When painting complex surfaces, such as large-curvature surfaces, poor coating quality is often obtained, which may be caused by lack of an appropriate atomization model, insufficient understanding of atomization mechanisms and laws, and improper painting parameters. This paper presents a numerical model of paint atomization of air spraying using the volume-of-fluid method and large eddy simulation. The interface capture and the turbulent flow were mainly considered in the model: the former was tracked by the volume-of-fluid method and the latter was predicted by the large eddy simulation. After the computational domain being meshed by the staggered-grid method, the governing equations were discretized by the finite volume method and were solved by the SIMPLE (Semi-Implicit Method for Pressure-Linked Equations) Consistent algorithm. The results of numerical simulations show that the characteristics of atomization flow field, such as velocity variation, pressure distribution, and paint volume fraction are in agreement with the regularities of atomization. Moreover, the primary and secondary atomization phenomena can be clearly observed: as soon as the paint issues from the nozzle, the paint flow begins to distort and the paint fragments continuously eject from the main paint flow and then these paint fragments distort and disintegrate into smaller elements. A comparison with the experimental data from the literature proves that the model of the whole atomization process of air spray is effective. The model is suitable for simulating the whole atomization process and easy to obtain initial conditions, which can be applied to set the appropriate painting parameters and study paint atomization mechanisms and laws in depth.

Purpose: Based on virtual maintenance, this paper aims to propose a time prediction method of assembly and disassembly (A&D) actions of product maintenance process to enhance existing methods’ prediction accuracy, applicability and efficiency. Design/methodology/approach: First, a framework of A&D time prediction model is constructed, which describes the time prediction process in detail. Then, basic maintenance motions which can comprise a whole A&D process are classified into five categories: body movement, working posture change, upper limb movement, operation and grasp/placement. A standard posture library is developed based on the classification. Next, according to motion characteristics, different time prediction methods for each motion category are proposed based on virtual maintenance simulation, modular arrangement of predetermined time standard theory and the statistics acquired from motion experiment. Finally, time correction based on the quantitative evaluation method of motion time influence factors is studied so that A&D time could be predicted with more accuracy. Findings: Case study of time prediction of products’ various A&D processes is conducted by implementing the proposed method. The prediction process of diesel cooling fan disassemble time is presented in detail. Through comparison, the advantages and effectiveness of the method are demonstrated. Originality/value: This paper proposes a more accurate, efficient and applicable product A&D time prediction method. It can help designers predict A&D time of a product maintenance accurately in early design phases without a physical prototype. It can also provide basis for the verification of maintainability, the balance of the design of product structure and system layout.

The paper proposes a sliding mesh model-based method to conduct a dynamic painting simulation for an arc connecting surface. In order to meet the requirements for using a sliding mesh model, the computational domain was designed with three parts—a stationary part, a translational part and a rotational part. The film-forming model based on the Euler–Euler model and the conservation equation for a sliding mesh model were established. The dynamic painting of arc connecting surface with the angles of 60, 90 and 120 degrees under the nozzle speed of 100 mm/s were simulated. It was found that the thickness on the arc surface section was larger than those on the plane sections, and through an analysis of the vector distribution, the reason for this was that more paint would be deposited on the arc surface section than on the plane sections due to the concavity of the arc surface. The results obtained from the simulation were in a reasonable agreement with the experimental results, which indicates the proposed method would be effective and applicable in simulating a dynamic painting process.

Painting a V-shaped surface, which is widely found in various facilities and equipment, often results in poor coating quality, which may be caused by an insufficient understanding of film-forming characteristics and mechanism. In this study, computational fluid dynamic (CFD) simulations were carried out for in-depth research on the film-forming characteristics and mechanism of painting V-shaped surfaces. The mathematical model of film formation was established with the Euler–Euler method, and the unstructured grids and adaptive-mesh refinement were adopted to discretize the computational domain. By solving the model, the coating thickness distribution law and flow-field characteristics of spraying a V-shaped surface were obtained. When painting a V-shaped surface with an angle less than 180°, the coating thickness distribution appeared as two peaks, instead of the single peak that appeared when painting a flat wall. As the V-shaped angle decreased, the coating thickness became thinner. The peak position gradually shifted to both sides, and the thickness distribution became wider. Analysis of the spray flow-field characteristics revealed the thickness distribution mechanism, by whichthe geometric characteristics of the V-shaped surface changed the near-wall distribution of the flow field. When the V-shaped angle decreased, the pressure peak at the center of the V-shaped surface and the eccentric pressure peaks that formed on both sides increased. The near-wall paint fluid was confined between the central pressure peak and the off-center pressure peak, resulting in paint droplets depositing between the pressure peaks and double-peak distribution of the coating thickness forming on the V-shaped surface. The spraying experiments verified the correctness of the numerical simulations, film-forming characteristics, and corresponding mechanism, which are of great significance for efficient and high-quality spraying on V-shaped surfaces.

To overcome the temperature effect of NaI(Tl) detectors for energy spectrometry without additional hardware, a new correction method was put forward based on pulse deconvolution, trapezoidal shaping and amplitude correction, named DTSAC. To verify this method, actual pulses from a NaI(Tl)-PMT detector were measured at various temperatures from −20 °C to 50 °C. Pulse processing and spectrum synthesis showed that the position drift of the ¹³⁷Cs 662 keV peak was less than 3 keV, and the corresponding resolution at 662 keV of the sum spectra ranged from 6.91% to 10.60% with the trapezoidal width set from 1000 ns to 100 ns. The DTSAC method corrects the temperature effect via pulse processing, and needs no reference peak, reference spectrum or additional circuits. The method solves the problem of correction of pulse shape and pulse amplitude at the same time, and can be used even at a high counting rate.

Estimating the gamma dose rate at one meter above ground level and determining the distribution of radioactive pollution from aerial radiation monitoring data are the core technical issues of unmanned aerial vehicle nuclear radiation monitoring. In this paper, a reconstruction algorithm of the ground radioactivity distribution based on spectral deconvolution was proposed for the problem of regional surface source radioactivity distribution reconstruction and dose rate estimation. The algorithm estimates unknown radioactive nuclide types and their distributions using spectrum deconvolution and introduces energy windows to improve the accuracy of the deconvolution results, achieving accurate reconstruction of multiple continuous distribution radioactive nuclides and their distributions, as well as dose rate estimation of one meter above ground level. The feasibility and effectiveness of the method were verified through cases of single-nuclide (¹³⁷Cs) and multi-nuclide (¹³⁷Cs and ⁶⁰Co) surface sources by modeling and solving them. The results showed that the cosine similarities between the estimated ground radioactivity distribution and dose rate distribution with the true value were 0.9950 and 0.9965, respectively, which could prove that the proposed reconstruction algorithm would effectively distinguish multiple radioactive nuclides and accurately restore their radioactivity distribution. Finally, the influences of statistical fluctuation levels and the number of energy windows on the deconvolution results were analyzed, showing that the lower the statistical fluctuation level and the more energy window divisions, the better the deconvolution results.