bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of Acid Etching on the Microstructure and Stiffness of Human Teeth
Authors: Zhai Yingnan , Shi Zhenshan , Premaraj Thyagaseely , Premaraj Sundaralingam , Karpova Tatiana , Dong Pengfei , Gu Linxia 
Published: September 2024

Abstract
The mechanical properties of acid-etched enamel and dentin are important for understanding tooth erosion and developing innovative dental restorative materials. In this study, the microstructure and mechanical properties of both enamel and dentin were characterized using scanning electron microscopy (SEM) and atomic force microscopy (AFM) to quantify the impact of acid etching. SEM images demonstrated that enamel rods have a diameter of approximately 5 μm, while dentinal tubules have a diameter of around 2 μm. After acid etching, the intertubular and peritubular regions were exposed, with the peritubular regions showing a thickness of approximately 1 μm. AFM measurements showed that the stiffness of enamel at the bottom, middle, and top layers is 26.28±4.24 GPa, 32.03±8.68 GPa, and 23.94±3.53 GPa, respectively. For dentin, the stiffness is 16.28±2.76 GPa at the bottom layer and 17.59±5.33 GPa at the middle layer. AFM morphology and stiffness maps illustrated the microstructures of enamel rod and sheaths, as well as dentin tubules in both unetched and acid-etched tooth sections. The stiffness of the acid-etched enamel rod and peritubular dentin decreased by 7-fold and 3.6-fold, respectively, compared to the unetched enamel rod and peritubular dentin.
Computational Modeling of Cough Droplet Behavior in the Human Upper Respiratory Airway
Authors: Khan Rafid Jahangir , Ilegbusi Olusegun 
Published: September 2024

Abstract
This study investigated the interaction of cough droplets with airflow in a realistic human airway. The ultimate aim was to understand the behavior of cough droplets inside the airway and to assess the potential of droplets to be retained in the airway or transmitted to the lungs. A computational fluid dynamics (CFD) model, based on the Euler–Lagrangian framework, was employed to predict the two-phase, droplet-laden transient cough flow in a realistic three-dimensional (3D) human airway. The airway geometry was reconstructed from patient computed tomography (CT) scan dataset. The discrete phase model was used to track the motion of the droplets in the air flow. Two distinct cough profiles—a strong cough and a weak cough—acquired experimentally from human subjects, were used as input to simulate normal and disordered cough functions. The effects of cough strength and droplet size on droplet retention and aspiration in the airway were investigated. It was found that droplet retention was significantly higher for a weak cough compared to a strong cough. For a weak cough, the highest droplet retention percentage exceeded 60%, while for a strong cough, it was less than 20%. Larger sized droplets were more likely to be aspirated into the lungs, especially under weak cough conditions. In the case of weak cough, more than 5% of the 200 μm sized droplets were aspirated into the lungs, whereas for strong cough, aspiration was less than 2%.
Active Data-Enabled Robot Learning of Elastic Workpiece Interactions
Authors: McCann Lance , Yan Leon (Liangwu) , Hassan Sarmad , Garbini Joseph , Devasia Santosh 
Published: September 2024

Abstract
During manufacturing processes, such as clamping and drilling of elastic structures, it is essential to maintain tool–workpiece normality to minimize shear forces and torques, thereby preventing damage to the tool or the workpiece. The challenge arises in making precise model-based predictions of the relatively large deformations that occur as the applied normal force (e.g., clamping force) is increased. However, precision deformation predictions are essential for selecting the optimal robot pose that maintains force normality. Therefore, recent works have employed force–displacement measurements at each work location to determine the robot pose for maintaining tool normality. Nevertheless, this approach, which relies on local measurements at each work location and at each gradual increment of the applied normal force, can be slow and consequently time prohibitive. The main contributions of this work are: (i) to use Gaussian process (GP) methods to learn the robot-pose map for force normality at unmeasured workpiece locations; and (ii) to use active learning to optimally select and minimize the number of measurement locations needed for accurate learning of the robot-pose map. Experimental results show that the number of data points needed with active learning is 77.8% less than the case with a benchmark linear positioning learning for the same level of model precision. Additionally, the learned robot-pose map enables a rapid increase of the normal force at unmeasured locations on the workpiece, reaching force-increment rates up to eight times faster than the original force-increment rate when the robot is learning the correct pose.
A Distributed Layered Planning and Control Algorithm for Teams of Quadrupedal Robots: An Obstacle-Aware Nonlinear Model Predictive Control Approach
Authors: Imran Basit Muhammad , Fawcett Randall T. , Kim Jeeseop , Leonessa Alexander , Hamed Kaveh Akbari 
Published: September 2024

