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Configuration blade shape for enhancement crossflow turbine performance by the CFD method

International Journal of Thermofluids 2024年 22卷

作者： Adanta, Dendy Sari, Dewi Puspita Syofii, Imam Thamrin, Ismail Yani, Irsyadi Marwani Fudholi, Ahmad Prakoso, Aji Putro Department of Mechanical Engineering Faculty of Engineering Universitas Sriwijaya Ogan Ilir South Sumatera30862 Indonesia Study Program of Mechanical Engineering Education Faculty of Teacher Training and Education Universitas Sriwijaya Ogan Ilir South Sumatera 30862 Indonesia Serpong15314 Indonesia Solar Energy Research Institute Universiti Kebangsaan Malaysia Selangor Bangi43600 Malaysia Department of Mechanical Engineering Faculty of Manufacturing Technology Universitas Jenderal Ahmad Yani West Java Cimahi Indonesia

The pico scale crossflow turbine (CFT) is a prospect as an independent power plant for remote and rural areas because it has a stable efficiency range of 64 % to 79.5 % in high discharge fluctuation. An alternative to CFT performance enhancement is determining the upper blade configuration to increase lift force. Hence, this study investigates four configurations of the upper CFT blade: convex blade at the centre edge, convex at the trailing edge, convex at the leading edge and ordinary curvature. This research employs a computational fluid dynamics (CFD) method to visualise the flow field. The upper CFT blade configuration significantly affects its performance, and convex at the leading edge has higher performance than others. The performance related to each blade shape's specific speed is parabolic and expressed using empirical law. The empirical law recommends 4.88 as specific speed for designing a pico scale CFT. © 2024 The Author(s)

关键词： Turbomachine blades

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Unlocking development of green hydrogen production through techno-economic assessment of wind energy by considering wind resource variability: A case study

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International Journal of Hydrogen Energy 2024年 138卷 1249-1262页

作者： Hesty, Nurry Widya Aminuddin Supriatna, Nina Konitat Cendrawati, Dian Galuh Nurliyanti, Vetri Nurrohim, Agus Fithri, Silvy Rahmah Niode, Nona Al Irsyad, Muhammad Indra Research Center for Energy Conversion and Conservation National Research and Innovation Agency KST Habibie Serpong Tangerang Selatan153432 Indonesia Research Center for Process and Manufacturing Industry Technology National Research and Innovation Agency KST Habibie Serpong Banten Tangerang Selatan153143 Indonesia Magister of Industrial Engineering University of Mercu Buana Jakarta11650 Indonesia Departement of Mechanical Engineering Universitas Indonesia 16424 Indonesia Survey and Testing Center for Electricity New Renewable Energy and Energy Conservation Technology Ministry of Energy and Mineral Resources Jakarta12230 Indonesia Study Program of Advanced Climatology Departement of Geophysics and Meteorologi IPB University Bogor16680 Indonesia Research Center for Behavioral and Circular Economics Jl. Gatot Subroto No.10 Jakarta12710 Indonesia

Generating hydrogen from renewable energy sources is widely recognized as an effective strategy for addressing critical challenges in the energy sector while contributing to the reduction of greenhouse gas emissions. This study aims to assess the wind energy potential for electricity and hydrogen production in five locations on Sumba Island using 10 years (2011–2020) of data from the NASA's POWER Project. A wind variability assessment was performed on five wind turbines ranging from 500 kW to 1.5 MW and using electrolysis technology. The results indicated a hydrogen production potential of 25–57 tons per year. Economic analysis of hydrogen production for Haharu reveals an attractive internal rate of return (IRR) of 43% with a payback period (PBP) of 2.25 years and a net present value (NPV) of 1.3 MM USD, the levelized cost of electricity (LCOE) of 0.0241 USD/kWh, and the levelized cost of Hydrogen (LCOH) of 1.01 USD/kg. Sensitivity analysis underscores the critical influence of investment and revenue on project profitability, highlighting their substantial impact on determining a project's success or failure. These findings emphasize the potential of Sumba Island as a hub for sustainable energy production to meet the growing demand for clean and renewable energy sources. © 2024 Hydrogen Energy Publications LLC

关键词： Clean energy

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Wear of silicon carbide wheel during grinding of intermetallic titanium aluminide

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International Journal of Machining and Machinability of Materials 2020年第2期22卷 122-136页

作者： Mathew, Nithin Tom Vijayaraghavan, L. Mechanical Engineering Department Work Integrated Learning Program Division BITS Pilani Rajasthan333031 India Department of Mechanical Engineering Manufacturing Engineering Section Indian Institute of Technology Madras Chennai600036 India

