The impact of initial imperfections on the fatigue assessment of tower flange connections in floating wind turbines : a review

During the massive manufactures and installations of fixed offshore wind turbines in China, initial imperfections were often found in the inspection. As more and more attentions and efforts of the wind energy sector have been devoted to deep waters with fixed and floating wind turbines (FWTs), the impact of such initial imperfections on fatigue assessment is paramount to the reliable design and safe operation, which warrant rigorous study. This paper presents a comprehensive review of three different initial imperfections and their impacts on the fatigue lifetime of FWTs’ tower flange connections. A brief introduction on FWTs and flange connections is provided at first. This is followed by a detailed discussion of the environmental loadings and fatigue assessment on the flange bolted connections. Finally, a comprehensive review of the state-of-art research on three common initial imperfections, including flatness divergence, bolt loosening and tower inclination, are presented. Their impact on fatigue assessment is further discussed

Divide and Conquer Partition for Fourier Reconstruction Sparse Inversion with its Applications

A partition method, with an efficient divide and conquer partition strategy, for the non-uniform sampling signal reconstruction based on Fourier reconstruction sparse inversion (FRSI) is developed. The novel partition FRSI(P-FRSI) is motivated by the observation that the partition processing of multi-dimensional signals can reduce the reconstruction difficulty and save the reconstruction time. Moreover, it is helpful to choose suitable reconstruction parameters. The P-FRSI employs divide and conquer strategy, and the signal is firstly partitioned into some blocks. Following that, traditional FRSI is applied to reconstruct signals in each block. We adopt linear or nonlinear superposition to determine the weight coefficients during integrating these blocks. Finally, P-FRSI is applied to two-dimensional seismic signal reconstruction. The superiority of the new method over conventional FRSI is demonstrated by numerical reconstruction experiments

A feasibility study of multi-electrode high-purity germanium detector for Ge-76 neutrinoless double beta decay searching

Experiments to search for neutrinoless double-beta (0{\nu}\b{eta}\b{eta}) decay of 76Ge using a high-purity germanium (HPGe) detector rely heavily on background suppression technologies to enhance their sensitivities. In this work, we proposed a pulse-shape analysis method based on a neural network (NN) and a light gradient boosting machine (lightGBM; LGB) to discriminate single-electron (background) and double-electrons (0{\nu}\b{eta}\b{eta} signal) events in a multi-electrode HPGe detector. In this paper, we describe a multi-electrode HPGe detector system, a data-processing system, and pulse-shape simulation procedures. We built a fully connected (FC) neural network and an LGB model to classify the single- and double-electron events. The FC network is trained with simulated single- and double-electron-induced pulses and tested in an independent dataset generated by the pulse-shape simulation. The discrimination efficiency of the FC neural network in the test set for the 0{\nu}\b{eta}\b{eta} double-electron events signal was 77.4%, the precision was 57.7%, and the training time was 430 min. The discrimination efficiency of LGB model was 73.1%, the precision was 64.0%, and the training time was 1.5 min. This study demonstrated that it is feasible to realize single- and double-electron discrimination on multi-electrode HPGe detectors using an FC neural network and LGB model. These results can be used as a reference for future 76Ge 0{\nu}\b{eta}\b{eta} experiments.Comment: 16 pages,12 figure

An integrated approach using ozone nanobubble and cyclodextrin inclusion complexation to enhance the removal of micropollutants

Ozone (O3) has been widely used for the elimination of recalcitrant micropollutants in aqueous environments, due to its strong oxidation ability. However, the utilization efficiency of O3 is constrained by its low solubility and short half-life during the treatment process. Herein, an integrated approach, using nanobubble technology and micro-environmental chemistry within cyclodextrin inclusion cavities, was studied in order to enhance the reactivity of ozonisation. Compared with traditional macrobubble aeration with O3 in water, nanobubble aeration achieved 1.7 times higher solubility of O3, and increased the mass transfer coefficient 4.7 times. Moreover, the addition of hydroxypropyl-β-cyclodextrin (HPβCD) further increased the stability of O3 through formation of an inclusion complex in its molecule-specific cavity. At a HPβCD:O3 molar ratio of 10:1, the lifespan of O3 reached 18 times longer than in a HPβCD-free O3 solution. Such approach accelerated the removal efficiency of the model micropollutant, 4-chlorophenol by 6.9 times, compared with conventional macrobubble ozonation. Examination of the HPβCD inclusion complex by UV-visible spectroscopy and Nuclear Magnetic Resonance analyses revealed that both O3 and 4-chlorophenol entered the HPβCD cavity, and Benesi-Hildebrand plots indicated a 1:1 stoichiometry of the host and guest compounds. Additionally, molecular docking simulations were conducted in order to confirm the formation of a ternary complex of HPβCD:4-chlorophenol:O3 and to determine the optimal inclusion mode. With these results, our study highlights the viability of the proposed integrated approach to enhance the ozonation of organic micropollutant

