High-precision 3D Research Articles

Macro- and micro- deterioration mechanism of high-speed railway graded gravel filler during vibratory compaction

This study aims to explore the impact mechanism of the vibratory compaction deterioration in high-speed railway graded gravel (HRGG) fillers, which can contribute to the control compaction quality and enhance the service performance of subgrade. Firstly, vibratory compaction experiments were conducted with HRGG fillers using the intelligent vibratory compactor to reveal the vibratory compaction deterioration from the evolution of the dry density ρd, dynamic stiffness Krd. Secondly, X-ray computed tomography (X-CT) scan tests were conducted with the fillers of different compaction stages. Then, the evolution of coarse particle shape characteristics was obtained to reveal the key controlling factor of compaction deterioration. Finally, the high-precision 3D vibratory compaction discrete element method (DEM) models were established for different deterioration degrees. The micro-indicators, such as the coordination number, contact force chains, and fabric anisotropy were investigated to explore the inherent relationship between the compaction deterioration and the key controlling factor. The results showed that the Krd gradually decreased at the compaction deterioration. Additionally, it was found that the key controlling factor for compaction deterioration was the abrasion of coarse particles. From the DEM simulations with different compaction deterioration degrees (CDDS), the dynamic stiffness Krd decreased with increasing CDDS, which was consistent with the results of the vibratory compaction experiments. Moreover, it was observed that the micro-indicators exhibited a decreasing trend with increasing CDDS, indicating a decrease in the ability of coarse particles to wrap fine particles and particles interlocking, which disrupts the ability of the particle skeleton to withstand external loads. This study not only provides a novel approach to investigate the deterioration mechanism during vibratory compaction but also establishes a new theoretical basis for the controlling compaction quality of HRGG fillers.

High-resolution photogrammetry to measure physical aperture of two separated rock fracture surfaces

Photogrammetry, reconstructing three-dimensional (3D) models from overlapping two-dimensional (2D) photos, finds application in rock mechanics and rock engineering to extract geometrical details of reconstructed objects, for example rock fractures. Fracture properties are important for determining the mechanical stability, permeability, strength, and shear behavior of the rock mass. Photogrammetry can be used to reconstruct detailed 3D models of two separated rock fracture surfaces to characterize fracture roughness and physical aperture, which controls the fluid flow, hydromechanical and shear behavior of the rock mass. This research aimed to determine the optimal number of scale bars required to produce high-precision 3D models of a fracture surface. A workflow has been developed to define the physical aperture of a fracture using photogrammetry. Three blocks of Kuru granite (25 cm × 25 cm × 10 cm) with an artificially induced fracture, were investigated. For scaling 3D models, 321 markers were used as ground control points (GCPs) with predefined distances on each block. When the samples were well-matched in their original positions, the entire block was photographed. Coordinate data of the GCPs were extracted from the 3D model of the blocks. Each half was surveyed separately and georeferenced by GCPs and merged into the same coordinate system. Two fracture surfaces were extracted from the 3D models and the vertical distance between the two surfaces was digitally calculated as physical aperture. Accuracy assessment of the photogrammetric reconstruction showed a 20–30 μm digital control distance accuracy when compared to known distances defined between markers. To attain this accuracy, the study found that at least 200 scale bars were required. Furthermore, photogrammetry was employed to measure changes in aperture under normal stresses. The results obtained from this approach were found to be in good agreement with those obtained using linear variable displacement transducers (LVDTs), with differences ranging from 1 μm to 8 μm.

Cost-Effective Full-Color 3D Dental Imaging Based on Close-Range Photogrammetry.

