Documents published in Scipedia

• Computational Analysis of Newly Topp-Leone Data Using Adaptive Progressive Type-II Censoring and Its Applications in Medical and Industrial Sciences

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

  Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (3), 56

  
  

  Abstract

  Reliability analysis is critical in various scientific fields, necessitating robust lifetime models that effectively capture real-world failure mechanisms. This work explores a novel extension of the classical ToppLeone (TL) lifespan model, called the generalized-TL (GTL) distribution, when datasets are gathered from adaptive progressive Type-II censoring. This model is highly superior for analyzing complex lifetime data with diverse hazard rate structures, including decreasing, increasing, and bathtub-shaped patterns. Employing both likelihood and Bayes estimation approaches, this work attempts to infer the unknown parameters and the reliability and failure rate functions of the GTL model. The Bayesian inference is created using the squared-error loss and independent gamma assumptions. Asymptotic and credible intervals are also established for each unknown quantity. Since the posterior density is complicated, the Markov chain using the Monte Carlo approach is utilized to get information from the whole marginal posterior densities and thus assess the acquired Bayesian point and interval estimations. Using four optimality criteria, the optimum censoring is given among competing progressive techniques. The effectiveness of the offered estimations is tested against numerous parameters using comprehensive Monte Carlo comparisons. Lastly, the practical utility of the GTL model is demonstrated through two applications using different real-world datasets collected from veterinary medicine and engineering reliability studies. Our findings state that the Bayes’ setup outperforms classical approaches, particularly in smallsample settings, making the proposed methodology flexible and beneficial in concluding the study when the researcher’s foremost concern is the total number of failed items.OPEN ACCESS Received: 29/03/2025 Accepted: 21/05/2025 Accepted: 22/09/2025

  Abstract
  Reliability analysis is critical in various scientific fields, necessitating robust lifetime models that effectively capture real-world failure mechanisms. This work explores [...]

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• Surface Settlement of Small Clear Distance Tunnel in Soft Soil Layer during Shield Propulsion

  X. Zhao, S. Wu, F. Jiang, S. Chen

  Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (3), 55

  
  

  Abstract

  Shield tunneling has become a widely adopted method for urban underground transport construction. However, research on the impact of small-clearance shield tunnel construction in urban soft soil layers is still in its early stages. Understanding the effects of such construction on surface settlement and summarizing temporal settlement patterns is crucial for reducing construction risks and minimizing disturbances to the surrounding areas. This paper investigates the impact of two-lane small-clearance tunneling on surface settlement through finite element modeling and analysis, focusing on the Nanjing Heyan Road Crossing as a case study. The study also evaluates the feasibility of different construction distances in successive two-lane shield tunneling. Numerical simulations and on-site measurements were conducted to explore the surface settlement behavior under varying construction distances. The research examines the vertical and lateral settlement characteristics in the backfilled area, located 32 m from the tunnel initiation well. The findings reveal the settlement behavior throughout the shield tunneling process under different construction distances. The results indicate that the vertical settlement profiles of shield tunnel construction in soft soil layers conform to the Mindlin settlement curve, while the lateral settlement profiles follow the double-funnel Peck curves. Additionally, the closer the construction distance between the two tunnels, the greater the disturbance to the ground surface, whereas increasing the construction distance results in higher peak surface settlement. Soil settlement around the tunnel is significantly affected by construction disturbances, structural stiffness, lateral unloading bias, the extrusion effect of tube sheet weight, and shield machine movement. The use of synchronous grouting effectively mitigates excessive surface settlement. This study provides valuable insights and serves as a reference for similar shield tunnel construction projects in urban soft soil layers.OPEN ACCESS Received: 18/03/2025 Accepted: 16/05/2025 Published: 22/09/2025

  Abstract
  Shield tunneling has become a widely adopted method for urban underground transport construction. However, research on the impact of small-clearance shield tunnel construction [...]

