National Security Science Area

Oak Ridge National Laboratory scientists helped count the population of Nigeria – all without leaving the lab.

Medical teams with the Bill and Melinda Gates Foundation needed help finding patients while vaccinating for polio in Nigeria, a nation of roughly 190 million people. The last national census, conducted in 2006, did little good a decade later.

Researchers at ORNL and the University of Southampton estimated population counts for every village and neighborhood in Nigeria using satellite imagery and a national sample survey, called a microcensus.

“These estimates helped them figure out where to send people, how many vaccine kits to bring, how many children to expect when they went to a village,” said ORNL’s Eric Weber, who designed the microcensus described in the Proceedings of the National Academy of Sciences.

“We were able to do this by sampling just a tiny fraction of households.” – Matt Lakin

Horizon31, LLC, of Knoxville, Tenn., has exclusively licensed a novel communication system that allows users to reliably operate unmanned vehicles such as drones from anywhere in the world using only an internet connection. The technology, developed by the startup’s founders at the Department of Energy’s Oak Ridge National Laboratory will enable commercial, government and consumer drone use at scale.

Unmanned aerial vehicles, or drones, are typically operated by a single pilot on the ground using a handheld radio controller. This method works within the pilot’s visual range but becomes limiting as the aircraft flies beyond line of sight, where operation is more difficult and connectivity can be spotty. 

“To make these unmanned systems commercially viable – if you want to deliver packages, for instance – you have to be able to move beyond visual line of sight,” said Andrew Harter, chief executive officer of Horizon31. “In a lot of situations, you’re not going to have someone on the ground watching the entire time.”

The novel ORNL-developed software system, called the Multimodal Autonomous Vehicle Network, or MAVNet, solves this problem by enabling redundant connections through multiple communication pathways. With MAVNet, a pilot can simply log into the drone through the internet and “talk” to the system through a combination of local digital links, cellular services and satellite connections. These redundant options ensure positive control during a flight – even in areas with poor coverage or network lags.  

Uniquely, the system routes data via a central cloud server. Competing systems use an embedded computer integrated within the drone to provide remote connectivity, which can become bogged down when multiple users try to access information at the same time. Developed as part of ORNL’s advancement of the science of national security, the MAVNet architecture is fully scalable, making it ideal for large fleets or multiple simultaneous users.

MAVNet’s cloud-based data storage allows for multiple people to operate the system simultaneously and for one person to control multiple vehicles. This capability will make commercial-scale fleet management possible, opening the doors to applications in 3D mapping, infrastructure inspection, remote medical supply transport, search and rescue and commercial deliveries.

“We’re changing the ecosystem of how unmanned systems communicate and how people interact with them,” Harter said. “We’re excited to bring this new level of control to users everywhere.”

ORNL staff members Andrew Harter, Brad Stinson and Bogdan Vacaliuc conducted their original research and development as part of the National Security Sciences Directorate, which is currently expanding its activities and hiring staff in the area of unmanned vehicle technology. The trio formed Horizon31 to build a set of products and services that provide customized unmanned vehicle control systems. The Horizon31 team expects to have the first software prototype ready in the fall of 2020, with hardware available in the spring of 2021.

“ORNL is a leader in unmanned vehicle technology, and we are very interested in seeing a United States company bring this technology to the market,” ORNL’s Director of Technology Transfer Mike Paulus said of the licensing announced today. “We are excited that this team of entrepreneurs has formed a company in our region to commercialize MAVNet.”

The Defense Threat Reduction Agency within the Department of Defense supported the initial research behind this technology.

UT-Battelle manages ORNL for the Department of Energy’s Office of Science, the single largest supporter of basic research in the physical sciences in the United States. The Office of Science is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.

Each summer for the last 30 years, students and teachers from across Appalachia have travelled to the Department of Energy’s Oak Ridge National Laboratory for a unique STEM summer camp experience – the Appalachian Regional Commission/ORNL Science-Technology-Mathematics Institute.

The program was all virtual in 2020, but its research emphasis was as strong as ever, thanks in large part to dedicated ORNL volunteers who served as mentors and guest speakers.

During the program, more than 70 students representing 13 states learned about science topics such as climate change, robotics, spatial analysis, 3D printing and video game design. Over two weeks, students examined a research question related to their group’s science topic and created digital posters and video presentations to communicate their findings.

Jake McKee and Jessica Moehl of ORNL’s National Security Emerging Technologies Division mentored a group of high school students for the second year in a row. 

