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The Ultraviolet Transient Astronomy Satellite (ULTRASAT) is scheduled to be launched to geostationary orbit in 2027. It will carry a telescope with an unprecedentedly large field of view (204 deg2) and near-ultraviolet (NUV; 230–290 nm) sensitivity (22.5 mag, 5σ, at 900 s). ULTRASAT will conduct the first wide-field survey of transient and variable NUV sources and will revolutionize our ability to study the hot transient Universe. It will explore a new parameter space in energy and timescale (months-long light curves with minutes cadence), with an extragalactic volume accessible for the discovery of transient sources that is >300 times larger than that of the Galaxy Evolution Explorer (GALEX) and comparable to that of the Vera Rubin Observatory’s Legacy Survey of Space and Time. ULTRASAT data will be transmitted to the ground in real time, and transient alerts will be distributed to the community in <15 minutes, enabling vigorous ground-based follow up of ULTRASAT sources. ULTRASAT will also provide an all-sky NUV image to >23.5 AB mag, over 10 times deeper than the GALEX map. Two key science goals of ULTRASAT are the study of mergers of binaries involving neutron stars, and supernovae. With a large fraction (>50%) of the sky instantaneously accessible, fast (minutes) slewing capability, and a field of view that covers the error ellipses expected from gravitational-wave (GW) detectors beyond 2026, ULTRASAT will rapidly detect the electromagnetic emission following binary neutron star/neutron star–black hole mergers identified by GW detectors, and will provide continuous NUV light curves of the events. ULTRASAT will provide early (hour) detection and continuous high-cadence (minutes) NUV light curves for hundreds of core-collapse supernovae, including for rarer supernova progenitor types.

This study is dedicated to investigating the downsizing design and ensuring the structural robustness of pole-mounted slewing mechanisms, aligning with the dynamic requirements of the power industry. The research encompasses critical facets, including the intricacies of mechanical structure design, meticulous motor selection, and a thorough finite element analysis. The outcomes reveal a noteworthy safety factor of 2.08, surpassing the standard requirement of ≥ 2, albeit without factoring in stress concentration. This study underscores the paramount importance of downsizing design in meeting the evolving demands of the modern power industry. It offers invaluable insights into the structural integrity and stability of the mechanism, thereby ensuring its reliability and safety in practical applications. The implications of these findings are poised to catalyse significant technological advancements in the realm of pole-mounted electric slewing mechanisms.

Hydraulic excavators are mostly used in mines and construction sites. To minimize the energy consumption of hydraulic excavators during operation, a slewing energy-saving system of hydraulic hybrid excavators is presented. A parameter matching method of non-dominated sorting genetic algorithm (NSGA-II) considering feasible and infeasible solutions is proposed. In the parameter matching method, the population is divided into feasible solutions and infeasible solutions. By combining and iterating the excellent individuals in the feasible solutions and infeasible solutions, the optimal parameters of the accumulator are obtained under the condition of comprehensive optimal energy-saving efficiency and dynamic system performance. Furthermore, a control strategy is developed to augment the operational efficiency of the slewing energy-saving system. Finally, an Amesim simulation model is developed based on a 50-ton excavator manufactured by Sunward Intelligence. Simulation outcomes demonstrate that the energy-saving system pre-optimization achieved a 40.3% energy-saving efficiency compared to the conventional system. After optimization, the energy-saving system’s energy-saving efficiency increased to 46.6% compared to the conventional system, marking a 6.3% increase in energy-saving efficiency relative to the pre-optimization state. The effectiveness of the slewing energy-saving system and the proposed matching algorithm is verified.

Understanding the contact behaviour of slewing-ring thrust ball bearings is essential for accurate predictions of load distribution and evaluations of static and dynamic load capacity. Applying Hertz’s theory to non-standard slewing ring bearings presents unique challenges due to their complex geometries and difficulties in achieving uniform surface finishes, leading to significant deviations from actual stress. This study addresses these limitations by comparing experimental results, numerical results, and the Hertz theory. The analysis considers three Hertz contact configurations between the bearing ball and the raceway. The results reveal significant deviations from the experimental values. To determine the cause of these variations, the friction coefficient between the ball and the raceway is determined using the gravitational method by varying the number of balls. Uneven load distribution across balls in slewing ring bearings under mechanical loads is exposed by friction coefficient measurement. To further explore, load-deformation experiments are conducted on the LMMB by placing varying numbers of balls and their positions. Results expose variations in load-taking behaviour among the balls, emphasizing the critical influence of contact area load distribution.

To address the real-time attitude monitoring requirements for portal slewing cranes in automated operations, this study proposes a dynamic attitude detection method based on a quad-GPS receiver configuration. By deploying four GPS modules at critical kinematic nodes of the crane’s luffing mechanism, combined with coordinate transformation algorithms and quaternion-based attitude determination models, the system achieves real-time acquisition of three-dimensional spatial coordinates, yaw angles, and tilt states. A dual-validation framework was implemented to assess system accuracy: 1) comparative validation between handheld GPS measurements and fused GPS solutions, and 2) stability verification through integration with the automated control system. Experimental results demonstrate spatial positioning errors less than 0.3 meters and yaw angle deviations below 0.1°, meeting the precision thresholds for anti-collision and path-planning requirements in port automation. The multi-sensor redundancy design enhances anti-interference capability while maintaining cost-effectiveness, demonstrating engineering practicability for intelligent retrofitting of heavy lifting equipment.