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• Statistical Analysis of Progressive Interval Type-I Partially Accelerated Test and Its Inspection of Optimum Periods

  R. Alotaibi, C. Park, H. Rezk, A. Elshahhat

  Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (3), 54

  
  

  Abstract

  This study explores a general framework for reliability analysis named progressive interval Type-I censoring within a multi-stage step-stress partially accelerated life testing setting. A more flexible alternative to the traditional exponential model, known as the length-biased exponential (LBE) distribution, is employed to model failure times. Due to its symmetrical feature, it has extensive applications in real-world domains such as survival analysis, actuarial science, reliability, and mathematical finance. The maximum likelihood approach of estimation is utilized to estimate the model parameters, along with bootstrapping techniques to assess estimation efficiency. Confidence intervals for the LBE parameters are also derived based on asymptotic variances. To optimize the inspection period, two competing optimality criteria—variance minimization (Varoptimality) and determinant maximization (D-optimality)—are investigated. A comprehensive Monte Carlo simulation study is conducted to evaluate the performance of different estimation strategies, demonstrating the superiority of the proposed methodology. Steel is particularly valued for its toughness, wear resistance, and hardness, all of which can be significantly modified through heat treatment and annealing processes. So, a real-world application using hardened steel failure data validates the practical relevance of the developed inferential framework. The findings offer valuable insights for statisticians and reliability engineers in designing efficient life-testing experiments under constrained resources.OPEN ACCESS Received: 21/03/2025 Accepted: 07/05/2025 Published: 22/09/2025

  Abstract
  This study explores a general framework for reliability analysis named progressive interval Type-I censoring within a multi-stage step-stress partially accelerated life testing [...]

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• Numerical Simulation Analysis on the Stress and Strain Behavior of Composite Geomembrane in Rigid Landfill

  M. Huang, T. Tu, Y. Jiang, F. Yang

  Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (3), 53

  
  

  Abstract

  In order to investigate the stress characteristics of a composite geomembrane during the operation of a rigid landfill, a three-dimensional finite element model was developed for a specific rigid landfill project in Tongling China. This model takes into account the contact behavior between the composite geomembrane and concrete unit pool. It aims to calculate and analyze the distribution of stress and strain in both the composite geomembrane and rigid landfill under various working conditions, including empty and full storage. At the same time, the influence of the change of friction coefficient between the composite geomembrane and the concrete cell pool on the stress and strain of the geomembrane is analyzed under the condition of full reservoir. The results indicate that the stress and displacement distribution of the composite geomembrane and concrete structures in the landfill site remain reasonable and safe before and after transitioning from empty to full storage. Under critical conditions, specifically when the cell pool is fully loaded, significant tensile stress and strain occur at the top anchorage of the pool, the edge of the pool bottom, and the corners of the cell pool. The tensile stress in the concrete structure is notably higher at the junction between the side walls and the bottom floor of the cell pool, while compressive stress is more pronounced at the connection between the frame columns of the lower maintenance layer and the bottom floor of the cell pool. Increasing the friction between the composite geomembrane and the concrete cell pool can effectively mitigate stress concentration in the composite geomembrane, thereby enhancing the structural stability and safety.OPEN ACCESS Received: 14/03/2025 Accepted: 21/05/2025 Published: 22/09/2025

  Abstract
  In order to investigate the stress characteristics of a composite geomembrane during the operation of a rigid landfill, a three-dimensional finite element model was developed [...]

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• Existence and Uniqueness Results for a Class of Backward Neutral Fractional Differential Equations

  S. Abusalim

  Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (3), 52

  
  

  Abstract

  In this work, we investigate the existence and uniqueness results (EUR) for a class of neutral fractional differential equations (FDEs) with time advance, incorporating the Caputo derivative concerning. By employing the fixed-point theory, we establish rigorous criteria ensuring the wellposedness of the problem. Additionally, we explore the Ulam-Hyers stability properties of the proposed model, providing a comprehensive analysis of its dynamic behavior. To further support our theoretical findings, we present two examples that illustrate the applicability and effectiveness of the obtained results. These findings contribute to the growing body of research on FDEs and their applications in various scientific and engineering fields.OPEN ACCESS Received: 24/03/2025 Accepted: 29/05/2025 Published: 22/09/2025

  Abstract
  In this work, we investigate the existence and uniqueness results (EUR) for a class of neutral fractional differential equations (FDEs) with time advance, incorporating the [...]

