bluuebunny/crossref_metadata_2025_split huggingface dataset:
A re-design process of an industrial centrifugal fan through CFD and rapid prototyping
Authors: Piovan Mattia , Pinelli Michele , Suman Alessio , Zanini Nicola , Magnani Giorgia , Zanardi Andrea 
Published: December 2023

Abstract
Due to the ecological-green transition, it is fundamental to reduce the energy consumption of turbomachines in many fields. In particular, manufacturers of industrial fans are subjected to EU regulation N.327/2011, which indicates the limit for the absorbed power of this kind of machine. New design techniques allow to increase the overall efficiency satisfying the customer’s performance request. Recently, in order to reduce time to market, the manufacturers are very interested in using plastic materials in place of metal in the prototyping phase because they have higher formability, lower costs, and realization time. The aim of the authors is to present the re-design process of a commercial industrial centrifugal fan. The main goal was to change the shape and the number of the blades reducing the separation along the blade-to-blade channel, limiting the leakage flow, and increasing efficiency. Several modifications to the initial geometry were proposed and analyzed through numerical simulations. Three designs were then produced via a rapid prototyping process in plastic material and tested in a standardized rig. Moreover, a comparison between the experimental performances of the actual impeller made in metal sheets and the plastic one will be evaluated in order to view the effects of different roughness and deflation that characterize a plastic component realized using a 3D printing technique.
On the influence of twist and taper of HAWT blades on the rotational augmentation phenomenon: the NREL Phase VI – Phase II comparison
Authors: Mauro Stefano , Lanzafame Rosario , Messina Michele , Brusca Sebastian 
Published: December 2023

Abstract
The physics of 3D flows on rotating blades is currently one of the most important research fields related to wind turbines. Although many authors have studied the phenomenon thoroughly and they have proposed meaningful physical explanation of the mechanism which triggers the onset of the rotational augmentation, a universal correlation between rotor geometry, operating conditions and centrifugal pumping effects has not been derived yet. For instance, all the proposed corrections for rotational stall delay within 1D codes have demonstrated fairly good accuracy but in limited operating range or for specific airfoils or rotor geometries. In the present work the authors applied a consolidated methodology, based on the use of accurate CFD 3D models and of an inverse BEM code, to thoroughly analyze the differences in terms of rotational augmentation effects between the two widely known NREL Phase VI and Phase II HAWTs. This choice was made precisely since both the rotors used the S809 airfoil for the active part of the blade, had equal radial dimensions and the operating conditions were approximately the same. Thus, the substantial difference between the rotors was the fact that the Phase VI blade was twisted and tapered while the Phase II one had constant chord and pitch along the radial direction. In this way, the possible influence due to the twist and taper of the blade on the physics of the centrifugal pumping could be highlighted more easily. The CFD models were developed in Ansys Fluent and validated against experimental measurements available in the literature. The inverse BEM code, already implemented in a previous work, allowed the authors to extrapolate and compare sectional data obtained through the CFD simulations. The post-processing of the results demonstrated the strong influence of the twist and taper of the blade on the dynamics of the rotational augmentation. These results lead the way for a better understanding of the relation between rotor geometry and centrifugal pumping physics.
Design of High Transmission Frequency Circuit for Multiturn Small Loop Transient Electromagnetic Detection
Authors: Yan Fuxue , Sun Yishu , Zhang Yang , Lin Jun 
Published: December 2023

Abstract
Limited by urban road width and other factors, urban TEM detection can only use multiturn small loop as the transmitting coil. The traditional TEM transmitting circuit cannot transmit high frequency repetitive pulse for such large inductance coil. In order to solve this problem, a high transmission frequency circuit is proposed and built in this paper, which can clamp both the rising and falling edges of the emission current, and effectively improve the frequency. The repeated transmission frequency of 250 Hz for 0.73 mH coil at current of 30 A is realized. The circuit effectively improves the strong magnetic field excitation ability, which is of positive significance for the application of multiturn small loop TEM in urban environment.
Research on magnetic gradient method in underground metal pipeline detection
Authors: Wang Shaoqing , Liu Shucai , Qiao Shuai , Jiang Zhihai , Song Lei 
Published: December 2023

