NETL has named Kelly Rose, Ph.D., to serve as interim technical director for the Lab’s Science-Based Artificial Intelligence and Machine Learning Institute (SAMI), a joint institute led by NETL for advancing cutting-edge AI and ML computational technologies to drive innovative solutions for effective, environmentally sustainable fossil energy resource recovery and utilization. Established in 2020, SAMI builds off NETL’s unique strengths in science-based modeling and research data curation and management capabilities. It also capitalizes on NETL’s world-class capabilities in high-performance and other scientific computing capabilities to address fossil energy research in areas such as improving the performance, reliability and efficiency of the existing coal-fired fleet; beneficiating carbon ore and fossil energy byproducts; driving break throughs in advanced materials design and discovery; optimizing the recovery of oil and gas resources; and reducing the cost and risk of carbon capture utilization and storage.

The eXtremeMAT team will provide a webinar presentation Thursday, Jan. 21 to American Society of Mechanical Engineers (ASME) committee members, providing information and feedback including how eXtremeMAT’s work may impact ASME standards in the future.  The presentation, “Accelerating the Development of Extreme Environment Materials,” will summarize the team’s recent advances to develop physics-based models to predict long-term alloy performance in harsh service conditions and to detail a strategy proposed by eXtremeMAT for using these models to accelerate the qualification of alloys. Initiated in 2018, the eXtremeMAT consortium, led by NETL with support from the U.S. Department of Energy (DOE) and its Office of Fossil Energy, leverages the unparalleled materials science and engineering expertise and capabilities available within the DOE national laboratory complex to accelerate development of affordable and durable materials for extreme environment service. eXtremeMAT aims to develop, validate and integrate advanced models to predict how microstructure and composition of certain steels affect alloys designed for harsh service environments.

The U.S. Department of Energy (DOE) selected 29 projects to receive nearly $7.6 million in federal funding for cost-shared research and development. The projects will advance energy storage technologies under the Funding Opportunity Announcement (FOA) DE-FOA-0002332, Energy Storage for Fossil Power Generation. Energy storage combined with fossil energy assets offers a suite of benefits to asset owners, the electric grid, and society. These benefits include more reliable and affordable energy, a cleaner environment, and stronger power infrastructure. These projects will accelerate the development of technology options to manage the energy transition underway to decarbonize and increase the flexibility of fossil power generation and support the grid of the future with increasing variable renewable generation.

NETL experts in systems engineering and analysis (SEA) are developing multi-scale approaches to modeling and analysis of technology, processes and markets. In 2020, through models and digital tools, reports and collaborations, the Lab’s SEA researchers made significant progress toward advancing technology solutions for our nation’s energy challenges.

NETL experts in systems engineering and analysis (SEA) are developing multi-scale approaches to modeling and analysis of technology, processes and markets. In 2020, through models and digital tools, reports and collaborations, the Lab’s SEA researchers made significant progress toward advancing technology solutions for our nation’s energy challenges.

Throughout 2020, NETL’s materials engineering and manufacturing research has demonstrated how historic energy resources can be used in remarkable new ways and how elements commonly thought of as a liability may present exciting new economic opportunities. Harnessing the Potential of Carbon Dioxide For example, carbon dioxide (CO2) may one day transition from a waste gas that contributes to climate change to a high-value feedstock used in the production of fuels, pharmaceuticals, plastics, fertilizers and a range of consumer goods. During the summer, NETL researchers made important strides in dry reforming, a process that reacts CO2 with methane, rather than steam or oxygen, to yield the mixture of hydrogen and carbon monoxide known as synthesis gas or syngas, a chemical building block for many products.

NETL recently released version 20.3 of its world-renowned Multiphase Flow with Interphase eXchanges (MFiX) software suite, which included an improved modeling capability that allows for more accurate descriptions of real particle-size distributions, offering an important new tool for designing next-generation energy systems to power the nation. The new feature was sponsored by NETL’s Crosscutting Research Simulation-Based Engineering program. “Our discrete element method (DEM) in MFiX received a significant enhancement with this update,” NETL’s Jeff Dietiker, Ph.D., said. “Fundamental testing in our Multiphase Flow Laboratory also demonstrates that fluidization and flow behavior, even in cold flow systems, can be greatly impacted by the feed-size distribution, so this new version will add great value to our modeling work, especially for modeling larger-scale, complex reactor systems of mixed feedstocks like coal, biomass and plastics, where high fidelity is critical.”

Innovative and reliable energy conversion systems are at the heart of America’s evolving energy infrastructure. They allow for the production of power, fuels and chemicals from both fossil fuels and renewable sources to provide the electricity that powers nearly every aspect of our daily lives. NETL’s role in advancing these systems ranges from designing novel experimental modeling tools to testing more efficient solutions to generating power and materials in ways that reduce environmental impact. In 2020, these advancements helped reduce time, cost and technical risk while enabling efficient operation to drive the energy systems of the future.

The U.S. Department of Energy’s (DOE) Office of Fossil Energy (FE) and the National Energy Technology Laboratory (NETL) have announced $3.3 million in Federal funding for cost-shared research and development projects under the Funding Opportunity Announcement (FOA) DE-FOA-0002399, Water Management for Thermal Power Generation. The FOA seeks to support 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. It is envisioned that fossil asset owners or operators and technology developers will collaborate and advance near-term water treatment solutions that can be commercially deployed.

Artificial intelligence (AI) refers to algorithms that can — for a given set of human-defined objectives — learn, predict and make decisions, significantly increasing the speed and efficacy of decision-making. Most AI applications use machine learning (ML) to find patterns in massive amounts of data. The patterns are then used for making predictions. AI and ML have factored prominently in the Lab’s computational science and engineering (CSE) work in 2020 through the development of science-based simulation models, mathematical methods and algorithms and software tools required to address the technical barriers to the development of next-generation technologies. This research helps to generate information and understanding beyond the reach of experiments alone, saving time, money and materials.