An NETL collaboration with Cerebras Systems has demonstrated that their acclaimed CS-1 system could perform a key computational fluid dynamics (CFD) workload more than 200 times faster and at a fraction of the power consumption than the same workload on an optimized number of cores of the Lab’s supercomputer JOULE 2.0. Further development of this unique computational architecture could lead to a paradigm shift in NETL’s high-performance computing (HPC) efforts and help overcome challenges facing researchers as they design and model next-generation energy systems. The research was led by Dirk Van Essendelft, Ph.D., machine learning and data science engineer at NETL, and Michael James, Cerebras chief architect of advanced technologies and a cofounder of the company.

According to the latest rankings by TOP500, NETL’s Joule 2.0 supercomputer remains among the most powerful in the world, securing a position of 11th among DOE national labs, 26th in the United States and 82nd in the world. Supercomputing is essential in achieving NETL’s mission to discover, integrate and mature technology solutions that enhance the nation’s energy foundation and protect the environment for future generations. By expediting technology development through computational science and engineering, Joule 2.0 helps NETL cut costs, save time and spur valuable economic investments with a global impact. Named for the familiar unit of energy, Joule allows researchers to model energy technologies, simulate challenging phenomena and solve complex calculations using computational tools that save time and money to ensure that technology development ultimately proves successful. A $16.5 million upgrade in 2019 boosted Joule’s computational power to 5.767 PFLOPS, meaning that it can perform more than 5 quadrillion calculations per second. That’s equivalent to roughly 54,658 desktop computers combined.

The U.S. Department of Energy’s (DOE) Office of Fossil Energy (FE) issued a Notice of Intent for a Funding Opportunity Announcement (FOA) expected to support projects facilitating the design, construction, and operation of engineering-scale prototypes of water treatment technologies for the Nation’s existing and future fleet of thermoelectric power plants. Water is a fixed resource with competing demands. There is an inextricable link between water and energy, as thermoelectric power generation accounts for 40 percent of freshwater withdrawals and 3 percent of freshwater consumption in the United States. Identifying and treating alternative sources of water, such as effluent streams, supports DOE’s Water Security Grand Challenge Goal 3: “Achieve near-zero water impact for new thermoelectric power plants, and significantly lower freshwater use intensity within the existing fleet.”

The U.S. Department of Energy’s (DOE) Office of Fossil Energy (FE) and NETL invites public comment about the technical issues needed 1) to make treated and untreated produced water available for non-oilfield and oilfield use and 2) to reduce the volume of oilfield flowback and produced water disposed of in salt water disposal wells within the Permian Basin, by promoting its beneficial use in the oilfield or its use within other industries. The goal is to transform the produced water from a waste to a resource. Through a potential prize competition, DOE would seek demonstrations of higher technology readiness level (TRL) technologies that treat produced water for use within other industries or demand centers outside oil and natural gas operations.

A new, open-source computer model to quantify baseline life cycle impacts of electricity consumption in the United States is allowing for more robust and consistent analyses to inform decision makers and stakeholders. Developed through a collaboration among NETL, the U.S. Environmental Protection Agency, and the National Renewable Energy Laboratory, the model is transparent and multifunctional for users. The electricity and power generation sector in the U.S. is experiencing a state of rapid transformation via adoption of natural gas-fired power plants and deeper penetration of renewables into the market as older power-generation systems such as nuclear and legacy coal plants are gradually phased out.

The final week of the 2020 Virtual Integrated Project Review Meeting, hosted by the U.S. Department of Energy (DOE) and NETL, will explore the accomplishments and upcoming work to be undertaken by two NETL-led programs — the National Risk Assessment Partnership (NRAP) and the Science-informed Machine Learning for Accelerating Real-Time Decisions in Subsurface Applications (SMART) Initiative.  A full slate of presentations and updates on the SMART Initiative will be held Monday, Nov. 2, and Tuesday, Nov. 3. Click here to review the SMART Initiative Annual Review Meeting agenda and to obtain online registration and WebEx instructions. The NRAP Technical Meeting, scheduled for Wednesday, Nov. 4, and Thursday, Nov. 5, will feature an array of speakers who will discuss the development of tools and approaches for effective risk management of carbon storage sites. Click here to review the agenda for the NRAP sessions and to obtain online registration and WebEx instructions. Registration is free for all SMART Initiative and NRAP sessions.

A team of national laboratories, led by Lawrence Berkeley National Laboratory and Lawrence Livermore National Laboratory (LLNL) with support from the National Energy Technology Laboratory (NETL) and Stanford Linear Accelerator Laboratory, is collaborating in a multi-scale modeling project that resulted in an approach that significantly improves the prediction of hydraulic fracture propagation. The results and modeling approach from the multi-lab project titled “A New Framework for Microscopic to Reservoir-Scale Simulation of Hydraulic Fracturing and Production: Testing with Comprehensive Data from Hydraulic Fracturing Test Site (HFTS) and Other Hydraulic Fracturing Field Test Sites” have since been adopted by numerous oil and natural gas operators following the publication by the Society of Petroleum Engineers (SPE).

A team of national laboratories, led by Lawrence Berkeley National Laboratory and Lawrence Livermore National Laboratory (LLNL) with support from the National Energy Technology Laboratory (NETL) and Stanford Linear Accelerator Laboratory, is collaborating in a multi-scale modeling project that resulted in an approach that significantly improves the prediction of hydraulic fracture propagation. The results and modeling approach from the multi-lab project titled “A New Framework for Microscopic to Reservoir-Scale Simulation of Hydraulic Fracturing and Production: Testing with Comprehensive Data from Hydraulic Fracturing Test Site (HFTS) and Other Hydraulic Fracturing Field Test Sites” have since been adopted by numerous oil and natural gas operators following the publication by the Society of Petroleum Engineers (SPE).

NETL researchers such as Dominic Alfonso are using advanced computational tools to repurpose carbon dioxide (CO2) from a waste product into chemical building blocks to manufacture fuels and a range of high-value items. The work undertaken by Alfonso and other members of NETL’s Computational Materials and Engineering Team focuses on recycling CO2 generated by fossil energy plants and other industrial sources into chemicals, alcohols, acids and syngas, which are used to manufacture fuels, polymers and fertilizer. “For more than a century, we have used fossil fuels to produce our electricity and for a variety of other purposes. However, when we extract energy from fossil fuels, we create CO2, the primary greenhouse gas emitted through human activities,” Alfonso said. “We can address this issue by using CO2 from factories and power plants as a chemical feedstock. Waste CO2 emissions can become something you can recycle into valuable products, providing a strong financial incentive to reduce the amount of CO2 released into the atmosphere,” he added.

Since joining NETL last year, computer scientist MiKyung Kang, Ph.D., has supported the Lab’s high-performance computing (HPC) environment across all three of its research facilities, empowering the Lab to continue finding new ways to fuel the nation using the abundant supply of fossil fuels in a sustainable manner. Kang grew up on South Korea’s Jeju Island, one of the world’s New 7 Wonders of Nature and well known for its beautiful sand beaches and volcanic landscape of craters and cave-like lava tubes. She earned her B.S., M.S., and Ph.D. in computer science and statistics from Jeju National University, inspired by the rapid changes in technology she saw growing up. New Tech, New Possibilities