PENNSYLVANIA INFRASTRUCTURE TECHNOLOGY ALLIANCE
www.pitapa.org | Spring 2024
A Commonwealth-University-Industry Partnership for Economic Development through Research, Technology, and Education IN THIS ISSUE
INFRARED TRAFFIC PAINT TECHNOLOGY IN AUTONOMOUS DRIVING- P.3
DIRECT SOLAR THERMOCHEMICAL HYDROGEN PRODUCTION - P.4
DIGITAL TWINS IN NEXT-GEN MICROREACTOR TECHNOLOGY - P.5
MATHEMATICAL MODELING IN INMATE TREATMENT PROGRAM SCHEDULING - P.6
The Pennsylvania Infrastructure Technology Alliance (PITA) has connected Pennsylvania’s companies with the Commonwealth’s world-class university researchers and their students for the past 26 years, promoting economic development in Pennsylvania. Funded by the Pennsylvania Department of Community and Economic Development (DCED), PITA helps Pennsylvania increase the state’s market competitiveness through the development of new technologies and process improvements.
We are proud of the program’s strong history of working with Pennsylvania companies and students to foster economic growth in the state. The program has supported over 1,400 technology and process improvement projects in partnership with more than 550 Pennsylvania companies, obtaining more than two dollars of funding from industry and federal sources for every dollar of state funding. PITA has also mobilized more than 510 faculty members and over 2,300 students to work on Pennsylvaniaspecific technology, process improvement, and educational outreach projects, and has also enabled 15 startup companies to be created from PITA-sponsored technologies.
In this edition of the PITA Newsletter, we highlight recent partnerships with:
• PPG Industries
• Solarflux Energy Technologies, Inc.
• Westinghouse Electric Company
• Optamo LLC
As always, we welcome partnerships with new companies. Those interested in working with faculty and graduate students on short-term technology development or process improvement projects should contact the PITA associate directors: Chad Kusko, Lehigh University, chk205@lehigh.edu or Colleen Mantini, Carnegie Mellon University, cmantini@cmu.edu.
shk2@lehigh.edu
PITA Newsletter 2024 BURAK OZDOGANLAR PITA Co-DirectorPavement markings serve as a highly effective traffic control device to communicate critical visual information to road users. While motorists become adept at interpreting pavement markings through driving experience and intuitively navigate their surroundings, autonomous vehicles continue to be challenged by sensing and perception issues. Carnegie Mellon University (CMU) partnered with PPG Industries (PPG) to investigate encoding information in traffic paint to provide a richer control on driving environments as seen by machine perception systems, thereby reducing computational overhead and leading to a safer driving experience.
Pavement markings convey basic information about the layout of streets and the lanes within while ensuring visibility under different environmental conditions. Every few years, road workers replenish faded pavement markings with a fresh layer of paint. Aswin Sankaranarayanan, professor of electrical and computer engineering at Carnegie Mellon University, sees an opportunity to leverage this existing replenishment process and enhance the functionality of traffic paint using infrared additives invisible to the human eye but observable by cameras.
“In our project, we use this idea that the paint that we use on streets for traffic marking is changed much more frequently than road signs or traffic signals,” says Sankaranarayanan. “Repainting pavement markings is something that's done all the time, which presents an opportunity to do something innovative without changing this existing system as far as humans see it.”
PPG (Pittsburgh, PA) approached CMU with a project concept, and PITA facilitated an introduction to Sankaranarayanan, an expert in the study of light and materials sensors. The collaboration resulted in manipulating the spectral properties of traffic paints to encode data observable by a spectrally sensitive camera, significantly enhancing the amount of information that infrastructure can present to assisted and autonomous driving systems. By encoding information on existing lane markings and structures, the team believes it can make it simpler for autonomous vehicles to understand their surroundings without adversely impacting the current system that works well for humans.
The project leverages a phenomenon known as metamerism, in which colors that appear similar present different properties when viewed under different lighting conditions. Using two copies of the same paint color, a coat of paint containing near infrared light (NIR) additives is layered on top of another coat without additives, with no obvious perceptual difference to human drivers.
With this idea of metamerism that we're using, we can have two completely different spectrums of light that appear identical to people because the human eye is a weak distinguisher of colors
This project builds upon prior work by the PI on cameras that can identify differences in material using spectral signals. Above: Real world scenarios with an optical classification strategy capable of providing pixel level material maps for a wide range of objects.
relative to machine vision technology,” says Sankaranarayanan. “The color combination will look the same to us but any camera that can detect infrared light will see the barcode or design that you've laid out.”