An experimental investigation is reported on the wear of silicon carbide wheel and its influence on the wheel topography and grinding behaviour during the surface grinding of high performance intermetallic gamma titianium aluminide. The radial wear of the wheel was characterised by initial transient state followed by a steady state wear regime and finally a steel rise in wear rate. The initial transient region progressed up to a radial wear of 40 µm. The normal and tangential forces remained approximately constant up to about 25 µm wheel wear and subsequently progressively increased to a maximum at 60 µm wear. The specific energy began approximately at about u = 140 J/mm3 and started progressing beyond radial wear of 25 µm and increased up to 600 J/mm3 at wear of 60 µm. There was high initial roughness value with the fresh wheel with a progressive decrease with continued grinding. There was noticeable increase in roughness value after a radial wear of 60 µm. With the progress of wear there was presence of surface burns, chatter marks and cracking. The presence of blue oxide discoloration was observed during the visual inspection signifying the generation of reasonably high temperature. Copyright © 2020 Inderscience Enterprises Ltd.

关键词： Silicon carbide

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Smart Dome 4.0: Low-Cost, Independent, Automated Energy System for Agricultural Purposes enabled by Machine Learning 2

Smart Dome 4.0: Low-Cost, Independent, Automated Energy Syst...

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2021 2nd International Symposium on Automation, Information and Computing, ISAIC 2021

作者： Budiman, Arief S Gunawan, Fergyanto Djuana, Endang Pardamean, Bens Romeli, Sugiarto Putri, Dianing Nn Aji, Daisman Pb Rahardjo, Kuat Stevanus Ilham Wibowo, M. Daffa, Nadiev Owen, Raymond Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia Department of Manufacturing and Mechanical Engineering and Technology Oregon Institute of Technology Klamath FallsOR97601 United States Electrical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia PT. Impack Pratama Industri Tbk Jakarta Indonesia Mechanical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta Indonesia Industrial Engineering Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia

Many economically essential crops in Indonesia (such as coffee, tea, chocolate, or copra) require storage or drying under certain environmental conditions, especially temperature and humidity. The solar dryer dome, typically used for agricultural purposes in Indonesia, produces a sufficient amount of heat to increase the evaporation rate inside the dome and reduce the moisture content of the commodity. A hybrid solar dryer accompanied by a photovoltaic panel, fan, and ventilation system is generally suitable. The system can provide an optimum environment with minimum control. However, as the outdoor temperature and humidity change dramatically, such as at night time, more control is required. Based on Industry 4.0 technologies, we have developed a new kind of hybrid solar dryer that provides an optimum environment 24/7. The system, called Smart Dome 4.0, is an intelligent, low-cost, self-sufficient drying and storage system to support Indonesia Agriculture 4.0. The system has a local power generation unit to self-sustain the required energy and operate without connecting to the electricity grid. The system utilizes a machine-learning algorithm to predict the environmental condition and optimally uses self-generated electric power. The developed Smart Dome 4.0 technology is critical to producing a sustainable solar dome under drastic environmental dynamics. © Published under licence by IOP Publishing Ltd.

关键词： Learning algorithms

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Advancing electrochemical impedance analysis through innovations in the distribution of relaxation times method