Dental imaging plays a crucial role in clinical dental practice. Conventional 2D dental imaging serves general-purpose tasks, such as patient documentation, while high-precision 3D dental scanning is tailored for specialized procedures, such as orthodontics and implant surgeries. In this study, we aimed to develop a cost-effective 3D imaging technique that could bridge the gap between conventional dental photography and high-precision 3D dental scanning, with the goal of improving patient dental care. We developed a 3D imaging technique based on close-range photogrammetry and termed it close-range photogrammetry-based dental imaging (CPDI). We evaluated this technique on both in vitro dental models and in vivo teeth. For dental models, we conducted a parametric study to examine the effects of the depth of field and specular reflection on reconstruction quality. We showed that the optimal results were achieved with an f/5.6 lens and without a circular polarizer for reflection suppression. This configuration generated 3D scans with 57.7 ± 3.2% and 82.4 ± 2.7% of reconstructed points falling within ±0.1 mm and ±0.2 mm error margins, respectively. With such accuracy, these 3D dental models can faithfully represent dental morphology and features. During in vivo imaging, we were able to reconstruct high-quality 3D models of the anterior arch, further demonstrating its clinical relevance. The reconstructed models carry both 3D shapes and detail full-color surface textures, which positions CPDI as a versatile imaging tool in different areas of clinical dental care.

High-precision composite 3D shape measurement of aeroengine blade based on parallel single-pixel imaging and high-dynamic range N-step fringe projection profilometry

Aeroengine blade is a core component of aircrafts. Accurate measurement of its profile has a great significance for flight safety. However, obtaining a high-quality 3D model of blade is difficult because traditional methods are limited in simultaneously meeting the requirements of large-scale measurement of smooth areas and high-precision measurement of fine structures. We develop a high-precision composite 3D shape measurement method of aeroengine blade. The proposed system consists of two sensors: a global sensor for large-range measurement and a local sensor for high-precision measurement. The global sensor based on parallel single-pixel imaging is used for smooth areas such as blade body and back, which undertakes most of the measurement tasks. The local sensor based on high-dynamic range N-step fringe projection profilometry has a high resolution to measure fine structures such as blade edge and top. We also use the local sensor to complete the missing point cloud of strong reflective areas. A phase-based data alignment method is developed to obtain coordinate transformation between the global and local sensors. Experiment results demonstrate that the proposed method can achieve accurate measurement and finally reconstruct the high-quality 3D model of aeroengine blade.

Two-photon polymerization of silica glass diffractive micro-optics with minimal lateral shrinkage.

Three-dimensional printing enables the fabrication of silica glass optics with complex structures. However, shrinkage remains a significant obstacle to high-precision 3D printing of glass optics. Here we 3D-printed Dammann gratings (DGs) with low lateral shrinkage (<4%) using a two-photon polymerization (2PP) technique. The process consists of two steps: patterning two-photon polymerizable glass slurry with a 515 nm femtosecond laser to form desired structures and debinding/sintering the structures into transparent and dense silica glass. The sintered structures exhibited distinct shrinkage rates in the lateral against longitudinal directions. As the aspect ratio of the structures increased, the lateral shrinkage decreased, while the longitudinal shrinkage increased. Specifically, the structure with an aspect ratio of approximately 60 achieved a minimal lateral shrinkage of 1.1%, the corresponding longitudinal shrinkage was 61.7%. The printed DGs with a surface roughness below 20 nm demonstrated good beam-shaping performance. The presented technique opens up possibilities for rapid prototyping of silica diffractive optical elements.

Properties and performance of nitrogen laser systems for calibration of LHAASO-WFCTA

