Numerical investigation on the cavitating wake flow around a cylinder based on proper orthogonal decomposition

The non-cavitating and cavitating wake flow of a circular cylinder, which contains multiscale vortices, is numerically investigated by Large Eddy Simulation combined with the Schnerr–Sauer cavitation model in this paper. In order to investigate the spatiotemporal evolution of cavitation vortex structures, the Proper Orthogonal Decomposition (POD) method is employed to perform spatiotemporal decomposition on the cylinder wake flow field obtained by numerical simulation. The results reveal that the low-order Proper Orthogonal Decomposition modes correspond to large-scale flow structures with relatively high energy and predominantly single frequencies in both non-cavitating and cavitating conditions. The presence of cavitation bubbles in the flow field leads to a more pronounced deformation of the vortex structures in the low-order modes compared to the non-cavitating case. The dissipation of pressure energy in the cylinder non-cavitating wake occurs faster than the kinetic energy. While in the cavitating wake, the kinetic energy dissipates more rapidly than the pressure energy

Research on Intelligent Organization and Application of Multi-source Heterogeneous Knowledge Resources for Energy Internet

ABSTRACTTo improve the informationization and intelligence of the energy Internet industry and enhance the capability of knowledge services, it is necessary to organize the energy Internet body of knowledge from existing knowledge resources of the State Grid, which have the characteristics of large scale, multiple sources, and heterogeneity. At the same time, the business fields of State Grid cover a wide range. There are many sub-fields under each business field, and the relationship between fields is diverse and complex. The key to establishing the energy Internet body of knowledge is how to fuse the heterogeneous knowledge resources from multiple sources, extract the knowledge contents from them, and organize the different relationships. This paper considers transforming the original knowledge resources of State Grid into a unified and well-organized knowledge system described in OWL language to meet the requirements of heterogeneous resource integration, multi-source resource organization, and knowledge service provision. For the State Grid knowledge resources mainly in XML format, this paper proposes a Knowledge Automatic Fusion and Organization idea and method based on XSD Directed Graph. According to the method, the XML corresponding XSD documents are transformed into a directed graph in the first stage during which the graph neural network detects hidden knowledge inside the structure to add semantic information to the graph.In the second stage, for other structured knowledge resources (e.g., databases, spreadsheets), the knowledge contents and the relationships are analyzed manually to establish the mappings from structured resources to graph structures, using which the original knowledge resources are transformed into graph structures, and merged with the directed graphs obtained in the first stage to achieve the fusion of heterogeneous knowledge resources. And expert knowledge is introduced for heterogeneous knowledge fusion to further extend the directed graph. And in the third stage, the expanded directed graph is converted to the body of knowledge in the form of OWL. This paper takes the knowledge resources in the field of human resources of the State Grid as an example, to establish the ontology of the human resources training field in a unified manner, initially demonstrating the effectiveness of the proposed method

Numerical investigation of energy loss distribution in the cavitating wake flow around a cylinder using entropy production method

The wake flow of a circular cylinder is numerically investigated by Large Eddy Simulation (LES) combined with the Schnerr–Sauer cavitation model. By comparing entropy production in the presence or absence of cavitation, the energy loss distribution in the wake flow field of a cylinder is explored, shedding light on the interactions between multiscale vortex systems and cavitation. The comparative results reveal that, under non-cavitating conditions, the energy loss region in the near-wake area is more concentrated and relatively larger. Energy dissipation in the wake flow field occurs in regions characterized by very high velocity gradients, primarily near the upper and lower surfaces of the cylinder near the leading edge. The influence of cavitation bubbles on entropy production is predominantly observed in the trailing-edge region (W1) and the near-wake region (W2). The distribution trends of wall entropy production on the cylinder’s surface are generally consistent in both conditions, with wall entropy production primarily concentrated in regions exhibiting high velocity gradients

ISAC-Enabled Beam Alignment for Terahertz Networks: Scheme Design and Coverage Analysis

As a key pillar technology for the future 6G networks, terahertz (THz) communication can provide high-capacity transmissions, but suffers from severe propagation loss and line-of-sight (LoS) blockage that limits the network coverage. Narrow beams are required to compensate for the loss, but they in turn bring in beam misalignment challenge that degrades the THz network performance. The high sensing accuracy of THz signals enables integrated sensing and communication (ISAC) technology to assist the LoS blockage and user mobility-induced beam misalignment, enhancing THz network coverage. In line with the 5G beam management, we propose a joint synchronization signal block (SSB) and reference signal (RS)-based sensing (JSRS) scheme to predict the need for beam switches, and thus prevent beam misalignment. We further design an optimal sensing signal pattern that minimizes beam misalignment with fixed sensing resources, which reveals design insights into the time-to-frequency allocation. We derive expressions for the coverage probability and spatial throughput, which provide instructions on the ISAC-THz network deployment and further enable evaluations for the sensing benefit in THz networks. Numerical results show that the JSRS scheme is effective and highly compatible with the 5G air interface. Averaged in tested urban use cases, JSRS achieves near-ideal performance and reduces around 80% of beam misalignment, and enhances the coverage probability by about 75%, compared to the network with 5G-required positioning ability