Multi-Agent Deep Reinforcement Learning for Multi-Object Tracker

Multi-object tracking has been a key research subject in many computer vision applications. We propose a novel approach based on multi-agent deep reinforcement learning (MADRL) for multi-object tracking to solve the problems in the existing tracking methods, such as a varying number of targets, non-causal, and non-realtime. At first, we choose YOLO V3 to detect the objects included in each frame. Unsuitable candidates were screened out and the rest of detection results are regarded as multiple agents and forming a multi-agent system. Independent Q-Learners (IQL) is used to learn the agents' policy, in which, each agent treats other agents as part of the environment. Then, we conducted offline learning in the training and online learning during the tracking. Our experiments demonstrate that the use of MADRL achieves better performance than the other state-of-art methods in precision, accuracy, and robustness

Causal relationship between the immune cells and ankylosing spondylitis: univariable, bidirectional, and multivariable Mendelian randomization

BackgroundAnkylosing spondylitis (AS) is an autoimmune disease that affects millions of individuals. Immune cells have been recognized as having a crucial role in the pathogenesis of AS. However, their relationship has not been fully explored.MethodsWe chose to employ Mendelian randomization (MR) to investigate the potential correlation between immune cells and AS. We sourced the data on immune cells from the latest genome-wide association studies (GWASs). We obtained data on AS from the FinnGen consortium. Our comprehensive univariable MR analysis covered 731 immune cells to explore its potential causal relationship with AS. The primary analysis method was inverse-variance weighted (IVW). Additionally, we used Cochran’s Q test and the MR-Egger intercept test to assess the presence of pleiotropy and heterogeneity. We examined whether our results could be influenced by individual single-nucleotide polymorphisms (SNPs) using the leave-one-out test. We conducted a bidirectional MR to investigate the reverse relationship. We also applied multivariable MR to decrease the potential influence between the immune cells.ResultsOverall, our univariable MR analysis revealed eight immune cells associated with AS. Among these, four immune cells contributed to an increased risk of AS, while four immune cells were identified as protective factors for AS. However, the Bonferroni test confirmed only one risk factor and one protective factor with a significance level of p < 6.84E−05. CD8 on effector memory CD8+ T cell could increase the risk of AS (p: 1.2302E−05, OR: 2.9871, 95%CI: 1.8289–4.8786). HLA DR on CD33dim HLA DR+ CD11b+ could decrease the risk of AS (p: 1.2301E−06, OR: 0.5446, 95%CI: 0.4260–0.6962). We also identified a bidirectional relationship between CD4 on CD39+ activated CD4 regulatory T cells and AS utilizing the bidirectional MR. To address potential confounding among immune cells, we employed multivariable MR analysis, which revealed that only one immune cell had an independent effect on AS. HLA DR on CD33dim HLA DR+ CD11b+ could decrease the risk of AS (p: 2.113E−06, OR: 0.0.5423, 95%CI: 0.4210–0.6983). Our findings were consistently stable and reliable.ConclusionsOur findings indicated a potential link between immune cells and AS, which could provide a new idea for future research. Nevertheless, the specific underlying mechanisms require further exploration

Clinical features and surgical outcomes of high grade pleomorphic xanthoastrocytomas: a single-center experience with a systematic review

PurposeHigh grade pleomorphic xanthoastrocytomas (HGPXAs) are very rare and their management and prognostic outcomes remain unclear. To better understand the disease, we aimed to evaluate the risk factors for progression-free survival (PFS) and overall survival (OS), and propose a treatment protocol based on cases from our institute and cases from the literature.MethodsThe authors reviewed the clinical data of 26 patients with HGPXAs who underwent surgical treatment in Department of Neurosurgery of Beijing Tiantan Hospital between August 2014 and September 2021. We also searched the PubMed database using the keywords “anaplastic” combined with “pleomorphic xanthoastrocytoma(s)” between January 1997 and October 2022. Risk factors for PFS and OS were evaluated in the pooled cases.ResultsThe authors’ cohort included 11 males and 15 females with a mean age of 36.7 ± 20.3 years (range: 5.5-71 years). Gross-total resection (GTR) and non-GTR were achieved in 17 (65.4%) and 9 (34.6%) patients, respectively. Radiotherapy and chemotherapy were administered to 22 and 20 patients, respectively. After a mean follow-up of 20.5 ± 21.2 months (range: 0.5-78.1 months), 7 patients suffered tumor recurrence and 6 patients died with a mean OS time of 19.4 ± 10.8 months (range: 8-36 months). In the literature between January 1997 and October 2022, 56 cases of HGPXAs were identified in 29 males and 27 females with a mean age of 29.6 ± 19.6 years (range; 4-74 years). Among them, 24 (44.4%) patients achieved GTR. Radiotherapy and chemotherapy was administered to 31 (62%) patients and 23 (46%) patients, respectively. After a median follow-up of 31.4 ± 35.3 months (range: 0.75-144 months), the mortality and recurrence rates were 32.5% (13/40) and 70% (28/40), respectively. Multivariate Cox regression model demonstrated that non-GTR (HR 0.380, 95% CI 0.174-0.831, p=0.015), age≥30 (HR 2.620, 95% CI 1.183-5.804, p=0.018), no RT (HR 0.334,95% CI 0.150-0.744, p=0.007) and no CT (HR 0.422, 95% CI 0.184-0.967, p=0.042) were negative prognostic factors for PFS. Non-GTR (HR 0.126, 95% CI 0.037-0.422, p=0.001), secondary HGPXAs (HR 7.567, 95% CI 2.221-25.781, p=0.001), age≥30 (HR 3.568, 95% CI 1.190-10.694, p=0.023) and no RT (HR 0.223,95% CI 0.073-0.681, p=0.008) were risk factors for OS.Conclusion:High grade pleomorphic xanthoastrocytomas are very rare brain tumors. Children and younger adults have better clinical outcome than elderly patients. Secondary HGPXAs had worse OS than primary HGPXAs. Complete surgical excision plus RT and CT is recommended for this entity. The frequency of BRAF mutations in HGPXAs is 47.5% (19/40) in this study, however, we do not find the connections between BRAF mutations and clinical outcomes. Future studies with larger cohorts are necessary to verify our findings

