PITA Fiscal Year 2017 Projects

A Holistic Framework for Prioritizing Investments in Bridge Lifting
PI: Daniel Armanios, Engineering and Public Policy
Co-PI(s): Burcu Akinci, Civil and Environmental Engineering and Sean Qian, Civil and Environmental Engineering

America’s bridge infrastructure systems face two concurrent largescale challenges: (1) aging and continuously deteriorating infrastructure; and (2) limited funding availability to update these infrastructure systems due to budgetary constraints. Moreover, many of these bridges reflect old design standards and often did not anticipate the drastic technological advancements in our transportation system. In particular, bridge clearances for many of our oldest bridges do not adequately accommodate large commercial and mass transportation vehicles. As such, these bridges present both technical challenges as well as social costs of keeping the status quo due to connectivity and rerouting issues within the communities around them. Our aim is to develop a holistic decision making framework to help policymakers and bridge engineers around which bridges to lift in ways that are more technically reliable and economic feasible, while also mitigating the shortterm and longterm socials costs involved with such bridges.

We propose a threepronged approach that incorporates three factors: 1) technical and economic costs associated with different design and construction alternatives; 2) shortterm inconvenience costs due to rerouting and congestion due to the bridge lifting process; 3) longterm community opportunity costs due to reduced mobility and connectivity as well as heightened congestion the longer bridge remains not lifted. We then incorporate these three costs into a decisionmaking model and evaluate this model with existing approaches to ascertain the accuracy, efficiency, and reliability of our novel framework. Our strong collaboration with PennDOT will enable us to have access to an unprecedented amount of data which will help us characterize different aspects of this problem and assess the applicability of our framework to the practices in all of its twelve districts. Close interactions with PennDOT will allow us keep our work grounded and at the same time transfer the knowledge that will be generated seamlessly to the current practices.

Optimization of Passenger Flow at Pittsburgh International Airport
PI: Alexander Jacquillat, Heinz College
Co-PI(s): Ari Lightman, Heinz College and BeiBei Li, Heinz College

The Pittsburgh International Airport (PIT) is the second busiest airport in Pennsylvania and serves over 500,000 travelers each month. Over recent years, PIT has started to deploy information technologies to better monitor and serve its customers. The objective of this project is to develop a holistic approach to the acquisition and analysis of passenger flow data, and their integration into decision­-making tools for improved operations and customer experience. Specifically, it will focus on one specific passenger segment: passengers needing special assistance when travelling (e.g., passenger with physical disabilities). This builds upon work done in a Capstone project class in the spring of 2016. It will follow a three­-step process around (i) the deployment of technologies for systematic acquisition of spatial-­temporal data, (ii) the optimization of resource allocation to best serve passengers requiring special assistance, and (iii) field testing to calibrate, validate and assess the decision-­making support tools that will be developed. It will result in a systematic approach to allocate available resources to passengers. The ultimate impact will be optimized routes, better asset management, and digital processes to move these passengers efficiently from origin to destination.

Matching rider demand and sharing service in transportation infrastructure networks for the Pittsburgh Metropolitan Area
PI: Sean Qian, Civil and Environmental Engineering
Co-PI(s): Alexander Jacquillat, Heinz College

As of 2013, there were over 256 million private vehicles owned and operated in the United States. Estimates of the average cost to own, maintain, insure, and park a private vehicle ranges from $460 to $913 per month, an enormous economic and environmental burden. Those vehicles altogether generate on average 37 hours’ congestion per vehicle in the year of 2013. Sharing services, such as ridesharing and on­-demand taxi systems (e.g., Uber and Lyft) offer the potential to meet travel needs that are substitutional to self-­driving, which leads to significant savings of energy use and flow reduction. In turn, ridesharing can mitigate the costs, congestion and environmental impact of automobile transportation. More importantly, as they grow to represent a significant fraction of network flows, ridesharing systems can influence traffic flows in urban areas in order to improve infrastructure performance. In spite of great potential, sharing services are not provided optimally. Travelers (i.e., service demand) oftentimes have difficulty finding vehicles, or do so at high costs (e.g., Uber’s surge price). On the other hand, taxi/uber/lyft drivers (i.e., service supply) also face challenges to remain profitable, and can lose significant revenue opportunities through incomplete knowledge of traveler demand. This PITA research will address the mismatching among sharing service providers and consumers by proactively predicting traveler demand and sharing demand information to service providers, resulting in better service for travelers, better revenue opportunities for drivers, and better transportation infrastructure performance. In particular, partnering with Gridwise, a Pittsburgh-­based start­up company, the research team aim to develop predictive models from numerous input datasets that are likely to correlate with rideshare demand. The models will be trained and validated using data obtained from CMU Mobility Data Analytics Center (MAC) and the Gridwise platform, as well as other simulated “proxies” of this demand such as rideshare surge prices.

High-Speed Micro-Aerial Transportation through Cluttered Environments
PI: Koushil Sreenath, Mechanical Engineering

There is a pressing need for safe and reliable aerial load transportation. In dense urban places, there exists a rapidly-increasing energy and time costs of transportation packages through jam­packed road networks. Aerial load transportation using micro aerial vehicles (MAVs) provide an effective and alternative option. However, dense urban environments are complex and cluttered. While birds are incredibly maneuverable and are capable of flying at high-speed through extremely complex and cluttered environments, MAVs are not. The overarching goal of this project is to realize high-­speed aerial transportation through complex, cluttered and dynamic environments. In particular, by building on our prior work, we propose to use theoretical geometric controllers with formal notions of strict safety to fly through cluttered environments.

