Author: Orlando E

Modeling and Control Additive Manufacturing Processes for Ceramics and Glass

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Abstract: Additive Manufacturing (AM), which has been referred to as the 4th revolution in manufacturing, is a truly disruptive class of manufacturing. In AM, location-specific mechanical properties can be tailored by grading materials and microstructure, complex geometries that cannot be manufactured with traditional processes can be fabricated, and cost-effective part repair and low volume manufacturing can be realized. However, AM processes have tremendous variability and are not well understood. This has led to significant research efforts into controlling these processes. This talk will discuss our research efforts in the control-oriented modeling and feedback control of two AM processes. The first process is a ceramic extrusion process known as Freeze-form Extrusion Fabrication (FEF) of ceramics, where an aqueous-based ceramic paste is extruded in a freezing environment. This process is ideal for the fabrication of ceramic parts with complex geometries and multiple materials. We will explore the major variations in this process, empirical modeling techniques to describe its dynamic behavior and construct control-oriented models, and methods to control the extrusion force. We will then transition to our work in the first principle, control-oriented modeling of the extrusion force and filament freezing time, and the understanding of the process that is elucidated from these models. The second AM process we will discuss is a new direct energy deposition process to additively manufacture glass. In the AM glass process, filament or fiber is fed into a molten pool of glass formed by a laser energy source. The process can be used to fabricate fully dense transparent free-form parts for gradient index optics, complex structures for embedded optics and waveguides, and freeform structures that open up the glass design space. We will discuss our work in understanding the process and discovering process parameter spaces suitable for fabrication. Two issues that limit the AM glass process are bubble formation and the challenge of placing the glass in a desired location. We will discuss our work in controlling these two issues and discuss future directions for this process.

Biographical Sketch: Dr. Robert G. Landers (landersr@mst.edu) is a Curators’ Distinguished Professor of Mechanical Engineering in the Department of Mechanical and Aerospace Engineering at the Missouri University of Science and Technology (formerly University of Missouri Rolla) and served as the department’s Associate Chair for Graduate Affairs for eight years. He received his Ph.D. degree in Mechanical Engineering from the University of Michigan in 1997. His research interests are in the areas of modeling, analysis, monitoring, and control of manufacturing processes (laser metal deposition, glass direct energy deposition, selective laser melting, freeze–form extrusion fabrication, wire saw machining, metal cutting, friction stir welding), estimation and control of lithium ion batteries and hydrogen fuel cells, and digital control applications. He has over 200 refereed technical publications, including 79 journal articles, an h index of 22 with 1734 citations (Scopus), and $6.4M in funding. He received the Society of Manufacturing Engineers’ Outstanding Young Manufacturing Engineer Award in 2004 and the ASME Journal of Manufacturing Science and Engineering Best Paper Award in 2014, is a Fellow of ASME, a senior member of IEEE and SME, and a member of ASEE. He is currently a program manager at the National Science Foundation, served as associate editor for the ASME Journal of Dynamic Systems, Measurement, and Control (2009–2012), ASME Journal of Manufacturing Science and Engineering (2010–2014), and the IEEE Transactions on Control System Technology (2006–2012), and is currently an associate editor for Mechatronics.

Reversible Solid Oxide Cells and Protonic Ceramic Fuel Cell Technologies as Flexible, Dispatchable Energy Resources

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Abstract: ​L​ow-cost, high efficiency, electrical energy storage (EES) is needed for the future electric grid which will include more variable energy resources, such as wind and solar. Movement towards predominately low-carbon energy systems requires renewable resources and could be accelerated by integration of high temperature electrochemical technologies. Currently, substantial penetration of wind and solar resources into the electric power grid is challenged by their intermittency and the timing of generation which can place huge ramping requirements on central utility plants, which are also limited in dynamic response capability. This talk will discuss employing novel EES systems derived from reversible fuel cell technology and advances in protonic ceramics as dispatchable energy resources. Reversible solid oxide cells (ReSOCs) are capable of providing high efficiency and cost-effective electrical energy storage. These systems operate sequentially between fuel-producing electrolysis and power-producing fuel-cell modes with storage of reactants and products (CO​2/​ CH​4g​ ases) in tanks for smaller-scale (kW) applications and between grid and natural gas infrastructures for larger scale (MW) systems. In this talk, the use of ReSOC technology for both grid-scale energy storage and as a Power-to-Gas platform that can address issues with high renewables penetration is presented. In stand-alone systems, strategies for effective thermal management and balance-of-plant systems integration in both operating modes are critical to achieving high roundtrip efficiencies. Design challenges and techno-economic analyses which suggest levelized cost of storage that ranges between 15 – 30 $/MWh are highlighted. A brief overview of recent progress in the performance of intermediate temperature (500-600°C) protonic ceramic fuel cells (PCFCs) which have demonstrated both fuel flexibility and increasing power density that approach commercial application requirements will also be given. The PCFCs investigated in this work are based on a BaZr​0.8Y​ ​0.2O​ ​3-δ(​ BZY20) thin electrolyte supported by BZY20/Ni porous anodes, and a triple conducting cathode material comprised of BaCo​0.4F​ e​0.4Z​ r​0.1Y​ ​0.1O​ ​3-δ(​ BCFZY0.1). Performance characteristics, modeling challenges, and techno-economic outlook of mixed-charge conducting PCFCs are presented.

