RESEARCH PROJECTS
Multi-Scale Simulation of Dynamic Strain Aging in Al-Mg Alloy
- Catalin R. Picu,
Associate Professor,
Department of Mechanical, Aerospace, and Nuclear Engineering.
E-mail: picuc-at-rpi.edu.
- Antoinette M. Maniatty,
Professor,
Department of Mechanical, Aerospace, and Nuclear Engineering.
E-mail: maniaa-at-rpi.edu
- Frédéric Barlat, Technology Specialist, Alcoa Technical Center.
- Damon J. Burnett, Graduate Research Assistant,
Department of Mechanical, Aerospace, and Nuclear Engineering.
- Dawei Zhang, Graduate Research Assistant,
Department of Mechanical, Aerospace, and Nuclear Engineering.
E-mail: zhangd-at-rpi.edu
- Erick Pulido,
Undergraduate Research Assistant,
Department of Mechanical, Aerospace, and Nuclear Engineering.
Summary:
The objective of this project is to develop a model to predict
phenomena leading to poor formability in Al-Mg alloys based on
the underlying deformation mechanisms. Magnesium is added to
aluminum to improve strength properties but is found to also
have a detrimental effect on formability. The microstructural
mechanism responsible for poor formability is a process called
dynamic strain aging. Dynamic strain aging results from
fast diffusing solute atoms, such as magnesium, interacting with
dislocations. These interactions lead to unsteady, collective
motion of dislocations, within grains and across grain boundaries,
resulting in unstable flow and hence poor formability. At the
macroscopic level, a key defining manifestation of dynamic
strain aging is a negative strain rate sensitivity. Predicting
this phenomenon and the resulting poor formability, based
on microstructural events, is the primary objective of
this work.
More information.
Collaborative Research: Modeling Microstructure Evolution
during Hot Bulk Forming of Al-Mg-Si Alloys
Sponsor: National Science Foundation
Participants:
- Antoinette M. Maniatty,
Professor,
Department of Mechanical, Aerospace, and Nuclear Engineering.
E-mail: maniaa-at-rpi.edu
-
Wojciech Z. Misiolek,
Loewy Associate Professor and Director, Institute for Metal Forming,
Department of Materials Science and Engineering, Lehigh University.
E-mail: wzm2-at-lehigh.edu
-
David B. Williams,
Harold Chambers Senior Professor,
Department of Materials Science and Engineering, Lehigh University.
E-mail: dbw1-at-lehigh.edu
- Alex Bandar, Graduate Research Assistant,
Department of Materials Science and Engineering, Lehigh University.
E-mail: alb7-at-lehigh.edu
- Steven Claves, Graduate Research Assistant,
Department of Materials Science and Engineering, Lehigh University.
E-mail: src4-at-lehigh.edu
- Kelly Eaton, Graduate Research Assistant,
College of Education, Lehigh University.
E-mail: kpe2-at-lehigh.edu
- Jing Lu, Graduate Research Assistant,
Department of Mechanical, Aerospace, and Nuclear Engineering,
Rensselaer Polytechnic Institute.
E-mail: luj2-at-rpi.edu
Summary:
Al-Mg-Si alloys are among the most common materials used in
aerospace, construction, and automotive industries. The ability
to predict final microstructure, and therefore mechanical properties,
in a final aluminum part that results form a controlled deformation
process is extremely important for the US aluminum industry and
its customers.
The objective of this collaborative research project is to develop
a simulation tool, validated by experiments, capable of predicting
the evolution of key microstructural characteristics in Al-Mg-Si
alloys during hot, bulk forming. Specifically, the orientation
distribution of grains (texture), their size and shape, and the
precipitate size and distribution are of interest. It is
microstructural characteristics, such as these, that are responsible
for the macroscopic behavior of materials.
This work will guide process designers to design processes
that are lower in cost and produce aluminum products with
improved material characteristics.
Determining Stiffness in Human Tissue from Ultrasonic Measurements
Sponsors: National Science Foundation and National Institutes of Health.
Participants:
- Joyce R. McLaughlin,
Ford Foundation Professor,
Department of Mathematical Sciences. E-mail: mclauj-at-rpi.edu
- Antoinette M. Maniatty,
Professor,
Department of Mechanical, Aerospace, and Nuclear Engineering.
E-mail: maniaa-at-rpi.edu
- Lin Ji, Post-Doctoral Research Associate,
Department of Mathematical Sciences.
- Jeong Rock Yoon, Post-Doctoral Research Associate,
Department of Mathematical Sciences.
- Eunyoung Park, Graduate Research Assistant,
Department of Mechanical, Aerospace, and Nuclear Engineering.
- Daniel P. Renzi, Graduate Research Assistant,
Department of Mathematical Sciences.
Summary:
The objective of this research program is to explore methods to improve and extend
the information content and the spatial resolution of elastographic images. The
elastic properties of tissue are directly related to the underlying structure of the
tissue and are therefore strongly affected by pathological changes in the tissue. To
be precise, it is the elastic property of shear stiffness, i.e. the property that
characterizes resistance to shape change, that is most affected by pathelogical changes.
