bluuebunny/crossref_metadata_2025_split huggingface dataset:
Scale-resolving simulations of the flow in the Francis-99 turbine at part-load condition
Authors: Arabnejad Mohammad Hossein , Nilsson Håkan , Bensow Rickard E. 
Published: October 2022

Abstract
In this paper, we investigate the formation of the Rotating Vortex Rope (RVR) using scale-resolving methods, SAS and Wall-Modeled LES (WMLES). We compare the results from these simulation methods with the experimental data of the Francis-99 workshop. This comparison shows that the general features of the RVR can be captured with both methods. However, using WMLES methods would lead to a better quantitative agreement between the velocity profiles in the draft tube in the simulation and the experiment. The reasons for this better agreement are discussed in detail. A comparison of the pressure fluctuations in the draft tube captured in the simulations and the experiment is also presented. This comparison shows that all simulations under-predict the Root Mean Square (RMS) of these pressure fluctuations, although the RMS values predicted by the WMLES simulation are closer to the experimental values.
Towards accurate vibration prediction of pump-turbine runners in deep partial load operation
Authors: Khalfaoui K , Zorn M , Riedelbauch S 
Published: October 2022

AbstractWithin the XFLEX HYDRO project, operating power plants in low load conditions is being investigated as one of the possibilities to enhance the flexibility of hydropower. Therefore, the structural dynamic behaviour of a pump-turbine runner is numerically analysed in deep partial load (DPL) operating points. Based on highly resolved unsteady CFD simulations performed prior to this work, the pressure fluctuations are extracted and mapped onto the structure for subsequent Finite Element (FE) analyses. Herein, an efficient hybrid methodology combining purely structural and coupled Fluid-Structure-Interaction (FSI) modelling is applied. The obtained simulation results are compared to experimental measurements. Herein, the influence of several factors such as the CFD mesh size, the turbulence model, the simulated time window width, and the structural simulation type is studied. As a result, the numerical outcome is validated with good accuracy. The importance of highly resolved CFD simulations with appropriate turbulence modelling is highlighted. Besides, the necessity of coupled acoustic-structural analyses to accurately resolve the dynamic response to excitation by rotor stator interaction (RSI) pressure shapes is demonstrated despite the chaotically dominated nature of the structural vibrations. The results of this work can be used to extend the operating range of the pump-turbine runner and, most importantly, to calibrate numerical models to predict the structural vibrations accurately and efficiently in DPL and finally ensure safe operation of these components.
Decomposition of the structural response of the Francis-99 runner during resonance.
Authors: Solemslie Bjørn W. , Østby Petter T. , Iliev Igor 
Published: October 2022

Abstract
In this work, the complex structural response of the Francis-99 turbine runner is further investigated by decomposition of the output signal from previous Laser Doppler Vibrometry (LDV) measurements into the motion of each nodal diameter. During the structural measurements, the non-rotating runner was installed in the turbine pit, submerged in a non-flowing water, and excited with piezoelectric patches mounted on the hub. The patches were excited with phase shifted sinusoidal voltage to create overall excitation of the runner with a desired number of nodal diameters. The deflection of selected locations on the trailing edges were scanned with LDV, one point at a time, and the global movement was reconstructed by combining the data for all points.
The Francis-99 runner has its blades bolted to an over-dimensioned hub and shroud, where the hub is not fully axi-symmetrical and has several hollows in it. This, together with the fact that one patch was found to be non-functional, is believed to have excited other ND patterns in addition to the one that was intentionally excited, therefore contaminating the movement of the trailing edges with movements that does not belongs to the excited ND. To mitigate this and create a better representation of the movement of the trailing edge, which is not affected by the bleed from other ND, the LDV signal for each excited frequency of a particular ND is post-processed using discreet Fourier transformation to decompose the motion of each nodal diameter in the range ND0 to ND7. This unveils the contribution of each nodal diameter within the output signal where a spike is seen for the excited ND in all measurements. Influence from other nodal diameters were found, where the failed patched is believed to cause a ND1 like movement. In addition the clustering of multiple eigenmodes with differing nodal diameters previously found in narrow frequency bands were also found as interfering contribution when exciting at the relevant frequencies.
Effect of unbalancing mass placement in hydropower generators with floating rotor rim
Authors: Rondon D , Aidanpää J O , Gustavsson R 
Published: October 2022

