Article
Thermodynamics
Ahmad Shafee, M. Jafaryar, Elham Abohamzeh, Nguyen Dang Nam, Iskander Tlili
Summary: Simulation of swirl flow intensification with a new device inside a pipe was conducted, showing that dispersing hybrid nanopowders can enhance testing fluid characteristics, increase tangential velocity of nanomaterial with rising Re, and thinning the thermal boundary layer near the wall by reducing pitch ratio leads to higher Nu.
JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY
(2021)
Article
Thermodynamics
Houman Babazadeh, Zahir Shah, Ikram Ullah, Poom Kumam, Ahmad Shafee
Summary: We investigated the convection transportation of hybrid nanofluid within a permeable medium under the influence of an externally applied magnetic force using a control volume-based finite element method. The study looked into the effects of Darcy and Rayleigh parameters, as well as magnetic and radiation parameters on the performance of the nanofluid. The results showed that the Nusselt number increased with the consideration of radiation and the addition of Lorentz force improved the conduction mode sensitivity, with good agreement with published results validating the numerical computations.
JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY
(2021)
Article
Thermodynamics
Idir Mechai, Saleh Mousa Alzahrani, Hakeem A. Othman, Sami H. Altoum, Zahoor Iqbal, Al-Nashri Al-Hossain Ahmad, Hussein A. Z. AL-bonsrulah, Abd Elmotaleb A. M. A. Elamin, F. H. Damag
Summary: This article evaluates a curved enclosure with MHD (magnetohydrodynamics). Both the outer cold surface and the inner hot surface have curved shapes, which enhance the convective rate. The equations of MHD have been applied, and a negative term is present in the x direction with the application of horizontal magnetic fields. The presence of such a field results in the generation of Lorentz force, which hinders the acceleration of the nanofluid. The addition of nanoparticles with higher m and φ values can increase the convective flow. When Ra = 700, dispersing nano-powders can enhance the Nu by about 41.9% in the presence of MHD. When Ra = 150, Nu can improve by about 12.01% with an increase in m. Nu decreases by around 40.1% with the growth of Ha, while it increases by approximately 43.36% in the presence of higher Ra.
CASE STUDIES IN THERMAL ENGINEERING
(2023)
Article
Computer Science, Interdisciplinary Applications
Yahya Ali Rothan
Summary: The study illustrates the impact of Lorentz force on the migration of nanopowders. By modifying momentum equations and adding new source terms using FEM and FVM methods, the experiment shows that increasing permeability can enhance nanopowder speed, while the introduction of MHD can counteract buoyancy and decrease velocity.
INTERNATIONAL JOURNAL OF MODERN PHYSICS C
(2021)
Article
Chemistry, Physical
Honghe Nong, Abdulnasser Mahmood Fatah, S. A. Shehzad, T. Ambreen, Mahmoud M. Selim, Ahmad B. Albadarin
Summary: The research demonstrates steady-state magnetized nanofluid flow under radiative wavy cavity, modeling the porosity term using non-Darcy's theory. The working nanofluid is based on water-Al2O3 nano-powder with 4% concentration, and numerical modeling is estimated via CVFE technique. Results show that increasing media porosity leads to fluid advection decay and conduction dominates over convection in the process.
JOURNAL OF MOLECULAR LIQUIDS
(2021)
Article
Thermodynamics
A. K. Abdul Hakeem, S. Priya, Ganga Bhose, Sivasankaran Sivanandam
Summary: This study highlights the importance of considering porous media and viscous dissipation in the use of hybrid nanofluids for heat transfer. The results show that slip conditions significantly affect the momentum and temperature distribution in natural convective boundary layer flow. These findings are valuable for improving the energy efficiency of thermal systems.
INTERNATIONAL JOURNAL OF NUMERICAL METHODS FOR HEAT & FLUID FLOW
(2023)
Article
Thermodynamics
Renping Wang, Ahmad Shafee, M. Shamlooei, Nguyen Dang Nam, Iskander Tlili
Summary: The article investigates the transportation of hybrid ferrofluid using Lorentz forces and numerical methods, showcasing the effects of magnetic field on thermal behavior and nanopowder velocity. Parameters such as Hartmann number, Reynolds number, and Rayleigh number play significant roles in influencing the fluid properties.
JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY
(2021)
Article
Engineering, Multidisciplinary
M. Ijaz Khan, Sumaira Qayyum, Faisal Shah, R. Naveen Kumar, R. J. Punith Gowda, B. C. Prasannakumara, Yu-Ming Chu, S. Kadry
Summary: This study investigates the characteristics of hybrid nanofluids, including Marangoni convection, entropy generation, velocity, concentration, temperature, etc., under different influencing factors through calculations and graphical analysis.
AIN SHAMS ENGINEERING JOURNAL
(2021)
Article
Physics, Applied
Nidal H. Abu-Hamdeh, Khaled A. Alnefaie
Summary: A mathematical theory was developed to simulate the movement of hybrid nanopowder in space under the influence of magnetic force. The numerical approach combined the FEM and FVM, with triangular elements creating the grid. The properties of a hybrid nanomaterial consisting of iron oxide and MWCNT dispersed in water were assessed using empirical formulas. The study found that gravity force and radiation flux impact play a role in the phenomena, causing the formation of vortexes and impacting velocity and temperature distortions. The inclusion of Lorentz terms and consideration of factors like Da and Ra further affected the flow dynamics.
INTERNATIONAL JOURNAL OF MODERN PHYSICS B
(2023)
Article
Mathematics, Applied
S. A. Shehzad, M. Sheikholeslami, T. Ambreen, A. Saleem, A. Shafee
Summary: The study investigates the behavior of natural convection of aqueous-based hybrid nanomaterial under the combined effect of Lorentz force and radiation. The magnetic force slows down the flow, and the fluid tends to attract the magnetic field source. Nu(ave) is directly correlated with the Rayleigh number and radiation, but indirectly dependent on the Hartmann number.
APPLIED MATHEMATICS AND MECHANICS-ENGLISH EDITION
(2021)
Article
Thermodynamics
Meng-Ge Li, Chun Zheng, Qiang Zhao, Xiong Chen, Wei-Tao Wu
Summary: The study investigates the natural convection and anisotropic heat transfer of ferro-nanofluids in partially heated enclosures, showing that heat transfer can be controlled by adjusting the external magnetic field. In pure heat conduction, increasing the Hartmann number and nanoparticle concentration raises the anisotropic thermal conductivity; in natural convection, increasing the magnetic field intensity also increases Lorentz force resistance.
CASE STUDIES IN THERMAL ENGINEERING
(2021)
Article
Engineering, Multidisciplinary
Shaik Jakeer, P. BalaAnki Reddy, A. M. Rashad, Hossam A. Nabwey
Summary: This article focuses on the study of magneto Cu-Al2O3/water hybrid nanofluid flow in a non-Darcy porous square cavity, analyzing the influence of various dimensionless parameters on the flow. Results show that the rate of fluid flow and heat transfer in the direction of the moving heated obstacle play a crucial role in the process.
ALEXANDRIA ENGINEERING JOURNAL
(2021)
Article
Physics, Applied
Ahmad Shafee
Summary: A numerical technique was employed to study the transport of nanofluid within a porous container, using a single-phase approach and implementing Darcy law to involve the porous term in the equation. The equation format was converted to stream function format and solved using CVFEM. The code was verified using previous data and the results showed that loading alumina increased Nu by 26.71% at Ha=0 and by 41.22% at Ha=15. Applying a magnetic field reduced Nu by 37.93% at Ra=700. Increasing the strength of the rotating cell resulted in a 38.22% increase in Nu as Ra increased. Changing the shape of alumina increased Nu by 11.73% at Ha=15 and Ra=700.
INTERNATIONAL JOURNAL OF MODERN PHYSICS B
(2023)
Article
Thermodynamics
Umair Khan, Aurang Zaib, Sakhinah Abu Bakar, Nepal Chandra Roy, Anuar Ishak
Summary: This study investigates mixed convection of a thermo micropolar hybrid nanofluid through a vertical surface in a saturated porous medium, considering inertial and microstructure characteristics. It distinguishes the effects of two distinct nanoparticles, MgO and Ag, in enhancing heat transfer rates and thermal performance. By transforming the leading equations into ordinary differential equations using similarity transformations, unique outcomes are obtained for buoyancy aiding flow, while dual or multiple outcomes exist for buoyancy opposing flow.