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Joule 2024年第7期8卷 1958-1981页

作者： Maradesa, Adeleke Py, Baptiste Huang, Jake Lu, Yang Iurilli, Pietro Mrozinski, Aleksander Law, Ho Mei Wang, Yuhao Wang, Zilong Li, Jingwei Xu, Shengjun Meyer, Quentin Liu, Jiapeng Brivio, Claudio Gavrilyuk, Alexander Kobayashi, Kiyoshi Bertei, Antonio Williams, Nicholas J. Zhao, Chuan Danzer, Michael Zic, Mark Wu, Phillip Yrjänä, Ville Pereverzyev, Sergei Chen, Yuhui Weber, André Kalinin, Sergei V. Schmidt, Jan Philipp Tsur, Yoed Boukamp, Bernard A. Zhang, Qiang Gaberšček, Miran O'Hayre, Ryan Ciucci, Francesco Department of Mechanical and Aerospace Engineering The Hong Kong University of Science and Technology Hong Kong Metallurgical and Materials Engineering Colorado School of Mines Golden80401 United States Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology Department of Chemical Engineering Tsinghua University Beijing China Green Energy Storage Trento38123 Italy Department of Manufacturing and Production Engineering Faculty of Mechanical Engineering and Ship Technology Institute of Machine and Materials Technology Gdańsk University of Technology Gdańsk Poland Electrode Design for Electrochemical Energy Systems University of Bayreuth Bayreuth Germany School of Chemistry University of New South Wales Sydney Australia School of Advanced Energy Sun Yat-Sen University Shenzhen China Sustainable Energy Center CSEM Neuchâtel2002 Switzerland Interdisciplinary Faculty of Science and Engineering Shimane University Matsue Japan Centre for Electronic and Optical Materials National Institute for Materials Science Tsukuba Japan Department of Civil and Industrial Engineering University of Pisa Pisa Italy Department of Materials Imperial College London Exhibition Road LondonSW7 2AZ United Kingdom Department of Chemical Engineering Massachusetts Institute of Technology Cambridge02139 United States Electrical Energy Systems University of Bayreuth Bayreuth Germany Ruder Boskovic Institute Zagreb Croatia Department of Materials and Minerals Resources Engineering National Taipei University Taipei Taiwan Finland Johann Radon Institute for Computational and Applied Mathematics Linz Austria School of Science and Engineering Nanjing Tech. University Nanjing China Karlsruhe Germany Department of Materials Science and Engineering University of Tennessee KnoxvilleTN37996 United States Physical Science Division Pacific Northwest National Laboratory RichlandWA99354 United States Systems Engineering for Electrical Energy Storage University of B

Electrochemical impedance spectroscopy (EIS) is widely used in electrochemistry, energy sciences, biology, and beyond. Analyzing EIS data is crucial, but it often poses challenges because of the numerous possible equivalent circuit models, the need for accurate analytical models, the difficulties of nonlinear regression, and the necessity of managing large datasets within a unified framework. To overcome these challenges, non-parametric models, such as the distribution of relaxation times (DRT, also known as the distribution function of relaxation times, DFRT), have emerged as promising tools for EIS analysis. For example, the DRT can be used to generate equivalent circuit models, initialize regression parameters, provide a time-domain representation of EIS spectra, and identify electrochemical processes. However, mastering the DRT method poses challenges as it requires mathematical and programming proficiency, which may extend beyond experimentalists’ usual expertise. Post-inversion analysis of DRT data can be difficult, especially in accurately identifying electrochemical processes, leading to results that may not always meet expectations. This article examines non-parametric EIS analysis methods, outlining their strengths and limitations from theoretical, computational, and end-user perspectives, and provides guidelines for their future development. Moreover, insights from survey data emphasize the need to develop a large impedance database, akin to an impedance genome. In turn, software development should target one-click, fully automated DRT analysis for multidimensional EIS spectra interpretation, software validation, and reliability. Particularly, creating a collaborative ecosystem hinged on free software could promote innovation and catalyze the adoption of the DRT method throughout all fields that use impedance data. © 2024 Elsevier Inc.

关键词： Electrochemical impedance spectroscopy

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Tunable Multimodal Guided Surface Lattice Resonances in Index-Discontinuous Environments

arXiv

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arXiv 2024年

作者： Huang, Suichu Yao, Kan Huang, Wentao Zhao, Xuezheng Zheng, Yuebing Pan, Yunlu Key Laboratory of Micro-Systems and Micro-Structures Manufacturing Ministry of Education School of Mechatronics Engineering Harbin Institute of Technology Harbin150001 China Walker Department of Mechanical Engineering Material Science and Engineering Program Texas Materials Institute The University of Texas at Austin AustinTX78712 United States

Surface lattice resonances (SLRs) in metasurfaces are promising in applications of sub-wavelength devices, owning properties such as high quality (high-Q) factors, large local field enhancement and extensive long-range interaction. The tunable peak position and multimodal resonances of SLRs further enhance their appeal for flexible and multi-wavelength light-matter interactions. Despite these advantages, the realization of tunable multimodal SLRs often requires reconfiguring the lattices, leading to limited tunability. Furthermore, current high-Q SLR implementations necessitate a homogeneous dielectric environment, restricting potential applications such as biosensors that are typically operated in an aqueous or air cladding on a substrate. Here we present guided-SLRs (gSLRs), which are easily accessible in index-discontinuous environments while retaining the multimodal property and straightforward tunability of mode number, resonance wavelengths and mode coupling strengths. The gSLRs are achieved by coupling the scattered light from metasurface units into a slab waveguide, creating a light propagating channel in the lattice plane within an index-asymmetric environment. Tailoring the radiation pattern of individual units with guided transverse electric (TE) and transverse magnetic (TM) modes, multimodal resonances in both orthogonal and parallel coupling directions are accomplished. The mode number and resonance wavelengths can be easily controlled by adjusting the waveguide configuration, while the mode coupling strength is tuned by the vertical position of lattices in the slab. Further shift of the multimodal gSLRs from visible to near-infrared is achieved by introducing a gold backplane. The easy-to-access, flexibly tunable and multimodal gSLRs in inhomogeneous media offer a promising solution to advancing the realization of ultrathin and ultracompact nano-optical and optoelectronic devices. Copyright © 2024, The Authors. All rights reserved.

