Steering Acceleration Research Articles

Simulation study of impact dynamics during LNG transportation

Abstract: In this study, the Fluent software is utilized to simulate the lateral impact force on a tank during liquid sloshing when the tank is subjected to turns under varying steering accelerations and filling rates. It is observed that at a steering acceleration of 0.5g, the overall force vector pointing in the lateral direction of the tank body significantly increases the likelihood of tipping. A clear trend arises when steering acceleration is held constant; as filling rates range from 0.6 to 0.85, lateral impact forces due to tank liquid sloshing progressively increase with rising filling rates, whereas a decrease in force occurs between filling rates of 0.85-0.9. This analysis reveals that tanker truck safety is relatively high during turning maneuvers when the filling rate is between 0.85 and 0.9 and the steering acceleration is in the range of 0.1-0.4g.

Path planning for low‐altitude flight by fuzzy reasoning

AbstractThis paper discusses flight‐path planning for an aircraft flying at low altitude while avoiding terrain crashes. In a past study, several algorithms based on exploratory procedures have been proposed; however, they do not generate practical paths that take into account aircraft inertia. This paper proposes a new algorithm to generate a flight path taking account of the aircraft's inertia; this algorithm does not generate the flight path directly, but determines the aircraft's steering acceleration at every point along the way and then generates the flight path based on the steering acceleration. This algorithm extracts feature parameters representing a relation between the aircraft and the terrain, determines steering acceleration by fuzzy reasoning using the feature parameters, and updates state variables of the aircraft. Furthermore, this paper also proposes a learning algorithm to design the membership values in the fuzzy reasoning from reference flights since it is difficult to optimize them by trial and error. The flight‐path planning by the proposed algorithm is compared with that based on the exploratory procedure. The learning algorithm of the membership values is validated through computer simulations.