To optimize the assembly methods of honeycomb structures and enhance their design flexibility, this study investigated the impact mechanical responses of tandem honeycomb-core sandwich structures with varying misalignment assembly lengths. Impact tests were conducted across different energy levels on single-layer and tandem honeycomb-core sandwiches to observe their impact processes and failure behaviors. Our findings indicate that tandem honeycomb cores significantly enhance the impact resistance compared with single-layer configurations, even though a misaligned assembly can deteriorate this property. A finite element model was developed and validated experimentally; the model showed good agreement with the experiments, thereby allowing the simulation and evaluation of the impact responses. Herein, we reveal that specific misalignment lengths can either increase or decrease the impact resistance, providing insights into improving the resilience of tandem honeycomb-core structures. Our results not only contribute to enhancing the impact resistance of honeycomb-core sandwich structures but also offer a valuable basis for their practical applications in engineering.

Indentation is a versatile method to assess the hardness of different materials along with their elastic properties. Recently, powerful approaches have been developed to determine further material properties, like yield strength, ultimate tensile strength, work-hardening rate, and even cyclic plastic properties, by a combination of indentation testing and computer simulations. The basic idea of these approaches is to simulate the indentation with known process parameters and to iteratively optimize the initially unknown material properties until just a minimum error between numerical and experimental results is achieved. In this work, we have developed a protocol for instrumented indentation tests and a procedure for the inverse analysis of the experimental data to obtain material parameters for time-dependent viscoplastic material behavior and kinematic and isotropic work-hardening. We assume the elastic material properties and the initial yield strength to be known because these values can be determined independently from indentation tests. Two optimization strategies were performed and compared for identification of the material parameters. The new inverse method for spherical indentation has been successfully applied to martensitic steel.

Implant subsidence into the underlying trabecular bone is a common problem in orthopaedic surgeries; however, the ability to pre-operatively predict implant subsidence remains limited. Current state-of-the-art computational models for predicting subsidence have issues addressing this clinical problem, often resulting from the size and complexity of existing subject-specific, image-based finite element (FE) models. The current study aimed to develop a simplified approach to FE modeling of subject-specific trabecular bone indentation resulting from implant penetration. Confined indentation experiments of human trabecular bone with flat- and sharp-tip indenters were simulated using FE analysis. A generalized continuum-level approach using a meshless smoothed particle hydrodynamics (SPH) approach and an isotropic crushable foam (CF) material model was developed for the trabecular bone specimens. Five FE models were generated with CF material parameters calibrated to cadaveric specimens spanning a range of bone mineral densities (BMD). Additionally, an alternative model configuration was developed that included consideration of bone marrow, with bone and marrow material parameters assigned to elements randomly according to bone volume (BV%) measurements of experimental specimens, owing to the non-uniform nature of trabecular bone tissue microstructure. Statistical analysis found significant correlation between the shapes of the numerical and experimental force-displacement curves. FE models accurately captured the bone densification patterns observed experimentally. Inclusion of marrow elements offered improved response prediction of the flat-tip indenter tests. Ultimately, the developed approach demonstrates the ability of a generalizable continuum-level SPH approach to capture bone variability using clinical bone imaging metrics without needing detailed image-based geometries, a significant step towards simplified subject-specific modeling of implant subsidence.

Like other odontocetes, Risso\'s dolphins actively emit clicks and passively listen to the echoes during echolocation. However, the head anatomy of Risso\'s dolphins differs from that of other odontocetes by a unique vertical cleft along the anterior surface of the forehead and a differently-shaped lower jaw. In this study, 3D finite-element sound reception and production models were constructed based on computed tomography (CT) data of a deceased Risso\'s dolphin. Our results were verified by finding good agreement with experimental measurements of hearing sensitivity. Moreover, the acoustic pathway for sounds to travel from the seawater into the dolphin\'s tympanoperiotic complexes (TPCs) was computed. The gular reception mechanism, previously discovered inDelphinus delphisandZiphius cavirostris, was also found in this species. The received sound pressure levels and relative displacement at TPC surfaces were compared between the cases with and without the mandibular fats or mandible. The results demonstrate a pronounced wave-guiding role of the mandibular fats and a limited bone-conductor role of the mandible. For sound production modelling, we digitally filled the cleft with neighbouring soft tissues, creating a hypothetical \'cleftless\' head. Comparison between sound travelling through a \'cleftless\' head vs. an original head indicates that the distinctive cleft plays a limited role in biosonar sound propagation.

Investigating and understanding the biomechanical kinematics and kinetics of human brain axonal fibers during head impact process is crucial to study the mechanisms of Traumatic Axonal Injury (TAI). Such a study may require the explicit incorporation of brain fiber tracts into the host brain in order to distinguish the mechanical states of axonal fibers and brain tissue. Herein we extend our previously developed human head model by using an embedded element method to include fiber tracts reconstructed from diffusion tensor images in a host brain with the purpose of numerically tracking the deformation state of axonal fiber tracts during a head impact simulation. The updated model is validated by comparing its prediction of intracranial pressures with experimental data, followed by a thorough study of the effects of element types used for fiber tracts and the stiffness ratios of fiber to host brain. The validated model is also used to predict and visualize the damaged region of fiber tracts during the head impact process based on different injury criteria. The model is promising in tracking the state of fiber tracts and can add more objective functions such as axonal fiber deformation if used in the future design optimization of head protective equipment such as a football helmet.

