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ASME 2024 International mechanical engineering Congress and Exposition, IMECE 2024

作者： Azari, Fatemeh Jazaei, Robabeh Department of Mechanical Engineering and Materials Science College of Engineering University of Pittsburgh PittsburghPA United States Department of Engineering College of Engineering and Science Slippery Rock University Slippery RockPA United States

ISBN: (纸本)9780791888629

In contemporary biomedical innovation, Additive Manufacturing (AM) has been pivotal since the 1980s, crafting complex structures for bioengineering, biomedicine, and pharmacology [1]. Particularly in pharmacology, AM, notably through Stereolithography (SLA), has transformed drug delivery, enhanced dosage precision and advancing personalized therapies [2]. In tissue engineering, AM is crucial for bioprinting scaffolds and tissue constructs using bio-inks to mimic human tissues, facilitating significant advances in medical treatments [3].(i) Key techniques include SLA achieving 30-micrometer resolution [4-6], Fused Deposition Modeling (FDM) is an evolving drug delivery technique [9], and Powder Bed Fusion (PBF) 70% to 90% had minimal impact on osteogenesis when using a 700-μm pore size [41].(ii) Applications span tissue engineering with materials like PLA and PGA [16], achieving 97.2 ± 48.4 implant fit accuracy using MRI and CT scans [40-41]. Drug delivery systems, such as multi-layered tablets, enable sequential release [22]. Personalized medicine benefits from custom-made implants based on patient data [25]. (iii) Challenges include replicating intricate organ structures like the bladder and liver, ensuring vascularization, and integrating immune components [28]. Incorporating vascular endothelial growth factor (VEGF) into bioinks increases angiogenesis [31]. Material limitations and regulatory hurdles persist [34].(iv) Future directions focus on improving vascularization, immune integration, and personalized oncological treatments [37]. Continued research and technological innovations are essential for accurate tissue replication [40].(v) In conclusion, AM techniques like SLA and FDM revolutionize drug delivery and tissue bioprinting, marking a transformative period in biomedicine with significant potential for personalized medicine and regenerative therapies, promising breakthroughs in disease modeling and drug testing[41]. Copyright © 2024 by ASME.

关键词： Endothelial cells

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Impact of Artificial Compressibility on the Numerical Solution of Incompressible Nanofluid Flow

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Computers, materials & Continua 2023年第3期74卷 5123-5139页

作者： Tohid Adibi Shams Forruque Ahmed Seyed Esmail Razavi Omid Adibi Irfan Anjum Badruddin Syed Javed Department of Mechanical Engineering University of BonabBonabIran Science and Math Program Asian University for WomenChattogram4000Bangladesh School of Mechanical Engineering University of TabrizTabrizIran Energy Management Group Energy and Environment Research CenterNiroo Research InstituteTehranIran Mechanical Engineering Department College of EngineeringKing Khalid UniversityAbha61421Saudi Arabia

The numerical solution of compressible flows has become more prevalent than that of incompressible *** the help of the artificial compressibility approach,incompressible flows can be solved numerically using the same methods as compressible *** artificial compressibility scheme is thus widely used to numerically solve incompressible Navier-Stokes *** numerical method highly depends on its accuracy and speed of *** the artificial compressibility approach is utilized in several numerical simulations,the effect of the compressibility factor on the accuracy of results and convergence speed has not been investigated for nanofluid flows in previous ***,this paper assesses the effect of this factor on the convergence speed and accuracy of results for various types of *** improve the stability and convergence speed of time discretizations,the fifth-order Runge-Kutta method is applied.A computer program has been written in FORTRAN to solve the discretized equations in different Reynolds and Grashof numbers for various *** results demonstrate that the artificial compressibility factor has a noticeable effect on the accuracy and convergence rate of the *** optimum artificial compressibility is found to be between 1 and *** findings can be utilized to enhance the performance of commercial numerical simulation tools,including ANSYS and COMSOL.

关键词： Navier-Stokes equations incompressible flow artificial compressibility convergence rate convection flow

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ZnO/B-g-C3N4 Nanoplatelet/Nanosheet Heterostructures for the Electrochemical Detection of Metol in Real Sample Analysis

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ACS Applied Nano materials 2024年第2期7卷 2072-2085页

作者： Murugan, Ravikumar Hwa, Kuo-Yuan Santhan, Aravindan Ibrahim, Suriani Department of Molecular Science and Engineering National Taipei University of Technology Taipei10608 Taiwan Graduate Institute of Organic and Polymeric Materials National Taipei University of Technology Taipei10608 Taiwan Department of Mechanical Engineering Faculty of Engineering University of Malaya Kuala Lumpur50603 Malaysia