CASE STUDIES IN THERMAL ENGINEERING
(2021)
Article
Mathematics, Applied
Bharat Keshari Swain
Summary: This study investigates the magnetohydrodynamic (MHD) stagnation-point flow and heat transfer of a ternary-hybrid nanofluid consisting of water, Copper (Cu), aluminum oxide (Al2O3), and Silver (Ag) nanoparticles over a flat plate embedded in a porous medium. The impacts of viscous dissipation, buoyancy force, and heat source/sink are examined. The governing partial differential equations with corresponding boundary conditions are transformed into a system of ordinary differential equations and solved using numerical methods. The study aims to analyze the fluid flow, heat and mass transfer of nanofluids with MHD flow, and entropy generation, which have important applications in various industries, particularly in strengthening and improving the durability of products through the extrusion/layering of fluid with solute particles over other materials. Some important findings include the improvement of fluid velocity with an increase in the heat source parameter and a reduction in fluid velocity with an increase in the heat sink parameter. Both velocity and temperature increase with higher values of the Brinkman number, which results in greater entropy generation.
ZAMM-ZEITSCHRIFT FUR ANGEWANDTE MATHEMATIK UND MECHANIK
(2023)
Article
Computer Science, Interdisciplinary Applications
D. Dinh-Cong, T. Nguyen-Thoi
Summary: The article presents the application of a multi-objective cuckoo search algorithm for structural damage identification in composite structures made of functionally graded materials. The proposed algorithm is able to accurately identify the locations and extent of multi-damages using spatially incomplete measurement data with noise contamination. Numerical simulation studies show that the multi-objective cuckoo search algorithm provides better damage prediction compared to two other well-known algorithms.
ENGINEERING WITH COMPUTERS
(2023)
Article
Computer Science, Interdisciplinary Applications
Pham Toan Thang, Dieu T. T. Do, Jaehong Lee, T. Nguyen-Thoi
Summary: This paper presents an in-depth study on the influence of nanoscale parameters on the bending and free vibration responses of functionally graded carbon nanotube-reinforced composite nanoshells. Mathematical formulas and numerical calculations are used to investigate the effect of nanoscale parameters, material properties, and shell shapes on the deflection and fundamental frequency parameters of the nanoshells.
ENGINEERING WITH COMPUTERS
(2023)
Article
Computer Science, Interdisciplinary Applications
Quoc-Hoa Pham, Phu-Cuong Nguyen, Trung Thanh Tran, Trung Nguyen-Thoi
Summary: This paper proposes a finite element method for the free vibration analysis of a sandwich nanoplate with an auxetic honeycomb core. The method uses a nonlocal elasticity theory and a shear deformation theory without shear correction factors, and it is applicable to sandwich nanoplates with negative Poisson's ratio.
ENGINEERING WITH COMPUTERS
(2023)
Article
Engineering, Civil
H. S. Naveen Kumar, Subhaschandra Kattimani, Flavio D. Marques, T. Nguyen-Thoi, Mehdi Shariati
Summary: This research investigates the geometrically nonlinear behavior of functionally graded saturated porous material (FGSPM) plate under undrained conditions. The refined shear deformation plate theory (RSDPT) is used to model the FGSPM plate with von Karman's nonlinearity, and Biot's linear poroelasticity theory is applied to establish the constitutive equations. The results show that the saturated fluid significantly affects the nonlinear deflection and vibration behavior of the FGSPM plate.
INTERNATIONAL JOURNAL OF STRUCTURAL STABILITY AND DYNAMICS
(2023)
Article
Computer Science, Artificial Intelligence
Thao Nguyen-Trang, Trung Nguyen-Thoi, Kim-Ngan Nguyen-Thi, Tai Vo-Van
Summary: This paper proposes a technique to apply a metaheuristic optimization algorithm for solving the balance-driven automatic clustering problem of probability density functions (CDF). The proposed method can automatically determine the number of clusters and approximate the global optimal solution, considering both the clustering compactness and the clusters' size similarity. Experimental results on one-dimensional and multidimensional probability density functions demonstrate that the new method outperforms conventional techniques in providing higher quality clustering solutions.
