Shear Model Research Articles

Shear mechanism and strength calculation of steel shear keyed dry joints in precast segmental bridges

Precast concrete segmental bridges (PCSBs) are prone to weakness at the joints. To ensure accurate positioning and effective force transmission between segments, steel shear keyed joints were designed in the present study. A comprehensive investigation was also conducted into the shear performance of such joints, drawing on existing experimental research and theoretical analysis, so as to facilitate more comprehensive understanding of the shear mechanism and calculation methods involved. The results reveal that the steel shear keyed joint effectively transmitted shear force through the contact pressure between the steel key and concrete, aided by confining pressure. The steel keyed joint was also found to possess high shear capacity and exhibit good ductility. A mechanical model of the steel shear keyed joint was constructed, and the shear mechanism and failure modes were revealed, including shear failure of the steel key, local compression failure of concrete, and tearing failure of concrete. Finally, the present authors suggest that the shear failure of the steel key should be used as the basis for the shear resistance design of steel shear keyed joints, which can be calculated according to the formula ( The strength of concrete around the steel key should also be checked.

Stability of tunnel face in unsaturated sand possessing apparent cohesion: A micro-macro analytical approach

Although the stability of tunnel face in the dry and saturated sandy ground is widely studied, the unsaturated sandy ground which possesses apparent cohesion is more common in engineering. For remedying this deficiency, the theoretical association between apparent cohesion and the saturation degree is firstly established in microscopic prospective. Then, the formation mechanism of the self-stabilized arch and the limit support pressure (LSP) of the tunnel face are derived by incorporating apparent cohesion into the macroscopic limit equilibrium analysis of the multi-arches model. Subsequently, the validities of the proposed approach in estimating apparent cohesion, loosening zone height and LSP are well confirmed (the average error rates of LSP are within 12 %) via comparisons with direct shear tests, model tests and other existing methods. Finally, as revealed by the parametric discussion, under the effect of apparent cohesion, LSP is negatively correlated with compactness, internal friction angle, and contact angle while decreases firstly (to a minimum value of 0.09γD ∼ 0.15γD) and then increase with the rise of saturation degree. Besides, the LSP has a parabolic distribution along the depth with its peak value emerges between 0.3D and 0.45D.

Peierls plasticity of thermoelectric lead telluride assessed by local misfit energy

High brittleness observed in p-type PbTe is a significant obstacle in the commercial use of PbTe-based thermoelectric materials. An in-depth study of dislocations in PbTe is crucial due to their significant impact on material plasticity. In this work, the properties of 12[011](0 1¯ 1) edge dislocation in PbTe are investigated by using the local misfit energy of a shear model within the framework of the Peierls–Nabarro theory. By incorporating a moderate strain region size, a smooth and gradual transition of Pb–Te bonds during the shear process can be facilitated while balancing the elastic and inelastic components of the local misfit energy. The average misfit energy and the Peierls stress of the dislocation are calculated and compared with those of SrTiO3, a material that has demonstrated unexpected plasticity in its single crystal form. The findings indicate that undoped PbTe exhibits reasonably good plasticity. This work presents a theoretical approach to investigate dislocation properties in PbTe, laying the foundation for further research on the mechanical aspects of p-type dopant-induced issues in PbTe-based materials.

Effects of molecular weight of polyethylene glycol with size and ratio of fumed silica on rheological behavior of shear thickening fluid

The rheological models of shear thickening fluids (STFs), which have recently been used in many fields, are estimated using a statistical method in this study. Although research has been carried out to predict the rheological properties of STFs, the variation of the basic parameters affecting the rheological properties has not been studied much in these estimations. To produce shear thickening fluids, silica nanoparticles have been dispersed in polyethylene glycol (PEG). To make the rheological model estimation correctly, nanoparticle ratios (10 wt%, 15 wt%, 20 wt%, 25 wt%), the particle sizes (9 nm, 12 nm, and 14 nm), and the molecular weight of the liquid mediums are produced by changing three different sample set is used. At high shear rates, mixtures of fumed silica (aerosil) and PEG display shear thickening behavior. In the low shear rates (0-200 s-1), this mixture exhibits shear thinning property, while in the high shear rates (200-1000 s-1), shear thickening behavior. Fumed silica-PEG suspensions show pseudoplastic behavior in the first region and dilatant properties in the second region. Equations from theory are used to model the outcomes of the experimental data. Non-Newtonian models are used, and the best model is chosen based on the rheological behavior of the mixes. Herschel-Bulkley is discovered to be the most suitable non-Newtonian model in the first and second regions.

