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Marketing persuasive materials are often displayed on a curved surface (e.g. a curved hallway). This study aims to investigate how the curvature (concave vs convex) of a display surface influences the persuasion of the marketing appeals presented on it.

The conceptual framework was tested in a field experiment, a lab experiment and two online experiments on Amazon Mechanical Turk. Analyses of variance and mediation analysis were used to test the hypotheses.

This research demonstrates that a concave (vs convex) display surface may increase persuasion for marketing materials with social appeals. This occurs because a concave surface enhances consumers’ perception of self–other overlap, which is matched with the content of the social appeal presented on it, thereby enhancing the appeal’s persuasiveness. It further identifies the appeal content as an important moderator of the effect; a convex (vs concave) display would enhance persuasion when the marketing materials contain personal appeals.

Future research could investigate how a time delay (e.g. hours, days) and the curvature of a display board or wall would play a role in the effect of display curvature.

The findings offer a novel, simple and cost-effective approach to enhance persuasion for both nonprofit and for-profit marketing materials.

This research contributes to the persuasion literature by investigating the impact of one ubiquitous but overlooked aspect of the message setting (i.e. the curvature of the message’s display surface) on persuasion while holding the message source and content constant. It also advances knowledge on consumer shape perception by examining an underexplored shape (i.e. the curved shape of a display surface) that is nondiagnostic in message persuasion.

The main aim of this study is to generate curved-form cut on the edge of an adaptive layer. The resulting surface would have much less geometry deviation error and closely fit its computer aided design (CAD) model boundary.

This method is inspired by the manual peeling of an apple in which a knife's orientation and movement are continuously changed and adjusted to cut each slice with minimum waste. In this method, topology and geometry information are extracted from the previously generated adaptive layers. Then, the thickness of an adaptive layer and the bottom and top contours of the adjacent layers are fed into the proposed algorithm in the form of the contour and normal vector to create curved-form sloping surfaces. Following curved-form adaptive slicing, a customized machine path compatible with a five-axis abrasive waterjet (AWJ) machine will be generated for any user-defined sheet thicknesses.

The implemented system yields curved-form adaptive slices for a variety of models with diverse types of surfaces (e.g. flat, convex, and concave), different slicing direction, and different number of sheets with different thicknesses. The decrease in layer thickness and increase of the number of the sloped cuts can make the prototype as close as needed to the CAD model.

The algorithm is designed for use with five-axis AWJ cutting of any kind of geometrical complex surfaces. Future research would deal with the nesting problem of the layers being spread on the predefined sheet as the input to the five-axis AWJ cutter machine to minimize the cutting waste.

The algorithm generates adaptive layers with concave or convex curved-form surfaces that conform closely to the surface of original CAD model. This will pave the way for the accurate fabrication of metallic functional parts and tooling that are made by the attachment of one layer to another. Validation of the output has been tested only as the simulation model. The next step is the customization of the output for the physical tests on a variety of five-axis machines.

This paper proposes a new close to CAD design sloped-edge adaptive slicing algorithm applicable to a variety of five-axis processes that allow variable thickness layering and slicing in different orientations (e.g. AWJ, laser, or plasma cutting). Slices can later be bonded to build fully solid prototypes.

This paper aims to study the effect of isosceles triangle micro concave texture with different parameters on the performance of oil seal to obtain a reasonable combination of parameters.

Based on the theory of elastohydrodynamic lubrication, a numerical model is established by coupling the texture parameters of isosceles triangle with concave lip with the two-dimensional average Reynolds equation considering surface roughness.

The results show that there is an optimal combination of parameters to improve the performance of the oil seal. When hp = 5µm-6.5 µm, a = 110°−130°, O = 1.4, C = 1.6 mm-2.2 mm, the oil seal with isosceles triangle micro concave texture can show good lubrication characteristics, friction characteristics and sealing ability.

The model provides a new idea for the design of new oil seal products and provides a theoretical support for the application of surface texture technology in the sealing field in the future.

The purpose of this paper is to investigate, theoretically and experimentally, a concave mirror‐based fiber optic displacement sensor performance for three‐axes directional measurements.

Mathematical model is constructed based on spherical mirror properties of the concave mirror and the simulated result is found to be in good agreement with the experimental results.

Both theoretical and experimental results show that the focal length and radius of the concave mirror make significant influence to the displacement response. In the x‐axes measurement, six linear slopes are obtained with four of them are located in the vicinity of the position, two times of the focal length. The maximum measurement range of about 20 mm is obtained using a focal length of 10 mm. In the y‐ and z‐axes displacement measurements, the linear range increases as the diameter of concave mirror increases. The longest linear range of 8 mm is achieved at mirror radius of 10 mm.

This is the first demonstration of three axes directional displacement measurements using a concave mirror as a target

This second of a six‐part series presents a hierarchical scheme for classifying integral snap‐fits at the attachment level, bringing great order to where there appeared to be chaos. The scheme is then used to enumerate all possible design options. The proliferation of plastic parts, and the ability to mould such parts of great complexity at little cost penalty, has resulted in the growing use of integral attachment in the form of snap‐fit features in designs. Heretofore, the great diversity of part geometry and integral snap‐fit features has made it appear that design possibilities may be unbounded, and that attempts at optimization might be intractable. The result shows that options can quickly be reduced to a small enough number to allow designers to compare every possibility, thereby making true optimization a practical reality. As such, the scheme guides new designers and validates choices for experienced designers in ways never before possible.

This paper aims to present a new trajectory optimization approach targeting spray painting applications that satisfies the paint thickness requirements of complex-free surfaces.

