Search Results (30)

All-solid-state lithium-ion batteries (ASSBs) have a wide operating temperature range (−40 °C to +120 °C) and are expected to be applied to lunar exploration, which has become increasingly active in recent years. Since a ground development test confirmed that ASSBs are tolerant of the space environment, in this study, a space demonstration test is conducted on the International Space Station (ISS). The battery was exposed in the ISS Exposed Section for 434 days. A total of 562 charge–discharge cycle tests were conducted, in addition to basic charge–discharge characterization, with no significant degradation observed in the charge–discharge characteristics or battery appearance. These results confirm that the battery operates reliably even in a complex space environment. This test confirmed that the lifetime characteristics of ASSBs can be estimated via ground-based charge–discharge characteristics, encouraging their potential application in space exploration. Full article

Stimulating skeletal muscle satellite cells (SMSCs) with amino acids improves their proliferation and differentiation, enhancing skeletal muscle mass, thereby increasing lean meat rate. This study explored lysine (Lys)’s effects on SMSCs and their protein profiles in Sunit sheep. SMSCs were successfully isolated, assessing their survival and proliferation after Lys stimulation at varying concentrations using the CCK-8 assay. Western blotting revealed Lys-induced changes in myogenic differentiation protein expression, while immunocytochemistry detected α-Actinin and Myostatin within the SMSCs. TMT proteomics identified differentially expressed proteins, which underwent functional and interaction analyses, with RT-qPCR validating the corresponding gene expression. This study revealed that 4 mmol/L of Lys significantly boosted SMSC proliferation. A 24 h stimulation with this concentration reduced Myostatin expression, and increased MYOD1 and α-Actinin levels in the SMSCs. A proteomic analysis identified 577 differentially expressed proteins, primarily associated with lipoblast differentiation and muscle development, as highlighted by the GO enrichment analysis. A pathway analysis further demonstrated these proteins’ involvement in the autophagy–lysosome and NOD-like receptor signaling pathways. Lys enhances SMSC proliferation, differentiation, and adipogenesis in Sunit sheep, exhibiting antioxidant properties and supporting muscle stability and amino acid metabolism. It may also have anti-inflammatory, anti-pyroptotic, and proteolysis-inhibitory effects, offering insights into muscle growth mechanisms through amino acid supplementation in ruminants. Full article

Considerable technological progress has been made in ship handling and mooring in recent years, especially progress generated by the needs imposed by the introduction of ever larger ships. These advancements exploit the economic scale and environmental efficiency of larger vessels, but also present unique challenges, particularly in narrow waterways and harbour approaches. Precise navigation in these environments requires highly accurate hydrographic measurements, high-quality electronic charts, and advanced navigation systems, such as modern electronic chart display and information systems (ECDIS). Safe and efficient port operations also depend on the optimised allocation of port resources and comprehensive queuing strategies. Modern ships are increasingly susceptible to interference with Global Navigation Satellite Systems (GNSS) and Automatic Identification Systems (AIS), necessitating the development of resilient technologies and procedures to ensure navigational safety. In addition, climate change is exacerbating the challenges of ship handling in ports, as larger vessels are particularly vulnerable to sudden gusts of wind and have difficulty maintaining their position in the quay in strong crosswinds. Training and simulation are crucial to overcoming these challenges. Ship-handling simulators are invaluable for training purposes, but development is still needed to accurately simulate tilt and lean effects, especially when ships are sailing in narrow channels with following currents and changing winds. Improving the accuracy of these simulators will improve the preparation of seafarers for real-life conditions and ultimately contribute to safer and more efficient ship operations. Full article

Moore’s law states that the performance of computers doubles about every two years. This has dramatic consequences for any modern high development and for satellites. The long development cycles cause these expensive assets to be obsolete before the start of their operations. The advancement also presents challenges to their design, particularly from a thermal perspective, as more heat is dissipated and circuits are more fragile. These challenges mandate that faster spacecraft development methods are found and thermal management technologies are developed. We elaborate on existing development methodologies and present our own lean method. We explore the development of a thermal anomaly-detection payload, extending from conception to in-orbit commissioning, to stimulate discussions on space hardware development approaches. The payload consists of four miniaturized infrared cameras, heating sources in view of the cameras simulating an anomaly, an on-board processor, and peripherals for electrical and communication interfaces. The paper outlines our methodology and its application, showcasing the success of our efforts with the first-light activation of our cameras in orbit. We show our lean method, featuring reference technical and management models, from which we derive further development tools; such details are normally not available in the scientific-engineering literature. Additionally, we address the shortcomings identified during our development, such as the failure of an on-board component and propose improvements for future developments. Full article