Abstract
When the underground metal pipeline is powered by direct current, the magnetic field will be generated around it, and the buried information of the pipeline can be deduced by the change of the magnetic field. Therefore, a method of detecting underground metal pipeline by magnetic gradient is introduced. The mathematical relationship between the magnetic gradient and the buried depth of underground pipeline is derived. The theoretical feasibility of this method is verified by forward simulation, then the physical experiment proves that this method has high detection accuracy.
Influence of Collection Parameters on Lining Detection Results in Comprehensive Wave Field Method
Authors: Wang Yanlong , Yuan Mulin , Hu Xinmin , Xu Dexin 
Published: December 2023

Abstract
For hydraulic tunnel lining detection, a comprehensive wave field method is presented for the detection of hydraulic tunnel lining in this paper, and a 1:1 hydraulic tunnel model is built according to the actual engineering situation. The effects of source, sampling rate, offset and group interval on the detection results are analyzed through experiments, a set of parameters suitable for hydraulic tunnel lining detection is finally derived, which can effectively improve the efficiency and accuracy of lining defect detection in the subsequent work.
Application of Borehole Geophysical Prospecting Method in Pile Foundation Detection of Existing Buildings
Authors: Wang Jianli , Hou Dongmei , Huang Ming 
Published: December 2023

Abstract
It is particularly important to find out the pile foundation of existing buildings for building safety protection and engineering construction safety during the development and utilization of urban underground space. As a non-destructive, efficient and economic method, the borehole geophysical techniques such as magnetic gradient method, ground penetrating radar method and parallel seismic test method are used to detect the pile foundation of existing buildings, which have obvious advantages. According to the combined abnormal characteristics such as "strong magnetic anomaly, electromagnetic wave in-phase axis change and diffraction wave anomaly at the pile end, P-wave velocity variation", the pile foundation length can be judged.
Application of Shallow Reflection Seismic Exploration in The Investigation of Active Faults in Guanzhong Basin
Authors: Li Pei , Li Fengying , Wang Xiaojiang , Zhang Kai , Rong Lixin , Jiang Chunxiang , Wang Tong 
Published: December 2023

Abstract
Active fault detection is an important part of site selection of major projects in urban construction. In order to find out the distribution of active faults in Xixian New District of Guanzhong Basin, high-resolution shallow reflection seismic detection is carried out in the area. The optimal observation system parameters and vibrator excitation parameters are determined through a number of technical tests and the processing parameters are selected in the process of data processing to ensure to obtain high-quality seismic profiles. According to the detection test results, the distribution of the main active faults and the distribution characteristics of underground space in the area are found out, the buried depth of the bottom interface of the Quaternary is inferred and interpreted and the internal strata of the Quaternary are divided in detail.
Experiment on Interference Factors of High-precision Gravity Detection in Urban Underground Space
Authors: Lu Han , Bi Dong , Zhou Mingxia , Sun Hailong , Jiang Hong 
Published: December 2023

Abstract
The traditional geophysical methods in urban underground space detection suffer from many interference factors, and cannot obtain effective detection data. The high-precision gravity method has few interference factors. For human activities and other interference sources, reasonable research work arrangements can be made through preliminary experimental analysis, and these interference factors can be avoided in actual work to obtain effective gravity observation data and interpretation results. The author studies the theoretically affected factors in urban detection and conducts experimental detection and analysis. The high-precision gravity method has a good effect on the detection of urban underground space.
Application of High-density Resistivity Method in Fine Division of Quaternary Geological Structure in the Starting Area of Xiongan New Area
Authors: Guo Shujun , Sun Sheng , Cheng Zhengpu , Wang ChunHui , Xie Xinglong 
Published: December 2023

