The data obtained from this sub-project will include quantitative knowledge of the beam/powder/melt pool interaction and the energy transport as a function of the electron beam and laser variables and state of powder.

Principal Investigators:

Steve Cockcroft The University of British Columbia

Mary Wells University of Waterloo

A key question in AM is the interrelationship between the melt consolidation of the powder and its dependency on beam and powder bed characteristics. Understanding these phenomena hinges on describing the transport processes occurring at a meso-scale. Many of the existing models do not account for the granularity of the problem and miss fine-scale physics that are known to affect the melt track characteristics. Knowledge in this area is still in its infancy and lacking a comprehensive understanding of the complex interaction between AM process parameters, the powder, and the previously consolidated layer in order that the fabricated microstructure can be predicted. The objective of this sub-project is to develop a meso-scale model to predict melt consolidation behaviour for a range of AM process parameters.

Principal Investigators:

Steve Cockcroft The University of British Columbia

AM models based on the finite element method have predominantly been used to describe phenomena at micro-to-meso scale. Drawbacks of the limited scale of these simulations are: 1) not taking into account the changing thermos-physical characteristics of the parts as they undergo fabrication, and 2) the impossibility of predicting part deformation and residual stresses that develop on account of the global force equilibrium considerations. Simulating the thermal field evolution will be investigated in this project. A key outcome of this sub-project will be the ability to conduct detailed thermal response in part level and possibly to optimize process parameters. The objective of this subproject is to develop macro-scale 3D model to simulate the thermal field evolution for AM processes.

Principal Investigators:

Yaoyao Fiona Zhao McGill University

The development of comprehensive numerical multi-physics models for laser and EB-based AM processes are crucial to providing a fundamental understanding of these AM processes. Three objectives are pursued in this sub-project: a) developing a 3D thermal stress model to predict the residual stress and deformation generated in EB-DED process at macro-scale; b) developing a 3D thermal stress model to predict the thermal stresses, inelastic strain and thermal field in EB-PBF process at the meso-scale; and; c) developing and verifying a 3D FE model to simulate cavity radiation transport in the build chamber of an ARCAM – Q20, based on build layer cross-sectional area.

Principal Investigators:

Steve Cockcroft The University of British Columbia

Daan Maijer The University of British Columbia

The microstructure developed in an AM part is strongly related to the process parameters in AM processes. The interface between the modeling of AM processes and the resultant microstructure and properties of the part are critical. Thus microstructures and properties will be quantified and related directly to process conditions and model predictions that are used to generate the sample.

Principal Investigators:

Hani Henein University of Alberta

Development of fast process simulations and surrogate reduced-order thermal models capable of high-speed process predictions and closed-loop control implementation is pursued in this sub-project.

Principal Investigators:

Daan Maijer The University of British Columbia

Thermo-mechanical modeling is beneficial for predicting residual stress and deformation of printed parts. Such models minimize trial and error experimental tests. Computational cost is the major challenging issue for process modeling. Therefore, the objectives of this project are to develop a fast predictive model and accelerate the simulation and modeling without losing much accuracy in predicting the final residual stress and deformation of the manufactured parts.

Principal Investigators:

Ehsan Toyserkani University of Waterloo

Assessing and controlling the geometry of a manufactured part is a critical aspect of any manufacturing technology. Although AM processes allow for considerable design freedom to make complex parts, they suffer from the lack of availability of reliable geometry assessment, control and optimization methods. Most AM processes currently require several steps involving trial-and-error/tacit steps before and after printing, to obtain a part corresponding to a given requirement. In this subproject, the part build geometry assessment methods for AM will be further developed to enable the broader industrialization of the technology.

