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Investigating the sensitivity of nanofluid flow around a cylindrical disk: A study of Walter's B nanofluid using response surface methodology and artificial neural networks

Journal of Engineering Research (Kuwait)

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Journal of Engineering Research (Kuwait) 2025年

作者： Shafiq, Anum Çolak, Andaç Batur Sindhu, Tabassum Naz Abushal, Tahani A. School of Mathematics and Statistics Nanjing University of Information Science and Technology Nanjing 210044 China Jiangsu International Joint Laboratory on System Modeling and Data Analysis Nanjing University of Information Science and Technology Nanjing 210044 China Department of Information Systems and Technologies Niğde Ömer Halisdemir University Niğde 51240 United States Department of Statistics Quaid-I-Azam University Islamabad 44000 Pakistan Department of Mathematical Sciences Umm Al-Qura University Makkah 24382 Saudi Arabia

Modern technology development heavily relies on nanotechnology, which has gained significant attention from researchers in recent years, particularly in finding ways to enhance heat transfer rates. One approach to addressing this issue is to use nanoparticles in host fluids to greatly improve their thermal properties. This study employed response surface methods to investigate the Walter's B nanofluid, incorporating thermophoresis, Brownian diffusion, activation energy, and thermal radiation, using the Buongiorno model to examine nanofluid properties. To reduce the formed system of flow equations into a dimensionless differential form system, appropriate variables were used. In addition, we build a dataset for the proposed multilayer perceptron neural network using the Runge-Kutta fourth-order shooting method. The study analyzed effects of flow variables on the velocity field, temperature field, and species volumetric concentration fields, and probable error correlation coefficients were calculated to evaluate the statistical significance of the parameters. Additionally, a sensitivity analysis was conducted, which showed that with a high thermophoresis number, the Nusselt number is more sensitive. © 2024 The Authors

关键词： Artificial neural networks Brownian motion Response surface methodology (RSM) Sensitivity analysis Thermophoresis Walter's B nanofluid

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Optimal Harvest for Predator-Prey Fishery Models with Variable Price and Marine Protected Area

SSRN

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SSRN 2023年

作者： Chu, Cheng Liu, Wenjun Lv, Guangying Auger, Pierre Moussaoui, Ali School of Mathematics and Statistics Nanjing University of Information Science and Technology Nanjing210044 China Jiangsu International Joint Laboratory on System Modeling and Data Analysis Center for Applied Mathematics of Jiangsu Province Nanjing University of Information Science and Technology Nanjing210044 China UMMISCO Sorbonne Université Institut de Recherche pour le Développement IRD BondyF-93143 France Laboratoire d’Analyse Non Linéaire et Mathématiques Appliquées Department of Mathematics Faculty of Science University of Tlemcen 13000 Algeria

In this paper, we propose a predator-prey fishery model with prey harvesting, variable price and marine protected area. We assume the price changes faster than other processes such as population growth and predation, and get a slow fast ODE system. A simplified three-dimensional model is obtained by using approximate aggregation methods. The results show that there are two main scenarios, one is the depletion of fish stocks due to overfishing by fishermen, which is called a catastrophic equilibrium;and the other is a stable and sustainable fishery equilibrium. In order to avoid the extinction of fish, we consider establishing marine protected area (MPA) near fishing areas where fishermen only catch the prey. The results of the study provide the conditions for the establishment of MPA, allowing us to avoid the extinction of prey populations and establish sustainable fisheries. As another possibility, we consider increasing taxes to discourage overfishing by fishermen. In addition, when the tax revenue increases, the optimal harvest strategy is obtained. The optimal policy ensures the sustainable development of fisheries and maximizes the interests of fishermen. © 2023, The Authors. All rights reserved.