Recognizing the infrared paint, machine vision systems used in autonomous vehicles will have more input to identify the boundaries of individual traffic lanes and better anticipate upcoming stops and lane changes. Instead of relying on the camera to identity a specific marking, such as a stop sign, and reason where to stop the vehicle, the information can be reported in advance through paint on lane markers.
“We can help assisted and autonomous driving systems navigate potentially dangerous driving scenarios,” says Sankaranarayanan For example, road workers can embed a message on the lane marker of a curved road that alerts the vehicle to an obscured stop sign. “Even a small amount of advance information could make a significant difference in safety, especially when factors like weather, poor visibility, and [human] driver distractibility are considered.”
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Solarflux Energy Technologies, Inc. was founded in 2019 with a strong focus on developing groundbreaking technologies to address growing energy demands worldwide. The Solarflux team is optimistic about the potential of parabolic dish concentrators to provide cost-effective and sustainable energy solutions to underserved market sectors, particularly in regions of the world with an abundance of direct sunlight. Fostered by PITA, the company has collaborated with Lehigh University’s Energy Research Center (ERC) over the last five years on solar energy-related projects.
Solarflux (Reading, PA) manufactures solar concentrators from low-cost, fully recyclable materials that are easy to install with low maintenance requirements. The company’s flagship product is the FOCUS parabolic reflector dish system, capable of dual-axis tracking and a 10 kWth peak power rating. Electrically powered by PV panels, the concentrator is autonomous and is integrated with a Dynalene SF heat transfer fluid loop for operation up to 310°C. FOCUS also includes a CCD camera for direct solar tracking, supported by GPS for passive tracking during periods of cloud coverage.
The Solarflux team recently donated one of its FOCUS solar concentrator units to Lehigh University, where the ERC team continues to contribute their technical expertise in energy systems. The FOCUS unit, along with an associated Thermal Energy Storage (TES) system, will be used to study the dynamics of solar energy-TES as part of the PITA project.
"Thermal energy studies are generally done with steady thermal sources, whereas the current project will enable the study of the temporal nature of solar thermal energy storage,” says John Fangman, CEO of Solarflux.
Solarflux's flagship FOCUS parabolic reflector dish system. Image source: www.solarflux.co
The integrated system will also be available for instructional projects for students and as a testbed for joint research projects.
“The ERC has been working for many years on thermal energy storage projects that include sensible, latent and thermochemical energy storage,” says Dr. Carlos Romero, ERC director. “This testbed addition by Solarflux provides another resource to continue developing these thermal energy storage technologies while linking them with the real dynamics of solar harvesting.”
"This testbed addition by Solarflux provides another resource to continue developing these thermal energy storage technologies while linking them with the real dynamics of solar harvesting."
Dr. Carlos Romero, director, Energy Research Center at Lehigh University
The Solarflux and Lehigh University collaboration investigated research on membrane distillation (MD), a thermally-driven separation process in which only water vapor travels through a microporous hydrophobic membrane. This process has various applications, such as desalination and wastewater treatment. The MD project consisted of membrane selection, characterization, and process optimization for maximum clean permeate flux transport using process conditions typical of solar thermal collectors. A complete lab-scale rig was built for membrane testing. The project demonstrated the effectiveness of solar energy as a cost-effective option for impaired water treatment, resulting in a competitive cost of water cleaning using a renewable resource.
Continued on page 7
In recent years, there has been a significant increase in the adoption of renewable clean energy, signaling a crucial transition towards sustainable power production on a global scale. Technological progress, supportive policies, and a heightened public awareness of environmental issues have made renewable energy sources like solar, wind, and geothermal power increasingly accessible and cost-effective. Countries at the forefront of responsibly sourcing and manufacturing clean energy technologies stand to gain significant economic advantages.
Of America’s many abundant energy resources, nuclear energy emerges as a vital component of the U.S. renewable energy sector. According to the U.S. Department of Energy, nuclear power contributes nearly 20 percent of the electricity generated in America. Nuclear reactors are among the most viable options for a rapid transition to a carbon-free economy. A vital component of the portfolio of nuclear power generation is the development of next-generation small modular reactors (SMRs) and microreactors. Microreactors are compact in design and can potentially be connected entirely off the grid, offering a reliable and scalable solution to meet growing energy demands.
