2334913
Project Grant
Overview
Grant Description
Sbir Phase I: Computational Synthesis of 3D Printed Composite and Infill Layouts -this small business innovation research (SBIR) Phase I project expedites the growth of additive manufacturing for end-use parts through automated design software.
Additive manufacturing has emerged as an appealing alternative to traditional subtractive manufacturing to fabricate end-use parts with tailored stiffness and strength. A critical production stage required to unlock the potential of additive manufacturing for end-use parts is the design process, which currently requires extensive engineering experience and high engineering design time.
The new technology will allow a paradigm shift from the current slow, tedious, and failure-prone design process to an automated design process. The algorithm utilizes high-performance computing and designs components based on strength, specific material properties, and manufacturing constraints.
The technology is expected to reduce engineering design time and, as a result, the production cost and time, which will enable the industry to scale production. Additionally, by using the automated design process, the material distribution can be tailored to achieve the desired structural responses, and lightweight structures can be fabricated.
The reduction in weight results in a reduction in fuel consumption in aviation and auto industries, which will provide both ecological and economic benefits. This small business innovation research (SBIR) Phase I project advances the state of the art by (a) developing novel approaches to optimize layout, fiber paths, and plastic infill distribution, (b) generating additive manufacturing toolpaths based on structural performance and efficiency, and (c) implementing multiple failure criteria to understand failure loads in composite additive manufacturing.
Due to the significant cost difference between continuous fiber filament and plastic infill, it is crucial to consider the design of fiber paths, carbon fiber reinforced regions, and plastic infill layout. Another challenge is that current design processes do not include a single failure criterion that can predict failure under different loading scenarios.
To address these two challenges, the team is investigating a stiffness and strength-based topology optimization for composite additive manufacturing that will enable the design of the geometric layout and toolpath for 3D printing simultaneously. Anisotropic material properties for stiffness and strength in different directions are implemented to utilize the full potential of composite parts.
Toolpath constraints such as curvature, minimum length, and width are also implemented in the optimization process to prevent print failure. Finally, an intelligent slicing program will be developed to control the movement of the 3D printer nozzle and eliminate part failure due to stress concentration.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. - Subawards are not planned for this award.
Additive manufacturing has emerged as an appealing alternative to traditional subtractive manufacturing to fabricate end-use parts with tailored stiffness and strength. A critical production stage required to unlock the potential of additive manufacturing for end-use parts is the design process, which currently requires extensive engineering experience and high engineering design time.
The new technology will allow a paradigm shift from the current slow, tedious, and failure-prone design process to an automated design process. The algorithm utilizes high-performance computing and designs components based on strength, specific material properties, and manufacturing constraints.
The technology is expected to reduce engineering design time and, as a result, the production cost and time, which will enable the industry to scale production. Additionally, by using the automated design process, the material distribution can be tailored to achieve the desired structural responses, and lightweight structures can be fabricated.
The reduction in weight results in a reduction in fuel consumption in aviation and auto industries, which will provide both ecological and economic benefits. This small business innovation research (SBIR) Phase I project advances the state of the art by (a) developing novel approaches to optimize layout, fiber paths, and plastic infill distribution, (b) generating additive manufacturing toolpaths based on structural performance and efficiency, and (c) implementing multiple failure criteria to understand failure loads in composite additive manufacturing.
Due to the significant cost difference between continuous fiber filament and plastic infill, it is crucial to consider the design of fiber paths, carbon fiber reinforced regions, and plastic infill layout. Another challenge is that current design processes do not include a single failure criterion that can predict failure under different loading scenarios.
To address these two challenges, the team is investigating a stiffness and strength-based topology optimization for composite additive manufacturing that will enable the design of the geometric layout and toolpath for 3D printing simultaneously. Anisotropic material properties for stiffness and strength in different directions are implemented to utilize the full potential of composite parts.
Toolpath constraints such as curvature, minimum length, and width are also implemented in the optimization process to prevent print failure. Finally, an intelligent slicing program will be developed to control the movement of the 3D printer nozzle and eliminate part failure due to stress concentration.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. - Subawards are not planned for this award.
Awardee
Funding Goals
THE GOAL OF THIS FUNDING OPPORTUNITY, "NSF SMALL BUSINESS INNOVATION RESEARCH (SBIR)/ SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAMS PHASE I", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF23515
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Daytona Beach,
Florida
32114-3857
United States
Geographic Scope
Single Zip Code
Novineer was awarded
Project Grant 2334913
worth $275,000
from National Science Foundation in December 2023 with work to be completed primarily in Daytona Beach Florida United States.
The grant
has a duration of 1 year and
was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.
The Project Grant was awarded through grant opportunity NSF Small Business Innovation Research / Small Business Technology Transfer Phase I Programs.
SBIR Details
Research Type
SBIR Phase I
Title
SBIR Phase I: Computational Synthesis of 3D Printed Composite and Infill Layouts
Abstract
This Small Business Innovation Research (SBIR) Phase I project expedites the growth of additive manufacturing for end-use parts through automated design software. Additive manufacturing has emerged as an appealing alternative to traditional subtractive manufacturing to fabricate end-use parts with tailored stiffness and strength. A critical production stage required to unlock the potential of additive manufacturing for end-use parts is the design process, which currently requires extensive engineering experience and high engineering design time. The new technology will allow a paradigm shift from the current slow, tedious, and failure-prone design process to an automated design process. The algorithm utilizes high-performance computing and designs components based on strength, specific material properties, and manufacturing constraints. The technology is expected to reduce engineering design time and, as a result, the production cost and time, which will enable the industry to scale production. Additionally, by using the automated design process, the material distribution can be tailored to achieve the desired structural responses, and lightweight structures can be fabricated. The reduction in weight results in a reduction in fuel consumption in aviation and auto industries, which will provide both ecological and economic benefits.
This Small Business Innovation Research (SBIR) Phase I project advances the state of the art by (a) developing novel approaches to optimize layout, fiber paths, and plastic infill distribution, (b) generating additive manufacturing toolpaths based on structural performance and efficiency, and (c) implementing multiple failure criteria to understand failure loads in composite additive manufacturing. Due to the significant cost difference between continuous fiber filament and plastic infill, it is crucial to consider the design of fiber paths, carbon fiber reinforced regions, and plastic infill layout. Another challenge is that current design processes do not include a single failure criterion that can predict failure under different loading scenarios. To address these two challenges, the team is investigating a stiffness and strength-based topology optimization for composite additive manufacturing that will enable the design of the geometric layout and toolpath for 3D printing simultaneously. Anisotropic material properties for stiffness and strength in different directions are implemented to utilize the full potential of composite parts. Toolpath constraints such as curvature, minimum length, and width are also implemented in the optimization process to prevent print failure. Finally, an intelligent slicing program will be developed to control the movement of the 3D printer nozzle and eliminate part failure due to stress concentration.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Topic Code
M
Solicitation Number
NSF 23-515
Status
(Complete)
Last Modified 12/21/23
Period of Performance
12/15/23
Start Date
11/30/24
End Date
Funding Split
$275.0K
Federal Obligation
$0.0
Non-Federal Obligation
$275.0K
Total Obligated
Activity Timeline
Additional Detail
Award ID FAIN
2334913
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
YZCJBEAXLLT7
Awardee CAGE
9B9R7
Performance District
FL-06
Senators
Marco Rubio
Rick Scott
Rick Scott
Modified: 12/21/23