Combustion Conditions Research Articles

Monitoring of Thermoacoustic Combustion Instability via Recurrence Quantification Analysis and Optimized Deep Belief Network

Thermoacoustic oscillation is indeed a phenomenon characterized by the symmetric coupling of thermal and acoustic waves. This paper introduces a novel approach for monitoring and predicting thermoacoustic combustion instability using a combination of recurrence quantification analysis (RQA) and an optimized deep belief network (DBN). Six samples of combustion state data were collected using two distinct types of burners to facilitate the training and validation of GA-DBN. The proposed methodology leverages RQA to extract intricate patterns and dynamic features from time series data representing combustion behavior. By quantifying the recurrence plot of specific patterns, the analysis provides valuable insights into the underlying thermoacoustic dynamics. Among three different feature extraction methods, RQA stands out remarkably in performance. These RQA-derived features serve as input to a carefully tuned DBN, which is trained to learn the complex relationships within the combustion process. The classification accuracy of deep belief network optimized by genetic algorithm (GA-DBN) reached an impressive 99.8%. Subsequent multiple comparisons were conducted between GA-DBN, DBN, and support vector machine (SVM), revealing that GA-DBN consistently demonstrated satisfactory classification results. This method holds significant importance in monitoring intricate combustion states.

Graphitization: Microstructural and microtextural transformations of residual char from international coal combustion ash

Natural graphite is a critical raw material and its substitution in some applications will contribute to reduce its supply risk. Coal ash, which is still produced in high amounts, contains a carbonaceous solid residue (char) that may be a substitute of natural graphite. For this purpose, char may be graphitized and used in electrocatalysis reactions, however char properties depend on coal rank, composition and combustion conditions that affect the graphitization process. Research on industrial coal char graphitization is limited, resulting in restricted comprehension of the contributing factors. In order to provide novel insights, industrial residual chars (derived from Poland, Portugal, Romania and South Africa) subjected to high-temperature treatments (carbonization at 1000 °C followed by treatment at 2600 °C under environmental pressure) were examined regarding their microstructural and microtextural transformations. The samples were studied by focussing on its heterogeneity, namely its specific properties and interactions, including elemental composition, optical character, and structure. Furthermore, the evolution of structural order of selected char morphotypes in samples derived from coal of similar rank was assessed using Raman microspectroscopy.The results highlighted a set of aspects that could have influenced the transformations experienced by the different chars during high temperature treatments (graphitization). It was found that Hydrogen might play a role in the graphitization ability of isotropic chars derived from low rank coal. The prior preferential orientation of the Basic Structural Units (BSU) contributes to achieve a higher graphitization degree, but it can be enhanced or hindered by other factors, e.g., hydrogen content. Raman microspectroscopy showed that char morphotypes from the same group underwent different transformations during graphitization, indicating that morphotypes or sections with unfused optical character may be more prone to graphitization. However, the existence of disordered domains and specific microtextures, such as polyhedral pores identified under TEM, likely hindered further graphitization. Further research on this topic is needed.

Charcoal analysis for temperature reconstruction with infrared spectroscopy

The duration and maximum combustion temperature of vegetation fires are important fire properties with implications for ecology, hydrology, hazard potential, and many other processes. Directly measuring maximum combustion temperature during vegetation fires is difficult. However, chemical transformations associated with temperature are reflected in the chemical properties of charcoals (a by-product of fire). Therefore, charcoal could be used indirectly to determine the maximum combustion temperature of vegetation fires with application to palaeoecological charcoal records. To evaluate the reliability of charcoal chemistry as an indicator of maximum combustion temperature, we studied the chemical properties of charcoal formed through two laboratory methods at measured temperatures. Using a muffle furnace, we generated charcoal from the woody material of ten different tree and shrub species at seven distinct peak temperatures (from 200°C to 800°C in 100°C increments). Additionally, we simulated more natural combustion conditions by burning woody material and leaves of four tree species in a combustion facility instrumented with thermocouples, including thermocouples inside and outside of tree branches. Charcoal samples generated in these controlled settings were analyzed using Fourier Transform Infrared (FTIR) spectroscopy to characterize their chemical properties. The Modern Analogue Technique (MAT) was employed on FTIR spectra of muffle furnace charcoal to assess the accuracy of inferring maximum pyrolysis temperature. The MAT model temperature matching accuracy improved from 46% for all analogues to 81% when including ±100°C. Furthermore, we used MAT to compare charcoal created in the combustion facility with muffle furnace charcoal. Our findings indicate that the spectra of charcoals generated in a combustion facility can be accurately matched with muffle furnace-created charcoals of similar temperatures using MAT, and the accuracy improved when comparing the maximum pyrolysis temperature from muffle furnace charcoal with the maximum inner temperature of the combustion facility charcoal. This suggests that charcoal produced in a muffle furnace may be representative of the inner maximum temperatures for vegetation fire-produced charcoals.

