Journal of Engineering and Thermal Sciences
Not a member yet
1200 research outputs found
Sort by
Laser cladding powder flow field detection system based on ISR optimization algorithm
Get PDFIn coaxial powder feeding laser cladding, the morphology of the powder flow field is crucial for the forming quality. Therefore, this study utilizes high-speed imaging technology and an Image Super Resolution algorithm to create a laser cladding powder flow field detection system that is capable of detecting and tracking powder particles in the laser cladding environment. The experiment shows that the optimized algorithm has significant improvement in structural similarity indicators, with an improvement rate of nearly 11 %. For powder particle tracking, the distance accuracy of the optimized model is 1.5 lower than that of the unimproved model. In addition, by combining with the Kalman filtering algorithm, the tracking effect of powder particles has been further improved. This paper also found a relationship between powder transfer rate and powder utilization rate. In summary, the powder flow field analysis based on visual detection and image processing technology designed in this study can effectively reflect and predict the trend of changes in cladding quality
Editor’s Letter. Malocclusion treatment tools evolution – electromagnetic synergism. What is the current status of knowledge? Part I
Get PDFAn improved wavelet threshold function denoising method based on IGA optimization
Get PDFIn single crystal diamond tool grinding, cutting-edge quality is affected by various parameters, with tool vibration playing a crucial role. Due to environmental factors and the complexity of the process, vibration signals are often noisy and non-stationary. This study proposes a denoising method that optimizes the wavelet threshold function using an Improved Genetic Algorithm (IGA). The method introduces a configurable value α in the wavelet threshold function, which is optimized with IGA to improve denoising. MATLAB R2018b simulations show that this approach achieves better denoising, a higher signal-to-noise ratio, and lower mean square error
Secure metric dimension of new classes of graphs
Get PDFThe metric representation of a vertex v of a graph G is a finite vector representing distances of v with respect to vertices of some ordered subset S⊆V (G). If no suitable subset of S provides separate representations for each vertex of V(G), then the set S is referred to as a minimal resolving set. The metric dimension of G is the cardinality of the smallest (with respect to its cardinality) minimal resolving set. A resolving set S is secure if for any v∈V–S, there exists x∈S such that (S–{x})∪{v} is a resolving set. For various classes of graphs, the value of the secure resolving number is determined and defined. The secure metric dimension of the graph classes is being studied in this work. The results show that different graph families have different metric dimensions
Optimizing magnetic sensor placement and probe design for high-speed rail RCF crack detection
Get PDFThis study investigates the impact of the trailing effect on the accuracy of crack detection under high-speed conditions. Finite element simulation analysis was used to explore the effects of the trailing effect on the magnetic field distribution on the rail surface and compare the signal intensity and sensitivity at different detection positions. The optimal detection position with higher signal intensity and sensitivity was identified, and a probe structure suitable for electromagnetic non-destructive testing at high speeds was proposed. Experimental results show that at a detection speed of 20.0 m/s, this probe structure effectively quantifies cracks deeper than 1.0 mm, with relative errors and standard deviations within 10 %
A special graph for the connected metric dimension of graphs
Get PDFGiven a connected graph G=(V, E), let d(x, y) represent the separation between x and y at its vertices. If each vertex in a collection B is uniquely identified by its vector of distances to the vertices in B, then that set of vertices resolves a graph G. A metric dimension of G is represented by dim(G) and is the smallest cardinality of a resolving set of G. If the subgraph B- induced by B is a nontrivial connected subgraph of G, then a resolving set B of G is connected. The metric dimension of G is the cardinality of the minimal resolving set, while the connected metric dimension of G is the cardinality of the smallest connected resolving set. The connected metric dimension of the knots graph, whitehead link graph and jewel graph are determined in this study. Finally, we derive the explicit formulas for the triangular book graph, quadrilateral book graph and crystal planar map
A hierarchical estimation of road grade based on tire force observation