This research aims to contribute to the development of the Eco-LeanSat concept by focusing on a sustainable approach to satellite manufacturing and the repurposing of remaining satellite capabilities after failure. Despite satellites no longer being suitable for their original purposes, these remaining capabilities can find new applications. The study begins by identifying relevant innovative eco-design applications. Subsequently, it examines sustainability within the satellite lifecycle supply chain, categorizing it into four methods: (1) active debris removal, (2) transport logistics, (3) mission extension, and (4) repair and construction. Aligned with emerging trends in space activities, the study also considers future developments to maximize satellites’ potential to provide new services. Additionally, the research includes a description of a potential lean manufacturing process that encompasses logistic chains to support the development of a more sustainable space economy. Finally, the study concludes with a technological survey tracing the evolution of the development of the SmallSat and CubeSat platforms that identifies relevant innovative designs for a sustainable space environment. Full article

The atmospheric total water vapor content (TWVC) affects climate change, weather patterns, and radio signal propagation. Recent techniques such as global navigation satellite systems (GNSS) are used to measure TWVC but with either compromised accuracy, temporal resolution, or spatial coverage. This study demonstrates the feasibility of predicting, mapping, and measuring TWVC using spread spectrum (SS) radio signals and software-defined radio (SDR) technology on low Earth-orbiting (LEO) satellites. An intersatellite link (ISL) communication network from a constellation of small satellites is proposed to achieve three-dimensional (3D) mapping of TWVC. However, the calculation of TWVC from satellites in LEO contains contribution from the ionospheric total electron content (TEC). The TWVC and TEC contribution are determined based on the signal propagation time delay and the satellites’ positions in orbit. Since TEC is frequency dependent unlike TWVC, frequency reconfiguration algorithms have been implemented to distinguish TWVC. The novel aspects of this research are the implementation of time stamps to deduce time delay, the unique derivation of TWVC from a constellation setup, the use of algorithms to remotely tune frequencies in real time, and ISL demonstration using SDRs. This mission could contribute to atmospheric science, and the measurements could be incorporated into the global atmospheric databases for climate and weather prediction models. Full article

Magnetometers are important sensors with applications in the attitude determination and control systems of satellites. CubeSats have certain limitations related to power, mass, and volume. Due to this, CubeSat magnetometers are not separated from other electrical circuits inside the satellite. Thus, it is important to calibrate the magnetometer, simulating operating conditions while the satellite is running before the launch. However, due to the limited facilities, not every CubeSat is able to calibrate its magnetometers properly on the ground. This study focuses on the calibration of on-orbit magnetometer data observed by BIRDS-3 CubeSats with a genetic algorithm. High oscillations in the total magnetic field were found in the on-orbit magnetic field data measured by magnetometers inside BIRDS-3 CubeSats. Nine unknowns, scaling factors, non-orthogonal angles, and offsets are identified with the genetic algorithm. This paper discusses the factors that affect the high oscillations in the measured total magnetic field data. For the calibration, we used magnetic field data similar to those of a model magnetic field, as the deviation is smaller. This paper presents the accuracy of determining unknowns using the genetic algorithm, as well as the interchangeability of the answers with additional orbit data from the same satellite. This method can be used in the future to calibrate magnetometers inside CubeSats before or after launch. Full article

This research proposes a low-inclined orbit concept and design for the Internet-of-Things (IoT) using lean satellite standards in near-equatorial regions. The study aims to evaluate the coverage of various inclination angles at various latitudes and inclination angles in order to determine the most suitable satellite design for providing IoT coverage in these regions. The main methods applied in the study included analyzing the coverage performance of different inclination angles, the link budget analysis using simulations and the definition of the mission criteria. The results of the study show that the overall coverage performance decreases with an increase in the inclination angle. Satellites with lower inclination angles have ground tracks that are more closely aligned with the equator, while satellites with higher inclination angles have ground tracks that are inclined further toward the poles. In addition, the results show that the fraction of orbits with coverage (expressed as a percentage) declines with increasing latitude. Based on these findings, a low-inclined orbit of 24° provides the best coverage for IoT in near-equatorial regions within ±20 and 26° latitude, with a peak coverage of 27% at 24° latitude and a minimum coverage of 10% in the region spanning from 0° to ±27° latitude. This design offers more coverage time and a shorter revisit time to the selected regions for communication missions. Full article

