Accurate Shape Research Articles

Cost-Effective Simulations of Vibrationally-Resolved Absorption Spectra of Fluorophores with Machine-Learning-Based Inhomogeneous Broadening.

The results of electronic and vibrational structure simulations are an invaluable support for interpreting experimental absorption/emission spectra, which stimulates the development of reliable and cost-effective computational protocols. In this work, we contribute to these efforts and propose an efficient first-principle protocol for simulating vibrationally-resolved absorption spectra, including nonempirical estimations of the inhomogeneous broadening. To this end, we analyze three key aspects: (i) a metric-based selection of density functional approximation (DFA) so to benefit from the computational efficiency of time-dependent density function theory (TD-DFT) while safeguarding the accuracy of the vibrationally-resolved spectra, (ii) an assessment of two vibrational structure schemes (vertical gradient and adiabatic Hessian) to compute the Franck-Condon factors, and (iii) the use of machine learning to speed up nonempirical estimations of the inhomogeneous broadening. In more detail, we predict the absorption band shapes for a set of 20 medium-sized fluorescent dyes, focusing on the bright ππ★ S0 → S1 transition and using experimental results as references. We demonstrate that, for the studied 20-dye set which includes structures with large structural variability, the preselection of DFAs based on an easily accessible metric ensures accurate band shapes with respect to the reference approach and that range-separated functionals show the best performance when combined with the vertical gradient model. As far as band widths are concerned, we propose a new machine-learning-based approach for determining the inhomogeneous broadening induced by the solvent microenvironment. This approach is shown to be very robust offering inhomogeneous broadenings with errors as small as 2 cm-1 with respect to genuine electronic-structure calculations, with a total CPU time reduced by 98%.

Experimental investigation of the EDM tools coated with nano-alumina film

ABSTRACT During electrical discharge machining (EDM) drilling of small high-aspect-ratio holes, abnormal discharges between tool flank and workpiece will result in high process instability and poor shape accuracy. In order to solve this problem, dense nano-alumina insulating film is plated on the tool flank based on atomic layer deposition (ALD) to suppress the secondary discharge for the benefit of the tool’s integrity and shape accuracy. Drilling experiments on nickel base superalloy GH4099 workpiece were conducted to test machining effect of the coated brass tool. Experimental results show that it can enhance the process stability and improve the surface topography of the machined holes. The tool wear is reduced by about 21.7%, and the discharge craters and carbon black film along the tool flank are significantly reduced.

Investigating the Manufacturing Process of Heat-Treated Nb3Sn-CICC Conductor for CFETR CSMC Modules

The center solenoid model coil (CSMC) of the China fusion engineering test reactor (CFETR) requires a high heat treatment temperature of 650 °C, which would destroy the insulation layer by carbonization and cause coil failure. To avoid this, using the manufacturing technology and routine process of the ITER center solenoid coil as a reference, in this article, a solution is introduced that is applied for manufacturing the CFETR CSMC module. The coil is heat treated before insulation and after winding. A single turn of the heat-treated coil is separated and the wrapping turn insulation is applied, and then the separated layers are reversed back into the integrated coil. To manufacture the integrated coils, the heat-treated coils are molded. After heat treatment, the interlayer separation distance of the Nb <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> Sn cable-in-conduit conductor in the coil should satisfy the allowable strain range of the superconductor, which is crucial for designing the rotational support structure of the interlayer separation. In addition, to achieve the accurate final shape of the coil and meet the design requirements, as well as to ensure coil contour accuracy after layer by layer separation, the antideformation ability of the coil mold is a key research topic. Herein, mechanical properties of the key components were optimized and numerical calculations and ANSYS simulations were used for statistical analyses. Results from the analyses indicated that the equivalent stress on the device is less than the maximum permissible stress of the raw material. The device was manufactured and compared with a design mold. The overall deformation error was <5%, movement error of the electric frame was <2%, rotation error of rotating was less than ±1° per 360°, levelness between the upper and lower platform was <1 mm, and motion error was less than ±1 mm per 100 mm. These results demonstrated the optimized structure design of the device. In the as-obtained device, the coil could separate a single turn and wrapping turn insulation could be applied. Parameters of the manufactured coil satisfied all the CSMC design requirements; these results indicate that the proposed device is suitable for manufacturing the CFETR CSMC module coil.

