Documents published in Scipedia

• A Comparative Analysis of the Boundary Condition Schemes for an Immersed Cylinder in a Water Stream with the Lattice Boltzmann Method

  F. Garzeri, I. Martins, L. Cabezas-Gómez

  Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (4), 69

  
  

  Abstract

  In this paper, we investigate the performance of different boundary condition (BC) schemes for curved walls within the framework of the Lattice Boltzmann Method (LBM). A canonical benchmark problem—the flow past a circular cylinder in a channel—is considered, with Reynolds numbers ranging from 50 to 300. While prior studies have examined similar configurations, this work provides a novel comparative analysis under realistic conditions—using dimensional LBM simulations with actual fluid properties and consumer-grade hardware, rather than idealized lattice units. Additionally, we introduce an in-house GPU-accelerated solver, enabling efficient high-fidelity simulations without reliance on specialized computational resources. Four wall boundary conditions—the standard bounce-back scheme, the non-equilibrium extrapolation scheme, the fictitious equilibrium scheme and a one-point scheme—are implemented and analyzed through their influence on the time-averaged drag coefficient of the cylinder. The results are compared against both experimental and Navier-Stokes-based numerical data to assess accuracy. Additionally, the study evaluates the relative impact of outlet BC selection on simulation fidelity. The findings show that all tested solid wall boundary schemes can produce reasonable predictions under suitable conditions. Furthermore, based on our results, the accuracy of LBM simulations is notably more sensitive to the choice of the outlet boundary condition when compared to the choice of the ones used at the immersed body.OPEN ACCESS Received: 08/05/2025 Accepted: 24/06/2025 Published: 27/10/2025

  Abstract
  In this paper, we investigate the performance of different boundary condition (BC) schemes for curved walls within the framework of the Lattice Boltzmann Method (LBM). A canonical [...]

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• Effects of Fetal Development on Umbilical Artery Hemodynamics: A Computational Fluid Dynamics Study with Doppler Ultrasound

  X. Song, J. Wang, G. Li, S. Zang, M. Li, C. Lee

  Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (4), 82

  
  

  Abstract

  The umbilical artery (UA) plays a vital role in the exchange of substances between the mother and fetus through fetal circulation. In silico computational fluid dynamics (CFD) has emerged as an effective tool for simulating and analyzing UA blood flow, especially when combined with clinical Doppler ultrasound data. However, most existing studies have applied CFD to investigate UA hemodynamics only at isolated stages of gestation. In reality, UA hemodynamics undergoes continuous changes throughout fetal morphogenesis and physiological development during the entire gestational period. To address this gap, the present study employs CFD to investigate the evolution of UA hemodynamics across eight consecutive gestational age groups: 19, 23, 25, 27, 30, 33, 36, and 39 weeks. The simulations are based on Doppler ultrasound data acquired from clinical examinations of fetuses. The results demonstrate that UA blood flow velocity, secondary helical flow intensity, pressure drop, and wall shear stress generally increase with advancing gestational age. Furthermore, statistical analysis of clinical data across different gestational weeks reveals that the ratio of the Dean number to the Reynolds number (i.e., square root of the dimensionless curvature) remains basically stable during fetal development, with a value of 0.57 ± 0.06. This finding offers new insight into the scaling behavior of UA flow dynamics and may serve as a useful reference for clinical assessments. Overall, this CFD-based investigation provides a comprehensive characterization of UA hemodynamic development and may assist clinicians in gaining a deeper understanding of fetal circulatory adaptation throughout gestation.

  Abstract
  The umbilical artery (UA) plays a vital role in the exchange of substances between the mother and fetus through fetal circulation. In silico computational fluid dynamics (CFD) [...]

