Search

Due to the conflicting nature of quality measures, there are always multiple refactoring options to fix quality issues. Thus, interaction with developers is critical to inject their preferences. While several interactive techniques have been proposed, developers still need to examine large numbers of possible refactorings, which makes the interaction time-consuming. Furthermore, existing interactive tools are limited to the "objective space" to show developers the impacts of refactorings on quality attributes. However, the "decision space" is also important since developers may want to focus on specific code locations. In this paper, we propose an interactive approach that enables developers to pinpoint their preference simultaneously in the objective (quality metrics) and decision (code location) spaces. Developers may be interested in looking at refactoring strategies that can improve a specific quality attribute, such as extendibility (objective space), but they are related to different code locations (decision space). A plethora of solutions is generated at first using multi-objective search that tries to find the possible trade-offs between quality objectives. Then, an unsupervised learning algorithm clusters the trade-off solutions based on their quality metrics, and another clustering algorithm is applied to each cluster of the objective space to identify solutions related to different code locations. The objective and decision spaces can now be explored more efficiently by the developer, who can give feedback on a smaller number of solutions. This feedback is then used to generate constraints for the optimization process, to focus on the developer's regions of interest in both the decision and objective spaces. The manual validation of selected refactoring solutions by developers confirms that our approach outperforms state of the art refactoring techniques.

Airworthiness certification is a mandatory but expensive process in aircraft development. To reduce certification cost, it is desired to incorporate certification considerations into aircraft early...

In space exploration, instruments measuring magnetic fields require magnetic cleanliness because it helps to distinguish the magnetic field generated by the spacecraft from the ambient field. A spacecraft has its own DC and AC magnetic fields generated by the current flow and residual moments of the spacecraft instruments. Therefore, analysis and testing are required in the development phase. The Korea Pathfinder Lunar Orbiter (KPLO) carries the KPLO Magnetometer (KMAG) instrument to observe magnetic fields on the lunar surface and the space environment around the Moon. To verify the magnetic cleanliness of the KPLO, we analyzed the magnetic field generated by it. We used the positional information and the magnetic dipole moments of twenty-five instruments, with which the KPLO is equipped. The analysis method was a Python program using magpylib. Finally, the worst-case analysis results showed that the spacecraft field around the magnetometer is less than 700 nT, which is the KMAG magnetic cleanliness requirement.

This article develops a system dynamics model for innovation ecosystems in the high-tech industry. The model emphasizes the interactions between high-tech enterprises, the government, and universities in the innovation process. In particular, we use two high-tech instruments, the Mars Rock Corer and the Soil Preparation System, in the aerospace innovations developed by Hong Kong Polytechnic University. These instruments are a byproduct of collaborations with the European Space Agency, Russian Space Agency, and China Space Agency. They span decades of space missions to the moon and Mars. Furthermore, we propose a three parities systems dynamics model to study innovation behaviors. This model can be used to study and analyze the stakeholders’ interactions in high-technology-oriented innovation ecosystems. Theoretical, computational, and simulation studies are also conducted to understand and evaluate the evolution of the ecosystem. The results demonstrate the feasibility and effectiveness of this approach, which can be applied in on a large scale and in complex space projects.

The paper discusses the use of methane (generated in the process of oxygen recovery from carbon dioxide released by the crew during its hydrogenation in the Sabatier reaction, with subsequent extraction of 61% of oxygen through electrolysis of the resultant water) in a regenerative life support system for crews on space missions. It demonstrates that the methane resulting from Sabatier reaction can be used both for pyrolysis in order to return the resulting hydrogen into this reaction so as to extract 100% of oxygen from carbon dioxide, and for producing food protein for life support in space. The use of methane pyrolysis was enabled by new technologies which allowed lowering the process temperature down to 500–700°C and obtaining the easy-to-remove carbon. It provides recommendations for designing space systems for methane pyrolysis. The paper makes the case for use of the existing processes for industrial production of protein from methane using methanotrophic bacteria in the production of food protein for space food rations, determines the balance of a closed-loop methanotrophic reaction, provides calculation basis and recommendations for designing space systems for methanotrophic production of food protein. Development of a system for food protein production from methane will enable its use as one of the systems for providing food on the Moon and Mars, as well as a backup system in space transportation missions. Key words: space missions, crew life support, СО2 hydration, methane pyrolysis, methanotrophic bacteria, food protein.

Capturing near-Earth asteroids would be of great significance for future space missions. Due to its stability, distant retrograde orbit (DRO) around the Earth has the potential to be an ideal destination for the captured asteroids. In this paper, we propose three strategies to capture asteroids to DROs in the model of the circular restricted three-body problem in the Sun–Earth system. In the manifold-assisted strategy, Lyapunov orbits that are tangential to DROs are calculated, and then stable manifolds are employed to design transfers for capturing asteroids. The non-coplanar Hohmann transfer is used to guess the total cost of capturing an asteroid, and candidate asteroids are thus selected. The second strategy of asteroid capture is defined as direct capture to increase opportunities of capturing asteroids with low cost. The captured asteroid can be inserted into the target DRO with a maneuver at any position along the DRO. Then optimal results are obtained after analyzing the capture conditions. Finally, a strategy of using a flyby of the Earth is proposed as the power Earth-flyby capture, and an additional maneuver is imposed on an asteroid at the perigee of the transfer trajectory. Results show that the direct and powered Earth-flyby asteroid capture strategies potentially need fewer velocity increments than the manifold-assist strategy. Furthermore, 2020SO can be captured into DROs with lower energy than the other candidate asteroids in three capture strategies, and the minimum cost is approximately 189.93 m/s.

Most space missions utilize energy storage, such as a rechargeable battery onboard the spacecraft. Therefore, a continuing evolution of battery performance can benefit a wide gamut of space science...

A considerable volume of high-resolution remote sensing (HRRS) data is generated with the intense space explorations happening globally. Remote sensing image retrieval (RSIR) is a fundamental task ...

