joints are separated by long distances. To address the above issue, the authors propose a skeleton simplification method which aims to reduce the number of joints and the distance between joints by merging adjacent joints into simplified joints. Group convolutional block is devised to extract the internal features of the simplified joints. Additionally, the authors enhance the method by introducing multi‐scale modelling, which maps inputs into sequences across various levels of simplification. Combining with spatial temporal graph convolution, a multi‐scale skeleton simplification GCN for skeleton‐based action recognition (M3S‐GCN) is proposed for fusing multi‐scale skeleton sequences and modelling the connections between joints. Finally, M3S‐GCN is evaluated on five benchmarks of NTU RGB+D 60 (C‐Sub, C‐View), NTU RGB+D 120 (X‐Sub, X‐Set) and NW‐UCLA datasets. Experimental results show that the authors’ M3S‐GCN achieves state‐of‐the‐art performance with the accuracies of 93.0%, 97.0% and 91.2% on C‐Sub, C‐View and X‐Set benchmarks, which validates the effectiveness of the method.

Deflection and stress characteristics of single lap joint (adhesively bonded) theoretical analysis and experimental verification

The adhesively bonded single-lap joint strength is computed numerically and verified with the experiment. An ABAQUS model is prepared to analyze by adding the primary information, i.e., geometry, material properties, element, and solution type, including the boundary conditions. The model accuracy has been verified through two-step comparisons with published numerical deflection data and in-house experiments. The validated model is used to compute the energy-absorbing capacity better to understand lap joint strength. Further, the statistical analysis (variance-based sensitivity analysis) is conducted to measure the model output variability with the model input parameter. Additionally, the influences of geometry and property-dependent design parameters (layup schemes, loading position, adherend thickness ratio (L/t), and adhesive thickness ratio: (a/h), including the overlapping length (25, 30, 35, and 40 mm) are examined through several examples. The conclusions on the overlap length in bonded joints are that an increase in intact/lap length improves the joint stiffness and decreases the deflection. Similarly, a few insights on layer sequence (angle-ply) and shear stress thickness ratio are discussed in detail.

Artificial intelligence detects awareness of functional relation with the environment in 3 month old babies

A recent experiment probed how purposeful action emerges in early life by manipulating infants’ functional connection to an object in the environment (i.e., tethering an infant’s foot to a colorful mobile). Vicon motion capture data from multiple infant joints were used here to create Histograms of Joint Displacements (HJDs) to generate pose-based descriptors for 3D infant spatial trajectories. Using HJDs as inputs, machine and deep learning systems were tasked with classifying the experimental state from which snippets of movement data were sampled. The architectures tested included k-Nearest Neighbour (kNN), Linear Discriminant Analysis (LDA), Fully connected network (FCNet), 1D-Convolutional Neural Network (1D-Conv), 1D-Capsule Network (1D-CapsNet), 2D-Conv and 2D-CapsNet. Sliding window scenarios were used for temporal analysis to search for topological changes in infant movement related to functional context. kNN and LDA achieved higher classification accuracy with single joint features, while deep learning approaches, particularly 2D-CapsNet, achieved higher accuracy on full-body features. For each AI architecture tested, measures of foot activity displayed the most distinct and coherent pattern alterations across different experimental stages (reflected in the highest classification accuracy rate), indicating that interaction with the world impacts the infant behaviour most at the site of organism~world connection.

Tribological and mechanical properties of FSW joints of untainted stainless steel and titanium: novel characterization of similar and dissimilar joints

Friction Stir Welding (FSW) is an emerging solid-state welding process that joins dissimilar or similar metals based on requirements. The additional material to make the joint is also a weight reduction factor deemed vital in weight-sensitive industries like aerospace and orthopedic applications. The similar and dissimilar Ti-6Al-3Nb-2Zr-1Mo (Ti6321) and stainless steel (SS 310) joints are performed through friction stir welding. This investigation aims to identify the effect of process parameters on the mechanical behavior and microstructural characteristics of the FSW joints. Five plates are chosen; three are FSW joints, and two are kept in the original base material. In all five plates, tensile, microhardness, and wear tests are performed, including an analysis of grain size. It is observed that the similar Ti6321 joint with a 6 mm pin diameter, 60 mm transverse speed, 900 mm rotational speed, and a constant axial force of 1 KN exhibits a maximum microhardness of 362 HV and a tensile strength of 927 MPa when compared to other joints. The tribological properties are identified as varying load (10–50 N), sliding speed (1–5 m s−1), and a constant sliding distance (1000 m) on pin-on-disc apparatus. It reveals that welding parameters and tool diameter influence tribological characteristics. The surface morphology carried out by FE-SEM revealed that the HAZ is composed of acicular α. The increase in microhardness is higher in WC than in BM due to the uniform distribution of particles. The chemical composition and phases are analyzed using XRD.

