Diameter Error Research Articles

A Fabrication Method for Realizing Vertically Aligned Silicon Nanowires Featuring Precise Dimension Control

Silicon nanowires (SiNWs) have garnered considerable attention in the last few decades owing to their versatile applications. One extremely desirable aspect of fabricating SiNWs is controlling their dimensions and alignment. In addition, strict control of surface roughness or diameter modulation is another key parameter for enhanced performance in applications such as photovoltaics, thermoelectric devices, etc. This study investigates a method of fabricating silicon nanowires using electron beam lithography (EBL) and the deep reactive ion etching (DRIE) Bosch process to achieve precisely controlled fabrication. The fabricated nanowires had a pitch error within 2% of the pitch of the direct writing mask. The maximum error in the average diameter was close to 25%. The simplified two-step method with tight control of the dimensions and surface tunability presents a reliable technique to fabricate vertically aligned SiNWs for some targeted applications.

Optimization of FDM 3D Printer Process Parameters to Minimize Dimensional Errors with PLA Material Using Response Surface Methodology

This paper presents a response surface methodology to fit a second-order response surface model aimed to finding process parameters to minimize length error (LE) and diameter error of the cylindrical shafts (DE) in fused deposition modeling (FDM) using polylactic acid (PLA) material. The process parameters in this study included layer height (LH), which varied from 0.1 to 0.4 mm, and print speed (PS), which ranged from 20 to 60 mm/s, while other parameters were set to constant values. The results showed that optimal process parameters obtained in this study significantly lower dimensional errors than the initial parameterization recommended by UltiMaker Cura software.

Is the presence of peripapillary hyperreflective ovoid mass-like structures (PHOMS) in children related to the optic disc area, scleral canal diameter and refractive status?

Peripapillary hyperreflective ovoid mass-like structures (PHOMS) have been recently described on optical coherence tomography (OCT) scans of the optic nerve. We aim to determine if there is a causal relationship between OCT measurements of the optic disc area (DA), scleral canal diameter (SCD) and refractive error (spherical equivalent, SE) on the presence of PHOMS. Retrospective analysis of OCT scans which were graded for the presence or absence of PHOMS in children with suspected papilledema was undertaken. Data on disc area, DA (mm2) and scleral canal diameter, SCD (µm) were obtained from OCT scans. Statistical analysis was performed on two subgroups: unilateral PHOMS vs contralateral control; all eyes with PHOMS vs all eyes without PHOMS (controls). Logistic regression analysis was performed. In unilateral PHOMS (n = 32), there was a non-significant tendency towards a larger DA and SCD in the eye with PHOMS (3.33mm2, 1701 µm) compared to the contralateral eye in the same patient (2.83mm2, 1556 µm). Wider analysis of all eyes with PHOMS (n = 116) versus all eyes without (n = 104) showed there was a significant difference between the DA (3.38mm2 versus 2.65mm2 p = <.0001) and SCD (1763 µm versus 1571 µm, p = <.0001). Logistic regression showed that SCD made a significant contribution to predicting the presence of PHOMS (OR 1.0042, p = 0.0017). PHOMS are frequently seen in pseudopapilledema. It would be useful to understand their pathophysiology as an accurate diagnosis in the context of the asymptomatic paediatric population is crucial. We report that a wider scleral canal diameter was significantly associated with the presence of PHOMS.

Physics-informed and data-driven hybrid method for transmission accuracy design optimization of planetary roller screw mechanism

The planetary roller screw mechanism (PRSM) faces an ever-increasing precision transmission demand in current advanced equipment. The relationship between machining errors and transmission accuracy remains elusive due to the over-simplified physical models and small-sample experimental datasets. This work proposes a physics-informed and data-driven hybrid strategy for PRSM transmission accuracy evaluation and tolerance optimization. In the physical model, a PRSM transmission accuracy model is developed to calculate transmission error that considers 16 machining errors in eccentric, nominal diameter, pitch, flank angle, and roller consistency. In the dataset establishment, thread profile measurements and dynamic leadscrew inspections are conducted for the machining error and transmission accuracy data acquisition. A data augmentation approach combining the physical model with the generative adversarial network is utilized to predict travel deviation, variations, and axial backlash and estimate machining error contribution with the small-sample experimental dataset. It is firstly found that the roller consistency of nominal diameter significantly affects PRSM travel variation V2π with a 17.3 % importance value. With the developed framework, the key tolerances for screw, roller, nut, and roller consistency are optimized toward a typical precision transmission requirement using the non-dominated sorting genetic algorithm. It also provides a tolerance grade recommendation table with PRSM transmission accuracy level in engineering practice.

