This paper evaluates the reduction of airport noise that can be expected from an optimized LH2-fueled SST due to its shorter takeoff and landing performance compared to an equivalent kerosene-fueled SST. An initial comparison shows that flyover noise is reduced by 7.7EPNdB since the LH2-fueled SST has a steeper climb following a shorter takeoff roll. Although sideline and approach noises are increased, the total cumulative loudness is reduced by 6.5EPNdB. Then, the effect of reduced-thrust takeoff is evaluated for the LH2-fueled SST, which has a takeoff performance surplus. The result shows the sideline noise is reduced while flyover noise is increased. A parametric study is also conducted for further airport noise reduction potential.
To predict harmful acoustic loading due to the intense acoustic waves generated by exhaust jets from propulsion systems of launch vehicles during lift-off, a numerical method based on computational fluid dynamics is developed. High-fidelity large-eddy simulations, or hybrid large-eddy and Reynolds-averaged Navier-Stokes simulations are employed for the computation of the hydrodynamic field. Computational aeroacoustic simulations based on full-Euler equations are applied to compute acoustic propagation to the farfield. Validation and verification studies are conducted using experimental results of free and impinging jets from a 2.4%-scale solid motor. It is found that the prediction accuracy with approximately 4 dB in overall sound-pressure level is obtained for both the free and impinging jets.
On-board orbit determination (OD) using a Sun sensor and optical navigation camera (ONC) for autonomous navigation (AutoNav) is discussed in this paper. In low-Earth orbits, a global positioning system (GPS) is used for AutoNav. On the other hand, in deep space, the OD has been performed using range and range-rate (RARR), which is a traditional ground-tracking approach applying radio waves. RARR enables OD to have higher accuracy compared to other methods. However, such radio navigation has inevitable problems, such as the delay of radio waves, reduction in radio-wave strength and transmitter limitations. The influence of these problems becomes significant, especially for deep-space missions. Furthermore, it requires ground station staff to operate the spacecraft with full attention, which increases the operational cost considerably. Therefore there has been a growing interest in the AutoNav of the spacecraft in recent years because AutoNav can eliminate the aforementioned problems. The utilization of the AutoNav in deep space can reduce the complexity of operation at the ground station, and especially has a significant impact on reducing operational cost. This paper focuses on the configuration of observation objects and the sampling frequency for observation. Finally, as an example, the selection of observation and Earth-resonant trajectory are discussed.
A tether sling-shot system composed of a hub and a payload connected with a long tether is one example of space transportation systems. The facility is located at an arbitrary place on a rotating body. In this paper, the three-dimensional dynamics model for a tether sling-shot system whose hub can be inclined is presented. Tether oscillation stabilization is required to inject a payload to a predetermined orbit. Because the dynamics are complexly nonlinear, linear control methods such as the linear quadratic regulator (LQR) cannot show good performance for oscillation stabilization of the system. To overcome this problem, in this study, a model predictive control (MPC) method is chosen for stabilization. The performance of the MPC method is compared to that of suboptimal control based on (LQR) control. It is verified by numerical simulations that the MPC method can achieve faster stabilization along with smaller oscillation than the LQR control method.