关键词： Fisheries

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Sustainable Management of Predatory Fish Affected by an Allee Effect Through Marine Protected Areas Andtaxation

SSRN

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SSRN 2023年

作者： Yuan, Xiaoyue Liu, Wenjun Lv, Guangying Auger, Pierre Moussaoui, Ali School of Mathematics and Statistics Nanjing University of Information Science and Technology Nanjing210044 China Jiangsu International Joint Laboratory on System Modeling and Data Analysis Center for Applied Mathematics of Jiangsu Province Nanjing University of Information Science and Technology Nanjing210044 China UMMISCO Sorbonne Université Institut de Recherche pour le Développement IRD BondyF-93143 France Laboratoire d’Analyse Non Linéaire et Mathématiques Appliquées Department of Mathematics Faculty of Science University of Tlemcen Tlemcen13000 Algeria

In this work, we present a prey-predator model of marine community with predator harvesting in an environment made up of two sites connected by fast migrations of prey and predator. We assume that the prey grows logistically at each site, and further hypothesize that the growth of predators obeys an Allee effect in the absence of prey. The model takes into account the variation in the price of the resource under the effect of supply and demand. We use methods of aggregation of variables to derive a three-dimensional simplified model that governs prey fish biomass, predator biomass and fishing effort of the fishery. We study the effects of the installation of a marine protected area as well as taxation per unit of catch on the dynamics of the fishery in the long term. We seek conditions to avoid the extinction of species and maintain sustainable fishing activity. We carry out the analysis of the reduced model, consider the existence of positive equilibrium points, and look for the local and global stability. Our numerical simulations of the model with marine protected area show that it can protect fish stocks and notably avoid predator extinction. In addition, we consider the effect of a tax per unit of catch with the aim of limiting overfishing. We obtain the best tax policy by applying Pontryagin’s maximum principle with the aim of ensuring a good balance allowing the maintenance of the ecological community and sustainable economic development. © 2023, The Authors. All rights reserved.

关键词： Fisheries

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Statistical and entropy optimization modeling for radiative hybrid nanofluid flow with Hall effect over exponential stretching/shrinking plate

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international Journal of Thermofluids 2023年 20卷

作者： Jameel, Muhammad Shah, Zahir Shafiq, Anum Rooman, Muhammad Vrinceanu, Narcisa Alshehri, Ahmed Islam, Saeed Department of Mathematical Sciences University of Lakki Marwat Lakki Marwat Khyber Pakhtunkhwa28420 Pakistan School of Mathematics and Statistics Nanjing University of Information Science and Technology Nanjing210044 China Faculty of Engineering Department of Industrial Machines and Equipments "Lucian Blaga" University of Sibiu 10 Victoriei Boulevard Romania Department of Mathematics Faculty of Sciences King Abdulaziz University Jeddah21589 Saudi Arabia Department of Mathematics Abdul Wali Khan University Mardan 23200 Khyber Pakhtunkhwa Pakistan Jiangsu International Joint Laboratory on System Modeling and Data Analysis Nanjing University of Information Science and Technology Nanjing210044 China

Scientists have become intrigued by the capacity of two solid components to dissolve in a conventional fluid to enhance the thermal efficiency of novel hybrid nanofluids. The Bejan number and entropy formation of three-dimensional hybrid Al2O3 − Cu/H2O nanoparticles flowing via a stretching/shrinking bidirectional exponential plate are investigated in this research while taking into account thermal radiation and the Hall Effect. In the heat equation, the Joule heating and Cattaneo-Christov heat flux model are contemplated. Through using proper similarity transformations, equations involving momentum and heat transfer are simplified into ordinary differential equations. The Homotopy analysis approach is used to solve these equations using the computer software MATHEMATICA. By resolving the flow limitations on temperature and velocity, the entropy production is computed. Using graphical demonstration, the impact of various parameters such as suction/injection parameter, Brinkman number, magnetic parameter, stretching/shrinking parameter, temperature ratio parameter on flow, thermal relaxation parameter, temperature exponent parameter, Hall effect parameter, on velocity, temperature, entropy production, and Bejan number has been thoroughly discussed. The local Nusselt number and skin friction can also be identified for practical reasons for various approximations of physical parameters. The outcomes specify that the tangential velocity and redial velocity decrease for greater values of injection and suction parameters. The temperature profile falls for larger values of the suction parameter and rises for greater values of the thermal relaxation parameter and injection parameter. Entropy production develops when the magnetic parameter is improved. Bejan number was reduced in response to rising magnetic parameter values. © 2023 The Author(s)

