Geometric Analysis Method Research Articles

Forward modeling of single-sided magnetic resonance and evaluation of [formula omitted] fitting error based on geometric analytical method

Single-sided magnetic resonance (SSMR) offers advantages of portability and noninvasive measurement for water detection, with significant potential applications in groundwater exploration, petroleum well logging, and soil moisture monitoring. However, the inherent highly inhomogeneous static magnetic field and radiofrequency (RF) field in SSMR necessitate the utilization of the Carr–Purcell–Meiboom–Gill (CPMG) sequence measurement scheme. To accelerate forward modeling during pulse excitation, we introduce a Geometric Analysis Method (GAM) and assess T2 error using its primary parameters. The GAM involves applying spatial geometric rotations on the magnetization vector, leading to an analytical solution to the Bloch equation that disregards relaxation effects. Compared with the rotation matrix (RM) method, the GAM demonstrates high accuracy and reduces computational time by approximately 20.9%. By analyzing the primary parameters governing the magnetization vector in the analytical formula, we evaluated their impact on the transverse relaxation time (T2) obtained through fitting the SE signal. Ultimately, the forward modeling results of the CPMG sequence within the region of interest (ROI) of a single-sided Halbach magnet array are validated. The T2 fitting error increases as the primary parameters deviate from the ideal values, highlighting their significant role in the T2 fitting results. This study provides a theoretical foundation for optimizing the design of SSMR magnets and RF coils.

Semi-destructive methods for evaluating the micro-scale residual stresses of carbon fiber reinforced polymers

Micro-scale residual stress in carbon fiber reinforced polymers have a significant impact on their mechanical performance. The residual stresses in the carbon fibers were released by micro-slotting and micro-ring-core methods using focused ion beam (FIB). The released deformation fields were captured by cross-gratings and mapped by geometric phase analysis (GPA) and digital image correlation (DIC) methods. The in-plane residual stresses in the carbon fibers were experimentally determined to be −40.5 MPa using elastic constitutive relations, which is consistent with the composites cylinder model. The axial compressive residual stresses in the fibers were found to be greater than −100 MPa. Moreover, the maximum value of residual stress in the polymer matrix was observed at the interface, potentially serving as a crack initiation site.

A unified geometrical modeling and analysis method for evaluating CFRP machining performance: Cutting geometry space

Carbon Fiber Reinforced Polymer (CFRP) is extensively utilized in the cutting-edge industries, attributed to its superior mechanical performances. The machining performance of CFRP, however, is significantly influenced by its pronounced anisotropy, particularly the fiber orientation. Consequently, Fiber Cutting Angle (FCA) is widely employed to assess the relationships between cutting geometry and machining performance, yet the coupling of cutting orientation and fiber orientation, along with the absence of feeding angle, limits the further exploration into the underlying mechanisms. This article introduced a novel geometrical framework termed “Cutting Geometry Space” (CGS), for modeling CFRP machining process. Incorporating feeding orientation, cutting orientation and fiber orientation, CGS is applied in milling process for an enhanced comprehension of cutting geometry. Additionally, a pragmatic milling experiment is designed, efficiently evaluating the performances of 1092 combinations of CGS parameters in 13 T700-12K/epoxy CFRP specimens. Microscopical observations and morphological analyses reveals four predominant fracture mechanisms in CFRP machining, with fiber-matrix debonding and bending-induced fracture identified as the key contributors to macroscopic cavity formation. A designated "Damage Zone" within the CGS, encompassing a cutting angle range of 90°–270° and a fiber tilt angle of 15°–60°, is identified as a high-risk area for machining-induced surface cavities. Additionally, the impact of feeding orientation on the surface integrity is confirmed and explained by the influence on the equivalent FCA. Furthermore, the study elucidates chatter marks as a phenomenon induced by a confluence of factors, including generalized down milling, high FCA, and a significant effective cutting fiber count. The observed shift in chatter mark with varying feeding angles provides deep insights into the complex dynamics of machining parameters.

The effect of cutting depth, feed rate, and cutting angle on surface roughness in the lathe process of aluminum 6061.