Therefore, the ability to image, with high resolution, the shear stiffness field, or
the related property of shear wave speed, would be an extremely valuable diagnostic
tool. The long-term goal of this work is to develop methods to achieve this in
real-time for an ultrasound-based system developed by collaborator, Prof. M. Fink
of the Laboratoire Ondes et Acoustique, E.S.P.C.I., Universite Paris VII.
To be specific, the problem to be solved is to determine the 3-D shear stiffness
field from ultrasound measurements of interior displacements over time as a pulse-induced
elastic wave travels through the body. In mathematics, this is referred to as an
inverse problem of parameter identification. These problems are known to be typically
ill-posed, meaning the solutions are unstable, and thus, very sensitive to noise
in the data, unless special, "intelligent" algorithms are used. In the problem of
interest, the primary source of instability is due to the need to differentiate the data
twice, if a direct solution method is used. The algorithms that are being explored in
this work, either eliminate the need to directly differentiate the displacement data
altogether, or reduce the highest derivative to one. Level set methods based on
arrival time mapping, geometric optic methods, and finite element based methods are
be investigated. Furthermore, the algorithms need to be fast, so fast algorithms
and parallel computational methods are being explored too. Another important aspect
of this work is to analyze the errors, due to the model, data, and method. Detailed
forward finite element models are being developed that include complex material
behavior, such as anisotropy and viscoelasticity, to generate simulated data to
isolate and investigate these effects. The forward finite element model will also
be used to determine sensitivities and identify rich data subsets.
Optimal Design of Bulk Forming Processes
Sponsor: National Science Foundation
Participants:
- Antoinette M. Maniatty,
Professor,
Department of Mechanical, Aerospace, and Nuclear Engineering.
E-mail: maniaa-at-rpi.edu
- Binoj Ramesh, Graduate Research Assistant,
Department of Mechanical, Aerospace, and Nuclear Engineering.
Summary:
The objective of this work is to develop a simulation tool, which would
determine the optimal process geometry, temperature, and speed for
a given forming process that will also satisfy design criteria
specified by a designer. These design criteria may include
objectives, for example produce a product with certain material
characteristics or minimize the production time, and they may
also include certain design constraints, such as geometric
constraints. The work involves developing an optimization algorithm
based on an efficient finite element formulation for modeling
large deformation, thermo-elasto-viscoplastic contact problems,
typical in metal forming.
X-Ray Microbeam Studies of Electromigration
Sponsor: National Science Foundation
Participants:
-
G. Slade Cargill III, Fairchild Professor, Department of Materials Science
and Engineering, Lehigh University.
E-mail: gsc3-at-lehigh.edu
- Antoinette M. Maniatty,
Professor,
Department of Mechanical, Aerospace, and Nuclear Engineering.
E-mail: maniaa-at-rpi.edu
- Laura Roos-Moyer, Graduate Research Assistant,
Department of Materials Science and Engineering, Lehigh University.
E-mail: ler2-at-lehigh.edu
- Chia-Ju Yang, Graduate Research Assistant,
Department of Mechanical, Aerospace, and Nuclear Engineering.
E-mail: yangc3-at-rpi.edu
Summary:
Both electric and stress fields in electronic interconnects drive
diffusional processes that can lead to the structural failure
of a device through void formation. The grain structure and
grain orientation distribution of an interconnect affect these
diffusional processes, and thus affect the device reliability.
Furthermore, the interconnect feature scale is on the same order
as the grain scale. Thus, in order to predict the structural
reliability of an interconnect, it is desireable to
understand and model these
diffusion processes in realistic, three-dimensional grain
structures.
In this research, x-ray microbeam diffraction and flourescence
and other experimental techniques, together with microstructure
dependent, grain scale models, and numerical simulations will
be used to study the basic underlying mechanisms associated
with electromigration in Cu-based conductor lines and thin films.
A three-dimensional finite element formulation
for modeling electromigration and stress driven diffusion is
under development. The model allows for three-dimensional
grain structures, grain anisotropy, and non-uniform current
density.
Solving Inverse Problems for Determining Unknown
Interface Conditions
Participants:
- Antoinette M. Maniatty,
Professor,
Department of Mechanical, Aerospace, and Nuclear Engineering.
E-mail: maniaa-at-rpi.edu
- Christopher J. Clutz, Graduate Research Assistant,
Department of Mechanical, Aerospace, and Nuclear Engineering.
E-mail: clutzc-at-rpi.edu
Summary:
Interface conditions, such as tractions and heat flux conditions
on the interface between contacting bodies, have a significant
impact on wear and surface quality. It is generally difficult
to directly measure these interface conditions, however, in many
cases, easier and more accurate measurements of temperatures and
strains or displacements can be made at regions outside of
the contact zone. Problems of interest involve determining
unknown traction and heat flux boundary conditions in the contact
zone of coupled thermomechanical contact problems using strain
(or displacement) and temperature measurements outside of the
contact zone. This is a type of inverse problem because the
boundary conditions (typically required for a unique solution
in mathematical physics) are unknown on part of the boundary
and over-specified on another part of the boundary (i.e. part
of what is typically the solution is known).