High-precision Method Research Articles

Research on high-precision accounting methods for regional carbon emissions under the peak carbon target

In recent years, the level of digitalization and intelligence in the energy sector has profoundly changed the management mode of the energy sector. However, in the process of promoting the digital transformation of the energy sector, we also face some difficulties. One of the main manifestations is the lack of energy data sharing, and the difficulty of realizing the convergence and integration of various types of energy data. In addition, there is insufficient mastery of customer-side energy use data and a lag in the perception of customer demand, which requires the improvement and enhancement of energy efficiency diagnosis and energy saving services. At the same time, we have not yet established advanced digital technology monitoring means to grasp the user’s energy use and carbon emissions in real time. Therefore, this paper proposes the study of high-precision accounting methods for regional carbon emissions under the carbon peak goal. Based on the energy consumption and production activities of each region, a greenhouse gas emission inventory is compiled, so that carbon emissions can be accurately calculated. The high-precision accounting method of carbon emissions is analyzed, and by establishing a more complete database and model, and constructing a regional online monitoring system under the peak carbon target, we aim to improve the efficiency of data acquisition and processing, as well as how to combine carbon emission accounting with the peak carbon target, in order to provide support for the formulation of a more effective emission reduction policy. The testing experiments after flow and CO2 concentration measurements show that the accuracy of the experiments on regional carbon emissions is as high as 97.5%.

A high-precision image registration method for multi-channel single molecule localization

Single-molecule localization technology has been widely used in single-particle tracking and super-resolution imaging of biological samples, as it can bypass the diffraction limit of optical systems. Multi-channel single-molecule localization uses multiple imaging channels to simultaneously track different targets or perform multi-color super-resolution imaging, and can also improve the axial depth of single-particle tracking or achieve higher localization precision and density for super-resolution imaging. However, the difference between images in each channel can affect collaborative localization or quantitative analysis, so image registration is a key step in its image data preprocessing. Moreover, due to the high precision of single-molecule localization, its requirements for multi-channel image registration accuracy are also high. Existing technologies generally use control point-based registration methods and often use complicated and precise methods to obtain fiducial images for locating control point pairs to achieve high-precision image registration, which involves high sample or experimental equipment requirements and is difficult to directly extend to other systems. Therefore, developed in this work, is a high-precision image registration method that can directly use randomly distributed fluorescent beads as fiducial samples based on local nonlinear transformation and elimination of mismatched points. By monitoring and iteratively filtering control points in the process of feature matching and transformation model parameter estimation to eliminate control point pairs that are not accurately matched due to inaccurate or poor precision of single-molecule localization, the adverse effects on accurate acquisition and precise matching of control points when using randomly distributed fluorescent beads as fiducial samples are eliminated. At the same time, a second-order polynomial fitting based on local weighted mean is used for estimating the transformation model parameter to better adapt to the existence of local nonlinear deformation between different channels. The results show that using this method only requires three iterations to find and eliminate control point pairs that are not accurately located and matched, thereby achieving more accurate transformation model parameter and improving the registration accuracy by an order of magnitude, achieving a registration accuracy of about 6 nm in a complex dual-channel single-molecule localization imaging system based on orthogonal astigmatism.

Laser-machined micro-supercapacitors: from microstructure engineering to smart integrated systems.

With the rapid development of portable and wearable electronic devices, there is an increasing demand for miniaturized and lightweight energy storage devices. Micro-supercapacitors (MSCs), as a kind of energy storage device with high power density, a fast charge/discharge rate, and a long service life, have attracted wide attention in the field of energy storage in recent years. The performance of MSCs is mainly related to the electrodes, so there is a need to explore more efficient methods to prepare electrodes for MSCs. The process is cumbersome and time-consuming using traditional fabrication methods, and the development of laser micro-nano technology provides an efficient, high-precision, low-cost, and convenient method for fabricating supercapacitor electrodes, which can achieve finer mask-less nanofabrication. This work reviews the basics of laser fabrication of MSCs, including the laser system, the structure of MSCs, and the performance evaluation of MSCs. The application of laser micro-nanofabrication technology to MSCs and the integration of MSCs are analyzed. Finally, the challenges and prospects for the development of laser micro-nano technology for manufacturing supercapacitors are summarized.

