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The Elastic Analysis Facility's (EAF's) Contribution to the Future of Analysis at Multi-Experiment Institutions and Future Colliders

The Elastic Analysis Facility (EAF) hosted at Fermi National Accelerator Laboratory (Fermilab) is a platform being developed with the goal of providing a fast and efficient facility for physics analysis. As high-energy physics moves towards collecting larger datasets, such as those from the High-Luminosity LHC, the EAF strives to provide a powerful and adaptable framework for future colliders and multi-experiment institutions. Currently, the EAF supports several experiments including CMS, NOvA, and DUNE as well as serving accelerator physicists and beam line operations through integrated software and secure connections to Fermilab's computing resources. In addition, the EAF was designed with a user-friendly interface, intended to be more intuitive for emerging generations of physicists, that is still accessible for established styles of analysis. The EAF can also achieve better analysis efficiency due to the modernization of software and tools that can better utilize Fermilab's computing power. Furthermore, its design incorporates industry standards whenever possible, enhancing its sustainability and making it a possible template for other national or international laboratories and research facilities. Overall, the EAF is a forward-looking solution that will meet the evolving needs of particle physics, ensuring readiness for future colliders and multi-experiment research institutions.

Chavez, Elise [Wisconsin U., Madison]

In situ high-temperature Raman spectroscopy for online EAF slag analysis

Real-time monitoring of slag chemistry is critical for optimizing Electric Arc Furnace (EAF) steelmaking operations, where dynamic variations in slag composition directly influence slag foaming, refractory degradation, and thermal efficiency. Conventional techniques such as X-ray fluorescence (XRF), Fourier-transform infrared (FTIR), and scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM-EDS) are commonly used to analyze slag composition, but their offline nature and equipment constraints limit their applicability for online monitoring in harsh industrial environments. To address this challenge, we present an in situ, high-temperature analytical approach that integrates Raman spectroscopy with a custom designed fiber-optic probe for real-time slag characterization at 1550 °C. The system enables non destructive spectral acquisition from molten slags, providing molecular-level insights into silicate polymerization and iron oxidation states. Eight synthetic slag samples were evaluated, and key Raman features—such as Q n silicate units and FeO₄/FeO₆ coordination environments—were identified and quantitatively correlated with slag basicity and Fe₂O₃ content. The results demonstrate agreement between Raman spectral ratios and bulk slag chemistry, validating the method’s capability to track compositional and structural changes under molten temperature. This work establishes the feasibility of deploying fiber-optic Raman probe for online EAF slag monitoring and highlights their potential to support closed-loop control strategies, thereby enhancing process stability, refractory protection, and steel quality in industrial steelmaking applications.

47 OTHER INSTRUMENTATION

Optimization of Scrap Melting Using an Electric Arc in Steel Manufacturing

Steel industry is crucial to the national economy and security. Around 67% of crude steel in the U.S is produced in electric arc furnaces (EAF), which is energy intensive. Around 140 EAFs operate in the U.S., consuming about 8.6x10 7 MMBtu/year of electricity. One of major challenges for EAFs includes maximizing the efficiency of the electrical energy provided in the form of electric arcs to melt various scrap mixes. To address this issue, a computational fluid dynamics (CFD) methodology is chosen to analyze scrap melting using the electric arc. Due to complex furnace phenomena and the wide variety of potential scenarios, high performance computing (HPC) is essential to yield comprehensive and detailed CFD analyses and systematic parametric studies for optimized EAF operation. The objectives are to 1) simulate scrap melting using electric arc, 2) evaluate electrode/arc position for optimum scrap melting and 3) establish reduced order model for CFD data-base for fast model calculation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Advancing Temperature Monitoring of the Bottom Anode in a Direct Current Electric Arc Furnace Operations with Distributed Optical Fiber Sensors.

The bottom anode in the Direct Current Electric Arc Furnace (DC EAF) is critical for completing the electrical circuit necessary for sustaining the arc within the furnace. For pin-type bottom anodes, monitoring of the temperature of select pins instrumented with thermocouples is performed to track bottom wear in the EAF and inform the operator when the furnace should be removed from service. Furthermore, this work presents the results from a plant trial using distributed temperature monitoring of bottom anode pins in a 165-ton DC EAF over a two-month service period utilizing two optical fiber sensing techniques: fiber Bragg grating (FBG) and Rayleigh backscattering (RBS). The early detection of temperature anomalies along the length of the anode pin through distributed sensing enhances operational safety, providing a robust alternative to traditional thermocouples.

