Recent clinical studies have reported that heart failure with preserved ejection fraction (HFpEF) can be divided into two phenotypes based on the range of ejection fraction (EF), namely HFpEF with higher EF and HFpEF with lower EF. These phenotypes exhibit distinct left ventricle (LV) remodelling patterns and dynamics. However, the influence of LV remodelling on various LV functional indices and the underlying mechanics for these two phenotypes are not well understood. To address these issues, this study employs a coupled finite element analysis (FEA) framework to analyse the impact of various ventricular remodelling patterns, specifically concentric remodelling (CR), concentric hypertrophy (CH), and eccentric hypertrophy (EH), with and without LV wall thickening on LV functional indices. Further, the geometries with a moderate level of remodelling from each pattern are subjected to fibre stiffening and contractile impairment to examine their effect in replicating the different features of HFpEF. The results show that with severe CR, LV could exhibit the characteristics of HFpEF with higher EF, as observed in recent clinical studies. Controlled fibre stiffening can simultaneously increase the end-diastolic pressure (EDP) and reduce the peak longitudinal strain (ell) without significant reduction in EF, facilitating the moderate CR geometries to fit into this phenotype. Similarly, fibre stiffening can assist the CH and \'EH with wall thickening\' cases to replicate HFpEF with lower EF. These findings suggest that potential treatment for these two phenotypes should target the bio-origins of their distinct ventricular remodelling patterns and the extent of myocardial stiffening.

The natural convection in cavities is frequently used in fluid mechanics and heat transfer engineering, such as heat exchangers, electronics, solar collectors, and growing crystals. However, the physics of natural convection flow and heat transfer in cavities with split baffles is least understood. The fundamental aim of this research is to investigate the impact of heated split baffles positioned at various locations on steady-state free convection within a sinusoidal corrugated star cavity. In this model configuration, the outer wavy enclosure is maintained at a constant temperature of T c , while the inner split baffles are heated at a constant temperature of T h . The finite element method is employed to discretize and solve the governing equations describing the fluid flow and heat transfer within the enclosure. This numerical approach aimed to analyze the effects of baffle inclination angles, baffle spacing, Rayleigh number on the fluid dynamics and convective thermal transport characteristics. The variation in velocity and temperature profile is illustrated through the streamlines and isotherm contours. Moreover, the numerical result is displayed in term N u a v g of the heat transfer, which are analyzed for inside space of baffles and angles of the baffle ( θ = 0 0 , 45 0 , 90 0 ) . The key finding demonstrates that increasing the Rayleigh numbers and the different positions (up, central, down) of inner vertical split baffles enhances the magnitude of the velocity by 88.1 % , 85.9 and 89.6 % respectively. Furthermore, for the inner rectangular split baffle angles of 0 ° , 45 ° , and 90 ° , and within the Rayleigh number range of 10 4 to 10 6 , the N u a v g exhibits significant variations, with maximum increases of 71.9 % , 46.7 % and a subsequent decrease of 45.9 % .

In virtual surgical training, it is crucial to achieve real-time, high-fidelity simulation of the tissue deformation. The anisotropic and nonlinear characteristics of the organ with multi-component make accurate real-time deformation simulation difficult. A localized tissue constraint progressive transfer learning method is proposed in this paper, where the base-compensated dual-output transfer learning strategy and the localized tissue constraint progressive learning architecture are developed. The proposed strategy enriches the multi-component biomechanical dataset to fully represent complex force-displacement with minimal high-quality data. Meanwhile, the proposed architecture adopts focused and progressive model to accurately describe tissues with varied biomechanical properties rather than singular homogeneous model. We made comparison with 4 state-of-the-art (SOTA) methods in simulating multi-component biomechanical deformations of organs with 100 pairs of testing data. Results show that the accuracy of our method is 50% higher than other methods in different validation matrix. And our method can stably simulate the deformations in 0.005 s per frame, which largely improves the computing efficiency.