A high-precision self-calibration method for laser tracker without common points

A high-precision self-calibration method for laser tracker without common points

High precision and fast classification of different dimensions of Baijiu using an OptGSCV quadratic optimization network combined with AS-LIBS

For the traditional Baijiu qualitative analysis problem, a high-precision fast classification method for different dimensional Baijiu based on AS-LIBS combined with Optimized Grid Search Cross-Validation (Opt-GSCV) is proposed.

Research on high-precision rotational inertia characteristic modeling and control method for auxiliary services

Research on high-precision rotational inertia characteristic modeling and control method for auxiliary services

Numerical study on effect of design parameters of the single-circumferential groove on tip leakage flow reduction in a transonic turbine

In order to investigate the impact of design parameters (depth, width, and location) of the single-circumferential groove (SCG) on tip leakage flow (TLF) reduction in a transonic turbine stage, a systematic investigation was conducted by high-precision numerical simulation method. The numerical results show that the introduction of SCG could improve the stage efficiency (η) of turbine significantly. The optimal design parameters of depth coefficient (ζ), width (W), and location (L) were ζ = 3, W = W3, and L = 20%Cax (where Cax denotes the axial chord of the blade), which could reduce tip clearance leakage rate (m*) by 28.9% and improve the η by 0.56%. The implementation of flow field display methods reveals that the introduction of SCG influences the formation and development of the vortex system at the rotor tip region. The circumferential groove vortex (CGV), induced by SCG, divided the tip leakage vortex (TLV) into two segments TLV_1 and TLV_2 due to its blocking effect. TLV_1 interacted with the passage vortex (PV) and depress the strength of PV. Meantime, TLV_2 would regenerate from the trailing edge of SCG, due to its limited development range and insufficient growth, the strength and scale of TLV_2 were weakened. Given that the TLF passing through SCG flows in an opposite direction to the original TLF, the SCG at appropriate location could lead to a fact that the net flow rate of the leakage flow reached the minimum value, thereby considerably reducing the m* and flow loss caused by TLF.

High-precision alkali-atom density measurement and control methods using light absorption for dual-beam SERF magnetometers

High-precision alkali-atom density measurement and control methods using light absorption for dual-beam SERF magnetometers

High-precision spherical wavefront calibration method for shack-hartmann wavefront sensor

High-precision spherical wavefront calibration method for shack-hartmann wavefront sensor

Effects of magnetic field, fluid properties, and geometric parameters on double-diffusive convection of liquid metals

<sec>Thermal convection in conducting fluids under the influence of a magnetic field is a hot research topic. In this study, a high-precision and high-resolution numerical method is used to directly simulate the double-diffusive convection of liquid metal in a two-dimensional cavity. The study covers the effects of magnetic field strength (<i>Ha</i>), Prandtl number (<i>Pr</i>), Lewis number (<i>Le</i>), and aspect ratio on the dynamics of flow and heat/mass transfer under both horizontal magnetic field and vertical magnetic field. The study considers magnetic field intensities ranging from 0 to 100, Prandtl numbers from 0.01 to 1, Lewis numbers varying from 1 to 100, and aspect ratios spanning from 1 to 12. Within these specified parameter ranges, the outcomes under conditions of no magnetic field (<i>Ha</i> = 0), weak magnetic field (<i>Ha</i> = 10), and strong magnetic field (<i>Ha</i> = 50) are compared with each other.</sec><sec>The results show that the magnetic field primarily suppresses flow, heat transfer, and mass transfer. Under the same strength of the magnetic field, the horizontal magnetic field has a greater suppressing effect than the vertical magnetic field. However, the cases of weak magnetic field and strong magnetic field, their effects on heat and mass transfer are similar. Regardless of the orientation and strength of the magnetic field, the heat transfer efficiency and mass transfer efficiency always increase with Prandtl number increasing. The application of a magnetic field can reduce the increase in heat and mass transfer, and when the magnetic field strength reaches a certain level, the Lorentz force predominates, making the influence of the Prandtl number on heat and mass transfer very small. In the presence of a magnetic field, a bifurcation phenomenon is observed around <i>Pr</i> = 0.9.</sec><sec>Additionally, as the Lewis number increases, the flow transforms from steady flow to periodic flow, and the influence on mass transfer efficiency becomes more significant. For example, under a horizontal magnetic field, the mass transfer efficiency at the maximum Lewis number is about six times that at the minimum Lewis number. Similarly, under a weak vertical magnetic field, the mass transfer efficiency is about nine times higher. The influence of Lewis number on heat transfer efficiency is relatively minor.</sec><sec>Within the range of considered aspect ratios, the heat transfer efficiency and mass transfer efficiency exhibit oscillatory behavior under no magnetic field and weak magnetic field as the aspect ratio increases. However, the heat transfer efficiency and mass transfer efficiency under a strong magnetic field are less affected by the aspect ratio. For flows with the same number of vortices, lower aspect ratio can lead to stronger heat and mass transfer.</sec>