Influence of input parameters on the measurement accuracy of external clamp-on ultrasonic flowmeters: An experimental study

Abstract This study comprehensively evaluated the performance of clamp-on ultrasonic gas flowmeters at a natural gas field. The research focused on the influence of key input parameters on flow measurement accuracy during practical application of the instrument and proposed specific measures to improve measurement results. It was found that errors in outer diameter and wall thickness not only lead to flow calculation inaccuracies but also directly impact the propagation path of ultrasonic waves. Therefore, accurate input parameters are crucial to ensure precise flow results. Additionally, the study revealed that changes in installation distance have minimal effects on flow measurement results and adjustments can be made as needed to obtain better signal parameters. Variations in input temperature and pressure mainly affect the conversion coefficient from operating conditions to standard conditions, with minor impacts on flow velocity and operating flow rate. Thus, the velocity ratio method can be considered during on-site calibration to mitigate the effects of temperature and pressure changes.

Pixel-wise Phase Map Fusion Technique for High Dynamic Range 3-D Shape Measurement

Abstract Digital fringe projection technologies have been extensively applied in 3-D shape measurements. However, it is still limited to achieve accurate 3-D reconstruction of high reflective surfaces. To circumvent this problem, we propose a complete framework to realize pixel-by-pixel phase post-compensation of overexposed points, including the construction of hardware system and the guidelines of algorithm design. First, a virtual binocular vision system is established. Second, based on the fundamentals of projective and spatial transformation, three robust algorithms with low computational complexity are devised to generate a fused phase map that overcomes the information loss due to overexposure. Furthermore, experiments are conducted to evaluate the performance of the proposed method. Qualitative experiment results show that the presented technique achieve a similar surface coverage compared with the other two mainstream methods, but is superior to them in terms of measurement efficiency (13 images vs. 144 images, 13 images vs. 32 images). Quantitative experimentation further verifies the feasibility of our method in precise 3-D measurement, with sphere diameter errors of 0.0367mm and 0.0361mm, spherical centroid distance error of 0.0269mm, and plane distance error of 0.0186mm.

Additive Manufacturing of Ceramic Reference Spheres by Stereolithography (SLA)

Additive Manufacturing (AM) is advancing technologically towards the production of components for high-demand mechanical applications with stringent dimensional accuracy, leveraging metallic and ceramic raw materials. The AM process for ceramic components, known as Ultraviolet Laser Stereolithography (SLA), enables the fabrication of unique parts or small batches without substantial investments in molds and dies, and avoids the problems associated with traditional manufacturing, which involves multiple stages and final machining for precision. This study addresses the need to produce reference elements or targets for metrological applications, including verification, adjustment, or calibration of 3D scanners and mid- to high-range optical sensors. Precision spheres are a primary geometry in this context due to their straightforward mathematical definition, facilitating rapid and accurate error detection in equipment. Our objective is to exploit this novel SLA process along with the advantageous optical properties of technical ceramics (such as being white, matte, lightweight, and corrosion-resistant) to materialize these reference objects. Specifically, this work involves the fabrication of alumina hemispheres using SLA. The manufacturing process incorporates four design variables (wall thickness, support shape, fill type, and orientation) and one manufacturing variable (the arrangement of spheres on the printing tray). To evaluate the impact of the design variables, dimensional and geometric parameters (GD&amp;T), including diameters, form errors, and their distribution on the surface of the sphere, have been characterized. These measurements are conducted with high accuracy using a Coordinate Measuring Machine (CMM). The study also examines the influence of these variables in the dimensional and geometric accuracy of the spheres. Correlations between various parameters were identified, specifically highlighting critical factors affecting process precision, such as the position of the piece on the print tray and the wall thickness value. The smallest diameter errors were recorded at the outermost positions of the tray (rear and front), while the smallest shape errors were found at the central position, in both cases with errors in the range of tens of micrometers. In any case, the smallest deformations were observed with the highest wall thickness (2 mm).

