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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Measurement of Heat of Vaporization for Research Gasolines and Ethanol Blends by DSC/TGA

The heat of vaporization (HOV) is a relatively poorly studied fuel property that can be related to a fuel's evaporation characteristics and knock resistance and, therefore, the emissions and efficiency of direct-injection spark-ignition engines. Methods for measuring the HOV of complex gasoline mixtures and blends of gasoline with ethanol and other oxygenates require additional development. Recently, we described a differential scanning calorimetry/thermogravimetric (DSC/TGA) method to perform HOV measurements. Herein we describe a detailed investigation of factors affecting the precision and accuracy of the DSC/TGA method and examine enthalpy evolution and mass loss rate for research gasolines as a function of fraction evaporated. Examination of n-hexane evaporation using several DSC/TGA pan/lid configurations showed that initial sample loss can be reduced using a well-fitting pinhole lid on the sample pan, which reduces the evaporation rate during the balance of the experiment. However, additional experiments with research gasolines revealed that tight lid placement on the pans is not always achieved. Nevertheless, accurate total HOV measurements, with less than 10% initial sample loss, could be achieved for low volatility gasolines regardless of lid placement. A higher mass loss might be expected for higher vapor pressure (wintertime) gasolines. Because of variations in pan lids and their placement and their significant impact on results, quantitative comparisons between different samples of mass loss rate and heat flow curves versus time or fraction evaporated are not yet possible. However, features in the mass loss rate and heat flow curves are reproducible. Furthermore, results show that ethanol-gasoline blend evaporation is highly influenced by the formation of near-azeotropic mixtures of ethanol and specific gasoline components, causing a flattening of the mass and heat curves, with a sharp evaporation rate reduction after the ethanol is evaporated.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2014

Characterization of the ETEL and HZC 3-inch PMTs for the KM3NeT project

The KM3NeT collaboration constructs a multi-cubic-kilometer scale neutrino telescope in the Mediterranean Sea. The telescope’s detection units, deployed in the deep sea, will be instrumented with facet like Digital Optical Modules (DOMs), each housing 31 three-inch photomultiplier tubes (PMTs) and readout electronics inside of 17-inch pressure resistant glass sphere. Two companies, ET Enterprises Ltd (ETEL) from UK and HZC from China developed new 3-inch PMTs to meet KM3NeT requirements. 126 PMTs of types D783KFLA, D792KFLA, and D793KFLA from ETEL and 7 PMTs of type XP53 from HZC have been delivered to KM3NeT and tested by the KM3NeT groups of NIKHEF-Amsterdam and ECAP-Erlangen. Tests have been performed to measure the main PMT parameters listed in the KM3NeT specifications, such as gain, transit time spread, dark rate, fraction of spurious pulses, and quantum efficiency. Methods and results are presented in this report.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Structural and transport properties of metallic and semiconducting Sb{sub 2}Te{sub 3} alloy

Metallic and semiconducting Sb{sub 2}Te{sub 3} alloys have been synthesized by controlling the cooling rate in the solid state reaction method. Temperature dependent resistivity is measured down to 10 K for the identification of metallic and semiconducting phases. Structural studies are performed by both X-ray diffraction (XRD) and Raman spectroscopic analyses. XRD study confirms single phase nature of polycrystalline alloys in the detectable limit. Raman spectroscopy is used to understand the vibration properties of Sb{sub 2}Te{sub 3} crystals. Widening of full width at half maxima of the highest intense peak in the XRD analysis indicates higher amount of defects in the semiconducting phase than that in the metallic one. Raman study indicates presence of impurity phases in the semiconducting Sb{sub 2}Te{sub 3}. The resistivity of semiconducting Sb{sub 2}Te{sub 3} sample is higher than that of metallic one, which corroborates with the XRD and Raman analyses.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

