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New generation non-crimp fabric (NCF) offers an attractive thin and lightweight building block alternative in the design of composite materials and structures. Pre-assembly of multiple plies of parallel fibers, each laying in a different orientation would not require crimping of the fibers and would enable one-axis lay-up that can substantially reduce the labor, scrap, and manufacturing costs. A state-of-the-art tow-spreading technique enables ply thickness to be reduced to as low as one-third of the typical commercial high quality pre-preg ply thickness. The thin-ply NCF stacks result in well-dispersed plies of different fiber orientations and creates the so-called homogenized laminates without ply clustering. As an option, bi-angle thin-ply NCF offers two different fiber orientations with one being off-axis, e.g. at ϕ°, along with an on-axis 0° forming (0/ϕ) assembly. This allows to design in anisotropic properties within the NCF building block. An overview of several aspects of the thin-ply bi-angle NCF composites is provided to address associated benefits and opportunities in the lightweight structural composites design process.

This paper addresses tradeoffs between pressure sensitivity and electronic noise floor in optimizing the performance of a piezoresistive microphone. A design optimization problem is formulated to find the optimum dimensions of the diaphragm, the piezoresistor geometry and location for two objective functions: maximum pressure sensitivity and minimum electronic noise floor. The Pareto curve of optimum designs for both objectives is generated. The minimum detectable pressure (MDP) was also employed as an objective function, generating a point on the Pareto curve that may be the best compromise between the original two objectives. The results indicated that this application the critical constraints are the linearity and power consumption. The minimized MDP design was less sensitive to uncertainty in design variables. The optimization methodology presented in this paper as well as some of the conclusions are applicable to other types of piezoresistive sensors. Index Terms--Design methodology, microelectromechanical devices, microphones, multi-objective optimization, piezoresistive devices.

Bounds on response surface approximation errors as a result of model inadequacy (bias error) are presented, and a design of experiments minimizing the maximal bias error is proposed. The bias-error bounds are considered as a tool to identify locations in the design space where the accuracy of the approximation fitted on a given design of experiments might be poor. Two approaches to characterize the bias error assume that the functional form of the true model is known and seek, at each point in design space, worst-case bounds on the absolute error. The first approach is implemented before data generation. This data-independent error bound can easily be implemented in a search for a design of experiments that minimize the bias error bound as it requires very little computation. The second approach is to be used posterior to the data generation and provides tightened error bound consistent with the data. This data-dependent error bound requires the solution of two linear-programming problems at each point. The data-independent error bound for design of experiments of two-variable examples is demonstrated. Randomly generated polynomials in two variables are then used to validate the data-dependent bias-error bound distribution. Although the two approaches are used in conjunction in the given examples, the data-independent error bound design of experiment is not a prerequisite for the application of the data-dependent error bounds in search for the high bias-error regions.

The use of iteratively reweighted least squares (IRLS) for detecting design points where optimizations converge poorly is demonstrated. Because optimization error tends to be one-sided with poor results producing overweight designs, a nonsymmetrical version of IRLS (NIRLS) that accounts for the asymmetry in optimization errors is also developed. A parameterized Rosenbrock function problem, where a programming error caused poor optimizations, is used to demonstrate the techniques. The identified outliers were repaired by more accurate optimizations to improve response surface approximations. Structural optimization of a high-speed civil transport (HSCT) produced inaccurate wing structural weight. Optimization studies with various sets of convergence criteria showed that the optimization errors were due to incomplete convergence. The IRLS technique could identify many of the points with very large optimization errors, but the NIRLS techniques were much more reliable in this task. However, results of HSCT configuration optimizations using wing weight response surface models show that it may be preferable to identify and repair only a subset of the poorly converged optima.

In the past few years there has been interest in using response surface techniques to create surrogates to computer simulations. Response surface techniques allow detection and correction of errors as well as filtering out numerical noise, but these techniques introduce additional modeling errors. Methods of reducing both noise and modeling errors are explored. It is also demonstrated that repairing designs with large errors is preferable to eliminating these designs from consideration. Response surface approximations for a high-speed civil transport wing weight equation created from the results of a large number of structural optimizations are used for demonstration. It is shown that the statistical tools available for response surface techniques are effective for error detection and for filtering out noise. Once the noise is reduced, modeling errors can also be reduced by increasing the order of the approximation.

ABSTRACT We present a strategy for stabilizing the morphological integrity of electrospun polymeric nanofibers by heat stimuli in situ crosslinking. Amorphous polymer nanofibers, such as polystyrene (PS) and its co-polymers tend to lose their fiber morphology during processing at temperatures above their glass transition temperature ( Tg) typically bound to happen in nanocomposite/structural composite applications. As an answer to this problem, incorporation of the crosslinking agents, phthalic anhydride (PA) and tributylamine (TBA), into the electrospinning polymer solution functionalized by glycidylmethacrylate (GMA) copolymerization, namely P(St- co-GMA), is demonstrated. Despite the presence of the crosslinker molecules, the electrospinning polymer solution is stable and its viscosity remains unaffected below 60 °C. Crosslinking reaction stands-by and can be thermally stimulated during post-processing of the electrospun P(St- co-GMA)/PA-TBA fiber mat at intermediate temperatures (below the Tg). This strategy enables the preservation of the nanofiber morphology during subsequent high temperature processing. The crosslinking event leads to an increase in Tg of the base polymer by 30 °C depending on degree of crosslinking. Crosslinked nanofibers are able to maintain their nanofibrous morphology above the Tg and upon exposure to organic solvents. In situ crosslinking in epoxy matrix is also reported as an example of high temperature demanding application/processing. Finally, a self-same fibrous nanocomposite is demonstrated by dual electrospinning of P(St- co-GMA) and stabilized P(St- co-GMA)/PA-TBA, forming an intermingled nanofibrous mat, followed by a heating cycle. The product is a composite of crosslinked P(St- co-GMA)/PA-TBA fibers fused by P(St- co-GMA) matrix. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016, 133, 44090. [ABSTRACT FROM AUTHOR]