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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Inverse Calculation of Burden Distribution Matrix Using B-spline Model Based PDF control in Blast Furnace Burden Charging Process

The inverse calculation of burden distribution matrix (BDM) is one of the most important challenges in the blast furnace operation in iron-making processes. In general, blast furnace consumes 65% of the total energy for the whole steel-making. Focusing on this practical challenge, this article proposes a new burden distribution spatial model in calculating burden charging process, and develops a B-spline approximation-based probability density function (PDF) control algorithm to assign the expected thickness distribution of burden layer and, thus, develops a new method for the required inverse calculation of BDM. First, a novel method for the thickness distribution of burden layer is given using B-spline model to produce an expected distribution shape subjected to a desired tracking within a specific spatial constraint. Then, according to the coexistence of continuous and bounded discrete variables in BDM, a novel hybrid optimization control method by combining integer programming and PDF tracking is further established for the effective inverse calculation of BDM. Finally, the proposed PDF-based iterative inverse calculation of BDM using B-spline models are tested using various data from industrial examples. Furthermore, the simulation results show that the proposed method is well suited to solve the BDM inverse calculation problem in practice.

42 ENGINEERING↗
DOE OSTI2025

Thermocouples in Resistive and Induction Furnaces Operated in Strong Magnetic Fields

The thermomagnetic processing methods require an understanding of the in situ temperatures experienced by the workpieces. When commonly used thermocouples (TCs) are employed in induction furnaces, RF fields can contribute additional temperature uncertainties to the ones arising from the use of strong magnetic fields. Focusing on temperatures between 300 ° C and 1000 ° C produced by induction and resistive furnaces, the readings generated by Type-K TCs were contrasted to the ones produced by Type-S and Type-N sensors for magnetic fields up to 9 T. Overall, when comparing Type-K response to temperatures above 700 ° C in both zero field and high field ( ≤9 T), the differences amounted to less than 1% and when continuously measured has a linear relationship to the strength of the applied field. The relative invariance of Type-N and Type-S TCs was confirmed. In conclusion, these findings suggest that the use of TCs in high magnetic fields remains a viable option for applications, although the precision depends on the type used.

Tener, Zachary P. [Oak Ridge National Laboratory (↗
DOE OSTI2024

A compact furnace to support in situ neutron imaging of hydrogen dynamics in yttrium hydride moderators

A compact, nuclear microreactor that utilizes low-enriched uranium fuel is a promising solution to meet U.S. energy demands in nonconventional nuclear markets such as remote and decentralized energy grids. Yttrium hydride (YHx) is a potential moderator material for a microreactor design that reduces the amount of required fuel and provides superior retention of hydrogen at high reactor operating temperatures. Hydrogen diffusion properties in YHx are highly sought after for computer model validation and reactor prototyping. To characterize hydrogen diffusion, a compact dual-zone furnace was developed at Los Alamos National Laboratory and analyzed via neutron imaging at the Los Alamos Neutron Science Center (LANSCE). The goal of these measurements is to assess hydrogen diffusion in YHx samples as a function of applied temperature gradients. Included herein is recent progress in technique and furnace developments as well as initial results from concentration- and temperature-gradient measurements at LANSCE.

Torres, James↗
DOE OSTI2023

Medium Temperature Furnace Baking of Low-beta 650 MHz Five-cell Cavities

Medium Temperature baking of low beta 650 MHz cavities was conducted in a UHV furnace. A systematic study of cavity surface resistance components, residual and BCS, was conducted, including analyzing surface resistance due to trapped magnetic flux. Cavities showed an average 4.5 nano-ohm surface resistance at 17 MV/m under 2 K, which meets PIP-II specifications with a 40% margin. The results provided helpful information for the PIP-II project to optimize the cavity processing recipe for cryomodule application. The results were compared to the 1.3 GHz cavity that received a similar furnace baking.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

AGR-2 Loose Particle Heating Tests in the Furnace for Irradiated TRISO Testing

A furnace system was developed to thermally expose individual tristructural-isotropic (TRISO) coated particles to expand upon established postirradiation examination (PIE) safety testing that is used to explore particle failures and fission product release from compacts. Two systems were installed in the Irradiated Fuels Examination Facility (IFEL) at Oak Ridge National Laboratory (ORNL). The targeted design was intended to be simple and flexible to allow a range in conditions to be explored. Initial inert atmosphere testing indicated the presence of particle failures, so modifications to the testing approach were implemented to improve the furnace operation. Ultimately, burnback particles were analyzed to provide a direct measurement of fission product release, thus avoiding the complications from integral release that were observed during whole compact testing. Particles were exposed to temperatures ranging 1,150–1,300°C for up to 1,500 h and 1,600°C up to 500 h. No indication of uniform release of fission products such as 106 Ru, 125 Sb, or 154 Eu was observed, however, indication of particle dependent 154 Eu release was suggested for select particles. Exploration of 110m Ag release was limited to 1,150°C and 1,300°C up to 500 h. The analysis indicated that there was nonuniform release of 110m Ag and supports a possible bimodal temperature dependence on silver release.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