The JET hybrid scenario in Deuterium, Tritium and Deuterium-Tritium

The JET hybrid scenario has been developed from low plasma current carbon wall discharges to the record-breaking Deuterium-Tritium plasmas obtained in 2021 with the ITER-like Be/W wall. The development started in pure Deuterium with refinement of the plasma current, and toroidal magnetic field choices and succeeded in solving the heat load challenges arising from 37 MW of injected power in the ITER like wall environment, keeping the radiation in the edge and core controlled, avoiding MHD instabilities and reaching high neutron rates. The Deuterium hybrid plasmas have been re-run in Tritium and methods have been found to keep the radiation controlled but not at high fusion performance probably due to time constraints. For the first time this scenario has been run in Deuterium-Tritium (50:50). These plasmas were re-optimised to have a radiation-stable H-mode entry phase, good impurity control through edge T i gradient screening and optimised performance with fusion power exceeding 10 MW for longer than three alpha particle slow down times, 8.3 MW averaged over 5 s and fusion energy of 45.8 MJ.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Performance Test Protocol for Evaluating Inverters Used in Grid-Connected Photovoltaic Systems

Interconnection equipment that connects distributed resources (DR) to an electrical power system (EPS) are expected to do so efficiently. Standardized test procedures are necessary to establish methods for verifying inverter performance that leads to comparable results. These test procedures are provided as a repeatable, independent means of measuring inverter performance regarding maximum continuous power rating, conversion efficiency, and tare loss characteristics.

14 SOLAR ENERGY↗
DOE OSTI2022

Characterization of Particle and Heat Losses from a High-Temperature Particle Receiver (2 nd Ed)

High - temperature particle receivers are being pursued to enable next - generation concentrating solar thermal power (CSP) systems that can achieve higher temperatures (> 700 C) to enable more efficient power cycles, lower overall system costs, and emerging CSP - based process - heat applications. The objective of this work was to develop characterization methods to quantify the particle and heat losses from the open aperture of the particle receiver. Novel camera - based imaging methods were developed and applied to both laboratory - scale and larger 1 MW t on - sun tests at the National Solar Thermal Test Facility in Albuquerque, New Mexico. Validation of the imaging methods was performed using gravimetric and calorimetric methods. In addition, conventional particle - sampling methods using volumetric particle - air samplers were applied to the on - sun tests to compare particle emission rates with regulatory standards for worker safety and pollution. Novel particle sampling methods using 3 - D printed tipping buckets and tethered balloons were also developed and applied to the on - sun particle - receiver tests. Finally, models were developed to simulate the impact of particle size and wind on particle emissions and concentrations as a function of location. Results showed that particle emissions and concentrations were well below regulatory standards for worker safety and pollution. In addition, estimated particle temperatures and advective heat losses from the camera - based imaging methods correlated well with measured values during the on - sun tests.

14 SOLAR ENERGY↗
DOE OSTI2025

Beyond Magic Barrels: Digital manufacturing for crystallization, process development and optimization of explosive materials: Part II Resveratrol Exemplar

This SAND report summarizes work supported by an Engineering Sciences Research Foundation (ESRF) Lab Directed Research and Development (LDRD) project entitled “Beyond Magic Barrels: Digital manufacturing for crystallization, process development and optimization of explosive materials.” This SAND report is written in two parts with Part 1 discusses recrystallization of our explosive exemplar and Part 2 summarizing our work with recrystallization of resveratrol. We have studied resveratrol recrystallization with a multiscale approach combining experiments, modeling and simulation. At the single crystal scale, microscopy experiments illuminate crystal time-dependent growth rates using advanced image analysis. Bench scale experiments were carried out to look at growth of multiple particles in a small reactor creating thousands of particles and analyzing the results with microscopy and μCT. For the modeling we combine kinetic Monte Carlo (kMC) models with subscale information from density functional theory (DFT) or molecular dynamics. This work is discussed in Part 1 and can also be found in a paper from the project discussing a coarse-grained kMC model specifically developed for resveratrol. For well-mixed systems, we have population balance equations (PBE) linked with species mass conservation forming a set of ordinary differential equations that can be solved quickly. For more complicated geometries, such as the vat crystallization used throughout the complex, a coupled computational fluid dynamic (CFD)/PBE method was developed to account for gradients in temperature and concentration and differences in crystallization rates throughout the domain. These simulations are more complex and require high performance computing. We present results for two cases: 5% seed fast cool with parameters fit to the well-mixed case and 5% seed slow cool using the same parameters. We show reasonable agreement with experiments though are particles are significantly larger than the experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2017

