Publications:
1. S. Kerbal, S Khasanov , On Katugampola-Prabhakar fractional integral-differential operators, Gulf Journal of Mathematics, 2025.
2. Z Alimov, S. Kerbal,Inverse initial problem for fractional wave equation with the Hadamard fractional derivative, Kazakh Mathematical Journal, 2025
3. A.Z. Fino, M. Kirane, B. Barakeh, S. Kerbal , Fujita Type Results for a Parabolic Inequality With a Nonlinear Convolution Term on the Heisenberg Group, Mathematical Methods in the Applied Sciences, 2025
4. S Karaa, A.K. Pani, P.D. Damázio, N. Ahmed , Finite Element Analysis of the Time-Fractional Stokes System with Nonsmooth Initial Data,
Journal of Scientific Computing, 2025
5. Two-grid FEM for fractional diffusion problems with limited regularity
M. Al-Maskari, S. Karaa, Communications in Nonlinear Science and Numerical Simulation 146, 108776, 2025
6. M Al-Maskari, S Karaa , Strong approximation of the time-fractional Cahn–Hilliard equation driven by a fractionally integrated additive noise
, Computers & Mathematics with Applications, 2025
7. B. CHENTOUF, S. KARAA, S MANSOURI , A THEORETICAL AND NUMERICAL STUDY ON THE EXPONENTIAL STABILIZATION OF THE ROTATING DISK-BEAM SYSTEM WITH A BOUNDARY DELAY: A NONCLASSICAL CASE*,2025.
8. M. Al-Maskari , Numerical Methods for Approximating Stochastic Semilinear Time-Fractional Rayleigh-Stokes Equations, Journal of Computational Mathematics, 2025
9. F. Al-Musalhi, A Fernandez, Fractional differential equations involving Erdélyi–Kober derivatives with variable coefficients,
Fractional Calculus and Applied Analysis, 2025
10. Analysis of Fractional Linear Multi-Step Methods of Order Four from Super-Convergence
H.M. Nasir, K Al Hasani, Sultan Qaboos University Journal for Science,
11. Fino, A.Z., Decay of Mass for a Semilinear Heat Equation on Heisenberg Group, Contemporary Mathematics SingaporeOpen source preview, 2025, 6(5), pp. 7523–7542
12. M Kirane, AZ Fino, A Ayoub, Decay of mass for a semilinear heat equation with mixed local-nonlocal operators: Fractional Calculus and Applied Analysis, 2025
13. M. Kirane, A.Z. Fino, B.T. Torebek, Z. Sabbagh , Cazenave‐Dickstein‐Weissler‐Type Extension of Fujita'S Problem on Heisenberg Groups, Mathematical Methods in the Applied Sciences, 2025
14. Z. Sabbagh, A. Z. Fino and M. Kirane , The Fujita Exponent for a Heat Equation with Mixed Local and Nonlocal Nonlinearities on the Heisenberg Group, Lobachevskii Journal of Mathematics, 2025, Vol. 46, No. 12, pp. 6399–6412, 2025
15. A. Hasanov, E. Karimov, On Generalized Mittag–Leffler‐Type Functions of Two Variables, Mathematical Methods in the Applied Sciences, 2025
16. E. Karimov, N. Tokmagambetov, M. Toshpulatov ,Mixed partial differential equation: Forward problem linked with the wave-diffusion process, Georgian Mathematical Journal, 2025
17. E. Karimov, M. Toshpulatov , Mixed wave-diffusion-wave equation: solvability of an initial-boundary problem, Gulf Journal of Mathematics, 2025
18. A. Hasanov, E. Karimov , Euler-type integral representations for bivariate Mittag-Leffler-type functions, Cybernetics and Systems Analysis, 2025
19. N. Al-Salti, E. Karimov, M. Al-Ghabshi , An Initial-Boundary Problem for a Mixed Fractional Wave Equation, Progr. Fract. Differ. Appl. 11, No. 3, 613-621 (2025)
20. S. Shaimardan, E. Karimov, M. Ruzhansky, A. Mamanazarov, The Prabhakar fractional 𝑞-integral and 𝑞-differential operators, and their properties, Filomat 39 (6), 2003-2016, 2025.