Leading space agencies are increasingly investing in the gradual automation of space missions. In fact, autonomous flight operations may be a key enabler for on-orbit servicing, assembly and manufacturing (OSAM) missions, carrying inherent benefits such as cost and risk reduction. Within the spectrum of proximity operations, this work focuses on autonomous path-planning for the reconstruction of geometry properties of an uncooperative target. The autonomous navigation problem is called active Simultaneous Localization and Mapping (SLAM) problem, and it has been largely studied within the field of robotics. Active SLAM problem may be formulated as a Partially Observable Markov Decision Process (POMDP). Previous works in astrodynamics have demonstrated that is possible to use Reinforcement Learning (RL) techniques to teach an agent that is moving along a pre-determined orbit when to collect measurements to optimize a given mapping goal. In this work, different RL methods are explored to develop an artificial intelligence agent capable of planning sub-optimal paths for autonomous shape reconstruction of an unknown and uncooperative object via imaging. Proximity orbit dynamics are linearized and include orbit eccentricity. The geometry of the target object is rendered by a polyhedron shaped with a triangular mesh. Artificial intelligent agents are created using both the Deep Q-Network (DQN) and the Advantage Actor Critic (A2C) method. State-action value functions are approximated using Artificial Neural Networks (ANN) and trained according to RL principles. Training of the RL agent architecture occurs under fixed or random initial environment conditions. A large database of training tests has been collected. Trained agents show promising performance in achieving extended coverage of the target. Policy learning is demonstrated by displaying that RL agents, at minimum, have higher mapping performance than agents that behave randomly. Furthermore, RL agent may learn to maneuver the spacecraft to control target lighting conditions as a function of the Sun location. This work, therefore, preliminary demonstrates the applicability of RL to autonomous imaging of an uncooperative space object, thus setting a baseline for future works.

Recent advancements in CubeSat technology unfold new mission ideas and the opportunity to lower the cost of space exploration. Ground operations costs for interplanetary CubeSats, however, still represent a challenge toward low-cost CubeSat missions: hence, certain levels of autonomy are desirable. The feasibility of autonomous asteroid flyby missions using CubeSats is assessed here, and an effective strategy for autonomous operations is proposed. The navigation strategy is composed of observations of the Sun, visible planets, and the target asteroid, whereas the guidance strategy is composed of two optimally timed trajectory correction maneuvers. A Monte Carlo analysis is performed to understand the flyby accuracies that can be achieved by autonomous CubeSats, in consideration of errors and uncertainties in a) departure conditions, b) propulsive maneuvers, c) observations, and d) asteroid ephemerides. Flyby accuracies better than ±100 km (3σ)" role>±100 km (3σ)±100 km (3σ) are found possible, and main limiting factors to autonomous missions are identified, namely a) on-board asteroid visibility time (Vlim≥11" role=>Vlim≥11Vlim≥11), b) ΔV" role=">ΔVΔV for correction maneuvers (>15 m/s>15 m/s), c) asteroid ephemeris uncertainty (

Biological experiments on bacteria in extra-terrestrial environments have recently gained increased importance in the context of space exploration and the human space programme. Here, we demonstrate a modular self-contained device, based on the lab-on-a-chip (LoC) paradigm, for performing miniaturized biological experiments in microgravity or outer space environments. The device is designed to incubate microscopic organisms; in the present work it was employed to incubate bacteria via a suitable actuation mechanism and measure bacterial activity over long term by periodic querying, sensing and data transmission/storage. Growth is measured using optical density measurements using an on-board LED/photo-diode pair. The modular design enables several simultaneous experimental runs arranged in individual cartridges, each containing multiple experiments in separate cassettes. This allows for statistical significance and in-built redundancy in case of remote failure. We use this system to study the growth pattern of Sporosarcina pasteurii, a spore-forming bacteria widely explored for its capability to induce calcite precipitation. Growth in the device was confirmed by continuous monitoring of optical density (OD), as well as post log-phase optical and scanning electron microscopy (SEM). Additionally, the performance of the device was evaluated at multiple temperatures, pressures and under different device orientations, and found to be unchanged within experimental error. Given its modular structure, the proposed platform can be easily adapted as a biological payload for self-contained LoC based studies of other microorganisms in microgravity environments.

The goal of this work was to investigate the feasibility of developing machine learning models for predicting the values of aircraft configuration design variables when provided with time series of...

GPUs became the reference platform for both training and inference phases of Convolutional Neural Networks (CNN) due to their tailored architecture to the CNN operators. However, GPUs are power-hungry architectures. A path to enable the deployment of CNNs in energy-constrained devices is adopting hardware accelerators for the inference phase. The design space exploration of CNNs using standard approaches, such as RTL, is limited due to their complexity. Thus, designers need frameworks enabling design space exploration that delivers accurate hardware estimation metrics to deploy CNNs. This work proposes a framework to explore CNNs design space, providing power, performance, and area (PPA) estimations. The heart of the framework is a system simulator. The system simulator front-end is TensorFlow, and the back-end is performance estimations obtained from the physical synthesis of hardware accelerators, not only from components like multipliers and adders. The first set of results evaluate the CNN accuracy using integer quantization, the accelerators PPA after physical synthesis, and the benefits of using a system simulator. These results allow a rich design space exploration, enabling selecting the best set of CNN parameters to meet the design constraints.

