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Numerical study of convective heat transfer in static arrangements of particles with arbitrary shapes:A monolithic hybrid lattice Boltzmann-finite difference-phase field solver

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Particuology 2024年第2期85卷 186-197页

作者： Reza Namdar Mohammadhassan Khodsiani Hesameddin Safari Tanya Neeraj Seyed Ali Hosseini frank Beyrau Benoit Fond Dominique Thevenin Fathollah Varnik Interdisciplinary Centre for Advanced Materials Simulation(ICAMS) Ruhr-University BochumBochum44801Germany Laboratory of Technical Thermodynamics University of Magdeburg"Otto von Guericke"Magdeburg39106Germany Laboratory of Fluid Dynamics and Technical Flows University of Magdeburg"Otto von Guericke"MagdeburgD-39106Germany Department of Mechanical and Process Engineering ETH ZurichZurich8092Switzerland ONERA The French Aerospace Lab Department of AerodynamicsAeroelasticity and Acoustics(DAAA)Paris-Saclay UniversityMeudon92190France

A compressible lattice Boltzmann-finite difference method is extended by the phase-field approach into a monolithic scheme to study fluid flow and heat transfer through regular arrangements of solid bodies of circular,elliptical and irregular *** advantage of using the phase-field method is demon-strated both in its simplicity of accounting for flow and thermal boundary conditions at solid surfaces with irregular shapes and in the capability of generating such complex-shaped *** an array of discs,numerical results for the overall solid-to-gas heat transfer rate are validated via experiments on flow through arrays of hot *** thus validated compressible LB-FD-PF hybrid scheme is used to study the dependence of heat transfer on flow and thermal boundary conditions(Reynolds number,temperature difference between the hot solid bodies and the inlet gas),porosity as well as on the shape of solid *** are rationalized in terms of the residence time of the gas close to the solid body and downstream variations of gas velocity and *** for further applications of the proposed methodology are also discussed.

关键词： Lattice Boltzmann method Finite difference scheme Convective heat transfer Diffuse interface Thermal compressible flow

Empirically evaluating virtual reality’s effect on reservoir engineering tasks

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Visual Informatics 2024年第1期8卷 26-46页

作者： Bryson Lawton Nanjia Wang Steven Samoil Parisa Daeijavad Siqi Xie Zhangxin Chen frank Maurer Department of Computer Science University of Calgary2500 University Dr NWCalgaryT2N 1N4AlbertaCanada Department of Chemical&Petroleum Engineering University of Calgary2500 University Dr NWCalgaryT2N 1N4AlbertaCanada

To help determine in what ways virtual reality(VR)technologies may benefit reservoir engineering workflows,we conducted a usability study on a prototype VR tool for performing reservoir model analysis *** leveraging the strengths of VR technologies,this tool’s aim is to help advance reservoir analysis workflows beyond conventional methods by improving how one understands,analyzes,and interacts with reservoir model *** evaluate our tool’s VR approach to this,the study presented herein was conducted with reservoir engineering experts who used the VR tool to perform three common reservoir model analysis tasks:the spatial filtering of model cells using movable planes,the cross-comparison of multiple models,and well path *** study found that accomplishing these tasks with the VR tool was generally regarded as easier,quicker,more effective,and more intuitive than traditional model analysis software while maintaining a feeling of low task workload on ***,participants provided positive feedback regarding their experience with using VR to perform reservoir engineering work tasks,and in general,it was found to improve multi-model cross-analysis and rough object manipulation in *** indicates the potential for VR to be better than conventional means for some work tasks and participants also expressed they could see it best utilized as an addition to current software in their reservoir model analysis *** were,however,some concerns voiced when considering the full adoption of VR into their work that would be best first addressed before this took place.