One of the most important organic molecules is metol [4-(methylamino)phenol sulfate], which finds extensive usage in various applications as a monochromatic material. People, plants, and animals are all affected by it, and it raises serious environmental concerns. Developing a straightforward, quick, affordable, sensitive, and hands-on technique for metol determination in water bodies is of the utmost importance in the current scenario. A low-cost fabrication strategy is presented in this work for the synthesis of a zinc oxide nanoplatelet (ZnO) embedded into boron-doped carbon nitride nanosheet materials (ZnO/2D-BCN) utilizing a high-performance electrochemical sensor. The quantitative and qualitative information about the nanostructure of ZnO/2D-BCN were systematically analyzed further by using standard spectroscopic techniques such as XPS, XRD, FT-IR, EDAX, and Raman spectroscopy. 2D-nonstructural was observed to have a nanoplatelet/nanosheet through FE-SEM and TEM. Furthermore, electrochemical sensors’ performance was analyzed by using cyclic and differential pulsed voltammetry techniques. The fabricated ZnO/2D-BCN has peculiar intrinsic structural features, both connectivity and characteristic synergistic effect of B-dopants 2D-structure, which perturb mass transport with highly efficient electrochemical pathways. In addition, the electrochemical sensors of metol and its electrocatalytic mechanism were scrutinized further, which confirmed a fast electron transfer event. The as-prepared ZnO/2D-BCN exposed superior sensing conclusion through LOD (8.6 nM) in a wide-ranging linear 0.039-1617 (μM) as well as a remarkable sensitivity of 0.804 μA μM-1 cm-2. Additionally, other sensing parameters such as remarkable repeatability, electrodes’ reproducibility, materials’ stability, and a remarkable selectivity toward metol have been performed. Furthermore, the practical feasibility of as-made ZnO/2D-BCN/GCE has been inspected with biological and environment samples such

关键词： Zinc oxide

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Effective thermal conductivity estimation using a convolutional neural network and its application in topology optimization

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Energy and AI 2024年第1期15卷 236-247页

作者： Andre Adam Huazhen Fang Xianglin Li Department of Mechanical Engineering University of Kansas1530 W 15th St.Lawrence66045KSUSA Department of Mechanical Engineering and Materials Science Washington University in St.LouisOne Brookings DriveSt.Louis63130MOUSA

Topology optimization of heterogeneous structures can find significant use in a wide range of applications,and its fabrication has been made possible by recent advances in additive ***,the optimization procedure is computationally expensive,as each structural update requires the re-evaluation of the *** computational time is the major limiting factor in large-scale and complex structural *** this study,a convolutional neural network(CNN)model for predicting effective thermal conductivity inspired by the VGG networks is *** using 130,000 unique binary images,the model achieves high predictive ***,it shows a mean absolute percent error(MAPE)of 0.35%in testing when the thermal conductivity of the solid is ten times larger than the fluid,and when the thermal conductivities assigned are that of aluminum and water,the MAPE is 2.35%.The prediction time is 15 ms for a single image with 128×128 pixels,which is 3 to 5 orders of magnitude faster than a finite volume *** employed in topology optimization,the CNN retains a MAPE between 0.67%and 11.8%for different *** CNN model correctly predicts trends in effective thermal conductivity and improves the structure to close proximity of a theoretical maximum in all cases.

关键词： Machine learning Effective thermal conductivity Convolutional neural network VGG Numerical heat transfer Topology optimization

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ENHANCING TEACHING EFFECTIVENESS AND STUDENT ENGAGEMENT IN STRUCTURAL engineering THROUGH INTEGRATION OF RISA SOFTWARE: A PROJECT-BASED PEDAGOGY APPROACH

ENHANCING TEACHING EFFECTIVENESS AND STUDENT ENGAGEMENT IN S...

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ASME 2024 International mechanical engineering Congress and Exposition, IMECE 2024

作者： Jazaei, Robabeh Azari, Fatemeh Department of Engineering College of Engineering and Science Slippery Rock University Slippery RockPA United States Department of Mechanical Engineering and Materials Science College of Engineering University of Pittsburgh PittsburghPA United States

ISBN: (纸本)9780791888650

This study investigates the effect of integrating RISA Software within a project-based pedagogy framework on teaching effectiveness and student learning outcomes in a junior-level civil engineering structural analysis course. Over three consecutive years (2021-2023), the course was delivered to cohorts of 12-20 civil engineering students, employing various pedagogical approaches. Despite consistent teaching methodology effectiveness ratings in the lecture section across the first two years (average 3 ± 0.2 out of 4), the lab section of this course, where RISA Software was integrated, demonstrated a steady increase in teaching effectiveness from 3.09 to 3.32 for the first two years. Notably, in 2023, the introduction of project-based pedagogy resulted in an 11% improvement in teaching effectiveness in the lecture section and an impressive 27% increase in the lab section. Key findings suggest that the incorporation of RISA Software within a project-based pedagogical framework fosters enhanced teaching effectiveness, heightened student engagement, and a more profound understanding of structural engineering concepts. This research underscores the efficacy of integrating practical software tools with innovative teaching methodologies to optimize learning outcomes in complex engineering subjects. © 2024 by ASME.

