bluuebunny/crossref_metadata_2025_split huggingface dataset:
Numerical Analysis on Buckling of Ultrahigh Strength Steel Wheel
Authors: Luo Jintao , Li Zhengwen , Shan Yingchun , Liu Xiandong , Wang Yizhuo , Jiang Er 
Published: February 2024

Abstract
With superior mechanical properties than normal strength steels, ultrahigh strength steels (UHSS) have been increasingly used in the lightweight design of vehicle wheels. The lightweight wheels made by UHSS have superior strength and crashworthiness capabilities, but are also prone to buckling instability for the thinning cross section. Therefore, it is necessary to develop effective simulation methods for predicting the critical buckling load of wheels. In this paper, a novel method is proposed for the wheel buckling analysis by introducing a finite element tire model, which provides a more accurate description of the nonlinear tire-rim interface load. Compared to the simplified method of modeling interface load with a simple function form, the proposed method shows higher accuracy in predicting the wheel buckling load, with an error of less 2% than the experimental result. In addition, the effects of material mechanical properties, and initial imperfection by manufacturing factors on the wheel stiffness are investigated. The results show that wheel buckling load can be increased by decreasing the yield strength of the wheel material. A low imperfection factor achieved by controlling the wheel processing precision also helps to improve the wheel stiffness. The research provides reliable guidance for the stiffness improvement of UHSS wheels.
Dynamic Analysis of Parametrically Excited Stable Rotors With Unbalance
Authors: De Felice Alessandro , Sorrentino Silvio 
Published: February 2024

Abstract
The dynamic analysis of parametrically excited rotors is a research field of great interest and practical importance, since instability and resonant behavior can cause issues ranging from anomalous noise and wear to catastrophic failures. This study is focused on the effects of unbalance on a parametrically excited rotor operating in the asymptotically stable domain, a research topic which in the scientific literature has not been investigated. Rotor unbalance causes an additional harmonic load acting on flexural deflection, influencing the frequency response together with the parametric excitation, yielding additional combination external resonances. As a first insight into this problem, to study the effects of angular speed independently of variations of the natural frequencies, and to facilitate decoupling of the equations of motion, a simplified model of a distributed-parameter slender rotor is considered, consisting of a homogeneous Euler-Bernoulli beam with circular section, rotating at constant angular speed about its longitudinal axis on isotropic supports. It is affected by unbalance and loaded by an axial end thrust, assumed to have a harmonic time-dependent component. The steady-state response is studied after decoupling the equations of motion, reducing the problem to the analysis of a non-homogeneous single-degree-of-freedom damped Mathieu equation.
Modeling of Rate Effects in Detachment of Mushroom-Shaped Adhesive Structures
Authors: Li Ruozhang , Li Dongwu , Zhang Wenming 
Published: February 2024

Abstract
Gecko-inspired fibrillar adhesives have attracted much attention and have good application prospects in many fields. Rate-dependent adhesion of the fibrillar adhesives is a commonly observed but less discussed issue, particularly for mushroom-shaped structures. Mushroom-shaped structures have become a popular design in recent ten years due to the optimal interfacial stress and thus better adhesion performance than the traditional flat-ended structure. However, the rate-dependent adhesion in mushroom-shaped structures is far less known. In this study, we do a preliminary study with a focus on the influence of retraction velocity on the pull-off force of the mushroom-shaped adhesive structure. Two mechanical models corresponding to two typical crack propagation modes (center crack and edge crack), respectively, are established to describe the pull-off dynamics. It is found that the pull-off force-velocity relation shows a power law at large velocities for both two crack propagation modes. The power exponent is about 0.2, almost the same for both modes, when the power exponent in the Gent-Schultz law is equal to 0.5. This power exponent value is found to be consistent with experiments. This study would provide theoretical insight into the rate-dependent adhesion of mushroom-shaped adhesive structures and promote optimal designs in related applications.
Mechatronic System Design of a Ball Launcher Machine for Speed and Anticipation Training in Combat Sports
Authors: Roa Prada Sebastián , Barreto Sosa Duvan Smith 
Published: February 2024