关键词： Immersive analytics Visual analytics Data visualization Reservoir engineering Virtual reality VR

Application of machine learning in perovskite materials and devices:A review

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Journal of Energy Chemistry 2024年第7期94卷 254-272页

作者： Ming Chen Zhenhua Yin Zhicheng Shan Xiaokai Zheng Lei Liu Zhonghua Dai Jun Zhang Shengzhong(frank)Liu Zhuo Xu School of Electric Power Civil Engineering and ArchitectureCollege of Physics and Electronics EngineeringState Key Laboratory of Quantum Optics and Quantum Optics DevicesShanxiUniversityTaiyuan030006ShanxiChina Key Laboratory of Applied Surface and Colloid Chemistry National Ministry of EducationShanxi Engineering Lab for Advanced Energy TechnologySchool of Materials Science and EngineeringShaanxi Normal UniversityXi'an 710119ShaanxiChina State Key Laboratory of Catalysis Dalian National Laboratory for Clean EnergyDalian Institute of Chemical PhysicsChinese Academy of SciencesDalian 116023LiaoningChina

Metal-halide hybrid perovskite materials are excellent candidates for solar cells and photoelectric *** recent years,machine learning(ML)techniques have developed rapidly in many fields and provided ideas for material discovery and *** can be applied to discover new materials quickly and effectively,with significant savings in resources and time compared with traditional experiments and density functional theory(DFT)*** this review,we present the application of ML in per-ovskites and briefly review the recent works in the field of ML-assisted perovskite ***,the advantages of perovskites in solar cells and the merits of ML applied to perovskites are ***,the workflow of ML in perovskite design and some basic ML algorithms are ***,the applications of ML in predicting various properties of perovskite materials and devices are ***,we propose some prospects for the future development of this *** rapid devel-opment of ML technology will largely promote the process of materials science,and ML will become an increasingly popular method for predicting the target properties of materials and devices.

关键词： Machine learning Perovskite Materials design Bandgap engineering Stability Crystal structure

Hepatocellular Ballooning is due to Highly Pronounced Glycogenosis Potentially Associated with Steatosis and Metabolic Reprogramming

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Journal of Clinical and Translational Hepatology 2024年第1期12卷 52-61页

作者： Silvia Ribback Kristin Peters Mohd Yasser Jessica Prey Paula Wilhelmi Qin Su frank Dombrowski Peter Bannasch Institut für Pathologie Universitaetsmedizin GreifswaldGreifswaldGermany Cell Marque Millipore-SigmaRocklinCAUSA German Cancer Research Center(DKFZ) HeidelbergGermany

Background and Aims:Hepatocellular ballooning is a common finding in chronic liver disease,mainly characterized by rarefied cytoplasm that often contains Mallory-Denk bodies(MDB).Ballooning has mostly been attributed to degeneration but its striking resemblance to glycogenotic/steatotic changes characterizing preneoplastic hepatocellular lesions in animal models and chronic human liver diseases prompts the question whether ballooned hepatocytes(BH)are damaged cells on the path to death or rather viable cells,possibly involved in neoplastic ***:Using specimens from 96 cirrhotic human livers,BH characteristics were assessed for their glycogen/lipid stores,enzyme activities,and proto-oncogenic signaling cascades by enzyme-and immunohistochemical approaches with serial paraffin and cryostat ***:BH were present in 43.8%of cirrhotic *** pronounced excess glycogen storage of(glycogenosis)and/or lipids(steatosis)were characteristic,ground glass features and MDB were often *** glucose-6-phosphatase,increased glucose-6-phosphate dehydrogenase activity and altered immunoreactivity of enzymes involved in glycolysis,lipid metabolism,and cholesterol biosynthesis were ***,components of the insulin signaling cascade were upregulated along with insulin dependent glucose transporter glucose transporter 4 and the v-akt murine thymoma viral oncogene homolog/mammalian target of rapamycin signaling pathway associated with de novo ***:BH are hallmarked by particularly pronounced glycogenosis with facultative steatosis,many of their features being reminiscent of metabolic aberrations documented in preneoplastic hepatocellular lesions in experimental animals and chronic human liver ***,BH are not damaged entities facing death but rather viable cells featuring metabolic reprogramming,indicative of a preneoplastic nature.