Abstract
In the starting area of Xiongan New Area, the high-density resistivity method is used for fine detection of the deep-lying strata 0m ∽ 200m in the study area. The stratigraphic and lithologic framework of 0 m-200 m depth has been established. The results show that the middle and Late Pleistocene strata are rich in fine sand, and no hidden ground fissures have occurred. It is proved that the high-density resistivity method is effective and feasible in urban planning and construction geological exploration, and it can provide data support for the further construction of Xiongan New Area.
High Frequency Passive Surface Wave Dispersion Extraction by Linear Seismic Array Aligned with Noise Source Azimuth
Authors: Gao Ji , Zha Huasheng , Zhang Haijiang 
Published: December 2023

Abstract
Due to the uneven spatial and temporal distribution of noise sources, the dispersion data extracted from high-frequency (>1Hz) ambient noise data would be contaminated and biased. Based on the azimuth analysis of the noise sources, we propose a linear array data acquisition strategy that considers the noise source direction to get high quality dispersion data.
Critical Technical Problems of 3D GPR Road Cavity Detection Based on Vast Field Experiment Data Analysis
Authors: Ling Jianyu , Qian Rongyi 
Published: December 2023

Abstract
Utilizing 3D GPR to conduct road cavity detection can well prevent the occurrence of collapse. However, the problems existing in the application of 3D GPR in road cavity detection are not very clear. Hence, we have carried out more than 1000 km road cavity detection work and summarized the main points of data acquisition, processing and interpretation in engineering applications. The main points we found are related to the complexity of the pavement environment and the diversity of above and below ground interference sources, which are difficult to obtain in laboratory experiments. Then the solutions and ideas are put forward, aiming at accelerating the development of 3D GPR cavity detection technology in the field of engineering application.
Void Detection Behind Shield Tunnel Segments Using Ground Penetrating Radar: A Laboratory Experiment
Authors: Lai Sicong , Yue Yunpeng , Meng Xu , Liu Hai 
Published: December 2023

Abstract
As a recognized non-destructive testing (NDT) method, ground penetrating radar (GPR) has been applied for void detection in shield tunnel. However, due to the complex structures of shield segment with double-layer rebar meshes inside, the GPR responses of voids behind shield segment are still not clear. This paper presents a series of laboratory experiments to analyze and characterize the radar responses of voids based on a platform which is composed of two 1:1 scale shield segment. Results preliminarily show that the low-frequency radar signals from the near-segment voids are less obvious than the high-frequency signals. For the voids which are far away from the segment, the radar reflections appear as multi hyperbolas.
A GPR Resolution Enhancement Method Based on Weakly Supervised Learning
Authors: Zhou Mei , Wang Xiaokai , Shi Zhengsheng , Chen Wenchao 
Published: December 2023

Abstract
Ground penetrating radar (GPR) is mainly used to detect underground structures in archaeology, military and other fields. In practice, the detection depth and resolution of GPR data are often difficult to balance. Therefore, it is vital to develop a method that can obtain both deeper distance and higher resolution. In this paper, a weakly supervised method for improving the resolution of GPR data based on the Cycle-Consistent Adversarial Network (Cycle-GAN) is proposed, which improves the quality of GPR data by learning the mapping relation between low-resolution and unpaired high-resolution data. The actual data is used to verify the validity and feasibility of the proposed method. Experimental results have shown that our method is able to recover detailed high-frequency components and the resolution is effectively improved.
Deep Learning Inversion of Multi-processed GPR Data to Characterize Subsurface Defects
Authors: Wang Yuanzhen , Qin Hui , Tang Yu , Zhang Donghao , Zhang Lin , Yao Yao 
Published: December 2023

