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ANN-based analysis of thin film Maxwell fluid dynamics with electro-osmotic and nonlinear thermal effects

Alexandria engineering Journal 2025年 127卷 392-410页

作者： Din, Irfan Saif Ud Siddique, Imran Zahid, Zohaib Nadeem, Muhammad Islam, S. Department of Mathematics University of Management and Technology Lahore54770 Pakistan Department of Mathematics University of Sargodha Sargodha40100 Pakistan Mathematics in Applied Sciences and Engineering Research Group Scientific Research Center Al-Ayen University Nasiriyah64001 Iraq Federal University of Technology Paran UTFPR Mechanical Engineering Department DAMEC Postgraduate Program in Mechanical and Materials Engineering PPGEM Research Center for Rheology and Non-Newtonian Fluids CERNN R. Deputado Heitor Alencar Furtado 5000 - Bloco N - Ecoville PR Curitiba81280-340 Brazil Department of Mechanical Engineering Prince Mohammad Bin Fahd University P.O Box 1664 Al Khobar31952 Saudi Arabia

An intelligent Levenberg-Marquardt Technique (LMT) with artificial neural network (ANN) backpropagation (BP) has been used to analyze the thermal heat and mass transfer of unsteady magnetohydrodynamics (MHD) thin film Maxwell fluid flow in a porous inclined sheet with an emphasis on the influence of electro-osmosis. The activation energy, chemical reaction, mixed convection, melting heat, joule heating, nonlinear thermal radiation, variable thermal conductivity and thermal source/sink effect are taken into account for transport expressions. Appropriate similarity transformations were used to translate partial differential equations (PDEs) into ordinary differential equations (ODEs). After that, the built-in MATLAB BVP4C method was used for a data set assessed using the LMT-ANN strategy to solve these ODEs. The physical significance of the designed parameters is thoroughly discussed in both tabular and graphical form. The observed R-squared value is 1, and the mean square error up to 10−15 demonstrates the LMT-ANN's precise and accurate computing capability. The model's validity is also confirmed by the strong agreement between the obtained predicted findings and numerical results, which shows a high degree of accuracy within the range of 10−8 to 10−11. It was revealed that radiative heat considerably increases surface heat energy through accumulation, improving heat transfer qualities, whereas fluid temperature is raised by Joule dissipation, variable thermal conductivity, and heat source. Electro-osmosis and magnetic fields reduce fluid velocity by generating opposing forces that resist the flow. This problem works best in microscale fluid transport systems and drilling operations, where magnetic and electro-osmotic control are crucial. These systems include micro-electromechanical systems, lab-on-a-chip devices, porous geological formations, and thin film coating technologies. © 2025 The Authors

关键词： Activation energy

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Inner approximations of convex sets and intersections of projectionally exposed cones

arXiv

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arXiv 2025年

作者： Lourenço, Bruno F. Roshchina, Vera Saunderson, James Department of Fundamental Statistical Mathematics Institute of Statistical Mathematics Japan School of Mathematics and Statistics UNSW Sydney Australia Department of Electrical and Computer Systems Engineering Monash University Australia

A convex cone is said to be projectionally exposed (p-exposed) if every face arises as a projection of the original cone. It is known that, in dimension at most four, the intersection of two p-exposed cones is again p-exposed. In this paper we construct two p-exposed cones in dimension 5 whose intersection is not p-exposed. This construction also leads to the first example of an amenable cone that is not projectionally exposed, showing that these properties, which coincide in dimension at most 4, are distinct in dimension 5. In order to achieve these goals, we develop a new technique for constructing arbitrarily tight inner convex approximations of compact convex sets with desired facial structure. These inner approximations have the property that all proper faces are extreme points, with the exception of a specific exposed face of the original set. Copyright © 2025, The Authors. All rights reserved.

