Multipoint Method Research Articles

Changes of microbial active ingredients and antioxidant capacity during fermentation process of dark tea

Dark tea, a traditional fermented tea in China, is known for its unique flavor and enhanced health potential due to its fermentation process. However, previous studies on the evolution of its active ingredients and antioxidant properties have been limited by inadequate sample collection, single analytical methods, and insufficient data processing. To address these challenges, this study employed a comprehensive strategy to analyze the dynamic changes of active compounds and antioxidant efficacy during dark tea fermentation using refined sampling, diverse assay techniques, and advanced data analysis. A multi-point temporal sampling method was used to capture key stages of fermentation, ensuring comprehensive data. High-Performance Liquid Chromatography (HPLC) and various antioxidant assays (1,1-diphenyl-2-picryl-hydrazyl (DPPH), 2, 2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), Ferric ion reducing antioxidant power (FRAP)) enabled precise quantification of tea polyphenols, catechins, theaflavins, and thearubigins. Multivariate statistical analysis revealed that tea polyphenols and catechins decreased, theaflavins increased then slightly declined, and thearubigins steadily rose as fermentation progressed. These changes were linked to fluctuations in antioxidant capacity, peaking at around 30 mg/g of phenolic compounds. The study also explored optimizing fermentation to enhance the retention of beneficial components, maximizing antioxidant properties and improving product quality. This research advances the understanding of dark tea fermentation and supports the sustainable development of the dark tea industry.

A multi-point leakage prediction statistical method using Bayesian inference in water distribution networks

ABSTRACT Leakage in water distribution networks (WDNs) not only leads to serious water loss and pipe contamination but also affects residents’ daily water. Accurate localization of leaks in WDN is significant to conserve water resources and reduce economic losses. However, in traditional optimization and verification methods for leak detection, factors such as modeling and pressure monitoring point errors are not taken into account, resulting in the deviation from the actual location of leaks. To address the mentioned issues, this article presents a WDN leakage probability prediction method based on Bayesian inference. The method converts the prior probability of leakage events into posterior probability. Then, by utilizing the posterior probability density function, the uncertainty of modeling and measurement errors in the hydraulic simulation model are quantified. The probability distribution of leakage pipes and leakage quantity within the leakage area is calculated, allowing for the location prediction and corresponding magnitude of leakage. The experimental results indicate that the prediction model can detect unknown quantities of leakage events. By collecting multiple sets of leakage data, it is possible to accurately predict the location and quantity of leaks, enhancing the efficiency of leakage detection in large-scale water supply networks and providing decision-making assistance for water utilities.

The first spatio-temporal study of the microplastics and meso–macroplastics transport in the Romanian Danube

BackgroundTransport, accumulation, and degradation of microplastics (MiPs) in the aquatic environment represent a significant concern to the researchers and policy-makers, due to the detrimental impact on biota and human health through food ingestion. Although consistent investigations and research data are available worldwide, comparing the results is still challenging due to the need for more regulations regarding the sampling methods, analysis, and results reporting. The European regulatory efforts include studies on the MiPs transport in the western basin of the Danube River developed with active nets-based multipoint sampling methods from suspended sediments and proposed for standardization. In this context, the present study aimed to address for the first time the transport of MiPs in the Romanian sector of the Danube, starting after entering the country (Moldova Veche) and before the formation of the Danube Delta (Isaccea).ResultsThe multipoint nets sampling procedure facilitated the collection of suspended sediments in the water columns as deep as 0.0–0.6 and 3.0–3.6 m depths and near riverbed sediments (autumn 2022 sampling) during an extensive spatio-temporal study from spring 2022 until spring 2023. The estimate of the maximum annual transport of 46–51 and 93–100 t·y−1 for MiPs and total (micro–meso–macroplastics) MPs at Moldova Veche was based on 135 collected and processed samples using 2021 water flow data. Polyethylene (58–69%) and polypropylene (21–33%) were the main polymer components in the separated fragments, foils, microfibers, and different colors spheroids of MiPs ( < 5 mm), and the foils and fibers of meso–macroplastics (5–100 mm). Advanced investigations highlighted various microstructural degradations of the plastic fragments at the micro- and nanoscale and attached minerals (clays) and heavy metals.ConclusionThis paper presents the first comprehensive data set for microplastic annual transport in the "Low Danube", filling the need for a complete transport assessment in one of the most significant European rivers. 4–5 times lower values were measured before the entrance to the Danube Delta than those from Moldova Veche. The investigations should continue, including flooding events, and the sampling points should be expanded to deeper water column layers during all the campaigns for further validation.Graphical

