Modern metals processing: transfer of knowledge and core skills to new and emerging technologies

Lead Research Organisation: University of Sheffield
Department Name: Materials Science and Engineering

Abstract

Creativity and innovation in metal manufacturing is crucial for maintaining a competitive UK based metals industry. This applies to both current production methodologies such as rolling, forging etc and emerging disruptive technologies such as shaped metal deposition. Over the last ten years IMMPETUS (Institute for Microstructural and Mechanical Process Engineering: The University of Sheffield) has developed its unique systems driven approach for process and property optimisation for the latest metals process routes with significant success on the national/international stages. The ideal for predicting microstructure and properties is to use multi-scale modelling driven by well defined physically based equations. However, even where the process is well established and thought to be well understood, the reality is that there are inevitable uncertainties within such multi-scale models, and consequently most are not truly physically-based. Rather they rely on empirical parameters that allow the models to fit the data. Moreover, where the process is immature, as is the case with the projects we intend to investigate, the basic physics cannot be described accurately until the mechanisms are fully established experimentally, which can prove time-consuming. In order to cover the intractable factors not adequately and entirely described by physically based models, and to fast track the development of emerging non-traditional metal manufacturing technologies, we use hybrid models that merge (fuse) discrete data with knowledge-based and physically-based models to account for the uncertainties in the material processing route. This is a powerful approach for accurate and transparent process behaviour prediction even when data is sparse, knowledge is imprecise, but updated more often than not. All the modelling is informed and verified through the use of an impressive but parsimonious array of experimental techniques. We believe it is timely to apply such a strategy to new exciting technologies where the research is inevitably high risk, high adventure and certainly high impact. Specifically, we intend establish a novel approach to the modelling of friction stir and linear friction welding of steels and titanium alloys using a combination of our unique arbitrary strain path and thermomechanical compression machines and access to fully instrumented friction welding machines. In addition, we will bring our skills to bear on innovative metals processing with direct access to state-of-the-art equipment for e.g. shaped metal deposition. Pervasive to all of these processes is that the final microstructure is formed through transformation under dynamic conditions, with the presence of steep thermal gradients, intentional/unintentional stresses and plastic strain rates for which the current phase transformation models do not adequately predict microstructure. For all these areas, it is essential to retain highly skilled staff who have a proven track record in interdisciplinary integrated research.

Publications

10 25 50
 
Description Friction Stir Welding (FSW) is increasingly popular but remains a challenge for Ti alloys and steels. The complex material flow and thermal history makes it difficult to fully understand, predict and design. In our work, novel intelligent modelling and advanced data-driven correlation analysis have been applied to improve the efficiency and reliability of FSW. For the first time, a systems-modelling framework (based on Granular Computing) has been developed to predict and optimise the process' operating window, replacing expensive experimental trials and allowing a fundamental understanding of the process/properties relationship. A fully-coupled thermomechanical finite element model of FSW has been created using the Arbitrary Lagrangian Eulerian formulation of Abaqus to predict temperature, strain, strain rate and stress distributions. Model formulation and validation has been greatly aided by a novel fully instrumented sensory platform (ARTEMIS), which gives real-time in-process variables, allowing us to introduce on-line control for optimised welds, critical for success in steel and Ti alloys. FSW of Ti alloys is one of the greatest challenges as a result of low thermal conductivity and high reactivity. Understanding the FSW process is complicated by phase transformations on cooling that eradicates the high temperature structure. We have developed a unique approach through reconstructing the high temperature crystallographic texture from the room temperature structure. This has shown for the first time that most of the weld is formed in the beta phase, with a simple shear texture, giving a final texture related to the fixed axis of the work piece and not the local shear reference frame, i.e. the thermal stresses appear to dictate the crystallographic variant selection. In addition to our unique approach to quantifying high temperature deformation structure, we have used this to bring new insight into the thermomechanical processing of Ti alloys, specifically to produce gas turbine alloys free from macro zones that are known to origin of dwell fatigue crack initiation. Based on this work TIMET are introducing new production schedules with tangible benefits in reducing susceptibility to dwell fatigue. In addition, a validated physically-based model of microstructure and texture evolution during thermo-mechanical processes has been developed which includes microstructure deformation using a Crystal-Plasticity Finite Element model coupled with a Phase-Field model (which has proved far more powerful than the cellular automata model which we initially worked on). Our high-value manufacturing sectors (e.g. gas turbine engines) depend on traditional metal-forming technologies of forging and casting. Near Net-Shape (NNS) manufacturing technologies are disruptively displacing traditional technologies with greatly reduced resource consumption. The PG has allowed a major expansion of our Additive Layer Manufacturing (ALM) facility to address the needs of industry, hand in hand with fundamental research. A combination of thermodynamic modelling and expert experimental design has informed a programme which has taken the process from novelty to one which can produce complex shapes with mechanical properties that at least match those of the conventional route. We have not only made the process commercially viable for Ti-6Al-4V aerospace alloys, but also for a wide range of applications including heat shields for formula 1 and hip prostheses. A key challenge with ALM is that it currently uses alloys designed for the conventional wrought route which are unlikely to be optimum for ALM-the future will require alloys designed specifically for these resource efficient process routes. We are employing our integrated modelling methodologies to develop new alloys for ALM, including Ti alloys and Ti aluminides. Our novel alloy design approach is also being applied to new generation materials including metallic glasses and high entropy alloys.
Exploitation Route The models described in the above two sections for friction stir welding have allowed us to introduce on-line control for optimised welds in friction stir welding and to prevent defect formation, critical for success in steel and Ti alloys. Moreover, a model is available that can predict the process conditions that are required to provide the optimum weld quality. Further development of the process is now possible through the identification of previously unknown 'causal' relationships between the internal process variables.