关键词： Joule heating

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Brain MRIs classification based on 2D SWD-MF-DFA

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Journal of Neuroscience Methods 2025年 421卷 110468页

作者： Wang, Jing Wu, Xinpei Wang, Haozhe Wang, Jian School of Mathematics and Statistics Nanjing University of Information Science and Technology Nanjing 210044 China Reading Academy Nanjing University of Information Science and Technology Nanjing 210044 China Center for Applied Mathematics of Jiangsu Province Nanjing University of Information Science and Technology Nanjing 210044 China Jiangsu International Joint Laboratory on System Modeling and Data Analysis Nanjing University of Information Science and Technology Nanjing 210044 China

Background: To improve imaging classification accuracy, we modify the traditional 2D multifractal trend fluctuation analysis (MF-DFA) method to better preserve local feature values. Inspired by MF-DFA, we develop a novel method for extracting eigenvalues, enhancing the precision of imaging analysis. New method: In this paper, we propose an enhanced algorithm building upon the traditional 2D MF-DFA. Our approach introduces a 2D sliding window (SWD) technique for feature value extraction. Initially, the local generalized Hurst index of the imaging is derived using the SWD algorithm, based on MF-DFA principles. Subsequently, the generalized Hurst index is recalculated for the digital matrix formed by these local Hurst indexes. These vectors are then input into a support vector machine (SVM) for classification. This methodology seeks to refine the traditional 2D MF-DFA by more effectively preserving local feature values in imaging. Results: The classification accuracy of the SWD eigenvalue extraction method based on 2D MF-DFA reaches 91.54%. Comparison with existing methods: We employ brain magnetic resonance imaging (MRI) data sets to evaluate the efficacy of both the conventional 2D MF-DFA method and our proposed feature value extraction technique. Both methods are applied alongside a SVM for classification. The findings reveal that the conventional 2D MF-DFA method yields a classification accuracy of 59.40%, while our SWD feature value extraction method attains a classification accuracy of 91.54%. Conclusion: This substantial performance enhancement underscores the superiority of the SWD approach over the conventional method. © 2025 Elsevier B.V.

关键词： 2D MF-DFA 2D SWD MRI SVM

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Skill Assessment of North American Multi-Models Ensemble (NMME) for June-September (JJAS) Seasonal Rainfall over Ethiopia

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Atmospheric and Climate Sciences 2022年第1期12卷 54-73页

作者： Asaminew Teshome Jie Zhang Qianrong Ma Stephen E. Zebiak Teferi Demissie Tufa Dinku Asher Siebert Jemal Seid Nachiketa Acharya National Meteorological Agency of Ethiopia Addis Ababa Ethiopia Key Laboratory of Meteorological Disaster Ministry of Education (KLME)/International Joint Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD) Nanjing University of Information Science & Technology (NUIST) Nanjing China International Research Institute for Climate and Society (IRI) The Earth Institute Columbia University New York USA NORCE Norwegian Research Center Bjerknes Center for Climate Research Bergen Norway CGIAR Research Program on Climate Change Agriculture and Food Security (CCAFS) East Africa Addis Ababa Ethiopia Ethiopian Institute of Agricultural Research Addis Ababa Ethiopia Scuola Superiore Sant’Anna Pisa Italy Center for Earth System Modeling Analysis and Data Department of Meteorology and Atmospheric Science Pennsylvania State University University Park PA USA

