Design of Fiber Reinforced Polymer Building Systems
AssigneeNorthstar Technologies Group Inc.
InventorPaul A. Inglese
Life of this patent
Estimating the term…
Abstract
A method comprises configuring machine learning to generate an architectural model; configuring machine learning to adapt the architectural model to satisfy structural design constraints and optimize at least one objective function; configuring machine learning to select structural components for use in the architectural model; and configuring a machine for manufacturing or assembling the structural components. The architectural model can comprise fiber reinforced polymer (FRP) elements that are selected based on their performance characteristics in order to satisfy the structural design constraints and optimize the at least one objective function.
Claims20
An apparatus, comprising:
- an architectural plan machine-learning system configured to generate an architectural model;
- a structural design machine-learning system communicatively coupled to the architectural plan machine-learning system and configured to adapt the architectural model to satisfy structural design constraints and optimize at least one objective function, the structural design machine-learning system being further configured to select structural components for use in the architectural model;
- and
- an industrial process translation system communicatively coupled to at least one of the structural design machine-learning system and the architectural plan machine-learning system, and configured to generate manufacturing instructions or assembly instructions for use by at least one computer-controlled machine to manufacture or assemble the structural components.
An apparatus, comprising:
- an architectural plan machine-learning system configured to generate an architectural model;
- a structural design machine-learning system communicatively coupled to the architectural plan machine-learning system and configured to adapt the architectural model to satisfy structural design constraints and optimize at least one objective function;
- and
- a computer-aided design (CAD) system communicatively coupled to at least one of the structural design machine-learning system and the architectural plan machine-learning system, the CAD system being configured to provide an interactive display of manufacturing plans or construction plans produced by the structural design machine-learning system, the interactive display enabling a user to add, delete, and/or modify structural components in the manufacturing or construction plans.
A method, comprising:
- employing machine learning to generate an architectural model;
- employing machine learning to adapt the architectural model to satisfy structural design constraints and optimize at least one objective function;
- employing machine learning to select structural components for use in the architectural model;
- and
- generating manufacturing instructions or assembly instructions for use by at least one computer-controlled machine to manufacture or assemble the structural components.
Dependencies are inferred from the claim text.