Search NASA⌕ Search

SEARCH · Search NASA

Results for “ironmaking”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Interaction of Iron with Alumina Refractory Under Flash Ironmaking Conditions

A novel flash ironmaking technology (FIT) based on the direct reduction of iron ore concentrate by a reducing gas such as hydrogen, natural gas, or coal gas has been developed at the University of Utah. A proper choice of refractories is expected to play an important role in the development of FIT and its scale-up. In this work, the interaction of iron with alumina refractory under flash ironmaking conditions has been investigated. A thermodynamic basis for the interaction phenomena has been developed by considering the Fe-Al-O system, and a kinetic model based on solid-state diffusion is proposed to describe the growth of the hercynite (FeAl{sub 2}O{sub 4}) spinel formed as a result of the interaction between Fe, O (from H{sub 2}O and CO{sub 2}), and Al{sub 2}O{sub 3}. Experiments were conducted with Fe powders and pure Al{sub 2}O{sub 3} in the temperature range 1200 to 1500 °C under gas atmospheres relevant to flash ironmaking, and the reacted samples were analyzed using XRD, SEM-EDX, and EPMA techniques. The analyses of reacted samples confirmed the formation of the hercynite (FeAl{sub 2}O{sub 4}) spinel phase and the thickness of the FeAl{sub 2}O{sub 4} spinel as measured using elemental line scans in SEM-EDX and EPMA varied in the range of 0.5 to 1.3 mm. Results showed that the proposed model suitably describes the growth of the hercynite spinel layer, which obeyed the parabolic rate law at all temperatures. The parabolic rate constants were obtained and the diffusion-controlled growth of the FeAl{sub 2}O{sub 4} layer strongly depended on temperature. Furthermore, using the kinetic model, an expression for the effective diffusivity ( (D{sub eff})-bar ) was obtained and its values at the experimental temperatures were determined. The solid-state diffusion was an activated process, as expected, with an activation energy value of 231 kJ/mol.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Modeling error PDF optimization based wavelet neural network modeling of dynamic system and its application in blast furnace ironmaking

In general, the modeling errors of dynamic system model are a set of random variables. The traditional performance index of modeling such as means square error (MSE) and root means square error (RMSE) can not fully express the connotation of modeling errors with stochastic characteristics both in the dimension of time domain and space domain. Therefore, the probability density function (PDF) is introduced to completely describe the modeling errors in both time scales and space scales. Based on it, a novel wavelet neural network (WNN) modeling method is proposed by minimizing the two-dimensional (2D) PDF shaping of modeling errors. First, the modeling error PDF by the tradional WNN is estimated using data-driven kernel density estimation (KDE) technique. Then, the quadratic sum of 2D deviation between the modeling error PDF and the target PDF is utilized as performance index to optimize the WNN model parameters by gradient descent method. Since the WNN has strong nonlinear approximation and adaptive capability, and all the parameters are well optimized by the proposed method, the developed WNN model can make the modeling error PDF track the target PDF, eventually. Simulation example and application in a blast furnace ironmaking process show that the proposed method has a higher modeling precision and better generalization ability compared with the conventional WNN modeling based on MSE criteria. Furthermore, the proposed method has more desirable estimation for modeling error PDF that approximates to a Gaussian distribution whose shape is high and narrow.

Modelling↗
DOE OSTI2019

Energy Consumption and CO 2 Emissions in Ironmaking and Development of a Novel Flash Technology

The issues of energy consumption and CO 2 emissions of major ironmaking processes, including several new technologies, are assessed. These two issues are interconnected in that the production and use of fuels to generate energy add to the total amount of CO 2 emissions and the efforts to sequester or convert CO 2 require energy. The amounts of emissions and energy consumption in alternate ironmaking processes are compared with those for the blast furnace, currently the dominant ironmaking process. Although more than 90% of iron production is currently through the blast furnace, intense efforts are devoted to developing alternative technologies. Recent developments in alternate ironmaking processes, which are largely driven by the needs to decrease CO 2 emissions and energy consumption, are discussed in this article. This discussion will include the description of the recently developed novel flash ironmaking technology. This technology bypasses the cokemaking and pelletization/sintering steps, which are pollution prone and energy intensive, by using iron ore concentrate. This transformational technology renders large energy saving and decreased CO 2 emissions compared with the blast furnace process. Economic analysis indicated that this new technology, when operated using natural gas, would be economically feasible. As a related topic, we will also discuss different methods for computing process energy and total energy requirements in ironmaking.