Abstract
This paper aims to develop a distributed layered control framework for the navigation, planning, and control of multi-agent quadrupedal robots subject to environments with uncertain obstacles and various disturbances. At the highest layer of the proposed layered control, a reference path for all agents is calculated, considering artificial potential fields (APF) under a priori known obstacles. Second, in the middle layer, we employ a distributed nonlinear model predictive control (NMPC) scheme with a one-step delay communication protocol (OSDCP) subject to reduced-order and linear inverted pendulum (LIP) models of agents to ensure the feasibility of the gaits and collision avoidance, addressing the degree of uncertainty in real-time. Finally, low-level nonlinear whole-body controllers (WBCs) impose the full-order locomotion models of agents to track the optimal and reduced-order trajectories. The proposed controller is validated for effectiveness and robustness on up to four A1 quadrupedal robots in simulations and two robots in the experiments.1 Simulations and experimental validations demonstrate that the proposed approach can effectively address the real-time planning and control problem. In particular, multiple A1 robots are shown to navigate various environments, maintaining collision-free distances while being subject to unknown external disturbances such as pushes and rough terrain.
Stall Inception Analysis on Axial Compressors With Different Rotor Loading Distributions Under Radial Inlet Distortions
Authors: Sun Dakun , Zhu Hengyi , Xu Dengke , Hu Jiahao , Sun Xiaofeng 
Published: September 2024

Abstract
Stability studies were conducted on a single-stage, low-speed compressor with different rotor loading-distribution designs under a uniform inlet, 10% intensity, and 20% intensity total tip pressure distortion inlet conditions via numerical calculations, theoretical model predictions, and experimental methods. The steady numerical performance was in basic agreement with experimentally measured performance. The theoretical prediction model showed an error within 1.5%, which is less than that of the steady numerical calculation. The total tip pressure distortion reduced flow stability. Conversely, the design of moving the rotor loading axially rearward significantly improved the flow stability. The blade loading analysis showed that the radial distortion caused a radial redistribution of rotor loading. The increase in the rotor-tip loading due to tip distortion was the main reason for the reduced flow stability. In contrast, the design of moving the rotor loading axially rearward reduced the rotor-tip leading-edge loading, enhancing the flow stability. Moreover, an analysis of the unsteady flow validated the findings of the blade loading analyses. It was found that the periodic evolution of the tip leakage vortex (TLV) had an adverse effect on flow stability. In addition, the modified rotors could prevent the tip leakage flow (TLF) from spilling from the leading edge and prevent the interaction of different diffusing regions, decreasing the probability of flow separation.
Computational Analysis of Flow Around Two Wall-Mounted Trapezoidal Bluff Bodies Arranged in Tandem Position
Authors: Sarkar Sourav , Gupta Nishant , Debnath Koustuv , Lawrence Raj Prince Raj 
Published: September 2024

