Search Results (444)

Rock glaciers are critical indicators of periglacial environments and the spatial distribution of mountain permafrost. Given their complex deformation patterns and temporal variability, which may indicate progressive destabilization, a quantitative evaluation of their kinematic activity is critical from both climatological and geohazard perspectives. This study applies Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) to Sentinel-1 radar imagery on both ascending and descending orbits, in order to detect and map moving areas (MA) within the Pirin Mountains (Bulgaria). The primary objective of this study is to update the existing rock glacier inventory (RoGI) by integrating high-resolution Line-of-Sight (LOS) velocity data in accordance with the latest international standards established by the Rock Glacier Inventories and Kinematics (RGIK) standing committee. A secondary objective is to investigate the spatial relationships between the identified moving areas (MAs) and other surrounding geomorphological features (e.g., talus slopes), hence providing a wider context for slope dynamics and landform evolution. The results identified MAs with PSInSAR-derived Line-of-Sight (LOS) velocities reaching up to 10 cm yr⁻¹, which were subsequently classified according to RGIK kinematic categories. A substantial proportion of the detected moving areas occur outside mapped rock glacier boundaries and may reflect a range of geomorphological processes, including permafrost-related creep, talus creep, or other forms of slope deformation. The LOS velocity data were used to assess the activity status of 74 rock glacier units within the regional inventory, classifying 8 as transitional (velocity exceeding 1 cm yr⁻¹) and 66 as relict. Furthermore, we analyse the spatial distribution of these moving areas in relation to primary topographic variables, such as elevation, aspect, and slope. The results highlight the influence of topographic control factors and rock glacier dynamics and provide new insights into the distribution of active periglacial landforms and terrain potentially affected by permafrost in the Balkan Peninsula under changing climatic conditions. Full article

Landslide susceptibility assessment is essential for hazard mitigation and sustainable urban planning, yet many existing approaches rely primarily on static environmental predictors and often neglect active slope deformation. This limitation is particularly relevant in rapidly urbanizing areas, where human activity may destabilize slopes and reactivate dormant landslides. This study develops a process-informed susceptibility framework that integrates LiCSBAS-derived SBAS-InSAR deformation into a MaxEnt model for the urban and peri-urban residential areas of Cluj-Napoca, Romania. Two comparative models were implemented: (i) a baseline model using conventional conditioning factors and (ii) an enhanced model incorporating Sentinel-1 LOS velocity derived from SBAS-InSAR time-series analysis (2020–2023). The study quantitatively evaluates the predictive value of deformation-informed susceptibility modelling under single-orbit InSAR conditions, independently validates velocity data using EGMS observations, and constitutes the first integration of InSAR-derived ground deformation into landslide susceptibility assessment for Cluj-Napoca. Results show moderate-to-strong agreement between SBAS and EGMS deformation data (Pearson correlation ≈ 0.7). Incorporating LOS velocity improved model performance (AUC from 0.809 to 0.833; p < 0.001) and increased the spatial correspondence between mapped landslides and high- and very high-susceptibility zones. The integrated framework enabled the identification of localized active instability zones and provided a practical basis for hazard-informed urban planning and land management. Full article

The present work examines how variations in working fluid temperature govern the hydrodynamic behavior of a space-rated micropump. Using perfluorotriethylamine as the operating medium, three-dimensional CFD simulations employing the SST k-$\omega$ turbulence closure were carried out across a broad thermal spectrum, and the resulting flow physics were interpreted through entropy generation analysis. Based on the entropy production theory, the influence laws of different inlet temperatures on the external characteristics, internal characteristics, and flow loss characteristics of the micropump were quantitatively analyzed. The results show that temperature mainly affects the micropump performance by changing the viscosity and density of the working fluid. At low temperatures, the fluid viscosity increases significantly, leading to increased flow resistance, intensified internal friction, reduced head and efficiency, and increased shaft power. As the temperature increases to 0 °C and above, the viscosity change tends to moderate, and the external characteristic parameters tend to stabilize. The internal characteristic analysis shows that under low-temperature conditions, the high-pressure region in the impeller area expands and the turbulent kinetic energy decreases, but the flow separation is to a certain extent suppressed. The region near the volute tongue and the impeller outer edge are the main areas of entropy production loss, and their entropy production rates increase significantly with decreasing temperature. Moreover, at low temperatures, the high entropy production regions expand from locally isolated distributions to continuous large-scale distributions. The impeller outer edge dominates total entropy production, driven by peak fluid linear velocity and intense shear interaction with the volute wall. The findings elucidate how working fluid temperature governs both the hydrodynamic performance and the irreversible loss characteristics of the micropump. These insights can directly inform the engineering design of thermal management loops intended for orbital applications under severe temperature swings. Full article