Effects of Climate Change on Life-Cycle Safety, Sustainability and Resilience of Steel Bridges
Lead University: Lehigh University
PI: Dan M. Frangopol

Within the last decade, several attempts have been made to understand the effects of climate change on infrastructure systems. For instance, the Federal Highway Administration (FHWA) is supporting a multiphase research effort to understand the problems arising from climate change in the gulf coast area. Attempts have been made to quantify possible changes in temperature, precipitation, sea level, and increasing severity and frequency of storms. Although these studies can estimate possible changes associated with climate change, the effects of climate change on life-cycle safety, sustainability and resilience of transportation systems, including bridges, are not addressed. Accordingly, in this study, an integral approach to investigate these effects on life-cycle, safety, sustainability and resilience of steel bridges with and without corrosion resistant steel will be constructed to assist in decision making and management of these bridges under climate change conditions. Outcomes of this project include (a) integrate the effects of climate change into life-cycle management activities of steel bridges including design, maintenance and repair, (b) analyze the effects of climate change on life-cycle safety, sustainability and resilience of steel bridges with and without corrosion resistant steel, and (c) quantify the life-cycle benefits due to climate change effects in terms of life-cycle cost, safety, sustainability, resilience of steel bridges made of corrosion resistant steel. Outcomes from this project are relevant to the Nation’s steel bridge infrastructure by considering the effects of climate change, and in particular should provide economic and social benefits to Pennsylvania where steel bridges represent the majority of the total number of highway bridges. Companies such as ArcelorMittal will benefit from this project by using a novel model that includes the effects of climate change on life-cycle safety, sustainability and resilience of bridges made of maintenance-free steel.

Design and Prototyping of Locking Temporary Bridge Support Structure
Lead University: Lehigh University
PI: Joachim Grenestedt

This project is to expand the capabilities of the Temporary Bridge Support Structure by increasing the lifting capacity of the system along with the addition of a locking mechanism that allows the system to be set at an arbitrary height while still maintaining the full load capacity. With these expanded capabilities, the need for separate lifting jacks and shims would be eliminated during lifting operations; reducing support structure design and setup time while also increasing ease of implementation. The locking mechanism could also add an additional layer of safety to the system by providing the ability to carry the load in the case of a failure in the hydraulic system. Finally with the sensors being used for the locking mechanism, active load estimation may be done and warn if the structure is loaded beyond the rated load, presumably further increasing worker and structural safety. A scale prototype will be developed to test and verify the design and operation of the system and to identify any improvements or changes necessary before a full-scale system is built.


Enhancing Capabilities of a Multiple Sensors Internet of Things Platform
PI: Asim Smailagic, Engineering Research Accelerator
Co-PI(s): Dan Siewiorek, Human-Computer Interaction Institute

Any successful Internet of Things deployment means significant stream of sensor data. Although there are infrastructural challenges in storing, managing, learning, and securing such data, the true challenge is in making such data actionable and useful to everyday users. For example, it turns out that locating a vacant conference room on campus and finding other shared resources is the most useful application on campus and that is the topic addressed in this proposal. We adopt a top-­down, user centered approach in our infrastructure design, with a strong emphasis on the user experience.

Development of a Snake-like Robot with Construction, Inspection, Aerospace, and Disaster Recovery Applications.
Lead University: Lehigh University
PI: Brandon Krick

Performing electrical work inside the closed walls of a building is a destructive and difficult task requiring numerous holes to be cut then patched. As the facility infrastructure in the United States ages there is a continual need to upgrade safety, electrical, and telecommunication systems to increase their energy efficiency and capabilities. Impossible Incorporated LLC, a South Bethlehem, PA Keystone Innovation Zone company, has developed a patent pending 1 inch diameter snake-like robot which is able to run wires without the mess. The robot will be inserted through an outlet-sized hole then teleoperated inside the wall to the destination drilling holes in studs and joists along the way. At the far end wires are attached and then the robot rewinds through the wall while pulling them behind it. Other applications for the technology include locating trapped victims following natural disasters, inspection of critical infrastructure and hazardous areas, and as the next generation of robot arms for space exploration. The goal of this project is to use the expertise of Lehigh University’s Tribology Laboratory to address two critical tribological concerns. A casing will be developed to protect the flexible drive shaft within the robot using polymer composites that combine low wear with low friction properties. Small scale, high toque, gear trains are used within the robot to actuate the links. Specialty processes like Diamond-like carbon (DLC) need to be tested for their wear resistance and ability to keep the gears turning for millions of cycles. Through this industry/university partnership formed by the PITA program students will be able to learn the technical entrepreneurship process while using their research to solve industry problems. The results of this project will allow Impossible Incorporated LLC to commercially launch the robot and revolutionize how upgrades in existing structures are performed.

Polymer Melt Delivery Systems Incorporating Proactive Rheology Control for High Precision Injection Molding
Lead University: Lehigh University
PI: John P. Coulter
Co-PIs: Israd H. Jaafar

A Lehigh University – TE Connectivity collaborative effort is proposed to develop innovative polymer melt delivery technology that will enable successful and cost-effective manufacture of high precision thin-walled connection products using liquid crystal polymers (LCPs) and other difficult to process materials. Such products are of critical importance to the transportation, telecommunication, and information technology industries. The work will involve the synergistic partnership of injection molding expertise at Lehigh University with industrial practical experience at TE Connectivity, a leading global manufacturer of injection molded connector products. The Pennsylvania based manufacturing company constantly seeks innovative and cutting-edge technology to meet ever-growing demands and expand industry applications. The specific objective of this 18-month project will be to complete the development and validation of technology that arose from a successful previous collaborative project partially supported by the recent RAMP program. The work to date has led to the development of an innovative manufacturing concept to overcome the primary barrier to successful hot-runner based injection molding with complex rheology materials. The concept has been partially validated analytically and a prototype initial molding system based on it has been designed and fabricated. The proposed project will propel the technology toward commercial utilization by enabling a comprehensive experimental exploration/validation of the concept’s capability along with further analytical support for the innovation. Much of the work will be conducted at Lehigh University with important field testing at a TE Connectivity facility also included. The successful completion of the proposed work should yield a validated commercial ready innovation that will significantly strengthen TE Connectivity’s competitive position in the marketplace. The work will also provide the students involved with a high value learning experience that can only be obtained through active participation in collaborative industry-university projects such as this.