In the turning process, the machining parameters have a significant impact on the product quality. Consumers frequently request that certain industries adhere to product quality standards, especially regarding surface texture. Numerous product failures have resulted in dissatisfaction among the company's clientele because many lathe operators are fixated solely on product size drawings and are unaware of factors that can impact the surface roughness value. This investigation was conducted to ascertain how machining parameters affect surface irregularity. Variations in feed rates of 47.5 mm/min and 345.6 mm/min, cutting angles of 60° and 80°, and depths of cut of 1 mm and 3 mm were utilized to conduct the investigation on aluminum alloy 6061 specimens. The results of turning were evaluated for surface roughness using a surface roughness analyzer and a macro test to determine the structure of the surface roughness. Using the Minitab 2019 application, the obtained data was then analyzed to determine the influence of each trimming parameter working individually or simultaneously. Using the method of geometric factorial analysis, integrate the research parameters. The results indicated that the surface roughness increased as the feed rate increased; the lowest surface roughness was achieved with a depth of cut of 1 mm, a feeding rate of 47.5 mm/min, and a cut angle of 80°. In this study, the surface roughness value decreased as the cutting angle increased at lower levels of feeding rate, while the surface roughness value increased at higher levels of feeding rate.

Exploring sleep heart rate variability: linear, nonlinear, and circadian rhythm perspectives.

Heart rate variability (HRV) is believed to possess the potential for disease detection. However, early identification of heart disease remains challenging, as HRV analysis in dogs primarily reflects the advanced stages of the disease. The aim of this study is to compare 24-h HRV with sleep HRV to assess the potential utility of sleep HRV analysis. Thirty healthy dogs with no echocardiographic abnormalities were included in the study, comprising 23 females and 7 males ranging in age from 2 months to 8 years (mean [standard deviation], 1.4 [1.6]). This study employed a cross-sectional study. 24-h HRV and sleep HRV were measured from 48-h Holter recordings. Both linear analysis, a traditional method of heart rate variability analysis, and nonlinear analysis, a novel approach, were conducted. Additionally, circadian rhythm parameters were assessed. In frequency analysis of linear analysis, the parasympathetic index nHF was significantly higher during sleep compared to the mean 24-h period (mean sleep HRV [standard deviation] vs. mean 24 h [standard deviation], 95% confidence interval, p value, r-family: 0.24 [0.057] vs. 0.23 [0.045], 0.006-0.031, p = 0.005, r = 0.49). Regarding time domain analysis, the parasympathetic indices SDNN and RMSSD were also significantly higher during sleep (SDNN: 179.7 [66.9] vs. 156.6 [53.2], 14.5-31.7, p < 0.001, r = 0.71 RMSSD: 187.0 [74.0] vs. 165.4 [62.2], 13.2-30.0, p < 0.001, r = 0.70). In a geometric method of nonlinear analysis, the parasympathetic indices SD1 and SD2 showed significantly higher values during sleep (SD1: 132.4 [52.4] vs. 117.1 [44.0], 9.3-21.1, p < 0.001, r = 0.70 SD2: 215.0 [80.5] vs. 185.9 [62.0], 17.6-40.6, p < 0.001, r = 0.69). Furthermore, the circadian rhythm items of the parasympathetic indices SDNN, RMSSD, SD1, and SD2 exhibited positive peaks during sleep. The findings suggest that focusing on HRV during sleep can provide a more accurate representation of parasympathetic activity, as it captures the peak circadian rhythm items.

Material Selection for Artificial Femur Bone Using PROMETHEE-GAIA Method

Abstract When replacing bones and implants, choosing the right materials for the artificial bone and orthopedic implants is crucial to the procedure’s success. In this work, a thorough assessment of the literature was followed by a thorough and rigorous evaluation of prospective materials for prosthetic femurs using a multicriteria decision-making process known as PROMETHEE-GAIA (Preference Ranking Organization METHod for Enrichment Evaluation and Geometric Analysis for Interactive Assistance). The proposed approach was validated using a total of 12 assessment parameters, including density, tensile strength, and ultimate tensile strength, and 17 candidate materials. The significance of the chosen criteria is well described. These 17 candidate implant materials and the 12 assessment criteria were used to develop a choice matrix. Rankings over the prepared matrix were produced using the PROMETHEE-GAIA program. Ti-6Al-7Nb, Ti-6Al-4V, and ASTM F1537, Standard Specification for Wrought Cobalt-28Chromium-6Molybdenum Alloys for Surgical Implants (UNS R31537, UNS R31538, and UNS R31539), Co-Cr-W emerged as the top contenders and were demonstrated as possible materials for effective artificial femur materials because of the assessment. With a large number of pertinent criteria and a wide range of materials, this study offers a framework for the selection of implant materials. It also emphasizes how choosing materials carefully may increase the durability and efficiency of orthopedic implants.

