Documents published in Scipedia

• Evaluation and Optimization of High Collapse Resistance Casing Strings for Salt Cavern Gas Storage in Salt Formations

  G. Zhu, W. Wang, H. Diao, F. Ban, H. Xiong, X. Hou, X. Liu, T. Ma

  Rev. int. métodos numér. cálc. diseño ing. (2026). Vol. 42, (1), 9

  
  

  Abstract

  Salt cavern gas storage imposes stringent requirements on casing performance due to salt rock creep and high in-situ stress, necessitating a balance between mechanical strength and economic viability. This study evaluates the collapse resistance of BG110V and BG140V casings under 50°C–85°C through full-scale experiments (ASTM E2948) and elastoplastic finite element simulations. Results show that BG140V achieves a collapse strength of 75.94 MPa at 85°C, surpassing BG110V (52.96 MPa) at the same temperature by 43.4%, attributed to its thick-walled design (17.50 mm vs. BG110V’s 15.88 mm) and material enhancements. Simulations reveal lower prediction errors for BG140V (5.9% in full collapse) compared to BG110V (20.6%). A multi-criteria model integrating collapse strength (0.5), temperature sensitivity (0.3), and life-cycle cost (LCC, 0.2) with Monte Carlo analysis demonstrates BG140V’s LCC advantage in deep reservoirs (creep rate > 1.2× 10−7s−1, 12% maintenance cost reduction), while BG110V suits shallow scenarios (18% lower procurement cost). Dynamic selection strategies with real-time monitoring, low-friction thread optimization, crystal plasticity simulations, and smart maintenance systems are proposed. This study provides a quantitative framework for balancing safety and economy, advancing the standardization of non-API casings.OPEN ACCESS Received: 30/06/2025 Accepted: 19/08/2025 Published: 23/01/2026

  Abstract
  Salt cavern gas storage imposes stringent requirements on casing performance due to salt rock creep and high in-situ stress, necessitating a balance between mechanical strength [...]

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• Analysis of Airflow Velocity on Microdroplets Using Weibull StressStress Reliability Index under Unified Type-I Progressive Hybrid Data

  M. Nassar, R. Alotaibi, A. Elshahhat

  Rev. int. métodos numér. cálc. diseño ing. (2026). Vol. 42, (1), 10

  
  

  Abstract

  This work presents a novel and comprehensive inferential framework for analyzing the stress-strength reliability parameter,R= P(Y < X), where X and Y denote independent stress and strength variables, respectively, both modeled as Weibull-distributed with a shared shape parameter but distinct scale parameters. A key innovation of this study lies in its integration of the unified Type-I progressively hybrid censoring scheme, which simultaneously accommodates time constraints and partial failure information, conditions often encountered in real-world reliability testing. To estimate R, we propose and evaluate four distinct inferential strategies: two frequentist (maximum likelihood estimation and maximum spacings estimation) and two Bayesian, each tailored to either the likelihood or spacings-based posterior formulation. The Bayesian methods employ Monte Carlo sampling to compute both Bayes point estimates and credible intervals under informative priors, offering robustness in small-sample or heavily censored contexts. An extensive simulation study is conducted to systematically compare the estimators in terms of bias, efficiency, and interval coverage. To validate the practical applicability of our framework, we further analyze two real-world microdroplet datasets, revealing critical insights into stress-tolerance behavior under experimental constraints. This study not only advances methodological tools for reliability inference under hybrid censoring but also establishes a blueprint for combining classical and Bayesian paradigms in stress-strength modeling.OPEN ACCESS Received: 01/07/2025 Accepted: 02/09/2025 Published: 23/01/2026

  Abstract
  This work presents a novel and comprehensive inferential framework for analyzing the stress-strength reliability parameter,R= P(Y < X), where X and Y denote independent [...]

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• Classical and Bayesian Stress-Strength Reliability Estimation for Weibull Data under Unified Hybrid Censoring Scheme with LED Application

  M. Nassar, R. Alotaibi, A. Elshahhat

  Rev. int. métodos numér. cálc. diseño ing. (2026). Vol. 42, (1), 8

  
  

  Abstract

  The stress-strength reliability parameter is a key metric used in various fields, including engineering, medicine, and business. In engineering, it quantifies the probability that a system’s strength X exceeds the applied stress Y . In this study, we examine for the first time four estimation approaches for evaluating the stress-strength reliability parameter R= P(Y < X ), where X and Y are independent Weibull random variables with different scale parameters but a common shape parameter. The analysis is conducted under a unified hybrid censoring scheme. From the classical perspective, we employ the maximum likelihood and maximum product of spacings methods to obtain both point and interval estimates. From the Bayesian perspective, two forms of the posterior distribution, based on the likelihood and spacings functions, are derived and analyzed using Markov Chain Monte Carlo sampling techniques. The Bayes estimates of R are obtained under the symmetric squared error loss, and the corresponding Bayesian credible intervals are also computed. To compare the four point estimators and the four interval estimators, an extensive simulation study is performed using various experimental scenarios. Finally, comprehensive analyses for organic white light-emitting diode datasets mixed with three colors, namely red, green, and blue, are provided.OPEN ACCESS Received: 29/06/2025 Accepted: 16/09/2025 Published: 23/01/2026