In recent years, there has been increasing demand for high-resolution seasonal climate forecasts at sufficient lead times to allow response planning from users in agriculture, hydrology, disaster risk management, and health, among others. This paper examines the forecasting skill of the North American Multi-model Ensemble (NMME) over Ethiopia during the June to September (JJAS) season. The NMME, one of the multi-model seasonal forecasting systems, regularly generates monthly seasonal rainfall forecasts over the globe with 0.5 - 11.5 months lead time. The skill and predictability of seasonal rainfall are assessed using 28 years of hindcast data from the NMME models. The forecast skill is quantified using canonical correlation analysis (CCA) and root mean square error. The results show that the NMME models capture the JJAS seasonal rainfall over central, northern, and northeastern parts of Ethiopia while exhibiting weak or limited skill across western and southwestern Ethiopia. The performance of each model in predicting the JJAS seasonal rainfall is variable, showing greater skill in predicting dry conditions. Overall, the performance of the multi-model ensemble was not consistently better than any single ensemble member. The correlation of observed and predicted seasonal rainfall for the better performing models—GFDL-CM2p5-FLOR-A06, CMC2-CanCM4, GFDL-CM2p5-FLOR-B01 and NASA-GMAO-062012—is 0.68, 0.58, 0.52, and 0.5, respectively. The COLA-RSMAS-CCSM4, CMC1- CanCM3 and NCEP-CFSv2 models exhibit less skill, with correlations less than 0.4. In general, the NMME offers

关键词： Ethiopia Ensemble June-September Correlation Coefficient Skill

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INTRODUCTION

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Bulletin of the American Meteorological Society 2024年第8期105卷 S1-S11页

作者： Boyer, T. Blunden, J. Dunn, R.J.H. NOAA/NESDIS National Centers for Environmental Information Silver Spring Maryland NOAA/NESDIS National Centers for Environmental Information Asheville North Carolina Met Office Hadley Centre Exeter United Kingdom European Centre for Medium-Range Weather Forecasts Reading United Kingdom University of Maryland College Park Maryland Scripps Institution of Oceanography University of California San Diego La Jolla California NOAA/NWS National Centers for Environmental Prediction Climate Prediction Center College Park Maryland Brandenburg University of Technology (BTU) Cottbus-Senftenberg Germany Servicio Meteorológico Nacional Buenos Aires Argentina NOAA/OAR Physical Sciences Laboratory Boulder Colorado European Centre for Medium-Range Weather Forecasts Bonn Germany Center for Geophysical Research and School of Physics University of Costa Rica San José Costa Rica Department of Meteorology and National Centre for Earth Observation University of Reading Reading United Kingdom Centro Nacional de Monitoramento e Alertas de Desastres Naturais CEMADEN São Paulo Brazil Université Grenoble Alpes Institut des Géosciences de l’Environnement IRD CNRS Grenoble INP Grenoble France Hampton University Hampton Virginia Seychelles Meteorological Authority Mahe Seychelles Section for Glaciers Ice and Snow Norwegian Water Resources and Energy Directorate Oslo Norway National Research Institute for Agriculture Food and Environment (INRAE) CARRTEL Université Savoie Mont Blanc Thonon les Bains France Graduate School of Agriculture Osaka Metropolitan University Sakai Japan Science Faculty Universidad Nacional de Colombia Bogotá Colombia University of Bremen Bremen Germany NOAA Global Monitoring Laboratory Boulder Colorado Servicio Nacional de Meteorología e Hidrología del Perú Lima Perú Centro de Investigaciones sobre Desertificación – Spanish National Research Council (CSIC-UV-GVA) Valencia Spain Hydro-Climate Extremes Lab (H-CEL) Ghent University Ghent Belgium Department o

