波音

This paper presents a robot-mounted machine vision solution to achieve sub-millimeter localization accuracy of scribe lines and trim-edges on composite parts. In current practice, post-cure trimming to achieve a desired part shape is typically performed on large CNC gantry mills with complex fixtures, which are costly and inflexible. Six DOF industrial robots offer a more flexible platform, but part-to-part geometric variation and limited robot accuracy make it difficult to guarantee a desired trim tolerance in the sub-millimeter range. Scribe lines embedded in layup mandrels are used in practice to provide visual indication of the desired final part edge shape. Therefore, accurate localization of this scribe line feature is essential to perform robotic trimming of the composite parts along the scribe line. We present a telecentric camera-based imaging system mounted on a 6 DOF robot and an image processing pipeline to localize and measure the distance between the scribe line and part edge with sub-millimeter accuracy of less than ±0.5 mm. We also introduce a novel feature detection method which utilizes a finetuned monocular depth estimation deep neural network to generate relative depth images and enhance part-edge contour detection for challenging textures, surface anomalies, and varying edge and scribe line quality. The system is evaluated on carbon fiber reinforced polymer (CFRP) composite samples under dynamic scanning at 10, 25, and 50 mm/s speed. The proposed solution achieved an overall mean measurement error of −0.068 mm with a standard deviation of 0.038 mm in estimating the scribe line to trim-edge distance. The results demonstrate that the proposed robot-mounted machine vision system and algorithm can meet target trim tolerance requirements and enable perception informed robotic machining of large composite structures.

To date, process parameter developments for blown powder laser beam directed energy deposition additive manufacturing (DED-LB-BP) of pure molybdenum (Mo) frequently resulted in inconsistent depositions, cracking, and build plate delamination. In new statistics-guided work to identify better performing process parameter sets, multiple process parameter sets that achieve >99% dense pure Mo depositions are identified. Still, the density results using each set are stochastic. The origin of build-to-build density variance using the same parameter sets is identified to be intergranular cracking. This root cause is validated by contrasting depositions of pure Mo with depositions of Mo with hafnium carbide (HfC) additions to refine the grain structures and eliminate intergranular cracking (but not reduce porosity). Additionally, this work exhibits the capability of HfC additions to inoculate Mo microstructures during DED-LB-BP processing. Altogether, this work provides insight and future direction to the development of Mo-based alloys for DED-LB-BP, better enabling the potential for Mo-based alloys as high specific strength, lower cost, additively manufactured refractory structural materials.

Vortex generators (VGs) are small vanes typically placed on aircraft aerodynamic surfaces (e.g. wings and vertical stabilizers) to delay flow separation and stalling and increase control surface authority (e.g. for ailerons, flaps, and rudder control). Although they are essential for certain scenarios and flight conditions, such as low-speed take-off and landing, VGs are typically not required for the entire flight profile. Despite this, VGs are traditionally static and always deployed, thus adding drag and fuel consumption over the entire flight profile. The static nature of standard VGs stems from the inability to integrate conventional actuators due to mass, complexity, or footprint constraints given the VGs' small size and placement on outer surfaces of the aircraft. Shape memory alloys (SMAs) are capable of high energy density actuation and can enable reconfigurability of such devices with minimal added mass, volume and complexity. Additionally, SMAs can be passively used as sensors and actuators without the need for heaters, active controls, or additional instrumentation, if finely 'tuned' to respond to altitude temperature differentials. Recently, environmentally activated SMA reconfigurable technology vortex generators (SMART-VGs) were developed and successfully flight tested on the 2019 Boeing ecoDemonstrator airplane, a 777-200ER (extended range). This work is presented as a series of two manuscripts, covering the requirements, concept of operation, SMA development and characterization, device design, integration, and flight testing. Part I, presented here, is focused on the material development of low-temperature SMAs for environmentally activated VGs based on temperature changes between ground and cruise altitudes. For context, the background, concept of operation and some requirements will also be introduced. Starting with a binary NiTi alloy, the addition of low levels of Hf (similar to 2 at.%) were critical in tuning the transformation temperatures to match a typical commercial flight profile with standard day temperatures, bound between a martensite and austenite finish of -50 and 0 degrees C, respectively. Additionally, Hf helped stabilize the alloy's response during training in torsion, resulting in low accumulation of residual strains, while promoting very large shear strains of over 6%. The alloy formulation, microstructure, and resulting thermomechanical behavior are presented.

Over the past four decades, comprehensive rotorcraft analysis has undergone a dramatic evolution. During my 44-year career, including 33 years at Boeing, my goal has been to leverage this evolution and push the limits of existing analysis tools for advanced rotorcraft applications. In pursuit of this goal, I have applied state-of-the-art multidisciplinary analysis tools to a variety of rotorcraft products (e.g., CH-47 Chinook, V-22 Osprey, AH-64 Apache, and RAH-66 Comanche), new concepts (e.g., Boeing Heliwing VTOL uncrewed aircraft system (UAS) tail-sitter, dual-plane tiltrotor, and DARPA DiscRotor), and rotorcraft development programs such as the Joint Multi-Role Technology Demonstration and CH-47F advanced composite rotor blade. I had an opportunity to apply a rotorcraft comprehensive analysis tool to Boeing's high-altitude, very flexible, propeller-driven UAS for the DARPA Vulture program-a breakthrough for design analysis, loads, and whirl flutter stability. Each new application drove new requirements for analysis tools and expanded our horizons for rotorcraft design through the addition of fuselage and flight control modeling, VABS-based rotor blade properties, improved wake theory with viscous vortex particle method, and numerous other modeling and analysis improvements. This paper provides an in-depth review of the rich history of comprehensive analysis code development and applications, organized by decade to highlight the progression over time.

We address the problem of identifying the dynamical law governing the evolution of a population of indistinguishable particles, when only aggregate distributions at successive times are observed. Assuming a Markovian evolution on a discrete state space, the task reduces to estimating the underlying transition probability matrix from distributional data. We formulate this inverse problem within the framework of entropic optimal transport, as a joint optimization over the transition matrix and the transport plans connecting successive distributions. This formulation results in a convex optimization problem, and we propose an efficient iterative algorithm based on the entropic proximal method. We illustrate the accuracy and convergence of the method in two numerical setups, considering estimation from independent snapshots and estimation from a time series of aggregate observations, respectively.