  Abstract
  The stress-strength reliability parameter is a key metric used in various fields, including engineering, medicine, and business. In engineering, it quantifies the probability [...]

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• Numerical Investigation on Condensation of Non-Condensable Gas in Large Deformation Enhanced Tube

  Y. Zhang, T. Zheng, X. Zhang

  Rev. int. métodos numér. cálc. diseño ing. (2026). Vol. 42, (1), 7

  
  

  Abstract

  In order to improve the condensation heat transfer performance of tubelines in cooling systems, a new type of large deformation heat transfer tube was proposed. Based on the theory of diffusion, the distributions of temperature, velocity, heat transfer coefficient, and species are presented to compare with smooth tubes. In addition, the effects of relevant parameters on thermo-hydraulic performance are discussed. The numerical results show that the distributions of temperature and velocity show a periodic distribution. The unique structure of the large deformation heat transfer tube disturbs the fluid flow near the wall. The boundary layer of air concentration is destroyed, resulting in heat transfer enhancement. Within the scope of this paper, the heat transfer coefficient and friction factor of the large deformation heat transfer tube are increased by 1.01–3.47 times and 1.05–7.13 times compared with the smooth tube. The heat transfer performance increases with the rising dimple depth and declining noncondensable gas content and dimple pitch.OPEN ACCESS Received: 25/06/2025 Accepted: 29/07/2025 Published: 23/01/2026

  Abstract
  In order to improve the condensation heat transfer performance of tubelines in cooling systems, a new type of large deformation heat transfer tube was proposed. Based on the [...]

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• Reconfigurable Solar-Powered Multiple Input Multiple Output Terahertz Antenna System

  N. Sharma, A. Pandey, A. De

  Rev. int. métodos numér. cálc. diseño ing. (2026). Vol. 42, (1), 6

  
  

  Abstract

  The rapid evolution of terahertz (THz) technology has opened new frontiers in high-speed wireless communication, imaging, and sensing. However, the practical deployment of THz systems, particularly in remote or space-constrained environments, is often limited by power constraints and rigid antenna structures. A reconfigurable THz antenna system that is powered by solar energy is suggested. By leveraging real-time energy harvesting, the antenna system maintains operation without external power sources, making it ideal for deployment in remote IoT nodes, CubeSats, or energy-constrained sensor networks. Material used in antenna design is lead glass while gold is used as a radiator, the MIMO antenna loaded with graphene with chemical potential of graphene= 0 works from 2.4–2.5 THz, 3.87–3.98 THz, and 5.17–5.3 THz. The MIMO antenna with graphene chemical potential= 1 eV works from 2.54–2.63 THz, 3.96–4.1 THz, and 5.27–5.45 THz. The MIMO antenna with graphene chemical potential= 2 eV works from 2.6–2.68 THz, 4–4.2 THz, and 5.3–5.55 THz. Gain of antenna at 2.45, 3.95, and 5.3 THz maximum gain obtained at these frequencies is 6, 5 and 7 dBi, respectively. By integrating real-time solar energy harvesting with a tunable THz antenna structure, the design enables self-sustained, high-efficiency operation for remote IoT nodes, CubeSats, and energy-constrained sensor networks, merging green energy and next-generation THz communication in a compact platform. Advantages of the proposed design are self-powered operation, reconfigurable multi-band tuning, high gain, and suitability for diverse THz applications.OPEN ACCESS Received: 23/06/2025 Accepted: 17/09/2025 Published: 23/01/2026

  Abstract
  The rapid evolution of terahertz (THz) technology has opened new frontiers in high-speed wireless communication, imaging, and sensing. However, the practical deployment of [...]

