Various eVTOLs using multi propellers mounted on front of or behind the wings are being developed. In these eVTOLs, the estimation of the unsteady aerodynamic forces generated by the interaction between the propellers and the wings is one of the important problems. NASA X-57 Maxwell also mounts small multi propellers in front of the wing and two large cruse propellers are installed on the wing tips. These wing tip propellers reduce induced drag of the main wing by suppressing the wing tip trailing vortices. In this study, the calculation method based on unsteady lifting line theory including the effect of the shed vortices, which is able to treat the propeller-wing interaction is developed. We applied this method to the wing tip propellers of X-57 Maxwell and evaluated the unsteady aerodynamic forces obtained by this method.

In the future UAM (Urban Air Mobility) society, a wide variety of small aircraft, including drones, are cooperatively operated in urban spaces at lower altitudes. Unlike in undisturbed high-altitudes for large airliners, the UAM airspace might be atmospherically unstable, and severe turbulence like sudden crosswinds and downdrafts between buildings should be assumed. Such microclimate phenomena inherent to urban space are difficult to predict, and are a major threat to the safe operation of small lightweight aircrafts flying at low speeds. Hence, there is a great need for powerful attitude stabilization system that can back up manual control and typical SAS (Stability Augmentation System). In this study, the Flow Field Integrated Flight Control is proposed as a solution to this problem. The surface pressure field is used to obtain wind gust characteristics and improve flight stability. The feedback gain is tuned based on real-time modeling of the relationship between the aircraft motion and the surface pressure field, including the effect of turbulence. The proposed design method does not require any models in advance, such as aerodynamic model, mass properties, and turbulence models. The optimal pressure sensor location is also investigated by simulations.

Planetary rovers need to plan a safe route to ensure the success of their mission. Many missions to the Moon and Mars use existing remote sensing data to plan their exploration routes before launch under the assumption that the data is correct. For example, digital elevation models (DEMs) are biased in their accuracy depending on the density of their source data. Most studies of advance path planning using DEMs do not account for that uncertainty. Therefore, the path planned in advance is not necessarily safe for the actual rover. In this paper, we propose a path planning method that is robust against the uncertainty of terrain data generated from remote sensing data. Simulations using real data confirmed that the route planned by this method is safer than these two conventional methods: 1) route planning that assumes the topographic data is correct, and 2) route planning that adds Gaussian noise to the DEM to generate multiple DEMs and treats their variance as uncertainty.

The theoretical performance of gas turbines operating with pressure-gain combustion such as detonation and constant-volume combustion were evaluated by the cycle analysis. To clarify the unsteadiness of state quantities in the pressure-gain combustors, the time and spatial variations of state quantities were numerically computed for the case of pulse detonation combustor. It was found that the ideal pressure-gain combustion cycle had significantly higher thermal efficiency and specific work than that in the constant-pressure combustion cycle. However, when the adiabatic efficiencies of compressor and turbine and the limitation of turbine inlet temperature were introduced to the analysis the thermal efficiency of pressure-gain combustion cycle was identical to or lower than that of constant-pressure combustion cycle. Especially, the limitation of turbine inlet temperature largely degraded the thermal efficiency of pressure-gain combustion cycle. The numerical results showed the quite large variation of gas velocity and mass flow rate as well as pressure and temperature for the pulse detonation, which should be well considered when coupling the combustor with turbine and compressor. It is also found that although pulse detonation produced high peak values of pressure and temperature however their cycle-averaged values were substantially lower than the peak values.

We examined the construction of an analytical model to improve the accuracy of the thermal protection performance evaluation analysis of the ablator. In the conventional arc heating wind tunnel test, the difference in the thickness of the specimen before and after the test was used as the amount of surface recession, but the expansion of the ablator due to carbonization of the resin was included, which caused a difference from the numerical analysis. Therefore, we evaluated the expansion of the ablator due to carbonization of the resin and attempted to introduce it into the evaluation analysis by modeling the thermal expansion characteristics in order to further improve the analysis accuracy.

The drifting trajectory analysis of the reentry recovery module RATS with inflatable deployable aeroshell is validated with the drifting trajectory based on the flight experiment data. The RTOFS sea surface current forecast data and the GFS ocean wind forecast data, released from NCEP, are employed in the drifting trajectory analysis. It is shown that the RATS can float for a long time, although the inflatable ring is filled with CO₂ gas, which has large gas permeability of the gas-tight layer. The leeway coefficient for drifting trajectory analysis is estimated to be 0.038 based on the floating design of the RATS. The drifting trajectory analysis was performed using the RATS landing point as the initial position. It was confirmed that the predicted drift direction agrees with the RATS drifting trajectory. However, the difference between the predicted result and the drifting trajectory increases with time in the ocean wind direction. The difference is approximately 0.8 km after 100 minutes from splashdown.