Aerospace Sciences Research Articles

18th International Conference on Aerospace Sciences and Aviation Technology ASAT-18

List of Contents, Preface, Program of ASAT-18, Conference Venue, Location of Conference Sessions, Contributors, Conference Committees, Reviewers, Opening Lecture, Invited Speakers, Program of Scientific Sessions, s of Scientific Papers, Program of Workshops, Exhibition, Authors Index are available in the pdf.

Self-Healing Anti-Atomic-Oxygen Phosphorus-Containing Polyimide Film via Molecular Level Incorporation of Nanocage Trisilanolphenyl POSS: Preparation and Characterization.

Protection of polymeric materials from the atomic oxygen erosion in low-earth orbit spacecrafts has become one of the most important research topics in aerospace science. In the current research, a series of novel organic/inorganic nanocomposite films with excellent atomic oxygen (AO) resistance are prepared from the phosphorous-containing polyimide (FPI) matrix and trisilanolphenyl polyhedral oligomeric silsesquioxane (TSP–POSS) additive. The PI matrix derived from 2,2’-bis(3,4-dicarboxyphenyl)hexafluoropropane dianhydride (6FDA) and 2,5-bis[(4-amino- phenoxy)phenyl]diphenylphosphine oxide (BADPO) itself possesses the self-healing feature in AO environment. Incorporation of TSP–POSS further enhances the AO resistance of the FPI/TSP composite films via a Si–P synergic effect. Meanwhile, the thermal stability of the pristine film is maintained. The FPI-25 composite film with a 25 wt % loading of TSP–POSS in the FPI matrix exhibits an AO erosion yield of 3.1 × 10−26 cm3/atom after an AO attack of 4.0 × 1020 atoms/cm2, which is only 5.8% and 1.0% that of pristine FPI-0 film (6FDA-BADPO) and PI-ref (PMDA-ODA) film derived from 1,2,4,5-pyromellitic anhydride (PMDA) and 4,4’-oxydianline (ODA), respectively. Inert phosphorous and silicon-containing passivation layers are observed at the surface of films during AO exposure.

Finite Element Modelling of Thermal Behaviour of Solar Cells

Engineering Science Based on Modelling and Simulation (M & S) is defined as the discipline that provides the scientific and mathematical basis for simulation of engineering systems. These systems range from microelectronic devices to automobiles, aircraft, and even oilfield and city infrastructure. In a word, M & S combines knowledge and techniques in the fields of traditional engineering - electrical, mechanical, civil, chemical, aerospace, nuclear, biomedical and materials science - with the knowledge and techniques of fields such as computer science, mathematics and physics, and social sciences. One of the problems that arise during solar cell operation is that of heating them because of permanent solar radiation. Since the layers of which they are made are very small and thick it is almost impossible to experimentally determine the temperature in each layer. In this sense, the finite element method comes and provides a very good prediction and gives results impossible to obtain by other methods. This article models and then simulates the thermal composition of two types of solar cells, one of them having an additional layer of silicon carbide that aims to lower the temperature in the lower layer, where the electronic components stick to degradable materials under the influence of heat.

Low-energy (40 keV) proton irradiation of YBa2Cu3O7−x thin films: Micro-Raman characterization and electrical transport properties**Project supported by the National Natural Science Foundation of China (Grant No. 61473023), the Aerospace Science and Technology Innovation Fund, CASC and International S & T Cooperation Program of China (ISTCP) (Grant No. 2015DFR80190).

To investigate the damage profiles of high-fluence low-energy proton irradiation on superconducting materials and related devices, Raman characterization and electrical transport measurement of 40-keV-proton irradiated YBa2Cu3O7−x (YBCO) thin films are carried out. From micro-Raman spectroscopy and x-ray diffraction studies, the main component of proton-radiation-induced defects is found to be the partial transition of superconducting orthorhombic phase to the semiconducting tetragonal phase and non-superconducting secondary phase. The results indicate that the defects induced in the conducting CuO2 planes, such as increased oxygen vacancies and interstitials, can result in an increase in the resistivity but a decrease in the transition temperature TC with the increase in the fluence of proton irradiation, which is confirmed in the electrical transport measurements. Especially, zero-resistance temperature TCO is not observed at a fluence of 1015 p/cm2. Furthermore, the variation of activation energy U0 can be explained by the plastic-flux creep theory, which indicates that the plastic deformation and entanglement of vortices in a weakly pinned vortex liquid are caused by disorders of point-like defects. Point-like disorders are demonstrated to be the main contribution to the low-energy proton radiation damage in YBCO thin films. These disorders are likely to cause flux creep by thermally assisted flux flow, which may increase noise and reduce the precision of superconducting devices.

