NETL’s Computational Science and Engineering (CSE) directorate underpins much of the Lab’s research by generating information and analysis beyond the reach of physical experiments alone. CSE develops science-based simulation models, mathematical methods and algorithms and software tools required to address the technical barriers that often hinder development of next-generation fossil energy technologies. Through the integration of experimental information and computational sciences, scientists and engineers can efficiently simulate multitudes of technology variations to save time, money and materials. CSE work enabled advancements in several areas of NETL research in 2019, including significant achievements in multiphase flow science and carbon capture technology development.

NETL has issued a Notice of Intent (NOI) for a funding opportunity announcement (FOA) for cooperative agreements to competitively solicit and award projects that will focus on materials research, development, testing and validation to enhance the domestic materials supply chain and the reliability of the existing fossil power generation fleet.  Notice of Intent for DE-FOA-0002192, Extreme Environment Materials for Power Generation, will support DOE’s Crosscutting Research Program. It is anticipated that projects will fall under two areas of interest (AOIs). AOI 1: Addressing Fatigue Failures at Dissimilar Metal Joints in High-Temperature Steam-Cycle Components This AOI will focus on development of innovative materials or materials processing technologies that improve the cyclic durability of joined materials and components, reduce the time and cost associated with repairing and upgrading components and address barriers to deployment of mature joining technologies through demonstrating and documenting their value in a realistic environment.

NETL announced today up to $4.5 million in federal funding for cost-shared research and development (R&D) projects for fossil power plants. The projects fall under an amendment to funding opportunity announcement (FOA) DE-FOA-0002001.000001, Crosscutting Research for Coal-Fueled Power Plants. This amended FOA aims to develop advanced dry cooling technologies suitable for fossil power plants. Dry cooling is used to cool and condense steam in a thermoelectric power plant; however, costs and performance, particularly under hot conditions, remain a challenge. DOE will support projects that bring down costs and increase performance of dry cooling so it can be widely used and reduce water demand associated with power generation. While this FOA requires cooling technologies to be applicable to coal power plants, it is anticipated that most will also be applicable to natural gas-fired power plants as well.

NETL’s K-12 STEM Education & Outreach team members facilitated active learning experiences at several elementary schools throughout September and October, fostering the next generation of energy experts through engaging activities involving science, technology, engineering and math (STEM) subjects. Additionally, ambassadors from the Lab’s STEM Ambassador program provided information about careers in energy to spread the Lab’s mission to secure and enhance the nation’s energy foundation while protecting the environment. The Education & Outreach team brings exciting “hands-on, minds-on” programs to students located near NETL’s three sites in Morgantown, West Virginia; Pittsburgh, Pennsylvania; and Albany, Oregon. The program seeks to stimulate students’ and teachers’ interest in STEM and deliver important STEM content, as well as enhance children’s critical thinking skills and provide options for older students seeking careers in STEM.

An NETL review of corrosion sensing technology demonstrates the powerful potential of emerging applications to provide continuous real-time, in-situ monitoring of oil and natural gas infrastructure. This capability empowers industry to prevent pipeline leaks and failures, boosting infrastructure resilience and safety while mitigating unnecessary expenses that are often passed on to consumers via energy bills. The United States is home to roughly 400,000 miles of oil and natural gas pipelines, which transport vital fuels across the country to meet energy demands. Every inch is susceptible to corrosion, the natural deterioration of metal materials caused by chemical or electrochemical reactions with the environment. Corrosion leads to structural damage that costs billions of dollars each year; however, it’s challenging to detect during routine maintenance and inspections, and current state-of-the-art solutions typically involve periodic inspections rather than real-time monitoring. 

A new NETL study identified strong opportunities for global export of high-performance materials that are used in power plants and the aerospace industry – exports that could mean increased demand for U.S. goods and services and positive impacts for the U.S. economy. The report, “Assessing the Export Potential for High-Performance Materials,” examined the export potential and economic impacts resulting from both the primary and potential secondary applications of NETL high-performance materials (HPM) research. The research specifically assessed the potential international demand for HPMs in advanced ultra-supercritical (AUSC) and natural gas combined cycle (NGCC) power plants, as well as the aerospace sector. The study estimated the potential economic impacts within the U.S. associated with estimated HPM exports in each market.

An NETL-sponsored project is leveraging artificial intelligence in a manner that will lead to more efficient, long-lasting and reliable gas turbines to meet America’s growing energy needs. As advanced energy systems move toward higher temperatures to boost efficiency and reduce emissions, monitoring their performance under such harsh conditions becomes a challenge. Existing monitoring tools for gas turbines are costly, time-consuming and complicated, involving wires and risks for damage. With funding and guidance from NETL, North Carolina-based Siemens Corp. and its partners are developing smart sensor systems that provide real-time monitoring of gas turbine components, thereby enabling condition-based maintenance and prediction of each component’s remaining useful life.

NETL Director Brian Anderson, Ph.D., and other Lab personnel will exchange information and ideas with industry, universities, investors and end-use customers at the U.S. Department of Energy’s (DOE) InnovationXLab Artificial Intelligence (AI) Summit Oct. 2-3, at the historic Drake Hotel in Chicago. The AI Summit, hosted by Argonne National Laboratory, will convene industry leaders from the energy, transportation, manufacturing and health care sectors, public officials and researchers from DOE national laboratories to discuss how advanced AI tools and machine learning (ML) techniques can support business transformation and drive economic growth. The continued leadership of the United States in AI is of paramount importance to maintain economic and national security, and events such as the InnovationXLab AI Summit are highlighting how business and industry can leverage the power of DOE’s national laboratories and AI to enrich the lives of Americans.

The U.S. Department of Energy’s Office of Fossil Energy and NETL have selected four projects to receive approximately $4.6 million in federal funding for cost-shared research and development (R&D). The projects will accelerate the development and commercialization of treatment technologies that reduce waste water that is being injected into disposal wells and increase water supplies for reuse. These projects are supported through funding opportunity announcement (FOA) DE-FOA-0002004, Low-Cost, Efficient Treatment Technologies for Produced Water. This R&D effort supports the Water Security Grand Challenge, a White House-initiated, DOE-led framework to advance transformational technology and innovation to meet the global need for safe, secure, and affordable water. In particular, this FOA advances the Grand Challenge’s goal to transform the energy sector’s produced water from a waste to a resource.  

With the newest release of NETL’s carbonaceous chemistry for computational modeling, or C3M, software, researchers have leveraged machine learning approaches to overcome one of the biggest drains to computational resources when modeling advanced energy systems. Version 19.1 of C3M introduces the Machine Learning Accelerated Stabilized Explicit Variable Load (MLA-STEV) software that solves complex chemical reaction equations much faster than previous iterations, drastically shortening design time and significantly reducing research and development costs.“The MLA-STEV solver could be used to help accelerate the design of cleaner and more efficient energy systems like gasifiers,” said Dirk VanEssendelft, Ph.D., referring to an energy technology that converts organic material such a coal into useful fuels and chemicals.