The microstructural models developed for thermomechanical processing are versatile and have been proved successful in predicting microstructure and crystallographic texture evolution in other thermo-mechanical processes including forging and rolling. The impact of these models has been such that Tata Steel has recruited Dr Yongjun Lan, who was the named researcher on the platform grant, to give the company a leading edge in microstructure and texture predictions.



The operation of near alpha Ti alloys for gas turbine discs is limited by the concerns of dwell fatigue, which has catastrophic consequences should the disc fail. The initiation of dwell fatigue cracks starts in macro zones that are formed during solidification and survive the subsequent thermomechanical process. Our novel method for predicting the high temperature deformation structure from the room temperature microstructure for each stage of the production route has allowed TIMET to see how macro zones change during the process and thereby how to break them up. Based on this work TIMET are introducing new production schedules with tangible benefits in reducing susceptibility to dwell fatigue.



Near Net-Shape (NNS) manufacturing technologies are disruptively displacing traditional technologies with greatly reduced resource consumption. The PG has allowed a major expansion of our Additive Layer Manufacturing (ALM) facility to address the needs of industry, hand in hand with fundamental research. A combination of thermodynamic modelling and expert experimental design has informed a programme which has taken the process from novelty to one which can produce complex shapes with mechanical properties that at least match those of the conventional route. We have used this knowledge to produce proof of concept parts for a wide range of applications, including aerospace (e.g. partner Rolls-Royce), biomedical (e.g. partner JRI), automotive etc. Parts made by us have been tested on e.g. formula 1 cars and been shown to out perform the conventional product. We are effectively in a position to produce such components commercially.
Understanding the friction stir welding process has proved difficult because of the complex material flow and thermal history, and because in titanium alloys and steels, the high temperature structure formed during FSW is lost during cooling. A Computational Fluid Dynamics approach is commonly used to simulate the steady state temperature distributions during Friction Stir Welding, but has severe limitations. In this project a fully-coupled thermomechanical finite element model of FSW has been created using the Arbitrary Lagrangian Eulerian formulation of Abaqus to predict temperature, strain, strain rate and stress distributions. The models developed during this project have shown that it is indeed possible to predict the full time-history of the thermo-mechanical fields influencing both the material weldability and tool life through the complete simulation of the three phases of the process (plunge, dwell and steady state). Moreover the coupling with the newly developed microstructural models has shown that the experimentally measured textures can be accurately predicted. Moreover, for the first time, a systems-modelling framework, based on granular computing, has been developed and applied within the context of predicting multiple properties for the FSW processed welds to predict and optimise the process' multi-scale operating window - as opposed to carrying out time consuming and expensive experimental trials.



The prediction of crystallographic texture development during hot working (e.g. rolling and forging) has long been a topical subject. While deformation textures have been reasonably predicted in the literature the research carried out in this project has demonstrated that both recrystallization and transformation textures can also be quantitatively predicted with minimal number of parameters and for a range a materials of Face-Centred and Body-Centred-Cubic structures. The validated physically-based model of microstructure and texture evolution during thermo-mechanical processes includes microstructure deformation using a Crystal-Plasticity Finite Element model coupled with a Phase-Field model (which has proved far more powerful than the cellular automata model which we initially worked on). All these models offer new avenues for the prediction of the material response during the process including the formation of defects when coupled with a damage model such as the Cellular Automata Finite Element (CAFÉ) model developed in IMMPETUS.



One of the problems with understanding the thermomechanical processing of titanium alloys is that phase transformation on cooling removes the high temperature structure and therefore there is only indirect information available from the observed microstructure. We have developed a unique approach through reconstructing the high temperature crystallographic texture and microstructure from the room temperature microstructure. We have applied this to friction stir welding and hot rolling of several Ti aerospace alloys. For FSW, this has shown for the first time that most of the weld is formed in the beta phase, with a simple shear texture, giving a final texture related to the fixed axis of the work piece and not the local shear reference frame, i.e. the thermal stresses appear to dictate the crystallographic variant selection. In addition to our unique approach to quantifying high temperature deformation structure, we have used this to bring new insight into the thermomechanical processing of Ti alloys, specifically to produce gas turbine alloys free from macro zones that are known to origin of dwell fatigue crack initiation.