The Wide Field of view Cherenkov Telescope Array (WFCTA) of the Large High Altitude Air Shower Observatory (LHAASO), located in Haizishan National Natural Reserve, Sichuan Province, China, is designed to perform nearly calorimetric measurements of extensive air showers induced by cosmic rays with energies between 1013eV–1018eV. The end-to-end calibration method will be employed in the WFCTA and nitrogen lasers have been proven to work properly in our application at the altitude of 4410 m a.s.l. for the first time.Due to extremely harsh environment, especially outdoor temperature as low as about −30 °C during operation of WFCTA, a high-stability thermotank for lasers was designed to stabilize temperature and humidity, with a thermal stability of 1 °C. In order to precisely control the beam pointing, a high-precision 3D Lifting Rotating Platform (HiRoP) with a home-made standard zero monitoring system is developed. To eliminate the error of the beam pointing by manual controls, an automatic scanning program was adopted to control the beam pointing when scanning the full field-of-view (FOV) of WFCTA. Both the on-site and remote controls are applied for the nitrogen laser systems and ∼13 million laser shots have been recorded by WFCTA from Sept. 2020 to May 2022. In this paper, the design, properties, operation and the on-site performance of the nitrogen laser systems at LHAASO are reported.

High-Precision 3D Printing of Microporous Cochlear Implants for Personalized Local Drug Delivery.

Hearing loss is a highly prevalent multifactorial disorder affecting 20% of the global population. Current treatments using the systemic administration of drugs are therapeutically ineffective due to the anatomy of the cochlea and the existing blood-labyrinth barrier. Local drug delivery systems can ensure therapeutic drug concentrations locally while preventing adverse effects caused by high dosages of systemically administered drugs. Here, we aimed to design, fabricate, and characterize a local drug delivery system for the human cochlea. The design was relevant to the size of the human ear, included two different shapes, and incorporated two different microporous structures acting as reservoirs for drug loading and release. The four cochlear implant designs were printed using the two-photon polymerization (2PP) technique and the IP-Q photoresist. The optimized 2PP process enabled the fabrication of the cochlear implants with great reproducibility and shape fidelity. Rectangular and cylindrical implants featuring cylindrical and tapered tips, respectively, were successfully printed. Their outer dimensions were 0.6 × 0.6 × 2.4 mm3 (L × W × H). They incorporated internal porous networks that were printed with high accuracy, yielding pore sizes of 17.88 ± 0.95 μm and 58.15 ± 1.62 μm for the designed values of 20 μm and 60 μm, respectively. The average surface roughness was 1.67 ± 0.24 μm, and the water contact angle was 72.3 ± 3.0°. A high degree of polymerization (~90%) of the IP-Q was identified after printing, and the printed material was cytocompatible with murine macrophages. The cochlear implants designed and 3D printed in this study, featuring relevant sizes for the human ear and tunable internal microporosity, represent a novel approach for personalized treatment of hearing loss through local drug delivery.

Structural attributes, evolution and petroleum geological significances of the Tongnan negative structure in the central Sichuan Basin, SW China

The Tongnan secondary negative structure in central Sichuan Basin has controls and influences on the structural framework and petroleum geological conditions in the Gaoshiti-Moxi area. To clarify the controls and influences, the deformation characteristics, structural attributes and evolution process of the Tongnan negative structure were investigated through a series of qualitative and quantitative methods such as balanced profile restoration, area-depth-strain (ADS) analysis, and structural geometric forward numerical simulation, after comprehensive structural interpretation of high-precision 3D seismic data. The results are obtained in three aspects. First, above and below the P/AnP (Permian/pre-Permian) unconformity, the Tongnan negative structure demonstrates vertical differential structural deformation. It experiences two stages of structural stacking and reworking: extensional depression (from the Sinian Dengying Formation to the Permian), and compressional syncline deformation (after the Jurassic). The multi-phase trishear deformation of the preexisting deep normal faults dominated the extensional depression. The primary depression episodes occurred in the periods from the end of Late Proterozoic to the deposition of the 1st–2nd members of the Dengying Formation, and from the deposition of Lower Cambrian Longwangmiao Formation–Middle–Upper Cambrian until the Ordovician. Second, the multi-stage evolution process of the Tongnan negative structure controlled the oil and gas migration and adjustment and present-day differential gas and water distribution between the Tongnan negative structure and the Gaoshiti and Moxi-Longnüsi structural highs. Third, the Ordovician, which is limitedly distributed in the Tongnan negative structure and is truncated by the P/AnP unconformity on the top, has basic geological conditions for the formation of weathering karst carbonate reservoirs. It is a new petroleum target deserving attention.