Hybrid Algorithm for Development of Reduced Skeletal Kinetic Mechanisms with Specific Species Targeting.

A novel algorithm is introduced to reduce the number of detailed kinetic mechanisms. The algorithm uniquely employs a classification of species and a defined parameter that quantitatively identifies the contribution of each species under a combustion condition of interest with specific species targeting. It also incorporates sensitivity analysis, the directed relation graph (DRG) method, and dynamic refinement. The proposed procedure is applied to the GRI-3.0 mechanism with atmospheric pollutants (CO, CO2, NO, and NO2) targeted in a lean methane-air flame at high pressures. The performance of the reduced mechanism is assessed, and good accuracy with considerable computational cost reduction is achieved. Investigated properties by the perfectly stirred reactor (PSR) model incorporated adiabatic flame temperature and the concentrations of targeted pollutants versus equivalence ratio (0.5-1.2), pressure (1-14 bar), and residence time (0.001-1 s) variations. The maximum prediction errors of temperature and greenhouse gas (GHG) mole fractions' profiles were less than 1%, while NOx versus residence time showed errors of 11.7 and 4%, respectively. Additionally, the flame speed yielded a maximum deviation of less than 2%. The computational cost in a 2D (axisymmetric) simulation revealed a 61% reduction. It is shown that the introduced algorithm is effective and can be applied to large mechanisms aiming for particular species predictions under specified operating conditions with lower computational costs.

High Temperature Oxidation of Additively and Traditionally Manufactured Inconel 718

Abstract Additively manufactured nickel-based superalloys are now being considered as a replacement for traditionally manufactured components on commercial and military aircraft. While the potential of additive manufacturing for gas turbine engines is promising, the quality and performance of additive manufactured components still need extensive study. Coupon-sized test specimens comprised of as-printed additively and traditionally manufactured Inconel 718 with and without yttria-stabilized zirconia thermal barrier coating were tested under simulated isothermal and thermal cycling combustion conditions that were representative of gas turbine environments. Pre-test scanning electron microscopy indicated that traditionally manufactured coupons had a smooth surface finish with minor imperfections while additive manufactured coupons had a rough surface finish. Post-test scanning electron microscopy exhibited differences in oxide scale between the isothermal and thermal cycling conditions. The thermal cycling condition increased the amount of oxide scale for both additively manufactured and traditionally manufactured Inconel 718. The size of the oxide islands on traditionally manufactured coupons was significantly larger than the additively manufactured coupons. The results indicated that differences in surface roughness may affect the growth of the oxidation scale in a high-temperature combustion environment. The benefits of yttria-stabilized zirconia thermal barrier coating were characterized. The substrate of the coupons experienced little to no formation of oxide scales compared to the uncoated additive and traditionally manufactured coupons. The results further suggested that yttria-stabilized zirconia thermal barrier coating can be utilized to provide both insulation and oxidation protection when desired. Post-test energy-dispersive X-ray spectrometry results corresponded well with known elemental compositions and oxidation mechanisms.