Shear wave elastography-based deep learning model for prognosis of patients with acutely decompensated cirrhosis.

This study aimed to develop and validate a deep learning model based on two-dimensional (2D) shear wave elastography (SWE) for predicting prognosis in patients with acutely decompensated cirrhosis. We prospectively enrolled 288 acutely decompensated cirrhosis patients with a minimum 1-year follow-up, divided into a training cohort (202 patients, 1010 2D SWE images) and a test cohort (86 patients, 430 2D SWE images). Using transfer learning by Resnet-50 to analyze 2D SWE images, a SWE-based deep learning signature (DLswe) was developed for 1-year mortality prediction. A combined nomogram was established by incorporating deep learning SWE information and laboratory data through a multivariate Cox regression analysis. The performance of the nomogram was evaluated with respect to predictive discrimination, calibration, and clinical usefulness in the training and test cohorts. The C-index for DLswe was 0.748 (95% CI 0.666-0.829) and 0.744 (95% CI 0.623-0.864) in the training and test cohorts, respectively. The combined nomogram significantly improved the C-index, accuracy, sensitivity, and specificity of DLswe to 0.823 (95% CI 0.763-0.883), 86%, 75%, and 89% in the training cohort, and 0.808 (95% CI 0.707-0.909), 83%, 74%, and 85% in the test cohort (both p < 0.05). Calibration curves demonstrated good calibration of the combined nomogram. Decision curve analysis indicated that the nomogram was clinically valuable. The 2D SWE-based deep learning model holds promise as a noninvasive tool to capture valuable prognostic information, thereby improving outcome prediction in patients with acutely decompensated cirrhosis.

Shear strength and behavior of recycled strap fiber reinforced concrete haunched beams

Haunched beams also known as tapered beams, are structural elements characterized by varying depths along their span. In light of the growing concern over plastic accumulation on a global scale which provides a threat to the environment, and the challenges associated with employing traditional stirrups in the construction of tapered elements, this research paper has emerged.The approach of this study is divided into two main parts: an experimental phase and an analytical phase. In the initial stage, eight beams were subjected to testing to investigate the influence of tapered angles and the presence of recycled strap fiber on the shear behavior of tapered beams. The outcomes of this experimentation revealed a significant trend: as the tapered angles and fiber contents increased, the shear strength of haunched beams also increased.The subsequent phase of the study focused on an analytical examination, incorporating models proposed in various literature sources. A comprehensive database of 91 beams was assembled to facilitate the selection of the most suitable shear model for modification. Building upon the analysis of this extensive dataset, an equation was proposed. Additionally, a smaller dataset featuring tapered beams with fiber was collected to apply further analysis and demonstrate the models' performance. The predicted results by the proposed model showed good agreement with experimental test results.

Durability Analysis of CFRP Adhesive Joints: A Study Based on Entropy Damage Modeling Using FEM.

Experimental methodologies for fatigue lifetime prediction are time-intensive and susceptible to environmental variables. Although the cohesive zone model is popular for predicting adhesive fatigue lifetime, entropy-based methods have also displayed potential. This study aims to (1) provide an understanding of the durability characteristics of carbon fiber-reinforced plastic (CFRP) adhesive joints by incorporating an entropy damage model within the context of the finite element method and (2) examine the effects of different adhesive layer thicknesses on single-lap shear models. As the thickness of the adhesive layer increases, damage variables initially increase and then decrease. These peak at 0.3 mm. This observation provides a crucial understanding of the stress behavior at the resin-CFRP interface and the fatigue mechanisms of the resin.

WHAT IS THE MAIN FACTOR CONTROLLING THE SUKADANA BASALT IN THE SUMATRA BACK ARC?

The mechanism of the presence of the Sukadana basalt in the back arc of Sumatra is still an enigma, especially since the Sukadana basalt has a wide coverage area in Sumatra Island and even the Sunda Arc. In this study, we used the published research data as the main contributor to an in-depth analysis to determine the mechanism of the presence of Sukadana basalt in the back arc. This study is supported by other studies from different regions around the world. These strengthen our conclusion that the emergence of Sukadana basalt on the surface is controlled by extensional deformations associated with the northwest-southeast-trending normal fault, which are formed by the mechanism of gravitational subsidence due to the movement of the Sumatra fault. In this study we suppose that the Nishimura fracture is a sinistral strike-slip fault as it is consistent with the Riedel shear model.

