scholarly journals Test Frame Design for the Characterization of Additive Manufacturing Compliant Materials

2018 ◽  
Author(s):  
Sean T. Fry ◽  
Cameron J. Turner
Keyword(s):  
Additive Manufacturing ◽  
General Purpose ◽  
Combined Loading ◽  
Biaxial Test ◽  
Frame Design ◽  
Gpgpu Computing ◽  
Test Frame ◽  
Reducing Costs ◽  
Graphics Processing

This work presents a design of a 6 degree of freedom (DOF) robotic test frame designed to provide multiple and combined loading scenarios for additive manufacturing (AM) materials. The need is to provide a more in-depth look into the material properties of nonlinear anisotropic materials as traditional uniaxial or biaxial test frames have been shown to be inefficient in providing accurate material property values. With the application of surrogate models with General Purpose Graphics Processing (GPGPU) computing, “real-time” characterization is achievable. The work provided is a next generation 6 DOF test frame designed to reducing costs, increasing workspace, and reducing overall size over previous designs.

Open Uniaxial Test Machine (OpenUTM): Part 1 — A Low-Cost Electrohydraulic Test Frame for Additive Manufacturing Part Qualification

2018 ◽  
Author(s):  
John C. Steuben ◽  
Athanasios P. Iliopoulos ◽  
John G. Michopoulos
Keyword(s):  
Additive Manufacturing ◽  
Low Cost ◽  
Test Machine ◽  
Mechanical Stiffness ◽  
Uniaxial Test ◽  
Bill Of Materials ◽  
Test Frame ◽  
Force Displacement

A wide variety of scientific and engineering activities require the use of testing machines in order to acquire data regarding the response of materials subjected to mechanical loads. This is particularly applicable to the domain of Additive Manufacturing (AM), where mechanical qualification is essential. Such machinery should be capable of applying loads at required levels and exhibit high mechanical stiffness. Accurate force, displacement, and strain measurements are also required. As a consequence, such testing machines are typically very costly. In the present paper we introduce the Open Uniaxial Test Machine (OpenUTM) project, aimed at providing a low-cost (less than $2500.00) material testing hardware/software framework. This paper will focus on the engineering design and hardware aspects of the OpenUTM project, with particular attention paid to the use of an electrohydraulic actuator (EHA) to provide test loads. A full bill of materials and drawings package is provided, in order to enable the use of the OpenUTM framework by research groups with minimal machine tooling. We introduce several case studies demonstrating the successful use of the OpenUTM frame in AM research efforts, including the testing and characterization of AM polymers and ceramics. We conclude with discussion of the software aspects of the OpenUTM framework, which will be elaborated upon in a follow-up paper (part two). We also present a series of potential avenues towards the improvement of the OpenUTM frame in future hardware iterations.

Towards Real-Time Composite Material Characterization Using Surrogate Models and GPGPU Computing

2015 ◽  
Author(s):  
John Steuben ◽  
John G. Michopoulos ◽  
Athanasios Iliopoulos ◽  
Cameron Turner
Keyword(s):  
Real Time ◽  
Material Characterization ◽  
High Speed ◽  
Surrogate Models ◽  
General Purpose ◽  
Material System ◽  
Computationally Efficient ◽  
Gpgpu Computing ◽  
Material Systems ◽  
Graphics Processing

In this paper we address the particular need for high-speed or “real-time” characterization of realistic anisotropic material systems such as laminated composites. This is driven by the desire to dynamically alter the loading paths applied by a multiaxial robotic test frame during the testing of a specimen, so that strain states are developed in the specimen in a manner that activates the maximum excitation of the specimen’s constitutive properties. In order to achieve this goal, we present an evolutionary adaptation of earlier work into computationally efficient material characterization using response-surface surrogate models. This approach is enhanced by the adoption of highly-parallel General Purpose Graphics Processing (GPGPU) computing. We discuss the challenges of adapting the characterization problem for GPGPU computing, particularly in terms of parallelization, synchronization, and approximation. Two parallelized algorithms for characterization are developed, and the merits of each are discussed. We then demonstrate validation results on a simple linear-elastic material system, and present statistical data which demonstrate the robustness of the approach in the presence of experimental noise. We conclude with remarks regarding the performance of the GPGPU-enabled characterization algorithm, and its applicability to more complex material systems.