A pyrolysis‐gas chromatography/mass spectrometry study of volatile compounds produced by wood‐based materials

AbstractThe pyrolysis by‐products of five common wood‐based construction materials (low‐density wood fiberboard, oriented strand board, pine, particle board, and plywood) were studied using pyrolysis‐gas chromatography/mass spectrometry. Samples of wood‐based materials were pyrolyzed under helium from 300 to 800°C to further understand the production of compounds that may become airborne and available for respiratory and dermal exposure. Benzene, toluene, ethylbenzene, p‐xylene, styrene, and naphthalene were specifically targeted since these compounds are common by‐products of pyrolysis. These compounds have been measured in previous live fire scenarios and are associated with human health concerns. The generated pyrolysates were separated and identified with a gas chromatography/mass spectrometry instrument. The results from total ion chromatograms and selected ion monitoring chromatograms were analyzed to compare the abundance of chemicals of interest generated during pyrolysis. Oriented strand board and plywood generated the greatest total concentration of the targeted volatile organic compounds. Plywood and particle boards generated the largest variety in results. Samples from solid pine boards generated the smallest number of volatile compounds, followed by low‐density wood fiberboard that is manufactured with wood fibers, starch, and wax. Notably, pyrolysis by‐products are not the sole compounds generated during the combustion of biomass and these products evolve when they are exposed to the conditions of combustion. Our future work plans to study the combustion by‐products of these materials.

Analysis of Carbon Nanoparticle Coatings via Wettability

Wettability, typically estimated through the contact angle, is a fundamental property of surfaces with wide-ranging implications in both daily life and industrial processes. Recent scientific interest has been paid to the surfaces exhibiting extreme wettability: superhydrophobic and superhydrophilic surfaces, characterized by high water repellency and exceptional water wetting, respectively. Both chemical composition and morphology play a role in the determination of the wettability “performance” of a surface. To tune surface-wetting properties, we considered coatings of carbon nanoparticles (CNPs) in this study. They are a new class of nanomaterials synthesized in flames whose chemistry, dimension, and shape depend on combustion conditions. For the first time, we systematically studied the wettability of CNP coatings produced in a controlled rich ethylene/air flame stabilized over a McKenna burner. A selected substrate was intermittently inserted in the flame at 15 mm above the burner to form a thin coating thanks to a thermophoretic-driven deposition mechanism. The chemical-physical quality and the deposed quantity of the CNPs were varied by opportunely combing the substrate flame insertion number (from 1 to 256) and the carbon-to-oxygen ratio, C/O (from 0.67 to 0.87). The wettability of the coatings was evaluated by measuring the contact angle, CA, with the sessile drop method. When the C/O = 0.67, the CNPs were nearly spherical, smaller than 8 nm, and always generated hydrophilic coatings (CA < 35°). At higher C/O ratios, the CNPs reached dimensions of 100 nm, and fractal shape aggregates were formed. In this case, either hydrophilic (CA < 76°) or superhydrophobic (CA ~166°) behavior was observed, depending on the number of carbon nanoparticles deposed, i.e., film thickness. It is known that wettability is susceptible to liquid surface tension, and therefore, tests were conducted with different fluids to establish a correlation between the flame conditions and the nanostructure of the film. This method offers a fast and simple approach to determining mesoscale information for coating roughness and topographical homogeneity/inhomogeneity of their surfaces.

SiCf/SiC composites tolerance to high temperature combustion atmosphere and post ageing mechanical and microstructural characterisation

This article reports the activities carried out under WP4, coordinated by ENEA, within the CEM-WAVE European project, about experimental study on SiCf/SiC composites tolerance to high temperature combustion atmosphere. Water corrosion phenomena are known to affect mechanical properties of SiC-based CMC, due to the formation of a silica, volatile in certain condition. The study will simulate combustion conditions, aiming at using more environmentally friendly alternatives to methane, such as hydrogen, coke oven gas or biomethane, in steel production. It is essential to determine, in each case, if corrosion happens in active (that means continuous degradation) or passive (silica forms a protective “scale” on the component) regime. Since fibre-to-matrix interface can also be degraded, it is important to determine post-ageing mechanical flexural strength (by 4point bending tests). Water corrosion ageing was performed by means of direct flame exposure. When the oxidizing species becomes CO2, instead of O2, the formation rate of silica passivating layer is expected to be lower than the volatilization rate, and consequently active oxidation results in continuous weight loss. Ageing tests of SiCf/SiC composites were carried out at high temperature in a CO2/H2O/N2 gaseous environment at atmospheric pressure (reference conditions: 1200°C, 10/20/70 v/v). Bending tests up to failure are carried out at room temperature on these aged samples after different exposure times. Relationships are established between the evolution of mechanical properties, the ageing conditions, and the rates of oxidation reactions.