Space-based single-photon ranging of space debris is affected by sparse signal photons, strong background noise, motion-induced echo broadening, and the amplification of local ranging errors during velocity estimation. To address these problems, this paper proposes a reliability-aware joint distance–velocity extraction framework that couples coded-echo processing with inter-window motion continuity. In each observation window, a phase-space trajectory matrix is constructed from the photon-counting echo, and fixed-rank truncated SVD is used as a front-end structural enhancement step to preserve the dominant temporal structure of the broadened coded echoes while suppressing part of the diffuse photon-count fluctuation. Coded cross-correlation is then used for coarse delay localization, followed by peak-neighborhood sub-bin estimation. A composite range-observation reliability measure is constructed from the retained singular-value-energy ratio, correlation-peak significance, and peak-to-sidelobe ratio. Reliability-weighted local polynomial fitting and distance–velocity joint optimization subsequently provide continuous range and radial-velocity estimates. In an orbital-reference simulation, the proposed method reduced the range RMSE, MAE, and MaxAE by 84.74%, 83.22%, and 83.83%, respectively, relative to VBSPC, and reduced the corresponding velocity errors by 89.36%, 89.04%, and 94.30% relative to IMMK. A 30-trial ablation study indicated the complementary contributions of SVD enhancement, sub-bin estimation, and joint optimization, while repeated tests under different coding conditions and 20–100% signal-photon levels demonstrated robustness to photon-count reduction. A scaled moving-target experiment further achieved range and velocity RMSEs of 0.066 m and 0.033 m/s, respectively. The experiment validates the measured-echo processing chain rather than the complete orbital optical link. The results demonstrate that jointly exploiting coded-echo structure, observation reliability, and motion continuity provides robust range-trajectory and radial-velocity extraction for photon-starved moving targets. Full article

The apsidal motion in close eccentric binaries is a means to unveil the internal structure of stars. We make use of it to test the internal mixing processes in stars with the stellar evolution code GENEC. Apsidal motion is the slow precession of an eccentric orbit with time. Its rate depends on the tidal interactions that occur between the stars through k 2 , a measure of the star’s inner density profile. The apsidal motion rate is commonly derived from the eclipses’ times of minima, made possible thanks to high-precision TESS/Kepler observations. We propose an innovative approach: derive the apsidal motion rate from radial velocities obtained over a long timescale combined with light curves to obtain high-accuracy consistent physical and orbital parameters for the binaries. We highlight recent results concerning the most massive binary studied this way. Confronted to observations of massive stars, standard non-rotating single-star models usually predict stars with too low a density contrast; the so-called k 2 -discrepancy. We built bespoke GENEC stellar evolution models including tidally induced/suppressed rotational mixing for the twin massive binary HD152248. The models reveal the instabilities that allow us to reproduce the stellar density profiles. A large overshooting is necessary to converge towards the observed k 2 in both purely hydrodynamic and magneto-diffusive models. While a change in metallicity or mass-loss rate has no significant impact on k 2 , a large initial helium abundance allows us to better reproduce k 2 . However, is not observationally supported. These analyses highlight the need for a process in the stars that extends the size of the convective core. It paves the way for the next generation of stellar models. Full article