MLPER: A Machine Learning-Based Prediction Model for Building Earthquake Response Using Ambient Vibration Measurements

Deep neural networks (DNNs) have gained prominence in addressing regression problems, offering versatile architectural designs that cater to various applications. In the field of earthquake engineering, seismic response prediction is a critical area of study. Simplified models such as single-degree-of-freedom (SDOF) and multi-degree-of-freedom (MDOF) systems have traditionally provided valuable insights into structural behavior, known for their computational efficiency facilitating faster simulations. However, these models have notable limitations in capturing the nuanced nonlinear behavior of structures and the spatial variability of ground motions. This study focuses on leveraging ambient vibration (AV) measurements of buildings, combined with earthquake (EQ) time-history data, to create a predictive model using a neural network (NN) in image format. The primary objective is to predict a specific building’s earthquake response accurately. The training dataset consists of 1197 MDOF 2D shear models, generating a total of 32,319 training samples. To evaluate the performance of the proposed model, termed MLPER (machine learning-based prediction of building structures’ earthquake response), several metrics are employed. These include the mean absolute percentage error (MAPE) and the mean deviation angle (MDA) for comparisons in the time domain. Additionally, we assess magnitude-squared coherence values and phase differences (Δφ) for comparisons in the frequency domain. This study underscores the potential of the MLPER as a reliable tool for predicting building earthquake responses, addressing the limitations of simplified models. By integrating AV measurements and EQ time-history data into a neural network framework, the MLPER offers a promising avenue for enhancing our understanding of structural behavior during seismic events, ultimately contributing to improved earthquake resilience in building design and engineering.

Research on rheological properties and phenomenological theory-based constitutive model of magnetorheological shear thickening fluids

This paper investigates the rheological properties of magnetorheological shear thickening fluid (MRSTF) and proposes a phenomenological theory-based constitutive model. Multiple samples with varying mass fractions and particle sizes were prepared. Then, the rheological properties were experimentally studied, including the effects of silicon particle size and concentration, carbonyl iron powder concentration and magnetic field on rheological properties. Next, the sedimentation stability experiment was also carried out by the static observation method. Finally, based on phenomenological theory, a constitutive model called the M-S model was derived through geometric transformation of shear stress curves. The results show that there is an inhibitory relationship between magnetorheological and shear thickening effect, and the correlation between composition and rheological properties was established, which can provide guidance for preparation of MRSTF with required properties. It also shows that the MRSTF under specific preparation scheme could effectively avoid sedimentation, and its performance is clearly superior to traditional materials in terms of sedimentation resistance and damping adjustment. The accuracy and universality of the proposed model are fully verified by fitting shear stress curves and calculating the goodness of fit values. All these investigations can offer an effective guidance for further study of MRSTF in controllable damping equipment development.

A Molecular Dynamics Simulation Study on Enhancement of Mechanical and Tribological Properties of Nitrile-Butadiene Rubber with Varied Contents of Acrylonitrile.

The molecular models of nitrile-butadiene rubber (NBR) with varied contents of acrylonitrile (ACN) were developed and investigated to provide an understanding of the enhancement mechanisms of ACN. The investigation was conducted using molecular dynamics (MD) simulations to calculate and predict the mechanical and tribological properties of NBR through the constant strain method and the shearing model. The MD simulation results showed that the mechanical properties of NBR showed an increasing trend until the content of ACN reached 40%. The mechanism to enhance the strength of the rubber by ACN was investigated and analyzed by assessing the binding energy, radius of gyration, mean square displacement, and free volume. The abrasion rate (AR) of NBR was calculated using Fe-NBR-Fe models during the friction processes. The wear results of atomistic simulations indicated that the NBR with 40% ACN content had the best tribological properties due to the synergy among appropriate polarity, rigidity, and chain length of the NBR molecules. In addition, the random forest regression model of predicted AR, based on the dataset of feature parameters extracted by the MD models, was developed to obtain the variable importance for identifying the highly correlated parameters of AR. The torsion-bend-bend energy was obtained and used to successfully predict the AR trend on the new NBR models with other acrylonitrile contents.

Micromechanical fiber-matrix interface model for in-plane shear in unidirectional laminae

A novel analytical model is proposed for the in-plane shear response of unidirectional composites on account of fiber-matrix interface. The fiber-matrix interface influences the stiffness and induces nonlinear phenomena, playing a fundamental role in the damage onset and propagation. The interface consists of three zones: fiber-transition, core, and matrix-transition. The transition zones are assumed to have zero thicknesses, while the core zone is a layer with finite thickness. Fiber-transition zone is characterized by a nonlinear damage behavior. The analytical model is verified by comparing with finite element simulations and experimental data, indicating adequate description of the complex phenomena under study.