关键词： Chronic liver disease Carbohydrate metabolism Insulin signaling Preneoplasia Metabolic reprogramming

Magnificent Frigatebird Optimization: A New Bio-Inspired Metaheuristic Approach for Solving Optimization Problems

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Computers, Materials & Continua 2024年第8期80卷 2721-2741页

作者： Tareq Hamadneh Khalid Kaabneh Ibraheem AbuFalahah Gulnara Bektemyssova Galymzhan Shaikemelev Dauren Umutkulov Sayan Omarov Zeinab Monrazeri frank Werner Mohammad Dehghani Department of Mathematics Al Zaytoonah University of JordanAmman11733Jordan Faculty of Information Technology Al-Ahliyya Amman UniversityAmman19328Jordan Department of Mathematics Faculty of ScienceThe Hashemite UniversityP.O.Box 330127Zarqa13133Jordan Department of Computer Engineering International Information Technology UniversityAlmaty050000Kazakhstan Department of Big Data Analytics and Data Science Software Development Company《QazCode》Almaty050063Kazakhstan Department of Electrical and Electronics Engineering Shiraz University of TechnologyShiraz***Iran Faculty of Mathematics Otto-von-Guericke UniversityP.O.Box 4120Magdeburg39016Germany

This paper introduces a groundbreaking metaheuristic algorithm named Magnificent Frigatebird Optimization(MFO),inspired by the unique behaviors observed in magnificent frigatebirds in their natural *** foundation of MFO is based on the kleptoparasitic behavior of these birds,where they steal prey from other *** this process,a magnificent frigatebird targets a food-carrying seabird,aggressively pecking at it until the seabird drops its *** frigatebird then swiftly dives to capture the abandoned prey before it falls into the *** theoretical framework of MFO is thoroughly detailed and mathematically represented,mimicking the frigatebird’s kleptoparasitic behavior in two distinct phases:exploration and *** the exploration phase,the algorithm searches for new potential solutions across a broad area,akin to the frigatebird scouting for vulnerable *** the exploitation phase,the algorithm fine-tunes the solutions,similar to the frigatebird focusing on a single target to secure its *** evaluate MFO’s performance,the algorithm is tested on twenty-three standard benchmark functions,including unimodal,high-dimensional multimodal,and fixed-dimensional multimodal *** results from these evaluations highlight MFO’s proficiency in balancing exploration and exploitation throughout the optimization *** studies with twelve well-known metaheuristic algo-rithms demonstrate that MFO consistently achieves superior optimization results,outperforming its competitors across various *** addition,the implementation of MFO on four engineering design problems shows the effectiveness of the proposed approach in handling real-world applications,thereby validating its practical utility and robustness.

关键词： Optimization metaheuristic magnificent frigatebirds exploration exploitation

Optimization of Methylene Blue Dye Adsorption onto Coconut Husk Cellulose Using Response Surface Methodology: Adsorption Kinetics, Isotherms and Reusability Studies

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Journal of Materials Science and Chemical Engineering 2024年第2期12卷 1-18页

作者： frank Ouru Omwoyo Geoffrey Otieno School of Chemistry and Material Science Technical University of Kenya Nairobi Kenya

In this study, coconut husk cellulose was employed as a cost-effective and environmentally friendly adsorbent to eliminate methylene blue (MB) dye from aqueous solutions. The successful development of response surface methodology paired with a central composite design (RSM-CCD) enabled the optimization and modelling of the adsorption process. The study investigated the individual and combined effects of three variables (pH, contact time, and initial MB dye concentration) on the adsorption of MB dye onto coconut husk cellulose. The developed RSM-CCD model exhibited a remarkable degree of precision in predicting the removal efficiency of MB dye within the specified experimental parameters. This was demonstrated by the strong regression parameters, with an R2 value of 99.79% and an adjusted R2 value of 99.6%. The study depicted that the optimal parameters for attaining a 98.8827% removal of MB dye using coconut husk cellulose were as follows: an initial MB dye concentration of 30 mg∙L−1, contact time of 120 minutes, and pH 7 at a fixed adsorbent dose of 0.5 g. The Freundlich isotherm model provided the most satisfactory description of the equilibrium adsorption isotherms, suggesting that MB dye adsorption onto coconut husk cellulose occurs on a heterogeneous surface. The experimental results demonstrated a strong agreement with the pseudo-second-order kinetics model, indicating that the number of active sites present on the cellulose adsorbent predominantly influences the adsorption process of MB dye. Additionally, the adsorbent made from coconut husk cellulose exhibited the potential to be reused, as it retained its efficiency for a maximum of three cycles of adsorption of MB dye. The results of this study show that coconut husk cellulose has the potential to be an effective and sustainable adsorbent for removing MB dye from aqueous solutions.