Principal Investigators:

Ahmed Qureshi University of Alberta

The scope of subproject 2.3.2 is to study the mechanics of additively built lattice materials and the deviations of the expected mechanical behavior due to the presence of defects. Since these disruptions depend on the interplay between the base material and the material architecture, we explore these phenomena considering elastoplastic and hyperelastic base material properties. The objectives of the subproject are investigated in metallic and polymeric lattices:

• Metallic lattices (incorporating elastoplastic base material)
  In metallic lattices, our main interest is to characterize, to quantify, and to determine the impact of manufacturing induced defects on the mechanics of metallic lattice materials built with Selective Laser Melting under manufacturing constraints of cell size, minimum strut thickness, and porosity. The statistically quantified defects serve to generate predictive models that can better capture the properties of the as-built lattice and that guide the structural design of metallic lattice materials.
• Polymeric lattices (incorporating a hyperelastic base material)
  We are here extending the first objective to lattices that consist of a solid polymeric phase. Defects that disrupt the mechanical performance of metallic lattices can induce new functionalities in soft lattice materials made of a polymeric solid. After selecting a given cell topology, we will uncover principles that help us understand how non-linearity can result in the emergence of complex – yet exploitable – behavior in soft systems.

The knowledge generated from this subproject will be utilized to guide the design of 3D printed components made of metals and soft polymers.

Principal Investigators:

Damiano Pasini McGill University

Yaoyao Fiona Zhao McGill University

The objective of this sub-project is to study the mismatch between predicted properties from the design perspective using the intralattice software and the actual results obtained upon printing of lattice struts. The key components of this project involve determination of the critical cross sectional area, followed by statistical relationship linking the design file and geometry to the printing process and the obtained properties. This will be looked for various printing angles and configuration. The effect of resulting surface defects and dimensional deviations in lattice struts on its deformation behavior would be studied.

Principal Investigators:

Mathieu Brochu McGill University

Measurements of the geometry and radiation emitted by the laser-material interaction can be used to provide insight into process dynamics. This is to be accomplished by a sensor which captures both visible and IR data and processes the data to extract the critical process parameters. A model is also developed, which can be implemented with a controller to allow for reliable predictive control of LMP. The end-result of this sub-project will be a sensor monitoring system and model which can be used together for control.

Principal Investigators:

Amir Khajepour University of Waterloo

In-process vision data acquisition for AM typically involves a camera capturing the images of individual layers as the part is being built. Image processing examines the 2D geometry of the individual layer to detect defects. A 3D map can be constructed by combining measurements from previous layers. The process-reconstructed vision and radiometric 2D/3D architecture can be compared with the CAD digital design, as well as with part CT scan data from post-processing measurements. For LPF, a high power laser diode illumination source and high speed CMOS camera will be set up to focus on areas of interest in the process zone, where data will be extracted to refine process parameters based on potential perturbations or parameter drift. Laser illumination will enable clear vision through plasma plume and high intensity radiance without pixel saturation. In addition, for LPB and BJ, a structured lighting laser displacement system will be implemented to scan areas of interest in the fabricated layer, to extract information on powder spread defects, as well as layer fabrication defects.

Principal Investigators:

Ahmed Qureshi University of Alberta

Using eddy current sensors in the AM process is not effective due to the difficulty in distinguishing the surface noise from sub-surface defects. In this sub-project strategies will be taken into consideration to make the use of eddy current sensors for detection of sub-surface defects and features in LPF-AM systems possible. The end result of this sub-project is to deploy the novel detector in the commercially available LPF-AM systems to monitor defects in real-time.

Principal Investigators:

Behrad Khamesee University of Waterloo

Ehsan Toyserkani University of Waterloo

Porosities can occur in the metal matrix as a result of intended features or designs, or as part of process instability, resulting in porous defects. These porous defects are detrimental to part quality, as they provide a location for crack initiation and propagation, thus reducing the strength of the part. An ultrasonic sensing system is being developed as a non-contact ultrasonic interrogation technique, to detect information on the interior or surface of the solid, liquid or gaseous titanium alloy samples produced by the LPB-AM process.