Study on CO source identification and spontaneous combustion warning concentration in the return corner of working face in shallow buried coal seam.

Coal spontaneous combustion is a common problem faced by many coal mines. Spontaneous combustion in goaf releases a large amount of harmful gases, polluting the environment while causing a large amount of wasted resources, and even endangering the lives of workers. Due to the collapse of the interior of the mining area, it is impossible to measure the internal gas composition directly. In order to more accurately predict the spontaneous combustion state inside the mining airspace, this paper obtains the CO generation law and the main source of the working face through the combination of laboratory experiments and on-site monitoring. The CO concentration prediction model of the return corner is established with CO as the index gas. Finally, the safe concentration and warning concentration of the working face are calculated according to the example, which provides theoretical basis for the prediction of spontaneous combustion of coal.

Research: influence of air classification ratio on low nitrogen performance of natural gas burner

ABSTRACT An innovative low-nitrogen natural gas burner was developed, leveraging air-staged combustion as the primary mechanism, supplemented by swirl combustion and flue gas recirculation technology. This design enables adaptation to a multitude of combustion conditions through the adjustment of the secondary air ratio. A prototype burner with a power output of 60 kW was constructed for experimental study. The velocity field, gas concentration field, temperature field, and NO x concentration within the combustion zone were analyzed under different load, and the impact of the secondary air ratio on the burner’s low-nitrogen combustion performance was explored. Experimental results showed that the burner can maintain stable combustion and low NO x emissions and had good load adaptability. The introduction of secondary air resulted in a “W”-shaped distribution characteristic within the combustion zone’s velocity and concentration fields, and effectively suppressed the formation of high-temperature zones, thereby reducing the generation of thermal NO x . A secondary air ratio of 27% significantly enhanced the gas atmosphere within the combustion zone, leading to more uniform gas distribution and improved mixing of the gas mixture. Furthermore, it had a better low-nitrogen performance. With an increase in burner load, the NO x concentration within the combustion zone also increased, reaching a peak value of 31 mg·m−3 at full-load, which still complied with low-nitrogen emission requirements.

Ignition behavior of a mixture of brown coal and biomass during the movement of fine particles in a hot air flow

The combustion of brown coal, biomass and their mixtures was studied experimentally and analytically. The experimental research was conducted using a laboratory setup that reproduced the conditions of combustion of pulverized solid fuel in a boiler furnace. Thermogravimetric analysis was employed as part of the analytical study to determine the key characteristics of combustion of solid fuels, such as temperatures at which the ignition and burnout occur, as well as the combustion index. Scanning electron microscopy was utilized to analyze the surfaces of coal and wood particles to detect pores, cracks and channels. To determine the tendency of the solid fuel mixture to slag heat exchangers in boiler furnaces, the ash residue characteristics (iron oxide deposits, active alkali, calcium sulfate compounds) were obtained. Biomass is more reactive than brown coal. Its ignition delay times at 500 °C and 750 °C are 57 % and 25 % lower, respectively, than those for coal. The higher the biomass content in the solid fuel mixture, the lower the ignition delay time. The heating source temperature at which the coal/biomass fuel mixture ignites corresponds to the temperature at which biomass ignites. With a larger proportion of biomass, the temperature during the fuel mixture combustion goes down, while the combustion index increases. On the basis of the findings of the conducted research, optimal proportions of solid fuel components were found (80 % brown coal, 20 % biomass). Also, fuel preparation and feeding systems for pulverized fuel combustion and fluidized bed combustion of optimal fuel mixtures in a coal-fired boiler furnace were proposed.

