Feminist Teacher

Vakili S., Banejad A., Ramezani-Fard E., Passandideh-Fard M., Shaegh S.A.

Cristóvão Silva J., Brójo F.

Abstract This study presents a comprehensive analysis of contoured nozzle designs using the Method of Characteristics (MOC) and Fluent simulations. The study aims to compare the performance and flowfield predictions of these methods and explore the influence of various design param- eters on nozzle performance. Initial investigations validate the MOC algorithm’s accuracy against commercial software, highlighting its rapid computational capability despite limita- tions in handling real gas effects. Fluent simulations consistently predict slightly lower specific impulse values due to differing exit pressure predictions but align closely with MOC results in inviscid flow conditions. The research explores the role of the initial circular arc in defin- ing the nozzle’s expansion and straightening sections, finding that smaller circular arcs create larger property gradients, necessitating quicker expansions and leading to potential isentropic losses, which were almost imperceptible in the Fluent case, in fact, a more axial flow was deliv- ered. Variations in design parameters, such as the contour’s exit angle and cone nozzle fraction, demonstrate their impact on nozzle performance, with higher exit angles generally improving specific impulse, contrary to expectation. For some pairs of design options, longer nozzles al- low smoother expansions, resulting in lower average exit angles and improved specific impulse. The findings emphasize the contemporary relevance of the MOC for preliminary nozzle studies, highlighting the balance between accuracy and computational cost.

Geohagan A., Truszkowska A.

Elucidating the complex impact of the geometry and the topology of a porous environment on its performance is important in both studying and computational modeling of such media. This work complements these efforts by putting forth a novel approach capable of identifying media characteristics likely to dominate the underlying physical phenomena. We specifically focus on the flow of a fluid through the medium, due to its significance in nature and emerging engineering applications. Our approach uses statistical analysis to infer flow preferences from small perturbations of the porous environment. We show that the features identified by our methodology are uniquely bound to the type of examined media and that their choice seems uncorrelated among different material classes. We believe that the proposed approach can provide a first estimate of media characteristics that can be tuned in their real applications to achieve better performance. Additionally, it can be used to improve computational approximations, such as two-dimensional or network models.

Azad M.S., Eum D., Moriguchi S., Han T.

This paper presents the fundamental theories of Bayesian updating techniques and literature reviews on their application of the mechanical property assessments on cementitious materials. The application of Bayesian updating in assessing the mechanical properties of cementitious materials has gained substantial attention owing to its ability to integrate probabilistic modeling and uncertainty quantification. In this review, we explore the utilization of Bayesian updating techniques specifically designed for the probabilistic modeling of cementitious materials i.e., concrete as well as cement-treated soil. The effectiveness of the methodology to incorporate prior knowledge, experimental /simulated data to improve the predictions of material behavior was demonstrated and discussed. By combining existing research and highlighting recent developments, this review gives insights into the efficiency and potential prospects for future progress in using Bayesian updating to increase our understanding and prediction of the mechanical properties of cementitious materials The conclusion of this review highlights the scope and possibilities of applying and improving Bayesian updating of mechanical property assessments on cementitious materials.

Yu T., Paradis A.

Cracking of heterogeneous brittle materials like portland cement concrete (PCC) is usually caused by overstressing under tension. Unlike laminated and periodic materials such as fiber reinforced composites and polymers, cracking in heterogeneous brittle materials takes the form of irregular geometries. The objective of this paper is to investigate the quantitative features of multi-scale two-dimensional Julia sets for their use in simulating artificial cracks in heterogeneous brittle materials. Three parameters in the creation of Julia sets are identified in this study, including the maximum iteration number n, the real part of Julia coefficient ( $$c'$$ ), and the imaginary part of Julia coefficient ( $$c''$$ ). Fractal dimension of each Julia set is measured by the box counting method. Crack area A of each Julia set is used to quantify the severity of an artificial crack for engineering applications, as well as crack length L. Threshold value $$\mu $$ and the radius ratio of crack growth r are used to control crack opening width, crack area, and crack length. With an assumed descending relation between threshold value and the radius ratio of crack growth, a normalized simulation time t (depending on threshold value) is proposed to generate fractal cracks at different stages. From our parametric studies, it is found that crack area is exponentially related to fractal dimension by a power factor of 12.15, while fractal dimension is linearly related to the maximum iteration number. Both the increase of $$c'$$ and $$c''$$ generally leads to the linear decrease of fractal dimension but a linear increase of crack area. Crack area is affected by $$c'$$ , $$c''$$ , the maximum iteration number, threshold value and the radius ratio of crack growth. Crack opening width w is affected by iteration number and threshold value. Crack length L is affected by threshold value and the radius ratio of crack growth. A six-step design procedure is proposed for systematically generating fractal cracks at different stages of cracking.