Principal Investigators:

Ehsan Toyserkani University of Waterloo

The behavior of electron beam processes is complex and difficult to fully capture using modeling strategies. The work in sub-project 3.2.1 will focus on the development of experimentally-driven models for understanding the melting mode transition between lack of fusion, conduction and keyhole mode. Various approaches such as statistical, multi-input-multi-output models, grey-box models, as well as physics-based models will be explored to explain the observed phenomena. The models will be refined to perform beam path optimization for reduced surface roughness and reduced pore occurrence. If sensing can be deployed, these models will be enhanced using sensor-generated data to improve on the existing assumptions with more realistic process descriptors. The optimization and control strategies will be deployed towards the production of samples with complex architectures.

Principal Investigators:

Mihaela Vlasea University of Waterloo

Developing controllers that manage the dimensional accuracy and desired part microstructure, while effectively increasing process speed, repeatability, and reliability is pursued in this sub-project. Furthermore, machine-learning algorithms will be developed that will be customized to enable a smart data-picking paradigm from a large stream of data forms sensors that could be about 4 GB/s.

Principal Investigators:

Ehsan Toyserkani University of Waterloo

In this sub-project, a reliable model for powder compaction will be developed (via custom scripted discrete element modeling (DEM)), along with a powder compaction detection system for various powder spreading mechanisms. The model and detection system have the potential to be included in commercially available systems, including LPB and BJ. In addition, in this project, a reliable model for the pore network will be developed for future simulations of the dynamic liquid-powder interactions, along with software algorithms to control the binder droplet characteristics (via pattern recognition) for jetted materials onto powder substrates.

Principal Investigators:

Mihaela Vlasea University of Waterloo

Kaan Erkorkmaz University of Waterloo

Powder compaction can be achieved using a variety of mechanical compaction approaches such as: changing the rotational and linear velocity of a counter-rotating roller used to disperse powders, or by using a mechanical powder layer-wise compaction arm, or a vibration-inducing piezoelectric actuator. In addition, powder compaction and disturbance can be induced further through binder-powder interactions. The effect of these methods on the AM-made parts’ quality will be investigated to simulate and quantify their effect on part densification and to test the feasibility to design a reliable closed-loop control system for compaction density testing.

Principal Investigators:

Mihaela Vlasea University of Waterloo

Kaan Erkorkmaz University of Waterloo

The objective of this sub-project is to identify the optimal path for deposition, such that the AM takes place with the highest possible productivity, and within safe and acceptable production envelopes for the process and machine tool. The study is a scientific and technological first in understanding the trajectory optimization problem by modeling the thermal and stress defects of build material.

Principal Investigators:

Yusuf Altintas The University of British Columbia

The adaptive path planning protocols for LPBF and DED will be formulated based on a discrete-time system and it will encompass the adaptability property using a soft computing approach, particularly neural network, dynamic models, and black-box models. This will include two steps: 1) validation and optimization of the models developed in project 3.4.1, and 2) development of computing predictive protocols/controllers. Model-based platforms developed in 3.4.1 will be validated using an experimental design approach to optimize the dimensional accuracy, maximum cooling/solidifications rates and residual stresses. The target material is Ti and steels, subject to change based on material availability.

Principal Investigators:

Mihaela Vlasea University of Waterloo

In this sub-project, improving the powder catchment efficiency for LPF-AM using a regulated magnetic field around the powder stream to push particles towards the centre was investigated. The numerical and experimental results suggest that the proposed methodologies/setups are not sensitive adequately to increase the powder catchment efficiency.

Principal Investigators:

Ehsan Toyserkani University of Waterloo

Behrad Khamesee University of Waterloo

In this sub-project, two objectives are pursued in parallel: 1) embedding optical sensors in LPB-AM printed functional parts, and 2) developing look-up tables of cellular structures with feature optimization. These two objectives will eventually converge into one for the purpose of creating smart/functional lightweight prototypes. The cellular structures would be optimized to simplify embedding sensors for sensing multiple parameters such as temperature, stress, etc.