Shape Sensing of Flexible Robots Based on Deep Learning

In this article, a deep learning method for the shape sensing of continuum robots based on multicore fiber bragg grating (FBG) fiber is introduced. The proposed method, based on an artificial neural network (ANN), differs from traditional approaches, where accurate shape reconstruction requires a tedious characterization of many characteristic parameters. A further limitation of traditional approaches is that they require either multiple fibers, whose location relative to the centerline must be precisely known (calibrated), or a single multicore fiber whose position typically coincides with the neutral line. The proposed method addresses this limitation and, thus, allows shape sensing based on a single multicore fiber placed off-center. This helps in miniaturizing and leaves the central channel available for other purposes. The proposed approach was compared to a recent state-of-the-art model-based shape sensing approach. A two-degree-of-freedom benchtop fluidics-driven catheter system was built to validate the proposed ANN. The proposed ANN-based shape sensing approach was evaluated on a 40-mm-long steerable continuum robot in both 3-D free-space and 2-D constrained environments, yielding an average shape sensing error of 0.24 and 0.49 mm, respectively. With these results, the superiority of the proposed approach compared to the recent model-based shape sensing method was demonstrated.

Modelling and analysis of the micro-milling of micro-dimpled structures with copying method on glow discharge polymer (GDP)

The surface with micro-dimpled structures on the target ball is helpful for improving nuclear fusion efficiency in inertial confinement fusion. Micro ball-end milling with copying method can provide a simple and effective option in machining micro dimples with high surface finish and geometry (dimension and shape) accuracy. In this paper, based on the established geometric error model, the influence of geometric errors and structural parameters of the machine tool on the dimple dimension and shape was first studied. Next, a model expressing the trajectory of cutting edge for simulating dimple geometry generated by ball-end milling was built. The model was used to analyze the effect of the spindle attitude, tool run-out and deflection deformation on the dimple dimension and shape. Micro ball-end milling tests were carried out, and the dimension, shape and cross-section profile of simulated and milled dimples were compared. A good correspondence between the simulated and milled dimple was observed, the largest error is 6.87%. Finally, from surface morphologies and surface roughness of the milled dimples, it was found that spindle attitude, axial feed rate are the main factors affecting the surface quality of micro dimple machined using micro ball-end milling with copying method. In particular, the axial feed rate need being optimized, reducing the effect of cutting edge quality and avoiding the deterioration of dimple surface and contour caused by a high feed rate. This research is of great significance for fabricating micro-dimpled functional surfaces by surface texturing based on milling methods.

Evaluating 3D human face reconstruction from a frontal 2D image, focusing on facial regions associated with foetal alcohol syndrome

Foetal alcohol syndrome (FAS) is a preventable condition caused by maternal alcohol consumption during pregnancy. The FAS facial phenotype is an important factor for diagnosis, alongside central nervous system impairments and growth abnormalities. Current methods for analysing the FAS facial phenotype rely on 3D facial image data, obtained from costly and complex surface scanning devices. An alternative is to use 2D images, which are easy to acquire with a digital camera or smart phone. However, 2D images lack the geometric accuracy required for accurate facial shape analysis. Our research offers a solution through the reconstruction of 3D human faces from single or multiple 2D images. We have developed a framework for evaluating 3D human face reconstruction from a single-input 2D image using a 3D face model for potential use in FAS assessment. We first built a generative morphable model of the face from a database of registered 3D face scans with diverse skin tones. Then we applied this model to reconstruct 3D face surfaces from single frontal images using a model-driven sampling algorithm. The accuracy of the predicted 3D face shapes was evaluated in terms of surface reconstruction error and the accuracy of FAS-relevant landmark locations and distances. Results show an average root mean square error of 2.62 mm. Our framework has the potential to estimate 3D landmark positions for parts of the face associated with the FAS facial phenotype. Future work aims to improve on the accuracy and adapt the approach for use in clinical settings. Significance: Our study presents a framework for constructing and evaluating a 3D face model from 2D face scans and evaluating the accuracy of 3D face shape predictions from single images. The results indicate low generalisation error and comparability to other studies. The reconstructions also provide insight into specific regions of the face relevant to FAS diagnosis. The proposed approach presents a potential cost-effective and easily accessible imaging tool for FAS screening, yet its clinical application needs further research.

