Preliminary results of classifying otosclerosis and disarticulation using a convolutional neural network trained with simulated wideband acoustic immittance data.

Current noninvasive methods of clinical practice often do not identify the causes of conductive hearing loss due to pathologic changes in the middle ear with sufficient certainty. Wideband acoustic immittance (WAI) measurement is noninvasive, inexpensive and objective. It is very sensitive to pathologic changes in the middle ear and therefore promising for diagnosis. However, evaluation of the data is difficult because of large interindividual variations. Machine learning methods like Convolutional neural networks (CNN) which might be able to deal with this overlaying pattern require a large amount of labeled measurement data for training and validation. This is difficult to provide given the low prevalence of many middle-ear pathologies. Therefore, this study proposes an approach in which the WAI training data of the CNN are simulated with a finite-element ear model and the Monte-Carlo method. With this approach, virtual populations of normal, otosclerotic, and disarticulated ears were generated, consistent with the averaged data of measured populations and well representing the qualitative characteristics of individuals. The CNN trained with the virtual data achieved for otosclerosis an AUC of 91.1 %, a sensitivity of 85.7 %, and a specificity of 85.2 %. For disarticulation, an AUC of 99.5 %, sensitivity of 100 %, and specificity of 93.1 % was achieved. Furthermore, it was estimated that specificity could potentially be increased to about 99 % in both pathological cases if stapes reflex threshold measurements were used to confirm the diagnosis. Thus, the procedures' performance is comparable to classifiers from other studies trained with real measurement data, and therefore the procedure offers great potential for the diagnosis of rare pathologies or early-stages pathologies. The clinical potential of these preliminary results remains to be evaluated on more measurement data and additional pathologies.

Biomechanical analysis of spinal cord injury during scoliosis correction surgery.

Introduction: Surgical correction is a common treatment for severe scoliosis. Due to the significant spinal deformation that occurs with this condition, spinal cord injuries during corrective surgery can occur, sometimes leading to paralysis. Methods: Such events are associated with biomechanical changes in the spinal cord during surgery, however, their underlying mechanisms are not well understood. Six patient-specific cases of scoliosis either with or without spinal complications were examined. Finite element analyses (FEA) were performed to assess the dynamic changes and stress distribution of spinal cords after surgical correction. The FEA method is a numerical technique that simplifies problem solving by replacing complex problem solving with simplified numerical computations. Results: In four patients with poor prognosis, there was a concentration of stress in the spinal cord. The predicted spinal cord injury areas in this study were consistent with the clinical manifestations of the patients. In two patients with good prognosis, the stress distribution in the spinal cord models was uniform, and they showed no abnormal clinical manifestations postoperatively. Discussion: This study identified a potential biomechanical mechanism of spinal cord injury caused by surgical correction of scoliosis. Numerical prediction of postoperative spinal cord stress distribution might improve surgical planning and avoid complications.

Optimal tooth sectioning using a surgical handpiece and elevator: a finite element study of horizontally deeply impacted mandibular third molars.

OBJECTIVES: To conduct a finite element analysis of the impact of different variables on tooth sectioning efficiency and trauma to surrounding tissues when utilizing high-speed surgical handpieces and elevators. METHODS: CBCT data from the horizontally impacted third mandibular molar (M3M) of a patient were utilized to establish digital models of the M3M, adjacent M2M, and surrounding bone. To simulate tooth sectioning, a 3D finite element model was established with the following variables: remaining tooth tissue thickness (1-5 mm), tooth section fissure width (1-3 mm), elevator depth in fissure (2-6 mm), elevator position (buccal, lingual, central), elevator width (2-5 mm), and application of force (rotating, levering). Using this model, the distribution of stress on the M3M and the surrounding tissue was assessed while measuring tooth sectioning efficiency and trauma to the surrounding tissue. RESULTS: Factors associated with uniform stress at the site of sectioning included thin (≤ 3 mm) remaining tooth tissue, appropriate fissure width (~ 2 mm), a wide (≥ 4 mm) elevator, and central elevator positioning. Levering the elevator yielded greater stress on the M3M than rotating force. Greater sectioning efficiency was associated with increased stress placed on the distobuccal side of M2M. CONCLUSIONS: Tooth sectioning efficiency can be improved by adjusting the high-speed surgical handpiece and elevator. However, it is important to remain attentive to the trauma to which adjacent teeth are exposed during this process. CLINICAL SIGNIFICANCE: These results offer guidance for approaches to improving operator efficiency and reducing trauma to surrounding tissues during tooth sectioning.