关键词： Waveguides

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An application of conjugate gradient technique for determination of thermal conductivity as an inverse engineering problem

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Materials Today: Proceedings 2021年 47卷 3082-3087页

作者： Vivek Pandey Addisu Bekele Gulam Mohammed Sayeed Ahmed Nand Jee Kanu Gyanendra Kumar Singh Department of Thermal and Aerospace Engineering School of Mechanical Chemical and Materials Engineering Adama Science and Technology University Adama Ethiopia Centre of Excellence for Advanced Manufacturing Engineering Program of Mechanical Design and Manufacturing Engineering School of Mechanical Chemical and Materials Engineering Adama Science and Technology University Adama Ethiopia Department of Mechanical Engineering S. V. National Institute of Technology Surat India Department of Mechanical Design and Manufacturing Engineering School of Mechanical Chemical and Materials Engineering Adama Science and Technology University Adama Ethiopia

Inverse problems frequently occur when boundary conditions/thermal properties of a material are unknown, and are determined from known internal temperature measurements. A direct problem is the opposite of an inverse problem. For example, it would be the task of determining the temperature field within a material body, given boundary conditions and thermal properties. In an ill-posed, inverse problem, small variations in internal temperature measurement cause large variations in the estimated quantity such as boundary heat flux. Measured temperature variations may be due to noise, measurement error and instrumentation error, among other factors. There are various methods for solving inverse problems in materials engineering. In the paper, an inverse problem of estimating boundary heat flux for one-dimensional heat conduction is solved using the classical method of Beck and temperature dependent thermal conductivity is estimated using the more recent and advanced Conjugate Gradient method (CGM). The temperature values from the finite difference application to a direct heat transfer problem are used along with noise added to the data, in order to simulate real world, experimental conditions. The data is applied to the inverse problem of finding boundary heat flux and thermal conductivity. It is seen that Conjugate Gradient Method (CGM) along with sequential function specification method recovers the boundary heat flux and thermal conductivity quite accurately for noise levels of 1% and 2%. It is further observed that addition of future time steps stabilize the algorithm and increase accuracy of the desired results. It is also observed that CGM can recover the temperature dependent thermal conductivity quickly within few iterations, for different values of thermal conductivity function coefficients, k 0 and k 1 . CGM is found to be fast and robust when applied to one-dimensional case and can be extended to complex geometries.

关键词： Inverse problem Thermal conductivity Conjugate gradient

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A preliminary data fusion study to assess the feasibility of Foundation Process-Property Models in Laser Powder Bed Fusion

arXiv

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arXiv 2025年

作者： Vendrell-Gallart, Oriol Negarandeh, Nima Foumani, Zahra Zanjani Amiri, Mahsa Valdevit, Lorenzo Bostanabad, Ramin Department of Mechanical and Aerospace Engineering University of California IrvineCA92697 United States Materials and Manufacturing Technology Program University of California IrvineCA92697 United States Department of Materials Science and Engineering University of California IrvineCA92697 United States Department of Civil and Environmental Engineering University of California IrvineCA92697 United States

Foundation models are at the forefront of an increasing number of critical applications. In regards to technologies such as additive manufacturing (AM), these models have the potential to dramatically accelerate process optimization and, in turn, design of next generation materials. A major challenge that impedes the construction of foundation process-property models is data scarcity. To understand the impact of this challenge, and since foundation models rely on data fusion, in this work we conduct controlled experiments where we focus on the transferability of information across different material systems and properties. More specifically, we generate experimental datasets from 17-4 PH and 316L stainless steels (SSs) in Laser Powder Bed Fusion (LPBF) where we measure the effect of five process parameters on porosity and hardness. We then leverage Gaussian processes (GPs) for process-property modeling in various configurations to test if knowledge about one material system or property can be leveraged to build more accurate machine learning models for other material systems or properties. Through extensive cross-validation studies and probing the GPs’ interpretable hyperparameters, we study the intricate relation among data size and dimensionality, complexity of the process-property relations, noise, and characteristics of machine learning models. Our findings highlight the need for structured learning approaches that incorporate domain knowledge in building foundation process-property models rather than relying on uninformed data fusion in data-limited applications. © 2025, CC BY.