Principal Investigators:

Ehsan Toyserkani University of Waterloo

In conventional LPF-AM, one face of substrate cannot be accusable due to the need for a platform or substrate to support the fabricated 3D objects during the process. The objective of this sub-project is to develop a magnetic levitation system that can be easily incorporated into LPF-AM, to enable the conductive metal nucleus to be freely levitated in space to achieve full position deposition.

Principal Investigators:

Behrad Khamesee University of Waterloo

Ehsan Toyserkani University of Waterloo

This sub-project will utilize the knowledge generated from theme 2 to manufacture new and innovative implant structures. The results will materialize in new technology that can mimic bone tissue properties, through a tuned mixture of random and periodic variation of lattice materials that can enhance bone ingrowth. The mechanical properties of these implants will be tuned to match the variation of the elastic modulus of the surrounding bone tissue, so as to reduce concurrently bone resorption induced by stress shielding, subsidence, and bone-implant interface micromotion. The implant design will account for the impact of manufacturing defects that emerge during the AM process.

Principal Investigators:

Damiano Pasini McGill University

Sub-project 4.2.2 uses the background AM-based technologies developed at University of Waterloo and McGill University to develop efficient design optimization methods to improve the manufacturability of the conformal cooling channels, to optimize the location of sensors, and to improve the heat dissipation performance. Modeling approaches developed in Theme 2 are being used and integrated with existing thermal and mechanical simulation software for conformal channel design.

Principal Investigators:

Yaoyao Fiona Zhao McGill University

Ehsan Toyserkani University of Waterloo

The resource sector (oil/gas and mining) would gain critical benefits from the use of FGM printed AM structures. The use of a WC reinforced Nickel based matrix as a coating has already enhanced the wear resistance of digging tools but a tailored compositional transition from the base material would further increase their in-service lifespan. FGM use requires knowledge of developing strategies for working with multi-hopper in AM processes. In this sub-project, strategies for AM of FGM parts using AM-plasma transfer arc using two hoppers will be developed.

Principal Investigators:

Hani Henein University of Alberta

Part cooling time after plastic injection counts for almost 44% of cycle time. Reducing cooling time would substantially increase productivity. LPF-AM has the capability of producing FGM molds composed of Cu-embedded in a tool steel matrix to reduce the cooling time. The Cu acts as a heat sink, providing fast cooling to substantially reduce cycle time. The tool steel on the molding active surface provides the mechanical strength and wear resistance required for the tool.

Principal Investigators:

Kevin Plucknett Dalhousie University

The objective of this sub-project is to evaluate the repair interface, conducted by LPF-AM, and its effect on the service environment: 1) the reparability and deposition compatibility of the substrate, 2) the deposited material mechanical performance, and 3) the wear and corrosion response.

Principal Investigators:

Kevin Plucknett Dalhousie University

This sub-project will utilize the EBWF-AM process to investigate the reparability of high temperature materials that have a high affinity with gaseous contaminant, such as some titanium alloys and superalloys.

Principal Investigators:

Mathieu Brochu McGill University

This subproject will use plasma transfer arc AM with the same procedures explained in 4.4.1 and 4.4.2.

REPAIR PROCESS
This project provides a strategy for scan-assisted repair by additive manufacturing. A small interface gathering a number of algorithms is used for identification of damages and repair by subtractive and additive manufacturing.

MATERIALS
This project also addresses the application of Fused Filament Fabrication (FFF) to Metal Matrix Composites. The FFF is one of the AM processes that can benefit from the strategy being developed in the summary above. FFF is gaining interest in Additive Manufacturing of components. While it has largely grown based on the use of polymers, the feasibility to incorporate other classes of materials is an attractive option. When metals are incorporated into the polymer, FFF provides the opportunity to retain the fine structure of the rapidly solidified powder. In order to take full advantage of FFF for application in the resource sector, both metallic and ceramic powders will be mixed into a polymer filament that will subsequently be used for 3D printing.

Principal Investigators:

Hani Henein University of Alberta