Robust vision detection of pipeline solder joints

PurposeSolder joint inspection plays a critical role in various industries, with a focus on integrated chip (IC) solder joints and metal surface welds. However, the detection of tubular solder joints has received relatively less attention. This paper aims to address the challenges of detecting small targets and complex environments by proposing a robust visual detection method for pipeline solder joints. The method is characterized by its simplicity, cost-effectiveness and ease of implementation.Design/methodology/approachA robust visual detection method based on the characteristics of pipeline solder joints is proposed. With the improved hue, saturation and value (HSV) color space, the method uses a multi-level template matching approach to first segment the pipeline from the background, and then match the endpoint of the pipeline to accurately locate the solder joint. The proposed method leverages the distinctive characteristics of pipeline solder joints and employs an enhanced HSV color space. A multi-level template matching approach is utilized to segment the pipeline from the background and accurately locate the solder joint by matching the pipeline endpoint.FindingsThe experimental results demonstrate the effectiveness of the proposed solder joint detection method in practical detection tasks. The average precision of pipeline weld joint localization exceeds 95%, while the average recall is greater than 90%. These findings highlight the applicability of the method to pipeline solder joint detection tasks, specifically in the context of production lines for refrigeration equipment.Research limitations/implicationsThe precision of the method is influenced by the placement angle and lighting conditions of the test specimen, which may pose challenges and impact the algorithm's performance. Potential avenues for improvement include exploring deep learning methods, incorporating additional features and contextual information for localization, and utilizing advanced image enhancement techniques to improve image quality.Originality/valueThe proposed pipeline solder joint detection method offers a novel and practical approach. The simplicity, cost-effectiveness and ease of implementation make it an attractive choice for detecting pipeline solder joints in different industrial applications.

An Automatic Method for Elbow Joint Recognition, Segmentation and Reconstruction.

Elbow computerized tomography (CT) scans have been widely applied for describing elbow morphology. To enhance the objectivity and efficiency of clinical diagnosis, an automatic method to recognize, segment, and reconstruct elbow joint bones is proposed in this study. The method involves three steps: initially, the humerus, ulna, and radius are automatically recognized based on the anatomical features of the elbow joint, and the prompt boxes are generated. Subsequently, elbow MedSAM is obtained through transfer learning, which accurately segments the CT images by integrating the prompt boxes. After that, hole-filling and object reclassification steps are executed to refine the mask. Finally, three-dimensional (3D) reconstruction is conducted seamlessly using the marching cube algorithm. To validate the reliability and accuracy of the method, the images were compared to the masks labeled by senior surgeons. Quantitative evaluation of segmentation results revealed median intersection over union (IoU) values of 0.963, 0.959, and 0.950 for the humerus, ulna, and radius, respectively. Additionally, the reconstructed surface errors were measured at 1.127, 1.523, and 2.062 mm, respectively. Consequently, the automatic elbow reconstruction method demonstrates promising capabilities in clinical diagnosis, preoperative planning, and intraoperative navigation for elbow joint diseases.

Three-dimensional evaluation of temporomandibular joint and dental asymmetries in angle class II division 1 subdivision malocclusion