Effect of sagittal alignment on spinal cord biomechanics in the stenotic cervical spine during neck flexion and extension.

Spinal cord stress and strain contribute to degenerative cervical myelopathy (DCM), while cervical kyphosis is known to negatively impact surgical outcomes. In DCM, the relationship between spinal cord biomechanics, sagittal alignment, and cord compression is not well understood. Quantifying this relationship can guide surgical strategies. A previously validated three-dimensional finite element model of the human cervical spine with spinal cord was used. Three models of cervical alignment were created: lordosis (C2-C7 Cobb angle: 20°), straight (0°), and kyphosis (- 9°). C5-C6 spinal stenosis was simulated with ventral disk protrusions, reducing spinal canal diameters to 10 mm, 8 mm, and 6 mm. Spinal cord pre-stress and pre-strain due to alignment and compression were quantified. Cervical flexion and extension were simulated with a pure moment load of 2 Nm. The Von Mises stress and maximum principal strain of the whole spinal cord were calculated during neck motion and the relationship between spinal cord biomechanics, alignment, and compression was analyzed using linear regression analysis. Spinal cord pre-stress and pre-strain were greatest with kyphosis (7.53 kPa, 5.4%). Progressive kyphosis and stenosis were associated with an increase in spinal cord stress (R2 = 0.99) and strain (R2 = 0.99). Cervical kyphosis was associated with greater spinal cord stress and strain during neck flexion-extension and the magnitude of difference increased with increasing stenosis. Cervical kyphosis increases baseline spinal cord stress and strain. Incorporating sagittal alignment with compression to calculate spinal cord biomechanics is necessary to accurately quantify spinal stress and strain during neck flexion and extension.

The Evaluation and Prediction of Flame Retardancy of Asphalt Mixture Based on PCA-RBF Neural Network Model.

Warm mix flame retardant asphalt mixture can reduce the energy dissipation and harmful gas emissions during asphalt pavement construction, as well as mitigate the adverse effects of road fires. For this, this paper studies the design and performance of a mixture modified with a combination of warm mix agent and flame retardant, and the pavement performance and flame retardancy of the modified mixture are evaluated. Additionally, a flame retardancy prediction model based on the radial basis function (RBF) neural network model is established. On this basis, the principal components analysis (PCA) model is used to analyze the most significant evaluation indicators affecting flame retardancy, and finally, a three-dimensional finite element model is developed to analyze the effects of loading on the pavement structure. The results show that compared to virgin asphalt mixture, the modified mixture shows a reduction in mixing and compaction temperatures by approximately 12 °C. The high-temperature performance of the mixture is improved, while the low-temperature performance and moisture stability slightly decrease, but its flame retardancy is significantly enhanced. The RBF neural network model revealed that the established flame retardancy prediction model has a high accuracy, allowing for precise evaluation of the flame retardancy. Finally, the PCA model identified that the combustion time has a significant effect on the flame retardancy of the asphalt mixture, and the finite element model revealed that the displacements of the warm mix fire retardant asphalt mixture were lower than virgin asphalt mixture in all directions under the loading.

Experimental and numerical investigations on the bending capacity of cold-formed steel box headers.

The study investigates the bending strength of tracks of box headers beyond AISI, which considers the capacity of individual channels alone. Both experimental and FEM are used, and the results are compared to AISI. The findings highlight tracks' significant role in the overall bending capacity. AISI is found to be conservative by 34% to 152%. Failure mode is different from code theoretical expectations for a single channel. Fastener close spacing marginally improves the capacity, while side fasteners offer significant enhancement, but track widening limits this enhancement. A modification to AISI is proposed considering track strength, with outcomes showing good accuracy.

[Oblique Lumbar Interbody Fusion Combined With 4-Screw Fixation for Treating Two-Level Degenerative Lumbar Diseases:A Finite Element Study].

