Actin filaments are found in abundance in the neuron cytoskeleton, cell body, and dendrites. In the context of multiscale traumatic brain injury (TBI) analysis, in which a single mechanical impact can trigger damage ranging from molecular and subcellular disruptions to cellular and tissue-level structural changes, understanding the damage thresholds and failure mechanisms of actin filaments in response to mechanical trauma is essential. Structurally, actin filaments are comprised of polymerized globular actin (G-actin) and play a pivotal role in maintaining the structural integrity and functional properties of neurons. The dynamic nature of actin filaments, including their polymerization and depolymerization, enables them to respond rapidly to changes in mechanical stress and cellular signaling. However, this adaptability also makes actin filaments vulnerable to mechanical injury, especially in the event of TBI. Although there are a few isolated studies on the mechanical response of actin filaments, a systematic study of the failure strain threshold under mechanical loading remains unexplored. Nevertheless, modeling the overall failure analysis of neurons requires a reliable estimate of this value. This study primarily aims to evaluate the mechanical damage of actin filaments using Molecular Dynamics (MD) simulations. Using MD simulations, this research has reported the primary value of failure strain for actin filaments under varying high-strain-rate mechanical loadings 107, 108 and, 109 S−1. Here, failure refers to the structural rupture of the actin filament. The molecular simulations were conducted using LAMMPS, the widely accessible molecular dynamics solver. The interatomic potentials for the interacting atoms and molecules were modeled using OPLS force fields. Standard simulation steps, including energy minimization, equilibration, and uniaxial tensile stretching, have been followed. Here, we find that failure of actin filaments predominantly initiates at strains of approximately 5–8
Standard finite element analysis of the human femur often relies on simplified, homogenous STL surface meshes that neglect the bone’s intricate internal architecture. This study aims to bridge the gap between engineering models and biological reality by developing a high-fidelity composite model that accounts for the distinct mechanical behaviors of the cortical shell, trabecular lattice, and bone marrow. A realistic 3D femur geometry was generated from CT scan data. Unlike traditional solid models, this approach explicitly modeled the cortical bone as an anisotropic shell, the marrow as a solid volume, and the trabeculae as a discrete truss-like structure. An optimization framework using the Adaptive Multiple-Objective method (NSGA-II) was then implemented to adjust the spatial coordinates of the trabecular points. The goal was to minimize maximum equivalent stress under a 100 N physiological load while maintaining a constant geometry mass of 0.11953 kg. The optimization process evaluated 414 design points over 15 days. Results showed that by strategically relocating internal structural points, the model effectively redistributed stress concentrations. The final optimized candidate achieved a reduction in maximum stress to 889.14 MPa. This research demonstrates that incorporating internal bone components with precise material properties significantly alters predicted stress distributions. By successfully relocating structural elements to optimize load paths, this framework presents a structural optimization approach biologically inspired by the objectives of Wolff’s Law. Rather than simulating time-dependent biological remodeling pathways, the framework optimizes for the ideal final mechanical state of material placement. These findings offer a foundational framework for designing advanced orthopaedic implants and bio-synthetic bones that mimic the strength and efficiency of natural human anatomy.
This paper reviews techniques for modeling binders during electrode calendering process using the Discrete Element Method (DEM), one of the battery multiscale simulation techniques. Simulation techniques are broadly divided into two types: the first is the bonded-particle model, which implements the binder as a bond between active materials without explicit consideration of the binder, and the second is the explicit binder model, which explicitly considers the binder particles. Along with each binder model, the contact model between particles is also described. Afterwards, based on the case in the reference paper, the application of the binder model is explained, and the advantages and disadvantages of each binder model are explained based on the application. Overall, the bonded-particle model has the advantage of reducing the calculation time and reproducing the mechanical properties of the binder, while the explicit binder model has the advantage of more realistically simulating the electrode structure and electrochemical coupling. Based on this, the main limitations of the current simulation model and future research directions toward overcoming these limitations through multiscale, multiphysics simulation and data-driven approaches are presented.
This study involved a computational analysis of the flow of a boundary layer and heat/ mass transport over a plate that is in motion and submerged in a nanofluid. The examination considered factors such as the loss of energy due to viscosity, the variation in viscosity and the thermal conductivity. Utilizing the similarity variable, the model equations are reduced into a system of coupled nondimensional equation and an efficient numerical techniques like MATLAB package and Keller-box has been incorporated to solve the coupled nonlinear ODEs. By the analysis, it is found that solutions exists for the various influences on flow momentum and thermal profiles as well as the velocity and heat mass transfer rates along with nanofluid particle transfer characteristics. We conducted an analysis and discussion on the flow and heat mass transfer characteristics such as the Prandtl number, plate velocity, Brownian motion, effective temperature, thermophoresis, Brinkman number and Lewis number. The results agree with previously literature work. The results of this study suggest that elevating the values of effective temperature results in a reduction in the Nusselt number. The thermal conductivity parameter plays a critical role in amplifying the interaction between thermal and flow fields.
Steel bridge columns with circular hollow sections were parametrically analyzed for investigating their nonlinear behavior with respect to three factors. They are the compressive axial force, diameter-to-thickness ratio (D/t), and slenderness ratio. Three parameters, namely the compressive axial force, tube-wall thickness, and column length, were varied for defining 125 tube models with the same diameter and material of steel (S355). All models are prescribed with the same lateral drift ratio at their top surfaces in pushover analysis. Each parameter has 5 instances configured according to specifications by Caltrans and Japan Road Association. Abaqus was used to create these models and carry out their pushover analyses. And Abaqus scripting interface was utilized to automate creating each finite element model with different parameters. The analysis results show how the D/t ratio dominates the emergence of local buckling near the column bottom and the trend of a column’s pushover nonlinear behavior. It is also shown how the three parameters affect a column’s lateral strength, ductility, and strength degradation. Moreover, Caltrans’s upper bound of D/t specialized for S355 appears as a threshold above which local buckling is likely to emerge.
