https://www.jsstpub.com/ Journal of Space Science and Technology en daily 1 Sat, 01 Nov 2025 00:00:00 +0330 Sat, 01 Nov 2025 00:00:00 +0330 https://www.jsstpub.com/article_220588.html Controlling a spacecraft’s orbit and attitude is one of the most complicated problems in control engineering due to uncertainties and nonlinearities. Control design methods for dealing with such issues may involve many calculations. Matlab software automates many design methods in its control system toolbox. Many other advanced design methods must also be automated to achieve fast and accurate controller design for more complex control systems. Quantitative feedback theory (QFT), as a powerful method for addressing the complex issues, requires plenty of calculations that make it necessary for the method to be automated. A QFT design toolbox is developed by Tersoft company. However, this toolbox cannot treat some practical issues, such as actuator saturation in its design process. In the QFT framework, saturation can be dealt with by Horowitz architecture or noninterfering loop architecture, containing an inner loop around the saturation element in the control loop. Error overshoot is a common problem with the saturation in control loops. Non-overshoot plant input, non-overshoot plant output and fast-vanishing plant input error are three constraints assumed in literature, to avoid this problem. These constraints can be translated to the constraints on inner loop compensator. This paper presents a comprehensive algorithm for automating the process of obtaining above mentioned constraints, with detailed flowcharts to facilitate software development. To verify the proposed algorithm, the boundary on the saturation loop compensator, for a hydraulic actuator is determined using computer codes implemented in the Matlab environment. https://www.jsstpub.com/article_225098.html This article investigates the identification of periodic orbits and spacecraft attitude behavior in the Circular Restricted Three-Body Problem (CRTBP) using the Poincaré map as an innovative analytical tool. The CRTBP describes the motion of a spacecraft under the gravitational influence of two primary celestial bodies and presents challenges due to the absence of closed-form solutions for both orbital and attitude dynamics. To address this, the study employs the Poincaré map as an efficient numerical method to detect suitable initial conditions for periodic motion, thereby reducing mathematical complexity and improving computational performance. A notable innovation in this work is the integration of spacecraft attitude dynamics into the Poincaré-based analysis. Although the coupling is oneway, meaning attitude states do not influence the periodicity of orbital motion, they do affect the structure of the resulting Poincaré maps. The shape and position of islands on these maps vary with changes in the spacecraft’s inertia ratio, which demonstrates the method’s sensitivity to attitude behavior and its relevance to real-world applications. The proposed method is benchmarked against two classical techniques: the third-order approximation and Floquet theory-based approaches. Comparative analysis shows that the Poincaré map offers a superior balance of simplicity, computational efficiency, and accuracy. It achieves reliable identification of periodic orbits without requiring high-order models or intricate corrections. Overall, the study provides a novel and practical contribution to space mission design, offering a robust and accessible framework for analyzing trajectory and attitude dynamics in complex gravitational environments such as libration point missions. https://www.jsstpub.com/article_228269.html Formation of blood clot in the astronaut veins in space may have dangerous consequences. In the absence of gravity, body fluids shift from the legs to the upper body and the head. This shift affects the flow of blood through the vessels in the head. Removing of the blood clot in the vessels in space may help astronauts’ health. Although using the medicine to remove the blood clot in the vein, it can be applied just for very small size. When the blood clot is large, using the ultrasonic waves with making small bubbles may be a useful method to remove the blood clots in the veins. The goal of the present paper is to gain an optimal intensity of ultrasound to achieve required pressure field generated by the collapsing bubble in blood to deform blood clots. The collapse pressure within the bubble has been calculated using Rayleigh–Plesset (RP) equation. Moreover, a coupling simulation of the flow and clot structure is performed using the full Navier-Stokes equations, which governs the blood domain, and linearized discrete equations for the clot medium to calculate the desired bubble collapsing pressure necessary to deform the clots, which has immense importance in medical applications. Simulation results are presented to show the effectiveness of the proposed method. Using the captured results, one can find the optimum ultrasound frequency for clot fragment. It can be useful for an astronaut to use the ultrasonic waves to remove some clots in the vein, treat and get back the health. https://www.jsstpub.com/article_232115.html This research examines the free vibration and panel flutter of composite laminates with curvilinear fibers. It employs the isogeometric analysis (IGA) framework along with layerwise theory. The growing utilization of composite structures in the aerospace and mechanical industries has led to the increasing popularity of  variable-stiffness composite laminate (VSCL). These laminates with curvilinear fibers are designed to achieve customized mechanical properties and improve design efficiency. To achieve greater accuracy than equivalent single-layer theories (ESL) and improved computational efficiency compared to 3D elasticity models, a layerwise theory based on Ferreira's formulation was adopted. This approach uses the kinematic assumptions of first-order shear deformation theory (FSDT) to define the displacement field within each layer. Subsequently, the governing equations for free vibration and panel flutter are obtained from the Hamilton principle, utilizing first-order piston theory to model aerodynamic pressure. The geometric domain is discretized using the isogeometric analysis method, in which the cubic NURBS basis functions used for the exact geometric modeling are simultaneously employed as the approximation functions in the finite element formulation. Numerical results are obtained by solving the eigenvalue problem. A parametric study was performed to investigate the impact of several factors, including layup configuration, thickness ratios, fiber curvature, and boundary conditions of the VSCL plates. The findings demonstrate strong alignment with previous research, confirming