Objective To demonstrate the feasibility of oblique lumbar interbody fusion (OLIF) combined with 4-screw fixation for treating two-level lumbar degenerative diseases.Methods An intact finite element model of L3-S1 (M0) was constructed and validated.Then,we constructed the M1 model by simulating OLIF surgery at L3/4 and L4/5 segments on the M0 model.By attachment of posterior 4-screw or 6-screw fixation to the M1 model,three 4-screw fixation models (M2-M4) and one 6-screw fixation model (M5) were established.The segmental and overall range of motion (ROM) and the peak von Mises stresses of superior endplate,cage,and posterior screw-rod were investigated under each implanted condition.Results Under the motion modes of forward flexion,backward extension,bilateral (left and right) flexion,and left and right rotation,the L3/4 ROM of M2 model and L4/5 ROM of M3 model increased,while the L3/4 and L4/5 ROM of M4 and M5 models significantly decreased compared with those of M1 model.Under all motion modes,the L4 superior endplate in M2 model and the L5 superior endplate in M3 model showed the maximum peak von Mises stress,and the peak von Mises stresses of L4 and L5 superior endplates in M4 and M5 models were close.The L3/4 cage in M2 model and the L4/5 cage in M3 model showcased the largest peak von Mises stress,and the peak von Mises stresses of cages in M4 and M5 models were close.The peak stresses of internal fixation in M2-M5 models were close.Conclusion Four-screw fixation can replace 6-screw fixation in the OLIF surgery for treating two-level degenerative lumbar diseases.

Finite element analysis of a three-dimensional cervical spine model with muscles based on CT scan data.

BACKGROUND: The incidence of cervical spondylosis is increasing, gradually affecting people's normal lives. Establishing a finite element model of the cervical spine is one of the methods for studying cervical spondylosis. MRI (Magnetic Resonance Imaging) still has certain difficulties in transitioning from human imaging to establishing muscle models suitable for finite element analysis. Medical software provides specific morphologies and can generate muscle finite element models. Additionally, there is little research on the static analysis of cervical spine finite element models with solid muscle. PURPOSE: A new method is proposed for establishing a finite element model of the cervical spine based on CT (Computed Tomography) data and medical software, and the model's effectiveness is validated. Human movement characteristics based on the force distribution in various parts are analyzed and predicted. METHODS: The muscle model is reconstructed in medical software and a three-dimensional finite element model of the entire cervical spine (C0-C7) is established by combining muscle models with CT vertebral data models. 1.5 Nm of load is applied to the finite element model to simulate the cervical spine movement. RESULTS: The finite element model was successfully established, and effectiveness was verified. Stress variations in various parts under six movements were obtained. The effectiveness of the model was basically verified. CONCLUSION: The finite element model of the cervical spine for mechanical analysis can be successfully established by using medical software and CT data. In daily life, the C2-3, C3-4, C4-C5 intervertebral discs, rectus capitis posterior major, longus colli, and obliquus capitis inferior are more prone to injury.

Effect of patient specificity on predicting knee cartilage degeneration in obese adults: Musculoskeletal finite-element modeling of data from the CAROT trial.

Obesity is a known risk factor for development of osteoarthritis (OA). Numerical tools like finite-element (FE) models combined with degenerative algorithms have been developed to understand the interplay between OA and obesity. In this study, we aimed to predict knee cartilage degeneration in a cohort of obese adults to investigate the importance of patient-specific information on degeneration predictions. We used a validated FE modeling approach and three different age-dependent functions (step-wise, exponential, and linear) to simulate cartilage degradation under overloading in the knee joint. Gait motion analysis and magnetic resonance imaging data from 115 obese individuals with knee OA were used for musculoskeletal and FE modeling. Cartilage degeneration predictions were contrasted with Kellgren-Lawrence (KL) and Boston-Leeds Osteoarthritis Knee Score (BLOKS) grades. The findings show that overall, the similarities between numerical predictions and clinical measures were better for the medial (average area under the curve (AUC) = 0.62) compared to the lateral compartment (average AUC = 0.52) of the knee. Classification results for KL grades, full patient-specific models and patient-specific geometry with generic gait data showed higher AUC values (AUC = 0.71 and AUC = 0.68, respectively) compared to generic geometry and patient-specific gait (AUC = 0.48). For BLOKS grades, AUC values for both full patient-specific models and for patient-specific geometry with generic gait locomotion were higher (AUC = 0.66 and AUC = 0.64, respectively) compared to when the generic geometry and patient-specific gait were used (AUC = 0.53). In summary, our study highlights the importance of considering individual information in knee OA prediction. Nevertheless, our findings suggest that personalized gait play a smaller role in the OA prediction and classification capacity than personalized joint geometry.

