Sintering Behaviors of Synthetic Biomass Ash

Entrained flow gasification of biomass provides the opportunity to convert low-grade biogenic feedstocks to high-grade synthetic fuels. For a top-fired entrained flow slagging biomass gasifier, the thermophysical properties of the ash and slag limit process operation and affect process energy efficiency. The biomass ash has to be molten and slag viscosity has to be in a certain range for it to flow out of the gasifier. However, direct sampling, analysis, and evaluation of slag formation and behaviors are often challenging as entrained flow biomass gasification operates at high temperatures (i.e., 1200-1500°C) continuously. One alternative is to study synthetic ash's melting and sintering behaviors at elevated temperatures, which represent the major inorganic constituents in biomass ash. For thermochemical conversion of biomass, K, Ca and Si are typically the most common ash-forming elements. In this work, the synthetic ashes were prepared by mixing model compounds K2O, CaO and SiO2 in different mole ratios, which were pressed to form pellets. The selection of mole ratios was based on thermodynamic calculations that indicate that the tested model compound mixtures melt and flow with desired viscosity at certain temperature ranges. The pressed synthetic ashes were preheated at 900 °C for 8 hours to thermally homogenize them. Then the premelted synthetic ashes were heated at 1000 and 1400 °C in a muffle furnace with a residence time of 1 and 8 hours in air to study fusion behaviors and slag formation tendency, and were cooled down to room temperature gradually after the sintering test. The sintered residues were collected and analyzed by SEM/EDX to study the interactions of the model compounds and identify chemical compositions. The results showed that the mole ratios of model compounds have recognizable impacts on the composition, formation and transformation of mineral phases in residues from sintering tests. A strong correlation was also found between the sintering intensity of the synthetic ash and the mole ratios of model compounds.publishedVersio

Simulation of Oil Production from Homogenous North Sea Reservoirs with Inflow Control using OLGA/Rocx

Advances in drilling technology have made long, horizontal wells the preferred method to extract oil from reservoirs in the Norwegian Sector. Early water or gas breakthrough is a passive inflow control devices (ICD) are installed to even out the drawdown. However, a new technology called Autonomous Inflow Control Valve (AICV©) has the ability to autonomously close each individual inflow zone in the event of gas or water breakthrough. The objective of this paper was to study and compare these inflow control technologies. This was accomplished by conducting simulations in OLGA/Rocx. For this study, a high-permeability homogenous sandstone heavy oil reservoir was modelled based on data from the Grane oil field in the North Sea. Comparison of the oil production from the simulations with ICD and AICV completion was performed. The results, based on a time interval of 600 days, show that the oil production is 8% less and the water production is 43% less if AICV is used compared to ICD. This indicates that AICV has the potential to reduce the water production significantly in a homogeneous reservoir