Visualizing Trends in Physiological Measurements from Personal Mobile Devices
PI: Asim Smailagic
Co-PI(s): Dan Siewiorek

Application scraps data from mobile sensors and related websites including range and frequency of sensor readings. Doctors set thresholds and get automatically notified when those thresholds are exceeded.

We will develop visualization software with graphical summary and capabilities for preserving trends. Visualization schemes will include innovative dashboard for visualizing external sensor data.

Previous studies have focused on the individual parameters separately and have shown modest improvements in parameters such as hospitalization, but this study by including additional data in a collective format will allow for improved outcomes.

Continuous patient monitoring will yield additional benefits as it will allow to detect important signals and changes in time that would otherwise go undetected.


Development of binder jet 3D printing of cement-based components for structural applications

Lead University: Lehigh University
PI: Paolo Bocchini, Clay Naito
Co-PIs: John Fox

The research will investigate cement based concrete mixes for application in 3D printing and will be utilized for innovative solutions in structural engineering. Advances have been made in the use of fused deposition modeling technologies for concrete construction in which wet concrete is deposited in layers that are several inches thick for the fabrication of walls and structural components. While these systems are effective for large components where surface quality and accuracy are not critical, they are not ideal when refined topologies and lightweight components are desired. The research will utilize binder jet methods to deposit water-based liquid binding agents onto a dry cementitious powder aggregate material. This approach facilitates fabrication of components that are fully supported during construction by the unused material that surrounds it and allows for complex shapes with reentrant corners, negative draft, and hollow forms not currently possible with form based construction. The research will focus on the development of effective dry mix designs utilizing cementitious materials produced by Buzzi Unicem. The team involves experts in binder jet printing, structural engineering, and cement chemistry at Lehigh.


Integrating Robotic Exploration and Adaptive Modeling of Infrastructure Networks

PI: Matteo Pozzi, Civil and Environmental Engineering
Co-PI(s): Roja Malligarjunan, Civil and Environmental Engineering

In this project, we will collaborate with industrial partner RedZone Robotics to integrate their robotic inspection and data management services with probabilistic adaptive infrastructure performance models in order to optimize the management of wastewater collection systems. These systems are integral to the functioning of modern cities, but many are aging and subjected to increasing stresses, leading to declining performance. Up­to­date information on pipeline states can be efficiently obtained via robotic inspection efforts with autonomous sensor platforms. This data can also be processed using adaptive probabilistic models of pipeline conditions and deterioration processes. Together, timely pipe condition data coupled with predictive condition models can be used to better understand the current and future conditions of a wastewater system. Furthermore, probabilistic modeling of infrastructure conditions can guide future robotic inspector deployments to areas of greatest need, such as where pipe failures are predicted to occurs, or greatest uncertainty, where the model predictions are most unreliable based on current information. By collaborating with RedZone Robotics on this project, we will have access to large volumes of high-­quality pipeline inspection information from a variety of municipalities, which will allow us to calibrate robust models of pipeline performance which will be applicable across a wide variety of system. We expect to develop a suite of modeling and optimization tools which will allow RedZone Robotics to provide a high level of service to their customers, reducing their wastewater pipeline inspection and management costs and allowing the company to expand its customer base. This project will also advance the position of Pennsylvania as an incubator for smart infrastructure and smart city technologies, showcasing innovative applications of robotics and data mining to support optimized management of resources for infrastructure management and encouraging similar activities and collaborative innovations in the future.

Phosphate Recovery from Waste Water Using Lehigh University's Hybrid Ion Exchange
Nanotechnology (HIX-Nano)
Lead University: Lehigh University
PI: Arup SenGupta
Co-PIs: Derick Brown

During the last five years, Hybrid Ion Exchange Nanotechnology (HIX-Nano) was developed at Lehigh University. At the heart of this technology is a new class of polymeric materials that are essentially anion exchange resins within which zirconium oxide nanoparticles have been irreversibly dispersed through a proprietary technique. A US patent has been assigned to Lehigh University for invention of HIX-Nanomaterials. To date, this hybrid material has been used primarily to remove arsenic and fluoride from contaminated ground waters in Asia and Africa.

ESSRE Inc, a company in the commonwealth of Pennsylvania, is much interested in collaborating with Lehigh University to apply HIX-Nano for recovering phosphate from waste water. Pollutant nutrients, nitrogen and phosphorus, are known contributors to the impairment of estuaries and numerous other water bodies of water in and outside the Commonwealth of PA. Most importantly, the project attempts to recover phosphate from waste water collected from swine grazing plant and use that as a potential fertilizer. ESSRE will collect and provide wastewater from swine raising plants and the laboratory studies to develop a process to recover phosphate as commercially acceptable phosphate will be carried out at Lehigh University. During the course of the project, ESSRE is committed to providing a cash contribution of $10,000. ESSRE is also committed to applying for federal SBIR grants for the long-term application of the HIX-nanotechnology leading to removal and simultaneous recovery of phosphate from waste water streams.


