The influence of large foundation arrangement on underwater radiated noise of underwater vehicle engine compartment

Mechanical vibration is the main noise source of underwater vehicle. The foundation of the main power is an important pathway of mechanical noise. Large size foundation of the power not only affects the vibration transmitted from the power to the hull structure, but also affects the vehicle shell radiation area and radiation efficiency, thus affecting the radiation noise of underwater vehicle. Based on the study of the influence of the large size foundation arrangement on the radiated noise of underwater vehicles, two new types of foundation arrangement were proposed. The foundation could meet the requirements on the acoustic performance, and could greatly reduce the radiation surface area of the shell and reduce the radiated Sound Pressure. To the power compartment general layout and support function, three foundation layout schemes such as continuous style, large span style and bulkhead support style in the typical excitation of power equipment were designed. Further way, far field underwater radiation noise of the compartment was numerically calculated. The results show that bulkhead support style can effectively reduce underwater acoustic radiation of the compartment shell on the premise of the meet the weight control and impedance characteristics

Multi-Carrier NOMA-Empowered Wireless Federated Learning with Optimal Power and Bandwidth Allocation

Wireless federated learning (WFL) undergoes a communication bottleneck in uplink, limiting the number of users that can upload their local models in each global aggregation round. This paper presents a new multi-carrier non-orthogonal multiple-access (MC-NOMA)-empowered WFL system under an adaptive learning setting of Flexible Aggregation. Since a WFL round accommodates both local model training and uploading for each user, the use of Flexible Aggregation allows the users to train different numbers of iterations per round, adapting to their channel conditions and computing resources. The key idea is to use MC-NOMA to concurrently upload the local models of the users, thereby extending the local model training times of the users and increasing participating users. A new metric, namely, Weighted Global Proportion of Trained Mini-batches (WGPTM), is analytically established to measure the convergence of the new system. Another important aspect is that we maximize the WGPTM to harness the convergence of the new system by jointly optimizing the transmit powers and subchannel bandwidths. This nonconvex problem is converted equivalently to a tractable convex problem and solved efficiently using variable substitution and Cauchy's inequality. As corroborated experimentally using a convolutional neural network and an 18-layer residential network, the proposed MC-NOMA WFL can efficiently reduce communication delay, increase local model training times, and accelerate the convergence by over 40%, compared to its existing alternative.Comment: 33 pages, 16 figure

DoF-NeRF: Depth-of-Field Meets Neural Radiance Fields

Neural Radiance Field (NeRF) and its variants have exhibited great success on representing 3D scenes and synthesizing photo-realistic novel views. However, they are generally based on the pinhole camera model and assume all-in-focus inputs. This limits their applicability as images captured from the real world often have finite depth-of-field (DoF). To mitigate this issue, we introduce DoF-NeRF, a novel neural rendering approach that can deal with shallow DoF inputs and can simulate DoF effect. In particular, it extends NeRF to simulate the aperture of lens following the principles of geometric optics. Such a physical guarantee allows DoF-NeRF to operate views with different focus configurations. Benefiting from explicit aperture modeling, DoF-NeRF also enables direct manipulation of DoF effect by adjusting virtual aperture and focus parameters. It is plug-and-play and can be inserted into NeRF-based frameworks. Experiments on synthetic and real-world datasets show that, DoF-NeRF not only performs comparably with NeRF in the all-in-focus setting, but also can synthesize all-in-focus novel views conditioned on shallow DoF inputs. An interesting application of DoF-NeRF to DoF rendering is also demonstrated. The source code will be made available at https://github.com/zijinwuzijin/DoF-NeRF.Comment: Accepted by ACMMM 202

Architecture engineering of carbonaceous anodes for high‐rate potassium‐ion batteries

The limited lithium resource in earth's crust has stimulated the pursuit of alternative energy storage technologies to lithium‐ion battery. Potassium‐ion batteries (KIBs) are regarded as a kind of promising candidate for large‐scale energy storage owing to the high abundance and low cost of potassium resources. Nevertheless, further development and wide application of KIBs are still challenged by several obstacles, one of which is their fast capacity deterioration at high rates. A considerable amount of effort has recently been devoted to address this problem by developing advanced carbonaceous anode materials with diverse structures and morphologies. This review presents and highlights how the architecture engineering of carbonaceous anode materials gives rise to high‐rate performances for KIBs, and also the beneficial conceptions are consciously extracted from the recent progress. Particularly, basic insights into the recent engineering strategies, structural innovation, and the related advances of carbonaceous anodes for high‐rate KIBs are under specific concerns. Based on the achievements attained so far, a perspective on the foregoing, and proposed possible directions, and avenues for designing high‐rate anodes, are presented finally

Compound robust control of permanent magnet synchronous motor based on quasi‐Z source inverter

Abstract In this study, a compound control strategy for motor side and quasi‐Z source side is proposed to improve the robustness of the quasi‐Z source permanent magnet synchronous motor drive system subjected to external disturbance. In this method, the complementary sliding mode control and sliding mode control as feedback controllers are combined with the disturbance observer technology as a feed‐forward compensator to achieve fast tracking and disturbance suppression for the PMSM drive system. Firstly, the signal models of quasi‐Z source inverters and motors are established. Secondly, by introducing state variables, the composite sliding mode controller is designed with strong robustness based on matched disturbances. Then, in order to further improve the disturbance suppression performance, a disturbance observer based on a feed‐forward compensator is designed to estimate the mismatched external disturbances in the motor drive system. Finally, the global asymptotic stability based on Lyapunov criterion is proved. The simulation and experimental results show that the proposed compound control strategy has the advantages of fast convergence, small motor speed pulsation and strong robustness to external disturbances