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
(2023)
Article
Computer Science, Artificial Intelligence
Thao Nguyen-Trang, Trung Nguyen-Thoi, Tai Vo-Van
Summary: Clustering for probability density functions (CDF) can be divided into non-fuzzy and fuzzy approaches. A new clustering algorithm called DE-AFCF is proposed to solve the fuzzy CDF problem by using Gaussian prototype and a new objective function. This method can automatically determine the number of clusters k and consider both clustering compactness and separation.
APPLIED INTELLIGENCE
(2023)
Article
Computer Science, Interdisciplinary Applications
Son H. Nguyen, Nguyen N. Nam, Tien-Dat Hoang, Tan N. Nguyen, T. Nguyen-Thoi
Summary: This paper proposes a simple and efficient method called aARS-Poly for alpha assumed rotations and shear strains in polygonal plate elements. The method applies an alternative assumption of tangent rotations along element boundaries based on Timoshenko's beam theory, and scales up the quadratic term of the assumed field using a positive scaling factor. Through numerical experiments, a general-fixed value of 0.5 achieves optimal relative errors in the energy norm. The aARS-Poly element using this value passes all critical tests and ensures orientation independence, solution stability, and free shear-locking. The method can be implemented straightforwardly for arbitrary convex-shaped polygonal meshes. Numerical results demonstrate high reliability and optimal results in static and free vibration analyses.
COMPUTERS & STRUCTURES
(2023)
Article
Engineering, Multidisciplinary
Zing L. T. Tran, Tam T. Truong, T. Nguyen-Thoi
Summary: This study proposes a new method called DNN-DE, which combines deep neural networks (DNN) with differential evolution (DE), for optimizing the frequency of laminated functionally graded carbon nanotube (FG-CNT)-reinforced composite quadrilateral plates under free vibration. The DNN is used to predict the objective and constraints, replacing the time-consuming finite element analysis (FEA) procedures, while the DE acts as an optimizer. Numerical examples are provided to demonstrate the performance of the proposed method, and the results are compared with those obtained by other methods to verify its reliability and effectiveness. The study also investigates the influence of various parameters on the optimal results, such as boundary conditions, CNT volume fraction, and CNT distribution.
INTERNATIONAL JOURNAL OF COMPUTATIONAL METHODS
(2023)
Article
Engineering, Civil
Duy-Khuong Ly, Vinyas Mahesh, Chanachai Thongchom, T. Nguyen-Thoi
Summary: This study proposes an advanced cell-based smoothed discrete shear gap method (CS-DSG3) using zig-zag theory integrated with a hybrid control mechanism for analysis of smart damping control of laminated functionally graded carbon nanotube reinforced composite (FG-CNTRC) shell structures. The study successfully combines CS-DSG3 with zig-zag theory to provide an effective global-local numerical approach for analyzing the behavior of laminated FG-CNTRC shell structures.
THIN-WALLED STRUCTURES
(2023)
Article
Automation & Control Systems
Tam T. Truong, Jaehong Lee, T. Nguyen-Thoi
Summary: Most previous studies on damage detection in civil engineering structures have focused on either element damage detection or joint damage detection, separately. This study proposes an effective data-driven approach using an attention based convolutional gated recurrent unit network (ACGRU) for real-time damage detection of both joint and element in frame structures.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Construction & Building Technology
Nguyen-Minh Toan, Bui-Ngoc Tram, Jim Shiau, Tan Nguyen, Nguyen-Thoi Trung
Summary: This paper presents a novel approach for the stability evaluation of rectangular tunnels in undrained clay during lining process. By adopting isogeometric analysis and upper bound limit analysis, the tunnel geometry can be accurately represented using B-spline surfaces. The upper bound limit analysis is formulated as a second-order cone program, which can be solved using a numerical optimization algorithm. The proposed approach is validated and found to be accurate and reliable through comparisons with previous studies. Additionally, a deep learning model is trained to further enhance the accuracy and precision of the results.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2023)
Article
Materials Science, Multidisciplinary
Ngoc-Tu Do, Trung Thanh Tran, Trung Nguyen-Thoi, Quoc Hoa Pham
Summary: The main goal of this paper is to improve the mixed interpolation of tensorial components triangular (MITC3) by using the edge-based smoothed finite element method (ES-FEM), known as ES-MITC3, for analyzing the vibration of piezoelectric functionally graded porous (p-FGP) plates subjected to dynamic loading. The varying material properties of the FGP core through thickness with uneven porosity distribution are considered, as well as the linear relationship between electric potential and the thickness of the piezoelectric sublayer. A closed-loop control algorithm is used to actively control the vibration of p-FGP plates through feedback from displacement and velocity. The proposed method's performance is verified through comparative examples, and the authors hope it can be effectively applied to various smart material models and contribute to understanding texture control by piezoelectric materials through numerical results.