Postoperative maxillary stability after Le Fort I osteotomy using a u-HA/PLLA system: three-dimensional analysis by surface superimposition based on virtual Le Fort I osteotomy

The postoperative stability achieved with Le Fort I osteotomy (LFI) using bioabsorbable systems remains controversial. A new method – multipoint measurement method – was devised for detailed three-dimensional examination of postoperative stability following LFI, and the stability after LFI when using SuperFIXSORB-MX made of u-HA/PLLA was investigated. Thirty-one patients who underwent LFI using SuperFIXSORB-MX were evaluated retrospectively. The patients were divided into four malocclusion types: open bite, mandibular retrognathia, mandibular protrusion, and facial asymmetry. Seven maxillary reference points were measured three-dimensionally using computed tomography scans obtained preoperatively (T0), 4 days post-surgery (T1), and 1 year post-surgery (T2). Surgical changes (T1–T0) and the postoperative discrepancy (T2–T1) of the maxilla were analysed to evaluate postoperative stability by surface superimposition of the virtual LFI segments. Postoperative discrepancy was the largest for the facial asymmetry type, ranging from 0.75 ± 0.45 mm to 0.98 ± 0.52 mm in three-dimensional distance (minimum to maximum mean ± standard deviation values for the individual reference points). The relapse at U1 was 16% in the transverse axis, and the anterior nasal spine moved further upward by 17% of the amount of movement of the maxilla. Fixation with SuperFIXSORB-MX was considered to be within clinically acceptable limits.

Seepage monitoring and leaks detection along an earth dam with a multi-sensor thermal-active system

Thermal investigation using linear sensors installed in the ground is currently one of the most effective methods for analyzing seepage processes in the bodies of earth dams or dikes and their subsoil, including leaks detection. However, linear, fiber-optic temperature sensors present several limitations when applied to existing structures, including installation difficulties and substantial costs. To enhance the applicability of the thermal method for studying subsurface water flow, a novel Multi-Point Thermal-Active Monitoring method has been devised. The approach consists of installing, through hammering, thermal-active sensors side-by-side in the ground, at the same depth in a single line thereby achieving quasi-continuous measurements along the structure. Small openings from sensor installation are secured with bentonite and do not pose a threat to the structure. Each sensor is equipped with a micro-heater, which enables the use of the thermo-active method to determine in-situ seepage velocity. This article describes this method and its initial application in 2014 on one of the Polish earth dams. This application enabled the detection of two leakage zones and the monitoring of their flow velocities, leading to the successful validation of the described technology.

Design and Experimental Study of Banana Bunch Transportation Device with Lifting Mechanism and Automatic Bottom-Fixing Fruit Shaft