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• Dynamic and Control in a Three-Variable Chemical Reaction Model

  M. Martinez, F. Chavarette

  Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (4), 68

  
  

  Abstract

  Chaotic behavior in nonlinear chemical systems presents significant challenges for stability and control, particularly in practical applications. This study investigates the suppression of chaos in a three-variable reaction system through an optimal linear feedback strategy, formulated via the solution of an algebraic Riccati equation. The proposed control approach effectively eliminates chaotic oscillations, guiding the system to equilibrium even under parameter uncertainties of up to 20%. Numerical simulations confirm that the control action maintains high robustness, ensuring convergence with minimal effort. The stabilization time for x

  Abstract
  Chaotic behavior in nonlinear chemical systems presents significant challenges for stability and control, particularly in practical applications. This study investigates the [...]

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• Optimum Analysis and Parameter Inference of a New Improved Adaptive Progressive Unit-Weibull Model Censoring with Two Physical Applications

  H. Mohammed, O. Abo-Kasem, A. Elshahhat

  Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (4), 67

  
  

  Abstract

  Recently, a new bounded version of the Weibull lifetime has been introduced, retaining the flexibility of the standard Weibull model while restricting it to the unit interval, making it particularly useful for betalike modeling in various fields. This paper investigates the improved adaptive Type-II progressively censored plan by applying it to the bounded unit Weibull distribution. From a frequentist perspective, both maximum likelihood and maximum product of spacings methods are used, along with appropriate approximate confidence intervals. Bayesian point estimates, along with Bayesian credible intervals, are obtained using classical procedures that involve Markov-Chain Monte Carlo sampling, with two separate posterior distributions based on the squared error loss. The proposed estimation frameworks encompass both distribution parameters and key reliability metrics, notably the reliability and failure rate functions. Extensive simulations are conducted to evaluate the accuracy and efficiency of the estimators under various censoring levels, sample sizes, and thresholds. To determine the optimal removal strategy under both frequentist estimation paradigms, several metrics are proposed. Additionally, the model is applied to two real-world datasets from engineering reliability; one contains core samples from petroleum reservoirs collected across four cross-sections, and the other pertains to the tensile strength of polyester fibers, illustrating its practical utility and flexibility in modeling. The novelty of this study lies in integrating the bounded support of the unit-Weibull model with an improved adaptive censoring scheme, providing enhanced robustness and adaptability in reliability analysis across different fields.OPEN ACCESS Received: 21/06/2025 Accepted: 19/08/2025 Published: 27/10/2025

  Abstract
  Recently, a new bounded version of the Weibull lifetime has been introduced, retaining the flexibility of the standard Weibull model while restricting it to the unit interval, [...]

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• Approximate Calculation of the Generalized Erdélyi-Kober Operator Using a Cubic Spline

  S. Karimov, E. Islamov, E. Shishkina

  Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (4), 66

  
  

  Abstract

  This article investigates the problem of approximating the generalized Erdélyi-Kober fractional operator (often referred to as the Lowndes operator) using cubic splines. A method based on cubic spline interpolation is proposed for approximating the operator on a non-uniform grid. The convergence rate of the proposed method is proven, and its stability is analyzed. Error bounds are established for functions in the class C4[0; b], providing a mathematical justification for the accuracy of the approximation. The efficiency of the method is validated through practical examples using test functions such as f (x)= x4.7and f (x)= cos x, with results presented in graphical and numerical forms. This approach ensures high accuracy and flexibility in computing fractional integrals, which is of significant importance for solving fractional models used in physics, engineering, and other sciences. The article also provides an overview of the role of the generalized Erdélyi-Kober operator in modern fractional calculus and its applications.OPEN ACCESS Received: 06/06/2025 Accepted: 08/09/2025 Published: 27/10/2025

  Abstract
  This article investigates the problem of approximating the generalized Erdélyi-Kober fractional operator (often referred to as the Lowndes operator) using cubic splines. [...]