Abstract
Flow around two identical wall-mounted trapezoidal bluff bodies, arranged in tandem, is numerically investigated at a Reynolds number of 750,000. The investigation employs Reynolds-averaged Navier–Stokes (RANS) equations and the k–ω SST turbulence model. The effect due to the change of the angular orientation of the inclined faces (α) of this bluff body and the pitch distance (L/D) on hydrodynamic quantities and turbulence quantities is investigated. Furthermore, the drag coefficient and Strouhal number have also been evaluated to understand the vortex shedding and flow pattern-related phenomena. For d and intermediate types of bluff bodies, the streamwise mean velocity, cross-stream mean velocity, turbulence kinetic energy, and recirculation length decrease with the increase of α or L/D. Significant changes are also observed in the case of Strouhal number. Reduction in drag coefficient and recirculation length is observed with increased L/D at a constant α for d-type bluff bodies. The change of α and L/D also creates the formation of a periodic von Kármán vortex street at downstream of the second bluff body in the case of L/D = 7, making the flows more complex and unstable. The maximum size of the recirculation bubble occurs in the case of L/D = 10 at α = 30 deg. The investigation provides valuable insight into the complex dynamics of tandem configurations of wall-mounted bluff bodies.
Data-Guided Low-Reynolds-Number Corrections for Two-Equation Models
Authors: Hu Xiaohan , Huang George , Kunz Robert , Yang Xiang 
Published: September 2024

Abstract
The baseline Launder–Spalding k−ε model cannot be integrated to the wall. This paper seeks to incorporate the entire law of the wall into the model while preserving the original k−ε framework structure. Our approach involves modifying the unclosed dissipation terms in the k and ε equations specifically within the wall layer according to direct numerical simulation (DNS) data. The resulting model effectively captures the mean flow characteristics in both the buffer layer and the logarithmic layer, resulting in robust predictions of skin friction for zero-pressure-gradient (ZPG) flat-plate boundary layers and plane channels. To further validate our formulation, we apply our model to boundary layers under varying pressure gradients, channels experiencing sudden deceleration, and flow over periodic hills, with highly favorable results. Although not the focus of this study, the methodology here applies equally to the k–ω formulation and yields improved predictions of the mean flow in the viscous sublayer and buffer layer.
Improved Numerical Model to Investigate Self-Aeration Along Stepped Spillway
Authors: Masouminia Mohammadhosein , Türker Umut 
Published: September 2024

Abstract
The concept of understanding and predicting the behavior of flow characteristics such as velocity, pressure, and energy in the presence of bubbles and droplets of various morphologies has always fascinated researchers. Flow aeration has been a challenging topic contributing to drag force, flow morphology, and cavitation, which was successfully investigated through numerical studies. Subsequently, it has resulted in the development of numerical models that can predict and simulate the self-aerated flow more accurately with less cost and in a shorter time frame. This study presents a numerical model that utilizes drag coefficient, disperse phase diameter, and interfacial area concentration to provide a novel idea of drag force in the presence of bubbles and droplets in flow. As part of enhancing the numerical model's precision, a dynamic calibration parameter for drag coefficient is incorporated which captures the macro-and microflow characteristics as over- and subgrid effects. Additionally, bubbles and/or droplets lead to a variable eddy viscosity that implemented in the numerical model as modified mixture viscosity. Furthermore, this numerical model is implemented on a stepped spillway, a well-known structure that causes aeration, to validate its accuracy and present a better understanding of the flow velocity changes, pressure differences, aeration, and energy. Finally, this numerical model predicts the self-aeration with consistent precision to experimental data that can be used alternatively to create, investigate, and optimize the design of complex geometries like stepped spillways.
A Comparative Study on the Prediction of Hydrogen, Nitrogen, and Water Vapor of Regenerative Hydrogen Pump With Different Turbulence Models
Authors: Yang Tao , Wang Shengke , Sun Jinju 
Published: September 2024