FORCES IN MECHANICS
(2023)
Article
Engineering, Multidisciplinary
Duy-Khuong Ly, Ho-Nam Vu, Chanachai Thongchom, Nguyen-Thoi Trung
Summary: This paper presents a novel numerical approach for nonlinear analysis and smart damping control in laminated functionally graded carbon nanotube reinforced magneto-electro-elastic (FG-CNTMEE) plate structures, taking into account multiple physical fields. The approach employs a multi-physical coupling isogeometric formulation to accurately capture the nonlinear strain-displacement relationship and the magneto-electro-elastic coupling properties. The smart constrained layer damping treatment is applied to achieve nonlinear damped responses. The formulation is transformed into the Laplace domain and converted back to the time domain through inverse techniques for smart control using viscoelastic materials.
ENGINEERING ANALYSIS WITH BOUNDARY ELEMENTS
(2024)
Article
Mechanics
T. Nguyen-Thoi, Duy-Khuong Ly, S. Kattimani, Chanachai Thongchom
Summary: This article presents a novel numerical approach for modeling and analyzing smart constrained layer damping (SCLD) treatment in multilayer porous functionally graded graphene platelets-reinforced composite (PFG-GPRC) plates based on electromechanical coupling isogeometric analysis. The approach utilizes non-uniform rational B-splines (NURBS) basis functions to efficiently approximate the geometric, mechanical, and electric displacement fields. By integrating these basis functions with a zig-zag formulation, the approach can handle continuous/discontinuous material properties at interfaces and improve the effectiveness of global-local numerical solutions. The analysis considers different graphene platelet patterns and examines the impact of various parameters on the damping behavior of multilayer PFG-GPRC plates through parametric investigation.
Article
Mechanics
Quoc Hoa Pham, Trung Thanh Tran, Ashraf M. Zenkour, T. Nguyen-Thoi
Summary: This work studies the free vibration analysis and multi-objective optimization for L-shaped bi-functionally graded sandwich (L-BFGSW) plates. By using an effective finite element formulation and non-dominated sorting genetic algorithm, the optimal solution for the trade-off relationship between the maximum frequency and the minimum structural weight can be obtained.
COMPOSITE STRUCTURES
(2023)
Article
Physics, Multidisciplinary
Xiaoyu Shi, Jian Zhang, Xia Jiang, Juan Chen, Wei Hao, Bo Wang
Summary: This study presents a novel framework using offline reinforcement learning to improve energy consumption in road transportation. By leveraging real-world human driving trajectories, the proposed method achieves significant improvements in energy consumption. The offline learning approach demonstrates generalizability across different scenarios.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Junhyuk Woo, Soon Ho Kim, Hyeongmo Kim, Kyungreem Han
Summary: Reservoir computing (RC) is a new machine-learning framework that uses an abstract neural network model to process information from complex dynamical systems. This study investigates the neuronal and network dynamics of liquid state machines (LSMs) using numerical simulations and classification tasks. The findings suggest that the computational performance of LSMs is closely related to the dynamic range, with a larger dynamic range resulting in higher performance.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Yuwei Yang, Zhuoxuan Li, Jun Chen, Zhiyuan Liu, Jinde Cao
Summary: This paper proposes an extreme learning machine (ELM) algorithm based on residual correction and Tent chaos sequence (TRELM-DROP) for accurate prediction of traffic flow. The algorithm reduces the impact of randomness in traffic flow through the Tent chaos strategy and residual correction method, and avoids weight optimization using the iterative method. A DROP strategy is introduced to improve the algorithm's ability to predict traffic flow under varying conditions.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Chengwei Dong, Min Yang, Lian Jia, Zirun Li
Summary: This work presents a novel three-dimensional system with multiple types of coexisting attractors, and investigates its dynamics using various methods. The mechanism of chaos emergence is explored, and the periodic orbits in the system are studied using the variational method. A symbolic coding method is successfully established to classify the short cycles. The flexibility and validity of the system are demonstrated through analogous circuit implementation. Various chaos-based applications are also presented to show the system's feasibility.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Viorel Badescu
Summary: This article discusses the maximum work extraction from confined particles energy, considering both reversible and irreversible processes. The results vary for different types of particles and conditions. The concept of exergy cannot be defined for particles that undergo spontaneous creation and annihilation. It is also noted that the Carnot efficiency is not applicable to the conversion of confined thermal radiation into work.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
