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Results for “Structured Light Scanning”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Structured light scanning artifact-based performance study

Structured light scanning is used to create a digital twin of a manufactured part, where features are extracted to determine if the part meets the designer’s intent and required tolerances. This paper describes repeatability and reproducibility analyses for a commercially-available structured light scanning system and measurement artifact. The repeatability study used five repeated scans at 15 measurement positions. Repeatability was assessed by randomly selecting one of the five scans at each of the 15 positions and creating a part mesh. This process was performed 50 times and the statistics for the dimension variations were calculated to isolate the scanning effects only. The same sequence was then performed for 10 of the 15 positions and five of the 15 positions to evaluate the repeatability sensitivity to the number of measurement positions. Reproducibility was assessed by selecting 15 positions to create a mesh and repeating the 15-position measurement sequence 10 times using different positions for each mesh construction. The statistics for the dimension variations were then calculated. This incorporated the effects of both scanning and the position and orientation of the part relative to the scanner. This sequence was repeated for 10-position and five-position scans to evaluate the corresponding sensitivity. Finally, the artifact dimensions from structured light scanning were compared to coordinate measuring machine measurements of the same features.

42 ENGINEERING↗
DOE OSTI2023

Freeform Hybrid Manufacturing: Binderjet, Structured Light Scanning, Confocal Microscopy, and CNC Machining

This paper describes a hybrid manufacturing approach for silicon carbide (SiC) freeform surfaces using binder jet additive manufacturing (BJAM) to print the preform and machining to obtain the design geometry. Although additive manufacturing (AM) techniques such as BJAM allow for the fabrication of complex geometries, additional machining or grinding is often required to achieve the desired surface finish and shape. Hybrid manufacturing has been shown to provide an effective solution. However, hybrid manufacturing also has its own challenges, depending on the combination of processes. For example, when the subtractive and additive manufacturing steps are performed sequentially on separate systems, it is necessary to define a common coordinate system for part transfer. This can be difficult because AM preforms do not inherently contain features that can serve as datums. Additionally, it is important to confirm that the intended final geometry is contained within the AM preform. The approach described here addresses these challenges by using structured light scanning to create a stock model for machining. Results show that a freeform surface was machined with approximately 70 µm of maximum deviation from that which was planned.

Dvorak, Jake (ORCID:0000000260989944)↗
DOE OSTI2022

Hybrid manufacturing of Invar mold for carbon fiber layup using structured light scanning

This paper describes coordinate system definition and transfer for five-axis machining of additively-manufactured preforms. In this method, a set of fiducials are attached to the temporarily attached to the part, and their location relative to the preform geometry is calibrated using a structured light scanner. Those fiducials can then be measured in the machine tool to determine the location and orientation of the part. The method is demonstrated by finish-machining a carbon fiber layup mold from an additively manufactured Invar preform. In addition to showing the coordinate transfer methods necessary to machine the part, several key challenges with machining additively-manufactured preforms are discussed and potential solutions are proposed. Unfortunately, the final part was ultimately unusable due to porosity inside the part left from the additive process. Future work will remanufacture this part while taking steps to avoid porosity and other challenges encountered.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Digital force prediction for milling

This paper presents a fully digital, integrated approach for milling force prediction with arbitrary end mill-work material combinations. The approach includes: 1) structured light scanning to identify the end mill’s cutting edge macro-geometry along the tool axis; 2) structured light scanning to measure the cutting edge cross-sectional rake and relief profiles; 3) finite element analysis of orthogonal cutting to determine the force model coefficients that relate the force to chip area using the work material’s constitutive model and tool’s rake and relief profiles; and 4) time domain simulation with inputs that include the measured cutting edge macro-geometry, finite element-based force model, and measured structural dynamics. Milling force predictions are compared to in-process measurements to validate the method.

42 ENGINEERING↗
DOE OSTI2023

Hybrid manufacturing by additive friction stir deposition, metrology, CNC machining, and microstructure analysis

Aerospace flight panels must provide high strength with low mass. For aluminum panels, it is common practice to begin with a wrought plate and remove the majority of the material to attain the desired structure, comprising a thinner plate with the desired pattern of reinforcement ribs. As an alternative, this study implements hybrid manufacturing, where aluminum is first deposited on a baseplate only at the rib locations using additive friction stir deposition (AFSD). Structured light scanning is then used to measure the printed geometry. This geometry is finally used as the stock model for computer numerical control (CNC) machining. This paper details the hybrid manufacturing process that consists of: AFSD to print the preform, structured light scanning to generate the stock model and tool path, three-axis CNC machining, and post-process measurements for part geometry and microstructure.

