Search results

The purpose of this paper is to show the possibility of using the quartz regular surface profile in the form of protrusions and troughs of a triangular shape instead of a random surface profile characterized by a Gaussian correlation function when analyzing the electromagnetic field parameters above the quartz surface to determine the conditions of the effective surface subnano-polishing.

The numerical determination of the evanescent field optimal configuration formed near the quartz rough surface coated with an aqueous solution of calcium hypochlorite when illuminated from the side of the solution has been considered. The finite-element approach is used to solve the Helmholtz two-dimensional vector equation.

Conditions of effective photochemical polishing of rough surface with profile in the form of triangular protrusions and troughs to a sub-nanometer level of roughness are found. These optimal conditions are achieved when the light falls normally on the quartz surface and the height of the surface protrusions is small (up to 20 nm).

This paper shows the possibility of simplifying electrodynamic calculations and analyzing an evanescent field near a quartz surface for the purpose of photochemical polishing by replacing the random profile function with a deterministic periodic function. That is, the novelty of this paper, which supplements the works published earlier [Journal of Modern Optics, 67(3) (2020):242–251; Optik, 207 (2020):164438].

The purpose of this paper is to study the integration between this technology and barrel finishing (BF) operation to improve part surface quality. Fused deposition modeling (FDM) processes have limitation in term of accuracy and surface finishing. Hence, post-processing operations are needed. A theoretical and experimental investigations have been carried out.

A geometrical model of the profile under the action of machining is proposed. The model takes into account FDM formulation and allows to predict the surface morphology achievable by BF. The MR needed in the model is obtained by a particular profilometer methodology, based on the alignment of Firestone–Abbot (F–A) curves. The experimental performed on a suitable geometry validated geometrical model. Profilometer and dimensional measurements have been used to assess the output of the coupled technologies in terms of surface roughness and accuracy.

The coupling of FDM and BF has been assessed and characterized in terms of obtained part surfaces and dimension evolution. Deposition angle strongly affects the BF removal speed and alters nominal dimensions of part. The geometric profile model gave interesting information about profile morphology and machining mechanism; moreover, the height prevision allows to estimate BF working time to accomplish part requirements.

The prediction of the geometric profile as a function of FDM fabrication parameters is a powerful tool which permits to investigate surface properties such as mechanical coupling or tribological aspects. The coupling of BF and FDM has been assessed and now optimization of this process can be performed just evaluating effects of parameters.

This research has been focused to an industrial application, and results can be used in a computer-aided manufacturing. The prevision of surface obtainable by this integration is a tool to find the part optimum orientation to accomplish the drawing requirements. Both the experimental findings and the model can guide operator toward a proper process improvement, thus reducing or eliminating expensive trial and error phase in the post-processing operation of FDM prototypes.

In this paper, a novel model has been presented. It allows to know in advance profile morphology achievable by a specific surface of a FDM part after a determined BF working time. A particular application of FA curves gives the MR values.

The main aim of this paper is description of new apparatus and approach for contact less evaluation of surface roughness. For characterization of surface roughness, the procedures based on classical and non‐classical (complexity) parameters are proposed.

For obtaining the roughness profile in the selected direction (on the line transect of the surface), the special arrangements of textile bend around sharp edge is used. The image analysis is used for extraction of surface profile. The system of controlled movement allows one to obtain surface roughness profile in two dimensions.

By using aggregation (cut length principle), the roughness resolution is decreased and roughness profile is created without local roughness variation. After application of cut length principle, the direct combination of slices leads to the creation of roughness surface.

There exists plenty of roughness characteristics based on standard statistics or analysis of spatial processes. For evaluation of suitability of these characteristics, it will be necessary to compare results from sets of textile surfaces.

The measurement of fabric roughness by an RCM device is useful as simple tool for description of roughness in individual slices and in the whole rough plane. This method replaces the traditional contact stylus profiling methods

The reconstruction of surface roughness from individual slices. The utilization of aggregation principle for creation of micro and macro roughness. The evaluation of roughness parameters based on the geometrical characteristics, harmonic analysis and complexity indices.

Wear greatly influences the machine lifetime, performance and reliability and its quantification is very important. This paper aims to propose a modified bearing area curve method by combining the theory of the bearing area curve, and the relocation technique to calculate wear accurately and efficiently.

H13 steel was chosen as the material of wear pair, and the wear experiments were carried out at 50 N, 60 r/min for 20 min. The surface was measured before and after wear experiments. The relocation was made by comparing the mean lines (planes) of the unworn and worn surface profiles. The calculated results using the proposed method were compared with that of the surface profile method for a two-dimensional surface to validate its accuracy. The method was then applied for a three-dimensional (3D) wear analysis.

The worn surface shows clearly displacement compared to the unworn surface and implies the importance of including relocation in the bearing area curve method. The results from the proposed method are 98 per cent close to that from the surface profile method, indicating that the method is accurate for wear evaluation.

As no feature point or relocation mark is needed to calculate the relocation value using the proposed method, the method can be applied to mild to severe wear. Also, as the deviation of different scans does not affect the relocation calculation, and no matching and stitching is required, this method can be easily applied to a wide wear area and 3D surface wear analysis.

