If you are a JHU faculty member, please join the Ralph O’Connor Sustainable Energy Institute (ROSEI) for an informal opportunity to get to learn more about the Applied Physics Lab (APL). Jeff Maranchi and Konstantinos Gerasopoulos will present an overview of APL, as well as discuss APL’s Research and Exploratory Development (REDD) division. They will also focus on APL’s various research efforts in the area of sustainable energy and materials, as well as go over the best ways to start a collaboration with APL. Lunch will be provided to those who attend.

Note: This seminar is being organized and hosted by the JHU Department of Civil and Systems Engineering (CaSE). ROSEI is sponsoring the seminar. Title: Physics-informed data analytics approaches using constrained optimization - exploiting domain knowledge with hard information in a transportation network Abstract: Civil infrastructure as a system often faces challenges and complexity brought by interactions between spatially- and functionally- distributed components. Recognizing and incorporating these physical interactions in data driven approaches present challenges but also unique research opportunities for domain experts. In this talk, I will use transportation networks as examples to discuss how constrained optimization, by providing a flexible modeling framework for integrating domain knowledge, statistics, and data-driven approaches, could help addressing some fundamental data challenges that frequently arise in transportation applications. The first example shows how stochastic programming (SP) can be used to provide a statistically consistent and efficient estimate of global variables (network-level travel demand) that are not directly measurable based on partial local measurements (link-level traffic flows). In this example, domain knowledge reflecting network physics is modeled explicitly as constraints, and data samples are treated in some sense as uncertain scenarios in a SP framework. The second example shows how domain knowledge regarding the usage of data may be directly incorporated in data compression to support end-to-end learning. In this example, objectives of the downstream application may be included in the design of the loss function in the data dimension reduction process. The results demonstrate the importance of application-aware data compression approaches for networked data. Bio: Yueyue Fan is a professor in Civil and Environmental Engineering at University of California, Davis. She is also a faculty member in the graduate program of Applied Mathematics at UC Davis. Dr. Fan’s research is on transportation and energy infrastructure systems modeling, with a special interest in integrating applied mathematics and engineering domain knowledge to ad-dress fundamental challenges brought by data and system uncertainty, dynamics, and underdetermined issues. Dr. Fan is currently serving as the program director of the Civil Infrastructure Systems (CIS) program at the National Science Foundation.

The Ralph O'Connor Sustainable Energy Institute (ROSEI) is hosting an all-day in-person summit on January 18 to display different research being conducted at Johns Hopkins University (JHU) in the sustainable energy and materials fields. ROSEI’s goal for the event is for the Hopkins community to learn about and share the entirety of the sustainable energy and related research being conducted at the school.

Call for Presentations

This is a call for anyone JHU-affiliated to present their current or latest research in these areas at this university-wide event. This includes:

• Graduate students
• Postdoctoral candidates
• Research scientists
• Engineers
• Faculty

There will be keynote main sessions at the summit with all who attend, as well as several breakaway opportunities for people working in similar areas to collaborate and share ideas in small groups. There will also be presentations from the leaders of ROSEI's four research pillars - Carbon, Storage, Wind and Grid – who will discuss their current research and the impact it can have in the fight against climate change. If you are interested in creating a poster or presentation for this event, please click the link below to register. The registration period will close on December 14.

Register

Please continue to check this page as more information about the event becomes public. And see below if you would like to learn more about ROSEI's four pillars, and the main work being pursued in each area.

Carbon

Combatting carbon dioxide output is one of the main pillars ROSEI is founded upon. ROSEI’s main focus in this area is on a novel attempt at extricating the carbon in CO₂ and converting it into a form of solid carbon useful in applications ranging from farming to construction. Led by ROSEI leadership council members Jonah Erlebacher and Chao Wang, these efforts are house under an initiative titled “Negative Carbon Carbon (NC²).” “If we can do this, we would be the first in the world to demonstrate a complete carbon-to-carbon route, in which so-called ‘bad carbon’ is transformed into a globally useful ‘good carbon,’” Erlebacher says.

Storage

ROSEI’s main work in this area is funneled through the Light-Integrated Technology for Energy Storage (LITES) Initiative, which is attempting to use two different methods to expand solar energy’s uses. The first method involves the creation of new flexible, lightweight, high-efficiency solar technology with light-collecting capabilities, while the second focuses on photobatteries, which integrate two functions into one device without sacrificing either energy generation or storage performance. The research is led by a trio of ROSEI leadership council members: Jeff Maranchi, Sara Thoi and Susanna Thon. “We aren’t trying to come up with just incrementally better ways to store solar energy; we’re attempting to establish a whole new paradigm for solar energy where the generation and storage are integrated into one system,” Thon says.

Wind

Wind power is rising. Having grown from supplying less than 2 to over 8% of US electricity in only a few years, this renewable source of energy is a disruptive technology that can help usher in a sustainable energy future. One impediment to increasing reliance on this clean, sustainable power source is the vast size of many windfarms and the challenge of understanding turbine-turbine and turbine-atmosphere interactions. These interactions affect wind farm performance on a variety of levels—from power output to turbine loading and maintenance. High performance computer simulations can help by providing detailed insights into fluid mechanical effects associated with turbine placement, layouts, and environmental factors. Led by Dennice Gayme and Charles Meneveau, ROSEI has started an initiative focused on creating a public database of windfarm simulations, which will allow anyone with an internet connection to easily access and analyze the data in order to conduct research, generate knowledge, and evaluate models or wind field data to be used in wind farm planning or development projects.

Grid

The purchase and delivery of power through a grid that relies almost entirely on renewable energy and new paradigms for energy storage is vastly different from today’s grid. Our team is developing a complete power systems laboratory utilizing a simulation and hardware-in-the-loop platform that will interface software solutions developed by the ROSEI team – such as models and algorithms for efficient power grid and market operations – with a robust simulator emulating an inverter-dominated power grid. The focus on high-impact and high-visibility applications distinguish this ROSEI Research Initiative from other testbeds. We are also working with partners to bring these solutions to today’s power systems as expediently and equitably as possible. Faculty leaders in this area include Yury Dvorkin, Dennice Gayme, Ben Hobbs, and Enrique Mallada.