Numerical analysis of atomization characteristics of fuel-jet in crossflow

In order to study the breakup and atomization mechanisms of the fuel-jet in air crossflow and realize the accurate and controllable atomization effect of fuel, this paper proposes a method by coupling the large eddy simulation method and the VOF to DPM method. The results show that the breakup and atomization of the fuel-jet are mainly caused by the Rayleigh–Taylor (R–T) unstable surface wave and the Kelvin–Helmholtz (K–H) instability. The density of fuel-particles is higher near the central region of the fuel jet trajectory, decreasing as distance from the central region increases. As the momentum ratio increases, the penetration depth of the fuel-jet column also increases, resulting in a more concentrated spatial distribution of fuel particles. Conversely, with a lower momentum ratio, the spatial distribution of fuel particles becomes more uniform. For the spatial distribution of fuel particles, a new mathematical model is established to characterize the spatial distribution boundary of fuel particles. At the same momentum ratio, the higher the air velocity, the smaller the average particle diameter. At the same Weg number, the higher the fuel-jet velocity, the higher the average particle diameter. The relative error of the average particle diameter between the experiment and numerical simulation is very small, which is 6.4%.

Investigation on effect of cryogenic cooling on the hole-making of CFRP with conventional PCD tool and textured PCD tool

Carbon fiber reinforced polymer (CFRP) has obtained the widespread use in significant basic parts owing to its excellent properties. Different methods including the conventional PCD tool using dry machining (CPD), the conventional PCD tool with CO2 cryogenic cooling (CPC), and the textured PCD tool with CO2 cryogenic cooling (TPC), were introduced to investigated their effects on the holes-making performance. Results demonstrated that the obtained average entrance diameter and relative error of different spindle speeds using the CPC were about 4001 to 4005.4 μm and 0.025% to 0.65%, respectively. Dimensional accuracy and surface edge quality of entrance hole can be better improved by the CPC method. It was found that the cryogenic cooling method showed the remarkable effect in improving the anti-adhesion of tools than compared to the dry machining. Additionally, results indicated that the cryogenic cooling resulted in the significant fiber fractures and many pits inside the hole wall and the CPD method can help to improve the inner hole wall quality.

ASPEN study case: Real time in situ apples detection and characterization

Due to an increasing demand for food and pressures on our ecosystem, mechanisation and automation in agriculture has been proposed as one of the main solutions to the problems associated with overpopulation given today's life standards. To encourage the use of new technologies and bridge the gap between plant and computer science, here we validate an open-source pipeline capable of predicting real time in situ fruit characteristics, specifically in this case for apples. Using Agroscope's phenotyping tool (ASPEN), we achieve an average precision at intercept over union of 50 % of 0.75 when using YOLOv8 - m as the object detection algorithm, and with thanks to the use of multiple sensors, we find an average diameter error of 4.4 mm in the task of apple size determination. Our research demonstrates that although the pipeline tends to underestimate the actual fruit size, size estimation cannot only be used to determine the size of apples per scan, but also to track temporal apple size distribution in 4 different varieties. This research supports ASPEN in potentially replacing traditional field measurements, also suggesting that other traits could also be digitally measured for standard orchard phenotyping, either for scientific or agricultural output goals. Finally, we make publicly available a new dataset of more than 600 images (Agroscope_apple dataset) and a pre-trained model based on YOLOv8 and specifically trained for the in-situ apple detection task. By doing so, we hope to increase the accessibility and use of new technologies in the field of agriculture.

Experimental and Finite Element Analysis of Compressive Strength and Diametral Tensile Strength of Luting Cement: An In Vitro Study.

Background Strength parameters greatly influence the selection of luting agents. This study compared the compressive and diametral tensile strengths (DTS) of three luting cements. Materials and methods Three luting cements, conventional glass ionomer (CGI), resin-modified glass ionomer (RMGI), and resin cement (RC), were tested for compressive strength and DTS. Forty-two standardized specimens were prepared, measuring 4 mm by 6 mm for compressive tests and 6 mm by 3 mm for diametral tensile tests. The luting materials were prepared according to the manufacturers' instructions. Result Experimental mean compressive and diametral strengths and standard errors were calculated for each luting agent (n = 10). Analysis of variance was computed (p < 0.05), and multiple comparison tests were performed. RC showed significantly higher compressive strengths and DTS among the three tested luting cements, while the CGI showed the least. The results obtained by finite element analysis (FEA) for both tests closely matched the experimental results. Conclusion In this study, it was concluded that the mean compressive strength and DTSvalues of all three luting cements were significantly different. The resin luting cement exhibited the highest compressive strength and DTS, while the CGI exhibited the least.

