bluuebunny/crossref_metadata_2025_split huggingface dataset:
On the role of density fluctuations in the core turbulent transport of Wendelstein 7-X
Authors: Carralero D , Estrada T , Maragkoudakis E , Windisch T , Alonso J A , Velasco J L , Ford O , Jakubowski M , Lazerson S , Beurskens M , Bozhenkov S , Calvo I , Damm H , Fuchert G , García-Regaña J M , Höfel U , Marushchenko N , Pablant N , Sánchez E , Smith H M , Pasch E , Stange T 
Published: January 2022

Abstract
A recent characterization of core turbulence carried out with a Doppler reflectometer in the optimized stellarator Wendelstein 7-X (W7-X) found that discharges achieving high ion temperatures at the core featured an ITG-like suppression of density fluctuations driven by a reduction of the gradient ratio

η
i

=

L
n

/

L

T
i

(Carralero et al 2021 Nucl. Fusion
61 096015). In order to confirm the role of ITG turbulence in this process, we set out to establish experimentally the relation between core density fluctuations, turbulent heat flux and global confinement. With this aim, we consider the scenarios found in the previous work and carry out power balance analysis for a number of representative ones, including some featuring high ion temperature. We also evaluate the global energy confinement time and discuss it in the context of the ISS04 inter-stellarator scaling. We find that when turbulence is suppressed as a result of a reduction of η

i
, there is a reduction of ion turbulent transport, and global performance is improved as a result. This is consistent with ITG turbulence limiting the ion temperature at the core of W7-X. In contrast, when turbulence is reduced following a decrease in collisionality, no changes are observed in transport or confinement. This could be explained by ITG modes being combined with TEM turbulence when the latter is destabilized at low collisionalities.
Benchmark experiments of the power law parametrization of the effective ion collecting area of a planar Langmuir probe in low temperature plasmas
Authors: Lim Yegeon , Severn Greg , Yip Chi-Shung , Ghim Y-c 
Published: January 2022

Abstract
For unmagnetized low temperature Ar plasmas with plasma density ranging from 3 × 108 to 1010 cm−3 and an electron temperature of ∼1 eV, the expansion of the ion collecting area of a double-sided planar Langmuir probe with respect to probe bias is experimentally investigated, through a systematic scan of plasma parameters. In accordance with many existing numerical studies, the ion collecting area is found to follow a power law for a sufficiently negative probe bias. Within our experimental conditions, the power law coefficient and exponent have been parameterized as a function of the normalized probe radius and compared with numerical results where qualitatively comparable features are identified. However, numerical results underestimate the power law coefficient while the exponent is overestimated. Our experimental measurements also confirm that ion–neutral collisions play a role in determining the expanded ion collecting area, thus changing values of the power law coefficient and exponent. This work suggests that a power law fit to the ion collecting area must be performed solely based on experimentally obtained data rather than using empirical formulae from simulation results since material and cleanness of the probe, type of working gas, and neutral pressure may also affect the expansion of the ion collecting area, factors which are difficult to model in a numerical simulation. A proper scheme of analyzing an I–V characteristic of a Langmuir probe based on a power law fit is also presented.
Synthesis, structural, optical, and electrical properties of continuous wave and pulse laser sintered semiconductor Ge films
Authors: Islam Md Toriqul , Gupta Mool C 
Published: January 2022

