Session: 16-03-04: Foundational Framework II

Paper Number: 172651

Manufacturing a New Paradigm - Why We Need Data 

Integrated Computational Materials Engineering (ICME) has revolutionized materials and process development by connecting advanced computational models across various length scales, from the atomic to the macroscopic. This interconnected approach allows scientists to understand the intricate relationships between processing, structure, properties, and (most importantly) performance. Since being formally recognized as a discipline in 2008, the underlying paradigm of ICME has been utilized across a wide range of material classes, impacting the development of everything from traditional cast alloys to advanced structural composites and specialized functional materials. The ultimate goal of ICME is to accelerate materials design and deployment by predicting performance and optimizing processing parameters to better inform physical experimentation.

Additive manufacturing (AM) is particularly well-suited to leverage the power of ICME due to its inherent digital nature, starting with the initial computer-aided design (CAD) file through modern non-destructive evaluation (NDE) techniques of the final component. Additionally, AM exhibits an overlap across the material, process, and design – each is intimately connected with the other two. Therefore, an AM-based digital thread offers unique control over processing parameters and the potential for tailoring material properties with high precision. However, the effective implementation of ICME for AM faces challenges related to verification, validation, and uncertainty quantification (VVUQ). Accurate and reliable computational models rely heavily on comprehensive, high-quality experimental datasets for comparison and calibration. A scarcity of suitable benchmark data, particularly for emerging AM processes, hinders the development and refinement of robust ICME tools geared towards AM.

The Office of Naval Research (ONR) identified this gap in knowledge, especially as AM research shifts towards larger-scale manufacturing processes relevant to marine applications. The complexity of these AM processes, combined with the need for stringent performance metrics to meet needs of the end user, necessitates a deeper understanding of the underlying materials science and the influence of processing parameters on final part quality. To address this challenge, ONR helped initiate an off-shoot program from the original AM-Bench series which focused on generating the extensive experimental datasets needed for large-scale AM processes.

The data generated from this program will serve as a crucial foundation for advancing ICME capabilities for large-scale AM, enabling the development of more accurate and predictive models, accelerating the qualification of large-scale AM parts for critical applications, and ultimately unlocking the full potential of AM. This initiative highlights the growing importance of data-driven approaches in materials science and manufacturing and the strategic investment required to bridge the gap between computational modeling and experimental validation.

Presenting Author: Charles Fisher Office of Naval Research

Presenting Author Biography: Dr. Charles Fisher is the Integrated Computational Materials Engineering (ICME) Technology Expert at the Naval Surface Warfare Center, Carderock Division (NSWCCD). He has been with the U.S. Navy for over 12 years working in ICME-related programs, with a focus on inserting ICME technologies into the design and manufacturing paradigms. He is currently detailed as a Program Officer at the Office of Naval Research (ONR) in the areas of additive manufacturing, alloy and process simulation, and structural material design. He serves as the Chair of the TMS ICME committee and is the Chair for the AWS A9 Committee on Computerization of Welding Information. He holds a B.S. in Materials Engineering from Iowa State University and a M.S. and Ph.D. in Materials Science and Engineering from the University of Florida.

Authors:

Charles Fisher Office of Naval Research