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• Fundamental Mechanics and Precision Control of Optical Axis Stability and Parallelism in Multi-Sensor Electro-Optical Pods

  Z. Huang, S. Chi, L. Zhu

  Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (4), 65

  
  

  Abstract

  Modern electro-optical pods incorporatemulti-spectral sensors for reconnaissance, target acquisition, and laser designation, where sub-milliradian optical axis stability and inter-sensor parallelism are critical for mission success. This paper establishes a unified theoretical framework combining rigid-body kinematics and deformable body mechanics to develop a physics-based stability metric through screw theory formulation, expressing the optical axis dynamics as ˙O = [ω]×O+v, with thermo-mechanical constraints [ω]×O < ω, v < v for engineering implementation. A novel computational geometry method evaluates multi-sensor alignment errors by solving Ei = si − (si · ˆO) ˆO + JTT + Jgg, where JT and Jg represent thermal and gravitational Jacobians. The rigid-flexible coupling model with multi-point constraints (MPC) reveals thermal dominance (0.49 mrad IR sensor pitch displacement at 60◦C, 272× gravitational effect), material sensitivity (CTE mismatch contributing 68% of TV sensor’s azimuthal error), and cross-axis coupling (19% LD error amplification under thermal gradients). However, due to the limitations of current experimental conditions, the experimental validation ismainly carried out in controlled environments. The current experimental validation shows <5% deviation between predicted andmeasured parallelismerrors across −20◦C to 60◦C. In the future, we will supplement the evaluation of the robustness of the control method through existing simulation verifications (such as adding vibration and temperature disturbance models) in the “experimental discussion” or “prospect” section, and clarify the research plan for actual environment testing. The framework provides design guidelines for optimal sensor placement minimizing JT F, temperaturedependent calibration protocols, and 0.1 mrad allocable margin for manufacturing tolerances. This methodology advances electro-optical system engineering fromempirical tuning tomodel-driven optimization, demonstrating 0.12 mrad (3σ) stability in field tests under ISO 9022 environmental stress profiles, with key innovations including the first integration of Lie algebra kinematics with FEM-based deformation analysis for optical systems and physics-informed error budgeting separating thermal, mechanical, and alignment components.

  Abstract
  Modern electro-optical pods incorporatemulti-spectral sensors for reconnaissance, target acquisition, and laser designation, where sub-milliradian optical axis stability [...]

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• On Nonlinear Monge-Ampère Equations and Their Symmetry Classifications

  Z. Izgi, Ö. Avit, D. Baleanu, M. Yousif, M. Alharthi, P. Mohammed

  Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (4), 64

  
  

  Abstract

  The Monge-Ampère equation (MAE) plays a pivotal role across a broad spectrum of theoretical and applied sciences, with its solutions being essential for advancing various fields. This study explores all forms of the fully nonlinear MAE using Lie group transformations to reduce the equation into solvable forms. Analytical solutions are derived using ansatzbased methods, yielding novel and generalized results that enhance the existing body of knowledge. In particular, solutions for cases with diverse source functions and boundary conditions are obtained, addressing gaps in the literature. Stability of the solutions is studied through both analytical and numerical approaches. Comparisons with existing solutions demonstrate the efficiency and generality of the proposed methods. The results presented in this work are poised to impact numerous applications, providing a robust framework for further research on MAEs.OPEN ACCESS Received: 24/05/2025 Accepted: 07/08/2025 Published: 27/10/2025

  Abstract
  The Monge-Ampère equation (MAE) plays a pivotal role across a broad spectrum of theoretical and applied sciences, with its solutions being essential for advancing various [...]

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• RCS Simulation of Double S-Shaped Inlet with Radar Absorbing Materials Shedding Using Iterative Physical Optics with Impedance Boundary Condition

  X. Guo, X. Xia, Z. Zhao, M. Wu, Y. Liu

  Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (4), 63

  
  

  Abstract

  The inlet of an aircraft engine is a primary contributor to the aircraft’s forward electromagnetic scattering. S-shaped inlet and radar absorbing materials (RAM) coatings have been widely adopted as effective measures to reduce forward radar cross section (RCS). To investigate the influence of RAM shedding on the RCS reduction efficiency, the electromagnetic scattering characteristics of the inlet under five different shedding probabilities were calculated using the iterative physical optics (IPO) combined with impedance boundary condition (IBC). Numerical simulation results demonstrate that the forward RCS of the S-shaped inlets increases monotonically with shedding probability. In the yaw plane, intact non-magnetic RAM exhibits better RCS reduction efficiency (RRE) than that in the pitch plane across all scenarios. Specifically, at a shedding probability of 0.7, the remaining non-magnetic RAM maintains an RRE exceeding 40% in the pitch plane. Collectively, these results suggest that recoating the nonmagnetic RAM is recommended when the shedding probability exceeds 0.7 in either detection plane to sustain critical stealth performance.OPEN ACCESS Received: 20/05/2025 Accepted: 13/08/2025 Published: 27/10/2025