Allahkarami F., Tohidi H.

In this paper, postbuckling of functionally graded (FG) nanocomposite Timoshenko microbeam has been investigated. Using an adjusted micromechanics model of nanofillers, the effective elastic modulus of the structure is determined. The considered distribution scheme of graphene platelets (GPLs) consists of three different type schemes. To access the size-dependent nonlinear differential governing equations, assumptions of Timoshenko’s theory and a nonclassical theory named modified couple stress theory (MCST) have been utilized. After that, both sets of nonlinear governing equations and related boundary equations of microbeam are discretized exerting generalized differential quadrature method (GDQM) accompanied by a classic iteration technique to reach the buckling and postbuckling forces. The impact of diverse parameters including dimensional, size effects, GPLs-related properties and boundary edges’ type on buckling and postbuckling response of microbeam are propounded in detail. The results of this research indicate how the small scale and the GPLs-related properties simultaneously affect the postbuckling behavior of structure.

Jackson A., Koster A., Adnan A.

Recent advances in additive manufacturing have allowed the investigation of the static and dynamic performance of 3-dimensional cellular structures for the application of absorbing mechanical energy. This manuscript examines the performance of body-centered cubic (BCC), face-centered cubic (FCC), diamond cubic (DC), and Kelvin truss (KT) lattice structures. Using a commercially available Ultraviolet Ray (UV)-cured additive manufacturing process, these structures are made of Digital ABS and Shore hardness 60 (SH60) digital materials. The lattice structures were investigated at multiple strain rates under static compression and low velocity impact. The area under the stress–strain response, i.e. total strain energy, is considered as a measure for energy absorption under static test. For low velocity impacts, the differences in acceleration from the top impacted surface and the base of the lattice structure are recorded and are used as a measure for dynamic energy absorption in the context of impact resistance and protection. In static compression it was observed that the FCC and KT lattices had nearly two times more energy absorption compared to the BCC and DC lattices. Under impact the BCC reduced the most acceleration followed by the DC, FCC, and KT lattice. High-speed footage captures fracture modes during impact, while micro-CT scanning visualizes fracture surfaces and predicts damage and failure mechanisms. These findings offer insights into how into how strain rate and inertia variations influence energy absorption, acceleration mitigation, and failure modes of lattice structures, contributing to the development of future novel designs.

Zaman R., Rifat M.N., Maliha F., Hossain M.N., Akhtaruzzaman R., Adnan A.

This study aims to provide an overview of the recent developments in understanding multiscale traumatic brain injury (TBI) mechanisms from a multidisciplinary perspective. TBI is a major cause of death and disability in the United States, affecting people of all ages, genders, and races. On average, in every 5 s, someone in the U.S. experiences TBI-related injuries. According to the CDC, in 2019, there were more than 200,000 TBI-related hospitalizations in the USA. TBI is the most common traumatic injury in the U.S. military. As such, researchers from different fields attempt to investigate TBI risks and propose injury criteria. Yet, a unified TBI risk criterion is not available. This is primarily because the human brain has an overly complex and multiscale anatomy. From a length scale standpoint, the existing brain injury thresholds can be divided over three main scales and criteria: macroscale, tissue level, and cellular level. Macroscale criteria use quantifiable parameters such as acceleration and pressure that are typically taken on or near the head surface. Tissue level criteria are based on internal stress or strain-based injury analysis. Cellular-level injury analyses are based on molecular-level computations and cell culture, which is an emerging sector in brain injury threshold detection. However, there is a significant gap in the literature on connecting the parameters of the three scales and establishing a comprehensive injury criterion. We reviewed a combination of recent multidisciplinary evidence-informed literature and tried to connect the gaps by combining the three scales of TBI. Finally, we summarized the future challenges researchers may face and how we can approach and make progress in detecting TBI accurately.

Raouf I., Gas P., Kim H.S.