The Usability of an Online Learning Management System in an Aviation Curriculum Blended Course Design: A Case Study

The Aviation and Aerospace Science Department of Metropolitan State University of Denver has implemented a third-party Learning Management System (LMS) to standardize learning content in Aviation Fundamentals and Instrument Fundamentals, two core course s in the degree curriculum . Shifting primary content delivery to the online LMS allowed individual instructors to experiment with blended teaching techniques. In an effort to assess the usability of this course design, a survey of all student users was conducted . The findings presented in this article include dat a regarding the overall usability of the LMS system as well as student satisfaction and their preferences surrounding the blended format .

Analysis the Structural Propagations under Stochastic Variables with Arbitrary Probability Distributions Using Machine Learning

Analysing the structural propagations under stochastic variables with arbitrary probability distributions is a complex task due to the inherent uncertainties associated with such variables. Traditional analytical methods often rely on simplifying assumptions, limiting their applicability to scenarios with specific probability distributions. In this study, we propose a novel approach that leverages machine learning techniques to analyze and predict the structural propagations under stochastic variables with arbitrary probability distributions. The main objective of this research is to develop a machine learning-based framework capable of capturing the complex relationships between the stochastic variables and the resulting structural responses. To achieve this, a comprehensive dataset comprising input stochastic variables and corresponding structural responses is collected and pre-processed. Various machine learning algorithms, such as neural networks, random forests, and support vector machines, are trained on the dataset to learn the underlying patterns and correlations.
 The trained models are then used to predict the structural propagations for new sets of stochastic variables, allowing for efficient and accurate analysis without the need for exhaustive analytical calculations. The use of machine learning enables the consideration of a wide range of probability distributions, ensuring a more realistic and comprehensive understanding of the structural behaviour under uncertainties. The proposed methodology offers several advantages over traditional analytical approaches. Firstly, it eliminates the need for restrictive assumptions about the probability distributions, enabling a more flexible analysis that can accommodate real-world scenarios. Additionally, the machine learning-based framework allows for efficient analysis by leveraging the computational power of modern algorithms, reducing the time and effort required for complex calculations.
 The practical implications of this research are significant in fields such as civil engineering, aerospace, and materials science, where understanding and predicting structural behaviours under uncertainties are crucial. The ability to analyze structural propagations under stochastic variables with arbitrary probability distributions using machine learning opens up new possibilities for design optimization, risk assessment, and decision-making processes.
 This study presents a novel approach that utilizes machine learning to analyze and predict the structural propagations under stochastic variables with arbitrary probability distributions. The developed framework offers a flexible and efficient solution for understanding the complex relationships between stochastic variables and structural responses. The findings of this research have significant implications for various industries and pave the way for further advancements in analyzing and managing uncertainties in structural engineering.

Experimental investigation of flapping mechanism of the black-headed gull in forward flight

Many developments in aerospace science have originated from nature. One of these developments has been obtained through inspirations from flying locomotion. The aim of this study is to simulate the flapping mechanism of the black-headed gull in forward flight. The wing of the black-headed gull is characterized entirely by complex dihedral, dividing the wing into two distinct parts. Hence, a flapping mechanism with different bending deflection angles is constructed and compared with a primitive flapping mechanism. Firstly, parametric studies are conducted to assess the role of flapping frequency, velocity and bending deflection angle on the lift, thrust and power loading of the membrane flexible wing at 10 ° angle of attack. Secondly, dimensional analysis is used to establish the similarity between the real gull and the constructed mechanism. Superiority of the bending deflection mechanism is concluded in forward flight against simple flapping wing in terms of aerodynamic forces as well as power loading parameter. It is found that although the aerodynamic coefficients decrease with increase in advance ratio, the best power loading of the black-headed gull is obtained between advance ratio of 2 and 3, in the gull's aerodynamically quasi-steady regime.