Hybrid-Supervised Deep Learning for Proton-Acoustic Reconstruction for 3D In Vivo Proton Dose Verification

Proton-acoustic (PA) image has shown great potential to provide real-time 3D dose verification of proton therapy. However, the PA image quality suffers from severe limited view artifacts, which significantly impairs its accuracy for dose verification. In this study, we developed a hybrid-supervised deep learning method for PA reconstruction to address the limited-view issues. Our method consists of two stages. In the first stage, a transformer-based network was proposed to reconstruct initial pressure maps from protoacoustic signals. The network was first trained using supervision by the iteratively reconstructed pressure map and then fine-tuned using transfer learning and self-supervision based on the data fidelity constraint. In the second stage, the PA image was further enhanced by a 3D U-net. The final PA images were converted to dose maps using conversion coefficients derived from CT images. Data from 126 prostate cancer patients treated by proton therapy were collected under an IRB protocol and were split into 86 and 40 patients for model training and testing, respectively. Data of each patient contains the planning CT scan, the corresponding clinical treatment plan, and the dose map calculated by commercial software. The radiofrequency signals were generated by performing proton acoustic simulation based on CT images and the ground truth pressure map derived from the treatment plan. An ultrasound detector matrix with 64 × 64 size and 500kHz central frequency was simulated under the perineum to acquire the signals in the prostate area. In the testing results, the method's accuracy was evaluated using Root-mean-squared-error (RMSE) and structural-similarity-index-measure (SSIM) between the reconstructed and ground truth pressure map and dose distribution. Testing results showed that the reconstructed pressure map achieved an average RMSE/SSIM of 0.0292/0.96, demonstrating excellent 3D information with details. Dose maps derived from the pressure map achieved an average RMSE/SSIM of 0.018/0.99 with a gamma index of 94.7% and 95.7% for 1%/3 mm and 1%/5 mm criteria compared to the ground truth dose maps. The reconstruction time was 6s, which can be further reduced using GPU. Our study achieves start-of-the-art performance in the challenging task of direct reconstruction from limited-view radiofrequency signals, demonstrating the great promise of PA imaging as a highly efficient and accurate tool for in-vivo 3D proton dose verification. Such high-precision 3D online dose verification can substantially reduce the range uncertainties of proton therapy to significantly improve its precision and outcomes.

Применение технологии объединения методов разведочных работ для достижения экологического эффекта на месторождениях Каспия

The method of performing exploration works allowing to obtain an environmental effect in the Caspian Sea fields is described in the article. The research area includes the Rakushechno-Latitudinal and Khvalynsko-Sarmatian zones. Deposits of these zones differ in a complex geological structure. When creating a model of deposits a set of data is used: high-precision 3D seismic surveys on the study area and the results of drilling wells. Such detail of seismic exploration works allows to obtain high-quality results that are due to the high density of reflection points over the area and to the maximum use of various dynamic parameters of reflected waves. The results of such surveys are used in the calculation of reserves, justification of work on additional exploration and subsequent operation. Based on the results of seismic surveys a quantitative forecast of reservoir properties was carried out due to the inversion. For implementation seismic data was processed while preserving the true amplitudes of the seismic signal. Drilling wells were also the main source of information when performing work on calculating reserves. The complex structure and heterogeneity conditions of reservoir properties in area and section, the presence of discontinuous violations led to the use of the described technology, which involves the assessment of reserves and their transfer to the industrial category without testing in the column and causing inflow to the surface. This is done by means of a comprehensive accelerated diagnostics of productive formations for the assessment of reserves of the industrial category. Such a diagnosis provides for the study of productive formations based on the analysis and generalization of accumulated material on core, GIS, GDIS, GDK-OPK and PVT studies, without conducting tests in wells. With the help of these studies the filtration-capacitance properties of rocks, the nature of fluid saturation, contact positions, static levels, reservoir and bottom-hole pressures and reservoir temperatures, as well as deep sampling are determined. The use of modern instruments such as MDT (reservoir Tester) makes it possible to obtain reliable deep samples of the reservoir fluid. The results of data interpretation are successfully approved when making reports on UVS reserves calculation.