  Abstract
  The inlet of an aircraft engine is a primary contributor to the aircraft’s forward electromagnetic scattering. S-shaped inlet and radar absorbing materials (RAM) coatings [...]

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• Deep Learning Approaches for Hydrological Forecasting: A Systematic Review

  L. Singh, K. Singh, K. Robindro, N. Hoque, D. Bhattacharyya

  Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (4), 62

  
  

  Abstract

  Machine learning (ML) techniques, especially Deep Learning (DL) techniques, have been applied for flood risk analysis and prediction on spatial historical data to minimize the risk of the loss of lives and properties associated with floods. In recent years, various studies have established DL as an effective approach for building potential flood prediction models. However, a thorough, systematic integration of recent advancements in DL for hydrological forecasting, their reported performance, and challenges is essential for guiding future work effectively. This paper presents a systematic survey of various DL models applied to flood prediction. This systematic review integrates studies published between 2018 and 2025 that used DL models in hydrological forecasting, such as flood prediction, streamflow forecasting, and runoff modeling. A systematic search of major electronic databases was performed using pre-defined inclusion and exclusion criteria. The overall search provided 647 records, which were narrowed down to a final collection of 45 studies after screening and full-text examination based on factors like study design, hydrological forecasting relevance, and application of DL. The review quantitatively summarizes the reported performances of various DL models, including RNN variants (LSTM, GRU), CNN, GAN, and hybrid architectures, across different hydrological forecasting tasks and datasets. Findings indicate that DL models consistently achieve high performance metrics such as NSE of (0.99), RMSE of (24.61) and MAPE of (1.73) for certain applications. Despite these advancements, significant research gaps remain, particularly concerning the scarcity of high-quality, publicly available datasets with detailed spatial information, the need for more robust real-time prediction systems with minimized false alarms, and the development of more generalized models applicable across diverse geographical regions. this review highlights the significant potential of DL in hydrological prediction as well as clearly stating the fundamental challenges that need to be overcome in order to achieve more robust and generalizable flood prediction systems.OPEN ACCESS Received: 25/04/2025 Accepted: 22/07/2025 Published: 27/10/2025

  Abstract
  Machine learning (ML) techniques, especially Deep Learning (DL) techniques, have been applied for flood risk analysis and prediction on spatial historical data to minimize [...]

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• Inference of the Exponentiated Rayleigh Distribution on Step-Stress Accelerated Life Testing under Type-I Hybrid Censored Data with Physical Application

  M. Fawzy, I. Alasbahi, T. Alof, A. Ahmad, H. Taha, A. El-Bary, K. Lofty

  Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (4), 61

  
  

  Abstract

  This paper aims to estimate the unknown parameters for the exponentiated Rayleigh distribution using Type-I hybrid censored data under a step-stress model. The maximum likelihood and Bayes methods estimate the parameters and acceleration factor. The parameters’ approximate confidence intervals are created. The Bayes estimates of the parameters for the squared error and linear exponential loss functions are computed using the Markov Chain Monte Carlo (MCMC) method. Finally, we perform a simulation study to evaluate the effectiveness of the proposed estimators. We provide a real-life data example (Strength data measurement in GPA, for single and impregnated carbon fibers) to explain the obtained results.OPEN ACCESS Received: 15/04/2025 Accepted: 21/08/2025 Published: 27/10/2025

  Abstract
  This paper aims to estimate the unknown parameters for the exponentiated Rayleigh distribution using Type-I hybrid censored data under a step-stress model. The maximum likelihood [...]

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