Physics-Based 3D Simulation with Real-Time Extraction of Wave Parameters from Spatiotemporal Data

¹ Physics Education Program Study, Faculty of Mathematics and Natural Science, Universitas Negeri Jakarta, Jakarta, Indonesia
² Labschool Cibubur Senior High School, Jl. Raya Hankam Kampus Labschool No. 15-20, Bekasi 17432, West Java, Indonesia
³ Universitas Pancasakti Tegal, Indonesia
⁴ Primary School Teacher Education Program Study, Faculty of Islamic Education and Teacher Training, Universitas Alma Ata, Bantul, Indonesia
⁵ Dr. Emilio B. Espinosa Sr. Memorial State College of Agriculture and Technology, Philippines

^* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Published online: 2 July 2026

Abstract

Wave simulation has become a vital approach for studying dynamic propagation phenomena, representing temporal and spatial evolution simultaneously. Existing simulation platforms predominantly emphasize visual representation and conceptual demonstration, while the quantitative extraction of wave parameters remains separated from the simulation environment. Consequently, there is a lack of integration between physics-based simulation, spatiotemporal sampling, and real-time parameter extraction. This study proposes a physics-based 3D simulation framework capable of extracting frequency, wavelength, and amplitude directly from dynamically generated spatiotemporal wave data in real time. We utilize the 3D scalar wave equation, coupled with discrete spatial and temporal sampling mechanisms, to generate propagating waves. A real-time algorithm employing peak detection and zero-crossing analysis continuously acquires parameter values. Experimental scenarios covering frequency (1-10 Hz) and amplitude (0.1-1 m) variations demonstrate the system's high precision. Validation against analytical solutions reveals a Mean Absolute Percentage Error (MAPE) of less than 1.5% and a Root Mean Square Error (RMSE) below 0.02, while sustaining an operation rate of 60 frames per second. These results confirm that wave parameters can be extracted automatically and accurately, preserving physical consistency without compromising real-time computational performance, offering a robust tool for advanced computational physics education and extensive future multidisciplinary applied physical studies.