Feature-constrained automatic geometric deformation analysis method of bridge models toward digital twin

ABSTRACT It is very important to construct digital twin scenes, which can accurately describe the dynamically changing geographical environment and improve the level of refined management in bridge construction. This article proposes a feature constrained automatic diagnostic analysis method for geometric deformation of bridge digital twins. The geometric deformation feature library of bridge twins was first created to accurately describe structural relationships and behavior characteristics. Secondly, line surface feature constraints were used to extract geometric deformation information from bridge digital twins. Then, a geometric deformation diagnosis algorithm was designed based on an improved Hausdorff method. Finally, a case study was conducted to implement experimental analysis. The experimental results show that the method proposed in this paper can automatically extract the geometric morphology and rapidly calculate line and surface deformations for point cloud bridge digital twins. It achieves an efficiency improvement above 90% and with millimeter-level accuracy, which effectively enhances the diagnostic analysis capabilities for geographical digital twin models.

Segmentation of Individual Tree Points by Combining Marker-Controlled Watershed Segmentation and Spectral Clustering Optimization

Accurate identification and segmentation of individual tree points are crucial for assessing forest spatial distribution, understanding tree growth and structure, and managing forest resources. Traditional methods based on Canopy Height Models (CHM) are simple yet prone to over- and/or under-segmentation. To deal with this problem, this paper introduces a novel approach that combines marker-controlled watershed segmentation with a spectral clustering algorithm. Initially, we determined the local maxima within a series of variable windows according to the lower bound of the prediction interval of the regression equation between tree crown radius and tree height to preliminarily segment individual trees. Subsequently, using this geometric shape analysis method, the under-segmented trees were identified. For these trees, vertical tree crown profile analysis was performed in multiple directions to detect potential treetops which were then considered as inputs for spectral clustering optimization. Our experiments across six plots showed that our method markedly surpasses traditional approaches, achieving an average Recall of 0.854, a Precision of 0.937, and an F1-score of 0.892.

Maximum Reactive Power Generation Method Based on Limitation of Output Capacity for Star-Connected Cascaded H-Bridge STATCOM Under Voltage Sag

Star-connected cascaded H-bridge (SCHB) STATCOM is being widely used in medium and high voltage to support grid by injecting positive and negative sequence current. Under balanced conditions, the rated reactive power is usually utilized to calculate the required reactive current reference based on instantaneous power theory. However, under grid voltage sag, the rated reactive power changes due to the introduced negative sequence current and extra zero sequence voltage for cluster voltage balancing, which may increase overcurrent and overmodulation risk. Therefore, how to derive the maximum compensable reactive power is required for SCHB STATCOM under the grid voltage sag. In this paper, the quantitative relationship between the imbalanced degree of grid voltages and reactive power reference is fully explored. On this basis, the maximum reactive power is calculated under voltage sags by considering current and voltage limitation. In this calculation, a new geometrical analysis method is proposed, which makes the calculation speed faster for online calculation. Therefore, a new grid support control strategy is proposed for the SCHB STATCOM under grid voltage sag, which can effectively support the grid with the maximum output reactive power. Finally, the proposed method is verified by experimental results on a 400V/7.5kVar SCHB STATCOM prototype.