42 ENGINEERING↗
DOE OSTI2023

Process planning for hybrid manufacturing using additive friction stir deposition

Additive friction stir deposition (AFSD) provides a solid-state approach to metal deposition that does not rely on local melting and solidification, but rather on kinetic energy and plastic flow. Here, in this study, AFSD is combined with structured light scanning, turning, and milling to produce metal components while considering the unique requirements imposed by the hybrid manufacturing process sequences. Two demonstrations are presented which include: 1) a cylindrical build plate selection to enable coordinate system transfer between deposition and turning of a hollow cone; and 2) intermittent deposition-machining operations with structured light scanning to fabricate a two-sided hexagon-cylinder geometry.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

3D Scanning Laboratory

The 3D Scanning Lab uses a number of technologies to capture 3D surface data. Those technologies are structured light scanning, discrete point measurement photogrammetry and Light Detecting and Ranging(LIDAR). Structured light is a non-contact optical technique used to capture as built surface geometries quickly and accurately. LIDAR is a laser scanning technique used to capture 3D surfaces. And photogrammetry uses a certified DSLR camera to measure discrete registered and non-registered points in 3D space. MSFC’s 3D Scanning Team uses 3D scanning to provide hardware inspections, reverse engineered CAD models, manufacturing/process development and digital assemblies. The inspection process compares the captured data to CAD, providing a color plot detailing the deviations of the scan data to the CAD model. Dimensional measurements and GD&T can also be interrogated. Inspection can provide scan-to-scan data comparisons which is ideal for assessing tested hardware, e.g. comparing data captured before and after hardware testing. Reverse engineering is used to develop CAD models from scan data. This is useful for heritage hardware studies, developing building or structural models and inputs for simulation studies and design efforts. The lab uses the 3D surface scan data to drive manufacturing/machining processes, termed match machining. This technique has been used to modify nozzles, injectors, additive manufactured parts, composite barrel sections, etc. Parts of an assembly can be scanned and assembled in a virtual environment providing an accurate 3D representation of the assembled hardware in its as-scanned state. This can provide detailed information of internal components that would otherwise not be accessible.

Advanced Manufacturing↗
DOE OSTI2022

A machining digital twin for hybrid manufacturing

Hybrid manufacturing consisting of metal additively manufactured preforms and computer numerical control (CNC) machining has been established to be an effective method for high material use rates. However, hybrid manufacturing introduces unique challenges. Near-net shape designs are typically selected, which result in a smaller margin for part placement within the stock and stringent requirements for work coordinate system identification. Additionally, less stock material reduces the preform stiffness, which limits the material removal rates during machining. This paper demonstrates a digital twin for CNC machining of a wire arc additively manufactured preform that implements: 1) structured light scanning for stock model identification and tool path generation; 2) a fused filament fabrication apparatus to attach temporary fiducials and scan targets to the preform that enable coordinate system definition for both the CAM and CNC machine; 3) preform and tool tip frequency response function measurements to enable stable milling parameter selection; and 4) post-manufacturing measurements of geometry, surface finish, and structural dynamics to confirm designer intent. These efforts define key components of the machining digital twin for hybrid manufacturing.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

In-Space Laser Forming Simulated Under Thermal Vacuum (TVAC) Conditions

NASA Marshall Space Flight Center is investigating laser forming under thermal vacuum conditions representative of the space environment through a partnership with the DARPA NOM4D program. The thermal gradient mechanism (TGM) is used to bend a metal sheet towards the laser optics. Laser equipment and process parameters are being optimized for thermal vacuum conditions. Such conditions are representative of the extreme cold and hot temperatures and high vacuum that exist on orbit or on the lunar surface. in situ photogrammetry and thermography assess the bend/counterbend and elucidate the TGM in thermal vacuum. Structured light scanning and metallography after bending reveal the macroscopic and microscopic structure after TGM.

thermal vacuum↗
NASA NTRSDate not supplied

Implementing Geometric Surface Imperfections into Sandwich Composite Cylinder Finite Element Method Models

The buckling responses of certain cylindrical shell structures are extremely sensitive to geometric surface imperfections. The NASA Engineering and Safety Center (NESC) Shell Buckling Knockdown Factor Project (SBKF) is conducting research to develop analysis-based buckling design recommendations. Experiments are used to verify the analysis-based factors, but the sensitivity of the test articles to geometric imperfections requires implementing as-manufactured imperfections into high-fidelity finite element method models. Data collection methods such as structured light scanning are used for all geometric surface data used in this work. Common preprocessing and visualization steps used in SBKF are discussed, and steps on how surface scans are prepared for implementation into a finite element model is described. The Python Tool for Implementing Geometric Imperfections in Reduced Structures (Py_TIGIRS), written specifically for the use with SBKF, is briefly described and uses eight functions to extract, modify, and write geometric imperfections into Abaqus input files. Results of the pre-processing methods and results from Py_TIGIRS are provided and compared for Composite Test Article (CTA) 8.2B. Excellent agreement between the visualized scan data and the FEM-extracted geometry is demonstrated. A brief example of why geometric surface imperfections are significant in nonlinear numerical analyses for thin cylinders in axial compression is provided as motivation to use tools such as Py_TIGIRS. Future development of Py_TIGIRS including expansion to structures of arbitrary geometry is planned.