Abstract
Ground penetrating radar (GPR) is highly recommended for investing defects in concrete structures, yet interpreting GPR data is hindered by the fact that the images primarily display reflected electromagnetic waves rather than the actual shapes of the defects. In this paper, we introduce a deep learning network that aims to convert GPR B-scan images into permittivity maps of subsurface structures. This network takes three types of data as inputs and outputs the distribution of permittivity. These three types of data are the original data, the data obtained after applying migration to the original data, and the data obtained after processing the original data using a neural network. Each type of data is processed using different methods and contains distinct information, which is collectively used for inverting data. In this study, we validate the effectiveness of the proposed network by the finite-difference time-domain (FDTD) forward modeling data.
ES-MDA Method for Inverting SIP Data Based on Cole-cole Model Parameters
Authors: Su Peng , Wang Hui , Huang Zitong , Yang Jin 
Published: December 2023

Abstract
SIP reflects the characteristics of charge storage in underground media. IP parameters such as polarizability and relaxation time are correlated with minerals, pores and other physical properties of rocks, so when establishing the relationship between SIP and other petrophysical parameters, it is necessary to accurately estimate SIP parameters and quantify the uncertainty of estimation. In this paper, the ES-MDA method is used to inverse the synthetic SIP data based on the dual cole-cole model, and the uncertainty of the inversion results is quantified while estimating the parameters. The results show that the ES-MDA method can accurately estimate the SIP parameters, and the sample parameter set of the inversion results has less uncertainty.
Seismic Data Interpolation via Improved cGAN Network
Authors: Huang Zhen , Gao Jianjun , Li Fan , Li Chao Lin 
Published: December 2023

Abstract
The seismic data are always spatially undersampled during filed acquisition, limited by the natural environment and economic conditions. Irregularly missing seismic traces can affect the subsequent processing of seismic data, ultimately impacting the imaging and inversion results. Therefore, seismic data regularisation and interpolation are particularly necessary and have become an important step for data pre-processing. This abstract presents an improved GC algorithm with partial convolution layers and spectral normalization and applies it on 2D seismic data reconstruction. Compared with the traditional cGAN reconstruction method, The proposed method can effectively enhance the generative capability of the cGAN algorithm. Both synthetic and field data experiments demonstrate that the reconstruction performance of the improved cGAN method is better than the conventional cGAN method.
Description of Random Heterogeneity and Characteristic Analysis of Wave Field in Near-surface Medium
Authors: Fan Xiunan , Sun Zhangqing , Han Fuxuan , Wang Ruihu , Liu Yaguan , Lu Jipu , Cen Wenpan , Gao Zhenghui 
Published: December 2023

Abstract
Random heterogeneity of near surface medium is caused by weathering layer, desert and gravel layer etc. For seismic exploration in this complex area, it is helpful to improve the exploration effect that detailed description of this heterogeneity and in-depth analysis the characteristics of seismic wave field in this medium. In order to figure out the above-mentioned issue, firstly, a regional multi-scale disturbance random medium modeling method in complex topographical conditions is proposed to describe the random heterogeneity of near-surface medium. Secondly, in the condition of undulating earth’s surface, the finite difference method (FDM) of wave equation numerical simulation is used to simulate the seismic wave field. Finally, some seismic wave characteristics in near-surface random heterogeneity are obtained by analyzing seismic snapshots and gathers.
Forward Modeling Analysis of Cross-hole Resistivity Tomography (ERT) Using Unstructured Grids
Authors: Cai Yumei , Liu Zhengyu , Dong Zhao , Liu Benchao , Pang Yonghao , Liu Jiawen 
Published: December 2023

