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DOE OSTI2017

Reference scenarios for evaluating wood pellet production in the Southeastern United States

Wood pellet exports from the Southeastern United States (SE US) to Europe have been increasing in response to European Union member state policies to displace coal with renewable biomass for electricity generation. An understanding of the interactions among SE US forest markets, forest management, and forest ecosystem services is needed to quantify the effects of pellet production compared to what would be expected under a reference case or ‘counterfactual scenario’ without pellet production. Inconsistent methods to define and justify the counterfactual scenario result in conflicting estimates and large uncertainties about the impacts of pellet production on SE US forests. Guidelines to support more consistent and transparent counterfactual scenarios are proposed. The guidelines include identifying major influences on current SE US forest conditions, developing potential futures that clearly document underlying assumptions and associated uncertainties, identifying the most likely alternative feedstock fates, and estimating the effects of no pellet demand on future forest conditions. Finally, the guidelines can help modelers to more accurately reflect the past and current forest dynamics and to consider the implications for SE US forest landscapes of future scenarios with and without pellet production.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Framework for assessing land‐management effects on at‐risk species: Example of SE USA wood pellet production and gopher tortoise ( Gopherus polyphemus )

Abstract Land‐management choices made for economic and societal gains intrinsically influence landscapes and species that are dependent upon them. We propose a simple analysis framework to examine critical intersections between land‐management choices and the life‐history conditions of selected species of concern, thereby facilitating the identification of mitigation practices that can reduce negative impacts on species at risk. We test the proposed framework through application to gopher tortoise ( Gopherus polyphemus ), a keystone species that is the focus of conservation efforts across the southeastern region of United States of America, where wood pellets are being produced for bioenergy. Production of these wood pellets for export to Europe and Asia has drastically increased in the past decade, raising concerns about potential harm to biodiversity since many species in the forests sourcing pellet production were already at risk prior to the development of this new commodity. Identifying the mechanisms of potential impacts of wood pellet production on species of concern is essential to establishing meaningful management recommendations that can enhance conservation efforts while supporting sustainable bioenergy. By considering the intersections between life‐history conditions of gopher tortoise and forest‐management practices related to woody biomass extraction for pellet production, we identify several mechanisms by which the wood‐pellet industry might affect this species of concern, both positively and negatively. We then identify mitigation practices that can help offset the potential impacts of logging, thinning, and dead wood removal on gopher tortoise. Our analysis framework may be transferable to other species of concern and land‐management practices across diverse landscapes. This article is categorized under: Bioenergy > Economics and Policy Bioenergy > Climate and Environment

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Streamlining resummed QCD calculations using Monte Carlo integration

Some of the most arduous and error-prone aspects of precision resummed calculations are related to the partonic hard process, having nothing to do with the resummation. In particular, interfacing to parton-distribution functions, combining various channels, and performing the phase space integration can be limiting factors in completing calculations. Conveniently, however, most of these tasks are already automated in many Monte Carlo programs, such as MadGraph [1], Alpgen [2] or Sherpa [3]. In this paper, we show how such programs can be used to produce distributions of partonic kinematics with associated color structures representing the hard factor in a resummed distribution. These distributions can then be used to weight convolutions of jet, soft and beam functions producing a complete resummed calculation. In fact, only around 1000 unweighted events are necessary to produce precise distributions. A number of examples and checks are provided, including e + e – two- and four-jet event shapes, n -jettiness and jet-mass related observables at hadron colliders at next-to-leading-log (NLL) matched to leading order (LO). Furthermore, the attached code can be used to modify MadGraph to export the relevant LO hard functions and color structures for arbitrary processes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Unifying themes and distinct features of carbon and nitrogen assimilation by polysaccharide-degrading bacteria: a summary of four model systems