Since the seminal work of Daniele Mortari (“Moon-Sun Attitude Sensor,” Journal of Spacecraft and Rockets, Vol. 34, No. 3, 1997, pp. 360–364), the concept of an attitude sensor using images of illuminated celestial bodies has been pushed forward through the years. The basic idea consists of extracting two independent directions from the image of a celestial body, namely, the camera-to-planet and the planet-to-sun directions. The former is estimated from the center of an ellipse fitted to the imaged limb points and the latter from the symmetry axis of the illuminated region. These assumptions, however, only hold for far-distant spherical targets. In this work, the problem is reformulated in the framework of projective camera transformations of quadrics and conics, and an algorithm estimating the line of sight to the planet and the illumination direction from the limb and terminator ellipses, respectively, is presented. The method is applicable to any ellipsoidlike celestial body having known orientation. The algorithm is first validated on synthetically generated images and then tested using real pictures of Dione and Enceladus satellites gathered from Cassini spacecraft. Results show that the sensor concept returns rms errors in the order of the angular width of a pixel in computing the nadir direction, and subdegree accuracy in computing the sun direction.

With the rapid development of space technology and the increasing demand for space missions, the traditional spacecraft manufacturing, deployment and launch methods have been unable to meet existing needs. In-space assembly (ISA) technologies can effectively adapt to the assembly of large space structures, improve spacecraft performance, and reduce operating costs. In this paper, the development and technologies for ISA are reviewed. ISA is classified from multiple angles, and the research status of ISA is shown clearly through the visual mapping knowledge domain. Then the development status of autonomous robot assembly in the United States, Europe, Japan, Canada and China is reviewed. Furthermore, the key technologies of ISA are analyzed from three aspects: assembly structure design, robot technologies and integrated management technologies. ISA technologies are still facing major challenges and need to be further explored to promote future development. Finally, future development trends and potential applications of ISA are given, which show that ISA will play a vital role in human space exploration in the future.

Crew time requirements for human space exploration missions is as critical as mass, energy, and volume requirements. However, it has only been sporadically recorded in past analog and space missions for plant cultivation. In this retrospective study on crew time data collected in various analog facilities and on the Veggie hardware on ISS, we propose a methodology for efficient categorizing and reporting of crew time in space plant growth systems. Crew time is difficult to capture in operational environments, and this study intends to harmonize these efforts among different locations. This article also provides a current database for required crew time in several plant growth hardware and facilities, on the ISS, and on Earth. These data could serve mission planners as a baseline to establish standardized activities and extrapolate crew time needed to operate future plant growth units. Finally, we discuss how crew time needed for plant cultivation will change in future exploration missions, based on choices made for plant species, watering systems, level of automation, and use of virtual assistants, among others. Crew time will need to be accounted for as a decisive factor to design future space greenhouse modules.

As small satellites are finding increased applicability in a number of space missions, the community is actively exploring the feasibility of missions employing active instruments on small spacecraft. In particular, synthetic aperture radars are of interest as they prove to be versatile tools for Earth Observation purposes. This paper proposes a trade space exploration model to identify designs for space-borne satellite synthetic aperture radars that address the desired instrument requirements. Two trade space analysis approaches are proposed, based on a multivariate analysis with two evaluation metrics and using parallel coordinate plots. The paper demonstrates the utility of the trade space model by considering two case studies. The first study looks at radar instruments on a broad range of small satellite platforms. This study narrows down a trade space of 1265 feasible radar designs to less than 44 Pareto optimal designs at different center frequencies (C- and X-band), elicits conditions for L-band SARs feasibility, and discusses the feasibility bounds and technical constraints on associated instrument and spacecraft requirements. The second study considers radars for 3U CubeSat platforms. The study identifies 44 Pareto optimal designs within 12,928 feasible designs and sheds light on the operational constraints required for the development of such innovative miniaturized radars.

For on-orbit repair and space debris removal missions, a collision-free trajectory to the target is to be planned in a dynamically changing environment. Although such a trajectory can be learned in a ground simulator through repetitive trials, the established environment is often of limited precision due to space perturbations and measurement errors. Considering possible discrepancies between simulation and the real world, a tunnel, instead of a single trajectory, should be learned on the ground. In this paper, a robust planning method based on Q-learning is proposed for space missions with a priori environment information of limited precision. Based on a specific on-orbit repair scenario, reward functions in accordance with the multiple mission objectives are designed. The trajectories learned under different parameter randomization settings are combined and a robust tunnel is generated in the discrete grid world. By keeping the spacecraft inside the tunnel in the actual mission, collisions with the dynamic obstacles would be avoided and the goal of target rendezvous would be achieved. At last, a numerical simulation is carried out and the proposed method is validated under both nominal and randomized conditions.

This paper presents a novel application of a Multi-frame Super Resolution (MFSR) method for lunar surface imagery called Lunar HighRes-net (L-HRN) . In this work, we adapted and used NASA's Lunar Reconnaissance Orbiter (LRO) image database to train the Deep Learning architecture for image super resolution. Additionally, we also gathered an artificial image dataset from our virtual Moon to improve the amount of input data in the neural network training process. The network's architecture follows a standard MFSR algorithm that was enhanced for this specific use case. The proposed MFSR method has been evaluated using the well-known peak signal-to-noise ratio (PSNR) metric against other generic super-resolution methods of the state of the art. This work aims to improve environmental knowledge about the lunar surface to enhance future autonomous robots capabilities on the surface of the Moon.

In this paper, an integrated optimal flight plan with a guidance plan in a general transfer orbit is considered. Due to the need to simultaneously reduce energy consumption and flight time in some space missions, the spacecraft trajectory is optimized based on two criteria to minimize fuel consumption and flight time in the orbital transfer process. For this purpose, the total velocity impulse on both sides of the transition orbit and the elapsed time are defined as the criteria of the objective function which includes the spacecraft’s insertion conditions and orbital parameters related to the shape of the trajectory. The optimal transition (coasting) trajectory is then obtained using the multi-objective genetic algorithm (MOGA) search method. Subsequently, the velocity-to-be-gained guidance steering scheme is integrated to track the trajectory onboard and reach the final orbit. The numerical results of the proposed algorithm are extracted in three case studies and compared with other references that show its ability to find the optimal transfer.