This mini review provides a thorough examination of recent advances in finite element analysis (FEA) for cancer therapy, with a focus on magnetic nanoparticle (MNP) hyperthermia. The paper begins by discussing the fundamental principles of FEA and their applications in biomedical sciences. It then describes the application of FEA to the in vitro and in vivo modeling of MNP hyperthermia, including the development and validation of computational models that simulate magnetic nanoparticles behavior under alternating magnetic field (AMF), heat generation, its transfer, and cellular/tissue responses. The review further explores the emerging trends and future directions in the application of FEA for MNP hyperthermia, including the integration of experimental data, incorporation of patient-specific parameters, and optimization of treatment protocols. The paper also discusses the key challenges and limitations of current FEA models, shedding light on potential areas for future research and development. By synthesizing the most recent advances in this field, the review aims to provide a valuable resource for researchers, clinicians, and engineers working on the optimization and clinical translation of MNP hyperthermia for effective cancer therapy.

Mohammadimehr M.A., Loghman A., Ghorbanpour Arani A., Mohammadimehr M.

In the present study, vibration analysis of thick walled sandwich panel reinforced by nanocomposite facesheets based on higher-order shear deformation (HSDT) and nonlocal strain gradient theories (NSGT) is investigated. In this work, there are all components of normal and shear strain/stress. On the other hands, the novelty of this work is to investigate general strain/stress because the sandwich structure is assumed as a thick-walled panel. Also, the current work's significance and necessity is the investigation of two-types reinforcements including carbon nanotubes (CNTs) or graphene’s platelets (GPL) with two-types cores such as porous or metamaterials [graphene origami (GOri) with negative Poisson’s ratio] to analyze vibration response of a thick-walled sandwich panel using higher order shear deformation theory (HSDT) and considering size effect based on nonlocal strain gradient theory (NSGT), thus the above highlights were not done simultaneously until now and becomes the novelty of the present work. The governing motion’s equations for the sandwich panel are obtained using the Hamilton's principle and the extended mixture rule. The effects of different parameters such as Eringen’s non-local parameter, material length scale parameter, various distributions of porosity, porosity coefficient and various distributions of CNT, volume fraction of CNT, volume fraction of GPL, weight fraction of GOri, the folding degree $$\left( {H_{Gr} } \right)$$ and geometric dimensions of GPL on natural frequency is studied. The results of this study show that with an increase in non-local parameter and the length of structure, the natural frequency reduces and by enhancing the material length scale parameter and CNT volume fraction, the natural frequency increases because of increasing the stiffness of the structure. The functionally graded FG-X with respect to FG-O and uniform distribution (UD) has the highest natural frequency because it increases the most stiffness of sandwich panel and finally, the FG-O has the lowest natural frequency. With increasing the length and width of the GPL, the natural frequency increases and vice versa for the thickness of GPL.

Senapati N.P., Bhoi R.K.

The aim of the research is to evaluate the 3-D temperature distribution in the friction stir welding (FSW) joints of AA1100 alloy plates by using Finite difference method. The theoretical results are correlated with experimental output in terms of temperature profiles of the weld zones. Microstructure analysis and tensile test have been conducted to determine the joint quality that strongly depends on the amount of heat generation which again is governed by the processing parameters. Microstructure of the weld samples clearly shows the grain refinement in the weld zone. The friction coefficient is also an important factor that totally depends on the tool pin design. More is the friction; sound welds are produced with minimum defects and an enhanced weld strength. This process finds its applications in the automotive industries as the demand for better performance in joining components for vehicles prompts the implementation of aluminium alloy FSW technology.

Rifat M.N., Adnan A.