36 MATERIALS SCIENCE↗
DOE OSTI2018

A Novel Flash Ironmaking Process

The project goal is to develop an entirely new transformational process for alternate ironmaking based on the direct gaseous reduction of iron oxide concentrates in a flash reduction process, with the ultimate objective of significantly increasing energy productivity (by reducing energy consumption by up to 57 %) and reducing environmental emissions, especially CO 2 emissions, versus the conventional blast furnace ironmaking route.The Novel Flash Ironmaking Process uses gaseous reducing agents, such as natural gas, hydrogen, other syngas, or a combination thereof. The proposed technology is to be applied to the production of iron as a feed to the steelmaking process, eventually replacing the blast furnace and other alternate ironmaking processes. The process can also be a part of a continuous direct steelmaking process.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Design of Novel Flash Ironmaking Reactors for Greatly Reduced Energy Consumption and CO2 Emissions

The development of a novel ironmaking technology based on fine iron ore concentrate in a flash reactor is summarized. The design of potential industrial reactors for flash ironmaking based on the computational fluid dynamics technique is described. Overall, this simulation work has shown that the size of the reactor used in the novel flash ironmaking technology (FIT) can be quite reasonable vis-à-vis the blast furnaces. A flash reactor of 12 m diameter and 35 m height with a single burner operating at atmospheric pressure would produce 1.0 million tons of iron per year. The height can be further reduced by either using multiple burners, preheating the feed gas, or both. The computational fluid dynamics (CFD)-based design of potential industrial reactors for flash ironmaking pointed to a number of features that should be incorporated. The flow field should be designed in such a way that a larger portion of the reactor is used for the reduction reaction but at the same time excessive collision of particles with the wall must be avoided. Further, a large diameter-to-height ratio that still allows a high reduction degree should be used from the viewpoint of decreased heat loss. This may require the incorporation of multiple burners and solid feeding ports.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Pathways to Electrochemical Ironmaking at Scale Via the Direct Reduction of Fe 2 O 3

Electrochemical ironmaking can provide an energy efficient, zero-emissions alternative to traditional methods of ironmaking, but the scalability of low-temperature electrochemical cells may be constrained by reactor throughput and the availability of acceptable feedstocks. Electrodes directly converting solid iron-oxide particles to metal circumvent traditional mass-transport limitations but are sensitive to both the particle size and nanoscale morphology of reactants. Furthermore, the effect of these properties on reactor throughput has not been systematically studied at model electrowinning surfaces. Here, we have used size-controlled, homologous α-Fe 2 O 3 particles to study how the nanoscale morphology of oxides influences the obtainable current density toward Fe metal and integrated these results in a technoeconomic model for alkaline iron electrowinning systems. Micron-scale α-Fe 2 O 3 with nanoscale porosity can be used to form Fe at current densities commensurate with industrial water electrolysis (>0.6 A cm –2 ) in the absence of external convection, providing a path to cost-competitive and scalable ironmaking using electrochemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Activating magnetite ores for aqueous ironmaking at high current densities