Investigation of aluminum alloy 6061 in Wire-EDM regarding surface roughness and material removal rate by adopting optimization techniques

Wire-electric discharge machining offers a number of benefits in comparison to traditional manufacturing processes likewise, no obvious mechanical cutting traces also hard and rigid materials can be processed perfectly in WEDM. Since, aluminum alloys are used in aerospace, shipbuilding, breathing gas cylinders for scuba diving, surgical components and automotive industry for their high-strength-to-weight ratio, accurate shapes and dimensions. Through this method, complicated structures made of aluminum alloy are produced in a single setup with incredibly tight tolerances. The present investigation explores WEDM for AA6061 to optimize different process variables for attaining performance measures in terms of maximum MRR and minimum SR. Taguchi’s L18 OA matrix, S/N ratio, ANOVA and Grey Relational Analysis were employed to optimize SR and MRR. It has been noted from ANOVA that pulse on time and peak current are the most influential aspects for MRR and SR with their contributions of 13.33% and 16.25% respectively. Further, the best possible considered parameters setting has been established by applying GRA for MRR and SR are, pulse on time-50µs, pulse off time-13µs and peak current-4 amp.

Development of a New Micro Drilling Tool with H-Shaped Chisel Edge

In order to improve the tool life and micro-hole machining quality, the H-shaped chisel edge micro-drill (HCE-MD) was developed in this paper. The HCE-MD was characterized by the inner edge formed through the chisel edge thinning. In the micro-drilling process, the inner edge can perform positive rake cutting, so the machining area of the workpiece extruded by cutting edge with a negative rake angle is reduced. Based on this, the distribution of rake angle near the chisel edge corner is improved. Then, the HCE-MD was fabricated on the six-axis CNC grinding machine. The grinding process parameters of the micro-drill were optimized based on the orthogonal grinding test and grey relational grade theory. The size and shape accuracy of the micro-drill were controlled by the multi-axis linkage grinding method and the movement-axis micro compensation method. Finally, the 0.25 mm HCE-MD was fabricated with the cutting edge radius of 1.94 μm and the flank surface roughness of 0.25 μm. The drilling performance of HCE-MD was evaluated through comparative drilling experiments. The experimental results show that, compared with common micro drill, the HCE-MD produced lower thrust force and better micro-hole roundness accuracy, and reduced the micro-drill wear on the chisel edge and the flank.

A phase correlation based peak detection method for accurate shape from focus measurements

Estimating a 3D shape from 2D images is a classic computer vision problem. Shape from focus is a commonly used method for this purpose. With shape from focus, 3D depth is estimated using a so-called focus measure operator. Pixel focus follows a Gaussian-like distribution in which the location of the peak is an indicator of the 3D depth. Locating the peak in this distribution is complicated due to noise coming from various sources. We investigate the accuracy of some existing algorithms and introduce a new algorithm based on phase correlation. Phase correlation is a powerful method for finding correlations between signals, especially in a noisy environment. The accuracy and robustness to noise of the proposed method are tested and proven by applying it to synthetic data as well as measurements of a calibration target. The proposed method is over 30% more accurate than comparable methods, yet requires more computational effort.

Research on the Roundness Approximation Search Algorithm of Si3N4 Ceramic Balls Based on Least Square and EMD Methods