6th International Seminar of Aerospace Science and Technology

PrefaceInternational Seminar on Aerospace Science and Technology (ISAST) is yearly seminar sponsored by Indonesian National Aeronautics and Space Agency (LAPAN), to publish the results of research and development the aerospace science and technology conducted mainly in Asian region. The seminar has been held since 2013, therefore in 2018 is its sixth.The theme of this year seminar is Aeronautics and Space Technology Research and Industrial Development. The topics covers aerodynamics, astrodynamics, propulsions, light structures, propellant, energetic materials, avionics, flight dynamics, guidance & control, rocket technology, satellite technology, aircraft technology, flight sensor, and UAV applications. For such topics, eight distinguished scientists become the keynote speakers for the two-days seminar, i.e. Prof. Dr. Heri Budi from LAPAN representing Rocket Propellant Research in Indonesia, Prof. Marc Lesturgie from France representing Aerospace Testing.From 55 papers submitted, 40 papers were selected to be presented in the seminar held in Jakarta, Indonesia, on 25-26 September 2017. The seminar participants from Indonesia came from ITB, LAPAN, and Agency for Technology Assessment and Application (BPPT). International participants came from Hongkong, Universiti Teknologi MARA and Universiti Sains Malaysia, Malaysia, Hongkong University of Science and Technology.Bogor, October 2018ISAST Scientific CommitteeAcknowledgementsInternational Seminar on Aerospace Science and Technology (ISAST) 2018 was supported by Indonesian National Aeronautics and Space Agency (LAPAN).

Biobased thiol-epoxy shape memory networks from gallic acid and vegetable oils

Shape memory polymers play an increasingly significant role in the fields of electronics, aerospace and medical science. However, the most of shape memory polymers are derived from petroleum resource nowadays. Herein, biobased thiol-epoxy shape memory network was obtained from gallic acid-based thiol and diglycidyl ether of bisphenol A (DGEBA). The resulting network shows good shape memory performance with the shape-fixity ratio of 98.7%, shape-recovery ratio of 97.7% andexcellent cycle stability, which is comparable to the petroleum counterparts. Further, epoxidized vegetable oils were incorporated into the above thiol-epoxy network to investigate the effect of epoxidized vegetable oils on the properties of the resulting networks. After introducing the vegetable oils, shape-fixity ratios show irrelevance with the network structures and keep above 96%. Shape-recovery ratio declines with the increase of epoxidized linseed oil (ELO) contents, but when ELO content equals to 20 wt% of DGEBA, shape-recovery speed enhances compared to the network without epoxidized vegetable oils. This is the first attempt to fabricate the thiol-epoxy shape memory networks from renewable biomasses.

An infrared and visible image fusion method based upon multi-scale and top-hat transforms**Project supported by the National Natural Science Foundation of China (Grant No. 61402368), Aerospace Support Fund, China (Grant No. 2017-HT-XGD), and Aerospace Science and Technology Innovation Foundation, China (Grant No. 2017 ZD 53047).

The high-frequency components in the traditional multi-scale transform method are approximately sparse, which can represent different information of the details. But in the low-frequency component, the coefficients around the zero value are very few, so we cannot sparsely represent low-frequency image information. The low-frequency component contains the main energy of the image and depicts the profile of the image. Direct fusion of the low-frequency component will not be conducive to obtain highly accurate fusion result. Therefore, this paper presents an infrared and visible image fusion method combining the multi-scale and top-hat transforms. On one hand, the new top-hat-transform can effectively extract the salient features of the low-frequency component. On the other hand, the multi-scale transform can extract high-frequency detailed information in multiple scales and from diverse directions. The combination of the two methods is conducive to the acquisition of more characteristics and more accurate fusion results. Among them, for the low-frequency component, a new type of top-hat transform is used to extract low-frequency features, and then different fusion rules are applied to fuse the low-frequency features and low-frequency background; for high-frequency components, the product of characteristics method is used to integrate the detailed information in high-frequency. Experimental results show that the proposed algorithm can obtain more detailed information and clearer infrared target fusion results than the traditional multi-scale transform methods. Compared with the state-of-the-art fusion methods based on sparse representation, the proposed algorithm is simple and efficacious, and the time consumption is significantly reduced.