Abstract
Dynamic models for hydropower generators treat the rotor part as a rigid body; however, many studies have shown the opposite. The electromagnetic force distribution of deformed rotors is uneven, creating Unbalance Magnetic Pull, causing high forces on generator components leading to a risk of fatigue, therefore shortening the life of machines. Unbalancing masses can worsen the asymmetries of the rotor, which would further increase the effect of the electromagnetic interactions. This paper evaluates the rotor response using different unbalancing masses at the rotor and at the poles to quantify their impact in displacements and exciting frequencies. The model employed in this paper is based on the equation of motion derived using Lagrange equations in both co-rotating and stationary frames of reference, considering the effects of Centrifugal loads, Coriolis, and magnetization of poles. Different unbalancing mass placements affect different variables; extra weights in the poles contribute predominantly to the deformation of the rim, while the unbalance in the shaft affects the position of the shaft; a combination of placements was also studied. The simulations were performed and compared with and without radial electromagnetic forces, showing how the presence of magnetized poles further deforms the shapes of the rotor.
On the topic of added mass and acoustics in High Head Francis Runners
Authors: Østby P. T. K. , Knutsen S. , Billdal J. T. 
Published: October 2022

Abstract
Methods used to calculate the eigenmodes and eigenfrequencies of a Francis runner with the added mass from water are well established and have been verified by several experiments. The common explanation of the water’s role is the added mass it brings to the runners structural eigenmodes and thereby reducing the eigenfrequencies. In this paper we calculate the first eigenfrequency of the runner from the acoustic properties of the runner channel and compare the result with full FEA calculations. Using this method we show that the local speed of sound for the water in the channel can be as low as 200m/s and that the density of the runner is not necessarily an important parameter for the first eigenfrequency with some Nodal Diameters of High Head Runners.
CFD simulations of hydraulic short-circuits in junctions, application to the Grand’Maison power plant
Authors: Decaix J , Drommi J-L , Avellan F , Münch-Alligné C 
Published: October 2022

Abstract
In the framework of the XFLEX HYDRO H2020 European Project, the pumped-storage power plant of Grand’Maison (France), owned by Electricité De France, focuses on the implementation of the hydraulic short-circuit (HSC) operating mode. This mode increases the flexibility in pumping mode, which helps the integration of intermittent energies. Grand’Maison is divided into two power houses: the first features four Pelton turbine units and the second eight reversible pump-turbines units. A trifurcation splits the flow into three penstocks, each is then split into two branches that feed each power house. The HSC operating mode, which consists in operating the pumps and the Pelton turbines simultaneously, changes the flow paths in the junctions compared to the pump mode. The power plant was not designed to operate in HSC mode over a long duration, therefore an assessment of its feasibility is necessary. 151 computational fluid dynamic simulations are carried out for two bifurcations and one trifurcation. The numerical simulation results show that the local head losses in HSC mode represent less than 1% of the gross head. No flow instabilities are observed at the bifurcations contrary to the trifurcation. Additional analyses are required to better understand the flow in the trifurcation.
Water hammer issues in refurbishment of a high-head hydropower plant equipped with Francis turbine
Authors: Bergant A , Ješe U , Mavrič R , Mazij J , Nikolić Z , Karadžić U 
Published: October 2022