In this paper, a new trajectory generation approach is developed to optimize the transitional segments at the junction of adjacent patches for straight line, convex arc and concave arc combinations based on different angles between normal vectors of patches. In addition, the paint parameters including the paint gun velocity, spray height and the distance between adjacent trajectories have been determined in the generation approach. Then a thickness distribution model is established to simulate the effectiveness of trajectory planning.

The developed approach was applied to a complex-free surface of various curvatures, and the analysis results of the trajectory optimization show that adopting different transitional segment according to the angle between normal vectors can obtain the optimal trajectory. Based on the simulation and experimental validation results, the proposed approach is effective at improving paint thickness uniformity, and the obtained results are consistent with the simulation results, meaning that the simulation model can be used to predict the actual paint performance.

This paper discusses a new trajectory generation approach to decrease the thickness error values to satisfy spray paint requirements. According to the successfully performed simulation and experimental results, the approach is useful and practical in overcoming the challenge of improving the paint thickness quality on complex-free surface.

The well-known discrete methods of computational fluid dynamics (CFD), lattice Boltzmann method (LBM), cellular automata (CA), volume-of-fluid (VoF) and others rely on several parameters describing the boundary or the surface. Some of them are vector normal to the surface, coordinates of the point on the surface and the curvature. They are necessary for the reconstruction of the real surface (boundary) based on the values of the volume fractions of several cells. However, the simple methods commonly used for calculations of the vector normal to the surface are of unsatisfactory accuracy. In light of this, the purpose of this paper is to demonstrate a more accurate method for determining the vector normal to the surface.

Based on the thesis that information about the volume fractions of the 3 × 3 cell block should be enough for normal vector determination, a neural network (NN) was proposed for use in the paper. The normal vector and the volume fractions of the cells themselves can be defined on the basis of such variables as the location of the center and the radius of the circumference. Therefore, the NN is proposed to solve the inverse problem – to determine the normal vector based on known values of volume fractions. Volume fractions are inputs of NNs, while the normal vector is their output. Over a thousand variants of the surface location, orientations of the normal vector and curvatures were prepared for volume fraction calculations; their results were used for training, validating and testing the NNs.

The simplest NN with one neuron in the hidden layer shows better results than other commonly used methods, and an NN with four neurons produces results with errors below 1° relative to the orientation of the normal vector; for several cases, it proven to be more accurate by an order of magnitude.

The method can be used in the CFD, LBM, CA, VoF and other discrete computational methods. The more precise normal vector allows for a more accurate determination of the points on the surface and curvature in further calculations via the surface or interface tracking method. The paper contains the data for the practical application of developed NNs. The method is limited to regular square or cuboid lattices.

The paper presents an original implementation of NNs for normal vector calculation connected with CFD, LBM and other application for fluid flow with free surface or phase transformation.

A gas insulated substation (GIS) barrier with conical insulators from a cast epoxy resin is optimized to withstand AC and DC stresses. The field distribution across insulators with long creepage path and field distortion due to the deposition of charge on the insulator surface is calculated on a parametric geometry model by finite element techniques. The shape of the insulator and surrounding electrodes was improved fairly quickly using a direct search method with constraints. The results of optimization were verified by standard measurements on high voltage insulators in SF₆ gas.

This paper reports on the work done to decompose a large sized solid model into smaller solid components for rapid prototyping technology. The target geometric domain of the solid model includes quadrics and free form surfaces.

The decomposition criteria are based on the manufacturability of the model against a user‐defined manufacturing chamber size and the maintenance of geometrical information of the model. In the proposed algorithm, two types of manufacturing chamber are considered: cylindrical shape and rectangular shape. These two types of chamber shape are commonly implemented in rapid prototyping machines.

The proposed method uses a combination of the regular decomposition (RD)‐method and irregular decomposition (ID)‐method to split a non‐producible solid model into smaller producible subparts. In the ID‐method, the producible feature group decomposition (PFGD)‐method focuses on the decomposition by recognising producible feature groups. In the decomposition process, less additional geometrical and topological information are created. The RD‐method focuses on the splitting of non‐producible sub‐parts, which cannot be further decomposed by the PFGD‐method. Different types of regular split tool surface are studied.

Combination of the RD‐method and the ID‐method makes up the proposed volume decomposition process. The user can also define the sequence and priority of using these methods manually to achieve different decomposition patterns. The proposed idea is also applicable to other decomposition algorithm. Some implementation details and the corresponding problems of the proposed methods are also discussed.

This papers aims to provide a fixed cutter axis control (F-CAC) industrial robot (IR) milling for NURBS surfaces with large fluctuation, which can avoid over-cut and interference during IR milling in contrast to variable cutter axis control (V-CAC) IR milling.

After the design of a target surface, the IR reciprocating milling trajectory can be obtained using NURBS mapping projection method. A set of interpolation points of the reciprocating trajectory can be calculated using the equi-chord interpolation method. Combining with F-CAC method and curvature estimation, the IR reciprocating trajectory of the tool center point (TCP) without over-cut can be obtained. The programs corresponding to posture control using F-CAC can be generated by IR kinematics.

In contrast to the V-CAC milling method, the F-CAC method can machine successfully the NURBS surfaces with large fluctuation. The simulation and machining proves that F-CAC is feasible and effective to machine NURBS surface with large fluctuation without over-cut phenomenon. The F-CAC has wide application in carving and woodworking industry at present.

The F-CAC method is very practical and effective for IR milling of complex NURBS surfaces with large fluctuation without over-cut and interference phenomenon.