Tabletop Testbed for Attitude Determination and Control of Nanosatellites

AbstractTo simulate the conditions of the space environment at ground, the Laboratory of Application and Innovation in Aerospace Science (LAICA) of the University of Brasilia (UnB) is developing a ...

A photogrammetric approach for masking particle image velocimetry images around moving bodies**A preliminary version of this work was presented at the 55th AIAA Aerospace Sciences Meeting (Grapevine, Texas, USA), 9–13 January 2017.

Masking particle image velocimetry images can be a time consuming process in experiments involving moving bodies. Aircraft store separation and pitching airfoil investigations are examples of studies where particle image velocimetry data has to be acquired for many different body positions to properly resolve the attributes of the unsteady flow field. Laser reflections, perspective projection of the body, and non-uniform illumination in raw images can cause intensity-based algorithmic masking routines to fail in determining the correct mask for each individual image. A novel approach for automatic masking in moving body experiments is introduced in this paper. A pitching airfoil experiment is used to demonstrate the capability of the methodology. Photogrammetry is used to locate the airfoil model in the images and map the 3D body to the image space and define a mask. After performing photogrammetry for several known angles of attack and calibrating the photogrammetry parameters for each angle, a model was developed to estimate the parameters at other angles of attack where calibration data are not available. Results indicate that obtaining the necessary parameters required for masking a few reference images allows for robust automated masking of the remaining images leading to significant time reduction in the masking process. Masks generated using the automated masking technique show agreement with those generated by direct photogrammetry; the error in the predicted location remains less than 0.3% of the chord length. The automatically-generated masks prove to be effective when processing PIV images with the airfoil in different locations.

Exact and Heuristic Methods for Observing Task-Oriented Satellite Cluster Agent Team Formation

With the development of aerospace science and technology, Earth Observation Satellite cluster which consists of heterogeneous satellites with many kinds of payloads appears gradually. Compared with the traditional satellite systems, satellite cluster has some particular characteristics, such as large-scale, heterogeneous satellite platforms, various payloads, and the capacity of performing all the observation tasks. How to select a subset from satellite cluster to perform all observation tasks effectively with low cost is a new challenge arousing in the field of aerospace resource scheduling. This is the agent team formation problem for observation task-oriented satellite cluster. A mathematical scheduling model is built. Three novel algorithms, i.e., complete search algorithm, heuristic search algorithm, and swarm intelligence optimization algorithm, are proposed to solve the problem in different scales. Finally, some experiments are conducted to validate the effectiveness and practicability of our algorithms.

80 years education of aerospace science and technology in Tsinghua University

The development of aerospace science and technology largely relies on the education and academic contribution of students in universities covering aerospace science and technology. The School of Aerospace Engineering of Tsinghua University, with a history of eighty years since the set-up of its Department of Aeronautical Engineering in 1938, graduated 5273 undergraduate students, 1939 master students and 931 Ph.D. students. This paper provides an overview and analysis of the data related to undergraduate, master and Ph.D. students of this school. These data include the historical evolution of number of students and the actual status of students like their various interests and academic performance. The data and information shared in this paper may be useful for comparative study and for those who need primitive data to study relevant issues such as mental health of students, promotion of gender balance and educational improvement.

The Effects of Maleic Anhydride Grafted PP (MAPP) on the Mechanical Properties of Injection Moulded Kenaf/CNTs/PP Composites