the proposed formulation's accuracy and effectiveness. https://www.jsstpub.com/article_232243.html The design of optimal Low Earth Orbit (LEO) constellations is a complex, high-dimensional challenge central to modern telecommunications. While Genetic Algorithms (GAs) are potent optimization tools, their performance is notoriously sensitive to initial parameter settings, often leading to premature convergence and suboptimal designs. This paper introduces a novel Fully Adaptive Genetic Algorithm (AGA), engineered to overcome this critical limitation through a dynamic, self-correcting framework. The AGA employs an external control loop that co adjusts population size and crossover fraction based on real-time metrics of population diversity and convergence stagnation. To rigorously test its resilience, the AGA was intentionally initialized with the worst-performing parameters from a static GA baseline a configuration guaranteed to fail.First, its robustness was validated on the high-dimensional Rastrigin benchmark function, where, despite the poor start, it outperformed the best static GA by an astonishing factor of 380, proving its exceptional ability to escape deep local optima. The validated AGA was then applied to its primary mission: optimizing a 10-satellite, 30 variable LEO constellation for maximal coverage over Tehran. The results were decisive. The AGA achieved 19.45 hours of daily coverage, a 14.4% improvement over the 17.00 hours achieved by the best-tuned static GA. More remarkably, it accomplished this in just 15 hours, an 80.8% reduction from the 78 hours required by the static GA. This research not only contributes a highly efficient and reliable methodology for indigenous satellite constellation design but also presents a powerful paradigm for solving complex engineering problems where parameter sensitivity is major bottleneck https://www.jsstpub.com/article_232575.html This study addresses the critical challenge of selecting an optimal Walker satellite constellation architecture to ensure continuous and effective regional coverage. In particular, it focuses on a comparative analysis of two widely used configurations Walker Star and Walker Delta to determine which offers superior performance over a specific geographical region, namely the Middle East. Given the increasing demand for reliable satellite-based services in regional applications, identifying the most suitable constellation design is essential for both technical and cost-efficiency considerations. To tackle this challenge, a simulation-driven methodology was adopted using MATLAB and Systems Tool Kit (STK). The study assumes a fixed number of satellites to maintain a controlled comparison framework. MATLAB was utilized for scenario initialization, parametric calculations, and visualization of results, while STK was employed for precise orbit modeling, ground coverage analysis, and dynamic performance evaluation. Key performance indicators such as gap duration, access duration, and percentage of area covered were computed and analyzed to quantitatively assess each configuration’s effectiveness. The findings provide clear insights into the relative strengths and weaknesses of each constellation type and aim to support more informed decision-making in the design and implementation of regional satellite networks. https://www.jsstpub.com/article_232667.html CanSat is an educational competition where students design miniature satellite systems integrated into soda-can-sized containers. Iran CanSat is a competition at the student level that is held each year. In the Remote Sensing-Communication class of the competition, an image processing mission is designed. Target detection and area estimation are the main missions of this competition. In this paper, a simple, applied, and accurate framework based on clustering algorithms is proposed to find targets and areas within them. K-means, fuzzy c-means, and genetic algorithm (GA) K-means algorithms are employed in this study. The proposed framework was applied to a simulated image and an image captured by a CanSat. Results show that the clustering algorithms are appropriate for detecting targets in the image. Experimental results demonstrated identical performance between K-means and GA-optimized K-means clustering, with both methods estimating target areas within 8 m² of ground-truth measurements. Notably, fuzzy c-means (FCM) clustering outperformed these approaches, achieving an accurate area estimation of 661.63 m² – closely approximating field measurements. This precision validates the proposed framework's efficacy for CanSat image processing missions, particularly in target detection and area quantification tasks under competition constraints. https://www.jsstpub.com/article_233448.html Most modern reentry capsules usually have a conical structure with a spherical base, which is chosen due to its favorable aerodynamic properties and ability to withstand high thermal loads during the atmospheric entry phase. One of the key features of these capsules is the low lift-to-drag ratio, which is achieved by a small displacement of the center of mass from the capsule's axis of symmetry. This feature is determined at an angle of attack. In this study, with the aim of analyzing the dynamic behavior of reentry capsules in detail, different classes of reentry capsules are first introduced and then the critical atmosphere model is used to extract the values ​​of the atmospheric density at different altitudes. This information is used to calculate the aerodynamic forces acting on the capsule in the equations of motion. A comprehensive study of the reentry equations is carried out and, in particular, the two-dimensional plane equations of motion are analyzed. In this modeling, the flying body is modeled as a point mass with aerodynamic coefficients dependent on the angle of attack. Next, the effects of parameters such as entry path angle, dynamic pressure, and initial velocity on the dynamic stability of the trajectory in the uncontrolled mode are investigated. In the uncontrolled mode, the capsule has no active actuators for guidance, and only the inherent aerodynamic properties and mass distribution determine its stability and trajectory. This type of motion is especially important in simpler or lower-cost missions. The present study provides a clearer understanding of how small center-of-mass displacements affect the stability of the uncontrolled reentry of a space capsule. These studies can be used to better design future missions. https://www.jsstpub.com/article_232190.html Earthquakes are among the most significant natural disasters, posing persistent threats to human life. Accurate prediction of these events has long been a major challenge, and numerous efforts have been made to address it. A novel approach that has gained