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• Multi-Objective Optimization and Performance Evaluation of Manifold-Based Cooling Systems for Battery Thermal Management Using RSM and NSGA-II

  H. ZHANG, P. Ganesan, W. Chong, M. Zubir

  Rev. int. métodos numér. cálc. diseño ing. (2026). Vol. 42, (1), 5

  
  

  Abstract

  Efficient thermal management is critical to the safety, performance, and longevity of lithium-ion battery (LIB) energy storage systems. In this study, a novel manifold cold plate featuring an overflow channel with a triangular ridge at the bottom is proposed for a liquid-cooled Battery Thermal Management System (BTMS). A comprehensive multi-objective optimization framework is developed by integrating Response Surface Methodology (RSM), the Non-dominated Sorting Genetic Algorithm II (NSGA-II), and the Linear Programming Technique forMultidimensional Analysis of Preference (LINMAP) decision-making method to minimize the maximum temperature difference (Tcell) and pressure drop (P) across the cooling plate.Thedesign variables include the manifold channel width ratio (λ), the height ratio (φ), the inlet velocity (u), and the triangular ridge angle (θ). Second-order polynomial regression models are constructed and validated using Analysis ofVariance (ANOVA), yielding high coefficients of determination (R2 = 0.9926 forTcell and 0.9600 forP), confirming strong predictive accuracy. Sensitivity analysis reveals that the inlet velocity and channel angle are the primary factors influencing system performance. The LINMAP-based decision-making approach identifies an optimal configuration with λ = 1.031, φ = 1.47, u = 1.671 m/s, and θ = 29.8°, achieving a Tcell of 12.61°C and a P of 6742.99 Pa, with validation errors below 3%. Transient simulations at 0.5 and 1C discharge rates show that the LINMAP-optimized design reduces the maximumcell temperature by 13.12°C and 11.77°C, respectively, compared to the natural convection baseline, and by 1.42°C and 0.76°C compared to the prototype design, while maintaining comparable hydraulic resistance. This work offers valuable guidance for designing and optimizing liquid-cooled battery

  Abstract
  Efficient thermal management is critical to the safety, performance, and longevity of lithium-ion battery (LIB) energy storage systems. In this study, a novel manifold cold [...]

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• Analysis of Burr-XII Lifespan Using Adaptive Progressive Type-II Hybrid Binomial Censoring with Physical Modeling of Polyester and Carbon Fibers

  R. Alotaibi, H. Rezk, A. Elshahhat

  Rev. int. métodos numér. cálc. diseño ing. (2026). Vol. 42, (1), 4

  
  

  Abstract

  This study introduces advanced statistical methods, allowing for more efficient and accurate reliability testing of fibers such as polyester and carbon. Polyester ficbers are suitable for textiles and industrial use due to their wrinkle resistance and affordability, while carbon fibers offer superior strength, thermal stability, and corrosion resistance. To guarantee greater efficiency of inference methodologies and reduce overall testing time, the adaptive Type-II progressive hybrid censoring via binomial removals has gained popularity in reliability analysis and life-testing problems. The proposed scheme allows survival units to be removed at random stages according to a binomial law, thereby reducing experimental time while preserving statistical efficiency. When lifetimes are gathered using the suggested censoring technique, point and interval estimates of the unknown parameters of the Burr-XII model are obtained using both classical and Bayesian approaches. We obtain various Bayesian estimates using the squared loss function. Some numerical methods are employed to obtain the suggested estimators due to their complexity. The various Bayes estimates and related credible intervals are created using Markov chain Monte Carlo techniques. To assess estimator performance, extensive simulation studies are conducted, comparing bias, mean squared error, coverage probabilities, and interval lengths under varying censoring and removal settings. The simulation results confirm that the Bayesian framework, particularly with informative priors, provides more accurate and stable estimates than asymptotic likelihood-based methods. We examine two physics data sets representing polyester and carbon fibers to demonstrate the relevance of the suggested approaches in a real-world setting. These applications highlight the practical value of the proposed approach for material design, maintenance planning, and broader reliability engineering problems.OPEN ACCESS Received: 13/06/2025 Accepted: 12/09/2025 Published: 23/01/2026

  Abstract
  This study introduces advanced statistical methods, allowing for more efficient and accurate reliability testing of fibers such as polyester and carbon. Polyester ficbers [...]

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• AI-Driven Multi-Dimensional Computing Power Scheduling: Adaptive Resource Coordination via Task Demand Prediction in Heterogeneous Clusters

  T. Wang, X. Zhao, X. Qiao, S. Li, W. Yin

  Rev. int. métodos numér. cálc. diseño ing. (2026). Vol. 42, (1), 2

  
  