The Virtual Blast Furnace - An Integrated High Performance Computing Modeling, Simulation, and Visualization Capability for Steel Manufacturing (Final Report)

Many manufacturing industries require substantial capital and utilize energy intensive processes that involve complex phenomena. One example of such an industry is the steel industry, which is the fourth largest energy consuming industry in the U.S. By harnessing the power of High-Performance Computing (HPC) to enhance current simulation and visualization methods in the steel industry, it should be possible to increase resolution and/or decrease time of these methods by a factor of 1000. In this way, information can be obtained in a time frame that is useful for making business and engineering decisions, optimizing manufacturing processes and, ultimately, improving the completeness of U.S. industries. For example, if coke usage in blast furnaces were optimized such that the average coke rate was reduced from 797 lb/net tonne of hot metal (NTHM) to 604 lb/NTHM, costs could be reduced by $894 million/year. Additionally, members of the steel industry need the flexibility to efficiently operate blast furnaces at a range of production rates in order to meet fluctuating market demands. Large scale parameter studies can be utilized to discover workable operating parameters at a range of production rates.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

The Integrated Virtual Blast Furnace: Enabling Physics-Based Operational Guidance

As part of a DOE-supported research effort, Purdue University Northwest researchers are collaborating with Oak Ridge National Laboratory and United States Steel Corporation to develop a tool to provide blast furnace operators and engineers with process performance insight comparable to high-fidelity computational fluid dynamics modeling, accelerated to provide “what-if” scenarios at near-real-time speed. This is accomplished by pre-simulating a baseline case and a range of potential operating scenarios to establish how the furnace responds to changing inputs, then training a neural network-based Reduced Order Model to accelerate the speed at which predictions of key parameters can be generated.

Okosun, Tyamo↗
DOE OSTI2021

Coordination environment of Si in calcium silicate hydrates, silicate minerals, and blast furnace slags: A XANES database

Understanding the silicate polymerization of calcium silicate hydrate (C-S-H) gel and its crystalline polymorphs is important in cement science. NMR can determine Si environments, but the measurement can be time-consuming and provides no spatial information. X-ray absorption near-edge structure (XANES) spectroscopy is a fast tool for probing Si coordination, possibly with spatial information. However, there lacks an understanding of Si K-edge XANES spectra of cement-related silicate phases. Here, a Si K-edge XANES spectral database of nanocrystalline C-S-H, C-S-H minerals, blast-furnace slags, and metakaolin is provided. Si K-edge of C-S-H minerals shifts to higher energies with higher polymerized Si and lower CaSi connectivity in the Si second nearest neighbor shell. Si K-edge energy shows weak correlations with Ca/Si ratio, average SiO bond length, and SiO{sub 4} distortion due to the structural complexity of silicates. The substitution of Al for Si shifts the Si K-edge of tobermorite and slags to higher energies.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Robust Online Sequential RVFLNs for Data Modeling of Dynamic Time-Varying Systems with Application of an Ironmaking Blast Furnace

In a world where the increasing complexity of modern industrial processes brings difficulties for accurate mathematical modeling, taking advantage of data has become an efficient solution to complex dynamic process modeling issue. In this paper, we develop a novel robust online sequential version of random vector functional-link networks (RVFLNs) for data-driven modeling of dynamic time-varying system and applied it in a blast furnace (BF) ironmaking process. First, to overcome the time-varying dynamics of process and to enable the RVFLNs to learn online with avoiding data saturation, an improved online sequential version of RVFLNs (OS-RFVLNs) is first presented by online sequential learning with forgetting factor. This improved OS-RVFLNs algorithm is not only suitable for the real-time and large data transfer situation, but also can adjust the sensitivity of the algorithm to different samples with the help of the introduced forgetting factor. Second, since the output weights of the improved OS-RVFLNs as well as other RVFLNs algorithms are obtained by the least squares approach, a robustness problem may occur when the training dataset is contaminated with various outliers. To solve this problem, a Cauchy distribution weighted M-estimator is introduced to improve the robustness of the improved OS- RVFLNs. For this proposed robust OS-RVFLNs (R-OS- RVFLNs), since the weights of different outlier data are properly determined by the Cauchy distribution function, their corresponding contribution on modeling can be properly distinguished. Thus robust and better modeling results can be achieved. Experiments using actual industrial data of BF ironmaking process and comparative studies have demonstrated that the proposed method produces a better estimation accuracy and stronger robustness than other methods.