Ternary Hybrid Encapsulants with Enhanced Processability for LED Applications

PI: Michael Bockstaller, Materials Science and Engineering
Co-PI(s): Zhao Lu, Materials Science and Engineering

Solid-­state lighting technologies hold the potential to save 217 terawatt-­hours, or about one-­third of lighting site electricity consumption, by 2025. One major barrier to the advancement of current solid-­state lighting luminaires is the poor thermal conductivity of polymer encapsulants that limit energy efficiency, lumens output and manufacturability of devices. In this project a new process for the fabrication of hybrid encapsulants with increased thermal conductivity and photothermal stability is developed. Excluded volume interactions between asymmetric filler inclusions are being used to enable the assembly of high thermal conductivity particle fillers into ‘thermal network structures’ that result in high thermal conductivity at low particle loading levels. Development, testing and device integration of novel materials systems will be pursued in collaboration with researchers at OSRAM Sylvania, the leading provider of solid-­state lighting solutions in North America.

Computational Methods for Enterprise-wide Optimization: Infrastructure Investment and Water Management in Shale Gas Supply Chains
PI: Ignacio Grossman, Chemical Engineering
Co-PI(s): Lorenz T. Biegler, Chemical Engineering and Nicolas Sahinidis, Chemical Engineering

Our main vision has been to develop advanced computational models and solution methods for Enterprise-­wide Optimization (EWO) for the process industries. A major challenge that is involved in EWO is the integrated and coordinated decision­making across the various functions in a company (purchasing, manufacturing, distribution, sales), across various geographically distributed organizations (vendors, facilities and markets), and across various levels of time scales for decision-­making (strategic, tactical and operational). A major focus of the proposed PITA project is the optimization of infrastructure investment, operations and water management of shale gas supply chains. The project is in collaboration with EQT.

Development of Polymer Hybrid Materials for the Bottom-Up Fabrication of Luminescent Panels
PI: Kris Matyjaszewski, Chemistry
Co-PI(s): Michael Bockstaller, Materials Science and Engineering

Semiconductor quantum dot (QD)­based full color luminescent panels are expected to provide breakthrough advances in the area of energy efficient active display and lighting technologies. To facilitate this type of application established manufacturing processes apply four-­color screen or inkjet printing processes to fabricate monochromatic zones of distinct­-color QDs. The sequential nature of multistep zone printing presents a formidable challenge for the commercialization of QD­-based active display and lighting technologies because it limits scale­up and cost efficient production. The overarching technical objective of this proposal is to develop a transformative new bottom-­up approach for the high throughput and cost efficient production QD-­based luminescent panels by harnessing the autonomous organization of mixed polymer-­modified QD systems into monochromatic domain structures. The scientific objectives of this proposal are threefold: First, to extend existing polymerization techniques to the scalable synthesis of polymer-­functionalized QDs with precise control of the architecture of surface-­grafted chains. Second, to elucidate the mechanism and kinetics of phase separation processes in thin films of mixed polymer­-grafted QD systems. Third, to understand the effect of polymer­-graft modification on the microstructure and photoluminescence efficiency of QD­-array structures. The results of the proposed research will provide a foundation for the development of new and transformative fabrication strategies for the cost-­efficient production of full­-color quantum dot­-based luminescent panels by replacing the established fabrication process based on multistep zone printing with a uniform coating process and the subsequent self­-assembly of quantum dots in monochromatic domain structures.

Analyzing and Defending CyberAttacks on Electric & Autonomous Vehicle Battery Systems
PI: Venkat Viswanathan, Mechanical Engineering
Co-PI(s): Vyas Sekar, Electrical and Computer Engineering
and Koushil Sreenath, Mechanical Engineering

We envision two key technology trends that are poised to revolutionize the automotive industry in the near future and that is likely to stay for the foreseeable future: (1) the commoditization of electric vehicles (EVs) and (2) the emergence of autonomous driving systems. These trends offer great promise to different stakeholders (consumers, car manufacturers, governments, society) in terms of costs, efficiency, and environmental impact. While these benefits are promising, they are accompanied by (valid) concerns with respect to safety and security. EVs in particular at present have an increased perceived safety and security risk due to concerns about fire hazards (e.g., large battery packs contain electrolytes based on known flammable materials), “range anxiety” (e.g., how much can we drive on a single charge), and battery life. These concerns with respect to car safety are very real – recent hack with 2014 Jeep Cherokee proves this point! The goal of our research project is to develop a principled understanding of the challenges associated in electric vehicle safety and security, specifically targeted at the battery system (e.g., safety, range, life). Addressing this problem entails an interdisciplinary approach combining battery modeling with system-level security analysis. To this end, we will develop (1) develop robust models for degradation and identify danger zones of operation; (2) systematic “attack graphs” that shed light on possible attack strategies; (3) concrete demonstrations of attacks against EV batteries; and (4) control strategies to mitigate the damage from these attacks.

Hydrometallurgy Extraction of Rare Earth Elements from Coal and Coal By-Products Using Chelate Enhanced Supercritical CO2
Lead University: Lehigh University
PI: Jonas Baltrusaitis
Co-PIs: Carlos E. Romero and Zheng Yao

This proposal is for a research project on a metal extraction concept that uses chelate enhanced supercritical carbon dioxide (sCO2) to recover Rare Earth Elements (REEs) from coal and coal by-products. The ongoing development of advanced technologies has created an increasing demand for REEs in the international markets. REEs play a critical role in high-tech industries such as cell phones, computers, electric cars, satellite communication and medical detection systems among others. It is of critical importance for the U.S., an economically competitive supply of REEs to maintain America’s economic growth and national security. Coal and coal byproducts contain significant amounts of REEs and federal government agencies are interested in supporting research on novel approaches for REE recovery and reuse. The intention is to use the proposed project to launch a research program at Lehigh University that aims at achieving proof of concept, optimization of metallurgical method with chelate enhanced sCO2, and construction and operational demonstration of a small-scale REE recovery apparatus. The results of the proposed research will be used to develop a strategy to procure further support for a REE recovery program at Lehigh University, using a combination of internal and industrial funding, as well as state and federal grants, and industry participation.

