International Journal of Aviation Science and Engineering - AVIA

Analysis of Star Catalog Model Based on The Nearest Star Composition and Brightest Star as Guide Star

2025-01-11T07:18:15+07:00

Star sensor is the most advanced attitude determining instrument for spacecraft with very high accuracy, and it is independent of other attitude sensors. However, the star sensor's accuracy and processing time depend on selecting the algorithm, which starts from detecting the star pattern until the matching process with the star catalog. The star catalog consists of the right ascension and declination of stars' position and magnitude for 250.000 stars which need a large memory size. Therefore, modifying a new star catalog consisting of guide stars' position,
magnitude, and nearest star composition can reduce the required memory and processing time without losing accuracy. T he nearest star catalog model in this paper used radial based featurewhere for each guide star candidate, the number of stars in each binary (bin) layer around the guide star will be calculated. This paper focuses on determining the best architecture for the nearest star catalog model, such as the number of bin layers and bin ranges, and the influence of
star sensor field of view and guide star limitation with the model's accuracy. The proposed star catalog provides excellent performance in low-cost star sensors with a high and medium field of view.

Æ-6 eLena; Conceptual Design of 6-Seater Electric Aircraft

2025-01-11T07:18:15+07:00

Globalization has made a huge impact on worldwide interaction and integration in our lives. Traveling between locations, for instance, has become easier with the advancement of transportation modes such as aircraft. However due to the ever-increasing environmental concerns, alternatives of conventional aviation fuels have become necessary in order to provide more eco-friendly flights. Fortunately, alternatives such as aircraft batteries have become feasible with technology improvements, allowing an idea for resolving the issue, namely the development of an electric aircraft. This paper will be focused on designing a six-seater electric aircraft through parametric studies on several aspects such as aircraft configurations, weight and balance, stability, performance, structures, aerodynamics, and cost analysis while also aiming to meeting the given DRO. The designed aircraft, Æ-6 eLena, has a range of 540 km, a takeoff weight of 3003 kg, a cruising speed of 300 km/hr, and a lift-to-drag ratio of 13.5. The conceptual design of this aircraft is intended to be certified under current CASR 23 regulations, with production beginning in 2026.

Load Cell Design for Measurement of Propeller Thrust

2025-01-11T07:18:15+07:00

The design, analysis, and prototype testing of a load cell for measuring propeller thrust generated by propeller rotation in this study. Design concepts factors of safety, yield strength, stress, and strain values were evaluated using Solidworks simulation to ensure that the load cell would not fail. The force applied to the load cell is measured by four strain gauges connected in a Wheatstone bridge connection and amplified by HX711 amplifier. These instruments is then connected to Arduino and 16x2 LCD. A static testing was carried out to measure the thrust from an APC 6x4E propeller and compared with validated results to validate the accuracy of the load cell. The built-in load cell experimental results were compared to a commercialised load cell, manufacturer data and blade element momentum theory from other studies. A graph of thrust against propeller rotational speed was constructed. The rotational speed that starts to detect the thrust is about 2000RPM. The error between prototype load cell to the manufacturer, RC benchmark and BEMT is less than 1%, 0.05% and 0.05%, respectively.

Effects of Transition Strip on Aerodynamic Yaw Derivatives of MULDICON Wing using an Oscillating Rig at Various Angle of Attack

2025-01-11T07:18:15+07:00

This paper presents the effects of the passive flow control technique using transition strips on the transient aerodynamic stability derivative measured on the MULDICON AVT251 wing. The experiments were performed at two configurations; clean wing configuration and the transition strips attached to wing leading edge. MULDICON wind tunnel model was designed and fabricated in UTM based on the AVT251 design. The dynamic measurements were carried out in the Universiti Teknologi Malaysia Aerolab wind tunnel for Reynolds number of 0.3x10⁶ & 0.475x10⁶. MULDICON model was confined to oscillate with a single degree of freedom in yawing motion. The aerodynamic stability derivatives & are measured as aerodynamic stiffness and damping by extracting the stiffness and damping of the dynamic oscillating rig system. Springs of different stiffness are used to vary the oscillation frequencies with the reduced frequency range of 0.004-0.08. The unsteady aerodynamics effects are examined for both wing configurations. The angle of attack varies from α = 0° to 20° by comparing the transient measurements from the dynamic UTM-LST to the steady-state wind tunnel measurements. The dynamic results indicate that the aerodynamic stiffness derivative is not constant and exceeds the static values and strongly correlates with reduced frequency. The aerodynamic damping derivative is a function of reduced frequency as the damping derivatives become more negative with the increase of the reduced frequency. The amplification factor for the stiffness derivative is above unity which indicates that the steady-state derivative is under-predicted.

A feature extraction method for star identification algorithm based on convolutional neural network

2025-01-11T07:18:15+07:00

The need to determine the orientation while in "Lost-In-Space (LIS)" is essential for spacecraft navigation. Star pattern recognition, also known as the star identification algorithm, plays a vital role for a spacecraft in LIS mode. Data-driven solutions for this type of problem are becoming more captivating due to their stochastic nature. This paper presents an efficient feature extraction method for the LIS star identification algorithm using a convolutional neural network. The net pattern and the multi-triangles feature extraction methods are implemented on the model. The proposed idea is tested on several simulated star images having a field of view of 25 by 16 degrees. The obtained results show an improvement in the successful identification rate of star image classes. Furthermore, the algorithm shows promising running time and requires less onboard memory since it eliminates storing a star catalogue for the matching process.