Abstract Background Management of class II division 1 subdivision malocclusion has consistently offered an important challenge for orthodontic professionals. This problem arises not only from the complexities associated with its treatment but also from the complex nature of its asymmetric characteristics. Understanding the properties of asymmetry in this particular malocclusion has significant importance. Objectives Evaluate the features of temporomandibular joint and dental asymmetries in angle class II division 1 subdivision malocclusion by using cone-beam computed tomography (CBCT). Patients and methods Forty CBCT scans of adult patients were analyzed and divided into two groups: 20 CBCT for each group skeletal and dental measurements were measured and compared among both groups to evaluate the features temporomandibular joint and dental asymmetries in class II division 1 subdivision malocclusion. Results Dental parameters were significantly different (P < 0.01) between right and left sides in maxillary sagittal position (mandibular first), maxillary and mandibular canine. A comparison of condyle and glenoid fossa concerning right, and left sides showed together significant an differences (P < 0.01) in coronal position of GFI, GlS, Poi, and posterior wall angle of the articular tubercle. Conclusion In class II division 1 subdivision malocclusion the mandibular first molar was distal and lingual in position, while the maxillary first molar was mesial in class II side. In class ii subdivision malocclusion, glenoid fossa position and condylar morphology asymmetries caused skeletal asymmetry.

Creation and Validation of a Novel 3-Dimensional Pediatric Hip Ultrasound Model.

The aim of this study was to create and validate a 3-dimensional (3D) ultrasound model with normal and abnormal pediatric hip joint anatomy that is comparable to a pediatric hip joint in appearance and anatomy and replicates sonographic characteristics of a pediatric hip joint. A 3D rendering of the bone and soft tissue was created from a computed tomography pelvic scan of a pediatric patient. This rendering was modified to include a unilateral joint effusion. The bone was 3D printed with a photopolymer plastic, whereas the soft tissue was cast with a silicone mixture in a 3D-printed mold. The effusion was simulated by injecting saline into the soft tissue cavity surrounding the bone. The ultrasound model was validated by pediatric point-of-care ultrasonographers at an international pediatric ultrasound conference. A pediatric hip ultrasound model was developed that simulates both normal and abnormal pediatric hip joint anatomy, each with an appropriately sized, measurable joint effusion. Validation by pediatric point-of-care ultrasonographers showed that the key aspects of a normal pediatric hip joint (femoral physis, sloped femoral neck, and adequate soft tissue) with an identifiable and measurable effusion were included in the ultrasound model. In this study, we successfully created a cost-effective, reusable, and reproducible 3D pediatric hip ultrasound model. The majority of pediatric point-of-care ultrasonographers who evaluated the model agreed that this model is comparable to a pediatric patient for the purpose of teaching ultrasound skills and joint space measurement.

Multi-exposure fused light field image quality assessment for dynamic scenes: Benchmark dataset and objective metric

The luminance dynamic range in natural scenes is exceedingly wide. However, capturing the wide dynamic range information of natural scenes through a single exposure is challenging for commercial light field cameras. One solution to expand the luminance dynamic range of captured light field images is to employ multi-exposure imaging techniques. Nevertheless, this approach may introduce various distortions during the image fusion procedure, especially for dynamic scenes. To evaluate the visual quality of multi-exposure fused light field images (MEFLFIs) and compare the performance of different multi-exposure light field fusion methods, we initially conduct a subjective quality assessment on MEFLFIs for dynamic scenes and establish the first MEFLFI benchmark dataset, which comprises 480 fused light field images generated by eleven state-of-the-art multi-exposure fusion algorithms and two tone-mapping algorithms, along with their corresponding subjective scores. Subsequently, a novel specially designed objective quality assessment metric for MEFLFIs is developed, which incorporates both local–global joint features and angular quality-aware features. The key contribution of this work lies in establishing a pioneering benchmark dataset for MEFLFIs along with a novel tailored objective quality metric. Experimental results conducted over our established MEFLFI database demonstrate that the proposed metric achieves superior performance, with Pearson linear correlation coefficient (PLCC) and Spearman rank correlation coefficient (SROCC) values of 0.8895 and 0.8658 respectively, representing a significant improvement of approximately 5.7 % and 4.9 % compared to the second-best specifically-designed LFI quality metric available. Furthermore, ablation experiments have confirmed that the integration of local–global joint features and angular features significantly enhances the performance of our objective metric, resulting in a better alignment with human visual perception.

Investigation on uniaxial compression and fracture damage mode of prefabricated parallel double-jointed red sandstone.