Westinghouse Electric Company (Pittsburgh, PA) is a leader in the microreactor space with its nextgeneration eVinci® microreactor. In contrast to large, centralized stations, the transportable eVinci® was designed for decentralized remote applications, such as distant mining operations and other remote or edge-of-grid communities. Westinghouse refers to its revolutionary design as a “nuclear battery.” After generating electricity over a life span of 8+ years, the entire microreactor unit—including its spent fuel—can be seamlessly removed and replaced with a new unit, like a battery.
In October 2023, Westinghouse met with CMU College of Engineering faculty to discuss industrial and research challenges. Following an absorbing exchange of ideas during the CMU campus visit, continued discussion led to addressing the needs of the eVinci® development and related research opportunities.
Westinghouse's next-generation eVinci® microreactor Image source: www.westinghousenuclear.com
Supported by PITA, Westinghouse is collaborating with CMU researchers to investigate how to embed sensors in microreactors to monitor their performance and support decisions on reactor operation and maintenance. Led by Matteo Pozzi and Kaushik Dayal, professors of civil and environmental engineering at CMU, the project follows the paradigm of Digital Twins, where physical entities (microreactors) are represented by numerical models informed by data collected by the monitoring systems. In turn, the forecasts provided by the numerical models support the control process of the physical entities.
To Pozzi and Dayal, the application of Digital Twins to microreactors is particularly enabling because similar devices can be jointly analyzed, calibrating a general model for the reactor type and one specifically calibrated model per each microreactor, according to a set of interconnected probabilistic digital twins.
The team is optimistic about the project's potential for industrial and societal impact. Digital twins offer a valuable application in the realm of microreactors due to the need for mechanical modeling, the integration with sensor data, and the possibility of developing a hierarchical model, where the general model is related to specific models for each reactor. Benefitting from Westinghouse’s long history of innovation, the team believes their partnership will contribute to the commercial competitiveness of the eVinci® reactors and support Pennsylvania's leadership in clean energy research and manufacturing.
Pennsylvania currently houses approximately 40,000 inmates across 24 state correctional facilities. Prior to being granted parole, all inmates must complete a specific set of treatment programs. Certain programs can progress only at the pace of an individual undergoing treatment. That is, until one inmate completes the program, another must wait for their turn to begin. Other programs progress via a cohort, with a set number of inmates starting and ending the programs on the same days.
At issue is the fact that inmates can remain in the prison system longer than their minimum sentence if they miss treatment or are otherwise unable to access a required program. This can delay their return to society and result in increased demand for Department of Corrections resources and state funding. It is also extremely difficult and time consuming for corrections department officials to obtain a feasible and effective scheduling of the treatment programs for inmates.
A similar inmate assignment problem was previously solved by a group of graduate students working with Tamás Terlaky, professor of industrial and systems engineering at Lehigh University. Terlaky’s group was tasked with assigning up to a thousand inmates per week to the most appropriate prison facility. Graduate students Mohammad Shahabsafsa and Anshul Sharma incorporated the solution into their thesis work.
The deployment of their proposed solution method significantly reduced the time needed to complete this facility assignment task, resulting in millions of dollars saved for the state, improved safety, and a decrease in the prison population. Following the completion of this project, Terlaky, Shahabsafa, and Sharma founded the operations research and analytics consulting company Optamo LLC (Bethlehem, Pennsylvania).
Supported by PITA, Luis F. Zuluaga, professor of industrial and systems engineering at Lehigh University, and graduate student Ramin Fakhimi partnered with Optamo to investigate inmate treatment programs. The research team focused on tracking individual and group programs to optimize the treatment schedule required for parole. The team’s primary goal aimed to expedite the start of inmates' necessary programs and ensure they finish them within the shortest amount of time. A secondary goal aimed to reduce the amount of time program instructors spend holding classes, considering the number of inmates already in the program’s pipeline and the resources available.
Using data and scheduling procedures provided by the Pennsylvania Department of Corrections Office of Research and Development, the team developed a proof-of-concept mathematical optimization model for detailed scheduling of treatment programs for correctional systems using advanced prescriptive analytics and operations research methodologies. Led by Zuluaga, the team demonstrated that the best way to schedule the inmates and associated programs can be efficiently determined using appropriate data and mathematical optimization methods. Considering the large number of decision variables involved, as well as the number of inmates, the team believes their model will yield substantial benefits to a correctional system. A fully implemented system can assist in staffing support, monetary savings, security improvements, decreased prison population, reduced prison sentences, and an increased recidivism rate.