Blast furnace (BF), Modelling, Dynamic systems↗
DOE OSTI2021

Blast furnace slag reactions in various solutions (Interim Report)

Blast furnace slag (BPS) is a critical component of grout formulations for the remediation of low activity nuclear waste. This interim report describes the initial results of a study designed to investigate the fundamental mechanisms of BPS dissolution. The goal of the work is to delineate the physicochemical aspects of the slag that impart beneficial properties to grout formulations to enable the consistent production of a slag-replacement material (“designer slag”) that performs better than what is commercially available. This report documents the dissolution experiments that were conducted using nine different initial solution compositions. Solution measurements for each solution, including pH and solution composition, are given for 1, 7, 14, 28, and 56 day intervals samples. Scanning electron microscopy images are presented for the 56 day samples from each of the solutions. Inferences about reaction mechanisms and 56-day mineralogy are made based on the information collected to date. Some conclusions are made based on the work performed for this interim report, and a path forward including the strategy for making stronger conclusions based on X-ray diffraction (XRD) analyses is presented.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Enabling Production of Low Carbon Emissions Steel through CO 2 Capture from Blast Furnace Gases at Cleveland Cliffs’ 5 mtpa Steel Plant at Burns Harbor, Indiana

Dastur International Inc. has prepared a DOE-funded Pre-front-end engineering design (Pre-FEED) study to capture up to 2.8 mtpa of CO 2 from the available Blast Furnace (BF) gases at the Burns Harbor steel plant operated by Cleveland Cliffs in Burns Harbor, Indiana. The project consists of an amine solvent based pre-combustion carbon capture system, along with a unique BF gas conditioning process which significantly optimizes the project design and architecture in terms of higher volumes (2.8 mtpa vis-à-vis 1.6 mtpa without conditioning) & concentration (32 vol% in conditioned gas vs. 22% in raw BF gas) of CO 2 , which can be captured using a single train, resulting in reduced size and capital cost of the CO 2 capture island, and improved overall economics on a $\$$/tCO 2 captured basis.

42 ENGINEERING↗
DOE OSTI2025

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↗
DOE OSTI2020

Recovery of Cs-137 from Electric Arc Furnace Dust - 20562

The present work proposes the Cs-137 recovery from Electric Arc Furnace Dusts (EAFD) by leaching, in order to reduce the volume of radioactive waste to be managed. Leaching tests were performed on different samples of EAFD contaminated with Cs-137. Two leaching methodologies were tested: dynamic and static using as medium distilled water and in some cases NaOH. The results indicate the possibility of recovering Cs-137 from EAFD using the dynamic method; however, the recovery efficiencies of Cs-137 depend on EAFD's chemical composition. The leachates of Cs-137 were quantitatively adsorbed on exchange resins, showing its great potential to isolate or contain the Cs-137 recovery from EAFD. This study shows the feasible to apply the dynamic leaching methodology to recover Cs-137 from EAFD and the use of ion exchange resins for the isolation of removed Cs-137. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Correlating Impacts of Injected Fuels on Carbon Emissions in Blast Furnace with Computational Fluid Dynamics Modeling

A major challenge for steelmaking is the reduction of CO 2 emissions. In this regard, the blast furnace (BF) is critical due to the high associated CO 2 levels. This investigation assesses the impact of tuyere‐injected fuels on BF CO 2 emissions. Specifically, computational fluid dynamics results obtained previously at Purdue University Northwest are analyzed to obtain CO 2 emissions when natural gas (NG), syngas, hydrogen, or hydrogen/NG are injected. CO 2 emissions are compared with those produced when 95 kg of NG/thm is injected. Among these scenarios, the largest CO 2 reduction occurs when 102 kg of syngas/thm (COG feedstock #1) is injected at 973 K, reducing CO 2 by 190.6 kg thm −1 . The largest CO 2 reduction obtained with NG occurs when 130 kg thm −1 is injected at 600 K, reducing emissions by 65 kg thm −1 . H 2 injection also reduces CO 2 , but requires careful adjusting to reach stable operation. For instance, injecting 35 kg of H 2 /thm reduces CO 2 by 52 kg thm −1 . Increasing gaseous injection rates can significantly reduce CO 2 emissions, with fuel preheating providing an addendum, but high injection rates can lead to unstable operation. Furthermore, results show a correlation between CO 2 emissions and average temperature of shaft region for multiple fuels and injection conditions.