Near Net-Shape (NNS) manufacturing technologies are disruptively displacing traditional technologies with greatly reduced resource consumption. We have extensively expanded our Additive Layer Manufacturing (ALM) facility to address the needs of industry, hand in hand with fundamental research. A combination of thermodynamic modelling and expert experimental design has informed a programme which has taken the process from novelty to one which can produce complex shapes with mechanical properties that at least match those of the conventional route. Thus, we have moved from the standard "form on demand", where the shape is specified, towards the "microstructure on demand" which is required to optimise mechanical properties. We are now moving towards designing alloys specifically for the ALM route, given that the current approach is to use alloys developed for the cast and forged route. Our novel alloy design approach is also being applied to new generation materials including metallic glasses and high entropy alloys.
Sectors Manufacturing/ including Industrial Biotechology

URL http://www.immpetus.group.shef.ac.uk/
 
Description Friction Stir Welding (FSW) is increasingly popular but remains a challenge for Ti alloys and steels. The complex material flow and thermal history makes it difficult to fully understand, predict and design. In our work, novel intelligent modelling and advanced data-driven correlation analysis have been applied to improve the efficiency and reliability of FSW. For the first time, a systems-modelling framework (based on Granular Computing) has been developed to predict and optimise the process' operating window, replacing expensive experimental trials and allowing a fundamental understanding of the process/properties relationship. A fully-coupled thermomechanical finite element model of FSW has been created using the Arbitrary Lagrangian Eulerian formulation of Abaqus to predict temperature, strain, strain rate and stress distributions. Model formulation and validation has been greatly aided by a novel fully instrumented sensory platform (ARTEMIS), which gives real-time in-process variables, allowing us to introduce on-line control for optimised welds, critical for success in steel and Ti alloys. FSW of Ti alloys is one of the greatest challenges as a result of low thermal conductivity and high reactivity. Understanding the FSW process is complicated by phase transformations on cooling that eradicates the high temperature structure. We have developed a unique approach through reconstructing the high temperature crystallographic texture from the room temperature structure. This has shown for the first time that most of the weld is formed in the beta phase, with a simple shear texture, giving a final texture related to the fixed axis of the work piece and not the local shear reference frame, i.e. the thermal stresses appear to dictate the crystallographic variant selection. In addition to our unique approach to quantifying high temperature deformation structure, we have used this to bring new insight into the thermomechanical processing of Ti alloys, specifically to produce gas turbine alloys free from macro zones that are known to origin of dwell fatigue crack initiation. Based on this work TIMET are introducing new production schedules with tangible benefits in reducing susceptibility to dwell fatigue. In addition, a validated physically-based model of microstructure and texture evolution during thermo-mechanical processes has been developed which includes microstructure deformation using a Crystal-Plasticity Finite Element model coupled with a Phase-Field model (which has proved far more powerful than the cellular automata model which we initially worked on). Our high-value manufacturing sectors (e.g. gas turbine engines) depend on traditional metal-forming technologies of forging and casting. Near Net-Shape (NNS) manufacturing technologies are disruptively displacing traditional technologies with greatly reduced resource consumption. The PG has allowed a major expansion of our Additive Layer Manufacturing (ALM) facility to address the needs of industry, hand in hand with fundamental research. A combination of thermodynamic modelling and expert experimental design has informed a programme which has taken the process from novelty to one which can produce complex shapes with mechanical properties that at least match those of the conventional route. We have not only made the process commercially viable for Ti-6Al-4V aerospace alloys, but also for a wide range of applications including heat shields for formula 1 and hip prostheses. A key challenge with ALM is that it currently uses alloys designed for the conventional wrought route which are unlikely to be optimum for ALM-the future will require alloys designed specifically for these resource efficient process routes. We are employing our integrated modelling methodologies to develop new alloys for ALM, including Ti alloys and Ti aluminides. Our novel alloy design approach is also being applied to new generation materials including metallic glasses and high entropy alloys.
First Year Of Impact 2004
Sector Aerospace, Defence and Marine,Manufacturing, including Industrial Biotechology,Transport
Impact Types Economic

 
Description EPSRC
Amount £217,384 (GBP)
Funding ID EP/I012214/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Academic/University
Country United Kingdom
Start 06/2011 
End 05/2015
 
Description ArcelorMittal 
Organisation ArcelorMittal
Country Luxembourg 
Sector Private 
PI Contribution A new method of measuring martensite transformation has been devised. This allows large samples to be measured and then their microstructure subsequently investigated.
Collaborator Contribution Sponsorship of the PhD project. Supply of steel materials for the project.
Impact A new dilatometer has been constructed.
Start Year 2011