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Director of ORNL’s AI Initiative Prasanna Balaprakash addresses attendees at the Generative AI for ORNL Science Workshop. Credit: ORNL, U.S. Dept. of Energy

The Department of Energy’s 91°µÍø hosted its Smoky Mountains Computational Science and Engineering Conference for the first time in person since the COVID pandemic broke in 2020. The conference, which celebrated its 20th consecutive year, took place at the Crowne Plaza Hotel in downtown Knoxville, Tenn., in late August.

Researchers used the open-source Community Earth System Model to simulate the effects that extreme climatic conditions have on processes like land carbon storage. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Researchers from 91°µÍø and Northeastern University modeled how extreme conditions in a changing climate affect the land’s ability to absorb atmospheric carbon — a key process for mitigating human-caused emissions. They found that 88% of Earth’s regions could become carbon emitters by the end of the 21st century. 

Steven Hamilton, an R&D scientist in the HPC Methods for Nuclear Applications group at ORNL, leads the ExaSMR project. ExaSMR was developed to run on the Oak Ridge Leadership Computing Facility’s exascale-class supercomputer, Frontier. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

The Exascale Small Modular Reactor effort, or ExaSMR, is a software stack developed over seven years under the Department of Energy’s Exascale Computing Project to produce the highest-resolution simulations of nuclear reactor systems to date. Now, ExaSMR has been nominated for a 2023 Gordon Bell Prize by the Association for Computing Machinery and is one of six finalists for the annual award, which honors outstanding achievements in high-performance computing from a variety of scientific domains.  

A rendering of the CFM RISE program’s open fan architecture. (bottom) A GE visualization of turbulent flow in the tip region of an open fan blade using the Frontier supercomputer at ORNL. Credit: CFM, GE Research (CFM is a 50­–50 joint company between GE and Safran Aircraft Engines)

Outside the high-performance computing, or HPC, community, exascale may seem more like fodder for science fiction than a powerful tool for scientific research. Yet, when seen through the lens of real-world applications, exascale computing goes from ethereal concept to tangible reality with exceptional benefits.

A new nanoscience study led by an ORNL quantum researcher takes a big-picture look at how scientists study materials at the smallest scales. Credit: Getty Images

A new nanoscience study led by a researcher at ORNL takes a big-picture look at how scientists study materials at the smallest scales.

Autonomous additive manufacturing, or AI- guided 3D printing, can accurately estimate the strength and quality of printed components. This system collects information about conditions during production, including temperature, that influence the properties and quality of printed objects. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Autonomous labs are changing the nature of scientific investigation. Instead of humans manually orchestrating every part of an experiment, programmed equipment can carry out necessary functions. This workflow accelerates the pace of discovery by reducing the number of monotonous tasks that researchers must perform.

ORNL’s Travis Humble, Quantum Science Center director, addresses students during a working lunch. Credit: Teresa Hurt/ORNL, U.S. Dept. of Energy

Quantum computing sits on the cutting edge of scientific discovery. Given its novelty, the next generation of researchers will contribute significantly to the advancement of the field. However, this new crop of scientists must first be cultivated.

Group of attendees at the Quantum Computing User Forum

Hosted by the Quantum Computing Institute and the Oak Ridge Leadership Computing Facility, the fourth annual event brought together over 100 attendees to discuss the latest developments in quantum computing and to learn about results from projects supported by the OLCF’s Quantum Computing User Program.

AIRES 4 attendees hailing from seven national laboratories and from academia met to discuss robust engineering for digital twins. Credit: Pradeep Ramuhalli/ORNL, U.S. Dept. of Energy

ORNL hosted its fourth Artificial Intelligence for Robust Engineering and Science, or AIRES, workshop from April 18-20. Over 100 attendees from government, academia and industry convened to identify research challenges and investment areas, carving the future of the discipline.

ORNL team members applied three independent strategies to decrease their project’s computational workload, which reduced their time to solution from months to a few weeks. First, in a technique called qubit tapering, they decreased the number of qubits required to express the problem, reducing the size of the problem itself. Second, they took fewer measurements to solve the problem by measuring groups of terms once rather than measuring each individual term from every group

Using the full capabilities of the Quantinuum H1-1 quantum computer, researchers from ORNL not only demonstrated best practices for scientific computing on current quantum systems but also produced an intriguing scientific result.