Abstract
The crystallization process of Ge films by a continuous wave (CW) and a pulsed laser is very effective for producing smooth, homogeneous, and crack-free polycrystalline films to use in transistors, photodetectors, and photovoltaic applications. However, little progress has been made to directly crystallize Ge films based on micro/nanoparticles (NPs) using the laser sintering (LS) process. In this paper, a simultaneous LS and crystallization process of Ge micro/NPs to develop thick polycrystalline films on silicon substrates is demonstrated. Silicon substrates with a SiO2 insulating layer on top were considered for compatibility with complementary metal–oxide–semiconductor (CMOS) technology. The LS process was applied to solution deposited micro/NPs, 5 µm thick Ge films using both CW mode (infrared laser of wavelength 1070 nm) and pulse mode (UV laser of wavelength 355 nm) laser. After the LS process, around 2–2.5 µm thick film of polycrystalline Ge (pc-Ge) was achieved with optical and electrical properties comparable to traditionally developed chemical vapor deposited films. The crystallinity of the pc-Ge films was evaluated by Raman spectroscopy and x-ray diffraction (XRD). The laser-sintered films exhibited a Raman peak at 300 cm−1 and XRD 2θ peak at 27.35, which indicated the poly-crystalline structure. The fabricated film showed high hole mobility of 203 cm2 V−1 s−1, without any doping and film electrical resistivity value of 6.24 × 105 Ω-cm. The developed LS process allows the quick deposition of polycrystalline thick films, removing surface porosity and voids, increasing films adhesion with the substrate, and faster thermal annealing.
SuperMind: a survey of the potential of superconducting electronics for neuromorphic computing
Authors: Schneider Michael , Toomey Emily , Rowlands Graham , Shainline Jeff , Tschirhart Paul , Segall Ken 
Published: January 2022

Abstract
Neuromorphic computing is a broad field that uses biological inspiration to address computing design. It is being pursued in many hardware technologies, both novel and conventional. We discuss the use of superconductive electronics for neuromorphic computing and why they are a compelling technology for the design of neuromorphic computing systems. One example is the natural spiking behavior of Josephson junctions and the ability to transmit short voltage spikes without the resistive capacitive time constants that typically hinder spike-based computing. We review the work that has been done on biologically inspired superconductive devices, circuits, and architectures and discuss the scaling potential of these demonstrations.
Analytic correlation of inflationary potential to power spectrum shape: limits of validity, and `no-go' for small field model analytics
Authors: Wolfson Ira 
Published: January 2022

Abstract
The primordial power spectrum informs the possible inflationary histories of our universe. Given a power spectrum, the ensuing cosmic microwave background is calculated and compared to the observed one. Thus, one focus of modern cosmology is building well-motivated inflationary models that predict the primordial power spectrum observables. The common practice uses analytic terms for the scalar spectral index ns and the index running α, forgoing the effort required to evaluate the model numerically. However, the validity of these terms has never been rigorously probed and relies on perturbative methods, which may lose their efficacy for large perturbations. The requirement for more accurate theoretical predictions becomes crucial with the advent of highly sensitive measuring instruments. This paper probes the limits of the perturbative treatment that connects inflationary potential parameters to primordial power spectrum observables. We show that the validity of analytic approximations of the scalar index roughly respects the large-field/small-field dichotomy. We supply an easily calculated measure for relative perturbation amplitude and show that, for large field models, the validity of analytical terms extends to ∼ 3% perturbation relative to a power-law inflation model.
Conversely, the analytical treatment loses its validity for small field models with as little as 0.1% perturbation relative to the small-field test-case. By employing the most general artificial neural networks and multinomial functions up to the twentieth degree and demonstrating their shortcomings, we show that no reasonable and universal analytic expressions correlating small field models to the observables they yield exists.
Finally, we discuss the possible implications of this work and supply the validity heuristic for large and small field models.
Estimation of H ii Bubble Size Distribution from 21 cm Power Spectrum with Artificial Neural Networks
Authors: Shimabukuro Hayato , Mao Yi , Tan Jianrong 
Published: January 2022

