Computation

42 pages, 4557 KB

Open AccessArticle

Adaptive Neural Network System for Detecting Unauthorised Intrusions Based on Real-Time Traffic Analysis

by Serhii Vladov, Victoria Vysotska, Vasyl Lytvyn, Anatolii Komziuk, Oleksandr Prokudin and Andrii Ostapiuk

Computation 2025, 13(9), 221; https://doi.org/10.3390/computation13090221 - 11 Sep 2025

Abstract

This article solves the anomalies’ operational detection in the network traffic problem for cyber police units by developing an adaptive neural network platform combining a variational autoencoder with continuous stochastic dynamics of the latent space (integration according to the Euler–Maruyama scheme), a continuous–discrete [...] Read more.

This article solves the anomalies’ operational detection in the network traffic problem for cyber police units by developing an adaptive neural network platform combining a variational autoencoder with continuous stochastic dynamics of the latent space (integration according to the Euler–Maruyama scheme), a continuous–discrete Kalman filter for latent state estimation, and Hotelling’s T² statistical criterion for deviation detection. This paper implements an online learning mechanism (“on the fly”) via the Euler Euclidean gradient step. Verification includes variational autoencoder training and validation, ROC/PR and confusion matrix analysis, latent representation projections (PCA), and latency measurements during streaming processing. The model’s stable convergence and anomalies’ precise detection with the metrics precision is ≈0.83, recall is ≈0.83, the F1-score is ≈0.83, and the end-to-end delay of 1.5…6.5 ms under 100…1000 sessions/s load was demonstrated experimentally. The computational estimate for typical model parameters is ≈5152 operations for a forward pass and ≈38,944 operations, taking into account batch updating. At the same time, the main bottleneck, the O(m³) term in the Kalman step, was identified. The obtained results’ practical significance lies in the possibility of the developed adaptive neural network platform integrating into cyber police units (integration with Kafka, Spark, or Flink; exporting incidents to SIEM or SOAR; monitoring via Prometheus or Grafana) and in proposing applied optimisation paths for embedded and high-load systems. Full article

(This article belongs to the Section Computational Engineering)

18 pages, 2934 KB

Open AccessArticle

A Method for Synthesizing Self-Checking Discrete Systems with Calculations Testing Based on Parity and Self-Duality of Calculated Functions

by Dmitry V. Efanov, Tatiana S. Pogodina, Nazirjan M. Aripov, Sunnatillo T. Boltayev, Asadulla R. Azizov, Elnara K. Ametova and Zohid B. Toshboyev

Computation 2025, 13(9), 220; https://doi.org/10.3390/computation13090220 - 11 Sep 2025

Abstract

Calculations testing can be effectively used in the construction of discrete self-checking devices. Calculations testing is based on the parity and self-duality of the calculated functions. This can be used for modern blocks and nodes of control systems for responsible technological processes. However, [...] Read more.

Calculations testing can be effectively used in the construction of discrete self-checking devices. Calculations testing is based on the parity and self-duality of the calculated functions. This can be used for modern blocks and nodes of control systems for responsible technological processes. However, its use has a number of features that must be considered when building concurrent error-detection circuits. The authors used methods of discrete mathematics and Boolean algebra as well as technical diagnostics of discrete systems to investigate the problem of ensuring the testability of the parity encoder. Theorems on the testability of convolution functions modulo 2 are proved. Considering these theorems allowed the authors of the article to propose a method for synthesizing CED circuits. This method increases the testability of the encoder for parity. This method is based on the use of two diagnostic signs at once. The first sign is that the code words belong to the parity code. The second is the self-dual control function in the concurrent error-detection circuit. This method is guaranteed to increase the testability of the parity coder compared to using one of the diagnostic signs for calculations testing. Experiments with testing discrete devices have shown the effectiveness of the organization structure of the concurrent error-detection circuit that we developed. The theorems that we proved form the basis of proof of similar provisions for the use of other linear codes in the synthesis of concurrent error-detection circuits. Our proposed solutions with calculations testing based on two diagnostic signs should be used in the synthesis of discrete systems. Discrete systems should be self-checking and have improved testability indicators. Full article

(This article belongs to the Section Computational Engineering)

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37 pages, 5162 KB

Open AccessArticle

Fourier–Gegenbauer Integral Galerkin Method for Solving the Advection–Diffusion Equation with Periodic Boundary Conditions

by Kareem T. Elgindy

Computation 2025, 13(9), 219; https://doi.org/10.3390/computation13090219 - 9 Sep 2025

Viewed by 105

Abstract

This study presents the Fourier–Gegenbauer integral Galerkin (FGIG) method, a new numerical framework that uniquely integrates Fourier series and Gegenbauer polynomials to solve the one-dimensional advection–diffusion (AD) equation with spatially symmetric periodic boundary conditions, achieving exponential convergence and reduced computational cost compared to [...] Read more.

