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This paper studies the periodic event-triggered bipartite containment control problem of multi-agent systems with unmeasurable states and input delays. To deal with the system input delay problem, a Pade approximation technique is introduced. By utilising the sampled output of the system, a fuzzy state observer is constructed to estimate the unknown state. A periodic event-triggered mechanism is designed, which can effectively reduce the usage of communication resources. Compared with the traditional event-triggered control manner, a periodic event-triggered control manner only monitors the preset threshold condition at the sampling instant to determine whether to update the current control signal, which can automatically guarantee the minimum lower bound of the execution interval, avoiding the occurrence of Zeno behaviour. Stability analysis verifies that all signals in the closed-loop system are bounded, and the bipartite tracking error can converge to a small neighbourhood of the origin. Finally, a practical example further verifies the effectiveness of the designed control scheme. [ABSTRACT FROM AUTHOR]

During a design basis accident in a pressurized water reactor (PWR), the released hydrogen through reactor breaks would induce the hydrogen detonation. The hydrogen passive autocatalytic recombiner (PAR) is widely used as a hydrogen elimination measure in nuclear power plants due to its passive capability, low starting threshold and easy installation. The present work aims to study the hydrogen risk after the occurrence of cold section double-end shear fracture large break loss coolant accident (LBLOCA) by using the 3D computational fluid dynamics program GASFLOW. A full containment model of CPR1000 is built. The hydrogen production rate inside the containment after LBLOCA is calculated from the related physicochemical reactions. The hydrogen transport, hydrogen concentration distribution and temperature distribution inside the containment are simulated. The effects of different roughness of the structure surface on the simulation are investigated, and it is proved that the operation of PAR can control the hydrogen concentration under the safety threshold of 4 vol%. The effects of hydrogen flow rate and PAR’s position on the hydrogen elimination efficiency are studied. Based on these studies, this paper makes some suggestions and theoretical references for the spatial arrangement scheme of PAR in the containment to optimize the hydrogen elimination efficiency.

This paper investigates the problem of predefined-time event-triggered adaptive tracking control for strict-feedback nonlinear systems (SFNSs) with full-state constraints. To handle asymmetric full-state constraints, a nonlinear state-dependent function (NSDF) that purely depends on the constraint state is introduced. Then, a switching threshold event-triggered mechanism (ETM) is designed to enhance usage efficiency of communication resources. Moreover, a predefined-time event-triggered adaptive tracking controller is constructed by incorporating a smooth tuning function into each step of the backstepping design based on dynamic surface technology. Under such a control scheme, the output tracking error can be steered to the small neighborhood of the origin within the user setting time. Compared to various previous control schemes developed for full-state constrained systems, our proposed method can circumvent the demanding feasibility conditions in controller designs. Finally, a simulation result is given to illustrate the effectiveness of the control scheme. [ABSTRACT FROM AUTHOR]

Crack is a common concrete pavement distress that will deteriorate into severe problems without timely repair, which means the automated detection of pavement crack is essential for pavement maintenance. However, automatic crack detection and segmentation remain challenging due to the complex pavement condition. Recent research on pavement crack detection based on deep learning has laid a good foundation for automated crack segmentation, but there can still be improvements. This paper proposes an automatic concrete pavement crack segmentation framework with enhanced graph network branch. First, the nodes of the graph and nodes' attributions are generated based on the image dividing. The edges of the graph are determined based on Gaussian distribution. Then, the graph from the image is input into the graph branch. The graph feature map of the graph branch output is fused with the image feature map of the encoder and then enters the decoder to recover the image resolution to obtain the crack segmentation result. Finally, the method is tested on a self-built 3D concrete pavement crack dataset. The proposed method achieves the highest F1 and IoU (Intersection over Union) in the comparison experiments. And the graph branch addition improves 0.08 on F1 and 0.06 on IoU compared with U-Net., Author(s): Jiang Chen [1]; Ye Yuan [1]; Hong Lang (corresponding author) [1]; Shuo Ding [1]; Jian John Lu [1] 1. Introduction Road infrastructure is an essential asset for a country, [...]

Compliant strain sensors are crucial for soft robots’ perception and autonomy. However, their deformable bodies and dynamic actuation pose challenges in predictive sensor manufacturing and long-term robustness. This necessitates accurate sensor modelling and well-controlled sensor structural changes under strain. Here, we present a computational sensor design featuring a programmed crack array within micro-crumples strategy. By controlling the user-defined structure, the sensing performance becomes highly tunable and can be accurately modelled by physical models. Moreover, they maintain robust responsiveness under various demanding conditions including noise interruptions (50% strain), intermittent cyclic loadings (100,000 cycles), and dynamic frequencies (0–23 Hz), satisfying soft robots of diverse scaling from macro to micro. Finally, machine intelligence is applied to a sensor-integrated origami robot, enabling robotic trajectory prediction (<4% error) and topographical altitude awareness (<10% error). This strategy holds promise for advancing soft robotic capabilities in exploration, rescue operations, and swarming behaviors in complex environments.Due to the deformable nature of soft robots, developing robust sensors that can sustain stability and performance is a challenge. Here, the authors report a computational strain sensor design based on a programmed crack array for predictable, tunable, and stable sensing performance. [ABSTRACT FROM AUTHOR]

The winds of a typhoon are a significant meteorological hazard with substantial implications for maritime transportation and are of paramount importance. Studying wind field characteristics and establishing effective algorithms for wind correction are of significant practical and societal importance within the realm of cargo transport operations at ports and terminals, thereby guaranteeing the sustainable development of port shipping. This study investigates the influence of typhoon winds on ports in the central to northern areas of the Taiwan Strait, considering different typhoon paths, by utilizing ground automatic station observations and numerical model forecasts. Furthermore, this research examines deviations in wind field forecasts generated by the ECMWF numerical model and the subsequent correction of surface wind patterns. The results indicate that: (1) maximum wind speeds during typhoons following various paths are most notable in the proximity of coastal islands near Putian, Fujian province, predominantly due to the topographical effects of the strait. (2) Wind speeds at individual stations are contingent on the typhoon's trajectory, while the pressure difference could serve as a reliable indicator of typhoon intensity and onset timing. (3) Following polynomial fitting correction, the forecast deviations are reduced by 37% for the u component and 40% for the v component. The score for the u component increases notably from 41.60 to 63.17 after correction, representing an improvement of 51.85%, while the v component score rises significantly from 29.33 to 48.89, showing an enhancement of 66.70%. This research has implications for future forecasts of typhoon winds that impact ports in the central and northern sections of the Taiwan Strait, meeting the meteorological service needs of cargo ships entering the port and better serving the sustainable development of the local economy and society. [ABSTRACT FROM AUTHOR]