Applications of numerical analysis in computer simulations

Numerical analysis is a crucial field of mathematics dedicated to solving complex problems through approximation methods using algorithms and computers. This study investigates its multifaceted applications in computer simulations, especially for physical and biological processes. It highlights key...

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Bibliographic Details
Published inMultidisciplinary Science Journal Vol. 7; no. 8; p. 2025387
Main Authors Spahiu, Xhevdet, Orhani, Senad
Format Journal Article
LanguageEnglish
Published 01.08.2025
Online AccessGet full text
ISSN2675-1240
2675-1240
DOI10.31893/multiscience.2025387

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Summary:Numerical analysis is a crucial field of mathematics dedicated to solving complex problems through approximation methods using algorithms and computers. This study investigates its multifaceted applications in computer simulations, especially for physical and biological processes. It highlights key techniques like differential equation solvers, the finite element method (FEM), and numerical integration algorithms, which accurately model dynamic systems and natural phenomena. Case studies illustrate the application of these methods in fluid dynamics, wave propagation, thermodynamic analysis, and biological processes, including cell growth and infectious disease modeling. Advances in computational power and algorithmic efficiency have expanded the scope and complexity of problems addressed through numerical simulations. This study combines theoretical exploration with practical simulations to evaluate the accuracy, stability, and computational efficiency of these methods. Results indicate that modern techniques achieve high precision and adaptability, making numerical analysis a bridge between theoretical mathematics and practical problem-solving in engineering, biology, and environmental science. By examining nonlinear dynamic systems, multi-body interactions, and chaotic systems, the study demonstrates how numerical simulations provide solutions where traditional methods fail. Techniques like finite element analysis, iterative solvers, and discretization are highlighted as practical approaches for accurate solutions. The advantages of numerical methods include their ability to handle large-scale simulations with high precision and flexibility in modeling nonlinear phenomena. However, limitations such as high computational costs and sensitivity to initial conditions are acknowledged. The impact of advances in computational power and optimized algorithms, such as parallel processing, GPU acceleration, and adaptive mesh refinement, is also examined. This study emphasizes numerical analysis as a transformative tool for modern scientific inquiry, supporting advancements in technology, healthcare, and engineering. The findings underline its role in enabling precise simulations, enhancing algorithmic efficiency, and driving technological progress in a variety of scientific disciplines.
ISSN:2675-1240
2675-1240
DOI:10.31893/multiscience.2025387