Biographical Sketch: ​Dr. Robert Braun is Associate Professor of Mechanical Engineering at the Colorado School of Mines. He received a Ph.D. from the University of Wisconsin–Madison in 2002. From 2002-2007, Dr. Braun was at United Technologies Fuel Cell and Research Center divisions where he last served as project leader for UTC’s mobile solid oxide fuel cell (SOFC) power system development program. Dr. Braun has multidisciplinary background in mechanical and chemical engineering and his research focuses on energy systems modeling, analysis, techno-economic optimization, and numerical simulation of transport phenomena occurring within fuel cell and alternative energy systems. His industry experience encompasses development of low-NOx burners, CO​2-​ based refrigeration, and fuel cell technologies (including PEM, PAFC, MCFC, SOFC, and PCFC). Dr. Braun’s current research activities focus on high efficiency hybrid fuel cell/engine systems, renewable energy pathways to synthetic fuel production, grid-scale energy storage, novel protonic ceramics, supercritical CO​2 p​ ower cycles, and dispatch optimization of concentrating solar power plants. He is a Link Energy Foundation Fellow, a member of ASME, ECS, and ASHRAE, and holds 6 U.S. patents.

Jiong Tang to serve as the General Chair for ASME IDETC & CIE 2019

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Prof. Jiong Tang will serve as the general conference chair for the American Society of Mechanical Engineers’ international annual design conference in Anaheim CA. The 2019 ASME International Design Engineering Technical Conference (IDETC) and Computers and Information in Engineering Conference (CIE) will take place between August August 18 – 21, 2019  at the Anaheim Convention Center.

Physical biology at the semiconductor-enabled biointerfaces

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Abstract: ​Recent studies have demonstrated that in addition to biochemical and genetic interactions, cellular systems also respond to biophysical cues, such as electrical, thermal, and mechanical signals. However, we only have limited tools that can introduce localized physical stimuli and/or sense cellular responses with high spatiotemporal resolution. Inorganic semiconductors display a spectrum of physical properties and offer the possibility of numerous device applications. My group integrates material science with biophysics to study several semiconductor-based biointerfaces. In this talk, I will first pinpoint domains where semiconductor properties can be leveraged for biointerface studies, providing a sample of numbers in semiconductor-based biointerfaces. Next, I will present a few recent studies from our lab and highlight key biophysical mechanisms underlying the non-genetic optical modulation interfaces. In particular, I will present a biology-guided two-step design principle for establishing tight intra-, inter-, and extracellular silicon-based interfaces in which silicon and the biological targets have matched mechanical properties and efficient signal transduction. Finally, I will discuss new materials and biological targets that could catalyze future advances.

Biographical Sketch: ​Bozhi Tian received his Ph.D. degree in physical chemistry from Harvard University in 2010. He is now an associate professor at the University of Chicago, working on semiconductor-enabled fundamental studies of subcellular biophysics and soft matter dynamics. Dr. Tian’s accolades from his independent career include the Inaugural ETH Materials Research Prize for Young Investigators (2017), Presidential Early Career Awards for Scientists and Engineers (2016), and TR35 honoree (2012).

Recent Progress in Black-Box Function Optimization for Industry Problems

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Abstract: One of the most common and important problems in the engineering industry is, arguably, to optimize a black-box expensive-to-evaluate function given a strict budget. The function can represent a real-world experiment or a costly simulation code. Specifically, given a set of potential power plant layouts, how do we find the best layout defined against a set of Quantities of Interest? Given a steam turbine, how do we configure its geometry to achieve the best efficiency? How can we optimize the life of a machine by knowing its design variables and how they connect to damage? Given a set of Computational Fluid Dynamics simulations, can we optimize a blade structure for cooling? The problem of course extends to a broad range of other industries and academia as well. As a different example, borrowed from materials discovery, consider a set of binary alloy lattice points: Which atoms should be placed on said points to discover the ground states? Surely, for all these cases, the faster we achieve high-quality optima (ideally global and robust) in terms of resources, the lower the overall cost.

Towards answering these questions, at General Electric Research our team has developed and maintain an industry-strength Efficient Global Optimization scheme called “Intelligent Design and Analysis of Computer Experiments” (IDACE) which builds on a time-tested Gaussian Process meta-model called Bayesian Hybrid Modeling (BHM) originally built from Kennedy O’Hagan’s work.

Having introduced the BHM/IDACE framework, we present in detail a set of successful BHM/IDACE industry case studies and compare to other optimization approaches such as Genetic Algorithms. Finally, we go on to discuss a range of recent modifications and enhancements to these tools all driven from real-world customer needs.