The runway for the General Planetary Vehicle is a unique in scale and complexity infrastructural construction - an overpass with a length of 40 000 km, covering the planet along the equator and combined with a string-rail transport of the second level. This high-tech structure is a supporting structure for the General Planetary Vehicle and a communication artery that ensures the movement of passengers and goods, as well as the transfer of large amounts of energy and information. The article discusses the location of the overpass in the plan, indicates the most difficult sections and ways to overcome them. The options for the layout of the General Planetary Vehicle overpass are proposed, the main functional areas and structural elements are described. Significant factors affecting the implementation of the project, the problems inevitable in the development of the main elements, as well as solutions to optimize this transport and infrastructure complex have been identified. Solutions were proposed to optimize the overpass routing to overcome mountainous areas of the earths surface, considering the required takeoff and landing characteristics of the General Planetary Vehicle.

Radio astronomy and Space Infrastructures in the Azores have a great scientific and industrial interest because they benefit from a unique geographical location in the middle of the North Atlantic allowing a vast improvement in the sky coverage. This fact obviously has a very high added value for: i) the establishment of space tracking and communications networks for the emergent global small satellite fleets ii) it is invaluable to connect the radio astronomy infrastructure networks in Africa, Europe and America continents using Very Large Baseline Interferometry (VLBI) techniques, iii) it allows excellent potential for monitoring space debris and Near Earth Objects (NEOs). There is in S. Miguel island a 32-metre SATCOM antenna that could be integrated in advanced VLBI networks and be capable of additional Deep Space Network ground support. This paper explores the space science opportunities offered by the upgrade of the S. Miguel 32-metre SATCOM antenna into a world-class infrastructure for radio astronomy and space exploration: it would enable a Deep Space Network mode and would constitute a key space facility for data production, promoting local digital infrastructure investments and the testing of cutting-edge information technologies. Its Atlantic location also enables improvements in angular resolution, provides many baseline in East-West and North-South directions connecting the emergent VLBI stations in America to Europe and Africa VLBI arrays therefore contributing for greater array imaging capabilities especially for sources or well studied fields close to or below the celestial equator, where ESO facilities, ALMA, SKA and its precursors do or will operate and observe in the coming decades., Comment: 14 pages, 7 figures, 3 tables. Accepted for Publication at Advances in Space Research, COSPAR, Elsevier

Spacecraft relative trajectory planning is central to many space missions like on-orbit service and debris removal. While early attempts of machine-learning-based trajectory planning have been witnessed, they still face the open problem of how to acquire sufficient training samples to conduct robust training. In this article, we have introduced a meta-learning framework to improve the adaptation ability of the planner when facing new initial conditions. To achieve this goal, we divided the training trajectories as sub-training samples and fake testing samples. Then, the meta planner is trained by repeatedly conducting a trail training-and-testing process. To this end, the gradient information of the meta learner is initially obtained on the subtraining sets and is further adjusted by looking at its testing performance on those fake testing data. Therefore, the meta planer explicitly take account of the potential testing performance into consideration and, hence, alleviate the overfitting phenomena with few training trajectories. Simulation results substantiate the effectiveness of our approach, as well as the advantages of quick adaptation to new initial conditions without overfitting.

For the design of space missions in the Moon and planets, analysis of mobility in robots is crucial and poor planning has led to abortion of missions in the past. To mitigate the risk of mission failure, improved algorithms relying intrinsically on fusing visual odometry with other sensory inputs are developed for slip detection and navigation. However, these approaches are significantly expensive computationally and difficult to meet for future space exploration robots. Hence, today the central question in the field is how to develop a novel framework for in situ estimation of rover mobility with available space hardware and low-computational demanding terramechanics predictors. Ranging from pure simulations up to experimentally validated studies, this paper surveys dozens of existing methodologies for detection of vehicle motion performance (wheel forces and torques), surface hazards (slip-sinkage) and other parameters (soil strenght constants) using classical terramechanics maps, and compare them with novel approaches introduced by machine learning, allowing to establish future directions of research towards distributed exteroceptive and proprioceptive sensing for visionless exploration in dynamic environments. To avoid making it challenging to collect all relevant studies expeditiously, we propose a global classification of terramechanics according most common practices in the field, allowing to form an structured framework that condense most works in the domain within three estimator categories (direct/forward or inverse terramechanics, and slip estimators). Likewise, from the experiences collected in previous MER (Mars Exploration Rover) missions, five overlooked problems are documented that will need to be addressed in next generation of planetary vehicles, along three research questions and few hypothesis that will pave the road towards future applications of machine learning-based terramechanics.

Deep learning (DL) presents new opportunities for enabling spacecraft autonomy, onboard analysis, and intelligent applications for space missions. However, DL applications are computationally intensive and often infeasible to deploy on radiation-hardened (rad-hard) processors, which traditionally harness a fraction of the computational capability of their commercial-off-the-shelf counterparts. Commercial FPGAs and system-on-chips present numerous architectural advantages and provide the computation capabilities to enable onboard DL applications; however, these devices are highly susceptible to radiation-induced single-event effects (SEEs) that can degrade the dependability of DL applications. In this article, we propose Reconfigurable ConvNet (RECON), a reconfigurable acceleration framework for dependable, high-performance semantic segmentation for space applications. In RECON, we propose both selective and adaptive approaches to enable efficient SEE mitigation. In our selective approach, control-flow parts are selectively protected by triple-modular redundancy to minimize SEE-induced hangs, and in our adaptive approach, partial reconfiguration is used to adapt the mitigation of dataflow parts in response to a dynamic radiation environment. Combined, both approaches enable RECON to maximize system performability subject to mission availability constraints. We perform fault injection and neutron irradiation to observe the susceptibility of RECON and use dependability modeling to evaluate RECON in various orbital case studies to demonstrate a 1.5–3.0× performability improvement in both performance and energy efficiency compared to static approaches.