Determination of rotation center and diameter of femoral heads using off-the-shelf augmented reality hardware for navigation

In total hip arthroplasty (THA), determining the center of rotation (COR) and diameter of the hip joint (acetabulum and femoral head) is essential to restore patient biomechanics. This study investigates on-the-fly determination of hip COR and size, using off-the-shelf augmented reality (AR) hardware. An AR head-mounted device (HMD) was configured with inside-out infrared tracking enabling the determination of surface coordinates using a handheld stylus. Two investigators examined 10 prosthetic femoral heads and cups, and 10 human femurs. The HMD calculated the diameter and COR through sphere fitting. Results were compared to data obtained from either verified prosthetic geometry or post-hoc CT analysis. Repeated single-observer measurements showed a mean diameter error of 0.63 mm ± 0.48 mm for the prosthetic heads and 0.54 mm ± 0.39 mm for the cups. Inter-observer comparison yielded mean diameter errors of 0.28 mm ± 0.71 mm and 1.82 mm ± 1.42 mm for the heads and cups, respectively. Cadaver testing found a mean COR error of 3.09 mm ± 1.18 mm and a diameter error of 1.10 mm ± 0.90 mm. Intra- and inter-observer reliability averaged below 2 mm. AR-based surface mapping using HMD proved accurate and reliable in determining the diameter of THA components with promise in identifying COR and diameter of osteoarthritic femoral heads.

Automated Phenotypic Trait Extraction for Rice Plant Using Terrestrial Laser Scanning Data.

To quickly obtain rice plant phenotypic traits, this study put forward the computational process of six rice phenotype features (e.g., crown diameter, perimeter of stem, plant height, surface area, volume, and projected leaf area) using terrestrial laser scanning (TLS) data, and proposed the extraction method for the tiller number of rice plants. Specifically, for the first time, we designed and developed an automated phenotype extraction tool for rice plants with a three-layer architecture based on the PyQt5 framework and Open3D library. The results show that the linear coefficients of determination (R2) between the measured values and the extracted values marked a better reliability among the selected four verification features. The root mean square error (RMSE) of crown diameter, perimeter of stem, and plant height is stable at the centimeter level, and that of the tiller number is as low as 1.63. The relative root mean squared error (RRMSE) of crown diameter, plant height, and tiller number stays within 10%, and that of perimeter of stem is 18.29%. In addition, the user-friendly automatic extraction tool can efficiently extract the phenotypic features of rice plant, and provide a convenient tool for quickly gaining phenotypic trait features of rice plant point clouds. However, the comparison and verification of phenotype feature extraction results supported by more rice plant sample data, as well as the improvement of accuracy algorithms, remain as the focus of our future research. The study can offer a reference for crop phenotype extraction using 3D point clouds.

A Three-Dimensional Substation Reconstruction Method Based on Scenery Point Clouds

Abstract 3D modeling is the technical foundation for 3D visualization of substations, and accurate 3D panoramic modeling of substations is the key to achieving intelligent operation and maintenance of substations. However, the reuse rate of the model is low, resulting in low system modeling efficiency and bad model accuracy, which cannot fully leverage the advantages of 3D real scenery reconstruction technology. To address the aforementioned problems, this paper proposes a basic process and method for constructing a 3D model of a substation based on point cloud data, and provides an example of 3D reconstruction of the substation, which is then validated from three aspects. The experiment shows that the proposed process and method can achieve complete and accurate 3D reconstruction of substations, with a detail completeness of 98% and an outer diameter error of only 0.13 mm for transformer bushing leads.

Zonular fibre Insertion-to-Limbus Distance (ZLD): normative data to assess lens position and diagnose ectopia lentis

PurposeSubluxation of the crystalline lens (Ectopia Lentis, EL) can lead to significant visual impairment and serves as a diagnostic criterion for genetic disorders such as the Marfan syndrome. There is no established criterion to diagnose and quantify EL. We prospectively investigated the distance between the zonular fibre insertion and the limbus (ZLD) in healthy subjects as a parameter to assess the position of the lens, quantify EL and provide normative data.MethodsThis prospective, observational, cross-sectional study includes one-hundred-fifty eyes of 150 healthy participants (mean age 28 years, range 4–68). Pupils were dilated with tropicamide 0.5% and phenylephrine 2.5% eyedrops. ZLD was measured in mydriasis at the slit lamp as the distance between the most central visible insertions of the zonular fibres on the lens surface and the corneoscleral limbus. Vertical pupil diameter (PD) and refractive error were recorded. If zonular fibre insertions were not visible, the distance between limbus and the pupillary margin was recorded as ZLD.Results145 right and 5 left eyes were examined. 93% of study subjects were Caucasian, 7% were Asian. In eyes with visible zonular fibre insertions (n = 76 eyes), ZLD was 1.30 ± 0.28 mm (mean ± SD, range 0.7–2.1) and PD was 8.79 ± 0.57 mm (7.5–9.8). In the remaining 74 eyes, ZLD was 1.38 ± 0.28 mm (0.7–2.1), and PD was 8.13 ± 0.58 mm (6.7–9.4). For all eyes, ZLD was 1.34 ± 0.29 mm (0.7–2.1), and PD was 8.47 ± 0.66 mm (6.7–9.8). Refractive error and sex did not significantly affect ZLD. Smaller PD and older age were associated with larger ZLD (P < 0.001 and P = 0.036, respectively).ConclusionAverage ZLD was 1.34 mm in eyes of healthy subjects. Older age correlated with larger ZLD. These normative data will aid in diagnosing and quantifying EL.