Abstract
This research work presents the design and development of a ball throwing machine using the V-methodology. The machine aims to automate one of the most common exercises in martial arts for the development of anticipation speed. Samples were taken from different athletes performing the exercise to determine the response requirements of the machine. The design was then conceptualised based on the required movements and the different ways of solving them. The idea of a thrower with horizontal and vertical movement and ball speed was proposed. The dimensions were estimated based on trends in human proportions and commercial elements such as the ball, wheels, motors, gears, etc. Once the sketch was clear, the system was modelled using CAD software.
The next step was to calculate the actuator requirements to meet the needs identified in the first stage. Based on these requirements, commercially available actuators were selected along with their respective operating modules. The construction material was selected and the appropriate assembly was carried out, giving the physical properties to the CAD model. The physical dimensions of the parts were calculated and a structural analysis of the parts was carried out, making the necessary adjustments so that the parts could withstand the static and dynamic loads of the system.
The various subsystems were built and tested. Once the mechanical subsystems had been validated, general assembly was carried out and the tracking system was mounted. Calibration was performed on the mechanical system and the tracking system was tested with a laser, allowing real-time tracking to be compared with the generated model and the actual position of the body part being tracked.
A user interface was implemented where the randomness of speed and launch times could be selected, and launches could be tracked to verify that they were as requested. This completed the full validation of the system. The functional model was used to observe possible improvements and factors affecting the performance of the machine. The proposed ball launch machine allows for variation in the trajectory, speed, frequency and randomness of ball launches, thus personalising the triggering action in the athlete’s training. In addition, the machine provides a training optimisation solution by automating an exercise that under normal conditions can be monotonous and ineffective depending on the expertise of the available training partner or lack thereof. The machine also allows for personalised training schedules and times, as the athlete can train alone.
Deep Neural Network Based Saturated Adaptive Control of Muscles in a Lower-Limb Hybrid Exoskeleton
Authors: Ting Jonathan A. , Basyal Sujata , Allen Brendon C. 
Published: February 2024

Abstract
Hybrid exoskeletons are used to blend the rehabilitative efficacy and mitigate the shortcomings of functional electrical stimulation (FES) and exoskeleton-based rehabilitative solutions. This paper introduces a novel nonlinear controller that may potentially improve the rehabilitative efficiency of a lower limb hybrid exoskeleton by implementing four key features into the FES and exoskeleton controllers. First, the FES input to the user’s muscles is saturated based on user preference to ensure user comfort. Second, rather than discarding the excess control effort from the saturated FES input, it is redirected into the exoskeleton’s motor controller. Third, a safe deep neural network (DNN) is designed to estimate the unknown dynamics of the hybrid exoskeleton and the DNN is implemented in the FES controller to improve the control efficiency and tracking performance. Fourth, an adaptive update law is designed to estimate the unknown muscle control effectiveness to facilitate the implementation of the DNN. Lyapunov stability-based methods are used to generate real-time adaptive update laws that will train the adaptive estimate of the muscle effectiveness and the output layer weights of the DNN in real-time, ensure the effectiveness and safety of the controllers, and prove global asymptotic tracking of the desired trajectory.
It’s Curling Night in New Orleans!
Authors: Stach Eric , Lipp Genevieve , McGuire Patrick , Santillan Sophia 
Published: February 2024

Abstract
In a sophomore level dynamics class in Duke University’s Mechanical Engineering and Materials Science department, a tabletop sized ice rink was built to demonstrate collision mechanics of Curling stones. Cameras and image processing techniques were used to collect object position versus time data for single impact scenarios. The data was then analyzed by students to calculate the coefficient of restitution and velocities of each object after collision. Through this interactive, hands-on laboratory experiment, students were able to learn this foundational engineering concept.
A Performance-Based Reliability Approach
Authors: Mandelli Diego , Wang Congjian 
Published: February 2024

Abstract
Over the past decade, nuclear power plants have been transitioning from periodic to predictive maintenance strategies in order to reduce operational costs. This type of transition requires that new data be retrieved and different decision processes employed. Advanced monitoring and data analysis technologies are essential for supporting predictive strategies, as they can provide precise information on the health of a given component, track its degradation trends, and estimate its expected failure time. With such information, maintenance operations can be performed on a component shortly before its expected failure time. Classical reliability modeling is not suited for this dynamic context of maintenance operations, thus a new reliability mindset is required — one in which component health information (and not failure rates/probabilities) is propagated from the component to the system level in order to inform and optimize plant operations. The present paper addresses this situation by providing an alternative reliability modeling approach based on component margins rather than failure rates/probabilities. In this approach, component condition data and diagnostic/prognostic information can be directly employed to quantify component health in terms of margin. Lastly, we show how margin values can be propagated from the component to the system level in order to assess system health and identify those components most critical to system operation.
Optimization of Vane-Style Variable Area Flowmeter Calibration Through CFD Analysis
Authors: Imran Syed , Ma Shilei , Silaen Armin , Hackett Peter E. , Walla Nicholas , Guo Xipeng , Moss Robert , Zhou Chenn 
Published: February 2024