The link performance of free space optical communications (FSOC) and deep space optical communications (DSOC) are investigated by considering two scenarios in space communications, for example, for the downlink and uplink between the earth ground stations and the near earth geostationary (GEO) satellites, and between the earth and spacecraft with large distance of 1 astronomical unit (AU) to the earth. Generally a distance larger than 0.01 AU or approximately 1,500,000 km from Earth is considered as deep space. In these theoretical investigations, different realistic system parameters for the optical lasers, transmitters, receivers, avalanche photodiodes (APDs), optical telescopes, atmospheric disturbances like scintillation and absorption are considered. The simulation results are compared with existing project data and valuable ESA experimental results to verify and improve the simulation models. The comparison in this paper shows that the simulation models for the link budget and the scintillation estimation are feasible for the investigations of FSOC and DSOC, and can be used to investigate improved design and implementation of DSOC projects for planned long-term and medium-term space missions.

Analytical techniques commonly implemented for in situ organic analysis on space missions lack the sensitivity or specificity necessary to definitively characterize key markers of current or past life, such as amino acids. To this end, our group has developed an analytical method for amino acid analysis at low parts-per-billion levels, utilizing capillary electrophoresis coupled to laser-induced fluorescence detection. Europa has been identified as a particularly appealing target for life detection, but its intense radiation environment presents additional challenges for instrument development and qualification. Here, we present work toward the development of a flight qualifiable laser-induced fluorescence detection system that could be implemented on potential future missions to the Jovian system which could experience total ionizing dose exposures of up to 300 krad. Our results show that a gallium nitride based laser diode and micro-photomultiplier based system can meet our system performance requirements under radiation conditions expected for a potential Europa Lander mission.

The importance of interdisciplinary approaches through collaborative mindset, cross-field knowledge, and co-creative team actions is integral for continuing space exploration success as evidenced by past and ongoing terrestrial space habitat analog missions and extraordinary International Space Station (ISS) achievements. This paper presents the third annual iterative outcomes of an innovative university-based space program using Project Based Learning (PBL) methodology in creating design ideas for astronaut health support and wellbeing during a long duration mission (LDM) for a future inhabited lunar moon base or Mars Mission astronaut transit. University faculties including Built Environment, Industrial Design, Engineering, Science, and Health, at Western Sydney University Australia and supported by University of Houston USA are brought together to develop a new understanding of discipline capabilities with the prospect to co-creatively provide new opportunities and inspiration for teamwork across fields. This is of key interest to employers of new graduates in space or innovation-based industries where human factors and designing for high quality human-centered outcomes supports career resilience through currency, agility, and focus. The altruistic nature of interactions that make the ISS a success on multiple levels across cultural, scientific and humanitarian foundations provide the template for cross-disciplinary inspiration, that leverage synergies, and shared goals unattainable by single fields alone. It is not common for disciplines to work so closely together though industry has an expectation for this knowledge. Previously teams of three (2018); five (2019), and now ten undergraduates in 2020 represent team formation. Student numbers across the design for space theme have grown annually from fifteen, to twenty-five, to forty students in 2020. Now opportunities to respond to the complexities of the project in more detail are presented in addressing the overarching research domains in spatial design, human factors and design for health for LDMs. Team supervisory academic staff grew from 1-to-3 and provided further team guidance and discipline specialisations to inform three iterative project phases across the twelve activity weeks for four teams focusing on human spaceflight, exercise, related design performance and materials, and selected UNSDGs principles. The paper outlines the methodological approach, assessment methods, acculturation to working in teams and immersion in space knowledge for newcomers, and a review of forty collaborative outcomes all conducted by migrating Online during the COVID19 pandemic of 2020 by necessity. Periodic project collaborations with sports and health science, engineering, health informatics, space architects, a former astronaut, a representative from NASA Johnson Space Center (JSC) Flight Control, and industrial design academics (project host discipline and non-traditional space area) provided an environment for discussion, development, and co-creative processes that have led to new discoveries and stimuli for new collaboration, international understanding and advancing humankind in space and on earth.

The relevance of the task of improving the system of marine space reconnaissance and target guidance (ICRC), which involves conducting reconnaissance, processing target designation data and issuing them for the use of naval missile weapons (RV), is closely related to the effectiveness of the combat use (BP) of high-precision weapons (WCO) of sea-based (MB) and BRAV. The development of the system and the creation of new ICRC systems for ships of the Russian Navy are aimed primarily at ensuring the combat use of missile weapons (RO).

Nowadays, there is an increasing demand to design space systems with a higher level of onboard autonomy. One way to achieve this is to equip the satellite flight software with an autonomous decision system, such as model-based planning techniques. This article addresses an extended Hierarchical Task Network (HTN) description language for satellite onboard mission planning and acting. Our proposal seeks a lightweight and practical approach to model the space system and at the same time meets the current demands (scalability, intelligibility, and performance) for an autonomous satellite. To promote a clear understanding of the proposed language, we provide a grammar for the hierarchical domain and onboard problem representation. A realistic case study focused on a Brazilian remote-sensing satellite illustrates the effectiveness and practicability of our language. An onboard HTN planning approach is also implemented to verify in practice the usability of the model. We carry out experimental scenarios on a typical setup of satellite onboard computer using a space-qualified processor. The results obtained show that our proposal could overcome the main setbacks of the temporal planning model, which is the prevailing approach in the space domain until today.

For visual tracking methods based on reinforcement learning, action space determines the ability of exploration, which is crucial to model robustness. However, most trackers adopted simple strategies with action space, which will suffer local optima problem. To address this issue, a novel reinforcement learning based tracker called AEVRNet is proposed with non-convex optimization and effective action space exploration. Firstly, inspired by combinatorial upper confidence bound, we design an adaptive exploration strategy leveraging temporal and spatial knowledge to enhance effective action exploration and jump out of local optima. Secondly, we define the tracking problem as a non-convex problem and incorporate non-convex optimization in stochastic variance reduced gradient as backward propagation of our model, which can converge faster with lower loss. Thirdly, different from existing reinforcement learning based trackers using classification method to train model, we define a regression based action-reward loss function, which is more sensitive to aspects of the target states, e.g., the width and height of the target to further improve robustness. Extensive experiments on six benchmark datasets demonstrate that our proposed AEVRNet achieves favorable performance against the state-of-the-art reinforcement learning based methods.