Short Bio: Jesper Kristensen works as a Lead Engineer in the Probabilistics and Optimization team at General Electric’s (GE) Research Center in upstate New York. The team is managed by Dr. Liping Wang. He joined the team in the fall of 2015 as a research engineer. Among other projects, he is currently in charge of a $1MM project leading six engineers to ensure GE stays ahead in Probabilistic capabilities including, but not limited to, meta-modeling, optimization, uncertainty quantification, and uncertainty propagation. He is also the project leader on multiple damage modeling efforts to create Digital Twins of steam turbines.

 

Jesper is a graduate of the Technical University of Denmark (DTU) and holds a Ph.D. from Cornell University in Applied and Engineering Physics advised by Prof. Nicholas Zabaras. His work has generally focused on surrogate modeling and on advanced optimization methods such as adaptive sequential Monte Carlo and Bayesian Global Optimization for improving materials discovery and test cost reduction.

The Challenge of Modeling and Simulation for Molten Salt Nuclear Reactors

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Abstract: ​The rapidly expanding interest in molten salt reactors (MSRs), particularly as small modular reactors, is resulting in the generation of multiple design concepts with efforts at a variety of early developmental stages. Various companies and organizations in a number of countries are looking at such systems to be safe, economical, and rapidly deployable power systems. For efficient design, operation, and regulation of MSRs it will be necessary to have the ability to simulate reactor behavior across the spectrum from neutronics and fluid dynamics to corrosion and salt phase behavior. MSRs have not been considered since the original prototype, the Molten Salt Reactor Experiment, that ran successfully from 1965-1969 at Oak Ridge National Laboratory, and thus there is little legacy of useful information. Aspects of potential modeling and simulation of future molten salt reactors will be discussed with respect to the unique challenges they present. Among the current needs are extensive thermophysical and thermochemical properties describing salts and other reactor materials. In particular, the ability to compute chemical and phase equilibria (e.g., potential solid phase precipitation) throughout the molten salt loop(s). Activities and opportunities in these areas will be discussed as contributing to development of a knowledge base for molten salt reactor technology.

Biographical Sketch: ​Ted Besmann is Professor and SmartState Chair for Transformational Nuclear Technologies, directing the General Atomics Center at the University of South Carolina. Dr. Besmann received his B.E. in chemical engineering from New York University, M.S. in nuclear engineering from Iowa State University, and Ph.D. in nuclear engineering from the Pennsylvania State University. In 1975 he joined ORNL and subsequently became a Group Leader and Distinguished Member of the Research Staff. Besmann’s nearly 40 years at Oak Ridge National Laboratory included a joint appointment in the Nuclear Engineering Department at the University of Tennessee. Besmann has over 160 refereed publications, and is a Fellow of both the American Ceramic Society and the American Nuclear Society. He is chair of the Organization for Economic Cooperation and Development-Nuclear Energy Agency (OECD-NEA) Working Party on Multi-Scale Modeling of Nuclear Fuels and Structural Materials and is vice-chair of their Thermodynamics of Advanced Fuels-International Database program. Dr. Besmann is also Co-Director of the DOE Energy Frontier Research Center led by USC, the Center for Hierarchical Waste Form Materials.

Layer-to-Layer Control in Laser Metal Direct Energy Deposition Additive Manufacturing

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Abstract: ​Additive manufacturing (AM), or 3D printing, is beginning to deliver on its long-promised potential to transform industrial production.  Already, tooling and molds are making regular use of AM’s rapid CAD-to-part flexibility to deliver in days what previously took months.  In addition, AM facilitates much greater geometric complexity, which increases the value proposition for AM fabricated parts that are serving in increasingly critical roles.  However, the rate of industrial insertion remains slow due to stubborn problems in process variability arising from the spatial and dynamic complexity of AM, amplifying challenges in qualification.  In-process measurement and analysis, and the utilization of that data in closed-loop feedback control, are widely regarded as the remedy.   This talk will explore one such instance in a blown-powder, direct energy deposition (sometimes referred to as LENS) process.  Here, a laser scanner is used to detect and correct geometric anomalies.  The talk will consider how in-layer and layer-to-layer dynamics may couple to create multi-dimensional dynamic behavior not typically considered, and how novel control methods may stabilize these processes.

Biographical Sketch: Dr. Douglas A. Bristow is currently an Associate Professor in the Department of Mechanical and Aerospace Engineering at the Missouri University of Science and Technology (Missouri S&T).  He received his B.S. in Mechanical Engineering from Missouri S&T in 2001.  He received his M.S. and Ph.D., also in Mechanical Engineering, from the University of Illinois at Urbana-Champaign in 2003 and 2007, respectively.  Dr. Bristow is the Director of the Center for Aerospace Manufacturing Technologies, an industry consortium that currently includes eleven member companies.  He has more than 80 peer-reviewed publications and his research interests include precision motion control, repetitive and iterative process control, additive manufacturing process control, atomic force microscopy, and volumetric error compensation in machine tools and robotics.  Dr. Bristow’s research is currently funded by the National Science Foundation, the Department of Energy, the Digital Manufacturing and Design Innovation Institute, and multiple companies.  He is an Associate Editor at the ASME Journal of Dynamic Systems, Measurement and Control.