This study presents the Fourier–Gegenbauer integral Galerkin (FGIG) method, a new numerical framework that uniquely integrates Fourier series and Gegenbauer polynomials to solve the one-dimensional advection–diffusion (AD) equation with spatially symmetric periodic boundary conditions, achieving exponential convergence and reduced computational cost compared to traditional methods. The FGIG method uniquely combines Fourier series for spatial periodicity and Gegenbauer polynomials for temporal integration within a Galerkin framework, resulting in highly accurate numerical and semi-analytical solutions. Unlike traditional approaches, this method eliminates the need for time-stepping procedures by reformulating the problem as a system of integral equations, reducing error accumulation over long-time simulations and improving computational efficiency. Key contributions include exponential convergence rates for smooth solutions, robustness under oscillatory conditions, and an inherently parallelizable structure, enabling scalable computation for large-scale problems. Additionally, the method introduces a barycentric formulation of the shifted Gegenbauer–Gauss (SGG) quadrature to ensure high accuracy and stability for relatively low Péclet numbers. This approach simplifies calculations of integrals, making the method faster and more reliable for diverse problems. Numerical experiments presented validate the method’s superior performance over traditional techniques, such as finite difference, finite element, and spline-based methods, achieving near-machine precision with significantly fewer mesh points. These results demonstrate its potential for extending to higher-dimensional problems and diverse applications in computational mathematics and engineering. The method’s fusion of spectral precision and integral reformulation marks a significant advancement in numerical PDE solvers, offering a scalable, high-fidelity alternative to conventional time-stepping techniques. Full article

(This article belongs to the Special Issue Advances in Computational Methods for Fluid Flow)

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26 pages, 16767 KB

Open AccessArticle

Effect of Heated Wall Corrugation on Thermal Performance in an L-Shaped Vented Cavity Crossed by Metal Foam Saturated with Copper–Water Nanofluid

by Luma F. Ali, Hussein Togun and Abdellatif M. Sadeq

Computation 2025, 13(9), 218; https://doi.org/10.3390/computation13090218 - 6 Sep 2025

Viewed by 168

Abstract

Practical applications such as solar power energy systems, electronic cooling, and the convective drying of vented enclosures require continuous developments to enhance fluid and heat flow. Numerous studies have investigated the enhancement of heat transfer in L-formed vented cavities by inserting heat-generating components, [...] Read more.

Practical applications such as solar power energy systems, electronic cooling, and the convective drying of vented enclosures require continuous developments to enhance fluid and heat flow. Numerous studies have investigated the enhancement of heat transfer in L-formed vented cavities by inserting heat-generating components, filling the cavity with nanofluids, providing an inner rotating cylinder and a phase-change packed system, etc. Contemporary work has examined the thermal performance of L-shaped porous vented enclosures, which can be augmented by using metal foam, using nanofluids as a saturated fluid, and increasing the wall surface area by corrugating the cavity’s heating wall. These features are not discussed in published articles, and their exploration can be considered a novelty point in this work. In this study, a vented cavity was occupied by a copper metal foam with

P P I = 10

and saturated with a copper–water nanofluid. The cavity walls were well insulated except for the left wall, which was kept at a hot isothermal temperature and was either non-corrugated or corrugated with rectangular waves. The Darcy–Brinkman–Forchheimer model and local thermal non-equilibrium models were adopted in momentum and energy-governing equations and solved numerically by utilizing commercial software. The influences of various effective parameters, including the Reynolds number (

20 \leq R e \leq 1000

), the nanoparticle volume fraction (

0 % \leq φ \leq 20 %

), the inflow and outflow vent aspect ratios (

0.1 \leq D / H \leq 0.4

), the rectangular wave corrugation number (

N = 5

and

N = 10

), and the corrugation dimension ratio (

C R = 1

and

C R = 0.5

) were determined. The results indicate that the flow field and heat transfer were affected mainly by variations in

R e

,

D / H

, and

φ

for a non-corrugated left wall; they were additionally influenced by

N

and

C R

when the wall was corrugated. The fluid- and solid-phase temperatures of the metal foam increased with an increase in

R e

and

D / H

. The fluid-phase Nusselt number near the hot left sidewall increased with an increase in