The Multifaceted Roles of Data and Source in Energy Data Orchestration in Asset Optimization
Lead University: Lehigh University
PI: Rudy Shankar

Electric utilities have had stellar success in managing their expensive capital assets-- generators, transformers and distribution systems-- around the world by transitioning from a time-based protocol to one that is condition-based that exploit modern wireless sensor technology. The secret was integrating large amounts of data into detecting component health conditions using advanced pattern recognition software techniques. Data historians with vast capacities and now operating in the cloud allow asset health monitoring across time zones and continents. But for a deeper understanding of the root problems data access across different operating entities that have their own protocols, their own proprietary manufacturing techniques. Our industrial partner, OSIsoft, Inc., a leader in the data warehousing industry is working on a "Community Warehouse" concept where data across the entities will be accessed for various purposes inclusive of research and development, defining policies of access and maintaining intellectual property rights. The PITA award will explore the various uses through projects conducted by Lehigh ESEI M. Engg students and used to support deserving students through focused awards.

Design and fabrication of a test bed for metallurgical and mechanical characterization of metals treated with liquid chemical solutions
Lead University: Lehigh University
PI: Wojciech Z. Misiolek

Quaker Chemical Corporation is interested in better understanding of the mechanism by which the newly developed chemical solutions interact with the surface of the hot deformed and/or cold deformed metal plates and sheets. Some of these chemical products are developed to limit chemical interactions between a metal and environment such as oxidation. These products may have a very significant impact on metal processing in terms of the process yield, infrastructure investments as well as financial and environmental impact. The main goal of the proposed project is to build a test bed allowing testing and analysis of interaction between sprayed liquid chemicals and metal substrate under different test parameters representing corresponding various industrial processing conditions. The proposed test bed would allow application of chemicals of different composition and concentrations and testing under broad range of parameters allowing in depth process analysis as well as material characterization of surface and subsurface layers in the treated and untreated materials. Optimizing the chemical solution application process including parameters such as temperature, pressure, flow rate, nozzle distance from the metal surface and solution chemical composition in laboratory experiments is another important mile stone of the proposed collaboration. The development of new chemicals and their optimized application during metal processing can lead to elimination of environmentally unfriendly chemical processes such as pickeling. The proposed test bed will be verified for the first selected chemical and applied to mild steel at elevated temperature. We have already characterized first steel samples treated under industrial conditions using light optical microscopy. After laboratory testing we will perform standard metallography analysis on the tested material to evaluate how well we can reproduce the industrial processing conditions in the laboratory testing bed. The long term objective is to expand this type of testing to a broad selection of new chemicals treating other metals and alloys.

Sustainable Filter Treatment: Real-time Analysis and Treatment of DPF Waste
Lead University: Lehigh University

PI: John T. Fox

Diesel engines power 85% of the U.S. ton miles of freight. Mobile sources, including highway and non-road vehicles combine to the second leading anthropogenic source of PM in the United States. Diesel engines form particulate matter during combustion and results in both an ash and soot particulate component. The particulate matter emitted by diesel engines is captured by diesel particulate filters (DPF), a required emission control device, but must be cleaned and serviced at periodic intervals. Hunsicker Emissions Services LLC is currently developing an innovative, data driven process technology to clean the filters faster, and more efficiently, while using 50% less energy than the existing DPF cleaning process. In a recent PITA research effort, Hunsicker Emissions Services LLC collaborated with the Lehigh University team, utilizing the University’s analytical laboratory capabilities to optimize the proprietary process for more efficient DPF ash and soot cleaning. In moving from a development to commercial process, the innovative process technology will need the capability to make similar analytical measurements in real time. In addition, due to the nature of particulate matter captured in the diesel particulate filter, certain metal ash components in the cleaning process waste have been identified as environmentally unsuitable for direct disposal unless treated. This PITA project will build real-time analytical measurement capability to ensure the same (or improved) level of cleaning process efficiency and environmental sustainability attained during process development are realized consistently in the commercial application. The Lehigh University Team’s analytical capabilities will be utilized to evaluate and screen candidate real time analytical methods. The suitability of leading candidates in the commercial process will be determined by their durability in the process environment to which they will be subjected.


Controlled Release Technologies for Treating Brain Aneurysms

PI: Christopher Bettinger, Materials Science and Engineering

Brain aneurysms are a high-­risk condition in which bulging blood vessels in the brain are at risk of rupture. The mortality rate after rupture is 30­60% if no treatment is administered. Current treatment for both ruptured and unruptured aneurysms includes surgical clipping (exovascular therapy) and catheter-­based interventions (endovascular therapy) including endovascular coiling. With respect to the latter, we are currently advancing an innovative coated-­coil technology that can deliver genipin, a small molecular protein crosslinker, within the aneurysm sac. We posit that sustained release of naturally occurring crosslinking agents delivered from coated endovascular coils will increase the mechanical stiffness of the clots and reduce fibrinolysis. Clots stabilized with genipin crosslinks will resist coil compaction and enzymatic degradation thereby increasing the likelihood of successful treatment by via embolization. Preliminary in vitro and in vivo studies suggest that this approach is promising. However, many open questions remain about the fate of genipin delivered in vivo. This project will use 3D­printed in vitro model aneurysm to measure fundamentals of genipin reaction kinetics, determine the chemical composition of genipin­-based crosslinks, and model genipin transport. Spatiotemporal distributions of genipin in 3D-­printed synthetic aneurysm sacs will be predicted and compared to experimental results. In addition to understanding fundamentals of genipin reaction kinetics and genipin crosslink composition, these fundamental studies will provide key data that can be used to design the next-­generation of genipin eluting embolization coils for treating intracranial aneurysms and other diseases such as hepatocarcinoma. Furthermore, a deeper understanding of fundamental processes related to genipin reaction-­diffusion may expand the use of this non­toxic naturally occurring small molecule crosslinker for other applications including stabilizing protein-based scaffolds for regenerative medicine or synthetic matrices for use in controlled release technologies.