DYNAMIC PRA WITH COMPONENT AGING AND DEGRADATION MODELED UTILIZING PLANT RISK MONITORING DATA

In the nuclear industry, risk monitors are intended to provide a point-in-time estimate of the system risk given the current plant configuration. Current risk monitors are limited in that they do not properly take into account the deteriorating states of plant systems, structures, and components (SSCs), which are unit-specific. Current approaches to computing risk monitors use probabilistic risk assessment (PRA) techniques, but the assessment is typically a snapshot in time. Living PRA models attempt to address limitations of traditional PRA models in a limited sense by including temporary changes in plant and system configurations. However, information on plant component health are not considered. This often leaves risk monitors using living PRA models incapable of conducting evaluations with dynamic degradation scenarios evolving over time. There is a need to develop enabling approaches to solidify risk monitors to provide time and condition-dependent risk by integrating traditional PRA models with condition monitoring and prognostic techniques [1]. This paper presents a novel hazard-rate based model of incorporating degradation of nuclear SSCs into an existing PRA model. Time-varying instantaneous hazard-rate of component is used to model degradation based on time-varying performance measure. The instantaneous hazard-rate is used to determine and update time-varying probability of failure of the components in their PRA models. The method is applied to estimate evolution of probability of failure of an in-service pump using vibration measurement taken while the pump undergoes degradation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Passive acoustic leak detection for sodium cooled fast reactors using hidden Markov models

Acoustic leak detection for steam generators of sodium fast reactors have been an active research topic since the early 1970's and several methods have been tested over the years. Inspired by its success in the field of automatic speech recognition, we here apply hidden Markov models (HMM) in combination with Gaussian mixture models (GMM) to the problem. To achieve this, we propose a new feature calculation scheme, based on the temporal evolution of the power spectral density (PSD) of the signal. Using acoustic signals recorded during steam/water injection experiments done at the Indira Gandhi Centre for Atomic Research (IGCAR), the proposed method is tested. We perform parametric studies on the HMM+GMM model size and demonstrate that the proposed method a) performs well without a priori knowledge of injection noise, b) can incorporate several noise models and c) has an output distribution that simplifies false alarm rate control. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

A Thermal Model for the Performance Analysis of Large Scale Spent Fuel Cooling Pond - 19173

This paper presents a thermal model for the performance analysis of a large scale cooling pond for the long term storage of spent nuclear fuel. The model has been developed using the knowledge gained from fundamental investigation using CFD and has been validated by comparing against reliable experimental and/or numerical data. It was then applied in the context of operation of a large scale pond to ascertain the sensitivity of various operational and environmental conditions. To develop the model, the water body along with the heating elements was considered as one zone and humid air inside the building as another zone, both of which are considered as well-mixed zones. Various input conditions namely, total heat load from the heat source, environmental temperature and relative humidity, ventilation rate, efficiency of the cooling tower, recirculation and make-up water flow rates have been programmed in the model. The statistical method AVONA has been used to assess the influence of the above variables. The results reveal that the efficiency of the cooling tower is the most influential parameter on the cooling performance of cooling pond within the considered values of heat load. It has also been found that the majority of the heat is taken by the recirculating water for very high heat load while the other modes of heat transfer are small but not insignificant. The model is capable of simulating the scenario of loss of cooling water and suggests that it can be used for managing a large pond efficiently as well as recovery from an accident situation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Subplane-based Control Rod Decusping Techniques for the 2D/1D Method in MPACT

The MPACT transport code is being jointly developed by Oak Ridge National Laboratory and the University of Michigan to serve as the primary neutron transport code for the Virtual Environment for Reactor Applications Core Simulator. MPACT uses the 2D/1D method to solve the transport equation by decomposing the reactor model into a stack of 2D planes. A fine mesh flux distribution is calculated in each 2D plane using the Method of Characteristics (MOC), then the planes are coupled axially through a 1D NEM-P$_3$ calculation. This iterative calculation is then accelerated using the Coarse Mesh Finite Difference method. One problem that arises frequently when using the 2D/1D method is that of control rod cusping. This occurs when the tip of a control rod falls between the boundaries of an MOC plane, requiring that the rodded and unrodded regions be axially homogenized for the 2D MOC calculations. Performing a volume homogenization does not properly preserve the reaction rates, causing an error known as cusping. The most straightforward way of resolving this problem is by refining the axial mesh, but this can significantly increase the computational expense of the calculation. The other way of resolving the partially inserted rod is through the use of a decusping method. This paper presents new decusping methods implemented in MPACT that can dynamically correct the rod cusping behavior for a variety of problems.