In addressing the challenges of high labor intensity, cost, and potential mechanical damage to banana fruit in orchards, this study presents the design of a banana bunch transport device featuring a lifting mechanism and an automatic fruit shaft bottom-fixing system. The device is tailored to the planting and morphological characteristics of banana bunches, aiming for efficient, low-loss, and labor-saving mechanized transport. Key design considerations included the anti-overturning mechanism and the lifting system based on transportation conditions and the physical dimensions of banana bunches. A dynamic simulation was conducted to analyze the angular velocity and acceleration during the initial conveying stages, forming the basis for the fruit shaft bottom-fixation mechanism. A novel horizontal multi-point scanning method was developed to accurately identify and secure the fruit shaft bottom, complemented by an automated control system. Experimental results showed a 95.83% success rate in identification and fixation, validated by field trials that confirmed the necessity and stability of the fixation mechanism. To enhance the durability of the fruit shaft bottom-fixation mechanism, a multi-factor test was conducted, optimizing the device’s maximum travel speed and minimizing the banana bunch’s oscillation angle. Field tests showed an oscillation angle of 8.961°, closely matching the simulated result of 9.526°, demonstrating the reliability of the response surface analysis model. This study offers a practical and efficient solution for banana bunch transport in orchards, showcasing significant practical value and potential for wider adoption.

Identification of Shield Tunnel Segment Joint Opening Based on Annular Seam Pressure Monitoring.

Tunnels for subways and railways are a vital part of urban transportation systems, where shield tunneling using assembled segmental linings is the predominant construction approach. With increasing operation time and varying geological conditions, shield tunnels usually develop defects that compromise both structural integrity and operational safety. One common issue is the separation of segment joints that may cause water/mud penetration and corrosion. Existing inspection strategies can only detect openings after their occurrence, which cannot provide early warnings for predictive maintenance. To address this issue, this work proposes a multi-point seam contact pressure monitoring method for joint opening identification. It first derived the theoretical correlation between contact pressure distribution and segment opening; then, a finite element model was established to explore the stress and deformation responses under combined axial and bending loads. Finally, multi-point piezoelectric film sensors were implemented on a scaled segment model to validate the theoretical and numerical analyses. Results indicate that the multi-point monitoring method can effectively identify opening amounts at the segment joints with an average error of 8.8%, confirming the method's feasibility. These findings support the use of this monitoring technique for early detection and assessment of joint openings in shield tunnels.

Coupled vibration analysis of the spacecraft with the flexible shaft and solar panels assembly

Dynamical characteristics of the spacecraft with flexible components are investigated in this paper. The component consists of a flexible shaft and solar panels, where solar panels are completely fixed on the shaft. A novel power series multiplier polynomial method is proposed to describe the connecting condition between the shaft and solar panels. The deformation and force matching conditions between the one dimensional shaft and two dimensional panels are established, which is the major contribution about the multidimensional combined structure of this study. According to constraining boundary conditions of the shaft and solar panels, the bending-torsion coupled deformation of the component is expressed. The attitude maneuvering of the central platform and the elastic vibration of the component cause the rigid-flexible coupled effect. Then the discrete dynamical equation of the spacecraft is obtained by using the rigid-flexible coupled modal shapes. The correctness of the proposed method is verified by comparing the natural characteristics with that of the finite element model. The relative error of the higher order frequency is not more than 4%. Numerical results show that the degree of the bending angle polynomial should be at least quadratic to ensure the accuracy of the calculation. The proposed power series multiplier polynomial breaks through the barriers that the traditional Lagrange multiplier cannot express the continuous constraint. It is an effective method to fit the constrained boundary by the polynomial rather than by the discrete multipoint method.

A multisource data‐driven monitoring model for assessing concrete dam behavior

AbstractThe pivotal role of dam infrastructure necessitates continuous health monitoring, which results in extensive sets of data. Most monitoring data‐based models in dam engineering concentrate on predicting dam behavior. However, little attention has been systematically paid to the processing of extensive monitoring data, modeling of comprehensive dam behavior, and assessment of overall dam operation status. Here, we propose a novel monitoring model comprising three main aspects: a multidimensional data mining method, a multipoint response prediction method, and a multilayer data fusion‐based assessment method. Utilizing monitoring data from a mega concrete arch dam, we evaluate and discuss the effects of data mining, modeling accuracy for dam behavior, robustness against data pollution, and sensitivity to anomalies. Comparisons with classical benchmarks demonstrate the performance of the proposed model for the dam.