Virtual 3D trainers for out-patient palliative care
PI: Phil Campbell, Engineering Research Accelerator

Hospitals and associated healthcare infrastructure are faced with the challenge of meeting the ever-increasing needs of an increasingly older and frailer population. By 2030, this elderly population will be 72.1 million representing 19% of the population. Ninety million people in the US live with at least one chronic illness. Many of these patients are the elderly with multiple chronic morbidities and undergo extensive periods of illness characterized by intermittent acute and intermittent acute symptom intensification interspersed with periods of relative stability. This often results in enormous stresses on healthcare systems, doctors and other clinical personnel, and patients and their families, as a result of inadequately treated physical distress, a fragmented care system and poor communication. Palliative care will be critical to the solution. Palliative care is an interdisciplinary medical specialty with the purpose to prevent and relieve suffering for all stages of disease, often encompassing years of chronic illness, and to support the best possible quality of life for patients and their families facing serious illness. Palliative care is increasingly important as increasing numbers of elderly and frail patients are homebound with multiple medical conditions, functional and cognitive impairments. In addition to the patient, their caregivers, many also aged and in ill health, are often unprepared to meet their care responsibilities. And, the stresses often incurred by the caregiver can result in them becoming the “forgotten” patient. Medical simulation training will be essential in ensuring successful palliative services intervention. We propose to develop 3D virtual reality game-based training programs that will be the first such trainers for palliative care. The first trainer program will target medical students, nursing students, and clinical staff to improve their assessment skills for the at-home patient. The second program will target educating and training family caregivers.

Portable ultra-high-resolution wireless EEG system
PI: Shawn Kelly, Engineering Research Accelerator
Co-PI(s): Pulkit Grover, Jeff Weldon, Marlene Behrman, Michael Tarr
Electrical and Computer Engineering, Psychology

High‐resolution dynamic recording of neural activity can help millions of Americans suffering from neurological diseases and injuries improve their function, mobility, independence, and overall quality‐of‐life. In addition, such high‐resolution recording can pave the way for new discoveries in brain monitoring, such as in concussion detection, disease detection, and early detection of child developmental disorders. It is widely believed that Electroencephalography (EEG) – which measures “brain waves” in a noninvasive, inexpensive, and safe manner using electrodes applied to the scalp surface – cannot yield high‐resolution imaging of the brain activity. Challenging this belief, our research team brought together concepts from information theory, fundamental physics, and neuroscience to show that the classical theoretical results are misleading, and could be severely pessimistic on the potential of high‐density EEG systems. This leads to the hypothesis that increasing the number and/or density of electrodes can dramatically improve EEG’s imaging resolution, which we are able to verify through preliminary experiments. Our overall goal is to create the “Neural Web” (shown in the figure at right), a wearable, wireless, high‐density EEG system that can not only simplify clinical diagnostics and reduce health care costs, but also enable research into new methods of non‐invasive brain‐machine interfaces. Specifically, the research proposed here will create the recording system, optimize the electrode design, and create the wireless communication system, capable of relaying all of the recorded data from the high‐density EEG to a base station, allowing the user to move freely.

Characterization of autologous human mesenchymal stem cells: Towards improving patient outcomes
Lead University: Lehigh University
PI: Sabrina Jedlicka
Co-PIs: Xuanhong Cheng

Autologous stem cell transplantation is becoming a widely available treatment option for patients suffering from osteoarthritic disorders, however, the treatment is only recently being reviewed by the FDA to ensure therapeutic quality between clinics. The procedure involves stem cell extraction from bone marrow, either through the use of specialized needles designed to maximize stem cell concentration or through post-extraction concentration protocols. This solution is then re-injected back into a site of damage (knee, shoulder, ankle, etc.). Pain relief can be significant, however, patient outcomes are highly variable, which is an impediment to widespread adoption of the technique. Cytokine signaling by the injected cells is the hypothesized mechanism of pain relief, however, initial cell quality and signaling potential may be the differentiating factor between patients who respond well to the treatment and patients who have a limited therapeutic response. In this project, we propose a fundamental study comparing patient cell behavior and phenotype in a wide variety of patient extracts, to discover a correlating set of biomarkers that are indicative of favorable patient outcomes. These biomarkers will be built into a point-of-care device designed to quickly and efficiently characterize extracted stem cells to provide physicians with an early indicator of how the patient will respond. This can then be coupled with other surgical/pharmaceutical interventions to ensure patient pain relief is maximized during the recovery phase and that cells engraft and survive in the long term. In the long-term, through working collaboratively with a local orthopedic surgeon, we hope to develop a methodology and translational technology to improve cell retention and therapeutic potential post-injection.

Advanced 3D Printing Techniques with Biodegradable Polymers for Novel Multifunctional Biomaterials
Lead University: Lehigh University
PI: Lesley Chow
Co-PIs: Raymond Pearson

Native tissues in the body exhibit structure-function relationships where the specific structure and arrangement of components is closely linked to biological function. Biomaterials designed to guide the regeneration of tissues and organs must recapitulate this hierarchical organization to enable clinical translation of the engineered tissue replacements to significantly impact healthcare technologies. Additive manufacturing, or 3D printing, techniques offer the ability to generate complex architectures with high spatial resolution. The objective of this project is to develop strategies that exploit 3D printing methods to combine multiple biodegradable polymers to create multifunctional biomaterials with anisotropic, tissue-like properties. Our team of Lehigh professors and students with expertise in advanced 3D printing techniques and polymer characterization will collaborate with polymer experts at Polysciences to optimize 3D printing conditions for a range of Polysciences' biodegradable polymers. The results will be used to tailor the structure and properties of multifunctional biomaterials for tissue engineering applications.

