High-precision Data Research Articles

Assessment of Chinese urban land-use efficiency (SDG11.3.1) utilizing high-precision urban built-up area data

Assessment of SDG11.3.1 indicator of the United Nations Sustainable Development Goals (SDGs) is a valuable tool for policymakers in urban planning. This study aims to enhance the accuracy of the SDG11.3.1 evaluation and explore the impact of varying precision levels in urban built-up area on the indicator's assessment outcomes. We developed an algorithm to generate accurate urban built-up area data products based on China's Geographical Condition Monitoring data with a 2 m resolution. The study evaluates urban land-use efficiency in China from 2015 to 2020 across different geographical units using both the research product and data derived from other studies utilizing medium and low-resolution imagery. The results indicate: (1) A significant improvement in the accuracy of our urban built-up area data, with the SDG11.3.1 evaluation results demonstrating a more precise reflection of spatiotemporal characteristics. The indicator shows a positive correlation with the accuracy level of the built-up area data; (2) From 2015 to 2020, Chinese prefecture-level cities have undergone faster urbanization in terms of land expansion relative to population growth, leading to less optimal land resource utilization. Only in extra-large cities does urban population growth show a relatively balanced pattern. However, urban population growth in other regions and cities of various sizes lags behind land urbanization. Notably, Northeast China and small to medium cities encounter significant challenges in urban population growth. Our comprehensive framework for evaluating SDG11.3.1 with high-precision urban built-up area data can be adapted to different national regions, yielding more accurate SDG11.3.1 outcomes. Our urban area and built-up area data products provide crucial inputs for calculating at least four indicators related to SDG11.

On the Determination of Stellar Mass and Binary Fraction of Open Clusters within 500 pc from the Sun

We investigated the stellar mass function and the binary fraction of 114 nearby open clusters (OCs) using the high-precision photometric data from Gaia Data Release 3 (Gaia DR3). We estimated the mass of member stars by using a ridge line that is better in line with the observed color–magnitude diagram, thus obtaining more accurate stellar mass and binary mass ratio (q) at the low-mass region. By analyzing the present-day mass function (PDMF) of star clusters, we found that 108 OCs follow a two-stage power-law distribution, whereas six OCs present a single power-law PDMF. Subsequently, we fitted the high(low)-mass index of PDMF ( dN/dm∝m−α ), denoted as α h(α l), and segmentation point m c. For our cluster sample, the median values of α h and α l are 2.65 and 0.95, respectively, which are approximately consistent with the initial mass function results provided by Kroupa. We utilized the cumulative radial number distribution of stars with different masses to quantify the degree of mass segregation. We found a significant positive correlation between the state of dynamical evolution and mass segregation in OCs. We also estimated the fraction of binary stars with q ≥ 0.5, ranging from 6% to 34% with a median of 17%. Finally, we provided a catalog of 114 nearby cluster properties, including the total mass, the binary fraction, the PDMF, and the dynamical state.

Traffic conflict analysis in continuous confluence area of cross-river bridge driven by vehicle trajectory data

Objectives To conduct an in-depth study on the spatial distribution of traffic conflicts in the continuous merging areas of cross-river bridges and ensure public transportation safety. Methods First, we utilized drone aerial photography to collect videos of vehicle movements. Using the YOLOv7 object detection algorithm and the Strong SORT multi-object tracking algorithm, we extracted high-precision vehicle trajectory time-series data. Next, based on the motion characteristics of traffic entities, we proposed using Deceleration Rate (DR) to describe rear-end conflicts and Lane Change Speed (LCS) to describe lane-changing conflicts. Additionally, we employed the K-means clustering method to determine the threshold values for minor, moderate, and severe levels of rear-end and lane-changing conflicts. Finally, based on the obtained trajectory data, the values of traffic conflicts are calculated and their severity is classified. A heat map of the spatial distribution of vehicle conflicts in continuous merging zones is then created to study the spatial distribution patterns of traffic conflicts. Results The threshold values for minor, moderate, and severe levels of rear-end conflicts are determined to be 3.06 m/s2, 5.36 m/s2, and 8.04 m/s2, respectively. For lane-changing conflicts, the thresholds are 1.13 m/s, 2.07 m/s, and 3.45 m/s. The spatial distribution of traffic conflicts exhibits a “first increase, then decrease, and then increase again” trend. Conclusions The study identifies the critical areas of traffic conflicts in the continuous merging zones of cross-river bridges. The research results provide a novel approach for acquiring traffic data in these areas and offer a reliable quantitative method for assessing safety risks on these road segments. This provides a theoretical basis for proposing targeted traffic safety management strategies.