关键词： Data fusion

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Ab initio study on changing behaviors of lithium-rich layered composite cathode materials

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Electrochimica Acta 2024年 500卷

作者： Chuang, Yu-cheng Tran, Ngoc Thanh Thuy Tsai, Ping-chun Lin, Shih-kang Department of Materials Science and Engineering National Cheng Kung University Tainan70101 Taiwan Research Center National Cheng Kung University Tainan70101 Taiwan Department of Mechanical Engineering National Taiwan University of Science and Technology Taipei10607 Taiwan Program on Smart and Sustainable Manufacturing Academy of Innovative Semiconductor and Sustainable Manufacturing National Cheng Kung University Tainan70101 Taiwan Core Facility Center National Cheng Kung University Tainan70101 Taiwan

The lithium-rich composite-layered oxide, xLi2MnO3•(1-x)LiM'O2, where M’ represents transition metals, is a promising cathode material with excellent capacity at high working voltage for lithium-ion batteries (LIBs). Nevertheless, an unusual charge-discharge feature is observed for this material with sloping and plateau regions during the initial charging. In this work, ab initio calculations based on density functional theory were employed to examine the stability of xLi2MnO3•(1-x)Li(Ni1/3Co1/3Mn1/3)O2 composite-layered cathode materials during the first charging. Optimized atomistic models for different compositions (x = 0.0, 0.3, 0.4, 0.5, 0.7, and 1) unveil a pseudo-rhombohedral or monoclinic-like structure within the solid solution phase, with simulated X-ray diffraction patterns closely matching experimental data. Using these atomistic models, the first charging process of the 0.4Li2MnO3•0.6Li(Ni1/3Co1/3Mn1/3)O2 cathode were investigated. There exists phase transition from a layered to a spinel structure. Additionally, Bader charge analysis reveals intriguing trends during the first delithiation process, where the valence states of Ni and Co gradual increase, while that of Mn almost remains unchanged. Simultaneously, significant oxidation of O is observed. This finding leads to further evaluations on oxygen vacancy formation in comparison to the energy required for delithiation. Defect formation energy calculations demonstrate that the plateau in charging curve is resulted from oxygen vacancy formation during the first charging. By empirical fitting oxygen chemical potential at μO = -1.200 eV, the calculated charging-discharging curves aligned well with experimental data during the first and second charging. Furthermore, the pathways of lithium and oxygen deintercalation are elucidated. This work contributes fundamental understandings on the xLi2MnO3•(1-x)LiM'O2 composite-layered oxides as cathode for LIBs, providing valuable guidance for further developments

关键词： Cathodes

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The Performance Investigation of Smart Diagnosis for Bearings Using Mixed Chaotic Features with Fractional Order

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Sensors 2023年第8期23卷 3801-3801页

作者： Li, Shih-Yu Tam, Lap-Mou Wu, Shih-Ping Tsai, Wei-Lin Hu, Chia-Wen Cheng, Li-Yang Xu, Yu-Xuan Cheng, Shyi-Chyi Graduate Institute of Manufacturing Technology National Taipei University of Technology Taipei10608 Taiwan Institute for the Development and Quality 999078 China Department of Electromechanical Engineering Faculty of Science and Technology University of Macau 999078 China Master Program Graduate Institute of Mechatronic Engineering National Taipei University of Technology Taipei10608 Taiwan Department of Mechanical Engineering National Taipei University of Technology Taipei10608 Taiwan Department of Computer Science and Engineering National Taiwan Ocean University Keelung City202301 Taiwan

This article presents a performance investigation of a fault detection approach for bearings using different chaotic features with fractional order, where the five different chaotic features and three combinations are clearly described, and the detection achievement is organized. In the architecture of the method, a fractional order chaotic system is first applied to produce a chaotic map of the original vibration signal in the chaotic domain, where small changes in the signal with different bearing statuses might be present;then, a 3D feature map can be obtained. Second, five different features, combination methods, and corresponding extraction functions are introduced. In the third action, the correlation functions of extension theory used to construct the classical domain and joint fields are applied to further define the ranges belonging to different bearing statuses. Finally, testing data are fed into the detection system to verify the performance. The experimental results show that the proposed different chaotic features perform well in the detection of bearings with 7 and 21 mil diameters, and an average accuracy rate of 94.4% was achieved in all cases. © 2023 by the authors.

关键词： Fault detection

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