The Boeing Company

Jan Hendrik Vandenbrande

Thomas A Grandine

Brian Dale Laughlin

Richard Eugene Murrish

Stephen L Ray

Gregory Mikel Anderson

Douglas A Carr

Adriana Willempje Blom-Schieber

Paul Zack Thunemann

Laura Sumi Kang

John Michael Costello

John Terry Monahan

Miriam Lucian

Paul Zack Thuneman

Methods for optimizing fiber placement programming for use in automated manufacture of steered-fiber composite laminates. The optimization methods are implemented in software capable of optimally translating steered-fiber laminate definitions in fiber placement code for manufacturing steered-fiber laminates without overlaps. The optimization is set up to take into account manufacturing constraints, such as minimum cut length, minimum steering radius, and fiber straightening due to steering. This software includes both geometry and optimization and will take the aforementioned issues into account by optimizing the direction of lay down and the location and sequence of cutting and adding individual tows.

Fiber placement optimization for steered-fiber plies

The different illustrative embodiments provide a method for augmenting reality that may be applied to repairs performed on a composite structure. An image may be recorded of a first layer of a composite component. The image may relate to a first repair performed at a first time. Physical data may be captured for the composite component from a surface layer of the composite component using a number of portable devices. A multi-dimensional representation of a combined augmented reality of the composite component including a display of various layers of the composite component selected by a user may be generated. A user selection may include a time restriction and a spatial restriction. The number of portable devices may display the multi-dimensional representation comprising physical data for an image of the surface of the composite component and digital data for an overlay of composite layers beyond the surface.

Portable augmented reality

This description provides tools for lazy evaluation of geometric definitions of objects within procedural programming environments. Computer-based methods provided by these tools may parse input program code that includes statements that are syntactically consistent with a procedural programming language. These statements may also include defined functions that are not syntactically consistent with the procedural programming language. The defined functions may be associated with a given function that is defined according to the procedural programming language. The given function may relate to a geometric design of an object. The methods may identify inputs and outputs to this given function, and may build a dependency graph that relates this given function to other functions, based on the inputs and/or outputs of the given function. The methods may delay evaluating the given function until a triggering event occurs, at which time the methods may evaluate the given function to produce the output.

Lazy evaluation of geometric definitions of objects within procedural programming environments

The different advantageous embodiments provide a system comprising a processor unit, a sensor system, and a user interface. The processor unit is configured to execute a data manipulation process. The sensor system is configured to retrieve physical data about a number of physical objects. The user interface has data manipulation controls for the data manipulation process.

Systems and method for simulating liquid containment behavior. The system comprises a solid modeler and a nonlinear equation solver. The nonlinear equation solver takes as input the solid model representation of the containment vessel from the solid modeler, a desired orientation in space, dynamic conditions (e.g., lateral acceleration) and an amount of liquid. To find the level of liquid in the vessel, the system solver iteratively performs successive Boolean subtractions using an infinite horizontal half-space that represents the liquid level of the vessel. The resulting sliced solid model is used to compute the volume of the liquid at that level. The iterative system solver terminates when the computed volume of the sliced containment vessel matches the specified volume of liquid (e.g., fuel) within a given tolerance.

Calculating liquid levels in arbitrarily shaped containment vessels using solid modeling

A method of determining a rigid motion between a master solid model and an approximated target model (or, more generally, between any two models having different types) includes identifying, within each model, geometrical entities having a unique characteristic, and then determining the best match between the identified geometric entities. The system provides, in machine-readable form, a master model comprising a precise definition of a three-dimensional solid and a target model comprising a simplified definition of the three-dimensional solid. Then it identifies a first set of geometric entities (e.g., planar faces) within the master model that have a unique characteristic (e.g., planar area), and identifies a second set of geometric entities in the target model that have the unique characteristic. The system then determines a best match between a member of the first set of geometric entities and a member of the second set of geometric entities using, for example, a Hungarian matching algorithm. Linear edges of matched faces are compared to determine the appropriate rigid motion.

Methods and apparatus for automated part positioning based on geometrical comparisons

Systems and method for simulating liquid containment behavior. The system comprises a solid modeler and a nonlinear equation solver. The nonlinear equation solver takes as input the solid model representation of the containment vessel from the solid modeler, a desired orientation in space, dynamic conditions (e.g., lateral acceleration) and an amount of liquid. To find the level of liquid in the vessel, the system solver iteratively performs successive Boolean subtractions using an infinite horizontal half-space that represents the liquid level of the vessel. The resulting sliced solid model is used to compute the volume of the liquid at that level. The iterative system solver terminates when the computed volume of the sliced containment vessel matches the specified volume of liquid (e.g., fuel) within a given tolerance. To accommodate dynamic situations, e.g., when acceleration is present, the horizontal liquid plane is replaced with a plane at an angle that corresponds to the total acceleration.

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Sammamish, WA, United States of America

Jan Hendrik Vandenbrande