Numerical simulation for large baseline interferometric imaging altimeter

Sea topography information holds significant importance in oceanic research and the climate change detection. Radar imaging altimetry has emerged as the leading approach for global ocean observation, employing synthetic aperture radar (SAR) interferometry to enhance the spatial resolution of Sea topography. Nevertheless, current payload capacity and satellite hardware limitations prevent the extension of the interferometric baseline by enlarging the physical antenna size. This constraint hinders achieving centimeter-level accuracy in interferometric altimetry. To address this challenge, we conducted a numerical simulation to assess the viability of a large baseline interferometric imaging altimeter (LB-IIA). By controlling the baseline within the range of 600–1000 m through spiral orbit design in two satellites and mitigating baseline de-correlation with the carrier frequency shift (CFS) technique, we aimed to overcome the above limitations. Our findings demonstrate the efficacy of the CFS technique in compensating for baseline decoherence, elevating coherence from less than 0.1 to over 0.85. Concurrently. The height difference accuracy between neighboring sea surfaces reaches 1 cm within a 1 km resolution. This study is anticipated to serve as a foundational reference for future interferometric imaging altimeter development, catering to the demand for high-precision sea topography data in accurate global bathymetry inversion.

FPGA-based cesium optical pump magnetometer data recording system design

Abstract A cesium optical pump magnetometer is a kind of magnetic detection instrument commonly used in geophysical and military fields, which has significant advantages such as high sensitivity, insensitivity to attitude change, and no zero drift. Compared with manned aircraft, rotary-wing UAVs have the advantages of flexible takeoff and landing, low cost, and suitability for small measurement areas, so the aeromagnetic system based on the integration of rotary-wing UAV platforms and cesium optical pump magnetometers has a strong practical value. This paper investigates an FPGA-based CS-3 cesium optical pump magnetometer with a high-precision magnetic field data recording system for building a miniaturized aeromagnetic measurement system based on a rotary-wing unmanned aerial vehicle (UAV) platform, and the system achieves a magnetic field measurement accuracy of 3.4 pT.

Research on calibration method for measurement error of multiple rate carrier energy meter

Abstract With the rapid development of smart grid technology, the multi-rate carrier watt-hour meter is an important measurement tool in power systems; its accuracy directly affects economic benefits and energy management efficiency. This paper proposes a calibration method of measurement error for a multi-rate carrier watt-hour meter to improve the measurement accuracy and reliability of the watt-hour meter under changing load conditions. The multi-rate carrier energy data is collected in real-time by high-precision data acquisition equipment to ensure the comprehensiveness and accuracy of the data. Using advanced data analysis technology to extract the amplitude characteristics of abnormal metering data, on this basis, the output deviation of equipment without input signal is eliminated, and the metering error calibration of the electric energy meter is completed. The experimental results show that this method can significantly improve the metering accuracy of multi-rate carrier watt-hour meters under different power consumption conditions and has good adaptability and practical value.

Elimination of Exogenous Pollution Influence on the Microelement Composition of Medicinal Plants