Auditory nerve fiber excitability for alternative electrode placement in the obstructed human cochlea: electrode insertion in scala vestibuli versus scala tympani.

OBJECTIVE: The cochlear implant (CI) belongs to the most successful neuro-prostheses. Traditionally, the stimulating electrode arrays are inserted into the scala tympani (ST), the lower cochlear cavity, which enables simple surgical access. However, often deep insertion is blocked, e.g., by ossification, and the auditory nerve fibers (ANFs) of lower frequency regions cannot be stimulated causing severe restrictions in speech understanding. As an alternative, the CI can be inserted into the scala vestibuli (SV), the other upper cochlear cavity. APPROACH: In this computational study, the excitability of 25 ANFs are compared for stimulation with ST and SV implants. We employed a 3-dimensional realistic human cochlear model with lateral wall electrodes based on a µ-CT dataset and manually traced fibers. A finite element approach in combination with a compartment model of a spiral ganglion cell was used to simulate monophasic stimulation with anodic (ANO) and cathodic (CAT) pulses of 50 µs. MAIN RESULTS: ANO thresholds are lower in ST (mean/std = µ/σ =189/55 µA) stimulation compared to SV (µ/σ = 323/119 µA) stimulation. Contrary, CAT thresholds are higher for the ST array (µ/σ = 165/42 µA) compared to the SV array (µ/σ = 122/46 µA). The threshold amplitude depends on the specific fiber-electrode spatial relationship, such as lateral distance from the cochlear axis, the angle between electrode and target ANF, and the curvature of the peripheral process. For CAT stimulation the SV electrodes show a higher selectivity leading to less cross-stimulation of additional fibers from different cochlear areas. SIGNIFICANCE: We present a first simulation study with a human cochlear model that investigates an additional CI placement into the SV and its impact on the excitation behavior. Results predict comparable outcomes to ST electrodes which confirms that SV implantation might be an alternative for patients with a highly obstructed ST.

Real-time prediction of postoperative spinal shape with machine learning models trained on finite element biomechanical simulations.

PURPOSE: Adolescent idiopathic scoliosis is a chronic disease that may require correction surgery. The finite element method (FEM) is a popular option to plan the outcome of surgery on a patient-based model. However, it requires considerable computing power and time, which may discourage its use. Machine learning (ML) models can be a helpful surrogate to the FEM, providing accurate real-time responses. This work implements ML algorithms to estimate post-operative spinal shapes. METHODS: The algorithms are trained using features from 6400 simulations generated using the FEM from spine geometries of 64 patients. The features are selected using an autoencoder and principal component analysis. The accuracy of the results is evaluated by calculating the root-mean-squared error and the angle between the reference and predicted position of each vertebra. The processing times are also reported. RESULTS: A combination of principal component analysis for dimensionality reduction, followed by the linear regression model, generated accurate results in real-time, with an average position error of 3.75 mm and orientation angle error below 2.74 degrees in all main 3D axes, within 3 ms. The prediction time is considerably faster than simulations based on the FEM alone, which require seconds to minutes. CONCLUSION: It is possible to predict post-operative spinal shapes of patients with AIS in real-time by using ML algorithms as a surrogate to the FEM. Clinicians can compare the response of the initial spine shape of a patient with AIS to various target shapes, which can be modified interactively. These benefits can encourage clinicians to use software tools for surgical planning of scoliosis.

Effect of forefoot transverse arch stiffness on foot biomechanical response--based on finite element method.