A critical state three-dimensional multi-shear model for soil-structure interfaces under monotonic and cyclic loading

In this paper, a three-dimensional(3D) multi-shear model of soil-structure interface is established by using the plasticity theory of boundary surface. State parameters are introduced to predict the interface response under different soil densities and normal stress. A constitutive equation is established following the assumption that the interface response is decomposed into macro-response and a series of directional-dependent micro-shear responses. The calculation method of plastic microshear strain is modified, a new calculation method of microscopic plastic shear modulus is introduced, and the calculation parameters are reduced. The proposed model can reasonably describe the variation of stress–strain relationship under 3D shearing conditions and predict the three-dimensional non-linear mechanical behaviour of the contact surface. The proposed model has a unified calculation formula for loose and dense interfaces under different loading conditions. The proposed model can be accurately described the dilatancy characteristics under low normal stress and shear shrinkage under high normal stress. The proposed model can simulate the cyclic response characteristics of the interface, e.g., the normal displacement increases with increasing cycle number, however, the growth rate decreases with increasing cycle number. The validity of the proposed three-dimensional multi-mechanism shear model of soil-structure interface under different boundary and loading conditions is verified by comparing the calculation results with the experimental results.

Shear Stress and ROS Dual-Responsive RBC-Hitchhiking Nanoparticles for Atherosclerosis Therapy.

Atherosclerosis (AS), a leading cause of death worldwide, is a chronic inflammatory disease rich in lipids and reactive oxygen species (ROS) within plaques. Therefore, lowering lipid and ROS levels is effective in treating AS and reducing AS-induced mortality. In this study, an intelligent biomimetic drug delivery system that specifically responded to both shear stress and ROS microenvironment was developed, consisting of red blood cells (RBCs) and cross-linked polyethyleneimine nanoparticles (SA PEI) loaded with a lipid-lowering drug simvastatin acid (SA), and RBCs were self-assembled with SA PEI to obtain biresponsive SA PEI@RBCs for the treatment of AS. SA PEI could achieve sustained release of SA in response to ROS and reduce ROS and lipid levels to achieve the purpose of treating AS. Shear stress model experiments showed that SA PEI@RBCs could respond to the high shear stress level (100 dynes/cm2) at plaques, realizing the desorption and enrichment of SA PEI and improving the therapeutic efficiency of SA PEI@RBCs. In vitro and in vivo experiments have confirmed that SA PEI@RBCs exhibits better in vivo safety and therapeutic efficacy than SA PEI and free SA. Therefore, shaping SA PEI@RBCs into a biomimetic drug delivery system with dual sensitivity to ROS and shear stress is an effective strategy and treatment to facilitate their delivery into plaques.

Data Cleansing &amp; Overfitting Check for Interpretable ML in Concrete Design – a punching shear paradigm

AbstractEvaluation of shear capacity is crucial for existing concrete buildings and bridges. Shear failure can cause an abrupt and brittle loss of load‐carrying capacity, leading to load redistribution and progressive collapse. An internationally research and scietific discourse is actively ongoing on the best prediction model for shear, torsion, and punching shear capacity, with no clear consensus. A machine learning‐based strength model is suggested for accurate prediction of punching shear capacity, using Gaussian Process Regression and Support Vector Regression models. Data elaboration and thorough evaluation are needed to enhance the model's performance and interpretability. The paper discusses critical methodological steps based on the authors' experience of developing ML‐models for structural concrete design against punching shear failure using 544 full‐scale tests.

Studying X-ray spectra from large-scale jets of FR II radio galaxies: application of shear particle acceleration

ABSTRACT Shear particle acceleration is a promising candidate for the origin of extended high-energy emission in extra-galactic jets. In this paper, we explore the applicability of a shear model to 24 X-ray knots in the large-scale jets of FR II radio galaxies and study the jet properties by modelling the multiwavelength spectral energy distributions (SEDs) in a leptonic framework including synchrotron and inverse Compton–CMB processes. In order to improve spectral modelling, we analyse Fermi-LAT data for five sources and reanalyse archival data of Chandra on 15 knots, exploring the radio to X-ray connection. We show that the X-ray SEDs of these knots can be satisfactorily modelled by synchrotron radiation from a second, shear-accelerated electron population reaching multi-TeV energies. The inferred flow speeds are compatible with large-scale jets being mildly relativistic. We explore two different shear flow profiles (i.e. linearly decreasing and power law) and find that the required spine speeds differ only slightly, supporting the notion that for higher flow speeds the variations in particle spectral indices are less dependent on the presumed velocity profile. The derived magnetic field strengths are in the range of a few to 10 µG and the required power in non-thermal particles is typically well below the Eddington constraint. Finally, the inferred parameters are used to constrain the potential of FR II jets as possible ultra-high-energy cosmic-ray accelerators.