The Bohr radius is normally presented as a non-relativistic length scale. Less widely discussed is that Bohr’s 1913 work also indicated how the radius formula changes when the orbital velocity is not negligible compared with the speed of light. We revisit this relativistic prescription and show that, for a point nucleus and a one-electron Coulomb field, it gives $a_{0,r}^{\left(Z\right)}={\displaystyle \frac{a_0}{Z}}\sqrt{1-Z^2{\alpha }^2},$ which is exactly the most-probable radius obtained independently from the Dirac $1s_{1/2}$ radial probability density. The two radii are calculated independently and are found to be analytically identical. This equality does not derive the Dirac result from the Bohr model; rather, it shows that Bohr’s relativistic circular-orbit prescription selects the same radial scale as the maximum of the Dirac probability distribution. We also show that the same construction extends to the node-free circular Dirac excited states, for which $r_{\mathrm{mp}}^D(n,\kappa =-n)=(a_0/Z)n\sqrt{n^2-Z^2{\alpha }^2}$. We emphasize throughout that most-probable radii are distinct from expectation values and from empirical radii of many-electron atoms. Full article

It is challenging to detect continuous low-thrust maneuver parameters of non-cooperative satellites because the signals are weak over limited observation arcs and are readily masked by measurement noise and orbit-determination errors. This paper proposes a conditional diffusion model for detecting and estimating continuous low-thrust maneuver parameters from relative-orbit observations. The method uses relative-orbit observations of the non-cooperative target to construct conditional inputs that incorporate orbital dynamical priors. Single-step differencing and dimensionless processing are then used to strengthen weak maneuver signatures. The conditional diffusion model learns the evolution of maneuver parameters under noisy conditions and estimates three-axis continuous low-thrust acceleration sequences. Based on simulations considering the Gaussian noise of relative positions and velocities, the proposed method achieved 85.2% maneuver detection accuracy, while that of the batch least-squares benchmark method was 67.8%. The proposed method is simulated and verified based on Sentinel-6A. Results show that the continuous low-thrust maneuver can be robustly identified under low signal-to-noise ratios and the temporal parameter evolution can be recovered. The method provides a practical route for analyzing non-cooperative satellite maneuver and supporting on-orbit space situational awareness. Full article

Hybrid rocket motors are an attractive option for the upper-stages of low-cost small launchers, but are susceptible to variability in performance both in time and between firings. Moreover, key contributors to hybrid motors’ performance such as oxidizer-to-fuel ratio ($O/F$) are difficult to estimate, and by extension, to control. Four approaches were evaluated for the estimation and control of $O/F$ under system uncertainty, including through on-line estimation by an Unscented Kalman Filter (UKF). A Monte Carlo analysis was conducted of a simulated hybrid kick motor, where key sources of system uncertainty such as the characteristic velocity efficiency (${\eta }_{c^{*}}$), fuel regression coefficients, and oxidizer flow characteristics were allowed to be variable. Feedback control of $O/F$ informed by the UKF obtained 6.8% smaller control error than the best alternative approach. Yet the Monte Carlo analysis showed that among uncertainty sources considered, ${\eta }_{c^{*}}$ was the primary driver of performance variability, while $O/F$ regulation had a small influence. This was because the total and specific impulses were relatively insensitive to $O/F$ for the considered motor configuration and ranges of $O/F$ observed during the simulated burns—highlighting the importance of system uncertainty quantification when formulating performance-regulating interventions. Further, the proposed UKF observer provided data-informed estimates of combustion efficiency and propellant residuals in time, which are valuable for the planning and execution of accurate orbital insertions in a kick motor susceptible to performance uncertainty. The developed uncertainty quantification and control modeling framework can be used also during the design and assessment of other control interventions under system uncertainty. Full article