Developing Novel Therapeutics
Lead University: Lehigh University
PI: Neal G. Simon

Effective therapeutics for moderate-to-severe Traumatic Brain Injury (TBI) remains a major unmet medical need. In the Uited States alone, an estimated 1.7 million people sustain a Traumatic Brain Injury each year. Massive costs are associated with these injuries--52,000 deaths, 275,000 hospitalizations, and some 1.4 million individuals treated and released from emergency departments, with an annual economic burden estimated at $76.5 billion.TBI is a contributing factor to a third of all injury-related deaths in the United States. And among military personnel, there are over 30,000 medically diagnosed cases of TBI annually. In the proposed project, a collaborative effort between Lehigh University and Azevan Pharmaceuticals, experiments will be conducted to determine the feasibility of new therapeutic approaches to the treatment of this serious medical condition. With positive results, the project is expected to generate additional sources of funding that will support continued collaboration directed toward addressing these significant public health needs.

Quantifying Risks of Failure for Novel Health Technologies
PI: Alan Russel
Co-PI(s): Deborah Stine

Technology advancements are increasingly rapid and complex. Within healthcare, less than 1% of these advancements are transformative, or breakthrough, which have the potential to address the major limitations associated with the current healthcare system: cost, accessibility, and quality. Investors, companies, innovators and State agencies share a need to predict which health innovations will succeed in the marketplace to determine the magnitude of resources appropriate to focus on that technology.

The objective of our proposed research is to build a tool that can quantify the risks of failure associated with developing and regulating new health technologies by predicting the ‘transformative potential’ of a given technology. The successful regional development of this tool in Pennsylvania would position the Commonwealth to target the right technology with resources.

To do this, we propose combining FDA data, patent citation analysis, and interview data to build Bayesian belief networks (BBN), which is a probabilistic graphical model that represents variables and their conditional probability tables. The BBN is able to incorporate data- and opinion-driven variables, and our final design will output the ‘transformative potential’ of health technologies.

Preliminary analysis of 6,092 health technologies shows a correlation between some variable pairs, such as 510(k) Type and 2. Length of FDA Approval. Variable pairs with high correlations will indicate a conditional probability and help structure the BBN. Next, we will incorporate other FDA, patent, and company variables to continue building the BBN. Phase I of this project focuses on regulatory variables of cardiovascular technology (CVT), with the next phases expanding to other health technology areas. When complete, this tool will be used to better understand which variables influence transformative technologies entering the marketplace.


Small-Scale Structural Dynamic Testing Facility for Education, Training, and Research on the Effects of Natural Hazards on the Civil Infrastructure

Lead University: Lehigh University
PI: James Ricles
Co-PIs: Spencer Quiel and Chinmoy Kolay

A small-scale structural dynamic testing laboratory is essential for enhancing graduate and undergraduate structural engineering education on the effects of natural hazards mitigation on civil infrastructure and developing mitigation measures to promote resiliency of this infrastructure. This laboratory would provide hands-on laboratory exercises, research training, and enable the development and validation of innovative testing methods and algorithms. The proposed project is a continuation of a previously awarded PITA project to develop such a small-scale testing facility which will include a shake table, also called a seismic simulator, two dynamic servo-hydraulic actuators, and the hydraulic power supply system. The shake table, dynamic actuators, and servo hydraulic system will be acquired, while the existing real-time integrated control architecture and the servo-hydraulic controllers available at the Natural Hazards Engineering Research Infrastructure (NHERI) Lehigh Real-Time Multi-Directional (RTMD) Experimental Facility (EF) housed in the Advanced Technology for Large Structural Systems (ATLSS) Engineering Research Center will be used to drive and control the shake table and the actuators. The proposed facility will enable various types of testing to be performed on structural systems and components subjected to natural hazards, including extreme earthquake and wind loads. These tests include shake table testing for seismic simulation; and force/displacement controlled dynamic testing, hybrid simulation, and real-time hybrid simulation for both seismic and extreme wind loads. The reduced scale equipment will enable it to be conviently arranged for use, making it economical, while also reducing conjestion on the main laboratory floor.



The Value of Simplification: Firm and Workforce Implications of High-Variety Production in the Greater Pittsburgh Region

PI: Erica Fuchs, Engineering and Public Policy
Co-PI: Katie Whitefoot, Mechanical Engineering

With the decline in commodity prices, there have in the last few years been disproportionate lay­offs in the Greater Pittsburgh Region compared to other urban areas nation­wide, due to the region’s strong stakes in coke, steel, aluminum, and other alloys. As the region’s companies with tight ties to these commodities struggle under this crisis, they may be forced financially to favor short­-term cost (and labor) cutting decisions over strategic investments that will enhance their firm’s competitive position coming out of the crisis. Kennametal – which provides customers in a wide variety of industries including aerospace, energy, transportation, and general engineering innovative custom and standard metal cutting tools – is one of the unique and highly competitive firms in the Greater Pittsburgh Region deeply affected by this crisis. Core to Kennametal’s competitive advantage is its customized solutions. In Kennametal’s process, labor is likely one of the lowest contributors to production costs (and material one of the highest). Research also suggests that while automation can be essential to increasing productivity and reducing production costs at high-­volumes, automation can have little or negative value in production environments with high variety, where the unique knowledge and flexibility of humans offer competitive advantage. Leveraging extraordinary access to Kennametal’s production data systems, our project seeks to quantify these challenges considering the external swings in commodity prices.