“We try to introduce the students to spatial reasoning and analysis, and we try to tailor it to something that’s relevant and current,” McKee said.

Their group of eight students used open-access geospatial software to determine an ideal site for a new “smart neighborhood” in Blount County, Tennessee, a project very similar to one the researchers actually worked on last year. McKee and Moehl devoted much effort towards getting students to think about the realities that utilities and local governments must consider when planning developments.

“We don’t provide a particular ‘right answer’ for them,” Moehl said. “That approach is something that they’re not going to get in their high school classrooms.”

Students in the climate change modeling and communication group heard from eight different ORNL researchers who spoke about multiple facets of climate science – from the basics of the greenhouse effect to carbon capture to the importance of the world underfoot.

“The goal of my presentation was to introduce the group to soil and its role in climate change,” said ORNL researcher Elizabeth Herndon, who was immediately interested in the program after looking for educational opportunities offered by the lab. “Soil is something we are all aware of, but most people know very little about.”

Abby Regan, a rising high school junior from Huntsville, Alabama, said she learned about the importance and variation of soils. One presentation that stuck out to her was a talk from Herndon’s colleague Colleen Iversen, an ecosystem ecologist who walked the students through her field research on ways that atmospheric and climactic change alters belowground carbon and nutrient cycling in soil and roots.

“As someone who is potentially interested in a science career, I thought it was really cool to see how a real laboratory operates,” Regan said. “I'm also glad I got to see some examples of actual scientists and people who work in a science field. It was really inspiring to me.”

Teaching teachers

 Besides inspiring students, the ARC/ORNL Summer Institute gives teachers from around the region the chance to work with ORNL scientists on projects related to research at the lab. Barbara Evans, a researcher in ORNL’s Chemical Sciences Division, has led a teacher group each summer since 2015.

“This year I had to come up with something that they could actually do at home in their kitchens,” she laughed.

Teachers in her group grew tomato plants and observed over Zoom measurement of certain compounds produced by the leaves of similar plants growing in the lab, which could be used at scale to generate electricity. The goal was for the educators to participate in research while expanding their repertoires of inexpensive experiments for use in their own classrooms.

“The ARC program isn’t just providing teachers an educational opportunity during the summer, it really propagates,” Evans said. “The teachers use it to train their students, so it’s very useful and provides educational outreach to an entire school and entire community.”

Hometown advantage

Though the remote format presented unique challenges, like when Evans’ internet connection went out, it also opened up unique opportunities.

“For some of the groups, they were actually able to examine problems in their own neighborhood and gather research from their home locations, which they typically wouldn’t get to do during the in-person program,” said Chris Nelson, program manager at Oak Ridge Associated Universities.

The climate change group, for instance, used sensors provided by ORAU to measure ambient temperatures around their yards.  Students in the 3D printing group, led by researchers out of Los Alamos National Laboratory, received components that allowed them to 3D print at home.

“The sensors made it more hands-on,” said Isaac Sulfridge, a rising high school junior from LaFollette, Tennessee. “It also gave us raw data that we could process ourselves. I still have mine actively recording the temperature outside.”

Though students didn’t get to peek at the nation’s fastest supercomputer or tour research reactors at ORNL, they walked away with new tools, new knowledge and hopefully – says ORNL’s Jake McKee – new confidence. 

“Both Jessica and I are from smaller communities in southern Appalachia, so our number one goal was to ease any concerns students might have about growing up in a rural area, going to small schools,” McKee said. “We wanted to show them that it doesn’t matter where you’re from.”

For more information about ARC Oak Ridge Summer STEM programs, visit https://www.orau.org/arc-ornl/default.html. For educational resources and information on how to get a scientist to virtually visit your child’s classroom, visit ORNL’s STEM Source website at https://stem.ornl.gov.

UT-Battelle manages ORNL for the Department of Energy’s Office of Science, the single largest supporter of basic research in the physical sciences in the United States. The Office of Science is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.

From materials science and earth system modeling to quantum information science and cybersecurity, experts in many fields run simulations and conduct experiments to collect the abundance of data necessary for scientific progress. But gleaning useful insights from those data can be a challenge, especially when multiple complex variables influence research results.

To better analyze the so-called multivariate data, researchers at the Department of Energy’s Oak Ridge National Laboratory developed an open-source, customizable visual analytics system called CrossVis. Unlike similar tools — which tend to focus on numerical data and provide a single visual representation of results — CrossVis juggles numerical, categorical and image-based data while providing multiple dynamic, coordinated views of these and other data types.