Abstract
Precise measurement of the flowrate is crucial for both process control and energy consumption evaluation. The main aim of this work is to develop a methodology to calibratea vane-style variable area flowmeter, designed to measure high viscosity fluids, in water. In order to accomplish this, a series of computational fluid dynamics (CFD) analysis are carried out to determine how the vane’s angle of rotation varies with different flow rates of water and high viscosity fluids. This data is recorded and analyzed to develop calibration curves that relate the vane’s angle of rotation to the flow rates. From the calibration curves, it can be determined the required water flow rate to achieve the equivalent vane’s angle of rotation in a specified viscosity. This methode provides an efficient and cost-effective calibration process because it eliminates the need for calibrating using heated engine oil to achieve the fluid viscosity of the flow meter is designed. Flowmeter sensitivity analysis was also permored and it was observed that the angle of pointer curves converges as the size of the flowmeter increases suggesting that the effect of viscosity on flowmeter sensitivity decreases as the size of the flowmeter is increased, likely due to reduced resistance to flow and smaller pressure drops.
Evaluation of Power-Assisted Wheelchair to Reduce Burden on Elderly Caregivers
Authors: Asano Katsuhiro , Ota Shinichiro , Takato Jinro 
Published: February 2024

Abstract
The purpose of this study is to verify the effectiveness of a mechanical power-assisted wheelchair that does not require electrical charging for its operation. In this study, we investigated the burden experiences by a caregiver when pushing the wheelchair along with the assistive force with and without the power assistance.
First, the wheelchair was tested on a slope where the caregiver would feel strain while pushing the wheelchair, and the wheelchair pushing force and sensory evaluation were measured. The results showed that the caregiver’s pushing force was independent of the implementation of power assist in the wheelchair, and the sensory evaluation indicated that the power assist wheelchair was effective.
Furthermore, to investigate the inherent assist force of the power-assisted wheelchair, we conducted a static experiment without the caregiver and compared the results with theoretical values of the assist force. The static experiment showed that the power-assisted device exerted an assist force in the direction of the wheelchair motion.
The static experiment showed that the power-assisted wheelchair was not effective in the dynamic experiment with the caregiving participants but was effective in the static experiment without the caregivers. In addition, the reasons for the differences in assist force between the static and dynamic experiments were discussed.
Fabrication of NiTi Samples Using Pressureless Sintering of Uncompacted Metal Powder
Authors: Alawwa Fares , Abu Al-Rub Rashid K. , El-Khasawneh Bashar , Zaki Wael 
Published: February 2024

Abstract
Among the several metal systems capable of shape memory behavior, nickel-titanium (NiTi or nitinol) remains the most utilized. One way to fabricate nitinol components is by way of sintering of compressed elemental or pre-alloyed metal powder; a process that involves the design and use of an appropriate mold. This study investigates pressureless sintering of pre-alloyed NiTi powder, which eliminates the need for compaction to form a green part. The method involves preheating and sintering at an appropriate rate and time in a vacuum to achieve sintering of nitinol. After heat treatment, differential scanning calorimetry (DSC) thermograms reveal that the material exhibits shape memory performance through phase transformation peaks. Moreover, energy dispersive spectroscopy (EDS) is performed using scanning electron microscopy (SEM) to reveal a homogenous mixture of Ni and Ti. Brinell hardness test is used to demonstrate the qualitative performance of shape memory. Vickers hardness test revealed that the sample demonstrates a hardness value comparable to those reported in literature. Finally, micro-CT results demonstrating minimal porosity in the sample are presented. Overall, the results of this work show that pressureless sintering of pre-alloyed NiTi shape memory alloy (SMA) powder can be an effective and efficient method for the fabrication of functional nitinol. The elimination of the need for a mold to compress nitinol powder into a green part simplifies the fabrication process and reduces production cost. The structural homogeneity of the obtained samples and absence of easily distinguishable porosities further suggests that this method can result in high-quality NiTi samples.
Stimulating Critical Thinking Through Report Peer-Review in a Project-Based Learning by Engineering Freshman Students
Authors: Alves Anabela C. , Leão Celina P. , Abreu M. Florentina , Pimentel Carina , Malheiro M. T. , Oliveira Sérgio , Ramos M. Piedade , Oliveira Jorge Miguel 
Published: February 2024

Abstract
Project-based learning (PBL) is an active learning methodology proposed in the early 20th century. Nevertheless, it continues to be a very suitable methodology for the current generation of students. Probably, it is more relevant now than before, since recent generations are more motivated by these learning methodologies. This is due to the fact that today’s students are totally absorbed by technologies that, in spite of being useful, are a cause of distraction, in particular in what concerns the most important objective: learning. With PBL, many learning aspects could be explored, from the integration of course content to provide the technical to the transversal competencies such as: critical thinking, teamwork, personal relationship, project management and emotional intelligence development. PBL is used in the Integrated Project of Industrial Engineering and Management 1 (IPIEM1) course. IPIEM1 is an interdisciplinary project developed during a semester by teams of freshman students. These teams should apply the contents and knowledge learned in the five project support courses to develop the IPIEM1. Eight teams were formed with seven to nine members. The project theme involves sustainability and in the year of 2022/23 was to design a production system to value end-of-life clothes. Among other deliverables, student teams must review a report from a different team. This paper discusses the critical thinking developed by the student who undertake this report peer-review by analyzing the feedback given, questionnaire and technical aspects checklist and reports content results.
Bi-Level 3D Reconstruction of Malignant Pleural Mesothelioma Volume From CT Images
Authors: Ghidotti Anna , Regazzoni Daniele , Weiss Cohen Miri 
Published: February 2024