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• Neural Network Model Predictive Control Applied to Parafoil under Turbulence Wind Field

  J. Li, H. Sun, Q. Sun

  Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (3), 51

  
  

  Abstract

  In the field of parafoil flight control, a critical challenge is managing the complex control requirements and mitigating the effects of turbulenceinduced disturbances. This paper explores the intricacies of parafoil control and the influence of the turbulent wind field on system performance. To address the challenges, we propose a Neural Network Model Predictive Control (NNMPC) strategy that utilizes extensive historical operational data, including flight attitude records from multiple flights and control responses under various wind conditions, to develop a neural network model as an alternative to traditional 3-degree-of-freedom (3DOF) models. The proposed approach integrates a NARX (Nonlinear AutoRegressive with Exogenous inputs) neural network into the Model Predictive Control(MPC) framework, leveraging its temporal modeling capabilities to improve prediction accuracy and enhance disturbance rejection. Experimental validation was performed in a simulated turbulence environment using the Dryden turbulence model, with carefully designed control groups in which both traditional MPC and NNMPC were tested under identical initial conditions and target trajectories. The results demonstrate that NNMPC achieves superior trajectory tracking performance, indicating its potential for robust parafoil control in complex atmospheric conditions.OPEN ACCESS Received: 06/03/2025 Accepted: 06/05/2025 Published: 22/09/2025

  Abstract
  In the field of parafoil flight control, a critical challenge is managing the complex control requirements and mitigating the effects of turbulenceinduced disturbances. This [...]

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• Computational Investigation of Novel Half-Normal Data Using Improved Type-II Adaptive Progressive Censoring and Its Application to the Shasta Reservoir

  O. Alqasem, M. Nassar, M. Elwahab, A. Elshahhat

  Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (3), 50

  
  

  Abstract

  Shasta Reservoir is the largest in California, formed by Shasta Dam on the Sacramento River, and plays a major role in the Central Valley Project (CVP) by providing water storage, flood control, hydroelectric power, and irrigation. This study employs advanced statistical methods to evaluate the reservoir’s reliability and operational risks using censored hydrological data. We propose an improved adaptive progressive censoring plan and apply established statistical techniques, maximum likelihood and maximum product of spacings, alongside Bayesian estimation. The Bayes estimates are obtained through the squared error loss function and based on two sources for the observed data, namely the likelihood and spacing functions. The focus is on estimating the distribution’s scale parameter and two critical reliability metrics: the reliability function and the hazard rate function. The approximate confidence intervals based on the two classical approaches of the scale parameter and reliability metrics are studied. The highest posterior density credible intervals are also discussed. A simulation study evaluates the model’s accuracy under diverse data scenarios, and its practical utility is demonstrated through real-world data from Shasta Reservoir. The problem of optimizing data collection strategies is discussed with the same real data. The findings underscore the model’s value in enhancing reservoir reliability assessments, offering actionable insights for hydrology, disaster preparedness, and sustainable resource management.OPEN ACCESS Received: 15/03/2025 Accepted: 12/06/2025 Published: 22/09/2025

  Abstract
  Shasta Reservoir is the largest in California, formed by Shasta Dam on the Sacramento River, and plays a major role in the Central Valley Project (CVP) by providing water [...]