ORNL researchers John Goodall, Junghoon Chae, Artem Trofimov and Chad Steed, director of the ORNL Visual Informatics for Science and Technology Advances, or VISTA, laboratory, made CrossVis available online and published the system’s unique capabilities in Graphics and Visual Computing.

“CrossVis is a one-stop shop for analyzing many different types of data, and it reveals relationships among more than just two variables,” Steed said.

The tool’s main view consists of a parallel coordinates plot, or PCP, which is a popular information visualization technique. PCPs display a data table’s columns as vertical axes and its rows as polylines, which are chains of interdependent line segments connected to the axes. In this case, the CrossVis interface extends beyond traditional PCPs to include nonnumerical data, which have no natural order, and temporal, or time-based, data.

Additionally, CrossVis provides scatterplots, image panes and other options that complement the main view to help users identify key patterns and interesting anomalies in heterogenous, multivariate data. To narrow their focus, users can also choose to highlight a variable in all views simultaneously, generate new data or input parameters to filter existing data.

“Before, scientists had to use individual programs to analyze image data, numerical data and categorical data, then manually compare the results,” Steed said. “CrossVis lets them complete all those steps within a single framework.”

The team took advantage of the system’s ability to analyze categorical and image data by applying it to a genetic engineering project led by researchers at ORNL’s Center for Nanophase Materials Sciences, or CNMS, which involved verifying results from an artificial neural network, or ANN, applied to scanning electron microscopy images of diatoms. A type of algae, diatoms produce strong silica that could be useful for industrial purposes, including drug delivery and water filtration.

Specifically, the CNMS team characterized pores on the diatoms to distinguish between unmodified, or wild, diatoms and genetically modified versions of these organisms. Eventually, these insights could help scientists optimize and emulate diatom biomineralization, which is the process these organisms use to generate silica.

The team used CrossVis to examine relationships between diatom parameters, and the tool’s many views revealed subtle differences between the two categories. For example, the researchers determined that wild diatoms have more pores that are smaller than those of their modified counterparts, which have fewer pores that are larger in size.

“The ANN automatically derived image classifications that identified pores as an important feature for separating the two types of diatoms,” Steed said. “However, these results didn’t clearly show why the algorithm chose to classify pores the way it did, so CrossVis enabled the CNMS scientists to interpret and verify their findings.”

“Without CrossVis, we would not as thoroughly understand how to differentiate between wild and modified diatom images based on these crucial parameters, namely mean area and the density of pores,” added ORNL researcher Artem Trofimov, who led the CNMS project.

To prove the value of CrossVis at a larger scale, Steed and his collaborators also worked with the ORNL-led team that developed the Energy Exascale Earth System Model to help validate climate modeling techniques. Additionally, the team used CrossVis to verify data in the National Oceanic and Atmospheric Administration’s Atlantic Hurricane Database, which contains 21 columns and more than 50,000 rows of statistical information about the locations, sizes and other characteristics of hurricanes over time.

“That was a good use case because it was a much larger dataset with more variables,” Steed said. “We found patterns that confirmed known hurricane conditions, which demonstrated that CrossVis can effectively validate real-world results on a larger scale.”

Going forward, the CrossVis team aims to further improve this resource. For example, the researchers plan to scale up CrossVis to run on high-performance computing systems. With the processing power of supercomputers, such as ORNL’s Summit, CrossVis could more efficiently complete complex calculations.

By incorporating automated machine learning techniques, the team plans to more actively capture user interactions with the data. Scientists would label data samples, and built-in artificial intelligence algorithms would then identify, label and compile similar patterns in unseen sections of the data, enabling users to quickly analyze entire datasets and potentially make unexpected discoveries.

“If you tried to sort through something like the hurricane dataset or climate modeling data manually, it would take a lifetime,” Steed said. “This kind of human-machine cooperation, which combines the creativity and intuition of domain experts with the data-crunching power of computers, is the key to more effective data analysis.”

This research used ORNL’s VISTA laboratory and resources of CNMS, a DOE Office of Science User Facility. Support for this work came from ORNL’s Laboratory Directed Research and Development program and DOE’s Scientific Discovery Through Advanced Computing program.

UT-Battelle manages Oak Ridge National Laboratory for DOE’s Office of Science, the single largest supporter of basic research in the physical sciences in the United States. DOE’s Office of Science is working to address some of the most pressing challenges of our time. For more information, visit https://energy.gov/science. — Elizabeth Rosenthal