This study presents an optimal design approach of a pintle injector for a deep throttlable liquid-propellant rocket engine (LPRE). Even though the pintle injector is used in rocket engines, it has become more important since reusable launch vehicles (RLVs) recently became a trend due to their economic and environmental benefits. However, since many variables must be determined to design a pintle injector, optimizing the pintle injector design is complicated. For this, we design a pintle injector to optimize the performance parameters; the spray angle, vaporization distance, and Sauter mean diameter (SMD). To confirm the approach, we design a pintle injector using an optimization method based on convex quadratic programming (CQP) for a 1000 N thrust and a throttle ability of 5 to 1 LPRE with liquid oxygen and gaseous methane. Then, we verify the performance using a numerical simulation. Through this work, we check the effectiveness of the optimization method for a pintle injector design.

This study deals with the mathematical modeling and numerical simulation of chemical propulsion systems (CPSs). For this, we investigate and summarize a comprehensive collection of the simulation modeling developments of CPSs in academic works, applications, and industrial fields. Then, we organize and analyze the simulation modeling approaches in several ways. After that, we organize differential-algebraic Equations (DAEs) for fundamental mathematical modeling consisting of the governing Equations (ordinary differential equations, ODEs) for the components and other equations derived from several physical rules or characteristics (algebraic equations or phenomenological equations, AEs) and then synthesize and summarize the fundamental structures of analytic mathematical modeling by types (liquid-propellant rocket engines, solid-propellant rocket motors, and hybrid-propellant rocket motors) of CPSs.

The Kinesthetic Node and Autonomous Table-Top Emulator (KNATTE) is a three-degree-of-freedom frictionlessvehicle that serves as a multipurpose platform for real-time spacecraft hardware-in-the-loop experiments. The dataacquisition of the vehicle depends on a Computer Vision System (CVS) that yields position and attitude data, but alsosuffers from unpredictable blackout events. To complement such measurements, KNATTE incorporates an InertialMeasurement Unit (IMU) that yields accelerometer, gyroscope, and magnetometer data. This study describes amultisensor data fusion approach to obtain accurate attitude information by combining the measurements from theCVS and the IMU using nonlinear Kalman filter algorithms. To do this, we develop the data fusion algorithms andtest them in a MATLAB/Simulink environment. After that, we adapt the algorithms to the KNATTE platform andconfirm the performance in various conditions. Through this work, we can check the accuracy and efficiency of theapproach by numerical simulation and real-time experiments.

This paper deals with a performance comparison of the control algorithm for a variable-thrust solid-propellant rocket motor (VTSRM). To do this, we develop a simulation model of a VTSRM considering characteristic changes in the combustor and design control systems for pressure and thrust. We use three types of control algorithms for the pressure control: classical PID control, feedback linearization control, and fuzzy PID control, and two control algorithms for thrust control: classical PID control and fuzzy PID control. Finally, we compare the performance of each control system through a numerical simulation using step responses. Through this work, we check that feedback linearization is better in pressure control, and fuzzy PID control is more appropriate in thrust control. Especially using fuzzy PID control, we can get fast settling with a small undershoot even if the system is a nonminimum phase system.

The high cost of rocket technology has led to system reusability developments, particularly in the field of first-stage rockets. With the motivation of decreasing production costs, successful vertical rocket landing attempts by SpaceX and Blue Origin have led the path for autonomous recovery and reusability of rocket engines. After the success of the space companies, recovering and relaunching reusable first stages have demonstrated the possibility of building reliable and low-cost reusable first stages. In the landing process, an optimized trajectory and robust control algorithm of a reusable launch vehicle (RLV), which can be minimized propellant consuming, are needed because the RLV is affected by various uncertainties such as a wind gust, atmospheric condition, or aerodynamic problem. Therefore, it is necessary too btain an optimized trajectory and design a robust control algorithm to cope with the problems. The instantaneous impact point (IIP) is defined as “a touchdown point, following thrust termination of a launch vehicle calculated in the absence of atmospheric drag effects.” In launch operations, the IIP is considered a crash point after an abrupt end of the propelled flight, so the IIP should be calculated and monitored in real-time on the ground facility or the rocket to predict and prevent the potential risk in advance, which can occur around the touchdown point. In other words, the IIP can be used to obtain an optimized trajectory that can minimize the consuming propellants. Since the guidance and control for the landing process of reusable first stages is a specific research field that presents multiple goals and constraints, the fuzzy PID control algorithm is suitable for the system. The algorithm has several robustness strengths, bounded-input, bounded-output (BIBO) systems, and nonlinear systems. In the landing process, the control references generally are thrust magnitude and vector control for velocity control and reaction control system (RCS) or grid-fin for attitude control. We propose a fuzzy PID control algorithm for robust guidance and control of RLV with a liquid-propellant rocket engine (LPRE) in the landing process using an optimized trajectory obtained by the IIP algorithm. To do this, we develop the simplified mathematical model of SLV using LPRE, obtain optimized passage for landing using the IIP method, and design a fuzzy PID control system based on thrust magnitude and vector control to control velocity and grid-fin or RCS to control attitude. We demonstrate the performance through numerical simulation to confirm the control algorithm.