Graham, Aaron M↗
DOE OSTI2016

SU-F-P-39: End-To-End Validation of a 6 MV High Dose Rate Photon Beam, Configured for Eclipse AAA Algorithm Using Golden Beam Data, for SBRT Treatments Using RapidArc

Purpose: To use end-to-end testing to validate a 6 MV high dose rate photon beam, configured for Eclipse AAA algorithm using Golden Beam Data (GBD), for SBRT treatments using RapidArc. Methods: Beam data was configured for Varian Eclipse AAA algorithm using the GBD provided by the vendor. Transverse and diagonals dose profiles, PDDs and output factors down to a field size of 2×2 cm2 were measured on a Varian Trilogy Linac and compared with GBD library using 2% 2mm 1D gamma analysis. The MLC transmission factor and dosimetric leaf gap were determined to characterize the MLC in Eclipse. Mechanical and dosimetric tests were performed combining different gantry rotation speeds, dose rates and leaf speeds to evaluate the delivery system performance according to VMAT accuracy requirements. An end-to-end test was implemented planning several SBRT RapidArc treatments on a CIRS 002LFC IMRT Thorax Phantom. The CT scanner calibration curve was acquired and loaded in Eclipse. PTW 31013 ionization chamber was used with Keithley 35617EBS electrometer for absolute point dose measurements in water and lung equivalent inserts. TPS calculated planar dose distributions were compared to those measured using EPID and MapCheck, as an independent verification method. Results were evaluated with gamma criteria of 2% dose difference and 2mm DTA for 95% of points. Results: GBD set vs. measured data passed 2% 2mm 1D gamma analysis even for small fields. Machine performance tests show results are independent of machine delivery configuration, as expected. Absolute point dosimetry comparison resulted within 4% for the worst case scenario in lung. Over 97% of the points evaluated in dose distributions passed gamma index analysis. Conclusion: Eclipse AAA algorithm configuration of the 6 MV high dose rate photon beam using GBD proved efficient. End-to-end test dose calculation results indicate it can be used clinically for SBRT using RapidArc.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

A novel approach to assess the treatment response using Gaussian random field in PET

Purpose: The assessment of early therapeutic response to anticancer therapy is vital for treatment planning and patient management in clinic. With the development of personal treatment plan, the early treatment response, especially before any anatomically apparent changes after treatment, becomes urgent need in clinic. Positron emission tomography (PET) imaging serves an important role in clinical oncology for tumor detection, staging, and therapy response assessment. Many studies on therapy response involve interpretation of differences between two PET images, usually in terms of standardized uptake values (SUVs). However, the quantitative accuracy of this measurement is limited. This work proposes a statistically robust approach for therapy response assessment based on Gaussian random field (GRF) to provide a statistically more meaningful scale to evaluate therapy effects. Methods: The authors propose a new criterion for therapeutic assessment by incorporating image noise into traditional SUV method. An analytical method based on the approximate expressions of the Fisher information matrix was applied to model the variance of individual pixels in reconstructed images. A zero mean unit variance GRF under the null hypothesis (no response to therapy) was obtained by normalizing each pixel of the post-therapy image with the mean and standard deviation of the pretherapy image. The performance of the proposed method was evaluated by Monte Carlo simulation, where XCAT phantoms (128{sup 2} pixels) with lesions of various diameters (2–6 mm), multiple tumor-to-background contrasts (3–10), and different changes in intensity (6.25%–30%) were used. The receiver operating characteristic curves and the corresponding areas under the curve were computed for both the proposed method and the traditional methods whose figure of merit is the percentage change of SUVs. The formula for the false positive rate (FPR) estimation was developed for the proposed therapy response assessment utilizing local average method based on random field. The accuracy of the estimation was validated in terms of Euler distance and correlation coefficient. Results: It is shown that the performance of therapy response assessment is significantly improved by the introduction of variance with a higher area under the curve (97.3%) than SUVmean (91.4%) and SUVmax (82.0%). In addition, the FPR estimation serves as a good prediction for the specificity of the proposed method, consistent with simulation outcome with ∼1 correlation coefficient. Conclusions: In this work, the authors developed a method to evaluate therapy response from PET images, which were modeled as Gaussian random field. The digital phantom simulations demonstrated that the proposed method achieved a large reduction in statistical variability through incorporating knowledge of the variance of the original Gaussian random field. The proposed method has the potential to enable prediction of early treatment response and shows promise for application to clinical practice. In future work, the authors will report on the robustness of the estimation theory for application to clinical practice of therapy response evaluation, which pertains to binary discrimination tasks at a fixed location in the image such as detection of small and weak lesion.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