Nondestructive Inspection and Quantification of Select Interface Defects in Honeycomb Sandwich Panels.

Honeycomb sandwich panels are utilized in many industrial applications due to their high bending resistance relative to their weight. Defects between the core and the facesheet compromise their integrity and efficiency due to the inability to transfer loads. The material system studied in the present paper is a unidirectional carbon fiber composite facesheet with a honeycomb core with a variety of defects at the interface between the two material systems. Current nondestructive techniques focus on defect detectability, whereas the presented method uses high-frequency ultrasound testing (UT) to detect and quantify the defect geometry and defect type. Testing is performed using two approaches, a laboratory scale immersion tank and a novel portable UT system, both of which utilize only single-side access to the part. Coupons are presented with defects spanning from 5 to 40 mm in diameter, whereas defects in the range of 15-25 mm and smaller are considered below the detectability limits of existing inspection methods. Defect types studied include missing adhesive, unintentional foreign objects that occur during the manufacturing process, damaged core, and removed core sections. An algorithm is presented to quantify the defect perimeter. The provided results demonstrate successful defect detection, with an average defect diameter error of 0.6 mm across all coupons studied in the immersion system and 1.1 mm for the portable system. The best accuracy comes from the missing adhesive coupons, with an average error of 0.3 mm. Conversely, the worst results come from the missing or damaged honeycomb coupons, with an error average of 0.7 mm, well below the standard detectability levels of 15-25 mm.

Experimental and Simulation Research on Femtosecond Laser Induced Controllable Morphology of Monocrystalline SiC.

Silicon carbide (SiC) is utilized in the automotive, semiconductor, and aerospace industries because of its desirable characteristics. Nevertheless, the traditional machining method induces surface microcracks, low geometrical precision, and severe tool wear due to the intrinsic high brittleness and hardness of SiC. Femtosecond laser processing as a high-precision machining method offers a new approach to SiC processing. However, during the process of femtosecond laser ablation, temperature redistribution and changes in geometrical morphology features are caused by alterations in carrier density. Therefore, the current study presented a multi-physics model that took carrier density alterations into account to more accurately predict the geometrical morphology for femtosecond laser ablating SiC. The transient nonlinear evolutions of the optical and physical characteristics of SiC irradiated by femtosecond laser were analyzed and the influence of laser parameters on the ablation morphology was studied. The femtosecond laser ablation experiments were performed, and the ablated surfaces were subsequently analyzed. The experimental results demonstrate that the proposed model can effectively predict the geometrical morphology. The predicted error of the ablation diameter is within the range from 0.15% to 7.44%. The predicted error of the ablation depth is within the range from 1.72% to 6.94%. This work can offer a new way to control the desired geometrical morphology of SiC in the automotive, semiconductor, and aerospace industries.

Tumor conspicuity enhancement-based segmentation model for liver tumor segmentation and RECIST diameter measurement in non-contrast CT images