Composite materials have increasingly become crucial in manufacturing engineering products and producing commodity materials in the major industries including; automotive, aerospace, marine, construction, agriculture and health science. However, several improvements regarding the strength, dimensional stability and the cost of production are required. In this study, composite of Kenaf, multi-wall carbon nanotube (MWCNT) and polypropylene (PP) with maleic anhydride-grafted polypropylene (MAPP) are examined. The results highlight that increasing MAPP loading, in turn, increases the value of the mechanical properties. The composites are produced by blending kenaf/MWCNT/PP using a Sigma blade mixer and injection moulding. Injection moulding is a significant operation used to produce plastic products. In the study, Kenaf core fibre was mixed with MWCNT and polypropylene, in addition to MAPP. The MAPP is added by applying different percentage (1, 2, 3 and 4 wt. %) during the blending process. The main objective of the study was to analyse the effects of MAPP concentrations on the mechanical properties of the Kenaf/MWCNT/PP composite. The results of the study established that MAPP 3 wt. % concentration with MWCNT 3 wt. % loading and Kenaf 30 wt. % filler provide optimum results for the composites. There was approximately, a 21% enhance in tensile strength of Kenaf 30 wt. %/MWCNT, 3 wt. %/MAPP, 3 wt. %/PP observed compared to the (without) MAPP composite. The composites with coupling agent stimulate better filler dispersion between Kenaf, MWCNT and PP observed using a scanning electron microscope (SEM) and field-emission scanning electron microscope (FESEM).

5th International Seminar on Aerospace Science and Technology

PrefaceInternational Seminar on Aerospace Science and Technology (ISAST) is a yearly seminar sponsored by Indonesian National Aeronautics and Space Agency (LAPAN), to publish the results of research and development the aerospace science and technology conducted mainly in the Asian region. The seminar has been held since 2013 and is in it's fifth year in 2017.The theme of this year's seminar is Development of Aeronautics and Space Technology to Support Maritime Applications. The topics cover aerodynamics, astrodynamics, propulsions, light structures, propellant, energetic materials, avionics, flight dynamics, guidance & control, rocket technology, satellite technology, aircraft technology, flight sensor, and UAV applications. For such topics, seven distinguished scientists become the keynote speakers for the two-day seminar: Prof. Dr. Erna Sri Adiningsih from LAPAN representing Remote Sensing Satellite technology, Prof. Dr-Ing. Nicolas Gascoin from France representing rocket propulsion technology, Prof. Yoshifumi Inatani from JAXA, Japan, representing interplanetary space mission, Dr. Rais Zain from Institut Teknologi Bandung(ITB) representing aircraft design, Prof. Qin Shiyin from Beihang University, China, representing Guidance and Control technology for UAV, Dr. I Gusti Agung Aditya Jaya from Indonesia representing aircraft maintenance technology, and Dr. Himsar Ambarita from North Sumatera University (USU) representing computational science in fluid mechanics.From 79 papers submitted, 50 papers were selected to be presented in the seminar held in Medan, North Sumatra, Indonesia, on 27-29 September 2017. The seminar participants from Indonesia came from ITB, USU, Universitas Gajah Mada, LAPAN, Agency for Technology Assessment and Application (BPPT), and Indonesian Aerospace (PTDI). International participants came from Hongkong, Universiti Teknologi MARA and Universiti Sains Malaysia, Malaysia, Hongkong University of Science and Technology, and University of Surrey, UK.Bogor, October 2017ISAST Scientific Committee

Acknowledgements

International Seminar on Aerospace Science and Technology (ISAST) 2017 was supported by Indonesian National Aeronautics and Space Agency (LAPAN).

Can the implementation of aerospace science in elementary school help girls maintain their confidence and engagement in science as they transition to middle school?

There is a global crisis due to a lack of qualified applicants entering STEM careers, especially in science. Add the fact that women are greatly underrepresented in science, and the solution becomes obvious. Go to the source, and find out why girls as young as 12 years old are losing an interest in scientific endeavors that they once found to be captivating. This action research project sought to find out if the implementation of aerospace science, embedded both in the classroom and in an after school Space Club, could assist girls in maintaining their confidence and engagement in science overall as they transition to middle school. Furthermore, girls in fifth through seventh grade, who had previously been the teacher researcher's students, were included in the study in order to discover if their previous participation in a variety of authentic and ongoing aerospace activities had any impact upon their engagement in science as they entered the notable years of declined interest. The research took place at an international American school, Academia Cotopaxi, in Quito, Ecuador from September 2015 through April 2016. Data was collected through both qualitative and quantitative sources, and included attitude surveys, parent questionnaires, a writing prompt, photos, video, interviews and observations. Additionally, a control group was utilized in grades five to seven for purposes of comparison. Innovative activities included engaging and first-hand experiences with the Ecuadorian Civilian Space Agency (EXA), the National Aeronautics Space Administration (NASA), Space X and the Canadian Space Agency (CSA). Inquiry-based activities included, but were not limited to, experiences with: speaking live with both astronauts and cosmonauts on the International Space Station, robotics, rocketry, Skype chats with aerospace professionals, utilizing the Design Process, online resources and more. Findings suggested that embedding aerospace science in grade four, both during and after school hours, not only increased girls' interest and confidence in science, but also served to maintain and foster an interest in STEM as they transitioned to middle school.