Sandwich structures↗
NASA NTRSDate not supplied

Implementing Geometric Surface Imperfections into Sandwich Composite Cylinder Finite Element Method Models

The buckling responses of certain cylindrical shell structures are extremely sensitive to geometric imperfections. The NASA Engineering and Safety Center (NESC) Shell Buckling Knockdown Factor Project (SBKF) is conducting research to develop analysis-based buckling design recommendations. Experiments are used to verify the analysis-based factors, but the sensitivity of the test articles to geometric imperfections requires implementing as-manufactured imperfections into high-fidelity finite element method (FEM) models. Geometry measurement methods such as structured light scanning are used for all geometric surface data used in this work. Common preprocessing and visualization steps used in SBKF are discussed, and steps of how surface scans are prepared for implementation into a finite element model is described. The Python Tool for Implementing Geometric Imperfections in Reduced Structures (Py_TIGIRS), written specifically for the use with SBKF, is briefly described and uses eight functions to extract, modify, and write geometric imperfections into Abaqus input files. Results of the preprocessing methods and results from Py_TIGIRS are provided and compared for Composite Test Articles (CTA) 8.2, 8.2B, and 8.3. Excellent agreement between the visualized scan data and the FEM-extracted geometry is demonstrated. A brief example of why geometric surface imperfections are significant in nonlinear numerical analyses for thin cylinders in axial compression is provided as motivation to use tools such as Py_TIGIRS. Future developments of Py_TIGIRS including expansion to structures of arbitrary geometry is planned.

Geometric imperfections↗
NASA NTRSDate not supplied

Implementing Geometric Surface Imperfections into Sandwich Composite Cylinder Finite Element Method Models

The buckling responses of certain cylindrical shell structures are extremely sensitive to geometric imperfections. The NASA Engineering and Safety Center (NESC) Shell Buckling Knockdown Factor Project (SBKF) is conducting research to develop analysis-based buckling design recommendations. Experiments are used to verify the analysis-based factors, but the sensitivity of the test articles to geometric imperfections requires implementing as-manufactured imperfections into high-fidelity finite element method (FEM) models. Geometry measurement methods such as structured light scanning are used for all geometric surface data used in this work. Common preprocessing and visualization steps used in SBKF are discussed, and steps of how surface scans are prepared for implementation into a finite element model is described. The Python Tool for Implementing Geometric Imperfections in Reduced Structures (Py_TIGIRS), written specifically for the use with SBKF, is briefly described and uses eight functions to extract, modify, and write geometric imperfections into Abaqus input files. Results of the preprocessing methods and results from Py_TIGIRS are provided and compared for Composite Test Articles (CTA) 8.2, 8.2B, and 8.3. Excellent agreement between the visualized scan data and the FEM-extracted geometry is demonstrated. A brief example of why geometric surface imperfections are significant in nonlinear numerical analyses for thin cylinders in axial compression is provided as motivation to use tools such as Py_TIGIRS. Future developments of Py_TIGIRS including expansion to structures of arbitrary geometry is planned.

Geometric imperfections↗
DOE OSTI2020

Cutting force and stability for inserted cutters using structured light metrology

This paper describes force and stability prediction for inserted end and face mills using a reverse engineering approach. Structured light scanning is used to identify the spatial coordinates of the points that define the multiple insert cutting edges. These points are used to extract the cutting edge radius and angle and are then incorporated in a time domain simulation that predicts cutting force and tool/workpiece deflection for user-selected operating parameters. Good agreement between predicted and measured cutting forces is demonstrated. The process stability is then predicted using the validated force model and measured structural dynamics.

Machining↗
DOE OSTI2020

Cutting force and stability prediction for inserted cutters

Here, this paper presents an approach for inserted end/face mill force and stability predictions using a reverse engineering approach. Structured light scanning is implemented to identify the spatial coordinates of the points that define the multiple insert cutting edges. These points are analyzed to extract the cutting edge radius and angle values, which are then incorporated in a time domain simulation that predicts cutting force and tool/workpiece deflection for user-selected operating parameters. Good agreement between predicted and measured cutting forces is first demonstrated. The process stability is then predicted using the validated force model and measured structural dynamics. Observations about the stability dependence on insert geometry are finally presented for a selected end mill.

Machining↗
NASA NTRS2014

Cutting More than Metal: Breaking the Development Cycle

New technology is changing the way we do business at NASA. The ability to use these new tools is made possible by a learning culture able to embrace innovation, flexibility, and prudent risk tolerance, while retaining the hard-won lessons learned of other successes and failures. Technologies such as 3-D manufacturing and structured light scanning are re-shaping the entire product life cycle, from design and analysis, through production, verification, logistics and operations. New fabrication techniques, verification techniques, integrated analysis, and models that follow the hardware from initial concept through operation are reducing the cost and time of building space hardware. Using these technologies to be more efficient, reliable and affordable requires we bring them to a level safe for NASA systems, maintain appropriate rigor in testing and acceptance, and transition new technology. Maximizing these technologies also requires cultural acceptance and understanding and balancing rules with creativity. Evolved systems engineering processes at NASA are increasingly more flexible than they have been in the past, enabling the implementation of new techniques and approaches. This paper provides an overview of NASA Marshall Space Flight Center's new approach to development, as well as examples of how that approach has been incorporated into NASA's Space Launch System (SLS) Program, which counts among its key tenants - safety, affordability, and sustainability. One of the 3D technologies that will be discussed in this paper is the design and testing of various rocket engine components.

Singer, Chris↗