Research on the stability of the 3D frame on coral foundation subjected to impact load

This article presents an application of the finite element method (FEM) for the stability analysis of 3D frame (space bar system) on the coral foundation impacted by collision impulse. One-way joints between the rod and the coral foundation are described by the contact element. Numerical analysis shows the effect of some factors on the stability of the bar system on coral foundation. The results of this study can be used for stability analysis of the bar system on coral foundation subjected to sea wave load

Three invariants of geometrically vertex decomposable ideals

We study three invariants of geometrically vertex decomposable ideals: the Castelnuovo-Mumford regularity, the multiplicity, and the $a$-invariant. We show that these invariants can be computed recursively using the ideals that appear in the geometric vertex decomposition process. As an application, we prove that the $a$-invariant of a geometrically vertex decomposable ideal is non-positive. We also recover some previously known results in the literature including a formula for the regularity of the Stanley--Reisner ideal of a pure vertex decomposable simplicial complex, and proofs that some well-known families of ideals are Hilbertian. Finally, we apply our recursions to the study of toric ideals of bipartite graphs. Included among our results on this topic is a new proof for a known bound on the $a$-invariant of a toric ideal of a bipartite graph

Spatial-Temporal Recurrent Graph Neural Networks for Fault Diagnostics in Power Distribution Systems

Fault diagnostics are extremely important to decide proper actions toward fault isolation and system restoration. The growing integration of inverter-based distributed energy resources imposes strong influences on fault detection using traditional overcurrent relays. This paper utilizes emerging graph learning techniques to build a new temporal recurrent graph neural network models for fault diagnostics. The temporal recurrent graph neural network structures can extract the spatial-temporal features from data of voltage measurement units installed at the critical buses. From these features, fault event detection, fault type/phase classification, and fault location are performed. Compared with previous works, the proposed temporal recurrent graph neural networks provide a better generalization for fault diagnostics. Moreover, the proposed scheme retrieves the voltage signals instead of current signals so that there is no need to install relays at all lines of the distribution system. Therefore, the proposed scheme is generalizable and not limited by the number of relays installed. The effectiveness of the proposed method is comprehensively evaluated on the Potsdam microgrid and IEEE 123-node system in comparison with other neural network structures

Grid-Forming Inverter-based Wind Turbine Generators: Comprehensive Review, Comparative Analysis, and Recommendations

High penetration of wind power with conventional grid following controls for inverter-based wind turbine generators (WTGs) weakens the power grid, challenging the power system stability. Grid-forming (GFM) controls are emerging technologies that can address such stability issues. Numerous methodologies of GFM inverters have been developed in the literature; however, their applications for WTGs have not been thoroughly explored. As WTGs need to incorporate multiple control functions to operate reliably in different operational regions, the GFM control should be appropriately developed for the WTGs. This paper presents a review of GFM controls for WTGs, which covers the latest developments in GFM controls and includes multi-loop and single-loop GFM, virtual synchronous machine-based GFM, and virtual inertia control-based GFM. A comparison study for these GFM-based WTGs regarding normal and abnormal operating conditions together with black-start capability is then performed. The control parameters of these GFM types are properly designed and optimized to enable a fair comparison. In addition, the challenges of applying these GFM controls to wind turbines are discussed, which include the impact of DC-link voltage control strategy and the current saturation algorithm on the GFM control performance, black-start capability, and autonomous operation capability. Finally, recommendations and future developments of GFM-based wind turbines to increase the power system reliability are presented

Using Fine-Grained Sediment and Wave Attenuation as a New Measure for Evaluating the Efficacy of Offshore Breakwaters in Stabilizing an Eroded Muddy Coast: Insights from Ca Mau, the Mekong Delta of Vietnam

Offshore breakwaters can be effective in reducing the energy of incident waves through dissipation, refraction or reflection. Breakwaters are increasingly constructed to stabilize eroded muddy coasts, particularly in developing countries. Accumulation of fine-grained sediment and wave attenuation are two attributes of a stable muddy coast. Effective interventions in stabilizing eroded muddy coasts include two important elements: accumulation of fine-grained sediment and wave reduction. The efficacy of offshore breakwaters in stabilizing eroded muddy coasts is, however, not yet adequately understood. A crucial question needing attention is whether accumulation of fine-grained sediment and wave attenuation should be used in evaluating the efficacy of these offshore breakwaters in stabilizing eroded muddy coasts. To address this issue, a pile-rock offshore breakwater in Huong Mai, Tieu Dua of Ca Mau, Vietnam was selected as an appropriate example in this regard. Accumulation of fine-grained sediment and wave attenuation were tested as means to investigate the efficacy of the Huong Mai structure in stabilizing the eroded muddy coast. The study was undertaken using field-based measurements and semi-structured interviews in three stages between October 2016 and December 2020. We found that this structure has had limited efficacy in stabilizing the eroded muddy coast. The structure was effective in dissipating the energy of incident waves, but we found no evidence of fine-grained sediment accumulation due to an inappropriate structural design. There was also no monitoring system in place, leading to difficulties in evaluating its efficacy in terms of wave attenuation and accumulation of fine-grained sediment. The gaps between the shoreline and the structure have not been adequately explained, resulting in substantial challenges in replicating the structure elsewhere. The Huong Mai structure should be strengthened using supplementary measures and granulometric tests in order to improve the efficacy in stabilizing eroded muddy coasts. The methods in this study provide new insights in this regard

Outage performance analysis and SWIPT optimization in energy-harvesting wireless sensor network deploying NOMA

Thanks to the benefits of non-orthogonal multiple access (NOMA) in wireless communications, we evaluate a wireless sensor network deploying NOMA (WSN-NOMA), where the destination can receive two data symbols in a whole transmission process with two time slots. In this work, two relaying protocols, so-called time-switching-based relaying WSN-NOMA (TSR WSN-NOMA) and power-splitting-based relaying WSN-NOMA (PSR WSN-NOMA) are deployed to study energy-harvesting (EH). Regarding the system performance analysis, we obtain the closed-form expressions for the exact and approximate outage probability (OP) in both protocols, and the delay-limited throughput is also evaluated. We then compare the two protocols theoretically, and two optimization problems are formulated to reduce the impact of OP and optimize the data rate. Our numerical and simulation results are provided to prove the theoretical and analytical analysis. Thanks to these results, a great performance gain can be achieved for both TSR WSN-NOMA and PSR WSN-NOMA if optimal values of TS and PS ratios are found. In addition, the optimized TSR WSN-NOMA outperforms that of PSR WSN-NOMA in terms of OP.Web of Science193art. no. 61