Multivariate Signal Prediction Using Attention Transfer Learning for Early Detection of Thermoacoustic Instabilities

The prediction and control of thermoacoustic instability play a crucial role in combustion systems. This paper presents a novel methodology that employs attention transfer learning for the prediction of multivariate thermoacoustic signals, including acoustic pressure and heat release rate. By leveraging attention transfer learning, the proposed model can be generalized to thermoacoustic signal prediction under a variety of conditions with little additional training resources. Experimental data from various conditions in annular combustors are employed to evaluate the predictive performance of the model. The results demonstrate its ability to accurately predict future pressure signals over a wide-ranging time horizon while maintaining consistent dynamics, thus providing valuable information for active control. The proposed model is expected to be an effective step toward a data-driven solution for the early detection of thermoacoustic instability.

Optimization of combustion strategy for application of sustainable fuels regarding elimination of vehicles emission footprint

Abstract Nowadays, transport generates a significant portion of greenhouse gas emissions and at the same time it is also one of the dominant polluters within urban agglomerations. However, vehicles with piston combustion engines are still the most popular choice of consumers thanks to the unquestionable advantages of these engines. There are currently several hundred million cars driven by combustion engines in EU-countries, and approximately one-and-a-half billion of worldwide. The only possible way to reduce the emission footprint of automotive transport while at the same time keeping the current fleet of combustion engine vehicles, is the application of synthetic fuels. Of course, hydrogen will have its place in the new green economy. A very promising idea is the low temperature combustion (LTC) technology. This technology combines the high efficiency of modern combustion engines with utilization of climate-neutral fuels. Therefore, the LTC technology can be a suitable solution for the sustainable future of the current vehicle fleet. The presented scientific article is focused on the development of dual-fuel technology, specifically on optimization of combustion conditions as well as on design of a new geometrical shape of the combustion chamber regarding minimization of engine emissions. This article also introduces a unique LTC system, which is characterized by significant achievements in reducing emissions. This innovative system together with design of a new geometrical shape are the subjects of patent protection.

Machine Learning-Based Modeling and Predictive Control of Combustion Phasing and Load in a Dual-Fuel Low-Temperature Combustion Engine

<div>Reactivity-controlled compression ignition (RCCI) engine is an innovative dual-fuel strategy, which uses two fuels with different reactivity and physical properties to achieve low-temperature combustion, resulting in reduced emissions of oxides of nitrogen (NO<sub>x</sub>), particulate matter, and improved fuel efficiency at part-load engine operating conditions compared to conventional diesel engines. However, RCCI operation at high loads poses challenges due to the premixed nature of RCCI combustion. Furthermore, precise controls of indicated mean effective pressure (IMEP) and CA50 combustion phasing (crank angle corresponding to 50% of cumulative heat release) are crucial for drivability, fuel conversion efficiency, and combustion stability of an RCCI engine. Real-time manipulation of fuel injection timing and premix ratio (PR) can maintain optimal combustion conditions to track the desired load and combustion phasing while keeping maximum pressure rise rate (MPRR) within acceptable limits.</div> <div>In this study, a model-based controller was developed to track CA50 and IMEP accurately while limiting MPRR below a specified threshold in an RCCI engine. The research workflow involved development of an imitative dynamic RCCI engine model using a data-driven approach, which provided reliable measured state feedback during closed-loop simulations. The model exhibited high prediction accuracy, with an <i>R</i><sup>2</sup> score exceeding 0.91 for all the features of interest. A linear parameter-varying state space (LPV-SS) model based on least squares support vector machines (LS-SVM) was developed and integrated into the model predictive controller (MPC). The controller parameters were optimized using genetic algorithm and closed-loop simulations were performed to assess the MPC’s performance. The results demonstrated the controller’s effectiveness in tracking CA50 and IMEP, with mean average errors (MAE) of 0.89 crank angle degree (CAD) and 46 kPa and Mean absolute percentage error (MAPE) of 9.7% and 7.1%, respectively, while effectively limiting MPRR below of 10 bar/CAD. This comprehensive evaluation showcased the efficacy of the model-based control approach in tracking CA50 and IMEP while constraining MPRR in the dual-fuel engine.</div>

Utilization of Agricultural By-Products as a Partial Replacement of Cement in Construction: A Review