Our current understanding of enzymatic polysaccharide degradation has come from a huge number of in vitro studies with purified enzymes. While this vast body of work has been invaluable in identifying and characterizing novel mechanisms of action and engineering desirable traits into these enzymes, a comprehensive picture of how these enzymes work as part of a native in vivo system is less clear. Recently, several model bacteria have emerged with genetic systems that allow for a more nuanced study of carbohydrate active enzymes (CAZymes) and how their activity affects bacterial carbon metabolism. With these bacterial model systems it is now possible to not only study a single nutrient system in isolation (i.e. carbohydrate degradation and carbon metabolism), but also how multiple systems are integrated. Given that most environmental polysaccharides are carbon rich but nitrogen poor (e.g. lignocellulose), the interplay between carbon and nitrogen metabolism in polysaccharide-degrading bacteria can now be studied in a physiologically relevant manner. Therefore, in this review we have summarized what has been experimentally determined for CAZyme regulation, production, and export in relation to nitrogen metabolism for two Gram-positive (Caldicellulosiruptor bescii and Clostridium thermocellum) and two Gram-negative (Bacteroides thetaiotaomicron and Cellvibrio japonicus) polysaccharide-degrading bacteria. By comparing and contrasting these four bacteria we have highlighted the shared and unique features of each, with a focus on in vivo studies, in regard to carbon and nitrogen assimilation. Finally, we conclude with what we believe are two important questions that can act as guideposts for future work to better understand the integration of carbon and nitrogen metabolism in polysaccharide-degrading bacteria.

Cellvibrio japonicus↗

DOE OSTI2017

Cinnamic Acid Derivatives Enhance the Efficacy of Transarterial Embolization in a Rat Model of Hepatocellular Carcinoma

IntroductionWe hypothesize that the combination of transarterial embolization (TAE) plus inhibition of lactate export will limit anaerobic metabolism and reduce tumor survival compared to TAE alone. The purpose of this study was to test this hypothesis in a rat model of hepatocellular carcinoma (HCC).MethodsRat N1-S1 hepatoma cells were assayed in vitro using the Seahorse XF analyzer to measure extracellular acidification (lactate excretion) comparing effects of the addition of caffeic acid (CA) or ferulic acid (FA) or UK-5099 with control. Monocarboxylate transporter Slc16a3 was knocked down by RNAi. N1S1 tumors were orthotopically implanted in rats and 4 groups evaluated: (1) Control, (2) TAE-only, (3) TAE plus CA, and (4) TAE plus FA. Tumor size was determined by ultrasound and analyzed by repeated measures statistics. Tumors harvested at 4 weeks were examined by microscopy.ResultsSeahorse assays showed that CA and FA caused a significant reduction by >90% in lactate efflux by N1S1 tumor cells (p < 0.01). Knockdown of Slc16a3 prevented inhibition by CA. In vivo tumors grew 30-fold in volume over 4 weeks in untreated controls. By comparison, TAE resulted in near cessation of growth (10% in 4-week time period). However, both TAE + CA and TAE + FA caused a significant reduction of tumor volumes (87 and 72%, respectively) compared to control and TAE (p < 0.05). Pathologic evaluation revealed residual tumor in the TAE group but no residual viable tumor cells in the TAE + CA and TAE + FA groups.ConclusionAddition of CA or FA enhances the effectiveness of TAE therapy for HCC in part by blocking lactate efflux.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

A twentieth-century reanalysis forced ocean model to reconstruct the North Atlantic climate variation during the 1920s

The observed North Atlantic multi-decadal variability for the period 1872–2009 is reconstructed with the Max Planck Institute ocean model, which is forced with an ensemble of the atmospheric twentieth century reanalysis. Special emphasis is put on the early part of the experiments, which includes a prominent climate variation during the 1920s. The experiments are in agreement with selected hydrographic records, indicating a transition from cold and fresh North Atlantic water properties, prior to the 1920 climate variation, towards warm and saline waters afterwards. Examining the variation reveals that sea level pressure (SLP) anomalies prior to the 1900s resemble a negative phase of North Atlantic Oscillation and associated weak winds result in a weak North Atlantic Current (NAC) and sub-polar gyre (SPG). This leads to a reduced transport of warm and saline waters into the higher latitudes. Simultaneously, Arctic freshwater release results in the accumulation of cold and fresh water properties, which cover the upper layers in the Labrador Sea and subsequently suppress convection. From the 1910s, the Arctic freshwater export is reduced, and, NAC and SPG are strengthened as a result of an increased SLP gradient over the North Atlantic. Concurrently, Labrador Sea convection and Atlantic meridional overturning circulation (AMOC) increase. The intensified NAC, SPG, and AMOC redistribute sub-tropical water into the North Atlantic and Nordic Seas, thereby increasing observed and modelled temperature and salinity during the 1920s.