The geometrical accuracy of additively manufactured pure titanium clasps depends on the building orientation. The aim of this study is to compare the geometrical accuracy and the fatigue lives predicted by finite element analysis (FEA) among three clasps manufactured with different building orientations. Besides, this paper proposed a calculation method of the moment of inertia of area and cross-sectional area along with the arm as the geometrical parameters. One of the clasps manufactured with a cylindrical chucking part for the fatigue test had almost the same geometrical parameters with the CAD design. Also, the authors\' fatigue life prediction method using the CAD based FEA was verified through comparison with micro-CT image-based FEA. The other two clasps had larger geometrical parameters than the CAD design, resulting in longer fatigue lives. The results implied the importance of calculating the moment of inertia of the area in the design of the clasp arm.

This article investigates the behavior of hybrid FRP Concrete-Steel columns with an elliptical cross section. The investigation was carried out by gathering information through literature and conducting a parametric study, which resulted in 116 data points. Moreover, multiple machine learning predictive models were developed to accurately estimate the confined ultimate strain and the ultimate load of confined concrete at the rupture of FRP tube. Decision Tree (DT), Random Forest (RF), Adaptive Boosting (ADAB), Categorical Boosting (CATB), and eXtreme Gradient Boosting (XGB) machine learning techniques were utilized for the proposed models. Finally, these models were visually and quantitatively verified and evaluated. It was concluded that the CATB and XGB are standout models, offering high accuracy and strong generalization capabilities. The CATB model is slightly superior due to its consistently lower error rates during testing, indicating it is the best model for this dataset when considering both accuracy and robustness against overfitting.

Mixed convective nanofluid flow has substantial importance in improvement of thermal performance, and thermal engineering to meet the global energy crisis. In this study, mixed convective nanofluid flow in a porous-wavy channel with an inner heated triangular obstacle under magnetic field effect is numerically examined. Nanofluid within the channel is heated and cooled from its bottom and top wavy-surfaces. A heated triangular cylinder is located at the centerline of the wavy-channel. Finite element method is utilized to solve the non-dimensional governing equations. The code is validated comparing present results with published numerical and experimental results. The response surface method is also implemented to analyze the obtained results and its sensitivity. The numerical results indicate that strength of flow velocity is accelerated with rising Reynolds number, Darcy numbers and inlet-outlet ports length but declined for Hartmann number and volume fraction. Heat transferring rate and heat transfer irreversibility are substantially increased for higher values of Reynolds number, inlet-outlet ports length, Darcy number and nanoparticle volume fraction but a reverse trend is occurred for magnetic field effect. The thermal performance is found significantly improved with simultaneous increment in Re, ϕ, Da and decrement in Ha. Positive sensitivity is achieved for input factors Re, ϕ, Da in computing N u a v while negative sensitivity to Ha. Heat transfer rate is found more sensitive to the impact of Re and ϕ compared to Da and Ha. 45.59 % more heat transmission potentiality is developed for using Al2O3-H2O nanofluid (vol.5 %) instead of using base fluid water. Heat transfer enhancement rate is decreased by 36.22 % due to impact of magnetic field strength. In addition, 84.12 % more heat transferring rate is recorded in presence of triangular obstacle. Moreover, irreversibility components are influenced significantly for the presence of heated triangular obstacle. Bejan number is also found declined for increasing physical parameters. The findings of this investigation may offer a guideline for finding experimental results to design high-performance convective heat exchangers.

In this paper, the development of a 3D adaptive probabilistic explicit cracking model for concrete is reported. The contribution offered herein consists in a new adaptive mesh strategy designed to optimize the use of interface elements in probabilistic explicit cracking models. The proposed adaptive mesh procedure is markedly different from other strategies found in the literature, since it takes into account possible influences on the redistribution of stresses after cracking and can also be applied to purely deterministic cracking models. The process of obtaining the most appropriate adaptive mesh procedure involved the development and evaluation of three different adaptivity strategies. Two of these adaptivity strategies were shown to be inappropriate due to issues related to stress redistribution after cracking. The validation results demonstrate that the developed adaptive probabilistic model is capable of predicting the scale effect at a level similar to that experimentally observed, considering the tensile failure of plain concrete specimens. The results also show that different softening levels can be obtained. The proposed adaptive mesh strategy proved to be advantageous, being able to promote significant reductions in the simulation time in comparison with the classical strategy commonly used in probabilistic explicit cracking models.