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In the past, rapid advances in nanotechnology have created many opportunities for scientists and engineers to explore. Nanofluid is one of the amazing applications of such advancement. Nanofluids are engineered by suspending nanoparticles in traditional heat transfer fluids. Nanofluids are considered to offer important advantages over conventional heat transfer fluids. Nanofluids have novel properties that make them potentially useful in many heat transfer applications, including microelectronics, automotive, fuel cells, hybrid-power engines, advanced nuclear systems, pharmaceutical processes, and nano-drug delivery. They exhibit enhanced thermal conductivity, minimal clogging in the flow passage, long-term stability, and greater homogeneity than the base fluid. Nanoparticles are relatively close in size to the molecules of the base fluid and thus can realize very stable suspensions with little gravitational settling over long periods. Over the years, many industries facing thermal challenges urgently need ultrahigh-performance cooling. Therefore, manufacturers began using nanofluids for industrial cooling, resulting in significant energy savings and reduced emissions. Because of the wide range of applications of nanofluids, considerable research has been conducted in recent years to study their heat transfer characteristics.
The study of nanofluids provides one of the new challenges for thermo-science. Nanotechnology plays an imperative role in developing modern devices for practical use. However, specific research objectives guide our work: (1) to investigate convective heat transfer mechanisms in nanofluids, (2) to analyze nanoparticle deposition caused by various slip mechanisms under different flow and thermal conditions in numerous geometries, (3) to examine natural convective flows in nanofluid-saturated porous media, and (4) to utilize machine learning and artificial neural networks for optimizing thermal enhancement in nanofluids. We will develop and examine mathematical models for these processes analytically and/or numerically, interpret the results from an engineering perspective, and identify relevant implications for device performance.
The research group investigates multiple aspects of nanofluids, facilitating training for personnel at undergraduate, master's, and Ph.D. levels. This approach not only guarantees adequate personnel for the research project but also significantly advances capacity building in this important and emerging research area.
Professor Mohamed Al-Lawati, Sultan Qaboos University
Dr. Bushra Al Mur Al-Ghabshi, Sultan Qaboos University
Dr. Sheikha Al-Weheibi, Sultan Qaboos University
Dr. Latifa Al Balushi, Sultan Qaboos University
Professor Ziad Saghir, Toronto Metropolitan University
Prof. Md. Shariful Alam, Jagannath University
Dr. Jashim Uddin, Nizwa University
Overview:
The Scientific Computing Research Group is focused on developing advanced numerical algorithms and computational methods to solve complex scientific and engineering problems. The group's research covers a wide range of topics, including the development and analysis of efficient numerical methods for solving partial differential equations (PDEs), which are essential tools for modeling physical phenomena in areas.
A significant part of the group’s work also addresses the challenges of inverse problems, particularly in stabilizing ill-posed problems using innovative regularization techniques. These approaches are applied in fields like medical imaging, geophysics, and materials science, where accurate solutions are often difficult to obtain due to noisy or incomplete data.
The group further integrates cutting-edge advancements in Artificial Intelligence for PDEs and Machine Learning in Computational Science, enhancing both the efficiency and accuracy of traditional numerical solutions. These innovative approaches leverage data-driven methods to improve and extend conventional computational techniques, unlocking new possibilities for applications in engineering and the sciences.
Another key focus of the group’s research is numerical optimization and control, where it develops algorithms for the optimal control of systems governed by PDEs, with an emphasis on real-time control applications in advanced engineering systems.
The Scientific Computing Research Group is a multidisciplinary and interdisciplinary-oriented team with local and international members who have expertise in computational science, applied mathematics, and engineering. Through collaborative efforts with academic and industry partners, the group develops advanced computational tools and algorithms that tackle the growing complexity of real-world problems in science and technology.
Group Leader: Pro. Samir Karaa
Email: skaraa@squ.edu.om
Group Members Local:
Abdul Wahab, Sultan Qaboos University Mariam Al-Maskari, Sultan Qaboos University Abdelhamid Abdessalem, Sultan Qaboos University Samir Karaa, Sultan Qaboos University Yassine Bouchareb, Sultan Qaboos University
International:
Naveed Ahmed, Gulf University for Science and Technology, Kuwait Siraj-ul-Islam, University of Engineering and Technology, Pakistan Amiya K. Pani, BITS-Pilani, K.K. Birla Goa Campus, Goa, India Shujaat Khan, Computer Engineering Department, KFUPM, KSA.