Get PDFRoad grade is important for autonomous vehicles, but it is difficult to measure directly. To address this issue, a hierarchical estimation of road grade is suggested based on the observation of tire forces. First, a 7-degree-of-freedom (DOF) dynamics model, including vehicle longitudinal, lateral, and yaw motions together with wheel rotations, is developed while considering the road grade. Subsequently, a dual-layer road grade estimation strategy is proposed based on an unscented Kalman filter (UKF). The lower-layer UKF estimates the longitudinal and lateral tire forces for road grade observation, and the upper-layer UKF is employed to estimate the road grade by considering the vehicle’s lateral acceleration and yaw rate. Finally, CarSim and MATLAB joint simulations and road tests are performed under different conditions to validate the correctness and effectiveness of the proposed estimation method. The results show that the proposed tire force observation-based estimator exhibits a lower mean absolute error and root mean square error on sloping roads and combined curved and sloping roads, and presents a better overall estimation performance on road grade compared with the widely used kinematics and dynamics model-based estimators
The impact of occlusal plane rehabilitation on the face of a patient with traumatic peripheral facial paralysis by Timpanic jugular tumor – case report
Get PDFThe musculature of the face is innervated by cranial nerves, each with a motor, sensory and/or both function. The Facial nerve (FN) is responsible for the motor innervation of the muscles of the face. Some branches of the trigeminal nerve are responsible for the sensory part of the facial muscles and other branches act on the motor part of the chewing muscles. Traumatic Facial Paralysis (TFP) is the one where there was section or traction or compression or ischemia of the FN, in surgery for tumor resection or trauma in general. In this case occurs the nerve’s section in one surgery. Facial Paralysis (FP) can be evaluated subjectively through the House and Brackmann classification scale (HB) [1]. It is considered a chronic FP when it persists for a period longer than 6 months and leaves sequelae, such as synkinesis, contractures and lack of complete innervation of some nerve branches. Some patients who evolve with chronic FP may also evolve with alteration of the occlusal plane. The occlusal plane is the meeting point between the antagonist teeth, plane that is in the final stop of the masticatory cycle. The rehabilitation of this plan is performed according to the needs of each patient, in this case was made through implant prostheses
Prevalence of child malocclusion and its association with time of breastfeeding and/or deleterial habits in children from 2 to 6 years old at public schools in Bento Gonçalves, Rio Grande do Sul, Brazil – pilot project
Get PDFKnowing that the worldwide prevalence of malocclusion in early childhood is 54 %, we carried out a pilot project in the first half of 2022 at Public Schools in Bento Gonçalves RS, evaluating 1938 children between 2 and 6 years old. The prevalence of malocclusion found was 23 %. Anterior open bite, whether or not accompanied by posterior crossbite, was the most prevalent malocclusion. About 70 % of the children were not breastfed or breastfed for less than 6 months, presenting a non-nutritive sucking habit. Assessing 5 years old children alone, this prevalence rose to 54 %. The results reinforce the need of public health policies that promote and support prolonged breastfeeding, which expand the knowledge of parents or guardians and school staff about the adverse effects caused by the use of pacifiers and baby bottles, with the adoption of transdisciplinary measures for the prevention, interception and treatment of malocclusions in a timely manner
Development of an empirical model for the prediction of the sound absorption coefficient for thin and low-density fibrous materials
Get PDFCurrently, FEA software such as ABAQUS uses empirical models to predict the sound absorption coefficient of poroelastic materials. However, based on a recent review of the literature it was found that the current sound absorption empirical models are inadequate for accurate prediction of thin (t < 20 mm), low-density materials (ρB < 50 kg/m3). Therefore, the predictions of the sound pressure levels in vehicle cabins, using such software, will be inaccurate since the trim materials are thin and have a low density. Thus, this research aimed to develop an empirical model that can accurately predict the sound absorption coefficient of these materials. Hence, polypropylene fibres consisting of four different diameters were manufactured and converted into nonwovens. Thereafter, airflow resistivity and impedance tube experimental testing were performed on the specimens. Subsequently, statistical analysis of the data was performed using SAS software. SAS was used to identify which independent variables should be included in the models to be developed. The empirical models were developed using the regression analysis toolbox in Microsoft Excel. Once the models were developed, various checks were performed to validate the assumptions of linear regression. The software NumXL was used to perform Cook’s distance tests. Thereafter, the models were validated against the validation dataset, where it was found that the developed exponential model performed best. Finally, the exponential model was compared to existing models using two data sets i.e. an internal dataset, and an external dataset derived from the literature. The developed model outperformed all the historic models on both datasets