15 research outputs found

    Novel cost controlled materials and processing for primary structures

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    Textile laminates, developed a number of years ago, have recently been shown to be applicable to primary aircraft structures for both small and large components. Such structures have the potential to reduce acquisition costs but require advanced automated processing to keep costs controlled while verifying product reliability and assuring structural integrity, durability and affordable life-cycle costs. Recently, resin systems and graphite-reinforced woven shapes have been developed that have the potential for improved RTM processes for aircraft structures. Ciba-Geigy, Brochier Division has registered an RTM prepreg reinforcement called 'Injectex' that has shown effectivity for aircraft components. Other novel approaches discussed are thermotropic resins producing components by injection molding and ceramic polymers for long-duration hot structures. The potential of such materials and processing will be reviewed along with initial information/data available to date

    Comparison of resin film infusion, resin transfer molding, and consolidation of textile preforms for primary aircraft structure

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    Innovative design concepts and cost effective fabrication processes were developed for damage tolerant primary structures that can perform at a design ultimate strain level of 6000 micro inch/inch. Attention focused on the use of textile high performance fiber reinforcement concepts that provide improved damage tolerance and out-of-plane load capability, low cost resin film infusion (RFI) and resin transfer molding (RTM) processes, and thermoplastic forming concepts. The fabrication of wing 'Y' spars by four different materials and/or processes methods is described: fabricated using IM7 angle interlock 0 to 90 deg woven preforms with + or - 45 deg plies stitched with Toray high strength graphite thread and processed using RFI and 3501-6 epoxy; fabricated using G40-800 knitted/stitched preforms and processed using RFI and 3501-6 epoxy; fabricated using G40-800 knitted/stitched preforms using RTM and Tactix 123/H41 epoxy; and fabricated preforms using AS4(6K)/PEEK 150 g commingled angle interlock 0 to 90 deg woven preforms with + or - 45 deg commingled plies stitched using high strength graphite thread and processed by consolidation. Structural efficiency, processability, and acquisition cost are compared

    Comparison of resin film infusion, resin transfer molding, and consolidation of textile preforms for primary aircraft structure

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    Under NASA's Novel Composites for Wing and Fuselage Applications (NCWFA) Program, Grumman is developing innovative design concepts and cost-effective fabrication processes for damage-tolerant primary structures that can perform at a design ultimate strain level of 6000 micro-inch/inch. Attention has focused on the use of textile high-performance fiber-reinforcement concepts that provide improved damage tolerance and out-of-plane load capability, low-cost resin film infusion (RFI) and resin transfer molding (RTM) processes, and thermoplastic forming concepts. The fabrication of wing 'Y' spars by four different materials/processes methods is described: 'Y' spars fabricated using IM7 angle interlock 0/90 deg woven preforms with +/- 45 deg plies stitched with Toray high-strength graphite thread and processed using RFI and 3501-6 epoxy; 'Y' spars fabricated using G40-800 knitted/stitched preforms and processed using RFI and 3501-6 epoxy; 'Y' spars fabricated using G40-800 knitted/stitched preforms and processed using RTM and Tactix 123/H41 epoxy; and 'Y' spars fabricated using AS4(6k)/PEEK 150-g commingled angle interlock 0/90 deg woven preforms with +/- 45 deg commingled plies stitched using high-strength graphite thread and processed by consolidation. A comparison of the structural efficiency, processability, and projected acquisition cost of these representative spars is presented

    Transport-based Counterfactual Models

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    Counterfactual frameworks have grown popular in explainable and fair machine learning, as they offer a natural notion of causation. However, state-of-the-art models to compute counterfactuals are either unrealistic or unfeasible. In particular, while Pearl's causal inference provides appealing rules to calculate counterfactuals, it relies on a model that is unknown and hard to discover in practice. We address the problem of designing realistic and feasible counterfactuals in the absence of a causal model. We define transport-based counterfactual models as collections of joint probability distributions between observable distributions, and show their connection to causal counterfactuals. More specifically, we argue that optimal transport theory defines relevant transport-based counterfactual models, as they are numerically feasible, statistically-faithful, and can even coincide with causal counterfactual models. We illustrate the practicality of these models by defining sharper fairness criteria than typical group fairness conditions
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