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• A Novel Approach to Nonlinear Fractional Volterra-Fredholm Integro-Differential Equations via Caputo-Katugampola Operators

  M. Arab, A. Sharif

  Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (3), 49

  
  

  Abstract

  This paper aims to examine the solvability, uniqueness, and stability of a class of nonlinear implicit fractional Volterra-Fredholm integrodifferential equations involving the Caputo-Katugampola fractional derivative. The main objective is to establish rigorous conditions under which such equations admit unique solutions and to analyze their stability behavior under perturbations. Specifically, we apply Banach’s fixed-point theorem and a suitable form of the Gronwall inequality to derive sufficient criteria for existence and uniqueness. Furthermore, we investigate the stability of solutions in the sense of Ulam-Hyers and Ulam-Hyers-Rassias, providing a comprehensive understanding of the solution behavior under small deviations. To validate the theoretical results and highlight the applicability of the developed framework, a concrete illustrative example is included. This study contributes to the ongoing development of fractional calculus by deepening the theoretical understanding of fractional integrodifferential equations and expanding their potential for modeling complex dynamical systems in various applied sciences.OPEN ACCESS Received: 02/05/2025 Accepted: 19/06/2025 Published: 15/08/2025

  Abstract
  This paper aims to examine the solvability, uniqueness, and stability of a class of nonlinear implicit fractional Volterra-Fredholm integrodifferential equations involving [...]

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• Efficient Computing of Nonlinear Higher-Order Fractional Integro-Differential Equations via Aboodh-ADM Technique

  S. Trabelsi, M. Hamood

  Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (3), 48

  
  

  Abstract

  This paper introduces a novel semi-analytical method for solving nonlinear higher-order fractional Volterra-Fredholm integro-differential equations (FIDEs) of Hammerstein type. By combining the Aboodh transform with the Adomian Decomposition Method (ADM), the proposed approach efficiently handles Caputo fractional derivatives and nonlocal integral operators. The solution is derived as a rapidly convergent infinite series via the inverse Aboodh transform, offering analytical insight even in the absence of closed-form solutions. Rigorous stability analysis and convergence criteria are established, demonstrating the method’s numerical stability and confirming an algebraic order of convergence dependent on fractional order and discretization parameters. Truncated series solutions yield high-accuracy approximations, validated through numerical examples that highlight the method’s reliability, computational efficiency, and robustness for memory-dependent dynamics. The framework is broadly applicable to engineering and applied mathematics problems requiring precise modeling of nonlocal phenomena.OPEN ACCESS Received: 02/05/2025 Accepted: 25/06/2025 Published: 15/08/2025

  Abstract
  This paper introduces a novel semi-analytical method for solving nonlinear higher-order fractional Volterra-Fredholm integro-differential equations (FIDEs) of Hammerstein [...]

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• Physical and Biomedical Applications of a Newly Extended Version of the Log-Logistic Model Using AdaptiveProgressive Censored Sampling

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

  Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (3), 46

  
  

  Abstract

  This study explores an advanced three-parameter generalized log-logistic (GLL) model by incorporating an innovative shape parameter into the conventional log-logistic framework, allowing for greater flexibility in modeling data with increasing, decreasing, and bathtub-shaped failure rates. The estimation challenge under adaptive progressively TypeII censored data is addressed through both classical (likelihood-based) and Bayesian inferential methods. Utilizing observed Fisher information, asymptotic confidence intervals for unknown parameters are derived, while a Markov chain in the Monte Carlo approach is employed to obtain Bayesian point estimates and the highest posterior density intervals. In Bayes’ setup, the GLL parameters are presumed to have independent gamma conjugate priors against various symmetric and asymmetric losses. To examine the accuracy of the acquired estimators, an extensive Monte Carlo simulation is used. Four real-life data sets from the physical and biomedical industries are analyzed to illustrate the feasibility of the proposed techniques in an actual-world scenario. Numerical analyses revealed that the suggested model outperforms the other five models in the literature, including the alpha-power exponential, exponentiated exponential, log-logistic, Weibull, and gamma distributions. The findings emphasize the effectiveness of the Bayesian Markov chain Monte Carlo approach over frequentist techniques, reinforcing its practical significance in reliability analysis and survival studies.OPEN ACCESS Received: 27/03/2025 Accepted: 08/05/2025 Published: 15/08/2025

  Abstract
  This study explores an advanced three-parameter generalized log-logistic (GLL) model by incorporating an innovative shape parameter into the conventional log-logistic framework, [...]

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