Food and Shelter are the two main requirements for surviving in this cosmos. More than 50% of the geographical area of the country is under cultivation. After harvesting the rice crop there is a common practice to set fields on fire. This stubble burning creates havoc causing a large number of health hazards and also affects the soil properties. This method of decomposition of agricultural residue including rice straw and rice husk if replaced with some standard combustion conditions, temperature, and rapid cooling of ash produced, will prove beneficial to the construction industry. This review paper explores the possibility of utilizing these agricultural waste products i.e. Rice Straw Ash (RSA) and Rice Husk Ash (RHA) as a partial replacement of cement in concrete and analyzing the fresh and hardened properties of concrete. Research gaps and future scope of this study are also highlighted in this review paper. It has been observed that the physical, chemical, and strength properties of concrete are mostly affected by the pozzolan city of the ashes and compressive strength and tensile strength of concrete increases with increase in replacement level of cement with the agricultural ash up-to certain optimal levels. Various other factors that contribute to the enrichment of the existing properties of the resulting concrete include grinding, fineness and porosity of ashes.

Numerical Evaluation of Sodium Droplet Swarm Combustion and Its Modeling Optimization

Because of its superior thermal-hydraulic qualities, liquid sodium has been applied to a variety of industries, including energy storage, solar energy, sodium-cooled fast reactors, and aerospace. However, fires brought on by sodium leaks at high pressure can have major thermodynamic repercussions and put employees and equipment in use at risk directly or indirectly. As a result, a realistic and accurate forecast of the combustion behavior of sodium droplet swarm can offer technical backing for the use of liquid sodium in engineering as well as a way of sodium fire prevention and control. Spray dynamics (droplet settling, droplet particle size distribution, etc.), combustion kinetics (premixed combustion, gas phase combustion, etc.), sodium aerosol diffusion, and other specialized phenomena all contribute to the complex process of sodium droplet swarm combustion. The NACOM code created by Brookhaven National Laboratory for sodium droplet swarm combustion is utilized in this paper as a framework. The code is first validated using the benchmark of the sodium droplet swarm combustion tests carried out by prestigious institutions. The validation results demonstrate that the code’s drag model, droplet combustion model, and heat transfer model are to blame for the significantly overestimated thermodynamic effects of sodium droplet swarm combustion. NACOM is subsequently developed twice for the authors’ previously developed vapor-liquid two-layer-structure drag model, chemical kinetic combustion model, and suitable heat transfer coefficient. It is then thoroughly assessed for the separate-effects tests and integral-effects test. The evaluation results demonstrate that the optimized drag model accelerates the settling of sodium droplets due to the consideration of the sodium-vapor drag reduction effect, reducing the thermodynamic effects of liquid sodium combustion; the optimized premixed combustion model can accurately predict the low-temperature sodium droplet swarm combustion conditions, resolving the issue of serious misvaluation of the original version of NACOM. The associated research findings can serve as valuable resources and tools for deeper comprehension of the combustion effects and mechanisms of sodium droplet swarm under various operating settings (such as leakage rate and oxygen concentration).

Strong impact and engraving characteristics of multi-layer metallic materials under a two-stage combustion condition

Abstract This work is focused on the strong deformation motion mechanism of multi-layer metallic materials under extreme pressure conditions accompanied by a strong impact effect between the projectile composed of multi-layer metallic materials and the steel barrel of the launcher itself. Here, this transient engraving process of the projectile with complicated stress–strain based on a new type of structure and propulsion pattern is firstly studied by proposing a new physical and mathematical model with a coupling of dynamical equations and two-stage combustion ballistic equations. Comparisons of engraving distance of computational results are done with experimental studies, and a reasonable match has been obtained in these comparisons. Further, the thickness effect of the metal jacket of the projectile on the engraving stress and deformation level is analyzed to obtain universal engraving resistance equations. The results have also shown that the projectile's whole transient deformation motion process in the launcher can be divided into three periods due to the initial slide impact effect under the first-stage propellant gas and the later propelling effect as the second-stage propellant is ignited. However, the engraving durations are all less than 0.7 ms with different levels of elastic-plastic deformations between multi-layer metallic materials for different conditions.