Course evaluation of preschoolhygiene under the multimodal learning model

Abstract In traditional learning situations, teachers mainly evaluate students’ behavioral changes, emotional changes, and interactions to ensure teaching quality. The Random Forest algorithm is employed in this paper to determine the characteristics of students’ body postures and observe their behavioral changes. The geometric analysis method is used to recognize students’ head posture, and the image test classification module is used to capture students’ facial expressions. Analyze the teacher-student learning interactions in the classroom by examining the student’s question-answering records from the interactive cloud platform. A multimodal information fusion model was constructed to combine students’ multimodal performance data to complete the evaluation of the preschool hygiene course. The results of the case study of five students showed that the fusion results of the ratings of students 1-5 under the multimodal information fusion model of the course evaluation were 0.56, 0.888, 0.083, 0.452, and 0.957, respectively. The results of the fusion of the ratings of students 2 and 5 were very serious in learning the course, and the percentage of their time spent in attentive behavior was 0.452. Student 2 and Student 5 studied the course very seriously, spent 90% and 89% of their time engaged in attentive behaviors, respectively, and maintained an emotion of interest for 66% and 70% of the time, respectively. Furthermore, Student 2 answered all the questions in the interactive session, while Student 5 answered all the questions correctly. The median integration rating of the 40 participating students was 0.706, and the majority of the students rated the integration of the course in the middle to high range, which means that the content and format of this pre-school hygiene course were excellent and stimulating for the students.

Study on yield limit of steel containment under external pressure considering initial defects

The main objective of floating nuclear power plants (FNPP) is an emerging technology product formed by applying land small-scale nuclear power plant technology to the marine field. The containment structure studied in this article plays a great role in protecting the safety of FNPP’s nuclear power system. When exploring the safety performance of the containment structure under accident conditions, it is necessary to analyze and study the external pressure yield limit of the containment. This study provides a reference basis for the static buckling limit calculation of spherical shell structures similar to steel safety shells. The article adopts a geometric initial defect analysis method based on buckling mode to consider the initial defects of the model and explores the external pressure yield limit of the safety shell through the arc length method. The research results analyzed that the external pressure yield limit of the containment vessel decreased by about 30% under the influence of initial defects and pointed out the weak structural parts of the containment vessel in the buckling analysis.

Spatial Characterization of Wetting in Porous Media Using Local Lattice-Boltzmann Simulations

Wettability is one of the critical parameters affecting multiphase flow in porous media. The wettability is determined by the affinity of fluids to the rock surface, which varies due to factors such as mineral heterogeneity, roughness, ageing, and pore-space geometry. It is well known that wettability varies spatially in natural rocks, and it is still generally considered a constant parameter in pore-scale simulation studies. The accuracy of pore-scale simulation of multiphase flow in porous media is undermined by such inadequate wettability models. The advent of in situ visualization techniques, e.g. X-ray imaging and microtomography, enables us to characterize the spatial distribution of wetting more accurately. There are several approaches for such characterization. Most include the construction of a meshed surface of the interface surfaces in a segmented X-ray image and are known to have significant errors arising from insufficient resolution and surface-smoothing algorithms. This work presents a novel approach for spatial determination of wetting properties using local lattice-Boltzmann simulations. The scheme is computationally efficient as the segmented X-ray image is divided into subdomains before conducting the lattice-Boltzmann simulations, enabling fast simulations. To test the proposed method, it was applied to two synthetic cases with known wettability and three datasets of imaged fluid distributions. The wettability map was obtained for all samples using local lattice-Boltzmann calculations on trapped ganglia and optimization on surface affinity parameters. The results were quantitatively compared with a previously developed geometrical contact angle determination method. The two synthetic cases were used to validate the results of the developed workflow, as well as to compare the wettability results with the geometrical analysis method. It is shown that the developed workflow accurately characterizes the wetting state in the synthetic porous media with an acceptable uncertainty and is better to capture extreme wetting conditions. For the three datasets of imaged fluid distributions, our results show that the obtained contact angle distributions are consistent with the geometrical method. However, the obtained contact angle distributions tend to have a narrower span and are considered more realistic compared to the geometrical method. Finally, our results show the potential of the proposed scheme to efficiently obtain wettability maps of porous media using X-ray images of multiphase fluid distributions. The developed workflow can help for more accurate characterization of the wettability map in the porous media using limited experimental data, and hence more accurate digital rock analysis of multiphase flow in porous media.

Holistically-Attracted Wireframe Parsing: From Supervised to Self-Supervised Learning.