attention in recent years involves the use of CubeSat to monitor ionospheric changes prior to earthquakes. Variations in electron temperature and density within the ionosphere can serve as indicators of pre-seismic activity.Analysis of data from several similar missions indicates that this method is capable of detecting pre-seismic anomalies with a considerable degree of accuracy. In this study, an initial design of a one-unit CubeSat is presented using a systematic design approach, in which the components and key parameters of each subsystem have been thoroughly examined and evaluated. The results demonstrate that this design framework can provide a cost-effective, precise, and optimized platform for research missions focused on earthquake prediction.The proposed CubeSat is specifically designed for earthquake prediction through measurements of electron temperature and density. The primary payload was selected for its simplicity and higher measurement accuracy compared to alternative methods. The design process encompasses mission definition and analysis, system engineering, and the development of payloads and subsystems https://www.jsstpub.com/article_232245.html This study investigates the essential role of satellite constellations within the rapidly expanding space economy, emphasizing their increasing contribution to global connectivity, navigation, and economic development. As the demand for reliable space-based infrastructure accelerates, the design and optimization of efficient satellite constellations have become a critical engineering challenge. This research focuses on determining key orbital design parameters for satellite constellations, with particular emphasis on developing an optimized configuration specifically for the Tehran metropolitan region. To address the inherent complexity and high-dimensional nature of the constellation design problem, a hybrid optimization approach is introduced that combines the strengths of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) techniques. The problem is formulated as a thirty-variable optimization task that incorporates both global and local search strategies. Initially, the GA explores the broad solution space to identify high-quality global optima. These solutions subsequently serve as initial conditions for a refined optimization process using the GA-PSO hybrid algorithm, which further improves solution quality and enhances computational efficiency. Through this two-stage optimization process, the objective function was improved by 610 seconds compared to the GA-only approach, demonstrating the effectiveness and superiority of the proposed hybrid method. The final outcome is the design of a ten-satellite LEO constellation optimized to provide maximum coverage over Tehran, achieving 17 hours of daily coverage within a 24-hour period. The findings underscore the significant potential of advanced computational optimization techniques for improving better satellite constellation design and contribute to the development of more efficient, reliable, and cost-effective space-based telecommunication solutions. https://www.jsstpub.com/article_233451.html This paper introduces an efficient Neural Network (NN) model designed to predict the nonlinear mechanical behavior of fiber-reinforced elastomeric composites under large deformations. The foundation of this modeling approach is a scaler strain energy function derived from two tensoral values depending on material's deformation field and fiber orientation. The necessary training data for the NN is generated using a high-fidelity micromechanical homogenization method applied to a Representative Volume Element (RVE) that accurately captures the composite material's microstructure. By subjecting the RVE to large strain loading conditons, the complex micromechanical response is determined, yielding the equivalent macroscopic constitutive behavior for composite material. The developed NN model successfully predicts the complex outcomes of the micromechanical analysis, thus validating its efficacy for modeling anisotropic hyperelastic materials. The primary advantage of this methodology is its potential for a dramatic reduction in computational time during macroscopic Finite Element Analysis (FEM). By operating as a surrogate constitutive model, the NN eliminates the requirement for repeated, direct microstructure analysis at every computational increment, enabling faster and more feasible simulations of composite components. https://www.jsstpub.com/article_233452.html With the growing application of Global Navigation Satellite Systems (GNSS), ensuring the security of these systems has become a critical priority. Among the various threats targeting GNSS, spoofing attacks pose the greatest danger, as they exploit the inability of GPS receivers to distinguish between authentic and spoofed signals. This vulnerability can lead to incorrect navigation equation solutions, ultimately resulting in erroneous position estimations. Due to the lack of a universal method for detecting spoofing attacks, various approaches have been proposed, tailored to specific requirements. One prominent category involves the use of unsupervised machine learning clustering algorithms. While density-based clustering algorithms have demonstrated promising performance, their effectiveness is often limited by a strong dependence on input parameters. In this study, spoofing signals are detected using the HDBSCAN algorithm, a hierarchical density-based clustering approach. The algorithm distinguishes spoofing signals by analyzing signal phase, cross-correlation norm, and the power differential between spoofed and genuine signals. The algorithm's performance is assessed using the Silhouette index, Dunn index, and Confusion Matrix metrics. Field tests validated the proposed algorithm, which was implemented on a software-defined receiver. The results demonstrated a spoofing signal detection accuracy of 98.43%.- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - https://www.jsstpub.com/article_233453.html This study investigates the influence of orbital parameters on the number of satellite visibility events from ground stations, with the aim of optimizing orbit design for space weather monitoring missions. A two-body dynamical model was employed to simulate the satellite trajectory over a 24 hour period, and the number of visibility passes was evaluated with respect to a network of five ground stations located across Iran. The contribution of key orbital elements—including semi-major axis, eccentricity, inclination, RAAN, argument of perigee, and mean anomaly—was quantified using the global Sobol sensitivity analysis method. The first-order Sobol indices revealed that inclination and argument of perigee exert the strongest independent influence on visibility, with maximum values of 0.45 and 0.18, respectively. In contrast, parameters such as RAAN and mean anomaly exhibited minimal first order effects, yet their total indices indicated highly significant interactive contributions, in some cases exceeding 0.9. Furthermore, scenarios corresponding to the maximum number of daily passes were identified. All five stations recorded configurations yielding up to nine passes within 24 hours. The associated orbital parameters exhibited diverse geometrical characteristics, ranging from nearly circular orbits with low eccentricity (0.0028) to more elongated orbits with higher eccentricity (0.0915), and inclinations spanning approximately 40° to 60°. These findings demonstrate the critical role of both independent and interactive effects of orbital elements in determining ground visibility, and they provide valuable insights for the multi-objective design of satellite orbits aimed at enhancing temporal coverage, maximizing pass frequency, and improving the efficiency of space weather monitoring missions. https://www.jsstpub.com/article_233454.html Low Noise Amplifiers (LNAs) play a vital role in communication systems, especially in the receiver section, as they amplify weak received signals with minimal noise. These amplifiers come in various types, but the common-source structure with inductive degeneration is considered one of the most widely used topologies in this field due to its optimal balance between noise figure, gain, and input impedance matching. In this article, the design and simulation of an LNA for the 1.8 GHz GSM band with the aim of achieving high gain, a noise figure of less than 2 dB, and low power consumption are presented. The designed structure utilizes inductive peaking techniques, cascoded configuration to improve stability and isolation, and impedance matching networks. The simulations were conducted using the Cadence Virtuoso tool with the SpectreRF simulator, based on TSMC 0.18 μm RF CMOS technology, with S-parameter and linear and nonlinear analyses. The results show that the designed amplifier has a gain of 17.88 dB, a noise figure of 1.87 dB, and a power consumption of 4.3 mW, making it suitable for sensitive RF applications, especially in mobile devices and base stations. https://www.jsstpub.com/article_233456.html In aerospace structures, parametric resonance or dynamic instability, a destructive phenomenon, can occur due to fluctuating excitation sources such as engine thrust. Auxetic materials and structures are increasingly developed in advanced industries such as aerospace and aviation. Due to their negative Poissons’s ratio, they show interesting static and dynamic behaviors. In this paper, an auxetic structure is used in the core of a thin sandwich cylindrical shell. The effect of geometric parameters of the unit cell of the cellular auxetic core structure is modeled according to the existing relation for the equivalent mechanical properties. Based on the classical shell theory, the dynamic stability of aluminum three layered sandwich cylindrical shells with auxetic core under combined static and periodic loading is investigated. Expansion of a normal mode for the equations of motion leads to a Mathieu-Hill system of equations. The Bolotin method is employed to determine the instability regions for solving the Mathieu-Hill equations. Validation of the natural frequency and dynamic stability results is performed by comparison with other researchers' publications. Then, parametric study is achieved by studying the influence of the geometric parameters of the unit cell on the dynamic stability of the shell. Results show that the corner angle and dimensional aspect ratio of the unit cell govern the size and origin frequency of the unstable areas. https://www.jsstpub.com/article_233459.html The application of laminated fiberous composite materials is increasing in many structures such as shell and plates especially related to applications in airospace engineering. In this paper, the three-dimensional stress distribution in an cross-ply laminated composite cylindrical shell subjected to radial loading is investigated. The formulation is based on a layer-wise, displacement-based theory. First, the displacement and strain field of a cylindrical shell is derived within the framework of the layer-wise theory. Then, by employing the principle of minimum total potential energy, the governing equations of motion and the corresponding boundary conditions for the cross-ply laminated composite cylindrical shell are obtained. An analytical solution is subsequently developed for the governing equations, and the edge boundary conditions are applied to the solution. In the numerical results section, the convergence and accuracy of obtained numerical results are examined with available results in the literature, and stress distributions in a cross-ply composite cylindrical shell which is subjected to lateral loading are computed, and various results corresponding to different loading distributions are presented., the effect of various parameter and the numerical results are investigated. https://www.jsstpub.com/article_233460.html Synthetic Aperture Radar (SAR) image registration is a crucial preprocessing step for many remote sensing applications. However, the presence of speckle noise and homogeneous textures in SAR images makes this task challenging. In this study, we propose a method for SAR image registration. The proposed method, SARNet, is a lightweight and optimized deep neural network specifically designed for SAR images. It generates three distinct descriptors for each keypoint to increase the accuracy of keypoint matching. The method was evaluated on a diverse dataset including Radarsat, Sentinel-1, ALOS-PALSAR, and ERS-2 images. Experimental results show that (SARNet), along with a sub-descriptor matching algorithm, significantly establishes more accurate keypoint correspondences. The network achieves comparable accuracy to state-of-the-art deep learning methods while having the lowest number of parameters (115K) among the methods compared. https://www.jsstpub.com/article_233462.html This paper presents a novel approach for the optimal design of the orbital transfer trajectory of a satellite with proposed continuous-thrust. In this study, the thrust direction angle is approximated using a truncated Fourier series, with the Fourier coefficients selected via a genetic algorithm. The goal of this optimization is to ensure the satellite reaches the desired position in the final orbit while achieving tangential conditions at the entry and exit points, thereby minimizing fuel consumption. The advantage of the proposed method is its ability to account for orbital perturbations, such as the Earth's oblateness effect, without significantly increasing computational complexity. Additionally, the proposed model