Leveraging the same methodologies, Optamo also developed solutions to optimize the assignment of inmates to facilities and housing units as well as to optimize inmate transportation. These program scheduling systems, as well as the other solutions, can be implemented at any state department of corrections in the United States, benefiting corrections departments and inmates nationwide, and helping Optamo grow into a thriving Pennsylvania business.
Continued from page 3
Sankaranarayanan believes there is enormous potential for advancing the safety of autonomous driving using a low-cost, highly scalable technology that leverages existing infrastructure surrounding vehicles on roads and highways.
“The potential of rapid scalability is what excites me most about this project,” says Sankaranarayanan. “If in two years’ time you make an improvement to the paint combination that requires a slightly different shade or hue, you can implement that change whenever those roads are due to have pavement markings replenished. Within a matter of years, nearly every street in Pennsylvania can benefit from the technology.”
Currently, the team is collecting spectral signatures associated with various paints to find a combination of paints which look the same to the human eye but appear maximally different to a spectral camera. When the team identifies the right paint combination and their wavelengths, they will build a spectral camera which can lock on to these two signals and enter testing with autonomous vehicles.
Sankaranarayanan credits the PITA program for identifying the potential synergy between his group’s expertise and PPG’s interests. Pioneered by CMU in the 1980s, Western Pennsylvania has a rich history of over 30 years in autonomous driving research from academia, industry, and startups. Sankaranarayanan believes there are natural
partners around Pittsburgh who could deploy the team’s infrared paint technology in their test beds.
“I’m hopeful that there will be greater adoption of the technologies for assisting drivers in various ways because that will naturally lead to greater safety when it comes to navigating our streets,” says Sankaranarayanan. “If you can augment the infrastructure around a vehicle to make it safer and easier to drive, that benefits all of Pennsylvania. If successful here, the test that we're running in its [Pittsburgh] application then extends itself nationwide and potentially worldwide.”
“With the onset of autonomous vehicles, machine reading of traffic markings will be a required capability. This project will help us to understand what kind of changes and new technologies we need to develop in order to meet the need of both human interactions and interactions with modern cameras in the vehicle.”
Gobinda Saha Global Technical Director – Traffic Solutions PPG IndustriesContinued from page 5
The partnership also explored the production of hydrogen gas through solar energy. Hydrogen has been proposed as a potentially viable contributor to the global decarbonization effort and for moving the global economy to a net-zero carbon future. Direct solar thermochemical hydrogen (STCH) production by water splitting is one approach which can utilize the full spectrum of solar radiation and has the potential of achieving high solar energy conversion efficiencies.
The hydrogen conversion project is currently ongoing. It consists of a two-step STCH cycle, using a metal oxide high temperature step provided by a solar concentrator for metal oxide reduction, followed by an oxidation step for water splitting at a lower temperature. This concept will demonstrate the effectiveness of locating a solar hydrogen producing reactor at the focal point of Solarflux’s solar concentrator for utiliza tion of solar thermal energy for hydrogen production.
PENNSYLVANIA INFRASTRUCTURE TECHNOLOGY ALLIANCE
PITA is an industry-led program that enables companies to identify opportunities for Lehigh University and Carnegie Mellon University, and for the universities to provide expertise and capabilities, through faculty and students, that the companies may not otherwise be able to access.
Pennsylvania companies gain access to faculty expertise, university equipment, and students. University faculty and students are afforded the opportunity to work on real-world, market-driven challenges confronting Pennsylvania companies.
Faculty and students assist companies in creating technology of the future and enhancing the competitiveness of Pennsylvania companies with the goal of the creation of jobs in Pennsylvania and the retention of highly trained/educated students in Pennsylvania.
PITA Technology focus areas include:
• Transportation
• Telecommunications and information technology
• Facilities
• Water systems
• Energy & environment
• Public health & medicine
• Hazard mitigation & disaster recovery
Nathan Snizaski Chief Editor
Carnegie Mellon University nsnizask@andrew.cmu.edu 412-268-9157
Chad Kusko
PITA Co-Associate Director Lehigh University chk205@lehigh.edu 610-758-5299
Colleen McCabe Mantini
PITA Co-Associate Director
Carnegie Mellon University cmantini@cmu.edu 412-268-5314