Background: The plantar vault, comprising the transverse and longitudinal arches of the human foot, is essential for impact absorption, elastic energy storage, and propulsion. Recent research underscores the importance of the transverse arch, contributing over 40% to midfoot stiffness. This study aimed to quantify biomechanical responses in the ankle-foot complex by varying the stiffness of the deep metatarsal transverse ligament (DTML). Methods: Using CT image reconstruction, we constructed a complex three-dimensional finite element model of the foot and ankle joint complex, accounting for geometric complexity and nonlinear characteristics. The focus of our study was to evaluate the effect of different forefoot transverse arch stiffness, that is, different Young's modulus values of DTML (from 135 MPa to 405 MPa), on different biomechanical aspects of the foot and ankle complex. Notably, we analyzed their effects on plantar pressure distribution, metatarsal stress patterns, navicular subsidence, and plantar fascial strain. Results: Increasing the stiffness of the DTML has significant effects on foot biomechanics. Specifically, higher DTML stiffness leads to elevate von Mises stress in the 1st, 2nd, and 3rd metatarsals, while concurrently reducing plantar pressure by 14.2% when the Young's modulus is doubled. This stiffening also impedes navicular bone subsidence and foot lengthening. Notably, a 100% increase in the Young's modulus of DTML results in a 54.1% decrease in scaphoid subsidence and a 2.5% decrease in foot lengthening, which collectively contribute to a 33.1% enhancement in foot longitudinal stiffness. Additionally, doubling the Young's modulus of DTML can reduce the strain stretch of the plantar fascia by 38.5%. Conclusion: Preserving DTML integrity sustains the transverse arch, enhancing foot longitudinal stiffness and elastic responsiveness. These findings have implications for treating arch dysfunction and provide insights for shoe developers seeking to enhance propulsion.

A Finite Element Model for Simulating Stress Responses of Permeable Road Pavement.

Permeable road pavements, due to their open-graded design, suffer from low structural strength, restricting their use in areas with light traffic volume and low bearing capacity. To expand application of permeable road pavements, accurate simulation of stress parameters used in pavement design is essential. A 3D finite element (3D FE) model was developed using ABAQUS/CAE 2021 to simulate pavement stress responses. Utilizing a 53 cm thick permeable road pavement and a 315/80 R22.5 wheel as prototypes, the model was calibrated and validated, with its accuracy confirmed through t-test statistical analysis. Simulations of wheel speeds at 11, 15, and 22 m/s revealed significant impact on pavement depths of 3 cm and 8 cm, while minimal effects were observed at depths of 13 cm and 33 cm. Notably, stress values at a depth of 3 cm with 15 m/s speed in the open-graded asphalt concrete (OGFC) surface layer exceeded those at the speed of 11 m/s, while at a depth of 8 cm in the porous asphalt concrete (PAC) base layer, an opposite performance was observed. This may be attributed to the higher elastic modulus of the OGFC surface layer, which results in different response trends to velocity changes. Overall, lower speeds increase stress responses and prolong action times for both layers, negatively affecting pavement performance. Increasing the moduli of layers is recommended for new permeable road pavements for low-speed traffic. Furthermore, considering the effects of heavy loads and changes in wheel speed, the recommended design depth for permeable road pavement is 30 cm. These conclusions provide a reference for the design of permeable road pavements to address climate change and improve performance.

Traumatic axonal injury: Clinic, forensic and biomechanics perspectives.

Identification of Traumatic axonal injury (TAI) is critical in clinical practice, particularly in terms of long-term prognosis, but also for medico-legal issues, to verify whether the death or the after-effects were attributable to trauma. Multidisciplinary approaches are an undeniable asset when it comes to solving these problems. The aim of this work is therefore to list the different techniques needed to identify axonal lesions and to understand the lesion mechanisms involved in their formation. Imaging can be used to assess the consequences of trauma, to identify indirect signs of TAI, to explain the patient's initial symptoms and even to assess the patient's prognosis. Three-dimensional reconstructions of the skull can highlight fractures suggestive of trauma. Microscopic and immunohistochemical techniques are currently considered as the most reliable tools for the early identification of TAI following trauma. Finite element models use mechanical equations to predict biomechanical parameters, such as tissue stresses and strains in the brain, when subjected to external forces, such as violent impacts to the head. These parameters, which are difficult to measure experimentally, are then used to predict the risk of injury. The integration of imaging data with finite element models allows researchers to create realistic and personalized computational models by incorporating actual geometry and properties obtained from imaging techniques. The personalization of these models makes their forensic approach particularly interesting.

Numerical Study on Mechanical Behavior and Electromechanical Properties of Solder-Jointed REBCO-Coated Conductors.