does not require a predefined number of orbital revolutions, offering high flexibility in mission design. Numerical results and simulations demonstrate that this method provides accurate and efficient transfers between different orbits. Furthermore, performance analysis of this method under varying parameters, such as thrust force and initial orbital conditions, shows its robustness and adaptability. Overall, this paper provides an efficient framework for designing continuous thrust maneuvers in space missions, leading to reduced fuel consumption, shorter operation times, and optimized mission costs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . https://www.jsstpub.com/article_233463.html Forests are vital ecosystems, but many have been greatly altered by human and natural factors, highlighting the need for ongoing monitoring and conservation. This study employs multitemporal satellite image analysis to quantify and characterize forest cover dynamics within the Kore Rood basin, Guilan Province, Iran. It is noteworthy that research on this critical region remains exceedingly scarce, thereby constituting a significant aspect of the novelty in the present study. Leveraging Landsat data from 2001, 2011, and 2023, we systematically assessed land-use and land-cover (LULC) transitions. Results indicate a progressive decline in forest area over the study period, with the maximum extent observed in 2001, followed by significant reductions by 2011 and 2023. Quantitatively, between 2001 and 2023, forest conversion occurred 1.1% to built-up areas, 2.0% to agricultural farms and 10.7% to tea Plantations.These findings demonstrate the substantial pressure exerted by agriculturalland conversion, particularly tea cultivation, on the region's forest resources. Consequently, we strongly advocate for implementing advanced geospatial monitoring systems utilizing high-spatiotemporal-resolution satellite imagery to enable continuous surveillance and inform evidence-based conservation strategies and sustainable land-use management policies for Iran's forest ecosystems. https://www.jsstpub.com/article_233464.html This study applies the Random Forest (RF) machine learning (ML) algorithm to GNSS radio occultation (GNSS-RO) data for two critical space weather forecasting tasks: the prediction of ionospheric amplitude scintillation (S4 index) and the classification of geomagnetic storm occurrence. For S4 index prediction, an RF regression model was trained on a comprehensive feature set derived from interplanetary magnetic field components, geomagnetic indices, solar radio flux, and historical S4 statistics. The model's architecture is optimized, and Recursive Feature Elimination with Gini Importance (Mean Decrease Impurity) method is applied to identify the most predictive features. For storm detection, an RF classifier was trained on parameters including Total Electron Content (TEC), S4 indices, and key solar and geomagnetic variables to distinguish between storm and non-storm conditions. The optimized S4 prediction model achieved high precision with a Mean Absolute Error of 0.007263 and an R² score of 0.517352. Feature selection via Gini Importance significantly improved model efficiency, increasing the Adjusted R² by 50.5%. The geomagnetic storm classifier demonstrated a critical strength of recall of 0.99 for storm events, ensuring missing only 1% of actual storms. Analysis of feature importance confirmed the model's physical validity, correctly identifying the Kp index, F10.7 solar flux and Dst index as the primary drivers for prediction, which aligns with established solar-terrestrial physics. The results demonstrate the high potential of machine learning, specifically Random Forests, for precise space weather forecasting. https://www.jsstpub.com/article_233465.html Wildfires are an integral part of the natural dynamics of forest ecosystems and play an important role in plant regeneration, nutrient cycling, biodiversity, and ecosystem structure. However, in recent decades, climate change, along with human activities, have increased the frequency, severity, and extent of these fires. Given the importance of identifying and managing areas with high fire risk, the aim of this study is to assess fire risk in protected areas of the Hyrcanian temperate forests in northern Iran (Guilan Province). For this purpose, the FlamMap MTT simulation model was used to analyze historical fire patterns in the period 1992-2022 in protected areas of Guilan Province. Using a complete and up-to-date dataset of historical fire data allowed for accurate and reliable analysis of the simulation model results. Guilan Province was selected as the study area due to the frequent occurrence of fires, especially in the autumn and winter seasons. Wildfire hazard maps were generated using burn probability (BP) and conditional flame length (CFL) indices and supported by field data and spatial analyses. The results show that about 8% of fires occurred in protected areas, although these areas cover less than 1% of the total area of the province, but approximately 17.6% of protected areas are located in high or very high hazard zones. These findings emphasize the importance of using fire modeling for the effective conservation and management of Hyrcanian temperate forests, preventive planning, and fire risk reduction, and can be valuable guidance for environmental policymakers and natural resource managers. https://www.jsstpub.com/article_233467.html This article provides an in- depth analysis of the space surveillance and monitoring systems employed by leading countries, focusing on their design principles, technologies, and operational strategies. It begins with a comprehensive review of the major space surveillance capabilities of the United States, China, Russia, and the European Union, highlighting the unique features and approaches each adopts.The United States operates a vast and sophisticated network that integrates multiband phased array radars with advanced optical telescopes. This combined system delivers comprehensive global coverage, enabling effective tracking and monitoring of objects in space across various orbits. China, meanwhile, has made significant strides by concentrating on large optical telescopes and establishing regional optical networks. This approach has particularly enhanced China’s ability to monitor geostationary (GEO) orbits, which are critical for communication and surveillance satellites. Russia continues to rely on its extensive legacy of Soviet-era radar infrastructure, which it supplements with modern technological upgrades to maintain effective space situational awareness. The European Union pursues a different strategy, focusing on scientific research and commercial applications. By integrating optical and radar sensors within a multinational network, the