A transient multibody dynamics simulation of rolling-element bearings is the basis for the design of high-speed rotating machinery; however, the established solvers are proprietary, cannot be used with automatic differentiation, and offer no built-in measure of their own physical consistency. We present OpenBEARD, an open-source, fully differentiable transient dynamics solver for angular-contact ball bearings. The solver steps a $40+13Z$-component state (inner ring, cage, and Z balls with quaternion attitude, plus guide-patch, lumped-thermal, and energy-audit states) forward in time under coupled Hertzian contact, Hamrock–Dowson and full-multigrid elastohydrodynamic lubrication, thermal–elastohydrodynamic traction, and centrifugal/press-fit clearance models, using nondimensionalized implicit stiff time integration. A built-in metriplectic conservation audit checks energy closure, the second law per dissipation channel, and the gyroscopic-power identity at every output step. OpenBEARD is cross-verified against two published ADORE references of Gupta. For a high-speed NASA angular-contact ball bearing, the quasi-static contact loads, angles, stresses, and centrifugal force match the published values to within $0.3\%$, and the ball spin and orbital velocities and the spin-axis orientation to ≤0.1%. The inner-race spin-to-roll ratio—a slip-derived secondary quantity that is the most model-sensitive metric in this class of solvers—differs from the NASA quasi-static reference by $8.8\%$. In the separate caged BallBearingTestCase benchmark, the corresponding quasi-static difference is $3.2\%$, and the transient settled value is $\approx 16\%$ above the ADORE step-100 snapshot; these bounded offsets reflect different spin-moment constitutive models. The BallBearingTestCase comparison—a caged bearing under combined thrust and radial load—matches the per-ball contact angles and loads to within $0.23\%$ RMS, and a single published dynamic snapshot (step 100) agrees with the transient contact mechanics to within a few percent. The built-in energy-closure residual stays of order ${10}^{-5}$ with no second-law violations. In the fully transient regime, race control emerges as a dynamical attractor of the coupled traction balance—ball-spin states perturbed by $\pm 12\%$ converge to a single outer-race-control solution—rather than the kinematic hypothesis assumed by quasi-static theory. OpenBEARD is released under the MIT license. Full article

Our research explores the sensitivity of satellite constellations to fluctuations in the quantum gravitational field, with the aim of quantifying their potential impact on critical operations and precision measurement. The main objective is to quantify the potential impact of hypothetical quantum effects on the precise orbital dynamics of satellite constellations. The methods employed will involve the development of a sophisticated computational model using the quantum toolbox QuTIP in Python. Our model will simulate the trajectories of various satellite constellation configurations in two distinct gravitational frameworks: one based on classical general relativity and the other incorporating theoretical models of quantum gravitational fluctuations. The main task is to meticulously analyze and compare the resulting differences in key orbital parameters, including position, velocity, and orbital period, between these two scenarios. This comparative analysis is crucial in determining whether the minute stochastic perturbations resulting from quantum gravity could accumulate over time and measurably affect the performance and objectives of current and future high-precision satellite missions, such as those related to Earth observation, global navigation satellite systems (GNSSs), or space-based gravitational wave detectors. The expected results have provided essential insights into the potential need to integrate quantum gravitational corrections into very high-precision astrodynamics and will contribute significantly to ongoing theoretical and experimental efforts to unify quantum mechanics and general relativity at the macroscopic scale. Full article

Over the past three decades, five satellites have succeeded one another on the reference orbit, building the longest continuous climate record of global sea level measurements. Its continuity is ensured thanks to tandem flights between consecutive satellites. In this paper, we demonstrate that the first satellite of the Sentinel-6 series (Sentinel-6 Michael Freilich) has enabled the detection of a processing anomaly in the Jason-1/2/3 ground segment. An inconsistency in the altimeter range reconstruction has been identified, causing its underestimation by 3.65 mm. At certain latitudes, determined by the satellite’s orbital velocity, the altimeter range shows no effect from the anomaly. For the reference orbit, the range is not affected at the poles, around the equator and, for ascending tracks, at 40° S. All Jason Geophysical Data Record (GDR) versions prior to GDR-G are impacted by the described processing anomaly. While a full reprocessing of the Jason data with the GDR-G standard is pending, this paper presents a latitudinal empirical correction to be applied to Jason datasets generated with GDR-F and earlier ground segments. This correction, to be applied on the altimeter range, is derived from one month of patched Jason-3 data and is intended for reference orbit only. Additionally, SWOT Nadir ground processing is also affected by the same processing error and has been corrected from the GDR-S2 version onward. Finally, our analysis shows a negligible impact of this processing anomaly on Jason Level-2-derived products, models and metrics. Full article

Ground-based optical observation is a key sensing modality for space-object monitoring, but reliable association becomes challenging when orbital priors are degraded, site-position information is imprecise, and each frame contains multiple point-source candidates. This paper proposes a robust framework for single-target association among multiple image candidates and recursive estimation under such conditions. The method first converts image-domain candidates into unit line-of-sight (LOS) directions and represents their local deviations in a prediction-aligned tangent plane. Angular measurement noise and site-position uncertainty are then propagated into the local covariance model. Based on this representation, a kinematic-photometric five-dimensional (5D) normalized innovation squared (NIS) gating statistic is constructed by jointly evaluating local position, pseudo-velocity, and photometric consistency. After association, a three-dimensional decoupled Kalman update is performed using only the single-frame position and photometric measurements. Experiments on four real ground-based optical satellite observation sequences, including two static scenarios and two dynamic scenarios, show correct association rates of 100.00%, 100.00%, 100.00%, and 85.86%, respectively. These results demonstrate that the proposed framework improves association reliability under degraded orbital priors and imprecise site-position information while maintaining stable recursive estimation. Full article