As the second-generation high-temperature superconducting conductors, rare earth-barium-copper-oxide (REBCO) coated conductor (CC) tapes have good potential as high-field and high-energy superconductors. In superconducting applications, several joints are required for conjugating comparatively short REBCO CC tapes. Soldering lap joints are the simplest and most commonly applied REBCO CC joints. In addition to joint resistance, the mechanical behavior and electromechanical properties are also crucial for superconducting applications. In this paper, the electromechanical properties and mechanical behaviors of soldering lap joints at 77 K under a self-field were studied. The mechanical behavior was addressed by using a full three-dimensional multilayer elastic-plastic finite element model (FEM) with REBCO CC tape main layers and solder connecting layers. Then, the electromechanical properties were analyzed by using Gao's strain-Ic degradation general model on the basis of the FEM results. Both the mechanical behavior and electromechanical properties were verified by experimental results. The effects of soldering lap conditions including lap length, soldering thickness and lap style on the electromechanical properties and mechanical behaviors were discussed. The results indicate that shorter overlap lengths and a thinner solder can reduce the premature degradation of Ic due to stress concentrations nearby the joint edges; moreover, the irreversible critical strain is significantly higher in the back-to-back joint approach compared to the widely used face-to-face joint approach.

Mitigating Measurement Inaccuracies in Digital Twins of Construction Machinery through Multi-Objective Optimization.

The advent of digital twins facilitates the generation of high-fidelity replicas of actual systems or assets, thereby enhancing the design's performance and feasibility. When developing digital twins, precise measurement data is essential to ensure alignment between the actual and digital models. However, inherent uncertainties in sensors and models lead to disparities between observed and predicted (simulated) behaviors. To mitigate these uncertainties, this study originally proposes a multi-objective optimization strategy utilizing a Gaussian process regression surrogate model, which integrates various uncertain parameters, such as load angle, bucket cylinder stroke, arm cylinder stroke, and boom cylinder stroke. This optimization employs a genetic algorithm to indicate the Pareto frontiers regarding the pressure exerted on the boom, arm, and bucket cylinders. Subsequently, TOPSIS is applied to ascertain the optimal candidate among the identified Pareto optima. The findings reveal a substantial congruence between the experimental and numerical outcomes of the devised virtual model, in conjunction with the TOPSIS-derived optimal parameter configuration.

Voxel Design of Grayscale DLP 3D-Printed Soft Robots.

Grayscale digital light processing (DLP) printing is a simple yet effective way to realize the variation of material properties by tuning the grayscale value. However, there is a lack of available design methods for grayscale DLP 3D-printed structures due to the complexities arising from the voxel-level grayscale distribution, nonlinear material properties, and intricate structures. Inspired by the dexterous motions of natural organisms, a design and fabrication framework for grayscale DLP-printed soft robots is developed by combining a grayscale-dependent hyperelastic constitutive model and a voxel-based finite-element model. The constitutive model establishes the relationship between the projected grayscale value and the nonlinear mechanical properties, while the voxel-based finite-element model enables fast and efficient calculation of the mechanical performances with arbitrarily distributed material properties. A multiphysics modeling and experimental method is developed to validate the homogenization assumption of the degree of conversion (DoC) variation in a single voxel. The design framework is used to design structures with reduced stress concentration and programmable multimodal motions. This work paves the way for integrated design and fabrication of functional structures using grayscale DLP 3D printing.

The C2 isthmus screw provided sufficient biomechanical stability in the setting of atlantoaxial dislocation-a finite element study.

BACKGROUND: The emerging of the C2 isthmus screw fixation technique is gaining popularity in the setting of atlantoaxial dislocation or other conditions requiring fixation of C2. However, the biomechanical stability of this fixation is poorly understood. PURPOSE: To compare and elucidate the biomechanical stability of C2 pedicle screw (C2PS), C2 isthmus screw (C2IS) and C2 short isthmus screw (C2SIS) fixation techniques in atlantoaxial dislocation (AAD). METHOD: A three-dimensional finite element model (FEM) from occiput to C3 was established and validated from a healthy male volunteer. Three FEMs, C1 pedicle screw (PS)-C2PS, C1PS-C2IS, C1PS-C2SIS were also constructed. The range of motion (ROM) and the maximum von Mises stress under flexion, extension, lateral bending and axial rotation loading were analyzed and compared. The pullout strength of the three fixations for C2 was also evaluated. RESULT: C1PS-C2IS model showed the greatest decrease in ROM with flexion, extension, lateral bending and axial rotation. C1PS-C2PS model showed the least ROM reduction under all loading conditions than both C2IS and C2SIS. The C1PS-C2PS model had the largest von Mises stress on the screw under all directions followed by C1PS-C2SIS, and lastly the C1PS-C2IS. Under axial rotation and lateral bending loading, the three models showed the maximum and minimum von Mises stress on the screw respectively. The stress of the three models was mainly located in the connection of the screw and rod. Overall, the maximum screw pullout strength for C2PS, C2IS and C2SIS were 729.41N, 816.62N, 640.54N respectively. CONCLUSION: In patients with atlantoaxial dislocations, the C2IS fixation provided comparable stability, with no significant stress concentration. Furthermore, the C2IS had sufficient pullout strength when compared with C2PS and C2SIS. C2 isthmus screw fixation may be a biomechanically favourable option in cases with AAD. However, future clinical trials are necessary for the evaluation of the clinical outcomes of this technique.