Metallurgy & Metallurgical Engineering↗
DOE OSTI2024

Recycling Perspectives of Electric Arc Furnace Slag in the United States: A Review

This article presents a comprehensive review of electric arc furnace (EAF) slag recycling in the United States, examining its classification and the associated challenges and opportunities of its industrial use. The study affirms EAF slag's nonhazardous status. Here, the main challenges identified in EAF slag applications include substantial variations in composition and volume instability during/after hydration. Analysis of the U.S. recycling practices reveals that EAF slag is predominantly reused, with minimal landfill disposal. However, its prevalent use as a low value-added aggregate in construction applications underscores the industry's ongoing challenge to get additional value from EAF slag recycling. Despite these challenges, the study highlights a great potential for increased value extraction from EAF slag recycling. Beyond conventional applications as a clinker material for the cement industry, the review explores modern technologies for steelmaking slag recycling, revealing options for recovering valuable metals such as Cr, V, Mo, and Fe through methods such as leaching, reduction, and oxidation.

42 ENGINEERING↗
DOE OSTI2022

Computational Methodology to Simulate Pyrometallurgical Processes in a Secondary Lead Furnace

Pyrometallurgical recovery of nonferrous metals involves a combination of thermally intensive transformations during exothermic gas-phase reactions, endothermic decomposition of solid charge, and melting of simpler solids. In the recovery of secondary lead, simultaneous thermal effects in a reverberatory-style furnace cause a melt pool to accumulate at the bottom, with lighter solids (slag) floating above and gaseous products from decomposition of the charge diffusing through the gas–slag interface. Species from oxy-fuel combustion of natural gas, species profiles from smelting reactions, and the formation of a melt pool consisting primarily of lead are simulated via a time-averaged formulation. Predictions of outflow are compared with preset inflow profiles to ensure conservation of mass. Thermal profiles for solid, liquid, and gas phases are presented by species. A novel method is implemented to model the latent heat of fusion using a heterogeneous chemical reaction. The simulation is conducted in Simcenter STAR-CCM+ v. 16.02.009-R8.

Rao, Vivek↗
DOE OSTI2024

A Dataset of CFD Simulated Industrial Furnace Images for Conditional Automatic Generation with GANs

The steel industry is constantly looking for ways to automate processes and improve efficiency. A standard practice in industry is to simulate how complex systems will operate before they are actually used. Some complex systems, including steel industry processes such as blast furnaces, require complex physics-based simulations utilizing computational fluid dynamics (CFD). These CFD physics-based simulations are very accurate but can take significant time and computational resources to process, resulting in challenges for the implementation of the models in real-world operational environments. In recent years, deep learning (DL) has been considered as a substitute for these CFD models. DL models can be trained on validated CFD simulation data and then used for industrial process inference. Previous DL-based solutions have made great contributions for industrial automation but are currently missing the additional visualization component that CFD simulations also provide. In this paper, we propose a dataset for simple DL generative approaches that can help to address this issue. The dataset and methodology under development to approach this prediction are discussed in this work.

Calix, Ricardo↗
DOE OSTI2020

Investigation of startup, performance and cycling of a residential furnace integrated with micro-tubular flame-assisted fuel cells for micro-combined heat and power

Solid Oxide Fuel Cells (SOFCs) offer advantages for micro-Combined Heat and Power (μCHP), but currently suffer from slow startup (>1 h) and limited thermal cycling which reduces the applications, energy savings and economics. In this work, a micro-Tubular SOFC stack is integrated into a residential furnace to create a micro-Tubular Flame-assisted Fuel Cell (mT-FFC) μCHP system. A high power density of 202 mW cm -2 is reported operating in synthesis gas generated from fuel-rich combustion of natural gas/air. Unlike previous reports, instabilities in the polarization are attributed to low temperature of the oxygen reduction reaction at the cathode. The mT-FFC stack achieved peak power density in 6 min after ignition. 200 thermal cycles at an average heating rate of 215 °C.min -1 and average cooling rate of 176 °C.min -1 were conducted and a low degradation rate of 0.0325 V per 100 cycles per fuel cell was achieved. Low NO x emissions (10 ppm) and high combined efficiency is reported.

25 ENERGY STORAGE↗