关键词： Adsorption Kinetics Isotherms Optimization Response Surface Methodology Cellulose

Construction Activity Analysis of Workers Based on Human Posture Estimation Information

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Engineering 2024年第2期33卷 225-236页

作者： Xuhong Zhou Shuai Li Jiepeng Liu Zhou Wu Yohchia frank Chen School of Civil Engineering Chongqing UniversityChongqing 400044China School of Automation Chongqing UniversityChongqing 400044China Department of Civil Engineering The Pennsylvania State UniversityMiddletownPA 17057USA

Identifying workers’construction activities or behaviors can enable managers to better monitor labor efficiency and construction ***,current activity analysis methods for construction workers rely solely on manual observations and recordings,which consumes considerable time and has high labor *** have focused on monitoring on-site construction activities of ***,when multiple workers are working together,current research cannot accu rately and automatically identify the construction *** research proposes a deep learning framework for the automated analysis of the construction activities of multiple *** this framework,multiple deep neural network models are designed and used to complete worker key point extraction,worker tracking,and worker construction activity *** designed framework was tested at an actual construction site,and activity recognition for multiple workers was performed,indicating the feasibility of the framework for the automated monitoring of work efficiency.

关键词： Pose estimation Activity analysis Object tracking Construction workers Automatic systems

Decoding complexity: the need to enhance precision and streamline spatial understanding in neuroscience

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Neural Regeneration Research 2025年第3期20卷 801-802页

作者： Sameehan Mahajani Armita Salahi Brenda Gonzalez Charlotte Nelson frank Hsiung Biology&Applications Division NodexusSan JoseCAUSA

Neuroscience is the ultimate frontier in our quest for a comprehensive understanding of human behavior. Since its launch in 2009, the Human Connectome Project has emerged as a pioneering force, making heroic strides i... 详细信息

关键词： behavior frontier dating

Physics-constrained graph modeling for building thermal dynamics

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Energy and AI 2024年第2期16卷 150-157页

作者： Ziyao Yang Amol D.Gaidhane Ján Drgoňa Vikas Chandan Mahantesh M.Halappanavar frank Liu Yu Cao School of Electrical Computer and Energy EngineeringArizona State UniversityTempeAZ 85287USA Pacific Northwest National Laboratory RichlandWA 99354USA Oak Ridge National Laboratory Oak RidgeTN 37830USA

In this paper,we propose a graph model embedded with compact physical equations for modeling the thermal dynamics of *** principles of heat flow across various components in the building,such as walls and doors,fit the message-passing strategy used by Graph Neural networks(GNNs).The proposed method is to represent the multi-zone building as a graph,in which only zones are considered as nodes,and any heat flow between zones is modeled as an edge based on prior knowledge of the building ***,the thermal dynamics of these components are described by compact models in the *** are further employed to train model parameters from collected *** model training,our proposed method enforces physical constraints(e.g.,zone sizes and connections)on model parameters and propagates the penalty in the loss function of *** constraints are essential to ensure model robustness and *** evaluate the effectiveness of the proposed modeling approach on a realistic dataset with multiple *** results demonstrate a satisfactory accuracy in the prediction of multi-zone ***,we illustrate that the new model can reliably learn hidden physical parameters with incomplete data.

关键词： Physics-constrained learning Graph Neural Networks Compact model Building thermal dynamics