Development of a Conformal Finishing Technique based on the Molecular Decomposition Process (MDP) for Additively Manufactured Metal Parts
PI: Burak Ozdoganlar, Mechanical Engineering, Biomedical Engineering, Materials Science and Engineering
Co-PI(s): Lee Weiss, Robotics Institute and Koushil Sreenath, Mechanical Engineering

Additive manufacturing (AM) of metals provided unprecedented capabilities for fabricating complex, three-­dimensional components. AM can bring many technological advances to a range of industries, such as aerospace and medical devices. However, in addition to geometric and form requirements, functional components need to satisfy surface-quality requirements. Unfortunately, parts fabricated by AM commonly have inferior surface quality. Considering the complex, curved surfaces of AM parts, finishing those parts to attain required surface quality demands utilization of very costly, time consuming, and non­standard processes. This significant challenge must be resolved to broaden the application of AM fabricated products. To address this need, we propose to develop a novel approach, which we refer to as the Conformal Molecular Decomposition Process (C­MDP), to enable finishing components with 3D complex geometries fabricated by AM. The MPD process uses electro­chemical and mechanical action to remove material, from a conductive workpiece, with very high precision, negligible forces, high material removal rate, and with no thermal or mechanical damage. Our partner Oberg has been the leader in MPD, and has demonstrated surface roughness better than 25nm in many materials of interest. Our innovative idea is to advance this process by developing and utilizing a conformal, brush­like tool (instead of flat grinding wheels) to enable finishing complex geometries. To this end, we propose to (1) develop the conformal CMDP tool, considering electrical and mechanical requirements; (2) advance an MDP system to realize a C­MDP testbed; (3) perform an experimental analysis to correlate process conditions to surface quality and process productivity metrics, and (4) to compare the C­MDP process with traditional finishing processes for AM parts.

The Development of Sustainable Polymers for Additive Manufacturing
Lead University: Lehigh University
PI: Raymond A. Pearson

The goal of this project is to develop sustainable polymer nanocomposites for SLS printing. Polyamide 11 and 12 have been chosen as the model polymer resins. The key technological enablers in the proposed work is the application of NOVEL NANOPARTICLES (from Cabot) with a novel mixing process (from Zzyzx) to produce sustainable materials (polymers from Arkema) that can be processed with a low energy consuming SLS printer. The performance of these new types of sustainable, biopolymer-based SLS powders will be compared to commercially available, petroleum-based powders.

Tungsten Heavy Alloy(WHA) powders for Additive Manufacturing (AM)
Lead University: Lehigh University
PI: Richard P. Vinci and Wojtek Misiolek
Co-PIs: Brian Slocum

Direct Metal Laser Sintering (DMLS) is an emerging alternative to traditional machining. DMLS is an additive manufacturing technique in which a metal component is built in a layer-by-layer fashion by selectively melting thin layers of metal powder using a high powered laser. After a layer is completed, a new layer of powder is added on top and the process is repeated. In this way, a complex solid 3D shape can be built to match a CAD drawing. The DMLS process requires that the laser is capable of melting the metal powder and that the melting and resolidification processes result in little or no porosity. There are numerous process parameters that must be set properly to achieve these outcomes. Tungsten and tungsten heavy alloys are challenging materials for DMLS because of the very high melting temperatures of these materials. The quality of the printed parts is also highly dependent on the nature of the metal powder. Together, GTP and Lehigh University will determine the optimum processing parameters for the powders produced by GTP, thereby guiding the development of tungsten-base powders for additive manufacturing.

Additive manufacturing rework and repair of metal manufacturing tooling
Lead University: Lehigh University
PI: Wojtek Misiolek and Richard P. Vinci
Co-PIs: Brian Slocum

The proposed collaborative project between Lehigh University and Medico Industries of Wilkes-Barre, PA is focused on a fundamental investigation of additive manufacturing as a means for repairing worn tooling used for metal forming operations. Current tooling repair methods are costly and slow. Additive manufacturing by metal powder laser sintering has the potential to reduce costs and accelerate the repair process significantly but much is unknown about the behavior of the materials processed in this unconventional manner. Stainless steel, nickel-base, and cobalt-base alloy cladding layers will be deposited onto tool steel substrates using a metal powder-based additive manufacturing process. In this proof-of-concept study, flat substrates will be clad using an additive manufacturing system recently installed at Lehigh. The structure and properties of the resulting clad alloys will be evaluated to determine compatibility with the tool steel materials and the potential for this technique to meet Medico's needs for cost-effective tooling repair. If successful, the project will serve as the motivation for pursuit of funding for a collaborative full demonstration project through the Department of Defense. This full demonstration project would enable repair and high temperature testing of actual Medico tooling.

ATLSS Research Experience for Undergraduates (REU) Program
Lead University: Lehigh University
PI: James Ricles

Conducting an educational outreach program for the benefit of PA companies and students, Lehigh University's Advanced Technology for Large Structural Systems (ATLSS) Research Center is developing a summer Research Experience for Undergraduate (REU) program for Summer 2017. The program, named the ATLSSreu Program, will introduce qualified undergraduate engineering and/or science students to a positive Civil Engineering-based research environment at Lehigh University. Goals of the program include inspiring the participants to pursue a graduate engineering degree at a Pennsylvania-based institution while exposing the students to select Pennsylvania companies during site visits. Participating students will be assigned an active research project at Lehigh University and will conduct the research under the direction of the project's Principal Investigator and a graduate student mentor. In addition to introducing the students to research methodologies, the program will expose students professional development workshops and industrial tours at Pennsylvania-based organizations focused on Civil Engineering-related operations. Student deliverables include the submittal of a final report and development of a formal presentation summarizing research findings during the program.