42 ENGINEERING

Dynamic Heat Flow and Current Distribution Analysis in the Bottom Anode of an Electric Arc Furnace Using Fiber-Optic Sensors

A reliable method for monitoring bottom anode wear during DC Electric Arc Furnace (DC-EAF) operation is of critical importance for safe and efficient steel production. Underestimation of bottom wear poses a serious safety risk that must be avoided, while overestimation of bottom wear also poses challenges, as premature anode replacement is expensive and affects EAF productivity. Previously, we demonstrated that fiber-optic sensors can be successfully deployed to create a spatially distributed temperature map to monitor the health of the anode. The present work explores the heat flow and current density distribution in bottom anode pins to predict bottom wear, steel penetration events, and monitor refractory erosion. Small dynamic variations in pin temperature induced by joule heating during arcing also provide a means to observe local current flows in each pin. When mapped, these measurements provide a real-time view of the non-uniform and dynamic current flow in the bottom anode during EAF operation that can affect bottom wear.

Bottom Anode

Environmentally Assisted Fatigue in Light Water Reactor Environment

This report summarizes the Environmentally Assisted Fatigue (EAF) research conducted at ANL under the US DOE Light Water Reactor Sustainability (LWRS) program. Starting from a rich background in theoretical and experimental EAF, ANL previously developed an approach to evaluate fatigue performance of reactor materials in light water reactor environments with the correction factor F en . The approach was based on a large body of experimental work performed at ANL and elsewhere, and was consistent with American Society of Mechanical Engineers (ASME)’s methodology governing the design and construction of reactor components. In recent years, the program was focused on component fatigue prediction and made several major and fundamental contributions in this area. These accomplishments help meet the needs identified by the industry concerning component level fatigue predictions in complex, transient conditions. The main contribution of the ANL program involved the development of a system-level model for estimating residual strain and life of nuclear reactor coolant system components under connected-system-thermal-mechanical boundary conditions. The goal was to predict the stress hotspots, strain residuals, strain amplitudes and the resulting fatigue lives. Thermal-mechanical stress analysis was performed considering thermal stratification and a design-basis reactor loading cycle. Based on the finite element (FE) model results, the strain residuals, strain amplitudes and resulting fatigue lives of reactor coolant system (RCS) components were predicted. The results show that some of the RCS components can have significantly different strain amplitudes, residual strain, and fatigue lives, despite having similar geometry and material. In addition, the simulated component-level strain profile can guide the selection of appropriate test inputs for conducting laboratory-scale EAF tests. Building upon the system-level model, ANL developed a digital twin (DT) framework to predict the structural states and associated fatigue life of components in real-time. This framework is a comprehensive system designed to predict the structural states and fatigue lives of reactor components. It includes multiple models and integrates artificial intelligence (AI), machine learning (ML), and FE based modeling tools to evaluate the structural states and fatigue lives.

22 GENERAL STUDIES OF NUCLEAR REACTORS

Energy Requirements for Integration of Nuclear Reactors with Iron and Steel Plants

This report identifies energy needs of heavy energy users within the domestic iron and steel industry and suggests solutions for integrating nuclear energy. The iron and steel industry, composed of several types of plants which perform different processes with varied energy demands and vectors, is a heavy consumer of electric power and fossil fuels including coke and natural gas. Almost all major process temperatures exceed the temperatures of direct heat available from advanced reactors, and so electricity and hydrogen were considered instead. Reference units were adopted and estimated energy demands computed for the blast furnace (BF), direct reduced iron (DRI) unit, electric arc furnace (EAF), and reheat furnaces. By utilizing production capacity data from industry reports, the ranges of power demands were estimated, including for hydrogen production by high temperature steam electrolysis (HTSE). For the EAF and DRI unit, more detailed integration studies with thermodynamic modeling were also conducted and determined a possible solution with a specific reactor design and number of modules. Furthermore, because many unit processes are co-located, entire plants were considered by adding the energy demands of the unit processes to form four hypothetical reference plants. The range of power needs for the reference plants is compatible with multi-unit banks of microreactors at the low end, and would create a need for multiple larger-capacity SMRs at the high end (1 GWe plus 0.14 GWt). Although the overall power need at the high end is well-matched with one present-day large reactor offering (1.1 GWe), redundancy considerations may require a minimum of two reactors, potentially eliminating the single large reactor from consideration. Auxiliary or house loads would increase the reference plant estimates. Finally, the report provides total estimated energy needs under integration of all U.S. units of each process (BF, DRI, EAF, and reheat furnaces), representing a national potential for nuclear energy in the industry. U.S. iron and steel plants may be candidates for integration with nuclear reactors via electricity and hydrogen, and many sites have energy requirements that correspond well to the capacities of several advanced nuclear power designs.