Method and Application of High-Precision Open-Loop Velocity Measurement of Tianwen-1 Probe

In view of the requirements of Tianwen-1 missions on precision orbit determination and scientific application, this paper proposes a high-precision open-loop velocity measurement method based on ground-based radio. At first, relying on space–ground TT&C resources of the Tianwen-1 probe, the paper designs an open-loop velocity measurement strategy based on China’s deep-space network. Then, it proposes a core algorithm of open-loop velocity measurement based on local cross-correlation reconstruction to obtain instantaneous Doppler frequency observables. This algorithm is characterized by a high ability to avoid phase lock loss, convenient and efficient implementation, and flexible parameter configuration and is suitable for high-precision velocity measurement in the case of high dynamics and low signal-to-noise ratios. On this basis, the similarity and difference of velocity observables between open-loop and baseband velocity measurements are analyzed comparatively. Finally, on the basis of the open-loop velocity measurement method, the paper carries out tests on high precision orbit determination with independent support of velocity measurement, as well as on Mars radio occultation. According to the research results, the accuracy of open-loop velocity measurement can reach 0.05 mm/s (in 1-s integration time), which is 2 to 3 times better than that of baseband velocity measurement. Open-loop velocity measurement can independently support orbit determination accuracy of 50 m of the Tianwen-1 probe and effectively support autonomous retrieval of Martian ionospheric electron density profiles. Thus, this method can be effectively applied to future missions of deep-space exploration and research of planetary radio science.

Study of a high-precision complex 3D geological modelling method based on a fine KNN and kriging coupling algorithm: a case study for Jiangsu, China

A high-precision, complex, three-dimensional (3D) geological model can directly express the attributes of stratum thickness, geological structure, lithology and spatial form, which can provide a reliable basis for the development and utilization of underground space and planning decisions. However, it is difficult to perform accurate modelling due to the lack of basic data. As such, this paper proposes coupling a machine learning algorithm (K-nearest neighbour (KNN)) with the kriging algorithm to construct the topological relationship between the Delaunay triangle and the Thiessen polygon in order to perform the simulation and prediction of virtual drilling. Based on KNN, support vector machine (SVM) and neural network algorithms as well as the virtual borehole encryption data, data standardization processing and analysis are carried out. Through model verification, algorithm optimization is realized, and the optimal modelling method is explored. The results show that the fine KNN algorithm improved by Bayesian optimization can effectively improve the modelling accuracy through 0.1-m encryption, standardization processing and 5-fold cross-validation. Stratum modelling combined with the fine KNN and kriging algorithms can obtain a more accurate modelling without adding virtual boreholes. The improved levels of upper and lower hybrid modelling with an appropriate number of profile boreholes can also effectively optimize model accuracy. Both modelling accuracy and efficiency can be significantly improved by using Delaunay triangles and Thiessen polygons with virtual boreholes. Stratum modelling can effectively express the geological pinch-out in areas with adequate degrees of stratification, and hybrid modelling performs well in irregular geological bodies such as karsts and lenses.

Surrogate model-based multi-objective design optimization of vibration suppression effect of acoustic black holes and damping materials on a rectangular plate

The acoustic black hole (ABH) is a ground-breaking passive technology for vibration reduction and noise attenuation, characterized by its ability to manipulate flexural waves. When multiple two-dimensional ABHs are embedded in an irregular shaped complex plate structure used in engineering, such as the support plate of a refrigerator compressor, its vibration characteristics often cannot be solved through analytical or semi-analytical methods, resulting in the inability to carry out subsequent ABH optimization design. To address this issue, we propose a high-precision modelling method that combines surrogate models with finite element methods to construct a vibration characteristic database of the compressor support plate embedded with multiple ABHs in all design spaces of the ABH and damping materials geometric parameters using limited sample data. A high-precision surrogate model was constructed based on the vibration response data of the ABH plate under 50 parameter combinations of ABH and damping layer, and the fitting accuracy of the surrogate model was verified through vibration response data under another 25 parameter combinations. Based on the constructed surrogate model, the Multi-objective Genetic Algorithm (MOGA) was employed to optimize the five parameters of ABH and damping layer simultaneously, aiming to maximize the vibration reduction effect of the ABHs. Our investigation reveals that the optimized ABH and damping materials significantly improve the vibration suppression effect in a wide frequency range compared to the unoptimized structures. Finally, experimental verification was conducted to solidify the accuracy and efficacy of our approach in enhancing vibration reduction effect for irregular shaped complex plate structures using acoustic black holes.