EU seeks to balance diverse objectives through collaboration among member states.Drawing on these international examples, the article proposes an indigenous space surveillance system tailored to Iran’s needs. This proposed system features a combination of ground-based and space- based sensors, including phased array radars and telescopes equipped with adaptive optics for improved accuracy. Additionally, it incorporates advanced data processing infrastructure to manage and analyze the collected information efficiently. https://www.jsstpub.com/article_233898.html Mitigation of high- energy particle radiation in space is necessary for executing long duration space missions successfully. Carbon based polymers and their composites are of huge interest in developing passive shielding techniques due to their high hydrogen content and lightweight nature. In this work, the radiation shielding properties of PEEK is evaluated in GCR free space environment using HZETRN. The total and particle wise dose equivalent is analysed in the human tissue. The variation in thermal conductivity of PEEK in is also studied based on the absorbed dose results. The optimization of the shield design considers a trade-off between mechanical integrity, particularly tensile strength, and its effectiveness in attenuating radiation. The objective is to develop a multi-layered shield with PEEK-W composite and Boron Nitride (BN) in order to get adequate structural integrity and effective shielding efficacy. It is found that PEEK - tungsten (W) composite, with an additional layer of boron nitride (BN) produces 2–4% greater reduction in dose equivalent in tissue as compared to traditional materials such as aluminum. Subsequently, the total shield thickness and tungsten concentration in PEEK are optimized. The results show that a radiation shield with PEEK composite containing 40% tungsten and a total thickness of 16 g/cm2 yields the lowest dose equivalent in tissue. Further, the energy spectrum after transport through the optimized shield is studied for different particle radiations such as proton and iron present in GCR spectrum. It demonstrates the viability of PEEK-W composite as an efficient shielding material for future space exploration. https://www.jsstpub.com/article_233901.html The microalga Haematococcus pluvialis is a natural source of astaxanthin, a red carotenoid that accumulates in the cytoplasm of algal cells under stress conditions and is produced from the transition of motile vegetative cells to non-motile cysts. In industrial astaxanthin production, cyst walls are mechanically disrupted to release astaxanthin, which results in loss of cell viability. In this study, the impact of suborbital flight on H. pluvialis cells was investigated at two growth stages of aplanospore and cyst for the first time. For flight experiments, samples were placed in the bio-capsule during suborbital flight, and then examined in terms of cyst germination, zoospore release, and astaxanthin production after flight. Results showed that 71% of the cyst cells germinated and released zoospores after 2 days post-flight, and the aplanospore cells tended to accumulate pigments. Cell biomass did not change significantly after 7 days of flight. Spaceflight conditions led to a 2.1 and 1.3-fold rise in H2O2 content after 2 and 7 days of flight, respectively. The highest content of astaxanthin (26.1 mg-1 g FW) and phenolic compounds (935.6 mg-1 g FW) was observed in the samples after 7 days of flight. These findings indicate that H. pluvialis can survive spaceflight conditions and may be a promising candidate for inclusion in human life support systems in space. https://www.jsstpub.com/article_233903.html This article focuses on the mitigation of cavitation in fluid flow under specified velocity conditions. A Clark-Y hydrofoil with a 70 mm chord length is designed to emulate a fish-gill-inspired configuration aimed at suppressing unsteady cavitation phenomena. Jet injection with a velocity of 0.5 𝑈∞ is implemented at 15% and 60% of the chord length on the hydrofoil surface under an 8-degree angle of attack. The jet is aligned parallel to the mainstream flow. The flow is modeled using the multiphase implicit Volume of Fluid (VOF) method coupled with the Large Eddy Simulation (LES) turbulence model to accurately capture the transient behavior of cavitating flow. Simulations are performed at a cavitation number of σ = 0.8 and a Reynolds number of 7 × 10⁵. The numerical findings demonstrate that jet injection effectively stabilizes the cavity shedding process and reduces the amplitude of pressure fluctuations on the hydrofoil surface. The injection at 15% chord length not only decreases cavity length but also delays the onset of cloud cavitation, resulting in a smoother pressure recovery and enhanced hydrodynamic performance. In contrast, injection at 60% chord length provides localized suppression of trailing-edge cavitation without significantly affecting leading-edge dynamics. Overall, the study highlights the capability of controlled jet injection as an efficient passive method for mitigating unsteady cavitation and improving flow stability around hydrofoils. https://www.jsstpub.com/article_234329.html In this research, a case study was conducted on a hypothetical satellite constellation based on standard 12U CubeSat satellites. Initially, the key technical specifications of the satellite, including the mass of its main subsystems, were extracted and presented in detail. The masses of subsystems such as Attitude Determination and Control System (1.845 kg), Central Processing Unit (0.716 kg), Electrical Power Supply (2.182 kg), Structure (3.965 kg), Payload (13 kg), and other components were identified, resulting in a total satellite mass of less than 24 kilograms. Subsequently, by employing the proposed cost model, a detailed cost estimation related to a single 12U satellite unit within the overall constellation program framework was provided (as per Table 3). The results of this modeling indicate that the estimated total cost per satellite amounts to $1,215,000. This total cost includes the main cost components as follows: satellite hardware and initial development ($620,100), Assembly, Integration, and Testing (AIT) costs ($899,140), program-level and management expenses ($196,140), launch operations support costs ($111,110), and ground support equipment costs ($92,320). This study demonstrates that directly linking the technical specifications of subsystems to cost components enables more accurate cost estimation and more efficient sensitivity analysis for planners and aerospace systems engineers. It significantly contributes to a better understanding of the key factors influencing the final costs of satellite constellations. https://www.jsstpub.com/article_234711.html In order to investigate