Discrete-Direct Model Calibration and Uncertainty Propagation Method Confirmed on Multi-Parameter Plasticity Model Calibrated to Sparse Random Field Data

A discrete direct (DD) model calibration and uncertainty propagation approach is explained and demonstrated on a 4-parameter Johnson-Cook (J-C) strain-rate dependent material strength model for an aluminum alloy. The methodology's performance is characterized in many trials involving four random realizations of strain-rate dependent material-test data curves per trial, drawn from a large synthetic population. The J-C model is calibrated to particular combinations of the data curves to obtain calibration parameter sets which are then propagated to “Can Crush” structural model predictions to produce samples of predicted response variability. These are processed with appropriate sparse-sample uncertainty quantification (UQ) methods to estimate various statistics of response with an appropriate level of conservatism. This is tested on 16 output quantities (von Mises stresses and equivalent plastic strains) and it is shown that important statistics of the true variabilities of the 16 quantities are bounded with a high success rate that is reasonably predictable and controllable. The DD approach has several advantages over other calibration-UQ approaches like Bayesian inference for capturing and utilizing the information obtained from typically small numbers of replicate experiments in model calibration situations—especially when sparse replicate functional data are involved like force–displacement curves from material tests. The DD methodology is straightforward and efficient for calibration and propagation problems involving aleatory and epistemic uncertainties in calibration experiments, models, and procedures.

42 ENGINEERING↗
DOE OSTI2014

Performance study of LMS based adaptive algorithms for unknown system identification

Adaptive filtering techniques have gained much popularity in the modeling of unknown system identification problem. These techniques can be classified as either iterative or direct. Iterative techniques include stochastic descent method and its improved versions in affine space. In this paper we present a comparative study of the least mean square (LMS) algorithm and some improved versions of LMS, more precisely the normalized LMS (NLMS), LMS-Newton, transform domain LMS (TDLMS) and affine projection algorithm (APA). The performance evaluation of these algorithms is carried out using adaptive system identification (ASI) model with random input signals, in which the unknown (measured) signal is assumed to be contaminated by output noise. Simulation results are recorded to compare the performance in terms of convergence speed, robustness, misalignment, and their sensitivity to the spectral properties of input signals. Main objective of this comparative study is to observe the effects of fast convergence rate of improved versions of LMS algorithms on their robustness and misalignment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Dynamic Strength and Equation of State of Epon 828 and Diethanolamine (DEA) Polymer Epoxy Under Shock Loading

Polymers are increasingly utilized in engineering applications that can experience high loading rates, necessitating increased understanding of their response under such conditions. The tamped Richtmyer-Meshkov Instability (RMI) method was used to characterize the equation of state and dynamic strength of the polymer Epon 828 cured with Diethanolamine (DEA). Plate impact experiments that drove a uniaxial shock compression wave across a sinusoidally corrugated metal-polymer interface were performed to generate shock stresses from 4-12 GPa and strain rates of approximately 1/s in the polymer. X-ray phase contrast imaging recorded the shock motion in the polymer and subsequent interface evolution. Analysis of this data yielded the polymer equation of state and, in conjunction with numerical modeling, the dynamic strength. The equation of state was validated against one-dimensional plate impact experiments from existing literature. The dynamic strength was compared to prior data for Epon 828 and related polymers at lower strain rates and found to exhibit significant strain rate and pressure-hardening effects. The strength of the Epon 828 polymer at 10 6 1/s was found to be approximately 1.5 GPa, suggesting that it is comparable to the strength of high strength metals at these dynamic conditions.

