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Fused Deposition Modelling (FDM) is affected by various factors such as process parameters during the layer-by-layer printing process, and the parts will have serious defects and unstable mechanical properties. Therefore, the real-time monitoring of the processing process can better study the relationship between the parameters and defects. In particular, the direct measurement of thin-wall component dimensions and surface defects can better realize the adjustment of process parameters to improve the mechanical properties. However, existing monitoring methods either indirectly predict part quality by checking equipment health situation or directly inspect the component with inflexible field-of-view. Hence, this paper proposes a novel monitoring proof-of-concept prototype based on the phenomenon of laser self-mixing to directly inspect for part quality. The system primarily uses a laser diode with a self-encapsulated photodiode which is capable of collecting optical feedback signal once the laser hits a target. And data processing and calculation are performed on the feedback signal to obtain the geometric size and defect size of the target. The measurement object is FDM single-wall plates. The results show that the laser scanning monitoring system can successfully measure the target, and the measurement accuracy of the average size of waviness defects can reach up to 99.36 %. To the best of our knowledge, this study is the first to apply the self-mixing phenomenon as a metrology technique for the monitoring of an additive manufacturing process.

Lattice structures fabricated by additive manufacturing (AM) technology have many excellent properties, such as lightweight, high strength, energy absorption, and vibration reduction, which have been extensively researched and made a breakthrough. Lattice structures have been commonly used in aviation, bioengineering, robotics, and other industrial fiber because of their outstanding properties. The first part of this article provides a short review on the assessment of mechanical properties of various lattice structures in terms of their classification, applications, materials and fabrication techniques, and complexity of designing, fabrication, and post-processing as well as some of the numerical models to predict the mechanical properties of the lattice structures. The second part of the article proposes a deep learning (DL) model for a highly accurate stress-strain behavior assessment of numerous lattice structures such as namely: the octet, face center-cubic, body-centered cubic, diamond, rhombic, cubic, truncated cube, and truncated cuboctahedron, etc, which were fabricated using many different materials via various approaches and methods. Using the proposed DL model, an accuracy in terms of R2 = 0.999 (correlation coefficient), MSE = 0.0017 (mean squared error), and MAE = 0.0312 (mean absolute error) can be achieved for the prediction of the deemed mechanical property of the lattice structures. The model contains simple, quick and precise predictability that makes it ideal for the use of lattice structures in various practical applications, including heater and heat exchangers, engine hood, biomedical implant, wings, gas turbine, vibration absorber, robotic device, etc. [ABSTRACT FROM AUTHOR]

In this paper, we examine two structure preserving numerical finite difference methods for solving the various reaction-diffusion models in one dimension, appearing in chemistry and biology. These are the finite difference methods in splitting environment, namely, operator splitting nonstandard finite difference (OS-NSFD) methods that effectively deal with nonlinearity in the models and computationally efficient. Positivity of both the proposed splitting methods is proved mathematically and verified with the simulations. A comparison is made between proposed OS-NSFD methods and well-known classical operator splitting finite difference (OS-FD) methods, which demonstrates the advantages of proposed methods. Furthermore, we applied proposed NSFD splitting methods on several numerical examples to validate all the attributes of the proposed numerical designs.

Polymer based additive manufacturing is a robust manufacturing paradigm and facilitates production of highly customized parts with substantially improved mechanical properties. Therefore, the aim of this research is to investigate seven polymeric lattice structures namely: Diamond, Gyroid, Kelvin, Split-P, SUP, Primitive, and Octet. The annealing heat-treatment was used at two different tempartures:110 °C and 130 °C for a constant time period (2 h). In total, five specimens were investigated for each sample (such as for each case of annealed and as built samples). The SEM images show greater smoothness of microstructure with application of heat treatment. However, a higher temperature can have an adverse effect. For example, the roughness of Gyroid, Octet, and SUP is decreased compared to the As-built sample. In addition, it is shown that surface roughness is directly proportional to the mechanical strength. Among all the structures, Diamond and SUP structures (As-built) demonstrate higher performance in terms of load-bearing capacity (at densification point) and lower flexibility compared to their counter-part. For instance, Diamond and Octet structures’ strength is increased by 22% and 20% whereas flexibility is decreased by 12% and 8%, respectively. Maximum energy absorption is achieved by the Diamond structure followed by the Gyroid, Split-P, Kelvin, SUP, and Primitive. Apparently, the heat treatment has induced brittleness in the structure making it prone to cracks. A newly designed SUP structure has demonstrated the maximum strength among all the tested structures whereas the Octet structure exhibited the least strength. In return, this increase in the strength of the SUP structure is achieved at a cost of a decrease in flexibility.

• Three dimensional reaction-diffusion epidemic system is considered for numerical study. • Numerical stability of the epidemic system and bifurcation value of transmission parameter from susceptibility to disease is evaluated with the help of Routh–Huwartiz criteria. • A novel structure preserving numerical method is proposed for solution of reaction-diffusion epidemic model in three dimension. • Simulations of a numerical experiment are presented to verify all the attributes of the proposed method. In this article, numerical solution of three dimensional susceptible-infected-recovered (SIR) reaction-diffusion epidemic system is furnished with a time efficient operator splitting nonstandard finite difference (OS-NSFD) method. We perform the comparison of proposed OS-NSFD method with popular forward Euler explicit finite difference (FD) method and time efficient backward Euler operator splitting finite difference (OS-FD) implicit method. The proposed OS-NSFD method is implicit in nature but computationally efficient as compared to forward Euler explicit (FD) scheme. The numerical stability and bifurcation value of transmission coefficient for SIR reaction-diffusion epidemic system is also investigated with the aid of Routh–Hurwitz method. At the end, we give two numerical experiments and simulation. In first experiment, all the numerical schemes are compared with the help of simulations. In second experiment we show the simulations of proposed NSFD technique at different values of parameters. Also we discuss the importance of transmission rate to control the spread of disease with the help of simulations. [ABSTRACT FROM AUTHOR]