the effect of the location of microstructured films on the aerodynamic performance of an airfoil, this paper numerically studies the aerodynamic forces resulting from the placement of V-shaped transverse microgrooves on a NACA 8-H-12 airfoil. To achieve this, microgrooves with a base and height of 150 μm were placed at eight different locations on the surface of an airfoil with a 220 mm chord. Their effects were then investigated at a velocity of 65 m/s and at angles of attack (AoA) of 0 and 4 degrees. The results indicate that the total drag force can either increase or decrease depending on the area and position of the microgrooved film on the airfoil. The maximum drag reduction observed in this study was 4.6%, which occurred with the installation of two 200 mm films at the mid-chord on both the suction and pressure sides of the airfoil at zero AoA. In all cases studied, the trend of increasing pressure drag was found to be the same as the trend of decreasing friction drag. Consequently, the greatest reduction in friction drag led to the largest increase in pressure drag, a behavior that was visible at both AoA. On the other hand, in most cases, the presence of microgrooves has led to an increase in the lift-to-drag ratio. https://www.jsstpub.com/article_235314.html In satellite constellation design, particularly for navigation and positioning applications, system performance and associated costs are among the key factors guiding the design process. In recent years, Low Earth Orbit (LEO) satellite constellations have attracted significant attention from researchers and industry professionals due to their ability to provide wide coverage, low latency, and relatively lower manufacturing and launch costs. In this context, the present study aims to develop a design tool for the simultaneous optimization of performance and cost in LEO based navigation constellations. The proposed tool is developed by linking MATLAB and STK software environments and employs the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm to explore the design space efficiently. The main performance indicator considered in this study is the Geometric Dilution of Precision (GDOP) at the Earth's surface. Additionally, to estimate the total system cost, a combination of the USCM8 and SSCM cost models is utilized. The design parameters include the number of satellites, the number of orbital planes, Walker constellation configurations, orbital elements, and transmitter power. The developed design tool is capable of conducting multi-scenario evaluations to provide a comprehensive and detailed analysis of the trade-off between coverage accuracy and system cost. The simulation results demonstrate that the tool generates reliable and realistic solutions, making it a robust framework for the conceptual design of navigation satellite constellations. This study contributes to the integration of intelligent optimization methods with advanced space simulation tools and paves the way for more advanced research in the field of space system design. https://www.jsstpub.com/article_235315.html Background: Long-duration space missions introduce complex physiological, psychological, and operational challenges due to microgravity, radiation, isolation, and confined environments. Ensuring astronaut health and mission success requires adaptive, evidence-based, and internationally harmonised selection protocols.Objective: This narrative synthesis evaluates current astronaut selection criteria for long-duration missions, critically examining physiological, psychological, and technical domains, identifying limitations of existing frameworks, and highlighting emerging technologies and international considerations.Methods: Peer-reviewed literature, agency standards, and technical guidance from NASA, ESA, JAXA, Roscosmos, and commercial entities were reviewed. Key physiological stressors, behavioural competencies, and skill requirements were linked to exclusion and competency criteria, with a focus on actionable recommendations, comparative analysis, and emerging AI- and digital twin–enabled assessment tools.Results: Critical selection domains include musculoskeletal and cardiovascular resilience, vestibular and immune system integrity, cognitive and emotional stability, leadership and teamwork capabilities, and advanced academic and operational competence. Comparative analysis reveals variability across agencies, highlighting gaps in mission-specific thresholds, duration-based criteria, and integration of emerging countermeasures. AI-assisted monitoring and digital twin simulations offer transformative potential for continuous risk assessment and personalised adaptation.Conclusion: Developing space programs should implement evidence-informed, adaptive selection frameworks that integrate physical, psychological, and technical competencies, harmonised international standards, and emerging technologies. Prospective evaluation, continuous monitoring, and tiered, mission-specific criteria are essential to optimise safety, performance, and operational success on long-duration missions. https://www.jsstpub.com/article_235316.html The International Space Station (ISS) presents a complex array of environmental, psychological, social, and technological stressors that challenge human adaptation in orbit. While many of these factors are well documented, this technical note advances a framework of integrated countermeasures tailored to crew size, mission phase, and system contingencies. Drawing from a synthesis of empirical and operational literature, it proposes a layered mitigation model uniting architectural, behavioural, physiological, and automation-based strategies. This multidimensional approach supports adaptive trade-offs between habitat constraints, crew autonomy, and mission control support, promoting sustained performance, safety, and psychosocial resilience in extreme environments. The analysis examines implications for expanding occupant capacity, sustaining extended-duration missions, and informing evidence-based design principles for future orbital and planetary habitats. Findings suggest that, under current operational and environmental limitations, an ISS crew size of six remains optimal; exceeding this threshold demands rigorous, system-wide application of integrated countermeasures. The paper concludes with targeted recommendations, interdisciplinary insights, and open research priorities to guide the evolution of human factors engineering, digital health integration, and adaptive mission design in next-generation space habitats and long-duration exploration missions. https://www.jsstpub.com/article_235317.html Integrated modelling of spacecraft roto-translational relative motion is an emerging topic of interest for multi-agent space systems design, analysis and control. Dual-quaternion is