Neurons are prone to deformations as a result of the shear effect between the grey and white matters caused by the rapid and sudden movement of the brain tissue during an event of a mechanical impact or neurodegenerative diseases. These structural damages are significantly prominent in the causation of axonal injuries which come in the form of stretching primarily and consequently followed by local swelling as a secondary effect. The microstructural alterations, which are brought about as a result of these physical distortions, have a significant impact on the electrophysiological performance of the neuron cells. The objective of our research was to examine the neural activity in response to the simultaneous impact of swelling and stretching resulting from an altered morphology referred to as varicosity. Our hypothesis postulates that the neuron is able to sustain its signal conduction capacities up to a specific threshold, following exposure to mechanical trauma, and experiences a loss of electrophysiological functionality afterwards upon reaching the critical threshold. Therefore, the aim of our study has been to examine the characteristics of action potential signals within a stretch-induced swelled segment of the axon using computational models aimed at imitating the electrical activity in neuronal cells. The simulations were structured according to the premise that the stretch-induced swelling site possesses ion channels that are vulnerable to mechanical damage, hence influencing the electrophysiology of the transmitted signals. The simulations were conducted to examine the effects of different swelling radii on mechanical strains of fluctuating magnitudes. Thus, we have obtained that the minimum threshold for the applied strain to be $$17\%$$ to cause alterations in the AP signal transmission through an unmyelinated stretched-swelled axon. Notwithstanding this comprehension, further investigation has been required to examine the impact of higher magnitudes of strain rate changes on the performance of ion channels. In summary, the utilization of numerical simulations in conjunction with the models facilitated our ability to predict the damage threshold for a neuron cell by analyzing the extent of axonal electrophysiological deficits in response to the injury sustained at the cellular level.

Koster A., Adnan A.

Due to the highly transient nature of head injury events that lead to traumatic brain injury (TBI) and the complexity of the human head, a structural-dynamics-informed design process is needed to augment research efforts that utilize human head surrogate models. Such models are capable of accurately mimicking the response of biological systems and allow for models that explore biological differences between individuals. This study explores the relevant mechanisms and parameters that contribute to the dynamic response of biological and additive manufactured surrogate head models and proposes an iterative design process to compare the two systems. Using experimental and finite element method (FEM) modal analysis, a balance between geometric complexity, computational resources, and manufacturability are considered when building a head model for obtaining pressures, strains, or other relevant injury indicators similar to that of a biological system. This study used a simplified ellipsoid head model to meaningfully change the response of the additive manufactured model similar to a model simulated with biological material properties. Additionally, a single layer of a digital material was used to mimic the dynamic response of the simulated head surrogate with two layers of biological materials; the scalp, and the skull. This study successfully outlined and exhibited the most basic application of a structural-dynamics-informed design process to create improved head surrogate models and to effectively compare the results from current head surrogate models to real biological systems.

Najman S., Yang P., Pao C.

Lead-halide organic–inorganic perovskite material has recently been the focus of investigation by numerous research groups due to its favorable properties when employed as an active layer in a wide range of photovoltaic and optoelectronic devices. 2D perovskite layered type was introduced as a solution to the inherent moisture instability of the 3D counterpart, while at the same time enabling the tunability of the aforementioned properties through a spacer to perovskite layer ratio. However, theoretical studies of the layered 2D perovskites have been limited to the density functional level of theory (DFT) due to the lack of reliable force-fields that are necessary to explore the properties of this material observable only on a large scale. In this work, we employed the machine learning enabled Spectral Neighbor Analysis Potential (SNAP) to obtain the quantum accurate description of energies and forces in 2D layered Ruddlesden–Popper perovskite material, with butylammonium (BA) molecule included as a spacer. The trained SNAP potential reproduces both energies and forces of the reference atomic configurations with high fidelity and comparable with DFT calculations. Furthermore, the potential is stable at both 300 and 400 K which is verified for the first five 2D perovskite members under the canonical ensemble in bulk phase for 0.5 ns.

Verma S., Singh G., Chanda A.

Vibrations can have a range of pathological effects on the human spine, such as lower-back pain. Such effects are commonly observed in tractor drivers, earthmoving machinery (Excavators, Backhoes and Bulldozers etc.) and buses, as well as in the general public who drive for prolonged time. To date, majorly experimental studies have been conducted to understand the negative vibrational effects on the spine, especially in the lumber section. However, there is insufficient knowledge about vibrational characteristics that may severely effect to the various spinal segments. In this work, a novel finite element model was created to study the vibrational effects on the spine's lumbar, thoracic, and cervical sections. Each spinal section was considered with various vertebrae and discs, sand both homogenous and composite-based material models were tested. The system equations were employed to solve the eigenvalue problem and quantify the natural frequencies for different spinal sections with both material models. The developed FE model was validated by comparing the results for the lumber section with the literature. The natural frequencies were estimated for the different spinal sections for the first time, which, if matched by any external vibration, may cause resonance and harm the spine, including lower back pain and fracture. The findings would be valuable for the global spine community and manufacturers of automobiles, railways, airplanes, and spacecraft.