Meteorology & Atmospheric Sciences↗

DOE OSTI2017

MJO simulation in CMIP5 climate models: MJO skill metrics and process-oriented diagnosis

The Madden-Julian Oscillation (MJO) simulation diagnostics developed by MJO Working Group and the process-oriented MJO simulation diagnostics developed by MJO Task Force are applied to 37 Coupled Model Intercomparison Project phase 5 (CMIP5) models in order to assess model skill in representing amplitude, period, and coherent eastward propagation of the MJO, and to establish a link between MJO simulation skill and parameterized physical processes. Process-oriented diagnostics include the Relative Humidity Composite based on Precipitation (RHCP), Normalized Gross Moist Stability (NGMS), and the Greenhouse Enhancement Factor (GEF). Numerous scalar metrics are developed to quantify the results. Most CMIP5 models underestimate MJO amplitude, especially when outgoing longwave radiation (OLR) is used in the evaluation, and exhibit too fast phase speed while lacking coherence between eastward propagation of precipitation/convection and the wind field. The RHCP-metric, indicative of the sensitivity of simulated convection to low-level environmental moisture, and the NGMS-metric, indicative of the efficiency of a convective atmosphere for exporting moist static energy out of the column, show robust correlations with a large number of MJO skill metrics. The GEF-metric, indicative of the strength of the column-integrated longwave radiative heating due to cloud-radiation interaction, is also correlated with the MJO skill metrics, but shows relatively lower correlations compared to the RHCP- and NGMS-metrics. Our results suggest that modifications to processes associated with moisture-convection coupling and the gross moist stability might be the most fruitful for improving simulations of the MJO. Though the GEF-metric exhibits lower correlations with the MJO skill metrics, the longwave radiation feedback is highly relevant for simulating the weak precipitation anomaly regime that may be important for the establishment of shallow convection and the transition to deep convection.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Projections of winter polynyas and their biophysical impacts in the Ross Sea Antarctica

Abstract This study investigates winter polynyas in the southern Ross Sea, Antarctica where several polynyas are known to form. Coastal polynyas are areas of lower sea ice concentration and/or thickness along the coast that are otherwise surrounded by more extensive, thicker sea ice pack. Polynyas are also locations where organisms can exploit both the ice substrate and pelagic resources. Using a self organizing map algorithm, we identify polynya events in the Community Earth System Model Version 2 Large Ensemble (CESM2-LE). The neural network algorithm is able to identify polynya events without imposing an ice concentration or thickness threshold, as is often done when identifying polynyas. The CESM2-LE produces a wintertime polynya feature comparable in size and location to the Ross Sea polynya, and during polynya events there are large turbulent heat fluxes and export of sea ice from the Ross Sea. In the CESM2-LE polynya event frequency is projected to decrease sharply in the later twentyfirst century, leading to increasing sea ice concentrations and thicknesses in the region. The drivers of the polynya frequency decline are likely both large scale circulation changes and local atmosphere and ocean feedbacks. If declines in wintertime polynya frequency over the twentyfirst century do occur they may impact Antarctic Bottom Water formation and local net primary productivity. Thus, better understanding potential local and unexpected sea ice changes in the Ross Sea is important for both assessing climate system impacts and ecological impacts on the Ross Sea ecosystem, which is currently protected by an internationally recognized marine protected area.

Meteorology & Atmospheric Sciences↗

DOE OSTI2022

Compartment-specific energy requirements of photosynthetic carbon metabolism in Camelina sativa leaves

