Fan Li¹, Hongxue Liu², Yongsong Li², Leilei Chen², Haojie Lian^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 2785-2809, 2025, DOI:10.32604/cmes.2025.066001 - 30 June 2025

Abstract This study explores a sensitivity analysis method based on the boundary element method (BEM) to address the computational complexity in acoustic analysis with ground reflection problems. The advantages of BEM in acoustic simulations and its high computational cost in broadband problems are examined. To improve efficiency, a Taylor series expansion is applied to decouple frequency-dependent terms in BEM. Additionally, the Second-Order Arnoldi (SOAR) model order reduction method is integrated to reduce computational costs and enhance numerical stability. Furthermore, an isogeometric sensitivity boundary integral equation is formulated using the direct differentiation method, incorporating Cauchy principal value More >

Ahed Habib^1,*, Mohamed Maalej², Samir Dirar³, M. Talha Junaid², Salah Altoubat²

Structural Durability & Health Monitoring, Vol.19, No.4, pp. 789-817, 2025, DOI:10.32604/sdhm.2025.064882 - 30 June 2025

Abstract Carbon nanotube-reinforced cement composites have gained significant attention due to their enhanced mechanical properties, particularly in compressive and flexural strength. Despite extensive research, the influence of various parameters on these properties remains inadequately understood, primarily due to the complex interactions within the composites. This study addresses this gap by employing machine learning techniques to conduct a sensitivity analysis on the compressive and flexural strength of carbon nanotube-reinforced cement composites. It systematically evaluates nine data-preprocessing techniques and benchmarks eleven machine-learning algorithms to reveal trade-offs between predictive accuracy and computational complexity, which has not previously been explored… More >

Ala’a R. Al-Shamasneh¹, Faten Khalid Karim², Arsalan Mahmoodzadeh^3,*

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 281-303, 2025, DOI:10.32604/cmc.2025.065748 - 09 June 2025

Abstract Soilcrete is a composite material of soil and cement that is highly valued in the construction industry. Accurate measurement of its mechanical properties is essential, but laboratory testing methods are expensive, time-consuming, and include inaccuracies. Machine learning (ML) algorithms provide a more efficient alternative for this purpose, so after assessment with a statistical extraction method, ML algorithms including back-propagation neural network (BPNN), K-nearest neighbor (KNN), radial basis function (RBF), feed-forward neural networks (FFNN), and support vector regression (SVR) for predicting the uniaxial compressive strength (UCS) of soilcrete, were proposed in this study. The developed models… More >

Hadi Fattahi¹, Hossein Ghaedi¹, Danial Jahed Armaghani^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 747-766, 2025, DOI:10.32604/cmes.2025.062390 - 11 April 2025

Abstract In contemporary geotechnical projects, various approaches are employed for forecasting the settlement of shallow foundations (S_m). However, achieving precise modeling of foundation behavior using certain techniques (such as analytical, numerical, and regression) is challenging and sometimes unattainable. This is primarily due to the inherent nonlinearity of the model, the intricate nature of geotechnical materials, the complex interaction between soil and foundation, and the inherent uncertainty in soil parameters. Therefore, these methods often introduce assumptions and simplifications, resulting in relationships that deviate from the actual problem’s reality. In addition, many of these methods demand significant investments of… More >

Alex Kibet^*, Gilbert Langat

Journal of Intelligent Medicine and Healthcare, Vol.3, pp. 1-14, 2025, DOI:10.32604/jimh.2022.062824 - 04 April 2025

Abstract Multiple Sclerosis (MS) is a disease that disrupts the flow of information within the brain. It affects approximately 1 million people in the US. And remains incurable. MS treatments can cause side effects and impact the quality of life and even survival rates. Based on existing research studies, we investigate the risks and benefits of three treatment options based on methylprednisolone (a corticosteroid hormone medication) prescribed in (1) high-dose, (2) low-dose, or (3) no treatment. The study currently prescribes one treatment to all patients as it has been proven to be the most effective on More >