Investigation of hybrid ultrasonic machining process of Nomex honeycomb composite using a toothed disc cutter.

Nomex honeycomb composite (NHC) has been increasingly used in the automotive, aerospace and defence applications due to its excellent thermal and mechanical properties. Its complex cellular hexagonal thin-walled configuration along with heterogeneous, soft and brittle nature pose substantial processing defects such as burr formation, tearing of walls, surface roughness, dimensional inaccuracy and low machining quality during conventional machining (CM). These surface defects have a substantial influence on the operating life and functional performance of its sandwiched structural members. Hybrid ultrasonic vibration assisted machining (HUSVAM) technology has been introduced to overcome such limitations. For an in depth research on HUSVAM of NHC using ultrasonic toothed disc cutter (UTDC), three dimensional finite element model was developed and experimental validation was carried out. The numerical simulation and experimental results were found to be in good agreement with one another. The influence of various machining parameters including the ultrasonic tool vibration amplitude (UTVA), feed rate (FR), depth of cut (DoC) and spindle angular speed (SAS) on NHC cutting forces, chip formation and surface quality was investigated using both HUSVAM and CM techniques. Furthermore, stresses, deformation and forces near tool-workpiece interaction along with the surface topography and morphologies were also analysed and compared for various operating conditions. A reduction in the cutting forces was found with the increase of SAS and UTVA (up to 65.47 % and 65.74 %, respectively). Although, the cutting forces were observed to increase by increasing the DoC and FR (up to 159.45 % and 126.33 %, respectively). DoC has a greater impact on the cutting forces among all machining parameters according to 4 levels, 4 factors (L16) orthogonal experiments based on Taguchi method. The results show that the chip formation and machining quality of NHC core can be improved with HUSVAM technique using UTDC. HUSVAM also reduced the cutting forces (up to 73 %) compared to CM. The ultrasonic toothed disc cutter generated large number of burr with very short length, no tearing defects and no uncut fibers as observed from scanning electron microscopy of NHC hexagonal cell structure, walls and triple points. A burr formation of less than 10 % was realized during HUSVAM of NHC cores for Fx≤3N, while it was found up to 20 % if Fx>3N, compared to at least 40 % during CM. The finite element model developed can be used to investigate the influence of HUSVAM on modern difficult to machine materials for enhanced surface quality.

Experimental and Numerical Study of Membrane Residual Stress in Q690 High-Strength Steel Welded Box Section Compressed Member.

High-strength steel (HSS) members with welded sections exhibit a notably lower residual compressive stress ratio compared with common mild steel (CMS) members. Despite this difference, current codes often generalize the findings from CMS members to HSS members, and the previous unified residual stress models are generally conservative. This study focuses on the membrane residual stress distribution in Q690 steel welded box sections. By leveraging experimental results, the influence of section sizes and welding parameters on membrane residual stress was delved into. A larger plate size correlates with a decrease in the residual compressive stress across the section, with a more pronounced reduction observed in adjacent plates. Additionally, augmenting the number of welding passes tends to diminish residual stresses across the section. Results showed that membrane residual stress adhered to the section's self-equilibrium, while the self-equilibrium in the plates was not a uniform pattern. A reliable residual stress simulation method for Q690 steel welded box sections was established using a three-dimensional thermal-elastic-plastic finite element model (3DTEFEM) grounded in experimental data. This method served as the cornerstone for parameter analysis in this study and set the stage for subsequent research. As a result, an accurate unified residual stress model for Q690 steel welded box sections was derived.