Abstract Main conclusion The oxidative pentose phosphate pathway provides cytosolic NADPH yet reduces carbon and energy use efficiency. Repressing this pathway and introducing cytosolic NADPH-dependent malate dehydrogenase may increase crop yields by ≈5%. Abstract Detailed knowledge about plant energy metabolism may aid crop improvements. Using published estimates of flux through central carbon metabolism, we phenotype energy metabolism in illuminated Camelina sativa leaves (grown at 22 °C, 500 µmol photons m −2 s −1 ) and report several findings. First, the oxidative pentose phosphate pathway (OPPP) transfers 3.3% of the NADPH consumed in the Calvin–Benson cycle to the cytosol. NADPH supply proceeds at about 10% of the rate of net carbon assimilation. However, concomitantly respired CO 2 accounts for 4.8% of total rubisco activity. Hence, 4.8% of the flux through the Calvin–Benson cycle and photorespiration is spent on supplying cytosolic NADPH, a significant investment. Associated energy requirements exceed the energy output of the OPPP. Thus, autotrophic carbon metabolism is not simply optimised for flux into carbon sinks but sacrifices carbon and energy use efficiency to support cytosolic energy metabolism. To reduce these costs, we suggest bioengineering plants with a repressed cytosolic OPPP, and an inserted cytosolic NADPH-dependent malate dehydrogenase tuned to compensate for the loss in OPPP activity (if required). Second, sucrose cycling is a minor investment in overall leaf energy metabolism but a significant investment in cytosolic energy metabolism. Third, leaf energy balancing strictly requires oxidative phosphorylation, cofactor export from chloroplasts, and peroxisomal NADH import. Fourth, mitochondria are energetically self-sufficient. Fifth, carbon metabolism has an ATP/NADPH demand ratio of 1.52 which is met if ≤ 21.7% of whole electron flux is cyclic. Sixth, electron transport has a photon use efficiency of ≥ 62%. Last, we discuss interactions between the OPPP and the cytosolic oxidation–reduction cycle in supplying leaf cytosolic NADPH.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Multi-Scale Temporal Patterns in Stream Biogeochemistry Indicate Linked Permafrost and Ecological Dynamics of Boreal Catchments

Temporal patterns in stream chemistry provide integrated signals describing the hydrological and ecological state of whole catchments. However, stream chemistry integrates multi-scale signals of processes occurring in both the catchment and stream. Deconvoluting these signals could identify mechanisms of solute transport and transformation and provide a basis for monitoring ecosystem change. Here, we applied trend analysis, wavelet decomposition, multivariate autoregressive state-space modeling, and analysis of concentration-discharge relationships to assess temporal patterns in high-frequency (15 min) stream chemistry from permafrost-influenced boreal catchments in Interior Alaska at diel, storm, and seasonal time scales. We compared catchments that varied in spatial extent of permafrost to identify characteristic biogeochemical signals. Catchments with higher spatial extents of permafrost were characterized by increasing nitrate concentration through the thaw season, an abrupt increase in nitrate and fluorescent dissolved organic matter (fDOM) and declining conductivity in late summer, and flushing of nitrate and fDOM during summer rainstorms. In contrast, these patterns were absent, of lower magnitude, or reversed in catchments with lower permafrost extent. Solute dynamics revealed a positive influence of permafrost on fDOM export and the role of shallow, seasonally dynamic flowpaths in delivering solutes from high-permafrost catchments to streams. Lower spatial extent of permafrost resulted in static delivery of nitrate and limited transport of fDOM to streams. Shifts in concentration-discharge relationships and seasonal trends in stream chemistry toward less temporally dynamic patterns might therefore indicate reorganized catchment hydrology and biogeochemistry due to permafrost thaw.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Developing an Interactive Data Visualization Tool to Assess the Impact of Decision Support on Clinical Operations

Due to mandates from recent legislation, clinical decision support (CDS) software is being adopted by radiology practices across the country. This software provides imaging study decision support for referring providers at the point of order entry. CDS systems produce a large volume of data, providing opportunities for research and quality improvement. In order to better visualize and analyze trends in this data, an interactive data visualization dashboard was created using a commercially available data visualization platform. Following the integration of a commercially available clinical decision support product into the electronic health record, a dashboard was created using a commercially available data visualization platform (Tableau, Seattle, WA). Data generated by the CDS were exported from the data warehouse, where they were stored, into the platform. This allowed for real-time visualization of the data generated by the decision support software. The creation of the dashboard allowed the output from the CDS platform to be more easily analyzed and facilitated hypothesis generation. Integrating data visualization tools into clinical decision support tools allows for easier data analysis and can streamline research and quality improvement efforts.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2018

Efficiency Improvement in a Busy Radiology Practice: Determination of Musculoskeletal Magnetic Resonance Imaging Protocol Using Deep-Learning Convolutional Neural Networks

