Modeling Tools for the Drilling of Polymer Matrix Composites (PMCs)

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8650-19-P-5065
Agency Tracking Number: F182-098-0062
Amount: $149,390.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: AF182-098
Solicitation Number: 2018.2
Timeline
Solicitation Year: 2018
Award Year: 2019
Award Start Date (Proposal Award Date): 2018-10-23
Award End Date (Contract End Date): 2019-10-23
Small Business Information
6475 City West Parkway, Eden Prairie, MN, 55344
DUNS: 938966090
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Chang Tsan Lu
 (952) 832-5515
 chang-tsan.lu@thirdwavesys.com
Business Contact
 Lisa Ferris
Phone: (952) 832-5515
Email: lisa.ferris@thirdwavesys.com
Research Institution
N/A
Abstract
In this Small Business Innovation Research Phase I program, Modeling Tools for the Drilling of Polymer Matrix Composites (PMCs), Third Wave Systems (TWS) will develop and demonstrate innovative multi-scale modeling tools for the drilling of polymer matrix composites (PMCs), which is enabled by integration of advanced material constitutive models, detailed-level finite element analysis (FEA), and NC toolpath-level modeling and process optimization,to reduce component costs by reducing machining cycle time, machining-induced damage and consumable tooling cost. TWS will utilize its detailed-level FEA software AdvantEdge and NC toolpath optimization software Production Module as the technical platforms for development. In AdvantEdge, TWS will develop a generic, comprehensively verified PMC material model capable of predicting anisotropic material responses, non-homogeneous failure modes and cutting temperature. Then AdvantEdge simulations will be used to create a database for the NC toolpath-level modeling and process optimization in Production Module. TWS innovative modeling tools will be capable of predicting the key characteristics of PMC drilling at both the detailed level and toolpath level, including stresses, forces, machining-induced damage, tool wear and temperature. Further process optimization for reducing the machining cycle time and improving part quality and tool life will be obtainable based on the simulation predictions.

* Information listed above is at the time of submission. *

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