Low-temperature electrochemical cells reducing iron oxides to metal in alkaline electrolytes can support fully electrified steelmaking processes. Previous studies on these cells have primarily focused on high-surface-area hematite, Fe 2 O 3 , reactants whereas attempts to reduce suspensions of magnetite, Fe 3 O 4 —one of the two feedstocks for existing ironmaking reactors—have generally been limited to low rates of reaction (<30 mA cm −2 ). Here, in this study, we control the crystalline domain size of Fe 2 O 3 and Fe 3 O 4 particles in 10 M NaOH electrolytes to study how the nanoscale morphology of oxides controls the rate of electrochemical ironmaking. Rotating-ring disk electrode measurements of Fe 2+ , in situ Raman spectroscopy of the electrode surface, and ex situ electron microscopy were consistent with a hypothesized passivation process at Fe 3 O 4 surfaces that may prevent the continuous formation of soluble intermediates. Sufficiently small (<100 nm diameter) oxide particles yielded Fe partial current densities >160 mA cm −2 , a fivefold increase relative to previously reported rates for Fe 3 O 4 suspensions and comparable to active Fe 2 O 3 . Electron microscopy revealed that electrodeposited films were composed of micron-scale crystalline Fe domains with a porous film of Fe 3 O 4 nanoparticles and supports a model where Fe is grown primarily from soluble Fe 2+ intermediates. Based on these insights, inactive blast-furnace-grade iron-oxides were transformed into high surface area nanoparticles (1.6 to 229.2 m 2 g −1 ) via reprecipitation, leading to a ninefold enhancement in faradaic efficiency and an Fe partial current density of 120 mA cm −2 . When integrated with chlor-iron cells producing reagents for reprecipitation, this approach could lead to a cost-competitive process for electrochemical ironmaking from industrially relevant feedstocks.

TEM↗
DOE OSTI2019

Interaction of magnesia-carbon refractory with metallic iron under flash ironmaking conditions

The interaction of a magnesia-carbon refractory with iron under flash ironmaking conditions has been investigated in this work. Oxidation of carbon from the magnesia-carbon refractory took place and the formation of magnesiowustite (Mg x Fe 1-x O) solid solution occurred as a result of the interaction between magnesia (MgO) in the refractory with iron (Fe). A kinetics model for the growth of magnesiowustite (Mg x Fe 1-x O) was developed based on the counterdiffusion of Fe 2+ and Mg 2+ cations through it. Experiments were conducted with iron powder and magnesia-carbon refractory in the temperature range 1200–1400 °C under gas atmospheres relevant to flash ironmaking and analyses of reacted samples using SEM-EDX and EPMA techniques confirmed the formation of magnesiowustite (Mg x Fe 1-x O). Using the kinetics model and the composition profiles determined with EPMA, the values of interdiffusion coefficient ( D ¯ F e - M g ), averaged over the composition range, were calculated. The activation energy ( E a ) for the solid-state diffusion process was determined to be 377 kJ/mol.

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 OSTI2018

Reactions in the Tuyere Zone of Ironmaking Blast Furnace

A series of slags can be formed in the lower part of the ironmaking blast furnace that play important roles in smooth furnace operation, and in determining iron quality and productivity. The final slag tapped from the BF has been investigated extensively as it can be collected directly. Unfortunately, difficulties in accessing the interiors of the blast furnace limit the full understanding of other slags such as primary and bosh slags. In this study, different types of samples directly obtained from the tuyere zone of the blast furnace have been systematically analyzed and characterized using scanning electron microscopy (SEM), electron probe X-ray microanalysis (EPMA), and X-ray fluorescence (XRF), with focus on the characteristics of slags formed in the tuyere level. The samples were identified into three groups according to their morphological, mineralogical, and chemical properties: (1) tuyere slags originating from the reactions between ash and dripping slags; (2) bosh slags in the CaO-SiO{sub 2}-Al{sub 2}O{sub 3}-MgO-FeO system, with a CaO/SiO{sub 2} weight ratio of around 1.50, and Al{sub 2}O{sub 3} and MgO concentrations close to those of final slags; and (3) coke ash that did not react with bosh slags. These findings will provide useful information on the evaluation of slags inside the blast furnace and the reactions in the tuyere zone.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Numerical Investigation of Novel Oxygen Blast Furnace Ironmaking Processes

Oxygen blast furnace (OBF) ironmaking process has the potential to realize “zero carbon footprint” production, but suffers from the “thermal shortage” problem. This paper presents three novel OBF processes, featured by belly injection of reformed coke oven gas, burden hot-charge operation, and their combination, respectively. These processes were studied by a multifluid process model. The applicability of the model was confirmed by comparing the numerical results against the measured key performance indicators of an experimental OBF operated with or without injection of reformed coke oven gas. Then, these different OBF processes together with a pure OBF were numerically examined in aspects of in-furnace states and global performance, assuming that the burden quality can be maintained during the hot-charge operation. The numerical results show that under the present conditions, belly injection and hot charge, as auxiliary measures, are useful for reducing the fuel rate and increasing the productivity for OBFs but in different manners. Hot charge should be more suitable for OBFs of different sizes because it improves the thermochemical states throughout the dry zone rather than within a narrow region in the case of belly injection. The simultaneous application of belly injection and hot charge leads to the best process performance, at the same time, lowering down hot-charge temperature to achieve the same carbon consumption and hot metal temperature as that achieved when applying the hot charge alone. This feature will be practically beneficial in the application of hot-charge operation. In addition, a systematic study of hot-charge temperature reveals that optimal hot-charge temperatures can be identified according to the utilization efficiency of the sensible heat of hot burden.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Increased Use of Natural Gas in Blast Furnace Ironmaking: Mass and Energy Balance Calculations