关键词： Cones

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Do Not Skip Over the Offline: Verifiable Silent Preprocessing From Small Security Hardware

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IEEE Transactions on Information Forensics and Security 2025年 20卷 4860-4873页

作者： Dong, Wentao Xu, Lei Zheng, Leqian Duan, Huayi Wang, Cong Wang, Qian City University of Hong Kong Department of Computer Science Kowloon Tong Hong Kong Nanjing University of Science and Technology School of Mathematics and Statistics Nanjing210094 China ETH Zürich Department of Computer Science Zürich8092 Switzerland Wuhan University School of Cyber Science and Engineering Wuhan430072 China

Multi-party computation (MPC) has gained increasing attention in both research and industry, with many protocols adopting the preprocessing model to optimize online performance through the strategic use of offline-generated, data-independent correlated randomness (or correlation). However, while extensive research has been dedicated to enhancing the online phase, the equally critical offline phase remains largely overlooked. This gap imposes significant yet unaddressed challenges in both security and efficiency, hindering the practical adoption of MPC systems. To address these challenges, we build upon the pseudorandom correlation generator (PCG) concept by Boyle et al. (CRYPTO’19, FOCS’20) and propose HPCG, a programmable, verifiable, and concretely efficient PCG construction using small security hardware. Our core technique, termed verifiable silent preprocessing, enables virtually unbounded, on-demand generation of diverse correlated randomness with provable correctness while effectively reducing offline overhead in a correlation-agnostic manner. To demonstrate the benefits of our approach, we experimentally evaluate HPCG and compare it with other preprocessing techniques. We also show how HPCG can further optimize specialized secure computation tasks (e.g., shuffling and equality test) by promoting new, customized correlations, which may be of new interest. © 2005-2012 IEEE.

关键词： Digital storage

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Repurposing Abandoned Offshore Oil Wells for Geothermal Energy by Numerical Analyses

Repurposing Abandoned Offshore Oil Wells for Geothermal Ener...

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Offshore Technology Conference, OTC 2025

作者： Zuo, Lihua Luo, Ning Department of Mathematics and Statistics Texas A&M University-Corpus Christi Corpus ChristiTX United States Department of Civil Engineering Texas A&M University-Corpus Christi Corpus ChristiTX United States

ISBN: (纸本)9781959025610

Due to the consideration of cost of maintaining a well production, the abandoned wells in Gulf of Mexico are getting more and more, so there are more needs to repurpose these abandoned wells as storage of carbons, waste or as geothermal resources. In this study, one offshore platform in Alaminos Canyon area is chosen for potential use of geothermal energy production. A numerical model is designed to simulate the fluid transport for horizontally drilled wells with existence of hydraulic fractures. The temperature profile of the geothermal fluid is calculated and different mechanisms for the fluid and surrounding rocks are investigated. In the end, the possible production plan is proposed. The results of this study could shed light on the possibility of repurposing abandoned offshore wells for geothermal energy. © 2025, Offshore Technology Conference.

关键词： Hot dry rock systems

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Mathematical Modelling for Community Based Intervention for Managing Diabetes: A Systematic Literature Review

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Journal of Multidisciplinary Healthcare 2025年 18卷 2429-2440页

作者： Irawan, Aalbrecht A. Anggriani, Nursanti Andriyana, Yudhie Abdulah, Rizky Doctoral Program in Mathematics Faculty of Mathematics and Natural Science Universitas Padjadjaran Jatinangor West Java Indonesia Department of Mathematics Faculty of Mathematics and Natural Science Universitas Padjadjaran Jatinangor West Java Indonesia Department of Statistics Faculty of Mathematics and Natural Science Universitas Padjadjaran Jatinangor West Java Indonesia Department of Pharmacology and Clinical Pharmacy Faculty of Pharmacy Universitas Padjadjaran Jatinangor West Java Indonesia

Diabetes mellitus (DM) poses a significant global health and economic challenge. Effective diabetes management requires a multifaceted approach that combines clinical and community-based interventions. Community-based interventions are critical to address the growing burden of diabetes. Despite numerous independent studies on community-based interventions for T2DM management and mathematical models, there has been no comprehensive review integrating these two domains. This systematic literature review aimed to fill this gap by examining mathematical modelling in the context of community-based interventions for T2DM management. Following the PRISMA guidelines, relevant articles were identified, screened, and assessed for eligibility using the Scopus, ScienceDirect, and PubMed databases. The inclusion criterion was English-language research articles published between 2014 and 2024 that focused on T2DM interventions using mathematical models. Seven articles met the final inclusion criteria and were analysed to answer research questions related to the geographical origin of the data, nature of the intervention, specific mathematical model used, and the main findings of the primary study. This review highlights that mathematical models are critical for optimising community-based interventions, by identifying key risk factors, predicting disease progression, and evaluating the effectiveness of various treatments. By synthesising findings from different geographical and economic contexts, this review highlights the importance of culturally and contextually relevant strategies for diabetes management. The integration of robust mathematical models with community-based approaches promises to develop more effective evidence-based strategies for diabetes management, particularly in resource-limited settings. © 2025 Irawan et al.