φ

by

(25 - 60) %

, while the solid-phase Nusselt number decreased by

(10 - 30) %

, and these numbers rose by around

3.5

times when the Reynolds number increased from

20

to

1000

. For the corrugated hot wall, the Nusselt numbers of the two metal foam phases increased with an increase in

R e

and decreased with an increase in

D / H

,

C R

, or

N

by

10 %

,

19 %

, and

37 %

. The original aspect of this study is its use of a thermal, non-equilibrium, nanofluid-saturated metal foam in a corrugated L-shaped vented cavity. We aimed to investigate the thermal performance of this system in order to reinforce the viability of applying this material in thermal engineering systems. Full article

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

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32 pages, 5016 KB

Open AccessReview

A Review on the Crashworthiness of Bio-Inspired Cellular Structures for Electric Vehicle Battery Pack Protection

by Tamana Dabasa, Hirpa G. Lemu and Yohannes Regassa

Computation 2025, 13(9), 217; https://doi.org/10.3390/computation13090217 - 5 Sep 2025

Viewed by 467

Abstract

The rapid shift toward electric vehicles (EVs) has underscored the critical importance of battery pack crashworthiness, creating a demand for lightweight, energy-absorbing protective systems. This review systematically explores bio-inspired cellular structures as promising solutions for improving the impact resistance of EV battery packs. [...] Read more.

The rapid shift toward electric vehicles (EVs) has underscored the critical importance of battery pack crashworthiness, creating a demand for lightweight, energy-absorbing protective systems. This review systematically explores bio-inspired cellular structures as promising solutions for improving the impact resistance of EV battery packs. Inspired by natural geometries, these designs exhibit superior energy absorption, controlled deformation behavior, and high structural efficiency compared to conventional configurations. A comprehensive analysis of experimental, numerical, and theoretical studies published up to mid-2025 was conducted, with emphasis on design strategies, optimization techniques, and performance under diverse loading conditions. Findings show that auxetic, honeycomb, and hierarchical multi-cell architectures can markedly enhance specific energy absorption and deformation control, with improvements often exceeding 100% over traditional structures. Finite element analyses highlight their ability to achieve controlled deformation and efficient energy dissipation, while optimization strategies, including machine learning, genetic algorithms, and multi-objective approaches, enable effective trade-offs between energy absorption, weight reduction, and manufacturability. Persistent challenges remain in structural optimization, overreliance on numerical simulations with limited experimental validation, and narrow focus on a few bio-inspired geometries and thermo-electro-mechanical coupling, for which engineering solutions are proposed. The review concludes with future research directions focused on geometric optimization, multi-physics modeling, and industrial integration strategies. Collectively, this work provides a comprehensive framework for advancing next-generation crashworthy battery pack designs that integrate safety, performance, and sustainability in electric mobility. Full article

(This article belongs to the Section Computational Engineering)

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Graphical abstract

21 pages, 3280 KB

Open AccessArticle

Predicting Properties of Imidazolium-Based Ionic Liquids via Atomistica Online: Machine Learning Models and Web Tools

by Stevan Armaković and Sanja J. Armaković

Computation 2025, 13(9), 216; https://doi.org/10.3390/computation13090216 - 4 Sep 2025

Viewed by 312

Abstract

Machine learning models and web-based tools have been developed for predicting key properties of imidazolium-based ionic liquids. Two high-quality datasets containing experimental density and viscosity values at 298 K were curated from the ILThermo database: one containing 434 systems for density and another [...] Read more.

Machine learning models and web-based tools have been developed for predicting key properties of imidazolium-based ionic liquids. Two high-quality datasets containing experimental density and viscosity values at 298 K were curated from the ILThermo database: one containing 434 systems for density and another with 293 systems for viscosity. Molecular structures were optimized using the GOAT procedure at the GFN-FF level to ensure chemically realistic geometries, and a diverse set of molecular descriptors, including electronic, topological, geometric, and thermodynamic properties, was calculated. Three support vector regression models were built: two for density (IonIL-IM-D1 and IonIL-IM-D2) and one for viscosity (IonIL-IM-V). IonIL-IM-D1 uses three simple descriptors, IonIL-IM-D2 improves accuracy with seven, and IonIL-IM-V employs nine descriptors, including DFT-based features. These models, designed to predict the mentioned properties at room temperature (298 K), are implemented as interactive applications on the atomistica.online platform, enabling property prediction without coding or retraining. The platform also includes a structure generator and searchable databases of optimized structures and descriptors. All tools and datasets are freely available for academic use via the official web site of the atomistica.online platform, supporting open science and data-driven research in molecular design. Full article

(This article belongs to the Special Issue Feature Papers in Computational Chemistry)

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17 pages, 3922 KB

Open AccessArticle

Time–Frequency Domain Analysis of the Ground Vibration of an Elevated Railway and Study on the Elliptic Polarization Dispersion Characteristics of Rayleigh Waves

by Shijie Liu, Yulan Song, Zhengping Liu, Zhe Liu and Qingling Du

Computation 2025, 13(9), 215; https://doi.org/10.3390/computation13090215 - 4 Sep 2025

Viewed by 246

Abstract

Elevated railways are a crucial component of railway lines, characterized by their widespread distribution, simple structure, and low cost, while actively promoting local economic development. However, they also cause significant ground vibrations when trains pass. Similarly, considerable vibration levels are transmitted to the [...] Read more.

