Naoaki Saeki

Analytical and Experimental Investigation of Base–Extension Separation Mechanism for Spacecraft Landing

Future planetary exploration requires spacecraft to land softly on rough terrain and in severe environments. Since conventional landing methods have problems such as high rebounds and excessive resource consumption, the base–extension separation mechanism, which combines springs and separable units, is proposed as a novel landing mechanism. Although the mechanism performed good soft landings, the performance evaluation was limited. Therefore, this study evaluated its performance multilaterally. The proposed technology was analytically compared with two other landing technologies: a generalized-hybrid momentum exchange impact damper and an aluminum foam landing gear. The proposed technology suppressed rebound and acceleration better than the generalized momentum exchange impact damper. Once the components of the proposed technology had been lightened, its energy conversion efficiency matched that of the aluminum foam landing gear. In addition, experiments were conducted using small-scale models to confirm ...

Gear-Part-Flying Mechanism for planetary exploration spacecraft landing

For planetary exploration, spacecrafts need to land softly. Conventional methods in previous missions have problems such as high rebound, impossibility of reuse, increase of the equipped mass, and expensive cost. To solve these problems, the author proposes a novel landing mechanism called Gear-Part-Flying Mechanism (GPFM). The main components of GPFM are the body, the head, and the gear. Here, the body corresponds to a spacecraft. GPFM realizes soft landing by converting the bodys mechanical energy to the mechanical energy of the head and gear. The energy conversion is obtained effectively by the separation of the body and the head at the optimal timing. In comparison with the previous landing methods, the advantages of GPFM are as follows: (i) GPFM is reusable. (ii) GPFM is effective to suppress the bodys rebound. (iii) GPFM is effective for both weight and cost saving of landing mechanisms. In this paper, the soft landing performance of GPFM is discussed. First of all, for simulation analysis, the model of GPFM is obtained assuming that it is a single-axis falling-type problem. The values of parameters are determined based on the 1/6 G similarity rule. This paper evaluates the robustness of GPFM against the variations of some parameters such as the ground stiffness, the body mass, the equipped mass, and the separation delay. For evaluation, this paper focuses on the maximum rebound height of the body. Simulation results reveal that GPFM has well robustness against the uncertainties of the ground stiffness, the body mass, and the equipped mass. However, the delay of separation causes a significant degradation of its performance.

Two-Dimensional Experimental Investigation of Base-Extension Separation Mechanism with Telescopic Gear

Spacecraft landing missions require a soft landing mechanism to prevent a large shock load and tipping over when landing on various types of terrain. The authors previously invented a novel landing mechanism called a telescopic-gear base-extension separation mechanism that operates by means of energy transfer and an adjustable structure. This mechanism passively adjusts the shape of the landing gear according to the landing terrain and transfers the energy of the lander to a spring as potential energy. The outstanding performance of this landing mechanism was demonstrated analytically in a previous study. However, its feasibility was not confirmed, and an effective parameter design method for various shapes of terrains was not presented. Therefore, in this study, two-dimensional experimental investigations are conducted using a small-scale prototype to assess the feasibility of the landing mechanism for several types of terrain. An effective parameter design approach based on a mathematical model derived ...

Human-computer interaction for part selection in product design

We examine how humans can interact with a computing machine to explore good (least cost) combinations of parts in a functionally decomposed modular product. The machine uses data of parts usage from previous applications and generates the preferred combination that meets current design requirements. We use a Boolean function to represent functionality requirements and a classifier to estimate the Boolean function from incomplete previous parts usage information based on a decision tree. When no previous data are available, we propose an efficient data collection strategy. Results from simulation are presented to validate the algorithmic concept.