TY - JOUR
T1 - Improving the modified linearly implicit quantized state system methods
T2 - step size, cycle detection, and linear approximation coefficient
AU - Elbellili, Elmongi
AU - Blondeel, Philippe
AU - Huybrechs, Daan
AU - Lauwens, Ben
N1 - Publisher Copyright:
© The Author(s) 2025
PY - 2025/7/30
Y1 - 2025/7/30
N2 - The growing intricacy of contemporary engineering systems, typically reduced to differential equations, poses a difficulty in digitally simulating them. The linearly implicit quantized state system (LIQSS) provides a different method from traditional numerical integration techniques for tackling such problems. This method is effective in large sparse stiff systems and systems with frequent discontinuities. However, this method could be further improved. First, the algorithm can step through the solution analytically or through iterations. A comparison is presented in this article. Second, the intrinsic discrete behavior of this new method can cause oscillations that lead to small unnecessary simulation steps. A prior approach was made to detect and terminate these cycles. Different detection mechanisms are examined in this article. Third, a linear approximation was used. Its enhancement is also investigated in this work. Finally, the article provides which of these modifications improved the overall performance of some systems simulations using LIQSS order one.
AB - The growing intricacy of contemporary engineering systems, typically reduced to differential equations, poses a difficulty in digitally simulating them. The linearly implicit quantized state system (LIQSS) provides a different method from traditional numerical integration techniques for tackling such problems. This method is effective in large sparse stiff systems and systems with frequent discontinuities. However, this method could be further improved. First, the algorithm can step through the solution analytically or through iterations. A comparison is presented in this article. Second, the intrinsic discrete behavior of this new method can cause oscillations that lead to small unnecessary simulation steps. A prior approach was made to detect and terminate these cycles. Different detection mechanisms are examined in this article. Third, a linear approximation was used. Its enhancement is also investigated in this work. Finally, the article provides which of these modifications improved the overall performance of some systems simulations using LIQSS order one.
KW - Quantized State Systems
KW - Numerical Integration
KW - Ordinary Differential Equations
KW - Stiffness
KW - Discrete event simulation
UR - https://www.scopus.com/pages/publications/105012548667
U2 - 10.1177/00375497251351941
DO - 10.1177/00375497251351941
M3 - Article
AN - SCOPUS:105012548667
SN - 0037-5497
SP - 1153
EP - 1164
JO - Simulation: Transactions of the Society for Modeling and Simulation International
JF - Simulation: Transactions of the Society for Modeling and Simulation International
M1 - 00375497251351941
ER -