Elevated railways are a crucial component of railway lines, characterized by their widespread distribution, simple structure, and low cost, while actively promoting local economic development. However, they also cause significant ground vibrations when trains pass. Similarly, considerable vibration levels are transmitted to the subgrade and surrounding structures when trains operate on viaducts within the Loess Plateau region. However, research on mitigating these vibration effects remains relatively scarce. This study focused on the impacts of such vibrations on surrounding buildings and stratum structures and evaluated the effectiveness of a vibration isolation trench in mitigating these effects. Time frequency domain analysis of ground vibrations during train passage revealed that the characteristic frequency of the train-induced pulse excitation in the track structure had a pronounced peak in the spectrum curve. The introduction of a vibration isolation trench effectively blocked the propagation of vibration waves in the soil, reduced soil vibration, and significantly lowered the peak value in the spectrum. Numerical simulations were employed to analyze the elliptical polarization dispersion characteristics of surface wave propagation with the vibration isolation trench in place, confirming the effective damping performance of the trench. These findings could offer a valuable reference for high-speed railway vibration isolation and significantly advance the application of surface wave theory in high-speed railway technology. Full article

(This article belongs to the Section Computational Engineering)

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21 pages, 1150 KB

Open AccessArticle

Modeling and Assessing Software Reliability in Open-Source Projects

by Maria T. Vasileva and Georgi Penchev

Computation 2025, 13(9), 214; https://doi.org/10.3390/computation13090214 - 3 Sep 2025

Viewed by 289

Abstract

One of the key components of the software quality model is reliability. Its importance has grown with the increasing use and reuse of open-source components in software development. Software reliability growth models are commonly employed to address this aspect by predicting future failure [...] Read more.

One of the key components of the software quality model is reliability. Its importance has grown with the increasing use and reuse of open-source components in software development. Software reliability growth models are commonly employed to address this aspect by predicting future failure rates and estimating the number of remaining defects throughout the development process. This paper investigates two software reliability growth models derived from the Verhulst model, with a particular focus on a structural property known as Hausdorff saturation. We provide analytical estimates for this characteristic and propose it as an additional criterion for model selection. The models are evaluated using four open-source datasets, where the Hausdorff saturation metric supports the conclusions drawn from standard goodness-of-fit measures. Furthermore, we introduce an interactive software reliability assessment tool that integrates with GitHub, enabling expert users to analyze real-time issue-tracking data from open-source repositories. The tool facilitates model comparison and enhances practical applicability. Overall, the proposed approach contributes to more robust reliability assessment by combining theoretical insights with actionable diagnostics. Full article

(This article belongs to the Section Computational Engineering)

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14 pages, 549 KB

Open AccessArticle

Matrix Factorization-Based Clustering for Sparse Data in Recommender Systems: A Comparative Study

by Rodolfo Bojorque and Remigio Hurtado

Computation 2025, 13(9), 213; https://doi.org/10.3390/computation13090213 - 3 Sep 2025

Viewed by 204

Abstract

Clustering techniques significantly enhance recommender systems by improving predictive accuracy and interpretability, particularly in sparse, high-dimensional datasets. This research presents a comprehensive comparative analysis of traditional clustering methods such as K-means and Fuzzy C-Means (FCM) against advanced probabilistic clustering methodologies based on Non-negative [...] Read more.