INTRODUCTION. The compendial analytical procedure for determining the content of heavy metals and arsenic impurities in herbal drugs does not differentiate between endogenous and exogenous elemental impurities. Higher-precision data on the microelement composition of plants, particularly data on endogenous and exogenous impurities, could be instrumental in chemosystematics and in the identification of raw materials.AIM. This study aimed to modify the analytical procedure for quantifying macro- and microelements in herbal drugs with the intention to eliminate the influence of exogenous pollutants on test results.MATERIALS AND METHODS. The study focused on herbal drugs from the Boraginaceae family, including reproductive shoots of lungwort (Pulmonaria mollis Wulf. ex Hornem) and leaves of common borage (Borago officinalis L.). A portion was spiked with elemental pollutants. All herbal drugs were ground and fractionated by sieving. Quantitative determination was performed by inductively coupled plasma mass spectrometry. Statistical analysis of the results used Microsoft Excel and Statistica 8 software.RESULTS. A total of 30 elements were quantified in 9 fractions of herbal drugs with different particle sizes. Cluster analysis showed that unfractionated herbal drugs and the fraction comprising particles smaller than 0.2 mm formed sepa rate clusters, indicating significant differences in elemental compositions. Grubbs’ test confirmed that these two samples were significantly different from the others. The fraction of particles smaller than 0.2 mm had the maximum content of the spiked elements; more than 90% of the spiked amounts were recovered from this fraction. The high content of elements observed in unfractionated herbal drugs was due to the plant parts that would have passed the 0.2 mm sieve had they been ground and fractionated.CONCLUSIONS. The use of unfractionated herbal drugs leads to a systematic error in the results of elemental content determination, which significantly hinders the applicability of such results for the identification of herbal drugs. To ensure reliable results in the determination of the microelement status of plants, the authors suggest performing additional fractionation of herbal drugs and discarding the fraction under 0.2 mm.

Multi-stage optimization placement of DPMUs based on node metric indices

The proliferation of distributed energy resources and the introduction of new loads in distribution networks present significant challenges for monitoring and operation. To satisfy the enhanced observability and controllability requirements of modern distribution networks, there is an increasing demand for advanced monitoring devices. Distribution Network Phasor Measurement Units (DPMUs) offer high-precision measurement data with precise timestamps, thereby improving both the accuracy and redundancy of measurements within the distribution network.This paper introduces an optimization model for the strategic placement of PMUs within distribution networks, leveraging node metric indices. The indices considered are node degree, spatiotemporal correlation, and node power ratio. The relative importance of these indices is determined using an improved entropy weight method, which quantifies the differentiation of nodes within the network. This method facilitates the prioritized placement of DPMUs at critical nodes. The proposed model also incorporates constraints such as the depth of unobservability and zero injection nodes. Utilizing a 0–1 integer programming algorithm, the model derives a multi-stage optimal placement scheme for PMU placement. This scheme evolves from incomplete observability to critical observability and ultimately to full redundancy. Importantly, this approach allows for the monitoring of key nodes within the distribution network and enhances measurement redundancy without necessitating an increase in the number of placements.

Tin isotope heterogeneity and baseline of the upper continental crust

Stable Sn isotope ratios are emerging as a novel tracer for a wide range of geological processes; however, the Sn isotopic baseline of the upper continental crust (UCC) is not yet well-constrained. Here, we report high-precision Sn isotope data of a wide range of UCC samples, including granites, pegmatites, and sediments, to document the Sn isotopic composition of UCC. Significant variations in δ122/118Sn3161a (per mil deviation in 122Sn/118Sn relative to NIST 3161a) values are revealed for I-type (δ122/118Sn3161a = 0.025 ± 0.026‰ to 0.495 ± 0.046‰, n = 20) and S-type (δ122/118Sn3161a = 0.156 ± 0.018‰ to 0.501 ± 0.075‰, n = 22) granites. More extreme Sn isotope variability is observed for pegmatites, which have δ122/118Sn3161a from 0.256 ± 0.047‰ to 0.930 ± 0.049‰ (n = 13). The δ122/118Sn3161a of I-type granites decrease with decreasing TFe2O3 (total Fe as Fe2O3) and MgO contents and are attributed to the segregation of Fe-bearing minerals. Conversely, the Sn isotope variation of S-type granites appears to reflect source heterogeneity, whereas the Sn isotope variability of pegmatites may reflect fluid activity. In contrast, the loess samples display homogeneous δ122/118Sn3161a values (0.132 ± 0.034‰ to 0.239 ± 0.020‰, n = 20) that show no correlation with the degree of chemical weathering, suggesting that loess is representative of the average Sn isotope composition of UCC. The δ122/118Sn3161a values of modern sediments and sedimentary rocks range from 0.080‰ to 0.490‰ (n = 25) and the Sn isotope variations may be related to chemical weathering or sediment provenance. Based on the lithology-weighted average δ122/118Sn3161a of UCC samples (41 granites and 45 sediments) in this study, the δ122/118Sn3161a value of UCC is estimated to be 0.233 ± 0.099‰, providing a reference point for further investigations. Tin is isotopically lighter in UCC compared to the mantle, owing to magmatic differentiation and crustal evolution processes.