22 GENERAL STUDIES OF NUCLEAR REACTORS

The Melting Behavior of Hydrogen Direct Reduced Iron in Molten Steel and Slag: An Integrated Computational and Experimental Study

Direct reduced iron (DRI) and hot briquetted iron (HBI) are essential feedstocks for tramp element control in the electric arc furnace (EAF). Due to greenhouse gas (GHG) concerns related to CO2 emissions, hydrogen as a substitute for natural gas and a reductant in DRI production is being widely explored to reduce GHG emissions in ironmaking. This study examines the melting behavior of hydrogen DRI (H-DRI) pellets in the EAF containing low-carbon (0.1 wt.%) molten steel and molten slag. A computational heat transfer model was developed to predict the melting behavior of H-DRI pellets. To validate the model, a set of experimental laboratory simulations was conducted by immersing H-DRI in a molten steel bath and slag. The temperature history at the center of the pellet during melting and the shell thickness at different melting stages were utilized to validate the model. The simulation results agree with the experimental measurements of steel balls and H-DRI in different metallic molten steel and slag baths.

Materials Science

Computational Methods for Multi-Physics Simulation of Melting in Steelmaking

Iron and steel production accounts for approximately 8% of global carbon dioxide (CO) emissions. Pathways to decarbonize include replacing fossil fuels in iron ore reduction and electrifying other steelmaking processes. Iron pellets produced by hydrogen, called Hydrogen Direct Reduced Iron (HDRI), have property differences from those produced using conventional DRI processes. These differences may impact melting in electric arc furnaces (EAF) and other downstream processes. The physical properties of iron pellets vary significantly with temperature during heating, complicating predictions of their behavior. In this project, we seek to develop an integrated simulation, including the fluid flow and convective thermal transport around the pellet particle. We also examine conduction and phase changes within the particle as they impact the melting process. We use adaptive mesh refinement (AMR) to resolve both the changing size of the particle and the complex physics of the interaction between the pellet and the surrounding fluid. We base our simulations on the AMReX-incflo module, which allows large-scale Navier-Stokes simulation while resolving the changing particle size during melting. As we advance our numerical tools, we anticipate an improved understanding of the dynamics of HDRI melting, which will, in turn, accelerate the adoption of low-carbon technologies in the steelmaking industry.

AMReX

Hybrid Grid-Renewable Strategies for Green Steel Production under Electricity Market Uncertainty

Volatility in grid spot prices is expected to rise with climate change-driven demand pressures and the intermittency of renewable generation. This volatility poses financial risks for green hydrogen-based steel production. The Direct Reduced Iron− Electric Arc Furnace (H 2 -DRI-EAF) is a promising pathway to decarbonize steel, which accounts for ∼8% of global GHG emissions. This study assesses how increased grid spot price volatility influences the optimal sizing and operation of H2-DRIEAF plants under three operational scenarios: grid-connected, fully behind-the-meter (islanded), and mixed-mode (semi-islanded). Our analysis identifies the semi-islanded configuration as the most cost-effective solution, achieving a Levelized Cost of Steel (LCOS) 10−35% lower than sourcing energy solely from the grid. Modeling also shows hydrogen storage or selective electricity purchases at high prices (>$1000/MWh) generally outperform battery storage, except under extreme volatility. Additionally, the study explores cost reduction strategies to strengthen the economic viability and sustainability of green steel production.