关键词： Structural Mechanics

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High Density 3D Carbon Tube Nanoarray Electrode Boosting the Capacitance of Filter Capacitor

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Nano-Micro Letters 2024年第11期16卷 242-254页

作者： Gan Chen Fangming Han Huachun Ma Pei Li Ziyan Zhou Pengxiang Wang Xiaoyan Li Guowen Meng Bingqing Wei Key Laboratory of Materials Physics and Anhui Key Laboratory of Nanomaterials and NanotechnologyInstitute of Solid State PhysicsHFIPSChinese Academy of SciencesHefei 230031People’s Republic of China Department of Materials Science and Engineering University of Science and Technology of ChinaHefei 230026People’s Republic of China Department of Mechanical Engineering University of DelawareNewarkDE 19716USA Mechano‑X Institute Applied Mechanics LaboratoryDepartment of Engineering MechanicsTsinghua UniversityBeijing 100084People’s Republic of China

Electric double-layer capacitors(EDLCs)with fast frequency response are regarded as small-scale alternatives to the commercial bulky aluminum electrolytic *** carbon-based nanoarray electrodes with precise alignment and smooth ion channels is crucial for enhancing EDLCs’***,controlling the density of macropore-dominated nanoarray electrodes poses challenges in boosting the capacitance of line-filtering ***,a simple technique to finely adjust the vertical-pore diameter and inter-spacing in three-dimensional nanoporous anodic aluminum oxide(3D-AAO)template is achieved,and 3D compactly arranged carbon tube(3D-CACT)nanoarrays are created as electrodes for symmetrical EDLCs using nanoporous 3D-AAO template-assisted chemical vapor deposition of *** 3D-CACT electrodes demonstrate a high surface area of 253.0 m^(2) g^(−1),a D/G band intensity ratio of 0.94,and a C/O atomic ratio of *** a result,the high-density 3D-CT nanoarray-based sandwich-type EDLCs demonstrate a record high specific areal capacitance of 3.23 mF cm^(-2) at 120 Hz and exceptional fast frequency response due to the vertically aligned and highly ordered nanoarray of closely packed CT *** 3D-CT nanoarray electrode-based EDLCs could serve as line filters in integrated circuits,aiding power system miniaturization.

关键词： Compactly arranged Three-dimensional carbon tube nanoarray Dimensional carbon tube nanoarray Fast frequency response Electric double-layer capacitors Layer capacitors AC line-filtering Filtering

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An inverse strategy to determine constitutive parameters of tubular materials for hydroforming processes

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Chinese Journal of Aeronautics 2022年第6期35卷 379-390页

作者： Bin ZHANG Benny ENDELT Lihui LANG Yang ZHAO Shu YAN Karl Brian NIELSEN Department of Materials and Production Aalborg UniversityAalborg 9220Denmark School of Mechanical Engineering and Automation Beihang UniversityBeijing 100083China School of Materials Science and Engineering Northeastern UniversityShenyang 110819China Department of Mechanical and Production Engineering Aarhus UniversityAarhus 8000Denmark

This paper is to determine the flow stress curve of 5049-O aluminium alloy by a tube hydraulic bulging test with fixed end-conditions. During this test, several tubular specimens are bulged under different internal pressures before their bursting, and the corresponding bulging height and wall thickness at the pole are measured. An inverse strategy is developed to determine the constitutive parameters of tubular materials based on experimental data, which combines the finite element method with gradient-based optimization techniques. In this scheme, the objective function is formulated with the sum of least squares of the error between numerical and experimental data, and finite difference approximation is used to calculate the gradient. The tubular material behavior is assumed to meet the von Mises yield criterion and Hollomon exponential hardening law. Then, constitutive parameters identification is performed by minimization of the objective function. In order to validate the performance of this framework, identified parameters are compared with those obtained by two types of theoretical models, and tensile tests are performed on specimens cut from the same tubes. The comparison shows that this inverse framework is robust and can achieve a more accurate parameter identification by eliminating mechanical and geometrical assumptions in classical theoretical analysis.