a satisfactory solution to this complex problem. Model Predictive Control (MPC) is, on the other hand, a powerful model-based control methodology with known superiorities over other modern control approaches used in the field of spacecraft control. Embedding the dual-quaternion model in the MPC approach for sophisticated systems, thus yields a valuable control framework. There are, however, some difficulties involved in this proposition that need to be addressed. This matter is scrutinized in the present work. To this aim, the concept of dual-quaternion and relevant tools are first reviewed. Subsequently, potential interfaces between dual-quaternion expressions and MPC framework are highlighted. Accordingly, a piecewise affine MPC scheme based on the dual-quaternion model is introduced and further developed in several aspects for space roto-translational relative control missions. First, it has been improved for zero steady-state error. Furthermore, it has been developed to explicitly deal with reaction wheels as attitude actuators, in terms of limitations as well as related costs. The efficacy of the proposed integrated scheme is assessed by comprehensive simulations. https://www.jsstpub.com/article_235318.html The direct fusion of Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS) data using a Kalman filter is a highly effective method for enhancing navigation solution accuracy and stability. This approach distinguishes itself from indirect methods by delivering superior performance in estimation speed and precision, achieved through a simplified filter structure and reduced processing delays inherent in other integration techniques. To validate these advantages, a nonlinear Extended Kalman Filter (EKF) was implemented for a detailed analysis of parameter estimation.A comprehensive analysis of real-world flight data confirms the significant benefits of the direct fusion method. The results demonstrate a notable increase in estimation accuracy, along with enhanced stability and robustness under adverse conditions such as signal degradation or dynamic maneuvers. This approach also demonstrated faster convergence speeds, allowing the navigation solution to stabilize more quickly. Furthermore, flight test validation confirms that this direct approach accelerates the estimation of initial INS errors. This capability leads to a more rapid determination of geographic north during the alignment phase, a critical factor for rapid system deployment. Ultimately, this study provides a comprehensive empirical validation of the direct fusion method, highlighting its practical value for modern navigation challenges. https://www.jsstpub.com/article_235319.html In conventional Inertial Navigation Systems (INS), the error accumulation due to the integration process leads to drift in the actual values of position, velocity, and attitude of an unmanned aerial vehicle. In this study, to mitigate such accumulated errors, a Rotating Inertial Navigation System (RINS) is implemented around the vertical axis using low-cost Inertial Measurement Unit (IMU) sensors. First, the influence of various error sources—including bias, scale factor, and misalignment errors—over time in a static scenario is analyzed for the rotary configuration. Then, a comparative evaluation is performed against a conventional INS. Subsequently, the effect of each error source is investigated in a dynamic test through software simulation of a single-degree-of-freedom RINS, with results compared to those of the conventional INS simulation. Moreover, to validate the simulation results, experimental tests are designed and conducted to assess the accuracy of the rotary inertial navigation system under real-world conditions. Finally, the RINS is implemented on a single-degree-of-freedom rate table in the Control Systems Laboratory environment of the aerospace department of Sharif University. The results demonstrate that the RINS configuration effectively reduces bias, scale factor, and misalignment errors around the body’s x and y axes. https://www.jsstpub.com/article_235320.html Accurate calibration of inertial sensor biases is critical for preventing accumulated error growth in inertial navigation systems (INS). Conventional approaches, such as Kalman filtering and its variants, often involve significant computational complexity, dependence on precise noise modeling, and require extensive parameter tuning to ensure stability and convergence. To address these challenges, this paper presents a novel online algebraic calibration method that reformulates the INS error dynamics to directly isolate and express accelerometer and gyroscope bias terms in a closed-form manner. The proposed algorithm estimates biases by solving a deterministic system of linear equations constructed from the error states between a reference and a dependent navigation system, thereby completely eliminating the need for iterative filtering or probabilistic updates. Comprehensive simulation studies under both stationary and cruise flight conditions demonstrate the method’s high accuracy, rapid convergence, and robustness against measurement noise. The results further highlight its excellent numerical stability and adaptability to time-varying sensor characteristics. Overall, the proposed approach achieves precise and consistent bias estimation with minimal computational cost, providing a fast, stable, and resource-efficient alternative for real-time implementation in safety-critical applications such as aviation, autonomous vehicles, and robotics. https://www.jsstpub.com/article_235321.html This paper presents a novel hybrid optimization approach that simultaneously employs B-spline and thin plate spline (TPS) basis functions for accurate reflector surface shaping in geostationary (GEO) satellite antennas. In this method, the reflector perturbation is modeled as the sum of expansions of these two sets of basis functions, and their unknown coefficients are determined using a minimax optimization technique. Since TPS functions minimize the bending energy and produce smoother surfaces, while B-splines provide higher precision in radiation pattern shaping, the proposed hybrid approach achieves both surface smoothness and pattern accuracy. Extensive numerical simulation results show that, although the convergence speed and accuracy of the hybrid method are about 10% lower than those of the pure B-spline method, the surface bending energy is reduced by more than 90%, resulting in a much smoother and more uniform reflector surface. Furthermore, the RMS optimization error is approximately 60% lower compared to the pure TPS-based approach. These results confirm that the proposed method preserves radiation accuracy while providing a smoother, more stable, and fabrication-friendly surface, outperforming conventional shaping methods.