Clustering techniques significantly enhance recommender systems by improving predictive accuracy and interpretability, particularly in sparse, high-dimensional datasets. This research presents a comprehensive comparative analysis of traditional clustering methods such as K-means and Fuzzy C-Means (FCM) against advanced probabilistic clustering methodologies based on Non-negative Matrix Factorization (NMF), focusing specifically on Bayesian NMF. Experiments conducted using the widely recognized MovieLens 1M dataset reveal Bayesian NMF’s superior performance in terms of predictive accuracy, intra-cluster cohesion, and interpretability compared to classical methods. The study systematically evaluates the influence of key parameters such as overlap (

α

) and evidence threshold (

β

) in Bayesian NMF, demonstrating that careful parameter tuning substantially improves recommendation quality. The results highlight the inherent trade-off between cluster cohesion and predictive accuracy, emphasizing the flexibility and robustness of probabilistic approaches in accurately modeling user preferences and behaviors. The paper concludes by proposing future directions, including the exploration of hybrid clustering methods, dynamic adaptation to evolving user preferences, and integration of contextual information, thereby fostering continued advances in personalized-recommendation research. Full article

(This article belongs to the Section Computational Engineering)

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34 pages, 1340 KB

Open AccessArticle

Metric-Driven Voronoi Diagrams: A Comprehensive Mathematical Framework

by Vishnu G. Nair

Computation 2025, 13(9), 212; https://doi.org/10.3390/computation13090212 - 3 Sep 2025

Viewed by 392

Abstract

Voronoi partitioning is a fundamental geometric concept with applications across computational geometry, robotics, optimization, and resource allocation. While Euclidean distance is the most commonly used metric, alternative distance functions can significantly influence the shape and properties of Voronoi cells. This paper presents a [...] Read more.

Voronoi partitioning is a fundamental geometric concept with applications across computational geometry, robotics, optimization, and resource allocation. While Euclidean distance is the most commonly used metric, alternative distance functions can significantly influence the shape and properties of Voronoi cells. This paper presents a comprehensive mathematical analysis of various distance metrics used in Voronoi partitioning, including Euclidean, Manhattan, Minkowski, weighted, anisotropic, and geodesic metrics. We analyze their mathematical formulations, geometric properties, topological implications, and computational complexity. This work aims to provide a theoretical framework for selecting appropriate metrics for Voronoi-based modeling in diverse applications. Full article

(This article belongs to the Section Computational Engineering)

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22 pages, 19638 KB

Open AccessArticle

Packing and Cutting Stone Blocks Based on the Nonlinear Programming of Tree Cases

by Taeyong Kim

Computation 2025, 13(9), 211; https://doi.org/10.3390/computation13090211 - 3 Sep 2025

Viewed by 538

Abstract

Typically, dimension stones, commonly called stone blocks, are cut into multiple small cuboid stones so that multiple sculptures can be produced. To use the stone block as efficiently as possible, it is essential to pack these small cuboids in each stone block as [...] Read more.

Typically, dimension stones, commonly called stone blocks, are cut into multiple small cuboid stones so that multiple sculptures can be produced. To use the stone block as efficiently as possible, it is essential to pack these small cuboids in each stone block as efficiently as possible while satisfying the limitations of the machining. This paper describes methods for packing and cutting stone blocks using nonlinear programming that generate sets of trees, which are also called forests, that decide the packing layout of the small cuboids inside the block. The containers and elements have their own prices and values, respectively. The elements can be translated to the corners of the containers or to the corners of the elements that are already in the containers, if the elements are not outside the containers after the translation. Then, the problem can be interpreted as finding the best forest that packs the elements as efficiently as possible at the lowest total price of containers, which is a subset of all containers. The formula for the score that defines the compactness of the packing is in this paper. The user can define the number of forests so that parallel computing methods can be applied. Each forest is generated randomly. Two different packing methods are introduced: simple packing and slab packing. Simple packing is based on a non-guillotine cutting method and slab packing is a guillotine cutting method for realistic scenarios, such as scenarios with machining limitations. By using this method, it is possible to plan the cutting in a digital environment, which is not possible when using the traditional method with physical templates. Furthermore, by restricting the rotation of the elements, it is possible to make the elements follow the horizontal vein direction of the stone blocks, which is a common vein direction in travertine. Full article

(This article belongs to the Special Issue Computational Approaches for Manufacturing)

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15 pages, 719 KB

Open AccessArticle

Space-Time Primal-Dual Active Set Method: Benchmark for Collision of Elastic Bar with Discontinuous Velocity

by Victor A. Kovtunenko

Computation 2025, 13(9), 210; https://doi.org/10.3390/computation13090210 - 1 Sep 2025

Viewed by 259

Abstract

The dynamic contact problem describing collision of an elastic bar with a rigid obstacle, prescribed by an initial velocity, is considered in a variational formulation. The non-smooth, piecewise-linear solution is constructed analytically using partition of a 2D rectangular domain along characteristics. Challenged by [...] Read more.