J/ψ photoproduction: Threshold to very high energy

A reaction model for γ+p→J/ψ+p photoproduction, which exposes the cc¯ content of the photon in making the transition γ→cc¯+P→J/ψ and couples the intermediate cc¯ system to the proton's valence quarks via Pomeron (P) exchange, is used to deliver a description of available data, viz. both differential and total cross sections from near threshold, where data has newly been acquired, to invariant mass W≈300GeV. The study suggests that it is premature to link existing γ+p→J/ψ+p data with, for instance, in-proton gluon distributions, the quantum chromodynamics trace anomaly, or pentaquark production. Further developments in reaction theory and higher precision data are necessary before the validity of any such connections can be assessed.

Water Conservancy Hub Geometric Modeling Based on Point Clouds

For hydraulic engineering, accurate geometric modeling is crucial for design, analysis, and maintenance. In recent years, point cloud technology, with its high precision and detailed data capture capabilities, has gradually become the preferred method for geometric modeling in hydraulic engineering. However, traditional point cloud processing methods exhibit slow data processing speeds and poor mesh quality when reconstructing 3D models. Therefore, we have studied the meshing method for the 3D reconstruction of large-scale discrete point cloud data and proposed a meshing method based on the Delaunay criterion and the growth method to achieve rapid meshing of discrete point cloud data. To demonstrate the efficiency and convenience of the proposed method, point cloud reconstruction experiments are conducted on various buildings. We compare our approach with the Poisson, BPA, and ONet methods. Additionally, we apply it to the Jiangsu Gaogang Water Conservancy Hub in China. The results show that our proposed method is superior in both reconstruction quality and efficiency, providing a promising solution for the reconstruction of 3D building models from point clouds.

A noise-reduction algorithm for raw 3D point cloud data of asphalt pavement surface texture

High-precision 3D point cloud data have various analyses and application use cases. This study aimed to achieve a more precise noise reduction of the raw 3D point cloud data of asphalt pavements obtained using 3D laser scanning. Hence, a noise-reduction algorithm integrating improved Gaussian filtering and coefficient of variation was developed. A portable laser scanner was used to collect raw, high-precision 3D point cloud data of surface textures from pavement slab samples prepared with three different types of asphalt mixtures: AC-13, SMA-13, and OGFC-13, as well as asphalt from the test sections of the Yakang Expressway. An improved Gaussian filtering and Gaussian filtering that extracts noise using the coefficient of variation were used to filter out the obvious outlier noise and small-scale burr noise, respectively. Finally, the filtering effect of the proposed algorithm, Gaussian filtering, median filtering, and mean filtering on raw 3D point cloud data of pavement textures was evaluated through subjective visual quality and objective index evaluations. The results showed that the proposed algorithm filters out noise while preserving the micro-texture structure information, outperforming Gaussian filtering, median filtering, and mean filtering.

Research on visualization of environmental landscape design based on digital entertainment platform and immersive VR experience

With the rapid development of digital entertainment platforms and immersive virtual reality (VR) technology, the visualization of environmental landscape design has attracted widespread attention. This study aims to explore the visualization methods and effects of environmental landscape design based on digital entertainment platforms and immersive VR experiences. By capturing three-dimensional point information in the environment, high-precision environmental data can be obtained. Next, convert the point cloud data into a digital model with terrain features, and use voxel scene construction technology to further transform the terrain model into a voxelated digital model. In the design process of landscape design systems based on digital entertainment platforms and immersive VR experiences, various interaction methods have been implemented, such as gesture recognition, head tracking, and touch control, so that users can freely browse and operate virtual landscapes. By introducing landscape design principles and rules, users can modify and customize the landscape in a virtual environment. The research results indicate that the visualization method of environmental landscape design based on digital entertainment platforms and immersive VR experience can effectively display the characteristics and details of the environmental landscape, improve user perception and participation.