In 2023, La Niña conditions that generally prevailed in the eastern Pacific Ocean from mid-2020 into early 2023 gave way to a strong El Niño by October. Atmospheric concentrations of Earth’s major greenhouse gases—carbon dioxide, methane, and nitrous oxide—all increased to record-high levels. The annual global average carbon dioxide concentration in the atmosphere rose to 419.3±0.1 ppm, which is 50% greater than the pre-industrial level. The growth from 2022 to 2023 was 2.8 ppm, the fourth highest in the record since the 1960s. The combined short-term effects of El Niño and the long-term effects of increasing levels of heat-trapping gases in the atmosphere contributed to new records for many essential climate variables reported here. The annual global temperature across land and oceans was the highest in records dating as far back as 1850, with the last seven months (June–December) having each been record warm. Over land, the globally averaged temperature was also record high. Dozens of countries reported record or near-record warmth for the year, including China and continental Europe as a whole (warmest on record), India and Russia (second warmest), and Canada (third warmest). Intense and widespread heatwaves were reported around the world. In Vietnam, an all-time national maximum temperature record of 44.2°C was observed at Tuong Duong on 7 May, surpassing the previous record of 43.4°C at Huong Khe on 20 April 2019. In Brazil, the air temperature reached 44.8°C in Araçuaí in Minas Gerais on 20 November, potentially a new national record and 12.8°C above normal. The effect of rising temperatures was apparent in the cryosphere, where snow cover extent by June 2023 was the smallest in the 56-year record for North America and seventh smallest for the Northern Hemisphere overall. Heatwaves contributed to the greatest average mass balance loss for Alpine glaciers around the world since the start of the record in 1970. Due to rapid volume loss beginning in 2021, St. A

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TEST OF CLOSED-LOOP DEGAUSSING ALGORITHM ON A MINESWEEPER ENGINE

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NAVAL ENGINEERS JOURNAL 1992年第3期104卷 219-227页

作者： WINGO, RA HOLMES, JJ LACKEY, MH Robert A. Wingo:is a technical specialist electrical engineer in the Protection Systems Department of the Naval Surface Warfare Center. During his 10 years at NSWC he has been a leader in the development and analysis of systems for the measurement and reduction of static magnetic signatures of mine counter measures vessels and steel hull ships. He currently holds the position of lead scientist of the Engineering Group for the joint U.S.-France Closed-Loop Degaussing Program. His responsibilities have included theory and modeling of static-magnetic fields closed-loop degaussing systems development and implementation scale and full-scale experimentation and the development of fleet magnetic signature measurement facilities. He holds a BSEE degree from Virginia Polytechnic Institute and has published several papers on various topics in magnetic silencing and closed-loop degaussing systems. John J. Holmes:is a principal electrical engineer in the Protection Systems Department of the Naval Surface Warfare Center. Dr. Holmes has been with NSWC for 14 years. During this time he has participated in and technically directed the development of several submarine and surface ship magnetic and electric silencing systems in the ULF (0 to 3 hz) and ELF (3 hz to 3 khz) band. His responsibilities have included threat and vulnerability studies theory and modeling of electromagnetic fields countermeasure systems development scale and full-scale experimentation and data analysis and the development of standards for countermeasure system performance testing and evaluation. He has published over fifty papers on various topics in magnetic silencing and electromagnetic theory. In addition he has participated in several international electromagnetic silencing R&D programs and is a member of the NATO Mine Warfare Working Party. Milton H. Lackey:is a senior physicist in the Protection Systems Department of the Naval Surface Warfare Center. He is currently director of the Center's Magnetic Ship Models Laboratory. During his 30-ye

A closed-loop degaussing technique for MCM (mine countermeasure) class vessels has been developed and tested on a minesweeper engine. The system was designed to accurately predict and degauss the off-board magnetic field signatures from measurements taken on-board a non-magnetic hull naval signature prediction algorithm have been investigated. An on-board sensor configuration, that requires only four single axis gradiometers, has been shown to accurately predict the magnetic signatures of the full-scale engine.

关键词： Warships

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