Wenna He, Yichen Yang, Dongqiong Liang, Heng Cheng^*

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 1415-1414, 2025, DOI:10.32604/cmc.2025.059839 - 26 March 2025

Abstract In this paper, we develop an advanced computational framework for the topology optimization of orthotropic materials using meshless methods. The approximation function is established based on the improved moving least squares (IMLS) method, which enhances the efficiency and stability of the numerical solution. The numerical solution formulas are derived using the improved element-free Galerkin (IEFG) method. We introduce the solid isotropic microstructures with penalization (SIMP) model to formulate a mathematical model for topology optimization, which effectively penalizes intermediate densities. The optimization problem is defined with the numerical solution formula and volume fraction as constraints. The… More >

Muhammad Imran^1,*, Brett McKinney¹, Azhar Iqbal Kashif Butt²

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1899-1931, 2025, DOI:10.32604/cmes.2024.059552 - 27 January 2025

Abstract The co-infection of corona and influenza viruses has emerged as a significant threat to global public health due to their shared modes of transmission and overlapping clinical symptoms. This article presents a novel mathematical model that addresses the dynamics of this co-infection by extending the SEIR (Susceptible-Exposed-Infectious-Recovered) framework to incorporate treatment and hospitalization compartments. The population is divided into eight compartments, with infectious individuals further categorized into influenza infectious, corona infectious, and co-infection cases. The proposed mathematical model is constrained to adhere to fundamental epidemiological properties, such as non-negativity and boundedness within a feasible region.… More >

Wenpeng Li¹, Zhenghe Liu¹, Yujing Ma¹, Zhuxuan Meng^2,*, Ji Ma³, Weisong Liu², Vinh Phu Nguyen⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1515-1543, 2025, DOI:10.32604/cmes.2025.059235 - 27 January 2025

Abstract This paper presents a framework for constructing surrogate models for sensitivity analysis of structural dynamics behavior. Physical models involving deformation, such as collisions, vibrations, and penetration, are developed using the material point method. To reduce the computational cost of Monte Carlo simulations, response surface models are created as surrogate models for the material point system to approximate its dynamic behavior. An adaptive randomized greedy algorithm is employed to construct a sparse polynomial chaos expansion model with a fixed order, effectively balancing the accuracy and computational efficiency of the surrogate model. Based on the sparse polynomial More >

Meng Zhao¹, Jiaao Liu², Yudi Liu³, Zhengwei Long^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1545-1564, 2025, DOI:10.32604/cmes.2025.058773 - 27 January 2025

Abstract Computational Fluids Dynamics (CFD) simulations are essential for optimizing the design of a cockpit’s internal environment, but the complex geometric models consume a significant amount of computational resources and time. Arbitrary simplification of geometric models may result in inaccurate calculations of physical fields. To address this issue, this study establishes a geometric model simplification strategy and successfully applies it to a cockpit. The implementation of the whole approach is divided into three steps, summarized in three methods, namely Sensitivity Analysis Method (SAM), Detail Suppression Method (DSM), and Evaluation Standards Method (ESM). Sensitivity analysis of the More >

Ritian Ji¹, Zhiguo Qu^1,*, Hui Wang¹, Binbin Jiao², Yuxin Ye²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.012210

Abstract In this manuscript, a finite volume discrete topology optimization method based on the continuous adjoint method is proposed to simulate turbulent flow using the k-omega turbulence model for solving the topology optimization problem of conjugate heat transfer at high Reynolds number. The manuscript simulates the conjugate turbulent convective heat transfer problem at high Reynolds number with a set of Reynolds-Averaged Navier-Stokes (RANS) equations coupled with energy transport equations and control equations of the k-omega turbulence model, and implements the methodology by using the variable density method, interpolates the material values of thermal conductivity, heat capacity,… More >