Abstract
Refurbishment and upgrading of ageing hydropower plants contribute to increase of renewable energy share in modern electrical grid systems. The potential increase of discharge and flexibility of load variation may result in much higher dynamic loads on both refurbished and non-refurbished plant components during transient operating events. First, water hammer control strategies are outlined including operational scenarios, surge control devices, redesign of the pipeline components, or limitation of operating conditions. Water hammer models and solutions are briefly discussed in the light of their capability, availability and uncertainty. The core of the paper is devoted to investigations of water hammer effects in a high-head hydropower plant Piva, Montenegro which is currently in the final phase of refurbishment. The flow-passage system of the Piva HPP is comprised of the intake structure, followed by three parallel penstocks each with Francis type water turbine at the downstream end. The outlet part starts with three parallel draft tubes that are connected to a common lower orifice-type surge tank followed by tailrace tunnel and outlet structure. Computed and measured results for a selected emergency shut-down (ESD) of one turbine form full-load are compared and discussed. Then the validated computational model is used for simulation of ESDs for a wide operating range.
On the correlation between runner blade dynamic stresses and pressure fluctuations in a prototype Francis turbine
Authors: Favrel Arthur , Nicolle Jonathan , Morissette Jean-François , Giroux Anne-Marie 
Published: October 2022

Abstract
Francis turbines operating in off-design conditions are subject to pressure fluctuations resulting from the development of hydrodynamic instabilities in the draft tube. Depending on the nature of the flow-induced pressure fluctuations (synchronous or convective), this may induce dynamic stresses on the runner blades, increasing fatigue and the risk of crack propagation. This paper proposes to identify the impact of draft tube flow instabilities on the dynamic stresses of Francis turbine runners. Measurements are conducted on a prototype Hydro-Québec Francis turbine from low-load to full-load, including pressure and strain measurements on the stationary and rotating components, respectively. It is first noted that the convective component of the part-load vortex is the main source of excitation for the runner blades. The amplitude of the corresponding dynamic stresses is however reduced at locations closer to the leading edge, for which the dominant fluctuations result from the propagation of synchronous pressure fluctuations. Finally, correlations between runner dynamic stresses and pressure fluctuations measured in water passages are tentatively established for flow instabilities observed at both deep part-load and part-load conditions. This aims to evaluate the feasibility of estimating runner blade dynamic stresses based on signals measured in the stationary components for further investigation.
All-dielectric electromagnetically induced transparency-like metasurface with breaking symmetric
Authors: Shen Zhaoyang , Wang Chengwen , Lu Na 
Published: October 2022

Abstract
We investigate an all-dielectric metasurface to mimic the electromagnetically induced transparency-like phenomenon in the microwave. The unit cell is comprised of two hollow split ring resonators with different parameters, which form an asymmetric structure. The proposed metasurface acquires a high transmission efficiency at 17.17 GHz, which is caused by magnetic resonance. The corresponding physical mechanism is discussed and analyzed by the distributions of the electric and magnetic fields. The experiment result of the transmission spectra is well in agreement with the simulation data. The geometric parameter of hollow split ring resonators has deep influences on transmission spectra which leads to transparency peak variation. Concurrently, the imaginary parts of the effective permittivity and permeability for the proposed metasurface are presented to explain the low-loss property. Furthermore, the transparency peak is sensitive to the surrounding environment, which exhibits potential application in refractive index sensor.
Transportation emissions during pandemic: duality of impacts
Authors: Kontar Wissam , Ahn Soyoung , Hicks Andrea 
Published: October 2022

Abstract
Through the lens of an electric bicycle (E-bike) sharing program, this paper shows how the impact of the pandemic on transportation emissions can be multifaceted by impacting both (i) modal usage and (ii) trip generation. The pandemic led to a decrease in the number of trips by travelers, but it also induced a modal shift away from shared mobility into personalized modes. As a result, estimates of transportation emissions can present conflicting figures. In this work, we collect data on the travel behavior of users of an E-bike sharing program in Madison, Wisconsin, before and during the pandemic. Observations on trip choices and modal shifts of users provide means to estimate their relative and overall impact on transportation emissions. Results suggest that the influence of the pandemic on transportation behavior and environmental emissions is convoluted. Post-pandemic environmental implications would depend on the extent of recovery between modal shares and trip generations.
Ensemble classification based feature selection: a case of identification on plant pentatricopeptide repeat proteins
Authors: Zhao Xudong , Zhai Jingwen , Liu Tong , Wang Guohua 
Published: October 2022