Analysis and comparison of the orbit determination accuracy of TianQin based on multiple ground-based measurements

TianQin project, a Chinese initiative in space gravitational wave detection, demands high precision in satellite orbit during both entry and scientific operations. As means of developmental maturation, ground-based measurements play a vital role in ensuring the smooth execution of TianQin satellite’s detection mission. This paper conducts a simulation analysis by utilizing various ground-based measurement data, including the China Deep Space Network (CDSN), S/Ka-band ranging system, and Satellite Laser Ranging (SLR). The main focus is to explore the distinctions in Precise Orbit Determination (POD) capabilities among different methods and to enhance POD accuracy through the integration of multiple techniques for TianQin satellites. The results indicate: (1) Leveraging a strategically positioned station distribution, CDSN stations offer extended observation time, averaging 17.3 h per satellite daily, compared to S/Ka’s 10.5 h. (2) In single-measurement POD scenarios, S/Ka proves superior, achieving accuracy better than 10 m and 0.4 mm s−1 for TianQin satellites with a 7-day orbit arc length. This superiority is attributed to its exceptional observational accuracy, outperforming CDSN’s 40 m and 2.2 mm s−1 for POD accuracy. (3) By integrating high-precision SLR data on the foundation of CDSN or S/Ka observations, the POD accuracy of TianQin satellites is further enhanced, despite the limited SLR data quantity.

Dynamic stall modeling of wind turbine blade sections based on a data-knowledge fusion method

Dynamic stall often leads to unsteady load and performance degradation in horizontal axis wind turbines. Therefore, accurate modeling of dynamic stall is crucial. However, due to the large variations of the blade aerodynamic profiles and the complexity of dynamic stall flow, numerical simulation and wind tunnel experiment are costly. On the other hand, widely used semi-empirical models have limited accuracy. Hence, this paper proposes a data-knowledge fusion method that incorporates physical knowledge into a neural network to improve its accuracy and generalization ability. Firstly, the force components of the Leishman–Beddoes model are incorporated into the network. An efficient dynamic stall model for the S809 airfoil is thus established with a small amount of high-precision experimental data. It achieves extrapolation predictions of reduced frequency and angle of attack with only 1/5 of the samples in the database to train. Moreover, to make full use of the accumulated existing airfoil data to assist in modeling other airfoils, the obtained S809 model is fused in the network to predict the aerodynamics of S810 and S814. The average relative error of the prediction cases is nearly 10%. Comprehensively, this paper provides a new paradigm for assessing the dynamic stall of the wind turbine blade.

Iron isotope constraints on the genesis of giant Beiya Au-base metal deposits, Yunnan, Southwest China

The Beiya Au-base metal deposit in southwest China is characterised by a huge amount of iron associated with gold mineralization. The formation of the Beiya deposit is generally thought to be related to Tertiary potassic intrusion, as porphyry- and skarn-type mineralization are the two most important types of mineralization in the region. However, the lack of direct evidence to constrain the source of iron and gold as well as other metals makes it difficult to accurately conceptualise the ore genesis model. In this study, we report high-precision (0.03 ‰; 2sd) Fe isotope data on Fe-bearing minerals including magnetite, pyrite and chalcopyrite, and major igneous rocks exposed in the area, including monzogranite porphyry (MGP), mafic microgranular enclave (MME), lamprophyre and basalt. Magnetites have a wide range of δ Fe from 0.15 to 0.64 ‰, reflecting substantial isotopic fractionation at different mineralization stages. MMEs have heaviest Fe isotopic composition (0.35 ‰ to 0.88 ‰) compared to MGPs (0.19 ‰ to 0.48 ‰), lamprophyre (∼0.2 ‰) and basalt (∼0.0 ‰). A negative correlation between δ56Fe and TFe2O3 is found for both MPGs and MMEs, which indicates the leaching of iron by hydrothermal fluids mobilizes light Fe and leaves behind isotopically heavy Fe in the remaining source rock. Fe isotopic compositions of MPG and MME overlap with those of magnetite, both of which are proposed to be the source of Fe in magnetite. The basalt has δ56Fe value of 0 ± 0.03 ‰, similar to those of global basalts, suggesting a negligible contribution to the formation of iron ores. Therefore, we propose that magmas parental to the MGP and MME may be the main source of iron to form the Beiya deposit; post-magmatism hydrothermal activities play a key role in leaching the metals out and transporting them to the mineralization area.