Migration and transformation of phosphorus and toxic metals during sludge incineration with Ca additives

The recycling and utilization of phosphorus resources in sludge is becoming increasingly important. In this study, we compared the conversion of phosphorus and toxic metal passivation effects of different Ca additives under oxygen-rich combustion conditions and elucidated their specific mechanisms of action. The experimental results indicated that four Ca-based additives improved the recovery rate of total phosphorus, and promoted the generation of stable apatite phosphorus (AP). The effect of CaCl2 and CaO was greater than that of Ca(OH)2 and CaSO4. CaCl2 promoted the formation of Ca3(PO4)2 and Ca2P2O7, and CaSO4 improved the conversion of AlPO4 to Ca(H2PO4)2 with increasing temperature. The conversion capacity of CaO on non-apatite inorganic phosphorus to AP was greater than that of Ca(OH)2, and more CaH2P2O7, Ca(PO3)2, and Ca–Al–P minerals were found. Toxic metal percentages decreased after sludge incineration with CaCl2. Compared with CaO and Ca(OH)2, the toxic metal adsorption effect of CaSO4 was more significant. The influence of Ca additives on the conversion of Zn into stable components was as follows: CaCl2 > Ca(OH)2 > CaO > CaSO4. Ca additives reduced the toxic metal contamination level and ecological risk index values, and the order of toxic metal contamination levels was Ni > Zn > Cr > Cu > Mn. The experiment confirmed the conversion of phosphorus and the toxic metal passivation effect of Ca additives during oxy-fuel combustion of sludge, which is beneficial for its resource utilization.

Combustion conditions influence toxicity of flame-generated soot to ocular (ARPE-19) cells.

Soot is a prevalent aerosol found both indoors and outdoors that has several sources, such as natural (e.g., wildfires), civilian (e.g., cooking), or military (e.g., burn pit operation). Additionally, within the sources, factors that influence the physicochemical properties of the soot include combustion temperature, oxygen availability, and fuel type. Being able to reproduce soot in the laboratory and systematically assess its toxicity is important in the pursuit of elucidating pathologies associated with its exposure. Of the organs of interest, we targeted the eye given the scant attention received. Yet, air pollution constituents such as soot have been linked to diseases such as age-related macular degeneration and proliferative vitreoretinopathy. We developed a bench-scale system to synthesize different types of soot, that is, soot with a systematically varied physical attributes or chemical composition. We used common analytical techniques to probe such properties, and used statistical analyses to correlate them with toxicity in vitro using ARPE-19 cells. Within the range of flame conditions studied, we find that soot toxicity increases with increasing oxygen concentration in fuel-rich premixed flames, and weakly increases with decreasing flame temperature. Additionally, soot particles produced in premixed flames are generally smaller in size, exhibit a lesser fractal structure, and are considerably more toxic to ARPE-19 cells than soot particles produced in non-premixed flames.

Gaseous alkali interactions with ilmenite, manganese oxide and calcium manganite under chemical looping combustion conditions

Alkali species present in biomass pose significant challenges in chemical looping combustion (CLC) processes and other thermal conversion applications. The interactions between different alkali species and three common oxygen carrier (OC) materials that are considered to be state of the art in CLC applications have been investigated. A dedicated fluidized bed laboratory reactor was used to study interactions of KCl, NaCl, KOH, NaOH, K2SO4 and Na2SO4 with manganese oxide, calcium manganite and ilmenite. Alkali vapor was generated by injecting alkali salts under reducing, oxidizing and inert conditions at 900 °C. Gaseous species were measured online downstream of the reactor, and the efficiency of alkali uptake was determined under different conditions. The result show significant alkali uptake by all OCs under the studied conditions. Ilmenite shows near complete alkali uptake in reducing conditions, while manganese oxide and calcium manganite exhibited less effective alkali uptake, but have advantages in terms of fuel conversion and oxidizing efficiency. Alkali chlorides, sulfates and hydroxides show distinctly different behavior, with alkali hydroxides being efficiently captured all three investigate OC materials. The findings contribute to a deeper understanding of alkali behavior and offer valuable guidance for the design and optimization of CLC with biomass.