This paper aims to obtain the best shape accuracy evaluation algorithm for silicon nitride ceramic balls after lapping, and to extract the initial signal of the ball surface to improve the accuracy and reliability of the algorithm. The research methods of this paper are as follows: Firstly, an analysis of the uniform envelope of the lapping trajectory of ceramic balls is carried out to verify whether the lapping trajectory after processing can achieve a consistent envelope on the balls' surface. On this basis, it is found through experiments that the standard deviation SD between the roundness deviations of different contour sections is small. The value is maintained at approximately 0.03 μm, and the roundness deviation can approximately replace the spherical deviation. Then the different contour sections of the sphere are sampled by the Taylor roundness instrument. Considering the uncertainty, the sampling points of different contour sections are averaged and used as the original signal of the sphere surface. Then the EMD method is used to process the signal to be detected on the sphere surface. The initial signal of the sphere surface is extracted by judging whether the number of ripples Kc obtained by decomposition is greater than the critical value. Then the initial signal is used as the input value of the approximation algorithm. Through the roundness deviation approximation algorithm based on the least square method, the given minimum approximation domain range is finely processed. The divided fine points are used as the center of the circle to intersect with the initial signal. The maximum, minimum, and range of each circle are calculated to obtain the roundness error based on the minimum circumscribed circle, the maximum inscribed circle, and the minimum region method. Finally, the calculated values are compared with those obtained by the traditional algorithm. The experimental results of this paper show that the algorithm is consistent with the roundness error measured by the instrument, compared with the mainstream evaluation criteria. In summary, the conclusions can be drawn as follows: Through a large number of experimental cases and comparative experiments, the algorithm has high accuracy and reliability. The research results of this paper have essential reference significance for accurately evaluating the shape accuracy of ceramic balls in actual production.

The Shape of Jupiter and Saturn Based on Atmospheric Dynamics, Radio Occultations and Gravity Measurements

AbstractThe shape of the two gas giants, Jupiter and Saturn, is determined primarily by their rotation rate, and interior density distribution. It is also affected by their zonal winds, causing an anomaly of O(10 km) at low latitudes. However, uncertainties in the observed cloud‐level wind and the polar radius, translate to an uncertainty in the shape with the same order of magnitude. The Juno (Jupiter) and Cassini (Saturn) missions gave unprecedented accurate gravity measurements, constraining better the uncertainty in the wind structure. Using an accurate shape calculation, and a joint optimization, given both gravity and radio‐occultation measurements, we calculate the possible range of dynamical height for both planets. We find that for Saturn there is an excellent match to the radio‐occultation measurements, while at Jupiter such a match is not achieved. This may point to deviations from a barotropic flow above the cloud level, which might be tested with the forthcoming radio‐occultation measurements by Juno.

3D printing of aluminum oxide via composite extrusion modeling using a ceramic injection molding feedstock

Composite Extrusion Modeling (CEM) is a screw-based material extrusion (MEX) additive manufacturing process that can produce plastic, metal and ceramic parts based on standard injection molding feedstocks. In this work, an aluminum oxide feedstock (Al2O3) originally developed for injection molding is processed via a screw-based MEX process for the first time by depositing the plasticized material in layers on the build platform. In order to identify appropriate process parameters, the feedstock is first characterized to estimate the printable temperature processing window. Initially, the best printable extrusion values were estimated in terms of green part density and dimensional accuracy. Afterwards, different nozzle diameters and layer heights are investigated to further improve the green part density and shape accuracy. An extrusion multiplier of 0.14, nozzle diameter of 0.4 mm and a layer height of 0.1 mm were found to be the optimum process parameters to achieve highly dense green parts with a density of 2.791 ± 0.001 g/cm3. The optimized parts were also debound and sintered and the shrinkage was investigated. A shrinkage of 17.43% in the z direction and 14.08% in the x-y direction was observed, and a density of 3.92 ± 0.0025 g/cm3 was achieved for the sintered parts.

Feed scheduling for time-dependent machining processes by optimization of bulk removal and NC blocks

Time-dependent processes such as CNC fluid jet polishing require feed-rate scheduling through deconvolution of a target removal profile and tool influence function. The dynamic constraints associated with the machine tool driving the process should be considered when solving this numerical problem. This research investigates how material bulk removal affects the scheduled feed-rate and acceleration both in the spatial and time domain, and proposes a method for matching exactly the maximum acceleration with the machine tool limit. Furthermore, the influence of CNC interpolator dynamics is investigated by means of the controller pulse response method. An optimization method for NC blocks is then proposed in order to achieve feed-rates that best match the intended profile. The benefit of bulk removal and NC blocks optimization is validated by fabrication, with and without optimization, of cylindrical Fresnel lenses. Both the shape accuracy and optical performance of the optimally fabricated lens are shown to substantially improve, suggesting that the proposed optimization method has strong potential for industrial application.

