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Lifetime & Degradation Science Workshop

Wednesday, November 14, 2012, 8am to 1pm
Case Western Reserve University
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Join faculty from Case Western Reserve University, University of Maryland, and Cleveland State University to learn about the latest advancements in Lifetime & Degradation Science (L&DS).  L&DS is a new engineering design paradigm that accelerates development and testing, reduces degradation, renormalizes standards, and builds technologies fitted to their real world environments. “Big Data” and data mining technology, combined with fundamental scientific expertise, make this possible, including the ability to predict future performance and design for its sustainability. The result will be systems that perform reliably and safely for years beyond what is possible today – arriving at new solutions faster and with a higher value.


AGENDA


7:30 Registration and Continental Breakfast


8:00 Welcome and Introduction to Lifetime & Degradation Science

Dr. Roger French, CWRU


Thrust I - Engineering Epidemiology

8:30 "Tracking the Natural History of Modular Metal-on-Metal Interfaces in Total Hip Replacements"

Dr. Clare Rimnac, CWRU

Abstract:  Damage at modular interfaces in retrieved total hip replacement systems (THRs), particularly metal-on-metal (MOM) systems, can be analyzed to investigate if increased modularity is associated with increased wear debris.  Related design factors such as bearing head size and component offset and dissimilar metal alloy pairings are also of interest.  The hypothesis that fretting and corrosion damage occurs at the variety of modular interfaces in contemporary MOM THRs is currently under investigation.  Preliminary findings of retrieved hip replacements will be presented.


8:45 "Improving the Outcomes of K-12 STEM Education"

Dr. Joanne Goodell, Cleveland State University

Abstract:  There is no doubt that the USA’s competitiveness in global STEM enterprises has declined over the past decade. Numerous state and federal reports have been commissioned to address this growing problem. Many reports point to the lack of a strong K-12 pipeline to feed the higher education programs that prepare STEM professionals, which has led to an explosion of funding for initiatives to address the problem. There is research evidence that the teacher has the biggest influence on the variance in student achievement apart from what the student brings to the classroom, and this is where the majority of my funded work has been focused. In this session, I will describe the programs I have implemented to improve teacher content knowledge and pedagogical practices with the intention of impacting their students’ interest, achievement and persistence in STEM subjects.


9:00 "Engineering Epidemiology Applied to the Wind Industry"

Dr. Dave Matthiessen, CWRU

Abstract: The United States of America is blessed with ample wind resources and the growth in wind farm installations has seen double digit percent increases.  An example of a commercial wind farm is the 500 MW Meadow Lake Wind Farm near Brookston and Chalmers, Indiana which could eventually reach a combined nameplate capacity of 1000 MW with over 600 wind turbines. 

Already installed, Meadow Lake I consists of 121 Vestas V82 1.65 MW wind turbines, for a total nameplate capacity of 199.65 MW and became operational in October, 2009. Meadow Lake II Wind Farm has an installed capacity of 99 MW consists of 66 Acciona AWs 1.5 MW turbines and achieved commercial operation in June 2010. Meadow Lake III Wind Farm has an installed capacity of 103.5 MW consists of 69 GE sle 1.5 MW turbines, achieved commercial operation in October 2010. Meadow Lake IV Wind Farm has an installed capacity of 98.7 MW consists of 47 Suzlon S88 2.1 MW turbines and achieved commercial operation in October 2010. Future phases will have capacities between about 100 MW and 200 MW each.

For the existing 303 wind turbines at this ONE wind farm, EACH measured and recorded sensor will produce about 320 million data records over the course of its expected 20 year service life. For EACH wind turbine, assuming only a hundred sensor measurements, control parameters and calculated values results in over 32 billion data records. Again, for just this one wind farm. given that there are hundreds of wind farms in the United States, trillions of data records are being recorded.

Such a large data set presents a unique opportunity for the wind industry to borrow from the field of medicine the techniques of epidemiology.