FDI AND ADAPTIVE THRESHOLD DETECTION OF PILOT BY APPLICATION DEVELOPMENT OF AVAILABLE MODELS USING BOND GRAPH METHOD

Hitherto, in the field of aerospace science and industry, some acceptable results from control behavior of human operator (pilot), are caught using usual methods. However, very fewer research, has been done based on personal characteristics. The performed investigations, show that many of happened faults (especially in helicopter), would result to the loss of natural behavior of system, and eventually some fatal accidents. Therefore, development of tools of assessment of pilot in this dynamical system, is one of the vital necessities. The tools of management of system, should be such that, can show the fault. The object of this paper is assessment of the modelled pilot in a simulator, in presence of standard fly inputs. For this purpose the performance of the pilot for collective control of the helicopter, is investigated. By now, some models for the human operator is presented, and in this paper one of them that is presented by Hess is used, and the helicopter systems that perform the controlling action are modeled by bond graph. The existence of uncertainties in the simulator system and the modeled pilot’s behavior, causes creation of fault threshold, for human behavior of pilot. By having these fault thresholds, the improper actions of the pilot, cause creation of behavioral reminders, which can perform the assessment of the pilot. By other speech, using fault detection and isolation (FDI), by bond graph method in state space, the assessment is performed and a non-zero reminder shows existence of fault in the system. Therefore, in this paper there are the novelties for modeling the pilot’s body performance and the helicopter’s systems integrally and designing a fault detection system for it that shows the source of the fault, and obviously it can be useful in aviation industry.Keywords: Helicopter Control, Human Model, Fault Detection and Isolation, Human Fault, Bond Graph

Two-probe calibration integral equation method for nonlinear inverse heat conduction problem of surface heat flux estimation

In this paper, a new two-probe surface heat flux calibration integral equation method (CIEM) is proposed for resolving nonlinear inverse heat conduction problem possessing temperature-dependent thermophysical properties and an unknown time-varying back surface boundary condition. Compared to the one-probe CIEM, the two-probe CIEM can be applied to a more general class of one-dimensional inverse heat conduction problems that can be used for accurately predicting the front surface heat flux without any restrictions on the back surface boundary condition. Temperature-dependent thermophysical properties and probe locations are not specified a priori but are implicitly accounted through a calibration campaign. The final mathematical formulation involves resolving a Volterra integral equation of the first kind for the unknown surface heat flux. A first kind Chebyshev expansion possessing undetermined coefficients, is used for approximating the introduced property transform function. Next, three well-defined calibration tests are used for estimating the undetermined coefficients associated with the Chebyshev expansion. A time sequential study of the coefficients is shown to yield the optimal truncation of the series expansion. A future-time method is applied for stabilizing the ill-posed first kind Volterra integral equation. Phase plane and cross-correlation analyses are employed for estimating the optimal regularization parameter (i.e., the future-time parameter) from a spectrum of chosen values. The effectiveness of the proposed approach is verified by numerical simulation using stainless steel as the host material. The calibration-based or “parameter free” inverse approaches significantly reduce time and costs in the resolution of the surface condition as there is no need to experimentally determine the thermophysical properties, probe locations, and probe characteristics. These system properties are implicitly included in the proposed calibration procedure. Many applications, especially in aerospace sciences where exotic materials are often used, do not have replicable properties among samples. Conventional inverse methods rely on accurately specifying the input parameters for forming the predictions. These “parameter required” methods are solely based on numerical algorithms and thus their predictions are strongly relied on accurate input of parameters and measured probe data.