scholarly journals DSPSR: Digital Signal Processing Software for Pulsar Astronomy

2011 ◽  
Vol 28 (1) ◽  
pp. 1-14 ◽  
Author(s):  
W. van Straten ◽  
M. Bailes
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Graphics Processing Units ◽  
High Performance ◽  
Digital Signal ◽  
General Purpose ◽  
Design Decisions ◽  
Extensive Range ◽  
Processing Software ◽  
Graphics Processing

Abstractdspsr is a high-performance, open-source, object-oriented, digital signal processing software library and application suite for use in radio pulsar astronomy. Written primarily in C++, the library implements an extensive range of modular algorithms that can optionally exploit both multiple-core processors and general-purpose graphics processing units. After over a decade of research and development, dspsr is now stable and in widespread use in the community. This paper presents a detailed description of its functionality, justification of major design decisions, analysis of phase-coherent dispersion removal algorithms, and demonstration of performance on some contemporary microprocessor architectures.

scholarly journals Characterization of a High Temperature Ceramics Produced via Two-Step Additive Manufacturing

Open Ceramics ◽  
2021 ◽  
pp. 100165
Author(s):  
Sergey N. Golubev ◽  
Olga Yu. Kurapova ◽  
Ivan Yu. Archakov ◽  
Vladimir G. Konakov
Keyword(s):  
High Temperature ◽  
Additive Manufacturing

scholarly journals Fatigue characterization of Titanium Ti-6Al-4V samples produced by Additive Manufacturing

2016 ◽  
Vol 2 ◽  
pp. 3168-3176 ◽  
Author(s):  
Victor Chastand ◽  
Astrid Tezenas ◽  
Yannick Cadoret ◽  
Philippe Quaegebeur ◽  
Wilson Maia ◽  
...  
Keyword(s):  
Additive Manufacturing

scholarly journals Automated Testing and Characterization of Additive Manufacturing (ATCAM)

2021 ◽  
Author(s):  
Arash Alex Mazhari ◽  
Randall Ticknor ◽  
Sean Swei ◽  
Stanley Krzesniak ◽  
Mircea Teodorescu
Keyword(s):  
Additive Manufacturing ◽  
Fused Deposition Modeling ◽  
Cell System ◽  
Automated Testing ◽  
Fused Deposition ◽  
Deposition Modeling ◽  
Machine Calibration

AbstractThe sensitivity of additive manufacturing (AM) to the variability of feedstock quality, machine calibration, and accuracy drives the need for frequent characterization of fabricated objects for a robust material process. The constant testing is fiscally and logistically intensive, often requiring coupons that are manufactured and tested in independent facilities. As a step toward integrating testing and characterization into the AM process while reducing cost, we propose the automated testing and characterization of AM (ATCAM). ATCAM is configured for fused deposition modeling (FDM) and introduces the concept of dynamic coupons to generate large quantities of basic AM samples. An in situ actuator is printed on the build surface to deploy coupons through impact, which is sensed by a load cell system utilizing machine learning (ML) to correlate AM data. We test ATCAM’s ability to distinguish the quality of three PLA feedstock at differing price points by generating and comparing 3000 dynamic coupons in 10 repetitions of 100 coupon cycles per material. ATCAM correlated the quality of each feedstock and visualized fatigue of in situ actuators over each testing cycle. Three ML algorithms were then compared, with Gradient Boost regression demonstrating a 71% correlation of dynamic coupons to their parent feedstock and provided confidence for the quality of AM data ATCAM generates.

Sign in / Sign up

Export Citation Format

Share Document