9:15 Break/Discussion


Thrust II - Engineering Research Informatics

9:25 “From PhysioMIMI to EnergyMIMI and Beyond: Translating a Medical Informatics Data Management Tool to Address Big Data Challenges in Lifetime & Degradation Science” 

Dr. GQ Zhang, CWRU

Abstract: We present an ontology-driven data integration environment called PhysioMIMI (Multi-modality, Multi-resource Information Integration Environment for Physiological and Clinical Research) and illustrate a variety of application scenarios of this environment for  Engineering Epidemiology.  PhysioMIMI uses a federated data management approach with a domain ontology as the semantic infrastructure driving data integration, query interface design, and data harmonization across studies. The front-end of PhysioMIMI is a reusable and user-friendly query interface called VISAGE (Visual Aggregator and Explorer). The backend of PhysioMIMI uses an ontology-driven Map and Connect approach, in contrast to the traditional ETL (Extract, Transform and Load) process used in a data warehouse approach. The Map and Connect paradigm embodies flexibility for accommodating data quality improvements in source data by pushing data curation tasks upstream in a source-specific, decentralized way, so that updates can be managed distributively throughout the data reuse life-cycle.

We will give a live demo and offer a roadmap for a more effective, community-level paradigm for data sharing data among a large number of stakeholders.


9:40 "Infrastructure Materials: Real World and Accelerated Degradation"

Dr. Xiong "Bill" Yu, CWRU

Abstract: Due to the huge amount of consumption, production of infrastructure materials accounts for a significant portion of energy consumption and greenhouse gas emission. This talk introduces methodologies and emerging trends in understanding the performance and degradation of infrastructure materials, including both full-scale and reduced-scale accelerated testing. Such efforts are inductive to the application of engineering measures to improve their durability and reduce life-cycle energy and carbon footprint.


9:55 “Engineering of InGaN Quantum Wells for High Efficiency and Reliable LEDs”

Dr. Hongping Zhao, CWRU

Abstract: Current InGaN QWs LEDs suffer from "efficiency droop" - the efficiency of LEDs quenches as the injection level increases. Two approaches are used to address this issue: 1) engineering of InGaN QWs to achieve large overlap QWs to enhance the radiative efficiency; and 2) novel QW-barrier designs to enhance the current injection efficiency. Both approaches will lead to significant enhancement of internal quantum efficiency of LEDs, which paves a way to achieve high efficiency and reliable LEDs.  


10:10 “Fundamental Studies of Dendritic Growth in Metal Electrodeposition - Applications to Transportation and Large-Scale Energy Storage Systems”

Dr. Rohan Akolkar, CWRU

Abstract: Electrodeposition is central to energy storage and conversion devices. Charging of anodes in high energy density lithium-metal batteries occurs via lithium electrodeposition. In large-scale energy storage systems, zinc and iron electrodeposition underlies the electrochemistry during charging of zinc-bromine and all-iron flow batteries. In these electrodeposition systems, dendrite formation is one of the primary root causes of battery degradation. Fundamental studies of the electrode-electrolyte interface and the role of additives in stabilizing this interface to prevent dendritic growth will be outlined.


10:25 Break/Discussion


Thrust III - LAST Prognostics

10:35 "Prognostics and Systems Health Management for Industrial Application"

Dr. Michael Pecht, University of Maryland

Abstract: Prognostics is a process of assessing the extent of deviation or degradation of a product from its expected normal operating conditions, and then, based on continuous monitoring, predicting the future reliability of the product. If one can monitor key control signals and loads, this data can be used in conjunction with precursor reasoning algorithms and stress-and-damage models to enable prognostics. By being able to determine when a product will fail, procedures can be developed to provide advanced warning of failures, reduce life cycle costs, and improve the design, qualification of fielded and future systems. This talk will discuss the concept of PHM and provide various cases where the methods have been successfully applied by industry.


10:50 “Statistics for Lifetime and Degradation Science and Some Examples”

Dr. Jiayang Sun, CWRU

Abstract: Sound statistical design and analysis are important for scientific research and discoveries that rely on data. Development of modern statistical techniques is necessary to overcome the challenges from the data that may come with both measurement errors and selection biases from multiple, heterogeneous sources. In this presentation, a statistical paradigm for the L&DS, statistical roles in the 4 thrust areas, and some quick examples that illustrate the importance of correct modeling, sound statistical analysis and interpretation, using R, will be presented.