Batteries

Simulating regional workforce impacts of decarbonizing integrated steelmaking

Global efforts to mitigate climate change are increasing pressure on heavy manufacturing industries to decarbonize production. The iron and steel industry is responsible for 7% of CO 2 emissions globally (2% in the United States) and is often a major employer in the regions where iron and steel is produced. Understanding the future prospects for workers in regions with high CO 2 emitting industries—including impacts of phasing out or evolving such industries—will be critical for informing regional economic and clean energy strategies. We simulate the impact of an “in-place” transition that replaces today’s integrated production with direct reduced iron (DRI) used in electric arc furnaces (EAFs), using Southwest Pennsylvania as an application of our generalizable approach. Our results suggest that the integrated steelmaking workforce today has the skills, knowledge, and abilities (SKAs) to fill over 95% of all jobs required by DRI/EAF facilities, but the number of jobs is only 25% of those at integrated plants. We also find that some occupational groups have greater general transferability into the broader job market, while other groups, such as production workers, are ill-equipped today based on current SKAs to transition out of the iron and steel industry. Our methodology further suggests factors that limit transitions: Around 85% of occupations are more limited by missing skills, while 15% are more limited by insufficient wages. These results may help to improve the design of social policy and the targeting of retraining programs, while the simulation approach can be readily adapted for other regions and industries.

decarbonization

Carbon Capture from ArcelorMittal Hot Briquetted Iron Plant Using Air Liquide Cryocap™ FG Technology – FEED Study

The process of steel production is energy and carbon intensive with global average energy consumption of 5.5 MWh/tonne of steel and CO2 emission intensity of 1.83 tonne CO2/tonne of steel. The steel making process has inherent CO2 emissions from mineral conversion and is considered major contributors to the global carbon emissions. The steel industry is responsible for 8% of global carbon emissions. The main objective of this research project is to execute and complete a front-end engineering and design (FEED) study for a commercial-scale, carbon capture project that separates 95% of the total CO2 emissions at the ArcelorMittal’s Hot Briquetted Iron (HBI) plant in Portland, TX (Figure 1). The HBI is an ore-based metallic that is used as high-grade feedstock for high-quality steel via an Electric Arc Furnace (EAF) route. The HBI plant produces 2.0 million metric tonnes of high-quality HBI and emits approximately 1 million tonnes CO2/yr. The capture system is a Pressure Swing Adsorption (PSA) system assisted Cryocap™ FG technology (Figure 2). The captured CO2 will be pipeline grade and will be geologically stored in a facility within 10 miles of the CO2 source. The Host Site location in Corpus Christi, TX, is near hydrocarbon processing facilities and near Environmental Justice (EJ) and Qualified Opportunity Zone (QOZ) communities. Due to the location of the Host Site, the retrofit project offers the ability to demonstrate how a workforce focused on the fossil energy sector can be redirected to the clean- energy sector. The Air Liquide Cryocap™ capture technology is a proven technology and has been extensively examined for large industrial applications. It has been shown to be applicable to a variety of industrial applications including the steel industry. Cryocap™ FG (specific setup for Flue Gas application) consists of a Pressure Swing Adsorption (PSA) unit coupled with a Cryogenic System. The PSA pre-concentrates the CO2 from the flue gas, while the cryogenic unit enables the CO2 purity to be increased to the desired level. The scope of this study incorporates completing FEED study of the CO2 capture system which includes point-source CO2 capture and balance-of-plant; Business Case Analysis (BCA) outlining the current and projected volumes of the steel plant’s point sources of CO2 and the potential utilization of tax credits, including its projected revenue and duration; Life Cycle Analysis (LCA); Environmental Justice Analysis; Economic Revitalization and Job Creation Outcomes Analysis; and Workforce Readiness Plan. The plant design work was divided into two components: Inside Battery Limits (ISBL) and Outside Battery Limits (OSBL). The ISBL focuses on the capture system, while the OSBL focuses on the utility feeds and ducting from the plant to the capture system. Various design and engineering deliverables will be developed to define commodity quantities, equipment specifications, and labour effort required to execute the project. These FEED study deliverables will be prepared with the intent to develop an overall project capital cost estimate consistent with an AACE Class 3 estimate. The modular approach for the Cryocap™ FG that is being designed for this study integrates compression, PSA, and cryogenic “bricks” to achieve the desired CO2 capture rates. This carbon capture system integrates easily with the existing plant, thus reducing project costs and risks. It is also capable of managing impurities such as nitrogen oxides (NOx), sulfur oxides (SOx), mercury, hydrocarbons, and particulate matter. The capture system has a smaller footprint than amine-based systems. The two-step process uses PSA to preconcentrate the CO2 in the feedstream and then uses the cryogenic portion to purify and compress the resulting high purity CO2 product. This combination of purification and compression (i.e., process intensification) significantly reduces the CAPEX associated with use of a separate compressor commonly utilized for amine solvent-based systems. Successful completion of the FEED study will provide DOE with a detailed understanding of the costs for scaling up this proven capture technology for commercial applications at industrial facilities.