Abstract
The cross-hole electrical resistivity tomography (ERT) method has advantages in obtaining deep geological information and can accurately image complex underground structures. However, it is usually difficult to fit complex boundaries using structured grids in the modeling process. The accuracy of forward modeling is affected by the meshing of the model. The unstructured grids may describe the irregular complex model more effectively. Therefore, we study cross-hole ERT forward modeling, using unstructured grids to analyze the forward characteristics of complex underground structures. The effectiveness of the unstructured grids in cross-hole ERT has been revealed in this work.
Application of Non-negative Matrix Factorization in Processing Self-potential Signals Caused by Geo-microbe
Authors: Zhang Lijuan , Cui Yi-An , Luo Yijian , Xie Jing , Guo Youjun 
Published: December 2023

Abstract
Microorganisms play a significant role in the evolutionary process of the Earth and are closely related to the modification and evolution of the Earth’s surface circles at different spatial and temporal scales. Given geological microbiology in the self-potential signal data can be represented with non-negative matrix, which makes use of non-negative matrix factorization method to deal with the data become possible. This paper introduces the basic principle of non-negative matrix factorization method, based on non-negative matrix factorization method is discussed to isolate the self-potential signal data in geological microbes may and effect. By separating two natural potential signals containing noise with blind sources, the separation effect is good and the non-negative matrix factorization method is found to be an effective method for extracting their self-potential signal data. Although this numerical simulation is the self-potential signal is introduced in the work of geological microbiology, but this method also has reference significance for other signal data processing, can also be used to other geophysical data processing, the implementation of the research on environmental protection, to improve the cognitive complex biological geological process of shallow earth environment has important significance.
The Magnetotellurics Inversion with a Tree Based Bayesian Framework
Authors: Tian Shengqi , Guo Rongwen , Yang Gangqiang 
Published: December 2023

Abstract
Bayesian inversion offers a valuable means of estimating uncertainty, allowing us to evaluate the impact of inversion. However, tackling Bayesian inversion in high-dimensional spaces remains a crucial area of research. Building upon Hawkins’ work, we have developed a tree-based Bayesian inversion scheme specifically designed to address the challenges posed by the magnetotellurics inversion problem. By employing the cdf9/7 wavelet as our basis function, we conducted a numerical simulation of a low-resistance abnormal body, yielding highly accurate inversion results.
Assimilating Seismic Data And Soil Basic Information to Predict Near-surface Permeability And Water Content
Authors: Song Zhengyi , Zhang Yu 
Published: December 2023

Abstract
Soil permeability plays a key role in the study of earth sciences for agriculture and forestry. Because the traditional laboratory measurement is time-consuming and laborious, and only discrete profile data can be obtained. In this paper, a simple and efficient method using soil transfer function (PTFs), is proposed to estimate permeability and other parameters indirectly by seismic wave observation. Based on Biot’s theory establishing the relationship between shear-wave velocity and permeability, and the basic soil information in the study area, including land survey, logging and drilling data, using the PTFs constraint to estimate saturated hydraulic conductivity, soil components, saturated water content and residual water content may favor the physical corrections of the PTFs. The results show that there are three distinct layers of permeability in the study area, consistent with the velocity structure. The measured basic information further verifies the accuracy of the saturated permeability coefficient estimation, which shows the reliability of the improved PTFs. The established near surface permeability estimation method by integrating seismic wave observation and soil basic information may provide further assimilation for parameter estimation combining geophysical observation and hydrogeographic statistics.
A Multi-resolution Approach to 3D Controlled-source Electromagnetic Modeling
Authors: Li Jian , Liu Jianxin , Guo Rongwen , Wang Yongfei , Xu Jingdao 
Published: December 2023

Abstract
We have introduced a multi-resolution sampling approach for 3D finite-difference controlled-source electromagnetic forward modeling. Inside this scheme, the discrete operators are constructed based on the original sampling points. At the same time, the algorithm reduces the number of discrete electromagnetic fields instead of the number of cells. To avoid the deterioration of the condition number of the coefficient matrix caused by multiplying by different levels of sparse operators, we introduce a novel technique to optimize the condition number of the coefficient matrix. The results show that the new approach improves computational efficiency without compromising the accuracy of the solution.