P. M. Centres, D. J. Perez-Morelo, R. Guzman, L. Reinaudi, M. C. Gimenez
Summary: In this study, a phenomenological investigation of epidemic spread was conducted using a model of agent diffusion over a square region based on the SIR model. Two possible contagion mechanisms were considered, and it was observed that the number of secondary infections produced by an individual during its infectious period depended on various factors.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Zuan Jin, Minghui Ma, Shidong Liang, Hongguang Yao
Summary: This study proposes a differential variable speed limit (DVSL) control strategy considering lane assignment, which sets dynamic speed limits for each lane to attract vehicle lane-changing behaviors before the bottleneck and reduce the impact of traffic capacity drop. Experimental results show that the proposed DVSL control strategy can alleviate traffic congestion and improve efficiency.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Matthew Dicks, Andrew Paskaramoorthy, Tim Gebbie
Summary: In this study, we investigate the learning dynamics of a single reinforcement learning optimal execution trading agent when it interacts with an event-driven agent-based financial market model. The results show that the agents with smaller state spaces converge faster and are able to intuitively learn to trade using spread and volume states. The introduction of the learning agent has a robust impact on the moments of the model, except for the Hurst exponent, which decreases, and it can increase the micro-price volatility as trading volumes increase.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Zhouzhou Yao, Xianyu Wu, Yang Yang, Ning Li
Summary: This paper developed a cooperative lane-changing decision system based on digital technology and indirect reciprocity. By introducing image scoring and a Q-learning based reinforcement learning algorithm, drivers can continuously evaluate gains and adjust their strategies. The study shows that this decision system can improve driver cooperation and traffic efficiency, achieving over 50% cooperation probability under any connected vehicles penetration and traffic density, and reaching 100% cooperation probability under high penetration and medium to high traffic density.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Josephine Nanyondo, Henry Kasumba
Summary: This paper presents a multi-class Aw-Rascle (AR) model with area occupancy expressed in terms of vehicle class proportions. The qualitative properties of the proposed equilibrium velocity and the stability conditions of the model are established. The numerical results show the effect of proportional densities on the flow of vehicle classes, indicating the realism of the proposed model.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Oliver Smirnov
Summary: This study proposes a new method for simultaneously estimating the parameters of the 2D Ising model. The method solves a constrained optimization problem, where the objective function is a pseudo-log-likelihood and the constraint is the Hamiltonian of the external field. Monte Carlo simulations were conducted using models of different shapes and sizes to evaluate the performance of the method with and without the Hamiltonian constraint. The results demonstrate that the proposed estimation method yields lower variance across all model shapes and sizes compared to a simple pseudo-maximum likelihood.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Przemyslaw Chelminiak
Summary: The study investigates the first-passage properties of a non-linear diffusion equation with diffusivity dependent on the concentration/probability density through a power-law relationship. The survival probability and first-passage time distribution are determined based on the power-law exponent, and both exact and approximate expressions are derived, along with their asymptotic representations. The results pertain to diffusing particles that are either freely or harmonically trapped. The mean first-passage time is finite for the harmonically trapped particle, while it is divergent for the freely diffusing particle.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Hidemaro Suwa
Summary: The choice of transition kernel is crucial for the performance of the Markov chain Monte Carlo method. A one-parameter rejection control transition kernel is proposed, and it is shown that the rejection process plays a significant role in determining the sampling efficiency.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Xudong Wang, Yao Chen
Summary: This article investigates the joint influence of expanding medium and constant force on particle diffusion. By starting from the Langevin picture and introducing the effect of external force in two different ways, two models with different force terms are obtained. Detailed analysis and derivation yield the Fokker-Planck equations and moments for the two models. The sustained force behaves as a decoupled force, while the intermittent force changes the diffusion behavior with specific effects depending on the expanding rate of the medium.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