An Improved Multi-point Chord Reference Measurement Device and Error Correction Method for Corrugation Measuring in Sharp Curves

Background: The traditional chord reference method and its device have faced challenges matching the sharp curve track. Thus, it is of utmost importance to research and develop a measurement device and method that can obtain accurate and comprehensive information regarding rail running band corrugation. Aims: It provides a solution for the measurement of the multi-point chord reference method on sharply curved rails and, at the same time, meets the demand for data richness and accuracy in theoretical studies on the causes of rail corrugation and wheel-rail contact relationships. Objective: This paper aims to research and design a measurement device based on the multi-point chord reference method for the rail running band corrugation. Meanwhile, the error in measuring the sharp curve rail is corrected and verified by simulation. Methods: The lateral information of rail running band is obtained by using a line laser profile sensor; the rail corrugation measurement model and error correction model of the rail running band area are established based on multi-point reference system; the simulation of the system model is carried out using Matlab; and the mechanical structure is built for static testing. Results: The measurement model based on the profile sensor and multi-point chord reference system can accurately obtain the rail corrugation waveform of any longitudinal measurement line in the running band area. The measurement results can be accurately corrected for a radius of 200m- 400m, the error parameters can be effectively improved, and the mechanical mechanism of the measurement system runs stably. Conclusion: The results show that the measurement model can accurately measure the rail corrugation of the sharp curve section, and the multi-waveform in the rail running band area has good measurement performance, but the mechanical structure can be optimized and improved in the light weight.

Two Novel With and Without Memory Multi-Point Iterative Methods for Solving Non-Linear Equations

Two Novel With and Without Memory Multi-Point Iterative Methods for Solving Non-Linear Equations

Enhancing parameter calibration for micro-simulation models: Investigating improvement methods

Calibrating microscopic traffic simulation models is a prerequisite for simulation applications. This study proposes three novel methods to improve the accuracy and interpretability of the calibration model. The proposed approach involves selecting the calibration parameter, refining the model parameter system, and optimizing the calibration results. The first method expands the single-point mean into a multi-point distribution. The cumulative distribution curve of delay was selected as the calibration parameter. The second method divides the parameter system into global and local parameters. Global parameters were calibrated using NGSIM measured data, and local parameters were calibrated through intelligent algorithms. The third method proposes a methodology of parameter clustering recursion based on the genetic algorithm results, with information entropy selected as the analysis index. To evaluate the effectiveness of the proposed optimization methods, this study used NGSIM trajectory data as a case study. Eight simulation schemes based on the three optimization methods were designed, and simulation experiments were conducted using the VISSIM platform. The results show that the accuracy of the multi-point distribution calibration and parameter value optimization method is significantly higher than the default method. Additionally, the optimization method with calibration of both global and local parameters was more consistent with actual driving characteristics. This study provides a theoretical foundation for improving the practical application of traffic simulation technology, which has significant implications for transportation planning and management.

Response spectrum-based analysis of airborne radar random vibration and multi-point control improvement

During the flight of a UAV (unmanned aerial vehicle), the LiDAR device undergoes random vibrations due to the changing flight attitude and wind speed conditions of the UAV. It is important to control the frequency and amplitude of the vibrations within a reasonable range by means of a damping structure. As the vibrations caused by various factors during flight are random and non-linear, this paper innovates the analysis principle and damping control means for the random vibrations of airborne optoelectronic devices. The response spectrum analysis theory is used to establish the shock response spectrum, and an optimised and improved recursive digital filtering method is used to fit the frequencies of random vibration to the synthetic shock response. Considering the uncertainty of the vibration excitation signal, a virtual excitation method is used for the first time to simulate the random vibration to which the radar may be subjected in the air, and to simplify the calculation steps. The shock plate structure is designed using a multi-point control method to innovate a passive response to the random excitation. Finally, a modal analysis of the synthesised impact response was carried out. It is verified that the first six modal frequencies are controlled within 220 Hz, realising the frequency reduction. The amplitude of the three x, y, and z directions is controlled to within 0.5 mm, thus achieving vibration damping.