Space systems require technologies intended for power generation and management most of the time. Within the Electric Power Subsystem, one or a group of several batteries conform the secondary power source of a space mission. In this work, the initial design of a Li-ion battery for small spacecraft, based on Commercial Off-The-Shelf (COTS) cells, is shown, the evolution of this design being thoroughly described from the first configuration. This battery has been sized to satisfy the power requirements of the UNION/Lian-He mission, the third Low Earth Orbit (LEO) microsatellite completely designed within an academic environment by the staff of Instituto Universitario de Microgravedad “Ignacio Da Riva” (IDR/UPM). Structural analyses of different battery configurations were carried out via Finite Element Method (FEM) modeling, in order to assure the viability of the design. The final configuration of the battery was reached based on these studies, which are described in the present work.

In this paper, an interactive tool for simulation of satellites dynamics and autonomous spacecraft guidance is presented. Different geopotential models for orbit propagation of Earth-orbiting satellites are provided, which consider Earth's gravitational field with various accuracies. The presented software is a 3D visualization platform for space orbit simulation with analytical capabilities through various modules. Taking advantage of a graphical user interface, it can evaluate, analyze and illustrate the motion of satellite based on different orbit propagation schemes. Several cases of satellites and autonomous spacecraft in the space rendezvous mission are simulated regarding different propagation models to demonstrate the performance of the application in space mission analysis, ground track visualization and trajectory optimization. Results are validated by comparing with other state-of-the-art tools, such as AGI System Toolkit (STK)., La Caixa Foundation SEV-2017-0718 TIN2016-78365R PID2019-1064536A-I00 Basque Government consolidated groups 2019-2021 IT1244-19

Since the conception of radio astronomy [1], researchers have been striving to develop a "zero-noise" broadband receiver. Although this goal has remained elusive, the pursuit of it has led to numerous low-noise circuit innovations [2], [3]. Perhaps the most notable of these innovations are cryogenic low-noise amplifiers (cryo-LNAs) [3]-[6] as this technology has been able to achieve the lowest noise levels to date. While references to cryogenic amplifiers in the literature date back to the early 1950s [7], they are still a subject of much interest among researchers. Cryo-LNAs were initially conceived of to address challenges in the fields of space exploration [8], [9] and radio astronomy [10]. More recently, researchers in other fields have become interested in "zero-noise" receivers, making this a topic of widespread interest among RF and microwave engineers.

Mastering semiconductor technology is essential to insert any country into the trends of the future, such as smart cities, internet of things, space exploration, etc. In this paper we present the growing annual revenue of the semiconductor industry in the last 20 years and comment on the importance of mastering semiconductor production technology and its implications for the development of a nation.

The utilization of space for human activities has increased steadily over the past several decades. In parallel, space debris has also grown at an alarming rate, posing risks to space missions and ...

The Apollo moon missions of the 1960s pioneered the classic phased approach to space mission management. While successful at the time, this rigid and inflexible management philosophy has become synonymous with cost and schedule overruns of most high-profile space missions. The software industry has recently adopted modern, more flexible project management techniques based on “lean-agile” methods that enable team collaboration and communication through distributed task and schedule management, online document sharing and rolling-wave planning. However, due to the inherent schedule complexities of hardware development and the firm constraints of design review and launch timelines, flexible project management frameworks have not been widely adopted for space mission management. This paper presents a modified version of the traditional agile management philosophy, adapted to the unique needs of the space industry. A recent satellite development project was managed using the new modified-agile approach, while collecting project hours and task durations. Comparisons were made between this new style of space project management and a recently completed satellite development project using traditional space project management techniques. Results show that the new management approach reduced strain on the project team, improved overall productivity, and maintained a more level task loading when compared to the traditional management approach. This paper also illustrates how the new management approach can enable project resilience to change by analyzing its response to the labor disruptions caused by the COVID-19 pandemic.

Safety of satellites as well as spacecrafts during space missions is a primary objective to preserve the physical and virtual assets onboard. Whipple shields belong to the class of protective equipment provided on the surface of the spacecrafts and satellites, to sustain impacts from the ultra-high speed debris, which can otherwise cause considerable damage to the corresponding structures. Recent works on whipple shields are focussed on determining the response of different geometrical arrangements and material properties under hyper-velocity impact at projectile speeds of 3-18 km/s. Advances in the whipple shield design include integrated and mechanised models employing high performance materials like fiber-metal laminates ensuring better operational capability. The forward bumper of the whipple shield is the first line of defence as it regulates the state of projectile after the primary impact. Use of aluminium alloys for front bumpers is popular, owing to their lightweight and strength characteristics. The advances for the front bumper have seen usage of ceramic, metallic foams, and super composite mixtures, which resulted in enhanced performance, durability and safety of the whipple shields. This work is a comprehensive coverage of the latest materials used for whipple shields, their performance characterization—both experimental and theoretical, and applications.

The paper deals with the problems of astronomical heritage. Criteria required for astronomical and archeoastronomical objects to be included in the list of Heritage and respective constraints have been developed in the framework of the UNESCO Thematic Initiative launched in 2004. Various objects which could be proposed from Russia and satisfying these criteria are thoroughly discussed.