In this paper, we consider the optimization of temperature conditions and the thermo-stressed state of a concrete gravity dam made of extra lean roller-compacted concrete constructed in climate conditions corresponding to the Pskem HPP in the Republic of Uzbekistan. We show the need to take into account the effect of solar radiation on the heating of the concrete mass during the layer-by-layer construction of a gravity dam. A methodology was used to estimate solar radiation, considering cloud cover and the use of field and satellite observations. The seasonality of the concrete work and the terrain surrounding the construction site were also examined. We assessed the degree of influence of the factors acting on the formation of the temperature regime and the thermo-stressed state using the factor experiment technique. Regression equations, which allowed us to estimate the values of temperature and thermal stress arising in the structure during the construction period, were obtained. The created numerical model has been used for the estimation and optimization of the thermo-stressed state of the Pskem HPP dam option made of low-cement roller-compacted concrete. On the basis of calculations of the stress–strain state in elastic and elastic-plastic formulations, the possible cracking of concrete was evaluated. The competitiveness of the considered concrete option of the dam with the ground one is shown. Full article

Satellite-based flood monitoring for providing visual information on the targeted areas is crucial in responding to and recovering from river floods. However, such monitoring for practical purposes has been constrained mainly by obtaining and analyzing satellite data, and linking and optimizing the required processes. For these purposes, we present a deep learning-based flood area extraction model for a fully automated flood monitoring system, which is designed to continuously operate on a cloud-based computing platform for regularly extracting flooded area from Sentinel-1 data, and providing visual information on flood situations with better image segmentation accuracy. To develop the new flood area extraction model using deep learning, initial model tests were performed more than 500 times to determine optimal hyperparameters, water ratio, and best band combination. The results of this research showed that at ‘waterbody ratio 30%’, which yielded higher segmentation accuracies and lower loss, precision, overall accuracy, IOU, recall, and F1 score of ‘VV, aspect, topographic wetness index, and buffer input bands’ were 0.976, 0.956, 0.894, 0.964, and 0.970, respectively, and averaged inference time was 744.3941 s, which demonstrate improved image segmentation accuracy and reduced processing time. The operation and robustness of the fully automated flood monitoring system were demonstrated by automatically segmenting 12 Sentinel-1 images for the two major flood events in Republic of Korea during 2020 and 2022 in accordance with the hyperparameters, waterbody ratio, and band combinations determined through the intensive tests. Visual inspection of the outputs showed that misclassification of constructed facilities and mountain shadows were extremely reduced. It is anticipated that the fully automated flood monitoring system and the deep leaning-based waterbody extraction model presented in this research could be a valuable reference and benchmark for other countries trying to build a cloud-based flood monitoring system for rapid flood monitoring using deep learning. Full article

The key to achieving low-carbon manufacturing is to effectively reduce the carbon emissions of production systems and improve carbon benefits. The use of lean and green tools aids in measuring the added value of products, and increases the efficiency and sustainability of production systems. To address this problem and verify that the synergetic relationship between lean and green innovation increases the efficiency and sustainability in production systems, a new low-carbon manufacturing evaluation indicator—carbon benefit—in lean manufacturing systems was discussed. A low-carbon decision-making model of multiple processes aiming at carbon benefit maximization, as well as the dynamic characteristics of carbon benefit and sustainable process improvements in a lean production system, was established. A case study of a certain satellite dish parts manufacturing line was introduced to analyze and verify the feasibility of the proposed model. After improvement, the processing time of unit parts was reduced from 63 s to 54 s. The workstations were optimized again according to the lean–green manufacturing concept, and the number was reduced by 37.5%. The process was recombined and reduced from 8 to 5 to achieve continuous-flow processing. This reduced the distance by 77 m, and at the same time, the number of operating personnel was reduced, and the after-improvement carbon efficiency increased from 12.98 s/kg CO₂e to 36.33 s/kg CO₂e in comparison with that before the improvement. The carbon benefit after improvement was 193.92% higher than that before the improvement. Full article