This article presents Holistically-Attracted Wireframe Parsing (HAWP), a method for geometric analysis of 2D images containing wireframes formed by line segments and junctions. HAWP utilizes a parsimonious Holistic Attraction (HAT) field representation that encodes line segments using a closed-form 4D geometric vector field. The proposed HAWP consists of three sequential components empowered by end-to-end and HAT-driven designs: (1) generating a dense set of line segments from HAT fields and endpoint proposals from heatmaps, (2) binding the dense line segments to sparse endpoint proposals to produce initial wireframes, and (3) filtering false positive proposals through a novel endpoint-decoupled line-of-interest aligning (EPD LOIAlign) module that captures the co-occurrence between endpoint proposals and HAT fields for better verification. Thanks to our novel designs, HAWPv2 shows strong performance in fully supervised learning, while HAWPv3 excels in self-supervised learning, achieving superior repeatability scores and efficient training (24 GPU hours on a single GPU). Furthermore, HAWPv3 exhibits a promising potential for wireframe parsing in out-of-distribution images without providing ground truth labels of wireframes.

Study on chip shape and cutting force model of milling process in any direction of space

This paper considers the calculation process for chip shape and cutting force of milling process in any direction of space.In the milling process with the existence of lead and tilt angle, the edges and boundary curves go through the process of one intersection, two intersections, tangency and non intersection in a milling cycle, thus the chip thickness needs to be calculated in various regions. The milling force is calculated by using the differential method. Then by comparing the milling forces when the lead angle is 5° and the tilt angle is 10° with when there is no inclination angle, the influence of inclination angle on machining process is studied. Meanwhile, by comparing the milling forces calculated by geometric analysis method with those calculated by classical Altintas model, the validity of the proposed method is verified. In addition, by comparing the milling forces obtained using the classical Altintas model with those obtained in published literature, the rationality of the method is further demonstrated.

The influence of combined effects of hyperbaria and hyperoxia on human heart rate variability during exercise strain

With the participation of 8 male volunteers, the dynamics of values of heart rate autonomic regulation were studied at response to physical load on a bicycle ergometer twice: both respirating by the room air under normobaric environment and simulating effects of the altered hyperoxic respiratory gas mixture (HRGM) by the rebreathe respiration methods from a rebreather at the high-pressure chamber (at «depth» 7 m). The devices and methods of Holter electrocardiogram monitoring were used under 24 hours research. The specialized software to analyze the data was used. The electrocardiogram (ECG) and calculated time series of cardiac intervals data obtained were subjected to mathematical processing to calculate statistical and spectral values of heart rate variability (HRV). Additionally, the geometric and nonlinear analysis methods of HRV were investigated. It has been established that influencing factors (compound and pressure of the HRGM) affect the autonomic regulation of heartbeats both at rest and during physical load. Clinical practitioners the HRV values are studied at rest and during strictly regulated tests, i.e. in stationary conditions. The analysis of non-stationary processes, for example, when it is necessary to continuously analyze data, the so-called transient processes under increasing psychological stress, to assess changes in the autonomic regulation of the heart during breathing of gas mixtures with different compositions (hypoxic therapy, hyperbaric oxygenation, etc.), and, especially during physically upload are used the methods of nonlinear and geometric analysis of HRV that are independent of the degree of nonstationary processes and, to some extent, of artifactual cardiac intervals. During the breathing the respiratory gas mixtures with an increased substance of O2 under conditions of high pressure, the activity of the parasympathetic branches of the autonomic nervous system (ANS) significantly increases. The nonlinear dynamics indexes reflect significant differences in the activity of autonomic components under experimental conditions in the direction of strengthening the parasympathetic links of the ANS. The use of nonlinear analysis values is more acceptable when evaluating obtained of non-stationary processes. In general, the study confirms that the regulatory response to the effects of hyperbaria and hyperoxia when performing a bicycle ergometer test with stepwise increase exercise strain is manifested by the prevalence of the activity of the parasympathetic part of the ANS autonomic regulation of cardiac rhythm compared to regular room air and barometric pressure.

Matrix analysis method for evaluation of lens parameters influence in polarization transmission.

Most studies on the influence of lens parameters in polarization transmission have been carried out in the traditional geometric analysis method, which has the problems of low accuracy and complicated calculation. In this paper, taking the Galileo beam expanding system as an example, a matrix analysis method is proposed to characterize the process of polarization transmission, and derived the polarization azimuth deflection equation. The numerical simulations of the matrix analysis method and the geometric analysis method are compared with the Zemax simulations and the experiments. The variance of the matrix analysis method is compared with the geometric analysis method under four parameters of the lens. It turns out that the numerical simulation results of the two methods are consistent with the Zemax simulation and the experiments. The variance of the matrix analysis method is mostly smaller than that of the geometric analysis method, which further shows that the matrix analysis method is closer to the Zemax simulations and the experiments, and the accuracy is higher.