42 ENGINEERING

Nuclear Thermal Energy Storage Configurations for Industrial Combined Heat and Power Supply: Conceptual Study and Engineering Designs

The industries examined in this report primarily rely on moderate-temperature heat provided by gas- or coal-fired boilers and combined heat and power (CHP) plants, delivered through standard process steam systems. High-temperature energy demands are often industry-specific and typically exceed the capabilities of high-temperature gas-cooled reactors (HTGRs). While it is technically feasible to replace process steam from fossil-based heat sources with nuclear energy, certain industries, such as methanol production and pulp and paper, face technoeconomic challenges in integrating nuclear energy without major changes or a technological shift. This is mainly due to the limited external energy demand remaining after the use of internal byproducts, waste heat recovery, and simple efficiency improvements. Achieving full decarbonization of these processes with nuclear energy would require significant technological advancements, involving experimental technology and substantial investments, making widespread adoption in existing industrial plants unlikely in the near term. This study reviews TES options in the context of enabling a flexible CHP supply while maintaining a steady nuclear heat input. Heat storage systems that interface between the reactor primary fluid and the CHP system offer superior performance and flexibility. Specifically, steam extraction downstream of the reheater with a two-tank molten-salt TES appears as the best solution regarding thermodynamic system benefits and system drawbacks. Using selected system configurations, a conceptual design of an industrial energy park was developed for industries with varying energy demands, such as steel production plants utilizing electric arc furnaces (EAFs) and chemical plants, as well as for those with constant energy demands, like petroleum refineries. This design highlights the capabilities of TES and explores its potential business cases. The study also conceptually develops the potential for integrating additional energy sources with nuclear systems through the implementation of TES. The potential of the HTGR-TES-CHP system was also evaluated considering key uncertainties such as industrial demand profiles, external grid access availability, and eligible tax credit levels, using the Holistic Energy Resource Optimization Network. Sensitivity of net present value to these uncertainties was analyzed to determine the optimal number of nuclear reactors (and CHP systems) and the suitable TES capacity. The results were interpreted from a decision-maker’s perspective, focusing on three key areas: deployment strategy (oversized units vs. undersized units with TES support), industrial process characteristics (thermal-intensive single profiles vs. electricity-intensive combined profiles), and operational goals (maximizing profits vs. minimizing natural gas (NG) consumption or external grid dependence). The optimization results indicate that the HTGR-TES-CHP system significantly reduces reliance on NG boilers for individual industrial processes by 9-60% (in NG capacity factor), with an average reduction of 38%, compared to standalone NG boiler operation case (Business As Usual [BAU]). For combined industrial processes, the reduction ranges from 37-77%, with an average of 60%. Additionally, the system greatly reduces dependence on external grids. In meeting industrial electrical demands, a 33-100% self-sufficient internal electricity supply is achieved for single industrial process, with an average of 74%, compared to the BAU scenario, where 100% of electricity is imported. For combined processes, 35-100% of internal electricity demands are met by the reactor, with an average of 73%. At last, the relative NG price levels at which the proposed HTGR-TES-CHP system can cost-effectively enter the market currently dominated by existing NG boilers were estimated. For a moderate HTGR CAPEX level ($\$$2500/kWth, $\$$6329/kWe), the analysis suggests that NG prices must be 2.5 to 7 times higher than HTGR variable operating and maintenance costs for single industrial process, and 5.5 to 9.5 times higher for a combined process scenario. Tax credit modeling shows that the Investment Tax Credit significantly reduces the price threshold needed to break even, making the system competitive with NG boilers in certain cases.

22 GENERAL STUDIES OF NUCLEAR REACTORS

Grid-Interactive Steelmaking with Hydrogen (GISH)

"Grid-Interactive Steelmaking with Hydrogen (GISH)," aims to advance the use of hydrogen in steelmaking processes in a flexible manner with natural gas based on renewable energy availability to reduce carbon emissions in steelmaking. The project is a collaboration involving multiple partners and spans from October 1, 2020, to January 31, 2025, with the report dated May 25, 2025.

03 NATURAL GAS