Onsite production of oxygen and hydrogen is an essential contribution to any manned mission to the Moon or to Mars. In both environments there are elements consisting of bound oxygen, such as water ice-bearing consolidated regolith on the moon and carbon dioxide on Mars. These resources can be used to generate oxygen gas through electrolysis, together with energy carriers, namely hydrogen and CO, as by-products. Solid Oxide Electrolysis (SOE) technology possesses the highest potential for this application, due to the high operation temperature ranging from, 650°C to 900°C. Therefore, it can split each or both H2O and CO2, into H2, CO and O2 without compromising the integrity of the electrodes by poisoning, while the process can be further integrated with other thermal processes, such as the reduction of mineral oxide to provide overall very high system efficiencies. The solid oxide cell (SOC) technology is also fully reversible (i.e., the cell works both as electrolyser and as fuel cell) and can be used for unitised reversible fuel cell systems (URFCS) for energy storage and generation. This paper describes the developments under a European Space Agency (ESA) activity for the development of a high-pressure steam electrolyser system for exploration surface missions. The base case scenario considered is a hydrogen and oxygen production unit for lunar missions, where water for the electrolyser is generated from ice-bearing consolidated regolith. The development of the electrolyte supported cells was based in an all-ceramic approach. Specifically, electrolyte (8YSZ, 3YSZ, 6Sc1CeSZ and 10Sc1CeSZ) supported cells were fabricated comprising substituted lanthanum chromite La0.75Sr0.25Cr0.9Fe0.1O3 (LSCrF), as fuel electrode, and (La0.80Sr0.20)0.95MnO3-x (LSM) or (La0.60Sr0.40)0.95Co0.20Fe0.80O3-x (LSCoF), as oxygen electrodes. The electrochemical characterization and performance assessment in button cells (with an electrode footprint of ~0.8 cm2) was conducted for (i) steam electrolysis and (ii) reversible cell operation (fuel cell and electrolysis modes). All cells exhibited stable performance within the whole range of potentials, thus revealing the fact that Solid Oxide technology is in principle reversible and versatile in functionalities. Regarding steam electrolysis, the effect of hydrogen co-fed was investigated. The lack of reducing agent (H2) in the fuel side results in a non-trivial evolution of the current-potential curve, as the Nernst potential is not fixed and the production of a substantial concentration of hydrogen is required for the IV curve to follow the typical linear relation. However, within the linear IV region the performance of the cells is similar in presence or in absence of hydrogen, exhibiting ~2 A/cm2 at 1.5 V. Following these key developments, a high-pressure short stack is designed and constructed, comprising five (5) cells with an active area of 42 cm2. The stack is enclosed in a hot box consisting of the mechanical and thermal environment for the stack. To operate at pressure up to 10 bars, the hot box is placed inside a stainless-steel chamber made of standard piping elements. The hot box is complemented with all necessary balance of plant (steam generator, water system, gas storage) to realise a complete a steam electrolysis system which will be validated in operation against a load profile representing energy storage in Lunar environment for 3 lunar days (~2,126 h). Figure 1

The need for space missions is ever growing with the complexity of problems encountered, requiring experiments at different physical conditions. The cost and other factors experienced in each of the space missions are soaring, irrespective of the entanglements of these missions. Micro and Nano satellites have paved way in this regard, as they are cheap, feasible and provide a platform for new technologies to be tested and validated in space which can then be extended to larger satellites for enhanced applications. Orbital harsh conditions make thermal system design very big challenge to satisfy the different operation conditions required per satellite components. Thermal Control system (TCS) analysis of Hyper-Spectral Remote Sensing Micro-Satellite is crucial in its conceptual design phase. The thermal system design concept of the Micro-Satellite may be passive or active system working on a non-hermetic platform. Satellite thermal system shall provide suitable temperature envelop allow components to work in full performance. It consumes daily average power about 45 W. Battery is the most critical component because of its capacity sensitivity to temperature changes.

Space resource utilization (SRU) can be a catalyst for a growing space economy. Significant reductions in cost, launch mass and risk for human and robotic activities beyond Earth can be achieved. Commercial entities will have the opportunity to generate revenue through economic development, allowing for a decreased dependency on governmental agencies for the exploration of space. A wide variety of materials can be found on planetary and small solar system bodies, which are potentially of great use to customers in space. This paper conducts a comparison of the economic and commercial potential of SRU on the surface of the Moon, Mars, a representative near-Earth asteroid and a representative main-belt asteroid. In particular, mining of water will be considered which will be electrolysed into hydrogen and oxygen using solar power. Coupled economic and trajectory optimization then results in the minimum specific cost to deliver propellant (LOX/LH 2 ) from these bodies to a number of customer locations. Customers on the surface of or in orbit around the Earth, Moon, and Mars are investigated, along with Psyche, a large metallic main-belt asteroid. Using a cost model that considers technology maturation to allow current aviation-like costs to be used for development and manufacturing, missions are optimized. Results show that for customers beyond low-Earth orbit, SRU should be used instead of launching water-derived resource directly from the Earth. In particular, near-Earth asteroids are shown to be in an attractive location for mining, processing and delivering a large quantity of LOX/LH 2 at a low specific cost, for customers in the vicinity of the Earth and the Moon, including nearby collinear Lagrange points. Exceptions are customers on the surface of the Earth and the Moon, who, together with customers on the surface of Mars, are better off mining and processing on that same surface. A sensitivity analysis shows that, for all investigated customers except Psyche, there are near-Earth asteroids available which can be used to deliver water-derived resources for a lower specific cost than the most ideal main-belt asteroid. Only once these near-Earth asteroids have been depleted, mining main-belt asteroids and transporting resources back to a customer in the vicinity of the Earth is worth considering.

By shifting how program patches are evaluated-away from quality and toward novelty-the novelty search technique increases a bug-repair system?s ability to explore the solution space, produce more viable patches, and repair more bugs.

