At high Reynolds number, the flow of an incompressible viscous fluid over a lifting surface is a rich blend of fluid dynamic phenomena. Here, boundary layers formed at the leading edge develop over both the suction and pressure sides of the lifting surface, transition to turbulence, separate near the foil's trailing edge, combine in the near wake, and eventually form a turbulent far-field wake. The individual elements of this process have been the subject of much prior work. However, controlled experimental investigations of these flow phenomena and their interaction on a lifting surface at Reynolds numbers typical of heavy-lift aircraft wings or full-size ship propellers (chord-based Reynolds numbers, $Re_C {\sim} 10^7{-}10^8$) are largely unavilable. This paper presents results from an experimental effort to identify and measure the dominant features of the flow over a two-dimensional hydrofoil at nominal $Re_C$ values from near one million to more than 50 million. The experiments were conducted in the US Navy's William B. Morgan Large Cavitation Channel with a solid-bronze hydrofoil (2.1 m chord, 3.0 m span, 17 cm maximum thickness) at flow speeds from 0.25 to 18.3 m s$^{-1}$. The foil section, a modified NACA 16 with a pressure side that is nearly flat and a suction side that terminates in a blunt trailing-edge bevel, approximates the cross-section of a generic naval propeller blade. Time-averaged flow-field measurements drawn from laser-Doppler velocimetry, particle-imaging velocimetry, and static pressure taps were made for two trailing-edge bevel angles (44$ ^\circ$ and 56$ ^\circ$). These velocity and pressure measurements were concentrated in the trailing-edge and near-wake regions, but also include flow conditions upstream and far downstream of the foil, as well as static pressure distributions on the foil surface and test section walls. Observed Reynolds-number variations in the time-averaged flow over the foil are traced to changes in suction-side boundary-layer transition and separation. Observed Reynolds-number variations in the time-averaged near wake suggest significant changes occur in the dynamic flow in the range of $Re_C$ investigated.

Purpose Additive manufacturing (AM) methods such as material extrusion (ME) are becoming widely used by engineers, designers and hobbyists alike for a wide variety of applications. Successfully manufacturing objects using ME three-dimensional printers can often require numerous iterations to attain predictable performance because the exact mechanical behavior of parts fabricated via additive processes are difficult to predict. One of that factors that contributes to this difficulty is the wide variety of ME feed stock materials currently available in the marketplace. These build materials are often sold based on their base polymer material such as acrylonitrile butadiene styrene or polylactic acid (PLA), but are produced by numerous different commercial suppliers in a wide variety of colors using typically undisclosed additive feed stocks and base polymer formulations. This paper aims to present the results from an experimental study concerned with quantifying how these sources of polymer variability can affect the mechanical behavior of three-dimensional printed objects. Specifically, the set of experiments conducted in this study focused on following: several different colors of PLA filament from a single commercial supplier to explore the effect of color additives and three filaments of the same color but produced by three different suppliers to account for potential variations in polymer formulation. Design/methodology/approach A set of five common mechanical and material characterization tests were performed on 11 commercially available PLA filaments in an effort to gain insight into the variations in mechanical response that stem from variances in filament manufacturer, feed stock polymer, additives and processing. Three black PLA filaments were purchased from three different commercial suppliers to consider the variations introduced by use of different feed stock polymers and filament processing by different manufacturers. An additional eight PLA filaments in varying colors were purchased from one of the three suppliers to focus on how color additives lead to property variations. Some tests were performed on unprocessed filament samples, while others were performed on objects three-dimensional printed from the various filaments. This study looked specifically at four mechanical properties (Young’s modulus, storage modulus, yield strength and toughness) as a function of numerous material properties (e.g. additive loading, molecular weight, molecular weight dispersity, enthalpy of melting and crystallinity). Findings For the 11 filaments tested the following mean values and standard deviations were observed for the material properties considered: pa = 1.3 ± 0.9% (percent additives), Mw = 98.6 ± 16.4 kDa (molecular weight), Ð = 1.33 ± 0.1 (molecular weight dispersity), Hm = 37.4 ± 7.2 J/g (enthalpy of melting) and = 19.6 ± 2.1% (crystallinity). The corresponding mean values and standard deviations for the resulting mechanical behaviors were: E = 2,790 ± 145 MPa (Young’s modulus), E’ = 1,050 ± 125 MPa (storage modulus), Sy = 49.6 ± 4.93 MPa (yield strength) and Ut = 1.87 ± 0.354 MJ/m^3 (toughness). These variations were observed in filaments that were all manufactured from the same base polymer (e.g. PLA) and are only different in terms of the additives used by the manufacturers to produce different colors or different three-dimensional printing performance. Unfortunately, while the observed variations were significant, no definitive strong correlations were found between these observed variations in the mechanical behavior of the filaments studied and the considered material properties. Research limitations/implications These variations in mechanical behavior and material properties could not be ascribed to any specific factor, but rather show that the mechanical of three-dimensional printed parts are potentially affected by variations in base polymer properties, additive usage and filament processing choices in complex ways that can be difficult to predict. Practical implications These results emphasize the need to take processing and thereby even filament color, into account when using ME printers, they emphasize the need for designers to use AM with caution when the mechanical behavior of a printed part is critical and they highlight the need for continued research in this important area. While all filaments used were marked as PLA, the feedstock materials, additives and processing conditions created significant differences in the mechanical behavior of the printed objects evaluated, but these differences could not be accurately and reliably predicted as function of the observed material properties that were the focus of this study. Originality/value The testing methods used in the study can be used by engineers and creators alike to better analyze the material properties of their filament printed objects, to increase success in print and mechanical design. Furthermore, the results clearly show that as AM continues to evolve and grow as a manufacturing method, standardization of feedstock processing conditions and additives would enable more reliable and repeatable printed objects and would better assist designers in effectively implementing AM methods.

Uncertainty in the input parameters to an engineering system may not only degrade the system’s performance but may also cause failure or infeasibility. This paper presents a new sensitivity analysis based approach called design improvement by sensitivity analysis (DISA). DISA analyzes the interval uncertainty of input parameters and using multi-objective optimization, determines an optimal combination of design improvements that will ensure a minimal variation in the objective functions of the system, while also ensuring the feasibility. The approach provides a designer with options for both uncertainty reduction and, more importantly, slight design adjustments. A two-stage sequential framework is used that can employ either the original analysis functions or their metamodels to greatly increase the computational efficiency of the approach. This new approach has been applied to two engineering examples of varying difficulty to demonstrate its applicability and effectiveness. The results produced by these examples show the ability of the approach to ensure the feasibility of a preexisting design under interval uncertainty by effectively adjusting available degrees of freedom in the system without the need to completely redesign the system.

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