The purposes of this study are to evaluate the feasibility of protocol determination with a convolutional neural networks (CNN) classifier based on short-text classification and to evaluate the agreements by comparing protocols determined by CNN with those determined by musculoskeletal radiologists. Following institutional review board approval, the database of a hospital information system (HIS) was queried for lists of MRI examinations, referring department, patient age, and patient gender. These were exported to a local workstation for analyses: 5258 and 1018 consecutive musculoskeletal MRI examinations were used for the training and test datasets, respectively. The subjects for pre-processing were routine or tumor protocols and the contents were word combinations of the referring department, region, contrast media (or not), gender, and age. The CNN Embedded vector classifier was used with Word2Vec Google news vectors. The test set was tested with each classification model and results were output as routine or tumor protocols. The CNN determinations were evaluated using the receiver operating characteristic (ROC) curves. The accuracies were evaluated by a radiologist-confirmed protocol as the reference protocols. The optimal cut-off values for protocol determination between routine protocols and tumor protocols was 0.5067 with a sensitivity of 92.10%, a specificity of 95.76%, and an area under curve (AUC) of 0.977. The overall accuracy was 94.2% for the ConvNet model. All MRI protocols were correct in the pelvic bone, upper arm, wrist, and lower leg MRIs. Deep-learning-based convolutional neural networks were clinically utilized to determine musculoskeletal MRI protocols. CNN-based text learning and applications could be extended to other radiologic tasks besides image interpretations, improving the work performance of the radiologist.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2017

Heterologous expression of a β- d -glucosidase in Caldicellulosiruptor bescii has a surprisingly modest effect on the activity of the exoproteome and growth on crystalline cellulose

Abstract Members of the genus Caldicellulosiruptor are the most thermophilic cellulolytic bacteria so far described and are capable of efficiently utilizing complex lignocellulosic biomass without conventional pretreatment. Previous studies have shown that accumulation of high concentrations of cellobiose and, to a lesser extent, cellotriose, inhibits cellulase activity both in vivo and in vitro and high concentrations of cellobiose are present in C. bescii fermentations after 90 h of incubation. For some cellulolytic microorganisms, β-d-glucosidase is essential for the efficient utilization of cellobiose as a carbon source and is an essential enzyme in commercial preparations for efficient deconstruction of plant biomass. In spite of its ability to grow efficiently on crystalline cellulose, no extracellular β-d-glucosidase or its GH1 catalytic domain could be identified in the C. bescii genome. To investigate whether the addition of a secreted β-d-glucosidase would improve growth and cellulose utilization by C. bescii, we cloned and expressed a thermostable β-d-glucosidase from Acidothermus cellulolyticus (Acel_0133) in C. bescii using the CelA signal sequence for protein export. The effect of this addition was modest, suggesting that β-d-glucosidase is not rate limiting for cellulose deconstruction and utilization by C. bescii.

09 BIOMASS FUELS↗

DOE OSTI2022

A Decision-Making Machine Learning Approach in Hermite Spectral Approximations of Partial Differential Equations

The accuracy and effectiveness of Hermite spectral methods for the numerical discretization of partial differential equations on unbounded domains are strongly affected by the amplitude of the Gaussian weight function employed to describe the approximation space. This is particularly true if the problem is under-resolved, i.e., there are no enough degrees of freedom. The issue becomes even more crucial when the equation under study is time-dependent, forcing in this way the choice of Hermite functions where the corresponding weight depends on time. In order to adapt dynamically the approximation space, it is here proposed an automatic decision-making process that relies on machine learning techniques, such as deep neural networks and support vector machines. The algorithm is numerically tested with success on a simple 1D problem, but the main goal is its exportability in the context of more serious applications. Here we also show at the end an application in the framework of plasma physics.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Advancing nuclear forensics competencies at the National Nuclear Center of the Republic of Kazakhstan and conceptual development of a National Nuclear Forensics Library

Since 2021, the National Nuclear Center (NNC) of the Republic of Kazakhstan has been successfully developing a project dedicated to nuclear forensics. The relevance of this project is underscored by Kazakhstan’s leading position in the global uranium mining and export market. The country operates research reactors and is involved in the production of experimental nuclear fuel. The nuclear forensics project is being implemented in several key areas: the project will develop competencies in laboratory research of samples, interpretation of results, and develop a prototype concept for the National Nuclear Forensics Library. In implementing these challenges, the NNC experts draw on the experience of colleagues from world-leading scientific and research centers. Designing a prototype National Nuclear Forensics Library (NNFL) is a challenging project. In conclusion, the solution to this task is based on the IAEA’s approaches, recommendations, and the experience gained from the construction of similar systems in other countries.