Abstract
The flow in a regenerative hydrogen pump used in a proton exchange membrane (PEM) fuel cell system is complex, including velocity mixing, streamline distortion, swirling flow, corner flow, and possible boundary separation. Experimental measurement and computational fluid dynamics (CFD) prediction are the main methods used to evaluate such performance. In this work, regenerative hydrogen designed for fuel cell electric vehicles with an impeller diameter of 91 mm and a shaft speed of 22,000 rpm is tested with a mixture of nitrogen, hydrogen, and water vapor. During the test, the flowrate and shaft speed ranges are 151–881 L/min and 8000–22,000 rpm, respectively. The inlet pressure and temperature are 171 kPa and 66 °C, respectively. Then, the flow is predicted by the k − ε model, the renormalization group (RNG) k − ε model, the explicit algebraic Reynolds stress models (EARSM) and the shear-stress transport (SST) detached eddy simulation (DES) model. The differences between the tested and predicted performances are compared. With these results, the velocity distribution in the side channel, the radial force of the impeller and casting, and the changes in the downstream pressure and velocity are analyzed in consideration of the ability of the turbulence models to simulate each characteristic flow. On this basis, the differences and abilities of the turbulence models for predicting the flow in regenerative hydrogen pumps are summarized.
Walking Slope and Heavy Backpacks Affect Peak and Impulsive Lumbar Joint Contact Forces
Authors: Sturdy Jordan T. , Sessoms Pinata H. , Rizeq Hedaya N. , Silder Amy , Whittier Tyler T. , Silverman Anne K. 
Published: September 2024

Abstract
Heavy load carriage is associated with musculoskeletal overuse injury, particularly in the lumbar spine. In addition, steep walking slopes and heavy backpacks separately require adaptation of torso kinematics, but the combined effect of sloped walking and heavy backpack loads on lumbar joint contact forces is unclear. Backpacks with hip belt attachments can reduce pressure under the shoulder straps; however, it is unknown if wearing a hip belt reduces lumbar spine forces. We used a musculoskeletal modeling and simulation approach to quantify peak and impulsive L1L2 and L4L5 lumbar joint contact forces in the anterior/posterior shear and compressive directions during walking on 0 deg and ±10 deg slopes, with no backpack and with 40% body weight backpack load using two different backpack configurations (hip belt assisted and shoulder-borne). Both walking slope and backpack load significantly affected shear and compressive peak and impulsive forces. The largest peak shear and compressive forces of 1.57 and 5.23 body weights, respectively, exceed recommended limits and were observed during uphill walking with shoulder-borne loads. However, only impulsive force results revealed differences due to the backpack configuration, and this effect depended on walking slope. During downhill walking only, the hip belt-assisted configuration resulted compressive impulses lower than during shoulder borne by 0.25 body weight seconds for both L1L2 and L4L5. These results indicate that walking uphill with heavy loads causes high shear and compressive lumbar forces that may increase overuse injury risk. In addition, our results suggest it is especially important to wear a hip belt when walking downhill.
Theoretical Model and Experimental Application for Solute Diffusion in Leaching Test With Time-Dependent Boundary Conditions
Authors: Tong Shan , Sample-Lord Kristin M. , Li Yu-Chao , Lang Ji 
Published: September 2024

Abstract
Measuring the diffusion coefficient of clay-based liner materials is important in estimating and predicting long-term barrier performance in waste containment facilities. Various theoretical models, including the finite cylindrical model, have been commonly used to determine the diffusion properties of clay-based liner materials in leaching tests. However, the assumption of zero-concentration boundary conditions of the traditional finite cylindrical model contradicts the measured variation of concentration in real leaching tests, likely resulting in (1) underestimated and unconservative diffusion coefficient, or (2) requirement of a relatively large liquid-to-soil ratio and frequent leachate replacement in the experiment to maintain the zero-concentration boundary condition. In this study, a theoretical model was developed to evaluate the solute diffusion process within a soil specimen under arbitrary, time-dependent concentration boundary conditions. The proposed model, incorporating the time-dependent boundary conditions, provides efficient calculations of the concentration distribution and the cumulative fraction leached of solute across the soil specimen. The example application of the proposed model to experimental data demonstrates the capability of the proposed model to determine apparent diffusion coefficients of clay-based liner materials without introducing errors associated with the assumption of a zero concentration boundary condition. The proposed model provides a comprehensive method to investigate the dynamic transport behaviors of solutes through clay-based liner materials in future studies.
Thermal Performance Investigation of Vapor Chamber Under Partial Heating and Different Heat Flux Conditions: Effects of Inclination Angle
Authors: Varol Yasin , Oztop Hakan F. , Tamdoğan Enes , Parlak Murat , Şenocak Şafak Melih , Coşanay Hakan 
Published: September 2024