关键词： Aluminum alloy Constitutive parameter Hydraulic bulging test Inverse modelling Tubular material

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Optimizing FeCoNiCrTi high-entropy alloy with hydrogen pumping effect to boost de/hydrogenation performance of magnesium hydride

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Rare Metals 2024年第7期43卷 3273-3285页

作者： Meng-Chen Song Fu-Ying Wu Yi-Qun Jiang Xiu-Zhen Wang Hu Zhao Li-Xin Chen Liu-Ting Zhang School of Energy and Power Instrumental Analysis CenterJiangsu University of Science and TechnologyZhenjiang 212003China Max Planck Institute for Iron Research 40237DuisseldorfGermany School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore State Key Laboratory of Silicon Materials Department of Materials Science and EngineeringZhejiang UniversityHangzhou 310027China

The exploration of efficient,long-lived and cost-effective transition metal catalysts is highly desirable for the practical hydrogen storage of magnesium hydride(MgH_(2)) in sustainable energy ***,FeCoNiCrTi high-entropy alloy(HEA) nanosheets were prepared via a facile wet chemical ball milling strategy and they were introduced into MgH_(2) to boost the hydrogen storage *** refined HEA exhibited superior catalytic activity on MgH_(2).In contrast to additive-free MgH_(2),the initial desorption temperature of the constructed MgH_(2)-HEA composite was reduced from 330.0 to 198.5℃ and a remarkable 51% reduction in the dehydrogenation activation energy was ***,the MgH_(2)-HEA composite only required one-twentieth time of that consumed by pure MgH_(2) to absorb 5.0 wt% of H_(2) at 225℃.The synergy between the "hydrogen pumping" effect of Mg_2Ni/Mg_2NiH_4 and Mg_2Co/Mg_2CoH_5 couples,as well as the good dispersion of Fe,Cr and Ti on the surface of MgH_(2) contributed to the enhanced de/hydrogenation performance of the MgH_(2)-HEA *** study furnishes important steering for the design and fabrication of multiple transition metal catalysts and may push the commercial application of magnesium-based hydrides one step forward.

关键词： Hydrogen storage Magnesium hydride High-entropy alloys Catalysis

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Employment of Finite Element Analysis Method to Analyze the Thermal Effects of Direct Energy Deposition on SUS316L

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Sensors and materials 2024年第4期36卷 1693-1706页

作者： Zheng, Wenjie Chang, Hung-Yu Hsu, Chao-Ming Yang, Cheng-Fu School of Ocean Information Engineering Jimei University Fujian Xiamen361021 China Department of Mechanical Engineering National Kaohsiung University of Science and Technology Kaohsiung807 Taiwan Department of Chemical and Materials Engineering National University of Kaohsiung Kaohsiung811 Taiwan Department of Aeronautical Engineering Chaoyang University of Technology Taichung413 Taiwan

In this study, we investigated the displacement behavior of SUS316L stainless steel under five consecutive direct energy depositions through experiments and the use of the ANSYS commercial finite element method software. We explored the effects of displacement after cooling the five deposited layers and examined the relationship between different curvatures and laser parameters, including laser power and laser feed rate. In this research, a complete cross-sectional profile was obtained through experiments. Subsequently, simulations were conducted using laser powers of 300, 400, and 500 W, along with laser feed rates of 3, 5, and 7 mm/s, employing a thermal-solid coupling model. The results indicated that the optimal preheating temperature during the deposition process was around 150 °C, leading to a more stable displacement difference. The influence of curvature on displacement was relatively consistent along the neutral axis, allowing for the prediction of large displacement amounts along a straight-line path. Through simulation, it could be understood that when utilizing direct energy deposition to deposit SUS316L, considering the displacement conditions during the deposition process, it was preferable to use a low laser power and a high deposition rate. © MYU K.K.

关键词： Finite element method

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A deep neural network regressor for phase constitution estimation in the high entropy alloy system Al-Co-Cr-Fe-Mn-Nb-Ni

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npj Computational materials 2023年第1期9卷 1661-1674页

作者： G.Vazquez S.Chakravarty R.Gurrola R.Arróyave Department of Materials Science and Engineering Texas A&M UniversityCollege Station 77843 TXUSA Department of Mechanical Engineering Texas A&M UniversityCollege Station 77843 TXUSA Department of Industrial and Systems Engineering Texas A&M UniversityCollege Station 77843 TXUSA

High Entropy Alloys(HEAs)are composed of more than one principal element and constitute a major paradigm in metals *** HEA space is vast and an exhaustive exploration is ***,a thorough estimation of the phases present in the HEA is of paramount importance for alloy *** Learning presents a feasible and non-expensive method for predicting possible new HEAs on-the-fly.A deep neural network(DNN)model for the elemental system of:Mn,Ni,Fe,Al,Cr,Nb,and Co is developed using a dataset generated by high-throughput computational thermodynamic calculations using *** features list used for the neural network is developed based on literature and freely available databases.A feature significance analysis matches the reported HEAs phase constitution trends on elemental properties and further expands it by providing so far-overlooked *** final regressor has a coefficient of determination(r^(2))greater than 0.96 for identifying the most recurrent phases and the functionality is tested by running optimization tasks that simulate those required in alloy *** DNN developed constitutes an example of an emulator that can be used in fast,real-time materials discovery/design tasks.

关键词： alloy neural network

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