Porosities-dependent wave propagation in bi-directional functionally graded cantilever beam with higher-order shear model

The contribution provided in this paper is to investigate the dynamic response of bidirectional graded material beams with porosities. Higher order shear deformation beam theory for wave propagation in porous functionally graded cantilevered beam are developed, taking into account the bidirectional distribution, which is mainly represented in the density and the Young’s modulus. The material properties of the porous FG beam are graded through the thickness and width using a power law distribution. The governing equations of the wave propagation in the porous FG beam are derived by employing the Hamilton’s principle. The analytic dispersion relation of the bidirectional porous FG beam is obtained by solving an eigenvalue problem. Two porosities models approximating the even and uneven distributions of porosity are considered. The results obtained for bidirectional FG beam were compared with those reported in the literature, and the results were very agreement. The effects of the volume fraction distributions, the number of wave propagation, various parameters and the porosity type on dynamic of functionally graded beam are discussed in details. The numerical results show that the power law index, number of wave, wave velocity, and porosity distribution model affect the dynamic behavior of the beam significantly. The results show that the uneven porosity predicts higher natural frequencies than the even porosity.

The contact mechanics of a UK railway ballast

A newly developed apparatus was used to investigate the contact mechanics between particles of a common UK railway ballast. The data were then compared with the models currently and commonly used in geotechnical discrete-element method (DEM) analyses, but the discrepancy between the predictions and measurements is large even at small loads. The first contact behaviour was much softer than the Hertz–Mindlin model for smooth spheres, both in normal and shear. Even if the normal loading could be fitted better with a model that accounted for roughness, the elastic nature of these models could not capture the plasticity that is evident on unloading. Large displacement shear cycles caused not only an increase of inter-particle friction, as discussed previously, but also a significant degree of particle interlock arising from the wear of the contacts. While there were no rate effects for sliding shearing, contact ageing displacements could be observed at pre-failure loads, although these stabilised after a few days. Pre-failure cyclic loading resulted in stiffnesses that increased in lateral loading but decreased in normal loading; in both cases, however, this stabilised after a few tens of cycles, while the stiffnesses at the reversals of the large displacement cycles did not evolve with continued cycling. The presence of water did not affect the lateral stiffness and the influence of the normal load was consistent with Hertz–Mindlin, even if the absolute values were much softer. It can be concluded that the current commonly used models for DEM analyses are not applicable for ballast/crushed rock and alternative models should also focus on plasticity at the asperity scale.

Pure shear model for crack width analysis of reinforced concrete members

Reinforcement corrosion in concrete structures with excessive crack width poses a high risk of reducing the structure's service life. The crack width behavior is one of the most complex aspects of the mechanics of reinforced concrete (RC). With most of the models used in practice being semi–empirical or empirical, very few analytical approaches have been proposed. However, the analytical models lack either accuracy or simplicity, or both. This paper presents a new analytical model, termed the Pure Shear Model, that predicts mean crack width by a simple formula. It is based on the partial interaction tension stiffening model considering a short RC tie subjected to short–term loading. The model assumes elastic material properties and neglects shrinkage, internal cracking, and slip at the interface. It presumes that the only deformations that occur in concrete are the shear strains due to shear lag that are taken constant across the cover thickness. Deplanation of concrete section due to shear lag results in crack width linearly increasing from zero at the bar to its maximum value on the surface of the RC member. Despite the simplicity of the proposed model, its accuracy in predicting mean crack width was shown to be comparable to that of the design code methods.

Design and performance evaluation of a multi-disc magnetorheological fluid brake for A00-class minicars

This paper presents the design and performance evaluation of a multi-disc magnetorheological fluid (MRF)-based brake (MRB) for A00-class minicars. The braking performance of the MRB is studied by means of theoretical analysis and experimental verification. Firstly, the MRB is designed according to the shear model of the MRF, and the structure optimization is carried subsequently. Secondly, multi-physical simulations of the MRB are conducted to investigate the transient temperature field, thermal stress and thermal strain distribution of the MRB under different braking models; Finally, a performance evaluating testbed is built to experimentally assess the braking performance of the MRB. The results indicate that the theoretical braking torque of the MRB fulfills the target value. The thermal strain-induced deformation of the disc is minimal and has a negligible effect on the torque output. In addition, the MRB is experimentally validated to exhibit excellent braking performance in terms of sufficient torque output capacity, rapid response, low temperature rise characteristic, as well as favorable velocity following property.