In this study, we propose a method for predicting welding deformation caused by multi-pass welding using the thermal elastic-plastic finite element method (TEP-FEM) by considering the interpass temperature. This method increases the interpass temperature, which has not been considered in the existing TEP-FEM, from 200 °C to 1000 °C, and simultaneously performs thermal and mechanical analyses. In addition, this method can also evaluate temperature history and the time it takes to weld. By predicting the welding deformation using this method, angular distortion prediction was reduced from 16.75 mm to 10.9 mm compared to the case where the interpass temperature was cooled to room temperature. Additionally, the deformation error was significantly reduced from 6.14% to 2.92% compared to that of the strain as directed boundary method used in a previous study. Additionally, our research demonstrated that interpass temperatures above 800 °C can result in increased deformation errors. In conclusion, it is essential to select an appropriate temperature to minimize deformation error.

OBJECTIVE: A personalized model of the knee joint, with adjustable effective geometric parameters for the transplanted autograft diameter in Anterior Cruciate Ligament Reconstruction (ACLR) using the bone-patella-tendon-bone (BPTB) technique, has been developed. The model will assist researchers in understanding how different graft sizes impact a patient\'s recovery over time.
METHODS: The study involved selecting a group of individuals without knee injuries and one patient who had undergone knee surgery. Gait analysis was conducted on the control group and the patient at various time points. A 3D model of the knee joint was created using medical images of the patient. Forces and torques obtained from the gait analysis were applied to the model to perform finite element analysis.
RESULTS: The results of the finite element (FE) analysis, along with kinetic data from both groups, indicate that models with diameters of 7.5 mm and 12 mm improved joint motion during follow-up after ACLR. Additionally, a comparison of the stress applied to the ACL model revealed that a 12 mm autograft diameter showed a more favorable trend in patient recovery during the three follow-up intervals after ACL reconstruction surgery.
CONCLUSIONS: The development of a personalized parametric model with adjustable geometric parameters in ACLR, such as the transplanted autograft diameter, as presented in this study, along with FE using the patient\'s kinetic data, allows for the examination and selection of an appropriate autograft diameter for Patella Tendon grafting. This can help reduce stress on the autograft and prevent damage to other knee joint tissues after ACLR.

The objective of the present research is to explore the temperature diffusion in healthy and cancerous tissues, with a specific focus on how physical activity impacts on the weakening of breast tumors. Previous research lacked numerical analysis regarding the effectiveness of physical activity in tumor prevention or attenuation, prompting an investigation into the mechanism behind physical activity and tumor prevention from a bio-heat transfer perspective. The study employs a realistic model of human breasts and tumors in COMSOL Multiphysics® to analyze temperature distribution by utilizing Penne\'s bio-heat equation. The research examines their influence on tissue temperature by varying tumor diameter (10-20 mm) and exercise intensities (such as walking speeds and other activities like carpentry, swimming, and marathon running). Results demonstrate that cancerous tissues generate notably more heat than normal tissues at rest and during physical activity. Smaller tumors exhibit higher temperatures during exercise, emphasizing the significance of tumor size in treatment effectiveness. Tumor temperatures range between 40 and 43.2 °C, while healthy tissue temperatures remain below 41 °C during physical activity. High-intensity exercises, particularly swimming, walking at 1.8 m/s, and marathon running, display a therapeutic effect on tumors, increasing effectiveness with intensity. The temperatures of healthy and malignant tissues rise noticeably due to constant metabolic heat and decreased blood flow. The study also identifies the optimal duration of high-intensity exercise, recommending at least 20 min for optimal therapeutic outcomes. The outcomes of this research would help individuals, doctors, and cancer researchers understand and weaken malignant tissues.