High-precision point cloud registration method based on volume image correlation

With the rapid development of binocular reconstruction, fringe projection profilometry, and time of flight, 3D imaging technology has been widely applied in the field of 3D measurement. However, due to limited measurement range and self-occlusion, point cloud registration methods are often used to obtain larger or more complete 3D contours. Although many scholars have proposed various point cloud registration methods, the accuracy and efficiency of point cloud registration still need to be further improved, especially for point clouds with different density or non-rigid transformation. Image registration technology based on image correlation has been developed for many years and has achieved great success in fields such as computer vision, photomechanics, and photogrammetry. Therefore, a simple and direct idea in this paper is to transform the point cloud registration problem into volume image correlation problem. By this, an efficient image registration method based on fast Fourier transform and an inverse compositional Gaussian Newton optimization method that only needs to calculate the Hessian matrix once can be introduced into the point cloud registration field, which can greatly improve the speed and accuracy of point cloud registration. Comparative experiments have shown that our method has doubled the accuracy and efficiency compared to the iterative closest point (ICP) method, and its practicality has also been verified in impeller reconstruction experiments.

High-density analysis of surface wave profile imaging based on a multiple coverage common-midpoint signal-couple array

Surface wave exploration technology has been extensively used in the inspection of construction engineering quality and shallow surface surveys. To enhance the efficiency of surface wave exploration field acquisition and achieve high-precision and high-density surface wave profile imaging, a wireless distributed seismic surface wave signal acquisition system has been developed based on the principles of active source transient surface wave signal acquisition and dispersion curve calculation methods. For the purpose of achieving rapid multiple coverage signal acquisition and enhancing fieldwork efficiency, a method for rapidly configuring common-midpoint signal couples (CMCs) for multiple coverage common-shot signal acquisition has been devised, and a high-precision visualization method for dispersion curve calculation based on the CMC array has been formulated. When compared with the multichannel analysis of the surface wave method under identical conditions, the CMC array can effectively enhance surface wave dispersion curve survey station density and lateral resolution, thereby enabling high-density analysis of surface wave profile imaging. Through model analysis and field examples related to construction quality detection, including foundation compactness and earth and rock mixture compactness, it has been demonstrated that this method offers significant advantages in terms of high accuracy, high density, and a wide application range. These advantages greatly enhance the efficiency of surface wave exploration and the accuracy of profile imaging for the construction of engineering projects.

Forecasting electricity consumption by LSTM neural network

Relevance. The need to enhance the precision of electricity consumption forecasting for improving energy efficiency and, consequently, enhancing the competitiveness of manufactured products by reducing the proportion of electricity costs in their total cost. When determining forecast indicators of electricity consumption by industrial enterprises, it is important to apply contemporary high-precision forecasting methods. Only 20–30 forecasting methods of the 150 existing ones are actively implemented in practice. An examination of prevailing forecasting methodologies used by industrial enterprises reveals that they are mainly based either on expert assessments of electricity volumes or on accounting for specific electricity consumption (per unit of product manufactured). Aim. To elevate the accuracy of electricity consumption forecasting at industrial enterprises by using artificial intelligence methods, specifically, artificial neural network techniques, including the Long-Short Term Memory (LSTM) approach. Methods. When developing the forecasting model, artificial neural network techniques were adopted, with a particular emphasis on the Long-Short Term Memory (LSTM) method. For primary data processing, Gaussian distribution principles and normalization/scaling techniques were applied. Results. Substantiated computationally by applying the proposed model based on the artificial neural network technique for forecasting electricity consumption of industrial enterprises. A significant advantage of this method is its capability for learning and adaptability to forecasting. Real-time computations demonstrate its successful implementation, attributed primarily to appropriate selection of input layers and mitigation of random variables.