Micro-scale models of lung tissue have been employed by researchers to investigate alveolar mechanics; however, they have been limited by the lack of biofidelic material properties for the alveolar wall. To address this challenge, a finite element model of an alveolar cluster was developed comprising a tetrakaidecahedron array with the nominal characteristics of human alveolar structure. Lung expansion was simulated in the model by prescribing a pressure and monitoring the volume, to produce a pressure-volume (PV) response that could be compared to experimental PV data. The alveolar wall properties in the model were optimized to match experimental PV response of lungs filled with saline, to eliminate surface tension effects and isolate the alveolar wall tissue response. When simulated in uniaxial tension, the model was in agreement with reported experimental properties of uniaxial tension on excised lung tissue. The work presented herein was able to link micro-scale alveolar response to two disparate macroscopic experimental datasets (stress-stretch and PV response of lung) and presents hyperelastic properties of the alveolar wall for use in alveolar scale finite element models and multi-scale models. Future research will incorporate surface tension effects, and investigate alveolar injury mechanisms.

The risk of aseptic loosening in cementless hip stems can be reduced by improving osseointegration with osteoinductive coatings favoring long-term implant stability. Osseointegration is usually evaluated in vivo studies, which, however, do not reproduce the mechanically driven adaptation process. This study aims to develop an in silico model to predict implant osseointegration and the effect of induced micromotion on long-term stability, including a calibration of the material osteoinductivity with conventional in vivo studies. A Finite Element model of the tibia implanted with pins was generated, exploiting bone-to-implant contact measures of cylindrical titanium alloys implanted in rabbits\' tibiae. The evolution of the contact status between bone and implant was modeled using a finite state machine, which updated the contact state at each iteration based on relative micromotion, shear and tensile stresses, and bone-to-implant distance. The model was calibrated with in vivo data by identifying the maximum bridgeable gap. Afterward, a push-out test was simulated to predict the axial load that caused the macroscopic mobilization of the pin. The bone-implant bridgeable gap ranged between 50 μm and 80 μm. Predicted push-out strength ranged from 19 N to 21 N (5.4 MPa-3.4 MPa) depending on final bone-to-implant contact. Push-out strength agrees with experimental measurements from a previous animal study (4 ± 1 MPa), carried out using the same implant material, coated, or uncoated. This method can partially replace in vivo studies and predict the long-term stability of cementless hip stems.

Carbon Fiber Reinforced Polymers (CFRP) have become increasingly significant in real-world applications due to their superior strength-to-weight ratio, corrosion resistance, and high stiffness. These properties make CFRP an ideal material for reinforcing concrete structures, particularly in scenarios where weight reduction is crucial, such as in bridges and high-rise buildings. The transformative potential of CFRP lies in its ability to enhance the durability and load-bearing capacity of concrete structures while minimizing maintenance costs and extending the lifespan of the infrastructure. This research explores the impact of reinforcing structural elements with advanced composite materials on the strength and durability of concrete and reinforced concrete structures. By integrating Carbon Fiber Reinforced Polymer (CFRP) reinforcements, we subjected both rectangular and T-section concrete beams to comprehensive three-point bending tests, revealing a substantial increase in flexural strength by 45% and crack resistance due to CFRP reinforcement. The study revealed that CFRP reinforcement increased the flexural strength of concrete beams by 45% and improved crack resistance significantly. Additionally, the load-bearing capacity of the beams was enhanced by 40% compared to unreinforced specimens. These improvements were validated through finite element simulations, which showed a close alignment with the experimental data. Furthermore, an innovative simulation study was conducted using a finely tuned finite element numerical model within the Abaqus calculation code. This model accurately replicated the laboratory specimens in terms of shape, dimensions, and loading conditions. The simulation results not only validated the experimental observations but also provided deeper insights into the stress distribution and failure mechanisms of the reinforced beams. Novel aspects of this study include the identification of specific failure patterns unique to CFRP-reinforced beams and the introduction of an enhanced interaction model that more accurately reflects the composite behavior under load. In CFRP-reinforced beams, specific failure patterns were identified, including flexural cracks in the tension zone and debonding of the CFRP sheets. These patterns indicate the points of maximum stress concentration and potential weaknesses in the reinforcement strategy. The study revealed that while CFRP significantly improves the overall strength and stiffness, careful attention must be given to the bonding process and the quality of the adhesive used to ensure optimal performance. These findings contribute significantly to the understanding of material interactions and structural performance, offering new pathways for the design and optimization of composite-reinforced concrete structures. This research underscores the transformative potential of composite materials in elevating the structural integrity and longevity of concrete infrastructures.

Cervical laminoplasty is an established motion-preserving procedure for degenerative cervical myelopathy (DCM). However, patients with pre-existing cervical kyphosis often experience inferior outcomes compared to those with straight or lordotic spines. Limited dorsal spinal cord shift in kyphotic spines post-decompression and increased spinal cord tension may contribute to poor neurological recovery and spinal cord injury. This study aims to quantify the biomechanical impact of cervical sagittal alignment on spinal cord stress and strain post-laminoplasty using a validated 3D finite element model of the C2-T1 spine. Three models were created based on the C2-C7 Cobb angle: lordosis (20 degrees), straight (0 degrees), and kyphosis (-9 degrees). Open-door laminoplasty was simulated at C4, C5, and C6 levels, followed by physiological neck flexion and extension. The results showed that spinal cord stress and strain were highest in kyphotic curvature compared to straight and lordotic curvatures across all cervical segments, despite similar segmental ROM. In flexion, kyphotic spines exhibited 103.3% higher stress and 128.9% higher strain than lordotic spines and 16.7% higher stress and 26.8% higher strain than straight spines. In extension, kyphotic spines showed 135.4% higher stress and 241.7% higher strain than lordotic spines and 21.5% higher stress and 43.2% higher strain than straight spines. The study shows that cervical kyphosis leads to increased spinal cord stress and strain post-laminoplasty, underscoring the need to address sagittal alignment in addition to decompression for optimal patient outcomes.

OBJECTIVE: 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.
CONCLUSIONS: 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.