11:05 “Rank Order of Degradation and Failure Modes of Dental Crowns and Potential Solutions"

Dr. Russell Wang, CWRU

Abstract: The degradation of dental ceramics generally occurs because of mechanical forces or chemical attack. Failure rates of single crowns and multiple dental bridges are to be improved by new materials design and CAD/CAM applications in dental field. Future research of new dental products and technologies will be beneficial by adopting the LAST concept.


11:20 Break/Discussion


Thrust IV - New Technology Insertion

11:30 “Integrating Electric Power Generation in the Distribution System

Dr. Mingguo Hong, CWRU

Abstract: The electric distribution system possesses great potentials with unrealized economic, reliability and environmental benefits. Distributed Generation (DG) is an effective approach to unleash the potentials. DG refers to a suite of power generation technologies that are implemented at or close to the electricity consumption sites. DG defers the need for building expensive transmission lines, and is an suitable platform for implementing many renewable technologies such as wind and photovoltaic at the smaller capacity scales (from a few kilowatts to a few megawatts). This talk discusses the needs to upgrade the electric distribution system and its operation, in order to accommodate a wide-scale implementation of the DG technologies. The on-going research effort at Case fits under the general framework of the Smart Grid, a strategic technology initiative proposed by the Department of Energy.  


11:45 “Optimizing the Performance of UHMWPE Orthopaedic Joint Replacement Components”

Dr. Clare Rimnac, CWRU

Abstract:  The performance of ultra high molecular weight polyethylene (UHMWPE) joint replacement components depends on the material's resistance to oxidative degradation, wear, and fracture.  These key features must also be considered in the context of implant design.  Lessons learned and current approaches to new technology in UHMWPE material development and design evolution in this area will be presented.  


12:00 “LED Light Extraction Efficiency Enhancement with GaN Micro-domes”

Dr. Honping Zhao, CWRU

Abstract: The enhancement of light extraction efficiency for thin-film flip-chip (TFFC) InGaN quantum wells (QWs) light-emitting diodes (LEDs) with GaN micro-domes on n-GaN layer was studied. The light extraction efficiency of TFFC InGaN QWs LEDs with GaN micro-domes were calculated and compared to that of the conventional TFFC InGaN QWs LEDs with flat surface. The three dimensional finite difference time domain (3D-FDTD) method was used to calculate the light extraction efficiency for the InGaN QWs LEDs emitting at 460nm and 550 nm, respectively. The effects of the GaN micro-dome feature size and the p-GaN layer thickness on the light extraction efficiency were studied systematically.


12:15 “Opportunities in STEM Education from outcome based insights”

Dr. Joanne Goodell, Cleveland State University

Abstract: Education across the world is undergoing a sea change from an input-focused model to an outcomes focused model, although the USA is certainly not as far down this road as some countries. Examples of outcome measures that are becoming increasingly important in higher education include freshman retention rates and graduation rates. Many accrediting bodies such as ABET are also increasingly focused less on educational inputs such as courses and credit hours and more on the knowledge and skills of graduates as they prepare to enter the workforce. Focusing on outcomes not inputs could be a catalyst for program, curriculum, teaching and assessment changes in higher education institutions, but most systems and institutions still base reward structures on inputs, and measure achievement with grades which tell the world nothing about what a student knows or is able to do. This has the effect of locking the system into a set way of doing things, and does not encourage or reward innovation. With an outcomes focus, those who can figure out how to reach the desired outcome in a more efficient, innovative or appealing way may well be the educational winners of the 21st century.

Professional programs such as those in engineering purport to produce graduates who enter the workforce ready to function independently, however the reality is that many new graduate engineers are not ready, and many companies spend a lot of time and money on induction programs to make up for gaps in knowledge, skills or both. Targeting outcomes to those things employers value most is possible only if the system is well articulated. To do this, a sample of some of things we need to know include

  • What outcomes are important
  • How to measure those outcomes
  • How to teach in an outcomes-based environment
  • How to link program outcomes to employability
  • How to measure employability of graduates
  • How to assess the success of graduates as they enter the workforce

In this session, I will lead a discussion on what types of data exist and how to access and make use of these data to inform the engineering education system.


12:30 Lunch


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Wednesday, November 14, 2012
8:00am to 1:00pm EDT

Case Western Reserve University
10900 Euclid Avenue, Nord Building, Room 310
Cleveland, OH, 44106

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