Deep learning-based end-to-end 3D depth recovery from a single-frame fringe pattern with the MSUNet++ network.

Deep learning (DL)-based single-frame fringe pattern to 3D depth reconstruction methods have aroused extensive research interest. The goal is to estimate high-precision 3D shape from a single frame of fringe pattern with limited information. Therefore, the purpose of this work attempts to propose an end-to-end DL-based 3D reconstruction method from the single fringe pattern with excellent capability of achieving high accuracy depth recovery and geometry details preservation of tested objects. We construct a multi-scale feature fusion convolutional neural network (CNN) called MSUNet++, which incorporates discrete wavelet transform (DWT) in data preprocessing for extracting high-frequency signals of fringe patterns as input of the network. Additionally, a loss function that combines structural similarity with edge perception is established. Through these measures, high-frequency geometry details of the reconstruction results can be obviously enhanced, while the geometric shape can be effectively maintained. Ablation experiments are involved in validating the effectiveness of our proposed solution. 3D reconstructed results and analysis of generalization experiments on different tested samples imply that the proposed method in this research enjoys capabilities of higher accuracy, better detail preservation, and robustness in comparison with the compared methods.

The CYGNO experiment: a directional Dark Matter detector with optical readout

We are going to discuss the R&D and the prospects for the CYGNO project, towards the development of an innovative, high precision 3D tracking Time Projection Chamber with optical readout using He:CF4 gas at 1 bar. CYGNO uses a stack of triple thin GEMs for charge multiplication, this induces scintillation in CF4 gas, which is readout by PMTs and sCMOS cameras. High granularity and low readout noise of sCMOS along with high sampling of PMT allows CYGNO to have 3D tracking with head tail capability and particle identification down to O(keV) energy for directional Dark Matter searches and solar neutrino spectroscopy. We will present the most recent R&D results from the CYGNO project, and in particular the overground commissioning of the largest prototype developed so far, LIME with a 33×33 cm2 readout plane and 50 cm of drift length, for a total of 50 litres active volume. We will illustrate the LIME response characterisation between 3.7 keV and 44 keV by means of multiple X-ray sources, and the data Monte-Carlo comparison of simulated sCMOS images in this energy range. Furthermore, we will present current LIME installation, operation and data taking at underground Laboratori Nazionali del Gran Sasso (LNGS), serving as demonstrator for the development of a 0.4 m3 CYGNO detector. We will conclude by mentioning the technical choices and the prospects of the 0.4 m3 detector, as laid out in the Technical Design Report (TDR) recently produced by our collaboration.

A Cooperative Game Hybrid Optimization Algorithm Applied to UAV Inspection Path Planning in Urban Pipe Corridors

This paper proposes an improved algorithm applied to path planning for the inspection of unmanned aerial vehicles (UAVs) in urban pipe corridors, which introduces a collaborative game between spherical vector particle swarm optimization (SPSO) and differential evolution (DE) algorithms. Firstly, a high-precision 3D grid map model of urban pipe corridors is constructed based on the actual urban situation. Secondly, the cost function is formulated, and the constraints for ensuring the safe and smooth inspection of UAVs are proposed to transform path planning into an optimization problem. Finally, a hybrid algorithm of SPSO and DE algorithms based on the Nash bargaining theory is proposed by introducing a cooperative game model for optimizing the cost function to plan the optimal path of UAV inspection in complex urban pipe corridors. To evaluate the performance of the proposed algorithm (GSPSODE), the SPSO, DE, genetic algorithm (GA), and ant colony optimization (ACO) are compared with GSPSODE, and the results show that GSPSODE is superior to other methods in UAV inspection path planning. However, the selection of algorithm parameters, the difference in the experimental environment, and the randomness of experimental results may affect the accuracy of experimental results. In addition, a high-precision urban pipe corridors scenario is constructed based on the RflySim platform to dynamically simulate the optimal path planning of UAV inspection in real urban pipe corridors.