Influence of Novel Electromagnetic Strengthening on Mechanical Properties of Spaceborne Elastic Components

Numerous elastic components are widely used in the power drive, vibration control, and pressure compensation of deployable antennas. Thus, the deployment and normal service of the antenna rely on the consistency and stability of their mechanical properties. They offer important support for deployable antenna products to meet the requirements of shape and surface accuracy. This study found that the electromagnetic field can improve the stiffness, hardness, and stability of the space-borne spring. In this experiment, the hardness variance distribution is reduced by 40.79%, the creep resistance is improved by 45.76% to 61.48%, and fatigue life is increased by 69%. With the enhancement of mechanical properties, the uniformity, consistency, and individual differences of the spring are improved. According to the observations of metallographic microstructure, fine grain strengthening and precipitation strengthening mainly contribute to the reinforcing effect. It is found that the electromagnetic field has an important influence on improving the performance stability and consistency of the space-borne elastic element structure, and this technology has great prospects in the future aerospace field.

Research on the Measurement Method of Key Shape and Position Errors of Hemispherical Harmonic Oscillator

Hemispherical resonance gyroscope originated in the 1960s. With its outstanding advantages of high precision, simple structure and long service life, it is increasingly widely used in aerospace, tactical weapons and other fields. The hemispherical resonator, the core part of the gyroscope, is a thin-walled part with high steepness curved surface and hard and brittle material. Limited by the current processing level, it is difficult to obtain good shape and position accuracy, resulting in uneven mass distribution and frequency cracking, which affects the accuracy of the gyroscope. Based on the precision machining of hemispherical resonator, this paper carries out the research on the measurement method of shape and position error, focuses on the measurement method of the roundness and end face of the resonator, uses the cylindricity meter to complete the measurement of the roundness error of the inner and outer hemispherical shell of the resonator, and uses the white light interferometer and the subaperture stitching technology to realize the measurement of the full aperture surface of the end face of the hemispherical shell. This work provides theoretical guidance for subsequent processing and is of great significance to improve the quality of harmonic oscillator.

A Direct Toolpath Constructive Design Method for Controllable Porous Structure Configuration with a TSP-based Sequence Planning Determination

The inherent capabilities of additive manufacturing (AM) to fabricate porous lattice structures with controllable structural and functional properties have raised interest in the design methods for the production of extremely intricate internal geometries. Current popular methods of porous lattice structure design still follow the traditional flow, which mainly consists of computer-aided design (CAD) model construction, STereoLithography (STL) model conversion, slicing model acquisition, and toolpath configuration, which causes a loss of accuracy and manufacturability uncertainty in AM preparation stages. Moreover, toolpath configuration relies on a knowledge-based approach summarized by expert systems. In this process, geometrical construction information is always ignored when a CAD model is created or constructed. To fully use this geometrical information, avoid accuracy loss and ensure qualified manufacturability of porous lattice structures, this paper proposes a novel toolpath-based constructive design method to directly generate toolpath printing file of parametric and controllable porous lattice structures to facilitate model data exchange during the AM preparation stages. To optimize the laser jumping route between lattice cells, we use a hybrid travelling salesman problem (TSP) solver to determine the laser jumping points on contour scans. Four kinds of laser jumping orders are calculated and compared to select a minimal laser jumping route for sequence planning inside lattice cells. Hence, the proposed method can achieve high-precision lattice printing and avoid computational consumption in model conversion stages from a geometrical view. The optical metallographic images show that the shape accuracy of lattice patterns can be guaranteed. The existence of “grain boundaries” brought about by the multi-contour scanning strategy may lead to different mechanical properties.