Abstract
The need for cooling technologies increases tremendously with raising demand on the powerful and compact electronics. There, it pushes the research and technology to the new investigations on varying heat transfer mechanisms and devices. While one of these devices is vapor chamber (VC), an experimental study has been carried out to investigate the heat transfer performance of a VC under partial heating, varying heat fluxes, and different inclination angles for different temperatures, in the current study. For this purpose, a VC with a dimension of 90 mm × 90 mm × 3 mm is evaluated via its resulting thermal resistance, performance, and the temperature distribution over the VC surface. There, the limited effect of inclination angle is observed on the performance, while the highest change is obtained with decreasing local heating surface area, thus increasing heat fluxes. Moreover, this trend is seen almost similar with a reasonable shift up or down according to the different temperature differences.
Measurement of Steam-Generator-Tube Vibration Damping Caused by Anti-Vibration-Bar Supports
Authors: Smith Bruce A. W. , Feenstra Paul , Liu Michael 
Published: September 2024

Abstract
In 2013, Atomic Energy of Canada Limited (now Canadian Nuclear Laboratories) experimentally measured the damping of a straight tube with a variety of tube supports to examine low-frequency damping. These tests were motivated by the discovery of severe tube damage caused by in-plane fluidelastic instability (FEI) in the U-bend regions of new replacement recirculating steam generators (SG). The measurements were intended to assess the applicability of existing design guidelines for estimating the support-related damping of a tube. In the tests, the damping ratios of a single steam generator tube were measured using both log-decrement and power-based methods. Noncontacting excitation and position-sensing techniques were employed to improve accuracy. Initial baseline tests explored configurations with no support and drilled-hole supports of different hole sizes, and these results were compared with previously published work. Subsequent tests were performed to measure damping of tube vibration parallel to flat-bar supports. Most of the tests were performed with the tube fully submerged in still water. The tests examined the effects of fluid (water or air), natural frequency, gap width, preload, and vibration normal to the bars. This paper describes the test apparatus, methods, and analysis techniques. A summary of the results is presented. The initial baseline results showed that the damping ratios measured without any supports and with a drilled-hole support were consistent with previously published data. However, the subsequent measurements showed that, contrary to a published design guideline, the anti-vibration bars resulted in no significant additional viscous or squeeze-film damping when the vibration was parallel to the bars. On the other hand, the results did show that anti-vibration bars could introduce significant in-plane Coulomb-type damping if there was sufficient tube-to-support preload or impacting.
Machine Learning Modeling for Predicting Tensile Strain Capacity of Pipelines and Identifying Key Factors
Authors: Park Dong-Yeob 
Published: September 2024

Abstract
Machine learning (ML) techniques have recently gained great attention across a multitude of engineering domains, including pipeline materials. However, their application to tensile strain capacity (TSC) modeling remains unexplored. To bridge this gap, this study developed and evaluated an ML model to predict the tensile strain capacity of girth-welded pipelines. The model was trained on over 20,000 data points derived from a TSC equation available in the literature. The ML model demonstrated robust performance in predicting tensile strain capacities. Evidence of this lies in the near-zero means, minimal standard deviations, and normal distribution of residuals for both the training and test datasets. These collectively suggest that the model provides a good fit for the data. Furthermore, the model's loss behavior indicates successful convergence and generalization, without signs of overfitting or underfitting. An analysis using the random forest method revealed that the geometry of the flaw, specifically the flaw depth, is the most influential variable in predicting the TSC. This could be attributed to its significant impact on the fracture toughness of materials. In contrast, material properties and fracture toughness exert less influence relatively, despite their contributions to the model. This finding underscores the importance of flaw geometry in TSC prediction models. Overall, the development of a data-driven TSC model has shown efficient TSC modeling. This model leverages ML techniques, allowing for continuous updates with new data via deep learning.