Abstract
The bubble size distribution of ionized hydrogen regions probes information about the morphology of H II bubbles during reionization. Conventionally, the H II bubble size distribution can be derived from the tomographic imaging data of the redshifted 21 cm signal from the epoch of reionization, which, however, is observationally challenging even for upcoming large radio interferometer arrays. Given that these interferometers promise to measure the 21 cm power spectrum accurately, we propose a new method, which is based on artificial neural networks, to reconstruct the H II bubble size distribution from the 21 cm power spectrum. We demonstrate that reconstruction from the 21 cm power spectrum can be almost as accurate as being directly measured from the imaging data with fractional error ≲10%, even with thermal noise at the sensitivity level of the Square Kilometre Array. Nevertheless, the reconstruction implicitly exploits the modeling in reionization simulations, and hence the recovered H II bubble size distribution is not an independent summary statistic from the power spectrum, and should be used only as an indicator for understanding H II bubble morphology and its evolution.
Validation of edge turbulence codes against the TCV-X21 diverted L-mode reference case
Authors: Oliveira D.S. , Body T. , Galassi D. , Theiler C. , Laribi E. , Tamain P. , Stegmeir A. , Giacomin M. , Zholobenko W. , Ricci P. , Bufferand H. , Boedo J.A. , Ciraolo G. , Colandrea C. , Coster D. , de Oliveira H. , Fourestey G. , Gorno S. , Imbeaux F. , Jenko F. , Naulin V. , Offeddu N. , Reimerdes H. , Serre E. , Tsui C.K. , Varini N. , Vianello N. , Wiesenberger M. , Wüthrich C. , the TCV Team  
Published: January 2022

Abstract
Self-consistent full-size turbulent-transport simulations of the divertor and scrape-off-layer (SOL) of existing tokamaks have recently become feasible. This enables the direct comparison of turbulence simulations against experimental measurements. In this work, we perform a series of diverted ohmic L-mode discharges on the tokamak à configuration variable (TCV) tokamak, building a first-of-a-kind dataset for the validation of edge turbulence models. This dataset, referred to as TCV-X21, contains measurements from five diagnostic systems from the outboard midplane (OMP) to the divertor targets—giving a total of 45 one- and two-dimensional comparison observables in two toroidal magnetic field directions. The experimental dataset is used to validate three flux-driven 3D fluid-turbulence models—GBS, GRILLIX and TOKAM3X. With each model, we perform simulations of the TCV-X21 scenario, individually tuning the particle and power source rates to achieve a reasonable match of the upstream separatrix value of density and electron temperature. We find that the simulations match the experimental profiles for most observables at the OMP—both in terms of profile shape and absolute magnitude—while a comparatively poorer agreement is found towards the divertor targets. The match between simulation and experiment is seen to be sensitive to the value of the resistivity, the heat conductivities, the power injection rate and the choice of sheath boundary conditions. Additionally, despite targeting a sheath-limited regime, the discrepancy between simulations and experiment also suggests that the neutral dynamics should be included. The results of this validation show that turbulence models are able to perform simulations of existing devices and achieve reasonable agreement with experimental measurements. Where disagreement is found, the validation helps to identify how the models can be improved. By publicly releasing the experimental dataset and validation analysis, this work should help to guide and accelerate the development of predictive turbulence simulations of the edge and SOL.
Induced stalled flow due to roughness sensitivity for thick airfoils in modern wind turbines
Authors: Gutiérrez R , Llorente E , Ragni D 
Published: January 2022

Abstract
The mid-span region of wind turbine blades can be thickened to fulfil the structural requirements of the blade. Hence, thick airfoils, that were designed to operate at the root region of the blade, are moved to the mid-span region. This could not imply remarkable variations of the blade performance once its surface is smooth. However, the sensitivity of thick airfoils to roughness could cause significant aerodynamic impacts such as flow separation. This research aims to quantify the impact of the blade thickness, under smooth and rough conditions, in the annual energy production and the fatigue loads of the blade. Ten blade designs, linearly interpolated in thickness, are studied employing aero-elastic computations. The results reveal that the thickest blade increases the annual energy production by 5% with respect to the thinnest blade under rough conditions. Whereas this increase is less than 1% under smooth conditions. The loss of annual energy production varies with the blade thickness linearly for thin blades while it varies exponentially for thick blades up to 22%. Fatigue loads assessment confirmed a reduction of the damage equivalent load under smooth conditions, whereas the thickest blade increased it 28% under rough conditions.
Transferability of site-dependent wind turbine performance predictions using machine learning
Authors: Hammer Florian , Barber Sarah 
Published: January 2022