S Karaa, AK Pani, PD Damázio, N Ahmed, Finite Element Analysis of the Time-Fractional Stokes System with Nonsmooth Initial Data, Journal of Scientific Computing 105 (3), 97, 2025
M Al-Maskari, S Karaa, Two-grid FEM for fractional diffusion problems with limited regularity, Communications in Nonlinear Science and Numerical Simulation 146, 108776, 2025
M Al-Maskari, S Karaa, Strong approximation of the time-fractional Cahn–Hilliard equation driven by a fractionally integrated additive noise, Computers & Mathematics with Applications 180, 28-45, 2025.
M Al-Maskari, Numerical Methods for Approximating Stochastic Semilinear Time-Fractional Rayleigh-Stokes Equations, Journal of Computational Mathematics 43 (3), 569-587, 2025.
Siraj-ul-Islam, Masood Ahmad, Muhammad Sattar, A non-iterative meshless method for heat source identification in steady and unsteady problems, Engineering Analysis with Boundary Elements 179, 106-280, 2025
Sakhi Zaman, Siraj-ul-Islam, Reproducing kernel function-based formulation for highly oscillatory integrals, Journal of Computational and Applied Mathematics 463, 116-507, 2025.
B Bir, H Hutridurga, AK Pani, On a Completely Discrete Discontinuous Galerkin Method for Incompressible Chemotaxis-Navier-Stokes Equations, Journal of Scientific Computing 105 (2), 1-41, 2025.
H Hutridurga, K Kumar, AK Pani, Discontinuous Galerkin Methods for the Vlasov–Stokes System, Computational Methods in Applied Mathematics 25 (1), 93-113, 2025.
P Danumjaya, A Kumar, A K. Pani,Asymptotic Behavior of the Semidiscrete FE Approximations to Weakly Damped Wave Equations With Minimal Smoothness on Initial Data, Mathematical Methods in the Applied Sciences, Volume 48, Issue 13, 2025.
N Ahmed, M Safdar, A Wahab, Poroelastic Attenuation in Flexible Cavities: A Semi-Analytical Approach, Journal of Vibration Engineering & Technologies 13, 449 2025.
N Al Tahifah, MS Ibrahim, E Rehman, N Ahmed, A Wahab, S Khan, Anticancer Peptides Classification Using Long-Short-Term Memory with Novel Feature Representation, IEEE Access 13, 67-79, 2025.
M Afzal, N Ahmed, M Safdar, M Umar, On the modeling of sound sources in waveguides with structural variations and sound-absorbent materials, Communications in Nonlinear Science and Numerical Simulation 145, 108714, 2025.
Mohd Yusof, N Ahmed, SNI Bakhir, Shiva Shanghari RV, The prevalence of leptospirosis infections among humans in Malaysia: a systematic review and meta-analysis. Tropical Biomedicine 42 (2), 201-212
M Luo, F Yousefirizi, P Rouzrokh, W Jin, I Alberts, C Gowdy, Y Bouchareb, Physician-in-the-loop active learning in radiology artificial intelligence workflows: opportunities, challenges, and future directions American Journal of Roentgenology, , November 2025.
Y Bouchareb, M Al Kharusi, A Al Maqbali, A Al Maimani, H Al Maskari, Establishing diagnostic reference levels for paediatric CT imaging: a multi-centre study, Healthcare 13 (14), 1728, 2025.
MS Jabbar, THM Siddique, K Huang, S Khan, Knowledge Distillation with Predicted Depth for Robust and Lightweight Face Presentation Attack Detection, Knowledge-Based Systems, 329 (4), 114325, 2025.
A Ali, K Memon, N Yahya, S Khan, Deep learning frameworks for MRI-based diagnosis of neurological disorders: a systematic review and meta-analysis,Artificial Intelligence Review 58 (6), 171, 2025.