Multipoint leak localization for pipelines via acoustic wave amplitude ratio

Pipeline leak localization is significant for maintaining the regular operation of pipelines. This paper proposes a multipoint leak localization method for pipelines via the acoustic wave amplitude ratio, which addresses the issue of the traditional time delay estimation method (TDE) not being able to locate multiple leaks simultaneously. Firstly, a multipoint leak localization method for pipelines is established without time delay estimation and acoustic velocity. This method merely needs to determine the amplitude of the leakage acoustic wave propagating to both ends of the pipeline to achieve leakage localization. Secondly, the improved empirical wavelet transform (IEWT) method denoises the leakage acoustic wave, which can obtain an accurate acoustic amplitude to reduce the localization error. Finally, the trouble that the mutation factor and crossover probability cannot be adaptively selected in the differential evolution (DE) algorithm is improved, and the improved differential evolution (IDE) algorithm is used to solve the objective function to obtain the position of each leakage point. Field experiments show that the multipoint leak localization method proposed in this paper has perfect accuracy, and the minimum localization error is 11 m.

Response of the TEROS 12 Soil Moisture Sensor under Different Soils and Variable Electrical Conductivity.

In this work, the performance of the TEROS 12 electromagnetic sensor, which measures volumetric soil water content (θ), bulk soil electrical conductivity (σb), and temperature, is examined for a number of different soils, different θ and different levels of the electrical conductivity of the soil solution (ECW) under laboratory conditions. For the above reason, a prototype device was developed including a low-cost microcontroller and suitable adaptation circuits for the aforementioned sensor. Six characteristic porous media were examined in a θ range from air drying to saturation, while four different solutions of increasing Electrical Conductivity (ECw) from 0.28 dS/m to approximately 10 dS/m were used in four of these porous media. It was found that TEROS 12 apparent dielectric permittivity (εa) readings were lower than that of Topp's permittivity-water content relationship, especially at higher soil water content values in the coarse porous bodies. The differences are observed in sand (S), sandy loam (SL) and loam (L), at this order. The results suggested that the relationship between experimentally measured soil water content (θm) and εa0.5 was strongly linear (0.869 < R2 < 0.989), but the linearity of the relation θm-εa0.5 decreases with the increase in bulk EC (σb) of the soil. The most accurate results were provided by the multipoint calibration method (CAL), as evaluated with the root mean square error (RMSE). Also, it was found that εa degrades substantially at values of σb less than 2.5 dS/m while εa returns to near 80 at higher values. Regarding the relation εa-σb, it seems that it is strongly linear and that its slope depends on the pore water electrical conductivity (σp) and the soil type.

Multi-point method using effective demodulation and decomposition techniques allowing identification of disturbing loads in power grids

The paper presents an innovative approach to identifying voltage fluctuation sources in power networks, also considering the localization understood as the indication of supply points of disturbing loads. The presented approach considers disturbance sources that change their operating state with a frequency higher than the power frequency. The implementation of the proposed solution is also proposed in such a way that its implementation in the smart meter infrastructure allows automatic localization of disturbance sources without additional expert knowledge. In the proposed approach, the modulation signal is estimated using a carrier signal estimator, which allows the estimation of a modulation signal with a frequency higher than the power frequency. The estimated modulating signal is decomposed into component signals associated with individual disturbing loads by decomposition by approximation using pulse waves. The decomposition process allows for the estimation of selected parameters associated with disturbing loads, on the basis of which the assessment of propagation of voltage fluctuations associated with the impact of individual disturbance sources is performed, which allows for the indication of their supply point. The proposed approach was verified in numerical simulation studies using MATLAB/SIMULINK and in experimental studies carried out in a real low-voltage power grid.