Optimal negative sequence current suppression strategy without phase‐locked loop based on the control of clustered new energy power stations

AbstractIn the context of extremely uneven sources and loads in China, several large‐scale power transmission systems have been established. Affected by the small equivalent impedance of the system, the increase of negative sequence currents during open‐phase operation has seriously threatened the stable operation of synchronous generators. The necessity of negative sequence current suppression is particularly prominent. To address the above issues, this paper analyzes the feasible negative sequence suppression capacity of the grid‐connected inverter under the principle of positive sequence priority. Using the geometric analysis method to determine the optimal suppression capacity. The none‐phase‐locked loop (PLL) control method is used to improve the response speed and form the negative sequence current suppression strategy adapted to the open‐phase operation period. A simulation model was built in PSCAD to verify the effectiveness of the proposed strategy. The result shows that the suppression strategy has a faster response than the conventional PLL control. In scenarios with large negative sequence currents to be suppressed, a maximum suppression effect of approximately 63% can be achieved. Compared with the traditional suppression capacity selection, the strategy in this paper can reduce the residual of negative sequence current by about 10% at most. The negative sequence currents intruding into the generator can be effectively suppressed without additional devices.

Design and analysis of a continuum manipulator for use in narrow spaces

PurposeThis paper aims to present a kinematics analysis method and statics based control of the continuum robot with mortise and tenon joints to achieve better control performance of the robot.Design/methodology/approachThe kinematics model is derived by the geometric analysis method under the piecewise constant curvature assumption, and the workspace and dexterity of the proposed robot are analyzed to optimize its structure parameters. Moreover, the statics model is established by the principle of virtual work, which is used to analyze the mapping relationship between the bending deformation and the applied forces/torques. To improve the control accuracy of the robot, a model-based controller is put forward.FindingsResults of the experiments verify the feasibility of the proposed continuum structure and the correctness of the established model and the control method. The force deviation between the theoretical value and the actual value is relatively small, and the mean value of the deviation between the driving forces is only 0.46 N, which verify the established statics model and the controller.Originality/valueThe proposed model and motion controller can realize its accurate bending control with a few deviations, which can be used as the reference for the motion planning and dynamic model of the continuum robot.

Relation between sampling, sensitivity and precision in strain mapping using the Geometric Phase Analysis method in Scanning Transmission Electron Microscopy

The sensitivity and the precision of the Geometric Phase Analysis (GPA) method for strain characterization is a topic widely discussed in the literature and is usually difficult to quantify. Indeed, the GPA precision is intricately linked to the resolution of the strain maps defined when masking the periodic reflections in Fourier space. In this study an additional parameter, sampling, is proposed to be analyzed regarding the precision of GPA by developing the concept of a phase noise in the GPA equations. Both experimentally and theoretically, the following article demonstrates how the precision, and the sensitivity of the GPA method is improved when using a larger pixel spacing to record an electron micrograph in Scanning Transmission Electron Microscopy (STEM). The counterintuitive concept of increasing the field of view to improve the GPA precision results is an extension of the application of strain characterization methods in STEM towards low deformation levels.

Geometric phase analysis for characterization of 3D morphology of carbon fiber reinforced composites

In carbon fiber-reinforced resin matrix composites, differences in the mechanical properties of carbon fibers and matrix resins can lead to differences in height, causing step faults at the interphase during grinding and polishing. Accurately and efficiently characterizing the step height at the interphase is crucial for analyzing the mechanical properties and residual stress distribution of the composite materials. In this paper, an orthogonal grating, with a frequency of 10,000 lines/mm, was prepared on the surface of the composite material using the SEM electron beam grating technique. The surface morphology of the T700 carbon fiber-reinforced epoxy resin matrix composite was analyzed using the geometric phase analysis method. The average step height between the fiber and matrix was found to be 128.6 nm. Moreover, the geometric phase analysis method can provide a morphology distribution map within the range of 155 × 100 μm2. This research will provide an effective way to quantitative characterization of three-dimensional surface morphology of composite materials.