The paper aims to predict the surface roughness of fused deposition modelling prototypes. Since average roughness is not comprehensive, this study aims to extend the characterization to all the roughness parameters obtainable by a profilometric analysis.

A theoretical model of the 3D profile is supplied as a function of process parameters and part shape. A suitable geometry was designed and prototyped for validation. Data were measured by a profilometer and complemented by microscopic analysis. A methodology based on the proposed model was applied to optimise prototype fabrication in two practical cases.

The proposed profile is effective in describing the micro‐geometrical surface of fused deposition modelling prototypes. The third dimension enables the calculation of amplitude, spatial and hybrid roughness parameters.

Because of mathematical assumptions and technological aspects, the validity of the model presents limitations related to the deposition angle.

The method is an effective tool in the process planning stage: it enables knowing in advance how to assure part specifications delivering a set of technical choices. Two practical applications point out the usability in the product development and process parameters optimisation.

This work fulfils an identified need to predict a complete surface characterization of fused deposition modelling technology.

The surface roughness is one of the main parts of hand prediction. Classical method of surface roughness measurements is based on the surface profile measurement. Characteristic of roughness is then variation coefficient of surface profile (surface height variation). The main aim of this work is to estimate the surface profile complexity by using variogram (structure function). The surface profile variation is classified to the group according to short‐ and long‐range dependence. The concept of fractal dimension is proposed especially for long‐term correlation cases. The applicability of the proposed approach is demonstrated on the typical heat protective clothing fabrics and compared with the results of surface roughness evaluated by the KES system.

The study focuses on the development of a numerical model to explore the impact of surface roughness in soft rolling nip contacts, including representation of a real surface. The solution of the governing equations required the application of a multigridding technique to capture the details of the fluid flow within the roughness wavelengths and a minimum number of fluid nodes per wavelength were established. In the case studies, two extreme roughness profiles were considered, longitudinal and circumferential. The longitudinal roughness had a significant impact on nip pressures and pumping capacity, the latter being determined by the minimum film thickness in the nip. The circumferential roughness was found to have a localised effect on film pressure, but only a very small impact on the film thickness profile. The consequent effect on pumping capacity was small.

To provide an advanced cutting trajectory algorithm for the profiled edge laminae (PEL) rapid tooling (RT) process, which is ideally suited for large‐scale dies and molds. The process involves assembling an array of laminae whose top edges are simultaneously profiled and beveled using a line‐of‐sight cutting method based on a CAD model of the intended tool surface.

The cutting profiles for an individual tool lamina are based on intersection curves obtained directly from the CAD model, and generated with exact geometrical accuracy. Two adjacent slice profiles, which define a lamination's top edge and are represented as polylines, are stitched together using an adaptive surface reconstruction algorithm. A cutting trajectory algorithm then develops a series of suitable cutting vectors (i.e. position and cutting direction) that minimize abrasive waterjet (AWJ) cutting errors due to non‐uniform motion and variations in kerf geometry resulting from process parameter variations. The proposed cutting trajectory generation process is demonstrated virtually for an actual production tool.

The proposed algorithm yields well‐behaved AWJ cutting trajectories for individual lamina used in a PEL tool that are better than those obtained using any other algorithm found in the literature.

The algorithm is intended for use with AWJ cutting of PEL tool surfaces. Suggested future research includes assessment of the algorithm for other lamina cutting methods including laser cutting and wire‐type electro‐discharge machining, extending the algorithm to handle conformal cooling/heating channels and internal cavities, and application of the algorithm to several industrial tool case studies.

The algorithm generates cutting trajectories directly from CAD geometry that are ideal for AWJ cutting of profiled edge lamina. It will simply make industrial implementation of the PEL RT process easier.

This paper provides a new cutting trajectory algorithm for the PEL RT process that is a significant improvement over comparable algorithms proposed in the literature.

An optical roughness sensor is described that is ideally suited for integration with a co‐ordinate measuring machine (CMM). The CMM provides an extremely stable platform for moving the sensor head over the surface specimen. The sensor consists of a fibre optic head, data processing electronics and software for controlling the sensor and calculating surface texture parameters from the sensor’s data. The software controls the data acquisition process, filters the data to remove sensor noise and calculates basic amplitude parameters that describe the texture profile of the surface. Tests have been conducted on surfaces and the results compared with stylus profilometer measurements on the same surface regions. Comparison of the amplitude parameter, R_a, shows differences of between 3 percent and 8 percent across the sample set for profiles in the 0.4 μm R_a range.

The purpose of this paper is to study the effects of shaft surface profiles on the load carriage capacity of journal bearings using an experimental and neural network approach. The paper aims to inspect the performance characteristics of journal bearing systems; the presence of transverse and longitudinal roughness on journal‐shaft surfaces is studied using the proposed neural network.

The collected experimental data such as pressure variations are employed as training and testing data for an artificial neural network (ANN). Quick propagation algorithm is used to update the weight of the network during the training.

As a result, a shaft with a transverse profile displays a favorable performance as far as load carriage capacity is concerned. Moreover, the proposed neural network structure outperforms the available experimental model in predicting the pressure as well as the load carriage capacity.

The paper discusses a new modelling scheme known as ANN. A neural network predictor has been employed to analyze the effects of shaft surface profiles in the hydrodynamic lubrication of journal bearings.