Argonne researchers win three 2023 R&D 100 Awards

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The awardees include two open-source HPC software packages and a web-based portal that was created using climate data generated on ALCF systems.

Researchers at the U.S. Department of Energy’s (DOE) Argonne National Laboratory and partner organizations have been honored with three awards as part of the 2023 R&D 100 Awards, colloquially referred to as the ​“Oscars of Innovation.” An additional Argonne project was named a finalist.

“We are thrilled to see Argonne researchers and partners recognized by this prestigious awards program for their innovative work,” said Megan Clifford, Argonne’s associate laboratory director for science and technology partnerships and outreach. ​“Argonne’s winning projects and those that were named finalists represent a wide range of cutting-edge science and engineering — from climate science to cancer research — that can have a profound impact on people and communities.”

Argonne has won 145 R&D 100 Awards since the competition began in 1963. Past winners also include Fortune 500 companies, other DOE national laboratories, academic institutions and smaller companies.

Argonne’s winning projects/technologies this year are:

CANDLE (CANcer Distributed Learning Environment) (Principal Investigator: Rick Stevens)

CANDLE is an artificial intelligence-based computer code that brings together machine learning, deep learning and cancer research to accelerate the discovery of new cancer therapies and treatments. This unique and powerful platform aims to solve three major challenges in cancer. First, it analyzes protein behaviors in tumor cells. Second, it looks at the relationship between tumors and drugs. Third, it can analyze biomedical records to extract new patterns and information. CANDLE was also used to research potential treatments for SARS-CoV-2.

In addition, scientists are using CANDLE codes to check the performance of the most advanced DOE computing systems, including Argonne’s upcoming Aurora exascale supercomputer.

CANDLE is designed in partnership with DOE and the National Cancer Institute.

This research was supported by the Exascale Computing Project, a collaborative effort of DOE’s Office of Science and the National Nuclear Security Administration.

Cardinal: Scalable High-Order Multi-Physics Simulation (Principal Investigator: April Novak)

Scientists and engineers rely on simulation to predict the behavior of nuclear reactors under a variety of design conditions. Often, experiments are too expensive to carry out or are incompatible with fast-turnaround design cycles. Science modeling and simulation is particularly important to the advancement of novel nuclear reactor designs and can enable critical insight for making better design decisions to increase efficiency and safety.

Cardinal is an open-source simulation software package that delivers highly accurate solutions for a wide range of applications in nuclear energy sciences. Cardinal features state-of-the-art, scalable algorithms for achieving multiphysics solutions with neutron transport, fluid flow, heat transfer and material behavior on platforms ranging from laptops to extreme-scale computers. The physical phenomena that can be simulated with Cardinal range from neutron interactions with matter on the atomic scale to the whole-system response of nuclear reactors coupled to electric grids on the kilometer scale.

Funding for Cardinal was provided by DOE’s Office of Nuclear Energy.

Climate Risk and Resilience Portal (ClimRR) (Principal Investigator: Carmella Burdi)

ClimRR is a free, web-based tool that gives emergency managers and community leaders access to localized data about future climate conditions and hazards. Climate projections and visualization at the neighborhood-level scale create opportunities for local decision makers to take informed action. This information is increasingly of interest to decision makers as the impacts of climate change become more frequent and intense.

Argonne developed ClimRR in a unique partnership with AT&T and the Federal Emergency Management Agency. To create ClimRR, Argonne first used the power of the Argonne Leadership Computing Facility, a DOE Office of Science user facility, to dynamically downscale data from three different global climate models, and then used that dataset as the basis for rendering more than 100 unique visualizations of climate impact variables over three different timeframes and according to two greenhouse gas emission scenarios. The data in ClimRR can be combined with data from the Resilience Analysis and Planning Tool to help users understand local-scale climate risks in the context of existing community demographics and infrastructure. For example, users can include locations of vulnerable populations and critical infrastructure.

ClimRR can be used to plan for and reduce heat emergency deaths or target assistance among those communities that are most vulnerable. Communities can use the tool to protect family farms and the future food security of millions of people. Decision makers can use ClimRR to help make infrastructure more resilient against increasingly extreme conditions. Also, decision makers can use the tool to help vulnerable local seasonal economies plan for change, and preserve the cultures, resources and lifeways of indigenous peoples.

AT&T originally commissioned Argonne’s Center for Climate Resilience and Decision Science to produce the climate projections in ClimRR for the company’s own adaptation efforts, but then sought to make that data publicly available.

In addition, another Argonne project/technology was named a finalist this year:

ActivO: A Machine Learning Driven Active Optimizer for Rapid Product Design Optimization (Principal Investigator: Pinaki Pal)

ActivO is an innovative software technology developed at Argonne that provides a unique turnkey solution to speed up product design optimization and massively accelerate virtual prototyping across a wide range of industries. Imagine designing a car engine or a wind turbine. You want it to work well and use less energy, but figuring out the best design can take a lot of time and money because of having to test many ideas and prototypes.

The secret to how ActivO accelerates the design process is a one-of-its-kind combination of: advanced ensemble machine learning (ML)-driven predictive surrogate models trained on simulation data; adaptive sampling of the design space via active learning for on-the-fly refinements of the ML surrogate models; and efficient algorithms for controlling the relative degree of local (exploitation) versus global (exploration) search of the design space during optimization — all within an automated, modular and scalable workflow. ActivO can be readily coupled with any simulation tool. It can also efficiently run on high performance computing clusters/supercomputers and cloud-based platforms, owing to its highly parallelizable and portable framework. The compact and end-to-end nature of ActivO enables easy adoption by engineers in industry, even those who do not have extensive ML expertise.

ActivO has wide applicability and ability to impact multiple industrial sectors, such as automotive, aerospace, chemical, iron and steel, oil and gas, carbon capture, and biomedical. Argonne has demonstrated the capability of ActivO to speed up design optimization of automotive engines by an order of magnitude — from months to a few days — compared with other contemporary commercial software tools. Companies like Dow Chemical are already leveraging it to optimize their products. By way of drastically accelerating design optimization campaigns, ActivO can shrink industry design cycles/costs and time-to-market for advanced products.

ActivO was developed under a Technology Commercialization Fund project funded by the Decarbonization of Off-road, Rail, Marine and Aviation program of DOE’s Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office.

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The Argonne Leadership Computing Facility provides supercomputing capabilities to the scientific and engineering community to advance fundamental discovery and understanding in a broad range of disciplines. Supported by the U.S. Department of Energy’s (DOE’s) Office of Science, Advanced Scientific Computing Research (ASCR) program, the ALCF is one of two DOE Leadership Computing Facilities in the nation dedicated to open science.

Argonne National Laboratory seeks solutions to pressing national problems in science and technology. The nation's first national laboratory, Argonne conducts leading-edge basic and applied scientific research in virtually every scientific discipline. Argonne researchers work closely with researchers from hundreds of companies, universities, and federal, state and municipal agencies to help them solve their specific problems, advance America's scientific leadership and prepare the nation for a better future. With employees from more than 60 nations, Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy's Office of Science.

The U.S. Department of Energy's Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time. For more information, visit https://energy.gov/science