A multi-scale model for longitudinal seismic design of prefabricated utility tunnel based on multi-point constraints

A multi-scale model for the longitudinal seismic analysis of underground prefabricated utility tunnel was proposed. In this multi-scale model, beam elements were used to model the utility tunnel segments, shell elements were used to model the weak parts, e.g., tunnel intersections, and node frames with multiple springs were used to simulated the behavior of the tunnel joint. The node frames, whose form are the same as that of the prefabricated joint, were established on a basis of the cross-sectional size and the joint form of the tunnel. By arranging multiple sets of nonlinear springs to connect adjacent node frames, the refined model of the utility tunnel joint was established. Based on the multi-point constraint method, the multi-point constraint equations between the structure model and the refined joint model were given. Finally, a specific straight utility tunnel as well as a specific cross-type utility tunnel were taken as the examples to verify the accuracy and applicability of the proposed model. The results indicate that the proposed model is suitable for the longitudinal seismic analysis of the utility tunnels with asymmetric cross-section and intersections, and may provide reference for the longitudinal seismic design of large-scale utility tunnels.

Hybrid methods for solving structural geometric nonlinear dynamic equations: Implementation of fifth-order iterative procedures within composite time integration methods

This paper studies a class of hybrid methods that implement multi-point iterative procedures as the nonlinear solver within optimized composite implicit methods. These multi-point methods are employed to enhance convergence order and accuracy without requiring higher-order derivatives for solving structural geometric nonlinear dynamic equations. The promising approach provides an opportunity to delve deeper into its implications and explore the potential applications of multi-point techniques and composite methods across the analysis of dynamical systems. This study involves the utilization of two-point and five-point iterative methods with fifth-order convergence within three-step and four-step optimized composite implicit time integration methods. Moreover, a comprehensive hybrid scheme is introduced by integrating a family of optimized composite implicit methods with single-point and multi-point iterative methods. Then, the performance of the hybrid scheme is analyzed through structural examples, considering factors such as time step size, tolerance threshold, and the degrees of freedom of structures. The findings and numerical results illustrate that multi-point methods outperform the single-point method in terms of the number of iterations. Simultaneously, the four-step time integration method exhibits superior performance compared to the three-step time integration method, albeit with a marginal difference. It is observed that the hybrid method, consisting of the four-step time integration method and the five-point iterative method, performs better than other methods in terms of the number of iterations and errors for solving geometric nonlinear dynamic equations, especially in large structures. Thus, it stands out as a favorable choice for practical analyses and a possible candidate for generalization to other types of nonlinear problems in computational mechanics.

Experimental research on the thermal performance of the dry conduction plate for multi-point electronic chips

This paper designs a dry conductive heat dissipation method using several parallel heat pipes to solve the difficulty of the thermal management problem of multi-point electronic chips. The heat sources are distributed along the heat pipe, whose heat is efficiently conducted from the middle to the cold plate on the two sides. The effect of gravity, flow rate, and heat source distributions on the heat transfer performance is studied. The testing data indicated that gravity has less effect on the conduction performance of heat pipes for the cooling on two sides. As the heat sources concentrate in the centre, the heat pipe temperature difference between the centre and the side increases under the same transmission power. The results demonstrated that the two-side cooling and multi-point distribution heat conduction method is conducive to improving the thermal management capability under different inclination angles.

Multipoint stress mixed finite element methods for linear viscoelasticity with weak symmetry

In this paper, we propose two Multipoint Stress Mixed Finite Element (MSMFE) methods for linear viscoelasticity with weak symmetry on quadrilateral grids. The methods are constructed based on the lowest order Brezzi–Douglas–Marini mixed finite element spaces for elastic and viscous stress, piecewise constant velocity and piecewise constant (linear) vorticity. A special quadrature rule is applied for local stress and vorticity elimination. This results in a positive definite cell centered velocity–vorticity or only velocity system at each time step. Unconditional energy-dissipation of the MSMFE methods is proved rigorously. The accuracy of all the numerical solutions in their nature norms are established to be first order space convergence, both for the semi-discrete and fully-discrete formulations. Numerical results validate the theory results of the proposed methods.