Abstract
This paper introduces an assistive system for diagnosing malignant pleural mesothelioma (MPM), a highly aggressive cancer caused by asbestos exposure. The system assists healthcare providers in accurately determining the tumor’s volume and the appropriate dose of chemotherapy to administer. It employs a bi-level process that uses machine learning and deep learning techniques to classify CT images of lungs and then calculate the tumor’s volume. The study addresses the challenges associated with deep nets, such as the need for large and diverse datasets, hyperparameter optimization, and potential data bias. Two CNN architectures, Inception-v3 and ResNet-50, were compared in terms of their features and performance, and three hyperparameters were optimized for each model to generate a broad range of training scenarios. To estimate the amount of cancer cells to target, CT images were used to calculate the tumor’s volume. This process involved image pre-processing, cropping volume, registering and filtering images, filling holes, segmentation, and 3D reconstruction. The results demonstrate that the developed system utilizing CNN optimizations and reconstruction of 3D images from CT images can benefit the treatment of MPM patients. The system has the potential to improve the accuracy of MPM diagnosis and the effectiveness of chemotherapy, ultimately improving patient outcomes.
Development of Modified Perturbation Solutions to the One-Phase Stefan Problems With a Convective Boundary
Authors: Xu Minghan , Mohit Mohammaderfan , Akhtar Saad , Sasmito Agus P. 
Published: February 2024

Abstract
The classical Stefan problem is used to track the moving solid-liquid interface during the freezing process. Perturbation theory has often been applied to find an approximate analytical solution due to the nonlinearity of the moving interface. However, the Stefan number (i.e., the sensible over latent heat) must be small and usually less than 0.01 to assume the perturbation expansion, which in turn limits the thermal engineering applications. In this study, a modified perturbation solution is developed by adding a correction term after the leading-order solution to be valid for a much wider range of Stefan numbers (i.e., 0.01 ≤ Ste ≤ 1). Specifically, a one-phase Stefan problem is first formulated subjected to a convective boundary in the Cartesian, cylindrical, and spherical coordinate systems for inward solidification. The leading-order solution is calculated based on the regular perturbation theory, while the correction term is obtained using the Monte-Carlo method and a multi-variant regression. Results show that the correction term has a linear relationship with the Stefan number and is not significantly influenced by the Biot number. The proposed modified perturbation solution can accurately and rapidly predict the nonlinear moving interface motion for the freezing process.
Flood Assessment & Modeling
Authors: Thibodeaux Austin , Monev Zhulien , Tyler Tabitha , DeCoursey Abbie , Zhang Ning 
Published: February 2024

Abstract
The purpose of our project aims to visualize, simulate, and analyze flood patterns on certain locations which have been impacted by flooding in the past. Blender is used to model the area and the FLIP Fluids Addon is then used to simulate the fluid causing the flood. The FLIP Fluids addon utilizes a cloud of particles which are based upon the Navier-Stokes equation which is the expression that describes the motion of any viscous incompressible fluid. This powerful addon can simulate the accurate flood patterns of fluid flowing with a designated velocity in any chosen direction. The velocity can be manipulated, as well as the viscosity of the fluid, gravity of the simulation world, and even the visual representation of the fluid type. FLIP Fluids words by assigning a domain, inflow, and any obstacles the fluid will interact with to the created model in Blender. Creating the model in Blender using topography data and building blueprints so that our model is as accurate as possible. One application of this is that of a building located on the southern side of McNeese State University named Collette Hall. Collette Hall is a co-ed dormitory that has a history of flooding from not only heavy rains but rising water levels in a canal just north of the building (Contraband Bayou). In our simulation, we not only worked to produce the direct behavior of flood waters entering the building, but also to demonstrate the rising water levels of Contraband Bayou using various velocity profiles of the flowing water. FLIP Fluids allows for a whitewater adaptation of the canal’s water level and gives an opportunity to manipulate and record velocity values so that the user can study the possible flooding effects. This can help administration predict the behavior of flood patterns in the Bayou, as well as giving students a visual representation of how the surrounding areas will be affected in the case of rising water levels. Our project drives home the importance of understanding flood patterns in the case of an emergency, while offering a scientific simulation for administration and students to analyze at their disposal.