关键词： community-based intervention diabetes mellitus type 2 mathematical model

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Machine Learning and Time Series Approaches for Stock Price Prediction: A Case Study of Indian Banks

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Procedia Computer Science 2025年 260卷 626-634页

作者： Tiya Chaudhary Minirani S Nilkamal School of Mathematics Applied Statistics and Analytics (NSOMASA) NMIMS University Mumbai – 400056 Department of Mathematics Mukesh Patel School Of Technology Management and Engineering NMIMS University Mumbai-400056

The Finance sector plays an important role in the economy of any country. With increased recognition of the stock market and its importance in the economy, correct investments and portfolio management has been the top priority in this sector. With the introduction of machine learning and time series models this has been easier. This research paper focuses on the comparative analysis of three most used machine learning and time series models namely Autoregressive Integrated Moving Average (ARIMA), Seasonal Autoregressive Integrated Moving Average (SARIMA) and Long Term Short Term Memory (LSTM) in predicting the stock prices of the Indian Banks namely ICICI Bank, IndusInd Bank, State Bank Of India, Kotak Mahindra Bank, HDFC Bank and Axis Bank using efficient and time saving means. Each models’ accuracy is evaluated using error metrics like Root Mean Square Error, Mean Squared Error and Mean Absolute Error. The findings aim to provide an insight about the most preferred model in this field and also help financial analysts and investors to make the correct decisions while investing into the market.

关键词： ARIMA SARIMA LSTM Root Mean Square Error Mean Absolute Error Stock price prediction

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Estimation of anisotropic viscosities for the stochastic primitive equations

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Stochastics and Partial Differential Equations: Analysis and Computations 2025年 1-48页

作者： Cialenco, Igor Hu, Ruimeng Lin, Quyuan Department of Applied Mathematics Illinois Institute of Technology 10 W 32nd Str John T. Rettaliata Engineering Center Room 220 Chicago 60616 IL United States Department of Mathematics Department of Statistics and Applied Probability University of California Santa Barbara 93106-3080 CA United States School of Mathematical and Statistical Sciences Clemson University Clemson 29634 SC United States

The viscosity parameters play a fundamental role in applications involving stochastic primitive equations (SPE), such as accurate weather predictions, climate modeling, and ocean current simulations. In this paper, we develop several novel estimators for the anisotropic viscosities in the SPE, using a finite number of Fourier modes of a single sample path observed within a finite time interval. The focus is on analyzing the consistency and asymptotic normality of these estimators. We consider a torus domain and treat strong, pathwise solutions in the presence of additive white noise (in time). Notably, the analysis for estimating horizontal and vertical viscosities differs due to the unique structure of the SPE and the fact that both parameters of interest are adjacent to the highest-order derivative. To the best of our knowledge, this is the first work addressing the estimation of anisotropic viscosities, with the potential applicability of the developed methodology to other models. © The Author(s) 2025.

关键词： Anisotropic viscosities estimation Asymptotic normality Inverse problems Nonlinear SPDEs Parameter estimation for SPDEs Statistical analysis of SPDEs Stochastic primitive equations

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A Finite Difference Method for a Normalized Time-Fractional Black–Scholes Equation

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International Journal of Applied and Computational mathematics 2025年第3期11卷 1-17页

作者： Nam, Yunjae Wang, Jian Lee, Chaeyoung Choi, Yongho Bang, Minjoon Li, Zhengang Kim, Junseok Program in Actuarial Science and Financial Engineering Korea University Seoul 02841 South Korea School of Mathematics and Statistics Nanjing University of Information Science and Technology Nanjing 210044 China Department of Mathematics Kyonggi University Suwon 16227 South Korea Computer and Information Engineering Daegu University Gyeongsan 38453 South Korea Department of Mathematics Korea University Seoul 02841 South Korea

In this article, we propose a normalized time-fractional Black–Scholes (TFBS) equation. The proposed model uses a normalized time-fractional derivative which has a distinctive feature wherein a weight function possesses the property that its integral with respect to time is always equal to one. This feature ensures a well-balanced integration over time and provides a fair comparison between different fractional orders. An implicit finite difference method is used for the numerical solution of the TFBS equation. We perform several standard numerical tests to examine the effect of the fractional parameter on the option pricing. These experiments are designed to investigate how variations in the fractional parameter influence pricing outcomes and provide valuable insights into the model’s behavior under different conditions. The computational results demonstrate the model’s potential for capturing more intricate market dynamics, which makes the proposed model a promising tool for financial analysis. In the appendix, we provide a computer program that implements the numerical methods discussed in the paper for interested readers. © The Author(s), under exclusive licence to Springer Nature India Private Limited 2025.