and nuclear chemistry↗

DOE OSTI2019

Evaluation of Impact of Potential Extreme Rainfall Events on Mining in Peru

The impact that climate change may play in the future sustainability of mining projects has become increasingly important for the mining industry and its stakeholders. The most significant areas of concern are mine infrastructure, supply chains, health and safety conditions, environmental management, community relations and exploration. This is particularly relevant to mining in a country as climatically vulnerable as Peru. This study focuses on the identification of mining regions and main commodities in Peru that are potentially vulnerable to future extreme rainfall events associated with climate change. From a mine design and planning perspective, this study is a first step to illustrate the importance of considering the impacts of different climatic scenarios on mining in Peru. Based on HadGEM2-ES global climate model projections, mining regions across Peru were clustered into “super-regions” with differing potentials of extreme rainfall events during the next three decades. Five indices for precipitation extremes were used, and their variations between 1971–2000 and 2015–2034 were computed. Current and future metallic mining projects expected to take place across Peru in the next 30 years were retrieved from a mining database and subsequently exported into a geographical information systems software to represent their location and interpolate the variation for each precipitation extreme index. The results of this study point out at a decreasing trend in rainfall extremes intensity and frequency in regions of southern Peru. For copper projects located in these regions, a decrease in rainfall events could also imply an eventual decrease in total precipitation and consequently a deficit in water availability during the next three decades. Mining regions in central Peru, with significant number of zinc projects, are likely to experience a marked increase in overall annual precipitation, average daily precipitation intensity, consecutive days of precipitation and number of heavy precipitation days. At a lesser extent than in central Peru, gold projects in northern Peru are also likely to experience an overall increase in precipitation extremes. The approach used for this research could be extended to other mining regions around the world with extreme weather events.

58 GEOSCIENCES↗

DOE OSTI2025

Empirical evidence that glucan-interacting amino acid side chains within the transmembrane channel collectively facilitate cellulose synthase function

The fundamental mechanism of cellulose synthesis is widely conserved across Kingdoms and depends on cellulose synthases, which are processive, dual-function, family 2 glycosyltransferases (GT-2). These enzymes polymerize glucose on the cytoplasmic side of the plasma membrane and export the glucan chain to the cell surface through an integral transmembrane (TM) channel. Structural studies of active plant cellulose synthases (CESAs) have revealed interactions between the nascent glucan chain and the side chains of polar, charged, and aromatic amino acid residues that line the TM channel. However, the functional consequences of modifying these side chains have not been tested in vivo in CESAs or other processive GT-2s. To test this, we used an established in vivo assay based on genetic complementation of CESA5 in the moss, Physcomitrium patens. For accurate prediction of glucan-interacting amino acid residues, we generated a complete homotrimeric molecular model of PpCESA5 using a combination of homology and de novo modeling. All-atom molecular dynamics-based analyses of contact metrics and interaction energy identified 23 amino acid residues with high propensity to interact with the nascent glucan chain within the TM channel or on the apoplastic surface of PpCESA5. Mutating any one of 18 of these amino acid residues to alanine, thereby removing their side chains, abolished or impaired CESA function, with the strongest effects observed upon the loss of charged amino acid side chains. This provides direct evidence to support the hypothesis that multiple amino acid residues collectively maintain a smooth energy landscape within the TM channel to facilitate glucan translocation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Static Thermochemical Model of COREX Melter Gasifier

COREX is one of the commercial smelting reduction processes. It uses the finer size ore and semi-soft coal instead of metallurgical coke to produce hot metal from iron ore. The use of top gas with high calorific value as a by-product export gas makes the process economical and green. The predictive thermochemical model of the COREX process presented here enables rapid computation of process parameters such as (1) required amount of ore, coal, and flux; (2) amount of slag and gas generated; and (3) gas compositions (based on the raw material and desired hot metal quality). The model helps in predicting the variations in process parameters with respect to the (1) degree of metallization and (2) post-combustion ratio for given raw material conditions. In general reduction in coal, flux, and oxygen, the requirement is concomitant with an increase in the degree of metallization and post-combustion ratio. The model reported here has been benchmarked using industrial data obtained from the JSW Steel Plant, India.

01 COAL, LIGNITE, AND PEAT↗