Abstract
In order to identify plant pentatricopeptide repeat (PPR) proteins, a framework of variable selection has been proposed. In fact, it is an effective feature selection strategy that focuses on the performance of classification. Random forest has been used as the classifier with certain variables automatically selected for discrimination between PPR functional and non-functional proteins. However, it is found that samples regarded as PPR functional proteins are wrongly classified in a high rate. In this paper, we plan to improve the framework in order to achieve better classification results. Modifications are made on the framework for better identifying PPR functional proteins. Instead of random forest, a hybrid ensemble classifier is built with its base classifiers derived from six different classification methods. Besides, an incremental strategy and a clustering by search in descending order are alternatively used for feature selection, which can effectively select the most representative variables for identification on PPR proteins. In addition, it can be found that different base classifiers alternately play an important role in the ensemble classifier with feature dimension increasing. The experimental results demonstrate the effectiveness of our improvements.
binny: an automated binning algorithm to recover high-quality genomes from complex metagenomic datasets
Authors: Hickl Oskar , Queirós Pedro , Wilmes Paul , May Patrick , Heintz-Buschart Anna 
Published: October 2022

AbstractThe reconstruction of genomes is a critical step in genome-resolved metagenomics and for multi-omic data integration from microbial communities. Here, we present binny, a binning tool that produces high-quality metagenome-assembled genomes (MAG) from both contiguous and highly fragmented genomes. Based on established metrics, binny outperforms or is highly competitive with commonly used and state-of-the-art binning methods and finds unique genomes that could not be detected by other methods. binny uses k-mer-composition and coverage by metagenomic reads for iterative, nonlinear dimension reduction of genomic signatures as well as subsequent automated contig clustering with cluster assessment using lineage-specific marker gene sets. When compared with seven widely used binning algorithms, binny provides substantial amounts of uniquely identified MAGs and almost always recovers the most near-complete ($\gt 95\%$ pure, $\gt 90\%$ complete) and high-quality ($\gt 90\%$ pure, $\gt 70\%$ complete) genomes from simulated datasets from the Critical Assessment of Metagenome Interpretation initiative, as well as substantially more high-quality draft genomes, as defined by the Minimum Information about a Metagenome-Assembled Genome standard, from a real-world benchmark comprised of metagenomes from various environments than any other tested method.
A universal model of RNA.DNA:DNA triplex formation accurately predicts genome-wide RNA–DNA interactions
Authors: Warwick Timothy , Seredinski Sandra , Krause Nina M , Bains Jasleen Kaur , Althaus Lara , Oo James A , Bonetti Alessandro , Dueck Anne , Engelhardt Stefan , Schwalbe Harald , Leisegang Matthias S , Schulz Marcel H , Brandes Ralf P 
Published: October 2022

Abstract
RNA.DNA:DNA triple helix (triplex) formation is a form of RNA–DNA interaction which regulates gene expression but is difficult to study experimentally in vivo. This makes accurate computational prediction of such interactions highly important in the field of RNA research. Current predictive methods use canonical Hoogsteen base pairing rules, which whilst biophysically valid, may not reflect the plastic nature of cell biology. Here, we present the first optimization approach to learn a probabilistic model describing RNA–DNA interactions directly from motifs derived from triplex sequencing data. We find that there are several stable interaction codes, including Hoogsteen base pairing and novel RNA–DNA base pairings, which agree with in vitro measurements. We implemented these findings in TriplexAligner, a program that uses the determined interaction codes to predict triplex binding. TriplexAligner predicts RNA–DNA interactions identified in all-to-all sequencing data more accurately than all previously published tools in human and mouse and also predicts previously studied triplex interactions with known regulatory functions. We further validated a novel triplex interaction using biophysical experiments. Our work is an important step towards better understanding of triplex formation and allows genome-wide analyses of RNA–DNA interactions.
scGNN 2.0: a graph neural network tool for imputation and clustering of single-cell RNA-Seq data
Authors: Gu Haocheng , Cheng Hao , Ma Anjun , Li Yang , Wang Juexin , Xu Dong , Ma Qin 
Published: October 2022

Abstract

Motivation
Gene expression imputation has been an essential step of the single-cell RNA-Seq data analysis workflow. Among several deep-learning methods, the debut of scGNN gained substantial recognition in 2021 for its superior performance and the ability to produce a cell–cell graph. However, the implementation of scGNN was relatively time-consuming and its performance could still be optimized.