  Abstract

  This paper introduces an AI-driven computing power scheduling framework that innovatively integrates multidimensional resource optimization with machine-learning-based task-demand prediction to significantly enhance computational efficiency and resource utilization. Unlike prior works that primarily focus on Graphics Processing Unit (GPU) allocation, our method pioneers a holistic resource-coordination mechanism that dynamically balances GPU, memory, Central Processing Unit (CPU), and other critical resources according to their joint impact on task performance and cluster efficiency. A core innovation is our data-driven resource predictor, which autonomously analyzes historical task patterns and forecasts future demand, enabling the scheduler to adaptively scale resources so that user over-provisioning is reduced and under-allocation bottlenecks are avoided. Experimental validation demonstrates that this closed-loop prediction–scheduling paradigm achieves breakthroughs in both scale and efficiency: a 25.7% increase in concurrent task deployment, a 15.6% increase in task completion rate, and substantial relative utilization improvements of 7.5% for GPU and 8.0% for memory, outperforming conventional single-resource optimization approaches. These advancements establish a new direction for intelligent resource management in large-scale heterogeneous computing environments.OPEN ACCESS Received: 15/05/2025 Accepted: 11/10/2025 Published: 23/01/2026

  Abstract
  This paper introduces an AI-driven computing power scheduling framework that innovatively integrates multidimensional resource optimization with machine-learning-based task-demand [...]

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• Statistical Inference of Step Stress Partially Accelerated Life-Testing for Insulating Fluid between Electrodes under Censored Data and Different Loss Functions

  R. Alotaibi, H. Rezk, E. Almetwally

  Rev. int. métodos numér. cálc. diseño ing. (2026). Vol. 42, (1), 3

  
  

  Abstract

  Long testing times are usually required for the life testing of very reliable products or materials. The testing process can be hastened by using accelerated life tests. The lifespan of the items that accelerated life tests inspect is reduced since they test products in more severe circumstances than those found in regular use scenarios. Data that was censored and disclosed the precise timings of failure may point to accelerated life tests where all units assigned to test are unknown, or where all units assigned to test have not failed for a few reasons, including challenges with technology, tools, costs, and schedules. The step-stress partially accelerated life test was examined in this work using the type-I progressive hybrid censoring scheme and the type-II progressive censoring scheme. The influence of the stress shift is explained using the tempered random variable model, where the failure times of the items are assumed to follow the alpha power Lomax distribution. The unknown parameters are estimated using the maximum likelihood estimation and Bayesian methods. The asymptotic theory of maximum likelihood estimation is also employed in the construction of the approximate confidence intervals. While the point estimates under two censoring schemes are compared in terms of absolute biases and root mean squared errors, approximate confidence intervals and coverage probabilities are compared in terms of their lengths and coverage probabilities. Additionally, three possible optimal test strategies are investigated using different optimal criteria. The performance of the estimators was evaluated and contrasted with two censoring techniques with various sample sizes using a simulation study. Finally, a numerical example for insulating fluid between electrodes data is presented to illustrate how the methods will work in real-world scenarios.OPEN ACCESS Received: 11/06/2025 Accepted: 29/07/2025 Published: 23/01/2026

  Abstract
  Long testing times are usually required for the life testing of very reliable products or materials. The testing process can be hastened by using accelerated life tests. The [...]

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• Numerical Simulation Analysis of Influence of Wind and Temperature on Deformation of Constructed Zhaidi River High Bridge Pier

  M. Tian, J. Sun, X. Chen, F. Xiong

  Rev. int. métodos numér. cálc. diseño ing. (2026). Vol. 42, (1), 1

  
  

  Abstract

  Bridges are key projects of high-grade Expressways in mountainous areas. The verticality of bridge piers with a height of more than 100 m is crucial to ensure the safety and stability of bridge projects. When a pier construction is completed but the upper beam structure has not yet been connected (socalled after construction or constructed), the verticality of the pier is most likely to vary due to some factors. Based on the Zhaidi River Bridge project of Yunnan Zhenhe Expressway, considering the natural environment of the bridge site, three wind force intensity levels (Beaufort Scale 8, 10, and 12) and two climate conditions (high temperature and high radiation in summer, and low temperature and low radiation in winter) were identified; and the wind-induced deformation, temperature-induced deformation, and wind-temperature coupled deformation of the constructed main pier of the Zhaidi River Bridge with a height of 112.60 m were simulated with ANSYS Workbench numerical simulation platform. The simulation results show that: the influence of wind on pier deformation is much greater than that of ambient temperature variation; the influence of solar radiation on temperature-induced deformation of the bridge pier is much greater than that of air temperature variation; the temperature-induced deformation of the pier body under low temperature and low radiation condition in winter is greater than that under high temperature and high radiation condition in summer; the directional effect of the superposition of wind-induced deformation and temperature-induced deformation is more significant under low temperature and low radiation condition in winter.OPEN ACCESS Received: 11/04/2025 Accepted: 16/10/2025 Published: 23/01/2026

  Abstract
  Bridges are key projects of high-grade Expressways in mountainous areas. The verticality of bridge piers with a height of more than 100 m is crucial to ensure the safety and [...]

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