As a special type of joint fracture, the fracture evolution characteristics of parallel double joints have important engineering significance for the stability analysis of fractured rock mass. In this work, a new method for calculating stress intensity factor of parallel double-jointed fractures was importantly proposed. Physical uniaxial compression tests were carried out on parallel double jointed red sandstone filled with cement mortar under different geometric parameters, and the macroscopic mechanical properties and failure characteristics of red sandstone are deeply analyzed. The results show that the larger the connectivity rate is, the smaller the peak stress and strain are. The increase of connectivity rate will affect the change rate of transverse strain in the center of rock bridge. The closer the dip angle of the joint is, the lower the peak stress is and the shorter the failure time is. The damage mode of joint tip encroachment affects the lateral displacement of the rock bridge center, and the displacement is always close to the first damage section. The closer the joint tip is to the load, the easier the end-face penetrating cracks occur. The research content can provide basic support for guaranteeing the stability of underground engineering rock mass.

Anatomical study of the limited osteotomy suture button fixation Latarjet procedure with coracoacromial ligament preservation

To investigate the morphological characteristics of the glenohumeral joint (including the glenoid and coracoid) in the Chinese population and determine the feasibility of designing coracoid osteotomy based on the preoperative glenoid defect arc length by constructing glenoid defect models and simulating suture button fixation Latarjet procedure. Twelve shoulder joint specimens from 6 adult cadavers donated voluntarily were harvested. First, whether the coracoacromial ligament and conjoint tendon connected was anatomically observed and their intersection point was identified. The vertical distance from the intersection point to the coracoid, the maximum allowable osteotomy length starting from the intersection point, and the maximum osteotomy angle were measured. Next, the anteroinferior glenoid defect models of different degrees were randomly constructed. The arc length and area of the glenoid defect were measured. Based on the arc length of the glenoid defect of the model, the size of coracoid oblique osteotomy was designed and the actual length and angle of the coracoid osteotomy were measured. A limited osteotomy suture button fixation Latarjet procedure with the coracoacromial ligament and pectoralis minor preservation was performed and the position of coracoid block was observed. All shoulder joint specimens exhibited crossing fibers between the coracoacromial ligament and the conjoint tendon. The vertical distance from the tip of the coracoid to the coracoid return point was 24.8-32.2 mm (mean, 28.5 mm). The maximum allowable osteotomy length starting from the intersection point was 26.7-36.9 mm (mean, 32.0 mm). The maximum osteotomy angle was 58.8°-71.9° (mean, 63.5°). Based on the anteroinferior glenoid defect model, the arc length of the glenoid defect was 22.6-29.4 mm (mean, 26.0 mm); the ratio of glenoid defect was 20.8%-26.2% (mean, 23.7%). Based on the coracoid block, the length of the coracoid osteotomy was 23.5-31.4 mm (mean, 26.4 mm); the osteotomy angle was 51.3°-69.2° (mean, 57.1°). There was no significant difference between the arc length of the glenoid defect and the length of the coracoid osteotomy ( P>0.05). After simulating the suture button fixation Latarjet procedure, the highest points of the coracoid block (suture loop fixation position) in all models located below the optimal center point, with the bone block concentrated in the anteroinferior glenoid defect position. The size of the coracoid is generally sufficient to meet the needs of repairing larger glenoid defects. The oblique osteotomy with preserving the coracoacromial ligament may potentially replace the traditional Latarjet osteotomy method.

Influence of process variations on clinch joint characteristics considering the effect of the nominal tool design

Focusing on upcoming challenges in lightweight design, such as increasing emission targets or novel multimaterial connections, versatile applicable and environmentally friendly production technologies are crucial. In this context, mechanical joining technology clinching offers a fast and energy-efficient procedure for assembling sheet metals, being a proper alternative to established joining methods, such as spot welding. However, the design of clinch points is a challenge, which is partly supported by numerical or data-based approaches for optimal tool dimensions assuring proper joint characteristics. While this is usually done for an ideal environment, real joining processes are characterized by multiple inevitably varying parameters, e.g. of the material, which have a significant impact on the quality of clinch points. Therefore, this contribution addresses the current gap by analyzing the effect of parameter variations or uncertainties on the resulting joint characteristics and studying the impact of the nominal tool design. Thus, an efficient meta-model-based variation simulation procedure is proposed and used for analyzing the effect of different tool design configurations and variation scenarios. Based on the results, it was found that varying process parameters have a strong impact on the resulting joint characteristics, whereby the effect significantly depends on the nominal tool design. This reveals the potential for a robust tool design and implies that the nominal tool design and the tolerancing of parameters should be done simultaneously for a reliable virtual joining point design without extensive iterations and physical tests.