Results
The implementation of scGNN 2.0 is significantly faster than scGNN thanks to a simplified close-loop architecture. For all eight datasets, cell clustering performance was increased by 85.02% on average in terms of adjusted rand index, and the imputation Median L1 Error was reduced by 67.94% on average. With the built-in visualizations, users can quickly assess the imputation and cell clustering results, compare against benchmarks and interpret the cell–cell interaction. The expanded input and output formats also pave the way for custom workflows that integrate scGNN 2.0 with other scRNA-Seq toolkits on both Python and R platforms.

Availability and implementation
scGNN 2.0 is implemented in Python (as of version 3.8) with the source code available at https://github.com/OSU-BMBL/scGNN2.0.

Supplementary information
Supplementary data are available at Bioinformatics online.
An enChIP system for the analysis of genome functions in budding yeast
Authors: Fujii Hodaka , Fujita Toshitsugu 
Published: October 2022

Abstract
The identification of molecules associated with a specific genomic region is essential for elucidating the molecular mechanisms underlying genome functions such as transcription. Engineered DNA-binding molecule-mediated chromatin immunoprecipitation (enChIP) is a technology that enables the purification of specific genomic regions and the subsequent identification of their associated molecules. In enChIP, the target genomic region is tagged with engineered DNA-binding molecules, such as variants of the clustered regularly interspaced short palindromic repeats (CRISPR) system consisting of a catalytically inactive form of Cas9 (dCas9) and a guide RNA. This article describes the generation of a plasmid expressing Streptococcus pyogenes dCas9 fused to a 3xFLAG-tag (3xFLAG-Sp-dCas9) and its successful expression in the budding yeast, Saccharomyces cerevisiae. Furthermore, we showed that this plasmid can be used for enChIP analysis in budding yeast. In addition, the plasmid may also be a useful tool for researchers analyzing genome functions such as transcription and for CRISPR interference experiments in budding yeasts.
Transcriptomic and connectomic correlates of differential spatial patterning among gliomas
Authors: Romero-Garcia Rafael , Mandal Ayan S , Bethlehem Richard A I , Crespo-Facorro Benedicto , Hart Michael G , Suckling John 
Published: October 2022

AbstractUnravelling the complex events driving grade-specific spatial distribution of brain tumour occurrence requires rich datasets from both healthy individuals and patients. Here, we combined open-access data from The Cancer Genome Atlas, the UK Biobank and the Allen Brain Human Atlas to disentangle how the different spatial occurrences of glioblastoma multiforme and low-grade gliomas are linked to brain network features and the normative transcriptional profiles of brain regions.From MRI of brain tumour patients, we first constructed a grade-related frequency map of the regional occurrence of low-grade gliomas and the more aggressive glioblastoma multiforme. Using associated mRNA transcription data, we derived a set of differential gene expressions from glioblastoma multiforme and low-grade gliomas tissues of the same patients. By combining the resulting values with normative gene expressions from post-mortem brain tissue, we constructed a grade-related expression map indicating which brain regions express genes dysregulated in aggressive gliomas. Additionally, we derived an expression map of genes previously associated with tumour subtypes in a genome-wide association study (tumour-related genes).There were significant associations between grade-related frequency, grade-related expression and tumour-related expression maps, as well as functional brain network features (specifically, nodal strength and participation coefficient) that are implicated in neurological and psychiatric disorders.These findings identify brain network dynamics and transcriptomic signatures as key factors in regional vulnerability for glioblastoma multiforme and low-grade glioma occurrence, placing primary brain tumours within a well established framework of neurological and psychiatric cortical alterations.