The dynamic contact problem describing collision of an elastic bar with a rigid obstacle, prescribed by an initial velocity, is considered in a variational formulation. The non-smooth, piecewise-linear solution is constructed analytically using partition of a 2D rectangular domain along characteristics. Challenged by the discontinuous velocity after collision, full discretization of the problem is applied that is based on a space-time finite element method. For an iterative solution of the discrete variational inequality, a primal–dual active set algorithm is used. Computer simulation of the collision problem is presented on uniform triangle grids. The active sets defined in the 2D space-time domain converge in a few iterations after re-initialization. The benchmark solution at grid points is indistinguishable from the analytical solution. The discrete energy has no dissipation, it is free of spurious oscillations, and it converges super-linearly under mesh refinement. Full article

(This article belongs to the Section Computational Engineering)

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15 pages, 3459 KB

Open AccessArticle

Modeling Thermal Energy Storage Capability of Organic PCMs Confined in a 2-D Cavity

by Abdullatif A. Gari

Computation 2025, 13(9), 209; https://doi.org/10.3390/computation13090209 - 1 Sep 2025

Viewed by 301

Abstract

Organic phase change materials (PCMs) are a useful and increasingly popular choice for thermal energy storage applications such as solar energy and building envelope thermal barriers. Buildings located in high-temperature locations are exposed to extreme weather with high solar radiation intensity. PCM envelopes [...] Read more.

Organic phase change materials (PCMs) are a useful and increasingly popular choice for thermal energy storage applications such as solar energy and building envelope thermal barriers. Buildings located in high-temperature locations are exposed to extreme weather with high solar radiation intensity. PCM envelopes could act as thermal barriers on the exterior walls to prevent excessive heat gain and save on air conditioning costs. The PCM cavity is represented as a square cavity in this project. This project studies the effect of different parameters on energy transfer through the cavity. These parameters are PCM, heat flux gain (solar radiation), and time period (day hours). One parameter was changed at a time while others remained the same. This model was simulated numerically using ANSYS FLUENT software version 6.3.26. The project was solved as a transient problem and was run for a full day in simulation time. A pressure-based model was used because it is ideal for viscous flow and suitable for mildly compressible and low-speed flow. The PISO algorithm was used here because of the transient nature of the project. Temperature and convection heat transfer flux on the inner surface were recorded to study how the inner temperature and the amount of convective heat flux gain react to different conditions after energy passes the PCM envelope. It was found that Linoleic Acid provides the highest convective heat flux gain, meaning it provides the lowest thermal resistance. On the other hand, Tricosane was found to provide the lowest convective heat flux gain, meaning it provides the highest thermal resistance. For longer days (τ_q < 1), the PCM was in a liquid form for a longer time, which means less conduction, while for shorter days (τ_q > 1), the PCM was in a solid form for a longer time. Full article

(This article belongs to the Special Issue Computational Methods for Energy Storage)

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16 pages, 4086 KB

Open AccessArticle

Topology Optimization for Rudder Structures Considering Additive Manufacturing and Flutter Effects

by Heng Zhang, Shuaijie Shi, Xiaohong Ding, Jiandong Yang and Min Xiong

Computation 2025, 13(9), 208; https://doi.org/10.3390/computation13090208 - 1 Sep 2025

Viewed by 295

Abstract

This paper presents a multi-constraint topology optimization strategy for rudder structures, integrating additive manufacturing (AM)-related overhang angle and flutter-performance considerations. To the best of our knowledge, this is the first study to couple AM overhang control with mass center (flutter) steering in a [...] Read more.

This paper presents a multi-constraint topology optimization strategy for rudder structures, integrating additive manufacturing (AM)-related overhang angle and flutter-performance considerations. To the best of our knowledge, this is the first study to couple AM overhang control with mass center (flutter) steering in a single density-based formulation for flight control rudder structures. The approach incorporates constraints on structural volume fraction, overhang angle for AM, and mass center positioning to address multi-function design objectives—structural lightweighting, stiffness, aerodynamic stability, and manufacturability. A build-direction-aware projection filter and a smooth Heaviside mass center constraint are introduced to enforce these requirements during every optimization iteration. The resulting layout converges to a sandwich-type rudder with balanced mechanical performance and AM feasibility. Simulation results show that enforcing overhang constraints reduces support material usage by 46.9% and residual deformation by 14.2%, significantly enhancing AM feasibility. Additionally, introducing center-of-mass constraints improves flutter velocity from 3327 m s⁻¹ to 3759 m s⁻¹, indicating a 6.84% increase over conventional optimization and demonstrating improved dynamic stability. These simultaneous gains in manufacturability and aeroelastic safety, achieved without post-processing, underline the novelty and practical value of the proposed constraint set. The strategy thus offers a practical and efficient design method for high-performance, AM-friendly rudder structures with superior mechanical and aerodynamic characteristics, and it can be readily extended to other mission-critical AM components. Full article