Dynamic 3D Measurement without Motion Artifacts Based on Feature Compensation.

Phase-shift profilometry (PSP) holds great promise for high-precision 3D shape measurements. However, in the case of measuring moving objects, as PSP requires multiple images to calculate the phase, the movement of the object causes artifacts in the measurement, which in turn has a significant impact on the accuracy of the 3D surface measurement. Therefore, we propose a method to reduce motion artifacts using feature information in the image and simulate it using the six-step term shift method as a case study. The simulation results show that the phase of the object is greatly affected when the object is in motion and that the phase shift due to motion can be effectively reduced using this method. Finally, artifact optimization was carried out by way of specific copper tube vibration experiments at a measurement frequency of 320 Hz. The experimental results prove that the method is well implemented.

Precision Control in Vat Photopolymerization Based on Pure Copper Paste: Process Parameters and Optimization Strategies.

Vat photopolymerization (VPP) presents new opportunities for metals to achieve the design freedom of components. However, the material properties of copper powder and the inherent defects of the technology seriously hinder its application in high-precision metal additive manufacturing. Precision control is the key to obtaining minimal precision metal parts when copper is prepared by reduction photopolymerization. This paper employed variance analysis (ANOVA) and root mean square deviation (RMSD) to determine the significant parameters affecting dimensional accuracy and their optimal regions. The results show that printing accuracy is improved by optimizing exposure time, intensity, layer thickness, and sweeper moving speed. When the exposure time is 21 s, and the exposure intensity is 220 mW/cm2, a hole with a height of 1 mm and a diameter of 200 μm can be printed with a minimum size deviation of 51 μm. In addition, RMSD and ANOVA provide an effective method for realizing high-precision stereolithography 3D printing metal copper, expanding the material adaptation in the 3D printing metals field. The study highlights the potential of VPP as a method for preparing metals in future studies.

A High-Precision 3D Target Perception Algorithm Based on a Mobile RFID Reader and Double Tags

With the popularization of positioning technology, more and more industries have begun to pay attention to the application and demand of location information, and almost all industries can benefit from low-cost and high-precision location information. This paper introduces a novel three-dimensional (3D) low-cost, high-precision target perception algorithm that utilizes a Radio Frequency Identification (RFID) mobile reader and double tags. Initially, the Received Signal Strength (RSS) is employed to estimate the approximate position of the target along the length direction of the shelf. Additionally, double tags are affixed to the target, enabling the perception of its approximate height and depth through phase information measurements. Subsequently, the obtained rough position serves as an initial value for calibration using the proposed algorithm, allowing for the refinement of the target’s length information relative to the shelf. Simulation results demonstrate the exceptional accuracy of the proposed method in perceiving the 3D position information of the target, achieving centimeter-level sensing accuracy.

Vehicle Localization in a Completed City-Scale 3D Scene Using Aerial Images and an On-Board Stereo Camera