Abstract
Within this work, machine learning models of site-specific machine learning models of wind turbine power curves of the Beberibe Wind Farm in Brazil, which consists of 32 turbines and one met mast, were developed. Previous work already showed that machine learning models taking into account site-specific effects can increase power prediction accuracy of single wind turbines by a factor of three compared to the standard power curve binning method. The main goal was to investigate the transferability of these models through power output predictions of various turbines depending on the distance from the met mast. It was found that transferring models within a wind farm is possible, but a decrease of prediction accuracy by up to 30% in certain cases could be observed. Neither the combination of various turbine data, nor the incorporation of site-specific data had an apparent effect on the transferability performance. It was thus concluded that a further investigation is needed, where a larger and more distributed subset of turbines should be used.
Calculated estimations of the performance for TKX-50 based formulations
Authors: Golubev V K , Klapötke T M 
Published: January 2022

Abstract
A computational study of the detonation characteristics of several explosive formulationsbased on the energetic material TKX-50 has been carried out. Materials such as paraffin, HTPB, GAP, AMMO and BAMO were considered as fillers or binders. The influence of such fillers (with a volumetric content of up to 50 %) on the detonation characteristics of the composite energetic materials was investigated. The influence of porosity on the detonation characteristics of composite explosive formulations with a binder mass content of 5 and 10% was determined. An analysis of the (limited) experimental data for the detonation velocity of explosive formulations based on TKX-50 was undertaken. The experimentally determined detonation velocities of three explosive formulations with inert and energetic binders which have been previously published in the literature were considered and analysed. Good agreement was found between the calculated and experimental results for the detonation velocity. A computational study of the explosion impact of charges of TKX-50, as well as of explosive formulations based on it containing the above-mentioned binders, on copper plates with a thickness of 1 mm and on layers with a thickness of 50 mm was carried out. The mass content of binders in the explosive formulations was 5 %. The charges were 50 mm thick and consisted of compact or porous materials with a porosity of 2 %. The Explo5 and Ansys Autodyn programs were used to perform thermochemical, thermodynamic and gas-dynamic calculations.
Equation of state for iridium at high pressures
Authors: Khishchenko K V 
Published: January 2022

Abstract
An equation of state for iridium is proposed in a wide range of density and internal energies. The results of calculations using this equation of state are compared with the available experimental data for this metal at high pressures. The proposed equation of state can beused to simulate adiabatic processes in iridium under shock-wave loading.
Double-K Differential Protection Principle of Regional Power Grid Based on Voltage Vector Compensation
Authors: Gao Meijin , Zhu Yanhan , Zhang Xiao , Fang Xinyan 
Published: January 2022

Abstract
In the regional active distribution network where the Distributed Generation (DG) penetration rate is getting higher and higher. When a high-resistance ground fault occurs in a heavy-load line, the traditional current differential protection has very low sensitivity, the protection may refuse to act. And the power differential protection has the voltage dead zone. In addition, the T-type branch will further reduce the sensitivity of the traditional differential protection. In order to solve the problems, this paper proposes a new principle of double-K differential protection with voltage vector compensation. The principle can flexibly adjust the braking zone range by setting two parameters, and then introduce the voltage vector to compensate the operating point, which effectively improves the protection sensitivity in the case of high-resistance ground fault occurs in a heavy-load line, and there is no voltage dead zone. Simulation shows that the principle can greatly improve the reliability of protection.
Research of Integrated Non-stop Operation Based on Emergency Power Supply Vehicle
Authors: Qian Zhong , Liu Yongqi , Dong Zhiwen , Fan Zihui , Gao Lingxiao , Wu Zijing 
Published: January 2022