On-Orbit Servicing (OOS) represents a viable strategy toward a sustainable and extended exploitation of the Low-Earth-Orbit (LEO) environment. The design of OOS missions requires optimizing both the scheduling of visited objects and the transfer trajectory between each pair of orbits, resulting in the great complexity of the global mission planning problem. This research considers a servicing spacecraft equipped with a high-thrust propulsion system, required to perform multiple orbit transfers to visit several Resident Space Objects (RSOs) in a given time frame with minimum fuel consumption. The proposed method leverages a two-stage approach: (i) first, the optimal transfers are computed for all pairs of orbits and discretized dates, and the associated overall velocity changes are stored in a cost matrix; (ii) then, the problem of visiting all RSOs is cast as a search problem, and the solution space is explored through an ${\mathrm{A}}^{\ast }$ algorithm. The transfer strategy exploits intermediate drift orbits to increase the differential precession due to the $J_2$ harmonic of the Earth’s gravitational potential. Moreover, the ${\mathrm{A}}^{\ast }$ procedure leverages a heuristic function based on a modified version of the Held–Karp algorithm, which is proven to be admissible and consistent, meaning that the optimal solution is always reached. The proposed strategy is integrated within a flexible architecture, where operational constraints on phasing and servicing activities can be enforced as well. Finally, the methodology at hand is successfully applied to a case study from the literature involving three successive missions, in charge of visiting 5 RSOs each. Different discretization grids are considered, and the results are compared in terms of overall velocity change and computational time. Full article

The effective-one-body (EOB) formalism accurately describes the conservative dynamics of general binary orbits, but current implementations of radiation reaction remain largely limited to quasi-circular inspirals. Extending EOB to eccentric orbits currently requires the corresponding post-Newtonian (PN) energy fluxes in EOB coordinates, which are only known to 1PN order. In this paper, we compute the instantaneous gravitational-wave energy flux in EOB coordinates to 2PN accuracy using a systematic coordinate transformation between the Arnowitt–Deser–Misner (ADM) and EOB phase-space variables. We derive the 2PN-accurate transformation laws for the relative coordinates and velocities between the two coordinate systems and re-express the 2PN instantaneous energy flux entirely in EOB variables. Working within the EOB test-particle framework (with finite mass ratio $\nu$) for an equatorial elliptic orbit, we adopt a Keplerian reparameterization in terms of the semilatus rectum p, eccentricity e, and two phase variables $(\xi ,\varphi )$ associated with the radial and azimuthal motion, which makes the calculations more transparent and facilitates the subsequent computation of gravitational waveforms. Using the conservative orbital angular frequency, we compute the orbit-averaged energy flux. In addition to the energy flux, we also compute the corresponding 2PN angular momentum flux in EOB coordinates using the same transformation method. Our results, expressed in gauge-invariant variables $x={\left(M\omega \right)}^{2/3}$ and eccentricity $e_t$, agree with known PN results and show improved accuracy compared to the 1PN EOB fluxes of Hinderer and Babak. Full article

Accurate ballistic trajectory prediction for upper stages on low Earth orbit is challenged by non-stationary atmospheric density driven by solar activity: as density varies, fixed noise covariance matrices in standard Kalman filters become mismatched with actual process statistics, causing degraded estimation accuracy. Non-stationary atmospheric density disrupts fixed-covariance Kalman filters in low Earth orbit, degrading trajectory prediction for upper stages. This paper characterises the quantitative position/velocity accuracy trade-off and performance boundaries of the Sage–Husa Adaptive EKF (AEKF), identifying an empirical sensor-noise approximate crossover region near σ* ≈ 100 m where the AEKF improves velocity accuracy by 38.9% at the cost of a 59% increase in position RMSE. Full article