Equation of state↗
DOE OSTI2021

Analysis of PNAR Spent Fuel Safeguards Measurements using the ORIGEN Data Analysis Module

This paper summarizes the analysis of the Passive Neutron Albedo Reactivity (PNAR) measurements using the ORIGEN data analysis module for 23 boiling water reactor spent fuel assemblies that were performed in Finland under an international collaboration on spent fuel safeguards verification methods. PNAR is part of the proposed integrated nondestructive system to be used for safeguards verifications at the planned Finnish encapsulation facility. Besides measuring passive neutron and gamma emission rates from an assembly like a Fork detector, PNAR also measures the PNAR ratio, which is expected to correlate with the fissile content in the assembly. The emission rates and PNAR ratio can be used to verify the operator declarations and the fissile content of an assembly, respectively. The analysis was performed using the ORIGEN Data Analysis Module, which was originally developed for predicting Fork detector neutron and gamma signals for spent fuel measurements and has been integrated into the Integrated Review and Analysis Package developed by Euratom and the IAEA. The Module includes the ORIGEN burnup analysis code and integrates detector response functions pre-generated using MCNP to predict detector signals in several seconds per assembly. In this study, new response functions specific to PNAR measurements were generated for ORIGEN Module. The study also analyzes impacts of using detailed fuel design and operation information vs. standard safeguards information on results calculated by ORIGEN Module. Using detailed information reduced the standard deviation of relative differences between calculated and measured neutron count rates among the 23 assemblies from ~10% to ~4%. The results obtained using standard safeguards information for these PNAR measurements were similar to those obtained for the Fork detector. A clear trend was found between the calculated net neutron multiplications and the measured PNAR ratios of the 23 assemblies. This paper describes how ORIGEN Module calculates the expected PNAR neutron and gamma signals and PNAR ratio and how they compare with corresponding measured values.

Ilas, Germina↗
DOE OSTI2016

Nonintrusive Uncertainty Quantification of Computational Fluid Dynamics Simulations of a Bench-Scale Fluidized-Bed Gasifier

Uncertainty quantification (UQ) analysis is increasingly becoming one of the major requirements of simulation-based engineering to assess the confidence in the results and make better-informed decisions based on the insight derived from the simulations. In an earlier study, Bayesian UQ analysis was applied to existing bench-scale fluidized-bed gasifier experiment results. In the current study, a series of simulations were carried over with the open-source computational fluid dynamics software MFiX to reproduce the experimental conditions, where three operating factors, i.e., coal flow rate, coal particle diameter, and steam-to-oxygen ratio, were systematically varied to understand their effect on the syngas composition. Bayesian UQ analysis was this time performed on the numerical results for comparison purposes. This is part of ongoing research efforts to explore the applicability of advanced UQ methods and processes such as Bayesian methods for large-scale complex multiphase flow simulations. As part of Bayesian UQ analysis, a global sensitivity analysis was performed based on the simulation results, which shows that the predicted syngas composition is strongly affected not only by the steam-to-oxygen ratio (which was observed in experiments as well) but also by variation in the coal flow rate and particle diameter (which was not observed in experiments). The carbon monoxide mole fraction is underpredicted at lower steam-to-oxygen ratios and overpredicted at higher steam-to-oxygen ratios. The opposite trend is observed for the carbon dioxide mole fraction. These discrepancies are attributed to either excessive segregation of the phases that leads to the fuel-rich or -lean regions or alternatively the selection of reaction models, where different reaction models and kinetics can lead to different syngas compositions throughout the gasifier.

01 COAL, LIGNITE, AND PEAT↗