In blast furnace ironmaking, coke can be partially replaced by injected natural gas. Tuyère injection of cold natural gas is commonly practiced in North America. In this work, limits to the tuyère injection rate have been quantified with mass and energy balances. The fundamental origin of the limits is the endothermicity of methane injection. In principle, shaft injection of preheated and partially combusted methane would obviate the endothermic effect. However, the thermal and chemical energy parameter indicates that the energy requirement in the lower part of the furnace—to melt hot metal and slag—might not be met in the case of shaft injection. Tuyère injection of preheated methane might be a feasible alternative. Calculated combustion kinetics support the feasibility of partial combustion of preheated methane (with sub-stoichiometric oxygen) before injection.

36 MATERIALS SCIENCE↗
DOE OSTI2019

An Investigation of Carburization Behavior of Molten Iron for the Flash Ironmaking Process

In order to recognize the dripping and the carburizing behaviors of the molten iron within the coke packed bed in the flash ironmaking process, a transient three-dimensional numerical model was developed. The volume of fluid (VOF) approach is used to describe the movement of the molten iron and the argon gas. The porous medium module is employed to define the momentum, heat, and mass transfer between the coke packed bed and the molten iron. Moreover, a factor is introduced to consider the influence of the ash film on the carburization process. A reasonable agreement between the experiment and simulation is obtained. The results indicate that the molten iron flows downward from the upper crucible to middle crucible. After entering the middle crucible, the molten iron spreads around within the coke packed bed and simultaneously moves downward. The carbon is, therefore, transferred from the coke to the molten iron. With the 47-mm-height coke packed bed, the carbon content in the molten iron after the carburization decreases from 3.19 to 1.97 pct, while the coke diameter ranges from 2 to 5 mm. With the 2-mm-diameter coke, the carbon content in the molten iron after the carburization increases from 2.84 to 4.81 pct, while the coke packed bed height increases from 37 to 97 mm.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Data-Driven Robust M-LS-SVR-Based NARX Modeling for Estimation and Control of Molten Iron Quality Indices in Blast Furnace Ironmaking

Optimal operation of an industrial blast furnace (BF) ironmaking process largely depends on a reliable measurement of molten iron quality (MIQ), which is not feasible using the conventional sensors. This paper proposes a novel data-driven robust modeling method for online estimation and control of MIQ indices. First, to completely capture the nonlinear dynamics of the BF process, the nonlinear autoregressive exogenous (NARX) model is constructed for the MIQ indices. Then, considering that the standard least-squares support vector regression (LS-SVR) cannot directly cope with the multi-output problem, the multi- task transfer learning is proposed to design a novel multi-output LS-SVR (M-LS-SVR) for learning of the NARX model. Furthermore, a novel M-estimator is proposed to reduce the interference of outliers and improve the robustness of the M-LS- SVR model. Since the weights of different outlier data are properly given by the weight function, their corresponding contributions on modeling can be properly distinguished, thus a robust modeling result can be achieved. Finally, a novel multi- objective evaluation index on modeling performance is developed by comprehensively considering the root mean square error of modeling and the correlation coefficient on trend fitting, based on which the NSGA-II algorithm is used to globally optimize the model parameters. Both experiments using industrial data and industrial applications illustrate that the proposed method can eliminate the adverse effect caused by the fluctuation of data in BF process efficiently, which indicates its stronger robustness and higher accuracy. Moreover, control testing shows that the developed model can be well applied to realize data-driven control of the BF process.

blast cavities, Control↗