Background and objectiveLiver tumor segmentation (LiTS) accuracy on contrast-enhanced computed tomography (CECT) images is higher than that on non-contrast computed tomography (NCCT) images. However, CECT requires contrast medium and repeated scans to obtain multiphase enhanced CT images, which is time-consuming and cost-increasing. Therefore, despite the lower accuracy of LiTS on NCCT images, which still plays an irreplaceable role in some clinical settings, such as guided brachytherapy, ablation, or evaluation of patients with renal function damage. In this study, we intend to generate enhanced high-contrast pseudo-color CT (PCCT) images to improve the accuracy of LiTS and RECIST diameter measurement on NCCT images. MethodsTo generate high-contrast CT liver tumor region images, an intensity-based tumor conspicuity enhancement (ITCE) model was first developed. In the ITCE model, a pseudo color conversion function from an intensity distribution of the tumor was established, and it was applied in NCCT to generate enhanced PCCT images. Additionally, we design a tumor conspicuity enhancement-based liver tumor segmentation (TCELiTS) model, which was applied to improve the segmentation of liver tumors on NCCT images. The TCELiTS model consists of three components: an image enhancement module based on the ITCE model, a segmentation module based on a deep convolutional neural network, and an attention loss module based on restricted activation. Segmentation performance was analyzed using the Dice similarity coefficient (DSC), sensitivity, specificity, and RECIST diameter error. ResultsTo develop the deep learning model, 100 patients with histopathologically confirmed liver tumors (hepatocellular carcinoma, 64 patients; hepatic hemangioma, 36 patients) were randomly divided into a training set (75 patients) and an independent test set (25 patients). Compared with existing tumor automatic segmentation networks trained on CECT images (U-Net, nnU-Net, DeepLab-V3, Modified U-Net), the DSCs achieved on the enhanced PCCT images are both improved compared with those on NCCT images. We observe improvements of 0.696–0.713, 0.715 to 0.776, 0.748 to 0.788, and 0.733 to 0.799 in U-Net, nnU-Net, DeepLab-V3, and Modified U-Net, respectively, in terms of DSC values. In addition, an observer study including 5 doctors was conducted to compare the segmentation performance of enhanced PCCT images with that of NCCT images and showed that enhanced PCCT images are more advantageous for doctors to segment tumor regions. The results showed an accuracy improvement of approximately 3%–6%, but the time required to segment a single CT image was reduced by approximately 50 %. ConclusionsExperimental results show that the ITCE model can generate high-contrast enhanced PCCT images, especially in liver regions, and the TCELiTS model can improve LiTS accuracy in NCCT images.

Deep learning-based frequency-multiplexing composite-fringe projection profilometry technique for one-shot 3D shape measurement

The pursuit of precise and efficient 3D shape measurement has long been a focal point within the fringe projection profilometry (FPP) domain. However, achieving precise 3D reconstruction for isolated objects from a single fringe image remains a challenging task in the field. In this paper, a deep learning-based frequency-multiplexing (FM) composite-fringe projection profilometry (DFCP) is proposed, where an end-to-end absolute phase retrieval network (APR-Net) is trained to directly recover the absolute phase map from a FM composite fringe pattern. The obtained absolute phase map exhibits exceptional precision and is devoid of spectrum crosstalk or leakage disturbance typically encountered in traditional FM techniques. APR-Net is intricately crafted, incorporating a nested strategy along with the concept of centralized information interaction. A diverse dataset encompassing various scenarios and free from spectrum aliasing is assembled to guide the training process. A seven-map loss calculation scheme is employed to guide the training process, of which the efficacy is proved through ablation experiments. In the first qualitative experiment, DFCP demonstrates comparable phase accuracy to ground truths with 47 fewer projected images, outperforming other three methods with mean absolute phase errors of 0.0052 rad, 0.1761 rad, 0.0169 rad, and 0.0139 rad. The second qualitative experiment and the quantitative evaluation respectively prove DFCP’s capability in high dynamic range 3D measurement and in precise 3D measurement, with sphere diameter errors of 0.0780 mm and 0.0726 mm, and a spherical centroid distance error of 0.0555 mm.

A method for the prediction of the atomization diameter distribution of the spray generated by swirl nozzles

Atomization is an indispensable process for achieving high-efficiency conversion in various energy applications. This study proposes a novel and simplified method to predict the droplet diameter distribution along the spray direction during atomization by swirl nozzles. The method considers the droplet breakup and coalescence and consists of three sub-models, i.e., the primary breakup model, the secondary breakup model, and the velocity model. The prediction method is verified by droplet sizing experiments using typical swirl nozzles. Combining the experimental results, the atomization process from fluid to droplets is analyzed in-depth. Results show that the present method can predict the droplet diameter distribution along the spray direction, with an average error of droplet diameter of approximately 7.7%. The effects of the orifice diameter and water supply pressure of nozzles on droplet diameter distribution are discussed. The droplet diameter decreases in the whole spray field as the water supply pressure rises. When the orifice diameter increases, the mass flow rate and Sauter mean diameter increase in the near-orifice region. However, the droplet diameter difference in nozzles reduces as the position is far away from the orifice. The proposed method can aid the design of some critical energy devices containing the atomization process.