Recent advances in silicon photomultiplier (SiPM) technology and new scintillator materials allow for the creation of compact high-performance gamma-ray detectors which can be deployed on small low-cost satellites. A small number of such satellites can provide full sky coverage and complement, or in some cases replace the existing gamma-ray missions in detection of transient gamma-ray events. The aim of this study is to test gamma-ray detection using a novel commercially available CeBr3 scintillator combined with SiPM readout in a near-space environment and inform further technology development for a future space mission. A prototype gamma-ray detector was built using a CeBr3 scintillator and an array of 16 J-Series SiPMs by ON Semiconductor. SiPM readout was performed using SIPHRA, a radiation-tolerant low-power integrated circuit developed by IDEAS. The detector was flown as a piggyback payload on the Advanced Scintillator Compton Telescope balloon flight from Columbia Scientific Balloon Facility. The payload included the detector, a Raspberry Pi on-board computer, a custom power supply board, temperature and pressure sensors, a Global Navigation Satellite System receiver and a satellite modem. The balloon delivered the detector to 37 km altitude where its detection capabilities and readout were tested in the radiation-intense near-space environment. The detector demonstrated continuous operation during the 8-hour flight and after the landing. It performed spectral measurements in an energy range of 100 keV to 8 MeV and observed the 511 keV gamma-ray line arising from positron annihilation in the atmosphere with full width half maximum of 6.8%. During ascent and descent, the detector count rate peaked at an altitude of 16 km corresponding to the point of maximum radiation intensity in the atmosphere. Despite several engineering issues discovered after the flight test, the results of this study confirm the feasibility of using CeBr3 scintillator, SiPMs, and SIPHRA in future space missions.

Purpose of Review The purpose of this review is to highlight space autonomy advances across mission phases, capture the anticipated need for autonomy and associated rationale, assess state of the practice, and share thoughts for future advancements that could lead to a new frontier in space exploration. Recent Findings Over the past two decades, several autonomous functions and system-level capabilities have been demonstrated and used in spacecraft operations. In spite of that, spacecraft today remain largely reliant on ground in the loop to assess situations and plan next actions, using pre-scripted command sequences. Advances have been made across mission phases including spacecraft navigation; proximity operations; entry, descent, and landing; surface mobility and manipulation; and data handling. But past successful practices may not be sustainable for future exploration. The ability of ground operators to predict the outcome of their plans seriously diminishes when platforms physically interact with planetary bodies, as has been experienced in two decades of Mars surface operations. This results from uncertainties that arise due to limited knowledge, complex physical interaction with the environment, and limitations of associated models. Summary Robotics and autonomy are synergistic, wherein robotics provides flexibility, autonomy exercises it to more effectively and robustly explore unknown worlds. Such capabilities can be substantially advanced by leveraging the rapid growth in SmallSats, the relative accessibility of near-Earth objects, and the recent increase in launch opportunities.

Advances in model-based system engineering have greatly increased the predictive power of models and the analyses that can be run on them. At the same time, designs have become more modular and component-based. It can be difficult to manually explore all possible system designs due to the sheer number of possible architectures and configurations; trade space exploration has arisen as a solution to this challenge. In this work, we present a new software tool: the Guided Architecture Trade Space Explorer (GATSE), which connects an existing model-based engineering language (AADL) and modeling environment (OSATE) to an existing trade space exploration tool (ATSV). GATSE, AADL, and OSATE are all designed to be easily extended by users, which enables relatively straightforward domain-customizations. ATSV, combined with these customizations, lets system designers “shop” for candidate architectures and interactively explore the architectural trade space according to any quantifiable quality attribute or system characteristic. We evaluate GATSE according to an established framework for variable system architectures, and demonstrate its use on an avionics subsystem.

The interstellar medium (ISM) represents the next frontier in space exploration, with many new discoveries to be made. The challenge, being so far away from Earth, the ISM requires many decades to reach. To advance our knowledge of what exists beyond our solar system, new approaches for rapid access are required. One such approach is solar thermal propulsion (STP). The approach uses several Venus and Earth gravity assists to fly to Jupiter and use its gravity well to dive towards the Sun. Approaching within three solar radii a perihelion burn would be performed, maximising the spacecraft’s ΔV to achieve high solar system escape velocities. A unique aspect of the STP mission concept is that the Sun is used not only as a gravity well for an Oberth manoeuvre, but also to heat the fuel to ultra-high temperatures (> 3000 K), enabling a monopropellant burn with high specific impulse (Isp). Prior preliminary studies indicated escape velocities of over 20 astronomical unit (AU)/year would be possible. An in-depth modelling exercise was undertaken to determine how such a system would perform. The model in this paper showed the current STP design is capable of providing just under 9 ± 1 AU/year, but there are many technology developments that could increase escape velocity. The technologies vary from items that could be implemented in the near term, like turbo-pumps driven by the hydrogen, to items requiring more extensive development programs like thin coatings which do not erode in superheated hydrogen. After reviewing the STP approach, and comparing it to a solid rocket motor (SRM), it was found that with currently available technology, SRM outperforms STP with an escape velocity of approximately 10–12 AU/year. However, future advances in heat exchanger lining materials, turbo pumps, and advanced heat exchanger geometries may enable solar thermal propulsion to provide higher escape velocities, providing one of the fastest ways to exit the solar system. Ultimately, if all technology paths could be implemented with minimal side effects, the performance in a best-case scenario could reach up to 16 AU/year.

Nowadays, design, development, and motion planning of a mobile robot explore research areas in the field of robotics. Mobile robots have an extensive area of applications in various fields like space exploration, military application, industrial use, and many more. Hence, the design and development of a mobile robot is a crucial part of the above application. Among all the mobile robot, the quadrupedal robot is a legged robot, which is superior to wheeled and tracked robot due to its potential to explore in all the terrain like the human and animal. In this paper, the survey concentrates on various design and development approaches for the quadrupedal robot, and environment perception techniques are discussed. Besides, Spot is one of the most advanced and intelligent quadrupedal robots. The performance of each quadruped robot and the future outline are provided in details.