M-estimation in Low-rank Matrix Factorization: a General Framework

Many problems in science and engineering can be reduced to the recovery of an unknown large matrix from a small number of random linear measurements. Matrix factorization arguably is the most popular approach for low-rank matrix recovery. Many methods have been proposed using different loss functions, for example the most widely used L_2 loss, more robust choices such as L_1 and Huber loss, quantile and expectile loss for skewed data. All of them can be unified into the framework of M-estimation. In this paper, we present a general framework of low-rank matrix factorization based on M-estimation in statistics. The framework mainly involves two steps: firstly we apply Nesterov's smoothing technique to obtain an optimal smooth approximation for non-smooth loss function, such as L_1 and quantile loss; secondly we exploit an alternative updating scheme along with Nesterov's momentum method at each step to minimize the smoothed loss function. Strong theoretical convergence guarantee has been developed for the general framework, and extensive numerical experiments have been conducted to illustrate the performance of proposed algorithm

Compact Autoregressive Network

Autoregressive networks can achieve promising performance in many sequence modeling tasks with short-range dependence. However, when handling high-dimensional inputs and outputs, the huge amount of parameters in the network lead to expensive computational cost and low learning efficiency. The problem can be alleviated slightly by introducing one more narrow hidden layer to the network, but the sample size required to achieve a certain training error is still large. To address this challenge, we rearrange the weight matrices of a linear autoregressive network into a tensor form, and then make use of Tucker decomposition to represent low-rank structures. This leads to a novel compact autoregressive network, called Tucker AutoRegressive (TAR) net. Interestingly, the TAR net can be applied to sequences with long-range dependence since the dimension along the sequential order is reduced. Theoretical studies show that the TAR net improves the learning efficiency, and requires much fewer samples for model training. Experiments on synthetic and real-world datasets demonstrate the promising performance of the proposed compact network

Dietary specialization drives multiple independent losses and gains in the bitter taste gene repertoire of Laurasiatherian Mammals

Background: Bitter taste perception is essential for species with selective food intake, enabling them to avoid unpalatable or toxic items. Previous studies noted a marked variation in the number of TAS2R genes among various vertebrate species, but the underlying causes are not well understood. Laurasiatherian mammals have highly diversified dietary niche, showing repeated evolution of specialized feeding preferences in multiple lineages and offering a unique chance to investigate how various feeding niches are associated with copy number variation for bitter taste receptor genes. Results: Here we investigated the evolutionary trajectories of TAS2Rs and their implications on bitter taste perception in whole-genome assemblies of 41 Laurasiatherian species. The number of intact TAS2Rs copies varied considerably, ranging from 0 to 52. As an extreme example of a narrow dietary niche, the Chinese pangolin possessed the lowest number of intact TAS2Rs (n = 2) among studied terrestrial vertebrates. Marine mammals (cetacea and pinnipedia), which swallow prey whole, presented a reduced copy number of TAS2Rs (n = 0-5). In contrast, independent insectivorous lineages, such as the shrew and insectivorous bats possessed a higher TAS2R diversity (n = 52 and n = 20-32, respectively), exceeding that in herbivores (n = 9-22) and omnivores (n = 18-22). Conclusions: Besides herbivores, insectivores in Laurasiatheria tend to have more functional TAS2Rs in comparison to carnivores and omnivores. Furthermore, animals swallowing food whole (cetacean, pinnipedia and pangolin) have lost most functional TAS2Rs. These findings provide the most comprehensive view of the bitter taste gene repertoire in Laurasiatherian mammals to date, casting new light on the relationship between losses and gains of TAS2Rs and dietary specialization in mammals

Endovascular treatment of multiple intracranial aneurysms in patients with subarachnoid hemorrhage: one or multiple sessions?

ObjectiveThis study aimed to compare the safety and efficacy of single- and multiple-stage endovascular treatment in aneurysmal subarachnoid hemorrhage (SAH) patients with multiple intracranial aneurysms.MethodsWe retrospectively analyzed the clinical and imaging data of 61 patients who harbored multiple aneurysms and presented to our institution with aneurysmal subarachnoid hemorrhage. Patients were grouped according to endovascular treatment strategy: one-stage or multiple-stage.ResultThe 61 study patients harbored 136 aneurysms. One aneurysm in each patient had ruptured. In the one-stage treatment group, all 66 aneurysms in 31 patients were treated in one session. The mean follow-up was 25.8 months (range, 12–47). At the last follow-up, the modified Rankin scale was ≤2 in 27 patients. In total, 10 complications occurred (cerebral vasospasm, six patients; cerebral hemorrhage, two patients; and thromboembolism, two patients). In the multiple-stage treatment group, only the ruptured aneurysm (30 in total) was treated at the time of presentation, and the remaining aneurysms (40 in total) were treated later. The mean follow-up was 26.3 months (range, 7–49). At the last follow-up, the modified Rankin scale score was ≤2 in 28 patients. In total, five complications occurred (cerebral vasospasm, four patients; and subarachnoid hemorrhage, one patient). During the follow-up period, there was one recurrence of aneurysm with subarachnoid hemorrhage in the single-stage treatment group and four recurrences in the multiple-stage treatment group.ConclusionBoth single- and multiple-stage endovascular treatment is safe and effective in aneurysmal subarachnoid hemorrhage patients who harbor multiple aneurysms. However, multiple-stage treatment is associated with a lower rate of hemorrhagic and ischemic complications