Simultaneous Localization and Mapping (SLAM) forms the foundation of vehicle localization in autonomous driving. Utilizing high-precision 3D scene maps as prior information in vehicle localization greatly assists in the navigation of autonomous vehicles within large-scale 3D scene models. However, generating high-precision maps is complex and costly, posing challenges to commercialization. As a result, a global localization system that employs low-precision, city-scale 3D scene maps reconstructed by unmanned aerial vehicles (UAVs) is proposed to optimize visual positioning for vehicles. To address the discrepancies in image information caused by differing aerial and ground perspectives, this paper introduces a wall complementarity algorithm based on the geometric structure of buildings to refine the city-scale 3D scene. A 3D-to-3D feature registration algorithm is developed to determine vehicle location by integrating the optimized city-scale 3D scene with the local scene generated by an onboard stereo camera. Through simulation experiments conducted in a computer graphics (CG) simulator, the results indicate that utilizing a completed low-precision scene model enables achieving a vehicle localization accuracy with an average error of 3.91 m, which is close to the 3.27 m error obtained using the high-precision map. This validates the effectiveness of the proposed algorithm. The system demonstrates the feasibility of utilizing low-precision city-scale 3D scene maps generated by unmanned aerial vehicles (UAVs) for vehicle localization in large-scale scenes.

Pavement preventive maintenance decision-making for high antiwear and optimized skid resistance performance

Insufficient pavement skid resistance due to traffic loads and environmental factors is a major cause of vehicular accidents. Hence, continually monitoring the pavement skid resistance has great theoretical significance and is crucial for practical maintenance. A pavement accelerated abrasion system developed by the research team, a high-precision 3D layer scanner, and a pendulum tribometer are used for lab testing. Forty-eight sets of asphalt pavement texture and friction coefficient data for 11 abrasion stages were collected, each comprising 20,000 abrasion cycles. Afterward, a model of asphalt pavement skid resistance deterioration was formulated by analyzing the downward trajectory of the asphalt pavement texture and friction coefficient indexes. The developed deterioration model had a high prediction accuracy with an R2 value of 91.64%, and the corresponding curve met engineering requirements. Subsequently, four pavement maintenance techniques, namely synchronous gravel sealing, microsurfacing, ultrathin overlaying, and thermal generation, were applied to rutted slab specimens after grinding to perform five additional stages of abrasion tests. Through comparisons with the established pavement skid resistance deterioration model, the optimal maintenance timing under the abrasion test conditions of this study was determined as 230,000 abrasion cycles, as determined via the time/pavement condition analysis approach. Cost-effectiveness analysis was performed for different surface treatment techniques, which yielded an equivalent annual cost of 6.7 for the SMA-5 ultra-thin overlay, which was identified as the most promising maintenance approach. This study provides a scientific basis for preventing traffic accidents and improving traffic safety by offering valuable insights into the evolution of pavement skid resistance and offers guidance on decision-making for the preventive maintenance of pavements for high-antiwear and optimized skid-resistance performance.

A space terahertz antenna fabricated by 3d printing technology

In this paper, a case of space high-precision THz antennas based on 3D printing technology in engineering has been proposed. The reflectors and the supporting structure have been printed in an integrated way by adopting the structural optimization design method suitable for the high-precision 3D printing process and using the honeycomb structure in the low-stress area. This can avoid the assembly error caused by the assembly of various components of the antenna and achieve the goal of integrated, high-precision, lightweight, and high-thermal stability 3D printing, and manufacturing, which provides an idea for high-precision manufacturing of 3D printing technology in space-borne THz devices.

An integrated optofluidic droplet lens driven by a fast thermoelectric cooler

This work demonstrates a tunable optofluidic droplet lens with a controllable liquid-air interface. The lens is actuated using a fast membrane-free thermo-pneumatic actuator. A liquid droplet with a clear aperture of 2mm is pinned at a circular hole that was fabricated using high-precision 3D printing technology. Movement of the liquid interface is performed by changing the temperature of a thermoelectric cooler (TEC) automatically. The properties of the TEC actuator are compared with those of a membrane thermal actuator through analytical solutions obtained from multi-physics finite element simulations. The average thermal response time of the lens is measured using an infrared thermal imager. The temperature distribution over the device and that over the optical liquid are compared in detail. Finally, the tunability properties of the liquid droplet, including its side profile, optical response time, back focal length, and image performance, are verified experimentally.