FEA model based cautious automatic optimal shape control for fuselage assembly

In a half fuselage assembly process, shape control is vital for achieving ultra-high precision assembly. To achieve better shape adjustment, we need to determine the optimal location and force of each actuator to push and pull a fuselage to compensate for its initial shape distortion. The current practice achieves this goal by solving a surrogate model based optimization problem. However, there are two limitations of this surrogate model based method: (1) Low efficiency: Collecting training data for surrogate modeling from many FEA replications is time-consuming. (2) Non-optimality: The required number of FEA replications for building an accurate surrogate model will increase as the potential number of actuator locations increases. Therefore, the surrogate model can only be built on a limited number of prespecified potential actuator locations, which will lead to sub-optimal control results. To address these issues, this paper proposes an FEA model based automatic optimal shape control (AOSC) framework. This method directly loads the system equation from the FEA simulation platform to determine the optimal location and force of each actuator. Moreover, the proposed method further integrates the cautious control concept into the AOSC system to address model uncertainties in practice. The case study with industrial settings shows that the proposed Cautious AOSC method achieves higher control accuracy compared to the current industrial practice.

Realizing Shape and Size Control for the Synthesis of Coordination Polymer Nanoparticles templated by Diblock Copolymer Micelles

The combination of polymers with nanoparticles offers the possibility to obtain customizable composite materials with additional properties such as sensing or bistability provided by a switchable spin crossover (SCO) core. For all applications, a precise control over size and shape of the nanomaterial is highly important as it will significantly influence its final properties. By confined synthesis of iron(II) SCO coordination polymers within the P4VP cores of polystyrene-block-poly-4-vinylpyridine (PS-b-P4VP) micelles in THF we are able to control the size and also the shape of the resulting SCO nanocomposite particles by the composition of the PS-b-P4VP diblock copolymers (dBCPs) and the amount of complex employed. For the nanocomposite samples with the highest P4VP content, a morphological transition from spherical nanoparticle to worm-like structures was observed with increasing coordination polymer content, which can be explained with the impact of complex coordination on the self-assembly of the dBCP. Furthermore, the SCO nanocomposites showed transition temperatures of T1/2 = 217 K, up to 27 K wide hysteresis loops and a decrease of the residual high-spin fraction down to γHS = 14% in the worm-like structures, as determined by magnetic susceptibility measurements and Mössbauer spectroscopy. Thus, SCO properties close or even better (hysteresis) to those of the bulk material can be obtained and furthermore tuned through size and shape control realized by tailoring the block length ratio of the PS-b-P4VP dBCPs.

A Variant Cubic Exponential B-Spline Scheme with Shape Control

This paper presents a variant scheme of the cubic exponential B-spline scheme, which, with two parameters, can generate curves with different shapes. This variant scheme is obtained based on the iteration from the generation of exponentials and a suitably chosen function. For such a scheme, we show its C2-convergence and analyze the effect of the parameters on the shape of the generated curves and also discuss its convexity preservation. In addition, a non-uniform version of this variant scheme is derived in order to locally control the shape of the generated curves. Numerical examples are given to illustrate the performance of the new schemes in this paper.

Adjustable Piecewise Quartic Hermite Spline Curve with Parameters

In this paper, the quartic Hermite parametric interpolating spline curves are formed with the quartic Hermite basis functions with parameters, the parameter selections of the spline curves are investigated, and the criteria for the curve with the shortest arc length and the smoothest curve are given. When the interpolation conditions are set, the proposed spline curves not only achieve C1-continuity but also can realize shape control by choosing suitable parameters, which addressed the weakness of the classical cubic Hermite interpolating spline curves.

Shape Preserving Piecewise KNR Fractional Order Biquadratic C 2 Spline

In a recent article, a piecewise cubic fractional spline function is developed which produces C 1 continuity to given data points. In the present paper, an interpolant continuity class C 2 is preserved which gives visually pleasing piecewise curves. The behavior of the resulting representations is analyzed intrinsically with respect to variation of the shape control parameters t and s. The data points are restricted to be strictly monotonic along real line.

C˜2 Continuous Cubic Hermite Interpolation Splines with Second-Order Elliptic Variation

In order to solve the deficiency of Hermite interpolation spline with second-order elliptic variation in shape control and continuity, c-2 continuous cubic Hermite interpolation spline with second-order elliptic variation was designed. A set of cubic Hermite basis functions with two parameters was constructed. According to this set of basis functions, the three-order Hermite interpolation spline curves were defined in segments 02, and the parameter selection scheme was discussed. The corresponding cubic Hermite interpolation spline function was studied, and the method to determine the residual term and the best interpolation function was given. The results of an example show that when the interpolation conditions remain unchanged, the cubic Hermite interpolation spline curves not only reach 02 continuity, but also can use the parameters to control the shape of the curves locally or globally. By determining the best values of the parameters, the cubic Hermite interpolation spline function can get a better interpolation effect, and the smoothness of the interpolation spline curve is the best.