The concept of the nanosatellite comes into play in launching miniaturized versions of satellites or regarding payloads with minimizing cost and building time. The economic affordability of nanosatellites has been promoted with a view to launching various nanosatellite missions. The communication system is one of the most important aspects of a satellite. The antenna is a key element for establishing a communication link between the earth and the nanosatellite. The antenna and solar panel of the nanosatellite are two of the most vital components that profoundly impact antenna type and design. This paper proposes a non-deployable lower ultra-high frequency (UHF) antenna, strategically mounted on the satellite body, to address the constraints of deployment complexity and solar panel integration. The antenna was fabricated and performances measured with a 1U nanosatellite structure, which achieved resonance frequency at 401 MHz frequency bands with 0.672 dBi realized gain. The overall antenna size is 0.13λ × 0.13λ × 0.006λ. The major challenges addressed by the proposed antenna are to design a nanosatellite-compatible lower UHF antenna and to ensure solar irradiance into the solar panel to minimize input power scarcity. Full article

A flight-proven electrical bus system for the 1U CubeSat platform was designed in the BIRDS satellite program at the Kyushu Institute of Technology. The bus utilizes a backplane board as the mechanical and electrical interface between the subsystems and the payloads. The electrical routes on the backplane are configured by software using a complex programmable logic device (CPLD). It allows for reusability in multiple CubeSat projects while lowering costs and development time; as a result, resources can be directed toward developing the mission payloads. Lastly, it provides more time for integration and system-level verification, which are critical for a reliable and successful mission. The current trend of CubeSat launches is focused on 3U and 6U platforms due to their capability to accommodate multiple and complex payloads. Hence, a demonstration of the electrical bus system to adapt to larger platforms is necessary. This study demonstrates the configurable electrical interface board’s scalability in two cases: the capability to accommodate (1) multiple missions and (2) complex payload requirements. In the first case, a 3U-size configurable backplane prototype was designed to handle 13 mission payloads. Four CPLDs were used to manage the limited number of digital interfaces between the existing bus system and the mission payloads. The measured transmission delay was up to 20 ns, which is acceptable for simple serial communications such as UART and SPI. Furthermore, the measured energy consumption of the backplane per ISS orbit was only 28 mWh. Lastly, the designed backplane was proven to be highly reliable as no bit errors were detected throughout the functionality tests. In the second case, a configurable backplane was implemented in a 6U CubeSat with complex payload requirements compared to the 1U CubeSat platform. The CubeSat was deployed in ISS orbit, and the initial on-orbit results indicated that the designed backplane supported missions without issues. Full article

CubeSat requirements in terms of size, weight, and power restrict the possibility of having redundant systems. Consequently, telemetry data are the primary way to verify the status of the satellites in operation. The monitoring and interpretation of telemetry parameters relies on the operator’s experience. Therefore, telemetry data analysis is less reliable, considering the data’s complexity. This paper presents a Machine Learning (ML) approach to detecting anomalies in solar panel systems. The main challenge inherited from CubeSat is its capability to perform onboard inference of the ML model. Nowadays, several simple yet powerful ML algorithms for performing anomaly detection are available. This study investigates five ML algorithm candidates, considering classification score, execution time, model size, and power consumption in a constrained computational environment. The pre-processing stage introduces the windowed averaging technique besides standardization and principal component analysis. Furthermore, the paper features the background, bus system, and initial operational data of BIRDS-4, a constellation made of three 1U CubeSats released from the International Space Station in March 2021, with a ML model proposal for future satellite missions. Full article

Many regions in developing countries do not have any access to communication networks even though the number of devices connected through the Internet of Things (IoT) is increasing significantly. A small satellite platform could provide global network coverage in low Earth orbit to these remote locations at a low cost. This paper describes the overall mission architecture and the implementation of remote IoT using a 1U volume in 6U CubeSat platform named KITSUNE. In KITSUNE, one of the missions is to leverage IoT for building a network of remote ground sensor terminals (GST) in 11 mostly developing countries. This paper evaluates the capacity and coverage of a satellite-based IoT network for providing remote data-collection services to these countries. The amount of data that could be collected from the GSTs and forwarded accurately to the users determines the actual capacity of the Store and Forward (S&F) mission. Therefore, there are several proposed parameters to estimate this capacity in this study. In addition, these parameters are retrieved from the simulations, ground test results, and on-orbit observations with the KITSUNE satellite. The proposed IoT system, which is composed of the GSTs and IoT subsystem onboard KITSUNE satellite, is determined to be capable of providing valuable information from remote locations. In addition, the collected data are achieved and analyzed to monitor sensory data specific to each country, and it could help to generate prediction profiles as well. Full article