(This article belongs to the Special Issue Advanced Topology Optimization: Methods and Applications)

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18 pages, 3402 KB

Open AccessArticle

Withangulatin A Identified as a Covalent Binder to Zap70 Kinase by Molecular Docking

by Corentin Bedart, Gérard Vergoten and Christian Bailly

Computation 2025, 13(9), 207; https://doi.org/10.3390/computation13090207 - 1 Sep 2025

Viewed by 302

Abstract

Inhibitors of the tyrosine kinase Zap70 are actively searched to improve treatments of lymphoid malignancies and autoimmune diseases associated with an abnormal T-cell response. The natural product withaferin A (WFA) has been characterized as a covalent inhibitor of Zap70 capable of blocking the [...] Read more.

Inhibitors of the tyrosine kinase Zap70 are actively searched to improve treatments of lymphoid malignancies and autoimmune diseases associated with an abnormal T-cell response. The natural product withaferin A (WFA) has been characterized as a covalent inhibitor of Zap70 capable of blocking the migration of human T-cells. By analogy, we postulated that other withanolides equipped with a thiol-reactive, α,β-unsaturated ketone may form covalent complexes with Zap70. The hypothesis was tested using a molecular modeling approach with a panel of 12 withanolides docked onto the kinase domain of Zap70. Seven natural products revealed a capability to form stable complexes with Zap70 comparable to that of WFA, including withangulatin A, 4β-hydroxywithanolide E, withaperuvin, and ixocarpalactone A. Withangulatin A surpassed all the other withanolides for its ability to engage an interaction with Zap70 kinase and to form covalent complexes via bonding to the Cys346 residue close to the enzyme active site. The physicochemical and ADMET properties of withangulatin A were analyzed via Density Functional Theory calculations and an analysis of its Fukui function descriptors. The C3 position of the enone moiety was identified as the most reactive (nucleophilic) site of the molecule. Withangulatin A revealed a satisfactory ADMET profile with no major toxicity anticipated. It represents a potential hit to guide the design of Zap70 inhibitors. Full article

(This article belongs to the Special Issue Feature Papers in Computational Chemistry)

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15 pages, 2356 KB

Open AccessArticle

Constrained Nonlinear Control of Semi-Active Hydro-Pneumatic Suspension System

by Biao Qiu and Chaiyan Jettanasen

Computation 2025, 13(9), 206; https://doi.org/10.3390/computation13090206 - 1 Sep 2025

Viewed by 316

Abstract

Aiming at the characteristics of limited actuation capability of the semi-active control system and strong nonlinearity of the hydro-pneumatic suspension, a constrained nonlinear control strategy of a semi-active hydro-pneumatic suspension system is proposed. According to the mathematical model of nonlinear hydro-pneumatic suspension, the [...] Read more.

Aiming at the characteristics of limited actuation capability of the semi-active control system and strong nonlinearity of the hydro-pneumatic suspension, a constrained nonlinear control strategy of a semi-active hydro-pneumatic suspension system is proposed. According to the mathematical model of nonlinear hydro-pneumatic suspension, the static stiffness and linear damping coefficient based on the equivalent energy are calculated, and then the control-oriented dynamic equation whose expression minimizes the nonlinear term is constructed. Combined with actuation capacity constraints, an optimization model with constraints is established to minimize the deviation between the actual overall control force and the expected optimal control force, and the optimal approximation from nonlinear control to linear quadratic optimal control is realized. The control simulation results of various methods show that the nonlinear control with constraints of the semi-active hydro-pneumatic suspension system, which effectively combines the actuation capacity constraints and nonlinear characteristics of the system, achieves a good comprehensive control effect for the nonlinear suspension control with constraints. Full article

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25 pages, 549 KB

Open AccessArticle

Fuzzy Lyapunov-Based Gain-Scheduled Control for Mars Entry Vehicles: A Computational Framework for Robust Non-Linear Trajectory Stabilization

by Hongyang Zhang, Na Min and Shengkun Xie

Computation 2025, 13(9), 205; https://doi.org/10.3390/computation13090205 - 1 Sep 2025

Viewed by 369

Abstract

Accurate trajectory control during atmospheric entry is critical for the success of Mars landing missions, where strong non-linearities and uncertain dynamics pose significant challenges to conventional control strategies. This study develops a computational framework that integrates fuzzy parameter-varying models with Lyapunov-based analysis to [...] Read more.