As the main bearing component of the tunnel boring machine (TBM), the three‐row roller slewing bearing is required to withstand a heavy load and overturning moment in the tunnelling process. Therefore, a dynamic model of a slewing bearing considering the external load and internal structural parameters is established. First, the influence of the complex load on the internal structural parameters (clearance, radial displacement, roller tilt and skew) of the slewing bearing is analysed. Then, by using the four‐stage Runge–Kutta method, the dynamic model is solved, and the influence of different parameters on the dynamic performance and stability is obtained. Finally, the proposed model is verified via experimental research, and the accuracy error of the model is less than 7%. The state of the inner ring’s motion progressively changes from stable to unstable as the rotational speed increases. The dynamic characteristics of a slewing bearing can be improved by reducing the radial clearance and the number of rollers while it is subjected to excessive eccentric loading. The results of this study provide important guidance for the design of slewing bearing structures.

This manuscript presents an innovative methodology for the assessment of the friction torque of ball slewing bearings. The methodology aims to overcome the limitations of state-of-the-art approaches, especially when the friction torque is conditioned by the preload of the balls. To this end, the authors propose to simulate the preload scatter when solving the load distribution problem, prior to the friction torque calculation. This preload scatter allows to simulate a progressive transition of the balls from a four-point contact state to a two-point contact one. By implementing this capability into an analytical model, the authors achieve a successful correlation with experimental results. Nonetheless, depending on the stiffness of the structures to which the bearing is assembled, it is demonstrated that the rigid ring assumption can lead to inaccurate friction torque results when a tilting moment is applied. The methodology described in this research work is meant to have a practical application. Therefore, the manuscript provides guidelines about how to use and tune the analytical model to get a reliable friction torque prediction tool.

To investigate the load-bearing characteristics of lightweight surface-mounted slewing cable anchorage, this paper takes the Yellow River Three Gorges Bridge project as an example, establishing a nonlinear finite element model and verifying its effectiveness through a 1:100 scale physical model test. Furthermore, a theoretical stability analysis model was established to quantify the contributions of base friction and toothed block clamping action. By analyzing displacement behavior, rock mass shear characteristics, and plastic zone evolution, the combined load-bearing mechanism was revealed. The results show that the anchorage system begins to destabilize when the load reaches 18P. Both numerical and theoretical analyses confirm that the toothed blocks significantly improve the stability of the anchorage system; the safety factor increases from 6.84 considering only friction to 16.59 considering clamping action, which is consistent with the 17P plastic threshold observed in the simulation. Rock mass resistance is generated from bottom to top, providing passive resistance through shear action. The final determined failure mode is the interconnection of local plastic zones and the overturning failure of the anchorage system.

Due to the fewer fault samples, it is difficult to diagnose the fault of slewing bearings in complex working conditions. For this reason, a model based on Time-series Generative Adversarial Networks (Time GAN) combined with Synergistic Similarity Graph Construction (SSGC) and Graph Attention Network (GAT) is proposed. Time GAN is introduced to generate new training sample features while preserving the unique temporal correlation of its samples. SSGC method is utilized to construct graph structure data for the newly generated training samples and put them into the GAT model with multi-head attention mechanism for classification. This solves the problem that traditional deep learning methods cannot fully utilize the spatial relationship between training sample features under different working conditions. The experimental results show that the proposed method can effectively recognize each health state of slewing bearing with classification accuracy of up to 90%, which is better than other methods.

We introduce a new capability of the Neil Gehrels Swift Observatory, dubbed “continuous commanding,” that achieves 10 s latency response time on orbit to unscheduled target-of-opportunity requests received on the ground. We show that this will allow Swift to respond to premerger (early-warning) gravitational-wave (GW) detections, rapidly slewing the Burst Alert Telescope (BAT) across the sky to place the GW origin in the BAT field of view at or before merger time. This will dramatically increase the GW/gamma-ray burst (GRB) codetection rate and enable prompt arcminute localization of a neutron star merger. We simulate the full Swift response to a GW early-warning alert, including input sky maps produced at different early-warning times, a complete model of the Swift attitude control system, and a full accounting of the latency between the GW detectors and the spacecraft. 60 s of early warning can double the rate of a prompt GRB detection with arcminute localization, and 140 s guarantees observation anywhere on the unocculted sky, even with localization areas ≫1000 deg2. While 140 s is beyond current GW detector sensitivities, 30–70 s is achievable today. We show that the detection yield is now limited by the latency of LIGO/Virgo cyberinfrastructure and motivate a focus on its reduction. Continuous commanding has been integrated as a general capability of Swift, significantly increasing its versatility in response to the growing demands of time-domain astrophysics. We demonstrate this potential on an externally triggered fast radio burst (FRB), slewing 81° across the sky, and collecting X-ray and UV photons from the source position <150 s after the trigger was received from the Canadian Hydrogen Intensity Mapping Experiment, thereby setting the earliest and deepest such constraints on high-energy activity from nonrepeating FRBs. The Swift Team invites the community to consider and propose novel scientific applications of ultra-low-latency UV, X-ray, and gamma-ray observations.