Wash waves generated by ship moving across a depth change

Unsteady wash waves generated by a ship with constant speed moving across an uneven bottom topography is investigated by numerical simulations based on a Mixed Euler–Lagrange (MEL) method. The transition is accomplished by the ship traveling from the deep water into shallow water via a step bottom. A small tsunami would be created after this transition. However, the unsteady wave-making resistance induced by this new phenomenon has not been well documented by literature. Therefore, the main purpose of the present study is to quantify the effects of an uneven bottom on the unsteady wash waves and wave-making resistance acting on the ship. An upwind differential scheme is commonly used in the Euler method to deal with the convection terms on free-surface condition to prevent waves in upstream. Evidently, it cannot be applied to the present problem when the ship-generated waves could propagate upstream. A MEL method is therefore employed to investigate the upstream wave generated by the ship moving over the uneven bottom. The central differential scheme provides more accurate results, but it is not unconditionally stable. Simulation results show that the hydrodynamic interaction between the ship and the uneven bottom could initiate an upstream tsunami, as well as unsteady wave-making resistance on ships. The unsteady wave-making resistance oscillates periodically, and the amplitude and period of the oscillations are highly dependent on speed and water depth

A new theoretical calculation of the equilibrium constant and temperature for the carbon isotope exchange reaction between CH4 and CO2

The equilibrium isotope fractionations among C–O–H gases in a variety of geological settings are commonly used as isotope geothermometers to evaluate the temperatures of geothermal fluids at depth, subsurface fluid-rock interactions, volcanic-hydrothermal systems and natural gas pools. However, due to limited experimental data and sophisticated theoretical calculations, applications of these geothermometers have been restricted. This study uses the carbon isotope exchange reaction between CH4 and CO2 as a case study to develop theoretical methods that can improve accuracies in calculating harmonic vibrational frequencies for CH4 and CO2, the equilibrium constants and temperatures for the carbon isotope exchange reaction between CH4 and CO2. Results suggest that the Bigeleisen-Mayer equation is sufficient to calculate the equilibrium constants and temperatures associated with the isotope exchange reaction between CH4 and CO2 with an accurate estimation of molecular harmonic vibrational frequencies. Calculations of the harmonic frequencies of CH4 and CO2 are achieved using the B3LYP density functional method with the 6-311+G(d) basis set, and the calculated harmonic frequencies are highly consistent with experimental values. The frequency correction factor is taken as 1.022 which puts the calculated fractionation factors in good agreement with experimental values. The calculated equilibrium constants are comparable to experimental data and a theoretical data set. They are highly consistent. In order to improve the accuracy and efficiency of solving for equilibrium temperatures using the Bigeleisen-Mayer equation, symbol operation and iterative algorithm in the MatLab software have been applied to compute the temperatures instead of using limited theoretical data sets or empirical fit equations. Our calculated results suggest that this algorithm can rapidly and conveniently yield relatively precise equilibrium temperatures. This algorithm can thus provide an important tool to evaluate whether the carbon isotope exchange reaction for CH4 and CO2 has attained equilibrium and estimate the formation temperature of CH4 and CO2 in high temperature geothermal systems

A new physarum network based genetic algorithm for bandwidth-delay constrained least-cost multicast routing

Bandwidth-delay constrained least-cost multicast routing is a typical NP-complete problem. Although some swarm-based intelligent algorithms (e.g., genetic algorithm (GA)) are proposed to solve this problem, the shortcomings of local search affect the computational effectiveness. Taking the ability of building a robust network of Physarum network model (PN), a new hybrid algorithm, Physarum network-based genetic algorithm (named as PNGA), is proposed in this paper. In PNGA, an updating strategy based on PN is used for improving the crossover operator of traditional GA, in which the same parts of parent chromosomes are reserved and the new offspring by the Physarum network model is generated. In order to estimate the effectiveness of our proposed optimized strategy, some typical genetic algorithms and the proposed PNGA are compared for solving multicast routing. The experiments show that PNGA has more efficient than original GA. More importantly, the PNGA is more robustness that is very important for solving the multicast routing problem