Accurate trajectory control during atmospheric entry is critical for the success of Mars landing missions, where strong non-linearities and uncertain dynamics pose significant challenges to conventional control strategies. This study develops a computational framework that integrates fuzzy parameter-varying models with Lyapunov-based analysis to achieve robust trajectory stabilization of Mars entry vehicles. The non-linear longitudinal dynamics are reformulated via sector-bounded approximation into a Takagi–Sugeno fuzzy parameter-varying model, enabling systematic gain-scheduled controller synthesis. To reduce the conservatism typically associated with quadratic Lyapunov functions, a fuzzy Lyapunov function approach is adopted, in conjunction with the Full-Block S-procedure, to derive less restrictive stability conditions expressed as linear matrix inequalities. Based on this formulation, several controllers are designed to accommodate the variations in atmospheric density and flight conditions. The proposed methodology is validated through numerical simulations, including Monte Carlo dispersion and parametric sensitivity analyses. The results demonstrate improved stability, faster convergence, and enhanced robustness compared to existing fuzzy control schemes. Overall, this work contributes a systematic and less conservative control design methodology for aerospace applications operating under severe non-linearities and uncertainties. Full article

(This article belongs to the Section Computational Engineering)

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21 pages, 1310 KB

Open AccessArticle

Optimal Control Strategies for a Mathematical Model of Pneumonia Infection

by Nuwayyir Almutairi and Moustafa El-Shahed

Computation 2025, 13(9), 204; https://doi.org/10.3390/computation13090204 - 23 Aug 2025

Viewed by 384

Abstract

In this study, we formulate and analyze a deterministic mathematical model describing the transmission dynamics of pneumonia. A comprehensive stability analysis is conducted for both the disease-free and endemic equilibrium points. The disease-free equilibrium is locally and globally asymptotically stable when the basic [...] Read more.

In this study, we formulate and analyze a deterministic mathematical model describing the transmission dynamics of pneumonia. A comprehensive stability analysis is conducted for both the disease-free and endemic equilibrium points. The disease-free equilibrium is locally and globally asymptotically stable when the basic reproduction number R₀ < 1, while the endemic equilibrium is locally and globally asymptotically stable when R₀ > 1. To evaluate effective intervention strategies, an optimal control problem is formulated by introducing time-dependent control variables representing awareness campaigns, screening of carriers, and treatment of infected individuals. Applying Pontryagin’s Maximum Principle, the simulation results confirm the effectiveness of the proposed control strategies in reducing the number of infections and mitigating the overall disease burden. The findings offer valuable insights into the control of pneumonia and highlight the potential impact of strategic public health interventions. Full article

(This article belongs to the Section Computational Biology)

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22 pages, 2709 KB

Open AccessArticle

SPL-Based Modeling of Serrated Airfoil Noise via Functional Regression and Ensemble Learning

by Andrei-George Totu, Daniel-Eugeniu Crunțeanu, Luminița Drăgășanu, Grigore Cican and Constantin Levențiu

Computation 2025, 13(9), 203; https://doi.org/10.3390/computation13090203 - 22 Aug 2025

Viewed by 322

Abstract

This study presents a semi-empirical approach to generalizing the acoustic radiation generated by serrated airfoil configurations, based on small-scale aerodynamic/acoustic experiments and functional regression techniques. In the context of passive noise reduction strategies, such as leading-edge and trailing-edge serrations, acoustic measurements are performed [...] Read more.

This study presents a semi-empirical approach to generalizing the acoustic radiation generated by serrated airfoil configurations, based on small-scale aerodynamic/acoustic experiments and functional regression techniques. In the context of passive noise reduction strategies, such as leading-edge and trailing-edge serrations, acoustic measurements are performed in a controlled subsonic wind tunnel environment. Sound pressure level (SPL) spectra and acoustic power metrics are acquired for various geometric configurations and flow conditions. These spectral data are then analyzed using regression-based modeling techniques—linear, quadratic, logarithmic, and exponential forms—to capture the dependence of acoustic emission on key geometric and flow-related variables (e.g., serration amplitude, wavelength, angle of attack), without relying explicitly on predefined nondimensional numbers. The resulting predictive models aim to describe SPL behavior across relevant frequency bands (e.g., broadband or 1/3 octave) and to extrapolate acoustic trends for configurations beyond those tested. The proposed methodology allows for the identification of compact functional relationships between configuration parameters and acoustic output, offering a practical tool for the preliminary design and optimization of low-noise serrated profiles. The findings are intended to support both physical understanding and engineering application, bridging experimental data and parametric acoustic modeling in aerodynamic noise control. Full article

(This article belongs to the Section Computational Engineering)

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Computation, Volume 13, Issue 9 (September 2025) – 19 articles

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