A Review of Machine Learning Methods in Turbine Cooling Optimization

In the current design work, turbine performance requirements are getting higher and higher, and turbine blade design needs multiple rounds of iterative optimization. Three-dimensional turbine optimization involves multiple parameters, and 3D simulation takes a long time. Machine learning methods can make full use of historically accumulated data to train high-precision data models, which can greatly reduce turbine blade performance evaluation time and improve optimization efficiency. Based on the data model, the advanced intelligent combinatorial optimization technology can effectively reduce the number of iterations, find the better model faster, and improve the optimization calculation efficiency. Based on the different cooling parts of turbine blades and machine learning, this research explores the potential of implementing different machine learning algorithms in the field of turbine cooling design.

Evolution of the Local Spiral Structure Revealed by OB-type Stars in Gaia DR3

The structure and evolution of the spiral arms of the Milky Way have long been an important yet controversial issue. The wide age range of OB-type stars, coupled with the large amount of high-precision astrometric data provided by Gaia DR3, presents us with an opportunity to explore this issue. After constructing overdensity maps and examining the variations of overdensities with Galactocentric distance along the Galactic azimuth, we compare the spiral structures traced by B3–B5, B6–B7, B8, and B9 stars with those of young O–B2 stars in the vicinity of the Sun. We find that as the ages of the OB tracer stars increase, the Perseus Arm traced by them gradually shifts toward the anti-Galactic center direction, and the pitch angle of the Carina Arm gradually decreases. These results will help us to understand better the evolutionary properties of nearby spiral arms.

SnowMotion: A Wearable Sensor-Based Mobile Platform for Alpine Skiing Technique Assistance.

Skiing technique and performance improvements are crucial for athletes and enthusiasts alike. This study presents SnowMotion, a digital human motion training assistance platform that addresses the key challenges of reliability, real-time analysis, usability, and cost in current motion monitoring techniques for skiing. SnowMotion utilizes wearable sensors fixed at five key positions on the skier's body to achieve high-precision kinematic data monitoring. The monitored data are processed and analyzed in real time through the SnowMotion app, generating a panoramic digital human image and reproducing the skiing motion. Validation tests demonstrated high motion capture accuracy (cc > 0.95) and reliability compared to the Vicon system, with a mean error of 5.033 and a root-mean-square error of less than 12.50 for typical skiing movements. SnowMotion provides new ideas for technical advancement and training innovation in alpine skiing, enabling coaches and athletes to analyze movement details, identify deficiencies, and develop targeted training plans. The system is expected to contribute to popularization, training, and competition in alpine skiing, injecting new vitality into this challenging sport.

Satellite orientation modelling with quaternions and its impact on BDS-3 PPP-AR

Satellite orientation is a fundamental component of processing high-precision data from the Global Navigation Satellite System (GNSS). However, insufficient handling of satellite orientation may substantially affect the quality of the precise point positioning (PPP) solutions. This research investigates the influence of satellite orientation using satellite attitude quaternions on the third-generation BeiDou Navigation Satellite System (BDS-3) PPP. To illustrate the impact of satellite attitude, both float and PPP with integer ambiguity resolution (PPP-AR) were undertaken using observations from a multi-GNSS Experiment (MGEX) network. To fully evaluate the effect of the quaternions on PPP, a comprehensive comparison between BDS-3 and Galileo constellations was conducted using nominal attitude and quaternions. The findings indicate a significant performance difference between BDS-3 and Galileo satellites in phase observations after resolving integer ambiguities, with Galileo consistently demonstrating superior phase residuals across various receivers. When it comes to positioning accuracy, the utilisation of quaternions improves coordinate precision across both constellations. Furthermore, the quaternions enhance the stability of time series for the positioning biases and observational residuals.