Computation

19 pages, 738 KiB

Open AccessArticle

A Novel Methodology for Scrutinizing Periodic Solutions of Some Physical Highly Nonlinear Oscillators

by Gamal M. Ismail, Galal M. Moatimid, Stylianos V. Kontomaris and Livija Cveticanin

Computation 2025, 13(5), 105; https://doi.org/10.3390/computation13050105 - 28 Apr 2025

Viewed by 20

The study offers a comprehensive investigation of periodic solutions in highly nonlinear oscillator systems, employing advanced analytical and numerical techniques. The motivation stems from the urgent need to understand complex dynamical behaviors in physics and engineering, where traditional linear approximations fall short. This work precisely applies He’s Frequency Formula (HFF) to provide theoretical insights into certain classes of strongly nonlinear oscillators, as illustrated through five broad examples drawn from various scientific and engineering disciplines. Additionally, the novelty of the present work lies in reducing the required time compared to the classical perturbation techniques that are widely employed in this field. The proposed non-perturbative approach (NPA) effectively converts nonlinear ordinary differential equations (ODEs) into linear ones, equivalent to simple harmonic motion. This method yields a new frequency approximation that aligns closely with the numerical results, often outperforming existing approximation techniques in terms of accuracy. To aid readers, the NPA is thoroughly explained, and its theoretical predictions are validated through numerical simulations using Mathematica Software (MS). An excellent agreement between the theoretical and numerical responses highlights the robustness of this method. Furthermore, the NPA enables a detailed stability analysis, an area where traditional methods frequently underperform. Due to its flexibility and effectiveness, the NPA presents a powerful and efficient tool for analyzing highly nonlinear oscillators across various fields of engineering and applied science. Full article

(This article belongs to the Special Issue Numerical Simulation of Nanofluid Flow in Porous Media)

24 pages, 3375 KiB

Open AccessArticle

Fractional-Order Modeling of Sediment Transport and Coastal Erosion Mitigation in Shorelines Under Extreme Climate Conditions: A Case Study in Iraq

by Ibtisam Aldawish and Rabha W. Ibrahim

Computation 2025, 13(5), 104; https://doi.org/10.3390/computation13050104 - 27 Apr 2025

Viewed by 55

Abstract

Coastal erosion and sediment transport dynamics in Iraq’s shoreline are increasingly affected by extreme climate conditions, including rising sea levels and intensified storms. This study introduces a novel fractional-order sediment transport model, incorporating a modified gamma function-based differential operator to accurately describe erosion rates and stabilization effects. The proposed model evaluates two key stabilization approaches: artificial stabilization (breakwaters and artificial reefs) and bio-engineering solutions (coral reefs, sea-grass, and salt marshes). Numerical simulations reveal that the proposed structures provide moderate sediment retention but degrade over time, leading to diminishing effectiveness. In contrast, bio-engineering solutions demonstrate higher long-term resilience, as natural ecosystems self-repair and adapt to changing environmental conditions. Under extreme climate scenarios, enhanced bio-engineering retains 55% more sediment than no intervention, compared to 35% retention with artificial stabilization.The findings highlight the potential of hybrid coastal protection strategies combining artificial and bio-based stabilization. Future work includes optimizing intervention designs, incorporating localized field data from Iraq’s coastal zones, and assessing cost-effectiveness for large-scale implementation. Full article

► Show Figures

Figure 1

31 pages, 1874 KiB

Open AccessArticle

Parallel Simulation Using Reactive Streams: Graph-Based Approach for Dynamic Modeling and Optimization

by Oleksii Sirotkin, Arsentii Prymushko, Ivan Puchko, Hryhoriy Kravtsov, Mykola Yaroshynskyi and Volodymyr Artemchuk

Computation 2025, 13(5), 103; https://doi.org/10.3390/computation13050103 - 26 Apr 2025

Viewed by 75

Abstract

Modern computational models tend to become more and more complex, especially in fields like computational biology, physical modeling, social simulation, and others. With the increasing complexity of simulations, modern computational architectures demand efficient parallel execution strategies. This paper proposes a novel approach leveraging the reactive stream paradigm as a general-purpose synchronization protocol for parallel simulation. We introduce a method to construct simulation graphs from predefined transition functions, ensuring modularity and reusability. Additionally, we outline strategies for graph optimization and interactive simulation through push and pull patterns. The resulting computational graph, implemented using reactive streams, offers a scalable framework for parallel computation. Through theoretical analysis and practical implementation, we demonstrate the feasibility of this approach, highlighting its advantages over traditional parallel simulation methods. Finally, we discuss future challenges, including automatic graph construction, fault tolerance, and optimization strategies, as key areas for further research. Full article

(This article belongs to the Section Computational Engineering)

15 pages, 1206 KiB

Open AccessArticle

A Simplified Fish School Search Algorithm for Continuous Single-Objective Optimization

by Elliackin Figueiredo, Clodomir Santana, Hugo Valadares Siqueira, Mariana Macedo, Attilio Converti, Anu Gokhale and Carmelo Bastos-Filho

Computation 2025, 13(5), 102; https://doi.org/10.3390/computation13050102 - 25 Apr 2025

Viewed by 88

Abstract

The Fish School Search (FSS) algorithm is a metaheuristic known for its distinctive exploration and exploitation operators and cumulative success representation approach. Despite its success across various problem domains, the FSS presents issues due to its high number of parameters, making its performance susceptible to improper parameterization. Additionally, the interplay between its operators requires a sequential execution in a specific order, requiring two fitness evaluations per iteration for each individual. This operator’s intricacy and the number of fitness evaluations pose the issue of costly fitness functions and inhibit parallelization. To address these challenges, this paper proposes a Simplified Fish School Search (SFSS) algorithm that preserves the core features of the original FSS while redesigning the fish movement operators and introducing a new turbulence mechanism to enhance population diversity and robustness against stagnation. The SFSS also reduces the number of fitness evaluations per iteration and minimizes the algorithm’s parameter set. Computational experiments were conducted using a benchmark suite from the CEC 2017 competition to compare the SFSS with the traditional FSS and five other well-known metaheuristics. The SFSS outperformed the FSS in 84% of the problems and achieved the best results among all algorithms in 10 of the 26 problems. Full article

► Show Figures

Figure 1

Journal Menu

Journal Browser

Computation, Volume 13, Issue 5 (May 2025) – 4 articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI