Funding Opportunity from U.S. Department of Energy's High Performance Computing for Energy Innovation (HPC4EI) Program

The U.S. Department of Energy's (DOE) High Performance Computing for Energy Innovation (HPC4EI) Program will issue its third joint solicitation in November 2019, covering the High Performance Computing for Manufacturing (HPC4Mfg) and High Performance Computing for Materials (HPC4Mtls) programs. This joint solicitation will mark the ninth solicitation for the HPC4Mfg Program and the fourth for the HPC4Mtls Program. The HPC4Mfg and HPC4Mtls programs are funded with support from the Office of Energy Efficiency and Renewable Energy’s Advanced Manufacturing Office and the Office of Fossil Energy. HPC4EI programs are designed to spur the use of national lab supercomputing resources and expertise to advance innovation in energy-efficient manufacturing and new materials that will enable advanced energy technologies.In this solicitation, we are seeking qualified industry partners to participate in short-term, collaborative projects with the DOE’s national laboratories. Selected industry

partners will be granted access to high performance computing (HPC) facilities and experienced staff at DOE’s national laboratories. The collaborations will address key challenges in U.S. manufacturing and material development by applying modeling, simulation, and data analysis to relevant problems with the intent to improve energy efficiency, increase productivity, reduce cycle time, enable next-generation technologies, test control system algorithms, investigate intensified processes, lower energy cost, and accelerate innovation. Projects must demonstrate potential impact to energy efficiency in manufacturing, material development, and mobility with a potential for broad national impact. We will solicit proposals that require HPC modeling and simulation to enable impactful manufacturing-process improvements and material-development resulting in reduced energy consumption and/or increased productivity. Eligibility for this program is limited to entities that manufacture products or operate systems in the United States for commercial applications and organizations that support them. Selected projects will be awarded up to $300,000 to support computing cycles and work performed by the national lab partners. All DOE national laboratories are eligible to participate. The industry partner must provide a participant contribution of at least 20% of the total project funding. Project durations are for one year. The HPC4EI Program anticipates making multiple awards, subject to the availability of funding, for the HPC4Mfg and HPC4Mtls programs.More information about the HPC4EI Program can be found at: https://hpc4energyinnovation.llnl.gov/Topics of interest specific to the offices supporting this solicitation are below.DOE’s Advanced Manufacturing Office (AMO) within Office of Energy Efficiency and Renewable Energy is the primary sponsor of the HPC4Mfg Program. FE and EERE’s VTO and Building Technologies Office (BTO) also sponsor select projects in this portfolio. AMO partners with private and public stakeholders to support the research, development, and deployment of innovative technologies that can improve U.S. competitiveness, save energy, and ensure global leadership in advanced manufacturing. AMO supports cost‐shared research, development, and demonstration activities in support of crosscutting next-generation technologies and processes that hold high potential to significantly improve energy efficiency and reduce energy-related emissions, industrial waste, and the life‐cycle energy consumption of manufactured products. Improved energy efficiency across the manufacturing industry is one of the primary goals of the HPC4Mfg Program. We solicit proposals that require HPC modeling and simulation to overcome impactful manufacturing process challenges resulting in reduced energy consumption and/or increased productivity. Proposals should provide a realistic assessment of the energy impact, the improvement in U.S. manufacturing competitiveness, and the increase in U.S. manufacturing jobs that a successful outcome of the project could have across the industrial sector.Of particular interest to AMO are: •        Improvements in manufacturing processes which result in significant national energy savings. Examples include: a.        Process improvements in high-energy consuming industries such as paper and pulp, primary metal manufacturing, glass and chemical industries b.        Improvements in additive manufacturing that will increase adoption •        Improvements in the lifecycle energy consumption of products of interest to AMO. Examples include:a.      Improvement in jet engine efficiency could save significant energy over the lifecycle of the engine  b.      Improved materials and shape optimization for lightweighting in transport technologiesc.     Semiconductor electrical efficiency •        Efficiency improvements in energy conversion and storage technologies. Examples include:a.      Improvements in combined heat and power units which save significant energyb.     Novel energy storage and energy conversion techniquesc.      Improvements in waste heat recoveryd.     Wide band-gap semiconductors  The HPC4Materials Program is sponsored by the DOE Office of Fossil Energy (FE) to enhance the U.S. materials-development, fabrication, and manufacturing industry to investigate, improve, and scale methods that will accelerate the development and deployment of materials that perform well in severe and complex energy application environments. This solicitation is aimed at demonstrating the benefit of HPC toward these goals within one year.  The program seeks proposals that will address key challenges in developing, modifying, and/or qualifying new or modified materials that perform well in severe and complex energy application environments through the use of HPC modeling, simulation, and data analysis. For each of the program offices supporting this solicitation, we provide a brief description of their mission and the topics of interest to them. The Office of Fossil Energy FE is the primary sponsor for this HPC4Mtls Program. FE plays a key role in helping the United States meet its continually growing need for secure, reasonably priced, and environmentally sound energy from our abundant fossil energy resources. The Office of Fossil Energy Research and Development (FER&D) Program advances transformative science and innovative technologies that enable the reliable, efficient, affordable, and environmentally sound use of fossil fuels. Fossil energy sources constitute over 80% of the country’s total energy use and are critical to the nation’s security, economic prosperity, and growth. It partners with industry, academia, and research facilities in transformative science and innovative technologies that enable the reliable, efficient, affordable, and environmentally sound use of fossil fuels. FE supports cost-shared research, development, and demonstration activities in support of  crosscutting next-generation technologies and processes that further the development of advanced fossil technologies. Proposals should provide a realistic assessment of the benefits to the domestic materials supply chain and/or fossil energy application (e.g. power plant).Of particular interest to FE in this solicitation are:•        Improving the understanding of detailed processes in critical focus areas such as oxidation, corrosion, and electrochemical interactions•        Use computational databases and machine learning for catalyst development to synthesis, test, characterize, and scale materials which convert carbon oxides into value-added products with increased energy efficiency, higher selectivity, and lower environmental impacts based on a lifecycle analysis relative to conventional products•        Developing machine learning capabilities to predict new materials for energy storage•        Developing the capability to predict the mechanical behavior and properties of additively manufactured components for use in advanced power cycles such as supercritical carbon dioxide cycles 1.     Materials Supply Chain for Fossil Energy Applications: •        Reducing the cost of ingot production for nickel superalloys suitable for fossil energy applications•        Improved high-temperature mechanical performance for lower-cost alloys as compared with more costly, high nickel/cobalt alloys•        Overcoming barriers to scale up new material production from grams to kilograms, and from kilograms to tonnes•        Overcoming barriers to the manufacture of components with High Entropy Alloys (HEA)•        Developing modeling and simulation tools that will reduce the time to qualification and certification of materials (e.g., American Society of Mechanical Engineers code materials), including but not limited to novel manufacturing processes such as chemical etching, diffusion bonding, and additive manufacturing•        Improve speed and quality of welding and other advanced joining methods for nickel superalloys•        Advanced manufacturing of components for fossil energy applications, particularly for repair of existing plant components and modular fabrication of new plants•        Machine learning within the supply chain to lower costs and improve productivity  2.     Existing and New Power Plant Applications•        Predicting material behavior in specific severe environments, such as high-temperature, cyclic, or oxidative/corrosive environments, found in fossil power plants•        Development of coatings, claddings, and other surface treatments to mitigate oxidation, corrosion, and erosion of high-temperature components•        AI applications for monitoring and diagnostics of power plants focused on materials failures such as calculating remaining useful life of components or pattern recognition•        Analysis of thermal fatigue-driven failures, particularly in coal-fired boilers and natural gas combined cycle heat recovery steam generators.•        Improve reliability of dissimilar welds between ferritic and stainless steels or nickel superalloys•        Overcoming barriers to the manufacture of components for fuel cells•        Developing machine learning capabilities to identify promising new materials for non-battery energy storage technologies that can integrate with fossil energy power generating units