Targeted Micro-Phase separation – A generic design concept to control the elasticity of extrudable hydrogels

Hydrogels are ubiquitous in nature and technology. Controlling their mechanical properties and under-standing their complex microstructure is critical e.g. for 3D bioprinting or tissue engineering applications. Here a generic design concept for tuning the elasticity of extrudable gels at given polymer or particle concentration is presented. Targeted micro-phase separation leading to micro-heterogeneities (1–100 µm) yields high gel strength allowing for extrusion of uniform filaments with high shape accuracy as long as the heterogeneity length scale is small compared to the extruded filament diameter (>500 μm). Micro-mechanical and structural heterogeneity was enhanced in alginate hydrogels by accelerating crosslinking kinetics, corresponding to gel elasticity variation of more than two orders of magnitude (17 Pa to 2300 Pa), enabling filament extrusion (1046 µm) with high shape fidelity. Introducing poly(vinylalcohol) into gelatin gels resulted in more heterogeneous materials with a 2-fold increase in elasticity (951 Pa to 1993 Pa) and thinner filaments (908 µm to 590 µm). Higher ionic strength in Laponite-based hydrogels induced nanoparticle aggregation, leading to higher elasticity (857 Pa to 2316 Pa) enabling smooth filament extrusion. Eliminating the often tacitly assumed hydrogel uniformity on the microscale provides additional degrees of freedom to achieve high gel strength without increasing polymer, particle or crosslinker concentration.

Recognizing the Shape and Size of Tundra Lakes in Synthetic Aperture Radar (SAR) Images Using Deep Learning Segmentation

Permafrost tundra contains more than twice as much carbon as is currently in the atmosphere, and it is warming six times as fast as the global mean. Tundra lakes dynamics is a robust indicator of global climate processes, and is still not well understood. Satellite data, particularly, from synthetic aperture radar (SAR) is a suitable tool for tundra lakes recognition and monitoring of their changes. However, manual analysis of lake boundaries can be slow and inefficient; therefore, reliable automated algorithms are required. To address this issue, we propose a two-stage approach, comprising instance deep-learning-based segmentation by U-Net, followed by semantic segmentation based on a watershed algorithm for separating touching and overlapping lakes. Implementation of this concept is essential for accurate sizes and shapes estimation of an individual lake. Here, we evaluated the performance of the proposed approach on lakes, manually extracted from tens of C-band SAR images from Sentinel-1, which were collected in the Yamal Peninsula and Alaska areas in the summer months of 2015–2022. An accuracy of 0.73, in terms of the Jaccard similarity index, was achieved. The lake’s perimeter, area and fractal sizes were estimated, based on the algorithm framework output from hundreds of SAR images. It was recognized as lognormal distributed. The evaluation of the results indicated the efficiency of the proposed approach for accurate automatic estimation of tundra lake shapes and sizes, and its potential to be used for further studies on tundra lake dynamics, in the context of global climate change, aimed at revealing new factors that could cause the planet to warm or cool.

Laser ultrasonic imaging of subsurface defects with the linear sampling method.

Laser ultrasonics is a remote nondestructive evaluation technique suitable for real-time monitoring of fabrication processes in semiconductor metrology, advanced manufacturing, and other applications where non-contact, high fidelity measurements are required. Here we investigate laser ultrasonic data processing approaches to reconstruct images of subsurface side drilled holes in aluminum alloy specimens. We demonstrate through simulation that the model-based linear sampling method (LSM) can perform accurate shape reconstruction of single and multiple holes and produce images with well-defined boundaries. We experimentally confirm that LSM produces images that represent the internal geometric features of an object, some of which may be missed by conventional imaging.

Application of the Improved Grinding Technology to Freeform Surface Manufacturing

In order to meet the manufacturing requirements of modern space remote sensors for high-precision freeform optical parts, the grinding technology and its application were studied. The objective of this paper was to improve the application effect of traditional grinding technology in the processing of hard and brittle materials, and then apply it in specific fields. Therefore, the influence of key process factors such as cutting speed and removal depth on subsurface damage (SSD) was studied based on orthogonal experiments, and an improved grinding technology characterized by low SSD and high surface shape accuracy was formed. Then, the effect of this grinding technology was further verified by the high-precision manufacturing of freeform surfaces. A surface of a 130 mm diameter freeform surface was machined by improved grinding technology and combined polishing technology, the final root mean square of surface shape reached 12.1 nm. The improved grinding technology can reduce SSD from 20 μm to 10 μm, and improve the manufacturing efficiency of freeform surfaces above 30% when the cut speed is 20 m/s and the remove depth is 10 μm. The proposed technology can be applied to the extreme manufacturing of hard and brittle materials.