Abstract
As the speed of social and economic development accelerates, the demand for reliability of power supply rises gradually in various industries. As an important method of power supply, the emergency power supply vehicle can effectively ensure the smooth implementation of comprehensive non-stop operation. In view of the existing multi-scene integrated non-stop operation methods, the integrated non-stop operation based on emergency power supply vehicle is systematized and modularized, and the integrated non-stop operation management platform based on emergency power supply vehicles is established to further improve the technical system of non-stop operation in the power industry.
Research on Adaptive Dynamic Access Control Model Based on Blockchain and Token
Authors: Yang Ke , Li Da , Zhou Lei , Cheng Kai 
Published: January 2022

Abstract
The new power system presents new features such as massive, decentralized, multiple types of equipment and user access, more complex interactions, and faster response speed. The zero-trust security model still has problems such as the single-point failure risk of permission control and the inability to balance dynamic fine-grained permission adjustment and real-time response. Based on this, this paper proposes an adaptive dynamic access control model based on blockchain and token. First, build a decentralized authorization management architecture based on blockchain smart contracts to provide users with reliable and intelligent authorization services. Secondly, an authorization technology based on short-term tokens is proposed, which realizes adaptive dynamic access authority adjustment through user trust evaluation and smart contract automatic discrimination. Finally, an intelligent identity authentication mechanism based on user behavior data analysis is designed to support the adaptive update of tokens. Experiments have verified that this model has certain advantages in accurate and adaptive dynamic authorization, which can provide a reference for the improvement of the zero-trust model.
Design of Virtual Power Plant System Model under Master-Slave Multi-chain
Authors: Xue Qingshui , Xue Zhen , Ma Haifeng , Sun Yue , Shi Xuelei 
Published: January 2022

Abstract
The emergence and development of new technology provides a new way of thinking for solving the problems in the traditional energy industry. Introducing block chain technology into virtual power plant can solve the problems existing in virtual power plant such as. to improve the safety, reliability and operation efficiency of virtual power plant. At present, the research on the application of block chain technology in virtual power plants is mostly based on single-chain structure, which makes the system not extensible. Based on this problem, a virtual power plant model with main and multi-chain structure is presented, which improves the scalability of virtual power plant with block chain technology. The use of block chain technology improves the security and fairness of power transactions. It can allocate power more efficiently to improve energy utilization.
Risk Assessment Method of Multi-station Integration Based on Neural Network
Authors: Li Jianlin , Wang Sijia , Wu Yiwen , Zeng Wei , Li Yaxin 
Published: January 2022

Abstract
In recent years, the safety risk assessment of integrated power station systems has become more important as more and more substations optimize the overall operating effect by increasing energy storage power stations. In this paper, after using the expanded Kalman filtering algorithm, the risk assessment model of the fusion power station is established by the neural network-based method to provide a reference for the engineering construction.
Study on the Impact of Renewable Energy Power Generation Transient Characteristics on System Stability in Weak Grid
Authors: Shen Xuhui , Tang Haiyan , He Weiguo , Wang Hongce , Li Yan , Li Dongqi , Yu Xiaoqing , He Fei , Yuan Qiujie 
Published: January 2022

Abstract
With the large-mount access of renewable energy to the electric power grid, the unique seasonal and day and night output fluctuation of renewable energy power generation has brought new challenges to the stable and safe operation of the power system. These challenges mainly include the impact on power grid voltage stability, frequency stability and power angle stability. Therefore, the impact of renewable energy power generation on the stable and safe operation of power system should be be paid enough attention. Due to the characteristics of long-distance, large-scale and high concentration of grid connected renewable energy, the ability of AC system to connect to power grid is relatively weak, which is a typical weak current network. With the continuous expansion of renewable energy grid connection scale, the dynamic characteristics of weak current power grid become more complex, which brings great challenges to the stability and security of power grid. However, in the calculation of power system security and stability, more conservative renewable energy generation model parameters are often used to fix the power grid operation reliability. For better improve the renewable energy acceptance capacity of the system, the proportion of renewable power generation will be further increased. Therefore, establishing an accurate and reasonable renewable energy model is the basis of large-scale renewable energy grid connection security and stability calculation. Further study on the control strategy and parameter adaptability of renewable energy model could be reduced stability risk of high proportion of renewable energy connected to weak current network.