Unbalanced optimal transport for full waveform inversion in visco-acoustic media

Abstract As a high-precision parameter inversion method, visco-acoustic full waveform inversion (QFWI) is widely used in the inversion of parameters such as velocity and quality factor Q in visco-acoustic media. Conventional QFWI, using the L2 norm as the objective function, is susceptible to face the cycle-skipping problem, especially with inaccurate initial models. Lately, adopting the optimal transportation (OT) distance as the objective function in QFWI (OT-QFWI) has become one of the most promising solutions. In OT-QFWI, converting oscillatory seismic data into a probability distribution that satisfies equal-mass and non-negativity conditions is essential. However, seismic data in visco-acoustic media face challenges in meeting the equal-mass assumption, primarily due to the attenuation effect (amplitude attenuation and phase distortion) associated with the quality factor Q. Unbalanced optimal transportation (UOT) has shown potential in solving equal-mass assumption. It offers the advantage of relaxing equal-mass requirements through entropy regularization. Owing to this advantage, UOT can mitigate the attenuation effect caused by inaccurate quality factor Q during the inversion. Simultaneously, the Sinkhorn algorithm can quickly solve the UOT distance through CUDA programming. Accordingly, we propose a UOT-based QFWI (UOT-QFWI) method to improve the accuracy of two-parameter inversion. The proposed method mitigates the impact of inaccurate quality factor Q by introducing the UOT distance to calculate the objective function, thereby helping to obtain more accurate inverted parameters. Experimental tests on the 1D Ricker wavelet and 2D synthetic model are used to validate the effectiveness and robustness of our proposed method.

A high-precision frequency measurement method combining π-type delay chain and different frequency phase coincidence detection

A high-precision frequency measurement method combining π-type delay chain and different frequency phase coincidence detection

A Low-Cost Detection Method for Nitrite Content in a Mariculture Water Environment Based on an Improved Residual Network

Nitrite content is one of the key indicators for measuring the quality of mariculture water and has a crucial impact on the benefits of aquaculture. Most of China’s fisheries are small-scale domestic aquaculture. For economic reasons, farmers generally use chemical colorimetry or rely on life experience (such as whether the water bodies have become turbid or whether aquatic organisms have abnormal or died) to determine the nitrite content in water; however, both methods can easily lead to misjudgment and cause losses. Another more accurate method is spectrophotometry, but the spectrophotometer used is more expensive. This article aims to propose a low-cost and high-precision nitrite detection method. The new method we propose is to first perform a color development reaction using chemical detection reagents, and then use an improved residual network instead of human eyes to determine the nitrite concentration in the water sample. The advantages of this method are the fast response of the chemical reagents and the high accuracy of the machine vision recognition. Our network can achieve an accuracy of 98.3% on the test set. The experimental results indicate that this method can be applied to practical mariculture.

A high-precision method for manufacturing tunable solid microneedles using dicing saw and xenon difluoride-induced dry etching

Numerous fabrication techniques have been employed to produce solid microneedles (MNs); yet precise manufacturing of MNs with adjustable features (height, aspect ratio, and array number) remains the main limitation. Developing tunable MNs holds immense promise for personalized and efficient drug delivery systems. In this study, we utilized a combination of dicing saw and XeF2 isotropic dry etching processes to fabricate solid MNs with tunable characteristics. We herein created rectangular arrays using a dicing saw with desired geometry followed by dry etching to form MN arrays without further processing. Employing optimized parameters, the average heights of the MNs were 522 ± 15 µm, 614 ± 42 µm, and 698 ± 22 µm for initial pattern depths of 500 µm, 600 µm, and 700 µm, respectively. Moreover, we achieved an aspect ratio as high as 3.7, a radius of curvature less than 10 µm, and a tip angle as low as 6.4o. The mechanical and surface properties of the MNs were enhanced through magnetron sputtering with titanium. An ex vivo penetration test conducted on porcine skin demonstrated the significant potential of these MNs for transdermal drug delivery in future investigations. Overall, a cost-effective production of a single solid MN patch, featuring 400 MN arrays per cm2, can be achieved within a remarkably short timeframe (approximately 2 h). Investigating fundamental principles, this study addresses the persistent challenge in manufacturing solid MNs with adjustable features, such as height, aspect ratio, and array number. This presents a substantial advantage over alternative fabrication techniques.