关键词： Implicit finite difference method Memory effect Normalized time-fractional Black–Scholes equation

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Thermal performance improvement of phase change materials using trapezoidal longitudinal fins integrating secondary tubes

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Energy Reports 2025年 13卷 5692-5703页

作者： Waqas, Hassan Zorgati, Hamdi Hussain, Mohib Al-Mdallal, Qasem M. School of Naval Architecture Ocean and Energy Power Engineering Wuhan University of Technology Hubei Wuhan430063 China Saudi Arabia School of Mathematics and Statistics Northwestern Polytechnical University Xian710072 China Department of Mathematical Sciences UAE University Al-AinPO Box 15551 United Arab Emirates

This work aimed to improve the phase change material (PCM) of latent heat energy storage systems (LHTESS) performance. Thermal energy is accumulated and stored in LHTESS during the phase transition from solid to liquid. The primary limitation of this system lies in the inadequate heat conductivity of the phase change material, which is employed to achieve equilibrium by balancing energy demand and supply. Various augmentation strategies are employed to address this challenge. This study employs the method of dispersing nanoparticles in pure Phase Change Material (PCM) to produce Nano-Enhanced Phase Change Material (NEPCM) and incorporates uniquely shaped fins to expedite the melting process. Subsequently, the impact of volume fractions on the melting rate is analysed, and a parallel investigation is conducted between nanoparticle dispersion and fin addition. This work presents novel fin configurations that draw inspiration from the crystal structure of trapezoidal longitudinal fins. The effects of adding fins to different structures on the performance of LHTESS have been examined, focusing on improving energy storage capacity and charging speed. The dispersion of nanoparticles in PCM and its effectiveness is further investigated. In summary, the results show that irrespective of the pattern of the fin on the energy storage chamber, the use of a fin demonstrates to be a better option to improve the charging process in LHTESS than using nanoparticle dispersion. As a result of these two attributes, a higher storage capacity for energy and a faster melting rate are observable. Also, adding an optimized longitudinal fin with PCM would significantly speed up the melting rate more than LHTESS with regular extended fins compared to optimized regular fins. © 2025 The Authors

关键词： Crystal structure

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Computational Modeling of Heat Transfer from a Horizontal Array of Cylinders for Low Reynolds Numbers

Computational Modeling of Heat Transfer from a Horizontal Ar...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Khan, Ovais U. Arshed, G.M. Raza, S.A. Ali, H. Department of Mechanical and Industrial Engineering Texas A and M University KingsvilleTX United States Department of Mechanical Engineering PNG University of Technology Morobe Province Lae411 Papua New Guinea Department of Mathematics and Statistics Wichita State University WichitaKS United States Department of Mechanical Engineering NED University of Engineering and Technology Karachi Pakistan

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

A numerical model based on the computational fluid dynamics (CFD) approach was developed to investigate heat transfer from a horizontal row of circular cylinders in a tandem, side-by-side arrangement. The study involved solving momentum and energy equations using the finite volume method, with convective terms discretized using a second-order upwind method and diffusion terms discretized using central differencing. A second-order implicit technique was used to integrate the temporal term. The numerical simulations were run with various values of free stream Reynolds number and dimensionless longitudinal pitch ratio. The numerical results were compared with analytical findings from the literature and found in good agreement for low values of free stream Reynolds number. The maximum percentage error between the average Nusselt number obtained from the numerical and analytical solutions was less than 20% for larger free-stream Reynolds numbers;however, it decreased to less than 2% as the free-stream Reynolds number decreased. The good agreement between the two models at low free-stream Reynolds numbers suggests that the CFD model is valid in this range and can be used to study similar fluid flow and heat transfer problems. The information generated would be useful in the design of more efficient fluid systems involving arrays of cylinders. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Finite volume method

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