Modelling of ash melts in gasification of biomass

The need for advanced biofuels produced from sustainable sources is stressed, both on national and international level due to a global agreement to limit the Earth’s global warming. The major goals in the Norwegian agreement on climate policy are to become climate neutral by 2030 and to become a net-zero emission society by 2050. One of the priority areas for action is to reduce the sources of greenhouse gases by speeding up the introduction of low-emission alternative transport fuels, such as liquid transport biofuels. A well-known process for converting biomass resources into liquid transport biofuels involves gasification, a thermochemical process that converts the biomass into a gaseous mixture of syngas in the presence of heat and a gasifying agent. The syngas consists of mainly hydrogen (H2) and carbon monoxide (CO), and can be further processed into biofuels. Among the different technologies applied for biomass gasification, fluidized beds have industrial advantages due to the ability to process a wide range of biomass under controlled operating conditions. The fluidized bed gasifiers also offer several other advantages, including good mixing, high heat and mass transfer and high productivity at a relatively low process temperature. However, processing biomass-derived fuels in fluidized beds suffers from ash related problems. The major challenge is associated with molten biomass ash and the formation of agglomerates that cause fluid dynamic disturbances in the bed. If not counteracted, the bed disturbances lead to operational problems that might result in decreased efficiency, high maintenance costs and unscheduled shutdowns. Bed agglomeration and de-fluidization are closely linked to the ash melting behaviour, and has been reported as one of the problematic issue prohibiting an economical and trouble-free operation. Hence, the key to unlocking fluidized bed biomass gasification as a viable route for biofuels production is by solving the challenges related to the ash. This PhD thesis addresses the key issues related to bed agglomeration and de-fluidization in fluidized bed gasifiers. Experimental work and computational modelling were combined in order to achieve a fundamental understanding, and insight into the underlying mechanisms of the ash melting behavior and the bed agglomeration processes. The main objective was to develop effective and accurate methods and models to be used in prediction of the agglomeration tendency of different types of biomass during gasification in fluidized beds. The overall approach was divided into three sections: (i) CPFD simulations combined with fluidization and gasification experiments to gain necessary knowledge on the fluidization characteristics, (ii) fluidization experiments to generate new sets of data that could form the basis for (iii) a mathematical model for prediction of the critical amount of accumulated ash/bed material in the gasifier. The experiments were carried out in three different fluidized bed systems: (i) a cold flow model, (ii) a 20 kW laboratory scale model, and (iii) a micro-scale model. The commercial CPFD software package Barracuda Virtual Reactor was used for the computational part. The investigated biomass samples were grass, wood, straw and bark. The results point out that the operating temperature and the composition of the major ash forming, in particular Si, K and Ca, are significant factors leading to ash melting problems in fluidized bed processes. Additionally, the findings show that the ratios between the major ash forming elements, K, Si and Ca, in the biomass play an important role in the agglomeration process, and that different combination of those elements are especially problematic when processing biomass fuels in fluidized bed systems. The results also indicate that bark tended to have the highest tolerance limit of accumulated ash in the bed for all the investigated temperatures. For example, the ash/bed material was measured to 7% by weight at 900°C, compared to grass (3%), straw (1%) and wood (1%). A multiple regression was calculated to predict the mass ratio of accumulated ash/bed material based on the operation temperature (T) and the mass ratios of (Si/K) and (K/Ca). The final model expresses the amount of accumulated ash/bed material at the onset of bed agglomeration and de-fluidization: Accumulated ash/bed material (wt %) = 17.06 – 0.02·T + 4.04·(Si/K) + 1.05·(K/Ca) The overall regression was statistically significant (R2 = 0.81, F (3, 30) = 38, p<0.0001)

Flow behavior in an agglomerated fluidized bed gasifier

The global energy demand has increased over the last decades and the need for utilization of energy produced from sustainable sources is stressed. Fluidized bed gasification of biomass is a thermochemical conversion process that involves heating and converting of biomass into a gaseous mixture of syngas. The syngas can be used for sustainable production of heat, power and biofuels for useful applications. Agglomeration of bed material due to ash melting is one of the biggest challenges associated with fluidized bed gasification of biomass. Inorganic alkali components from the biomass cause problems as they can form a sticky layer on the surface of the bed particles and make them grow towards larger agglomerates that will interfere with the fluidization process. The aim of this work was to study the effect of agglomerates on the flow behavior in a fluidized bed gasifier. The experiments were performed in a cold-flow model of a bubbling fluidized bed at ambient temperature. Three different experiments were carried out: (I) with sand particles as bed material, (II) with agglomerates located at the bottom of the bed and (III) with agglomerates located at the top of the bed. The results show that agglomerates lead to decreased pressure drop and increased minimum fluidization velocity. The minimum fluidization velocity increased from 0.035 m/s in the normal fluidized bed to 0.041 m/s in the agglomerated fluidized bed where the agglomerates were placed at the bottom of the bed. The minimum fluidization velocity increased further to 0.057 m/s in the agglomerated fluidized bed where the agglomerates where added from the top of the bed. This study also found that bed agglomeration causes channeling and poor fluidization conditions

Comparison of experimental and computational study of the fluid dynamics in fluidized beds with agglomerates

Particle agglomeration is one of the obstacles for successful application and commercial breakthrough of fluidized bed biomass gasification. The problem is generally associated with molten ash components that interact with the bed particles, forming agglomerates that interfere with the flow behavior. In this work experimental and computational study are combined in order to gain more insight into the fluid dynamics in a bubbling fluidized bed gasifier. The goal is to develop a Computational Particle Fluid Dynamic (CPFD) model that can be used in further investigations of the correlation between flow behavior and bed agglomeration during biomass gasification in fluidized beds. The experimental part was performed in a 20 kW laboratory scale bubbling fluidized bed system. The commercial CPFD software Barracuda Virtual Reactor (VR) version 17.4.1 was used for the computational study. Simulation results were compared to the experimental data in order to validate the CPFD model. Pressure drops predicted by the simulations were in good agreement with the experimental measurements, which indicate that the model is well capable of studying the fluid dynamics in a fluidized bed system

Experimental study of agglomeration of grass pellets in fluidized bed gasification

The agglomeration tendency during gasification of grass pellets in a bubbling fluidized bed reactor was studied. Particle agglomeration occurs as a consequence of interactions between the bed particles and the biomass ash during the thermal conversion of biomass in fluidized beds. The continuous operation and high efficiency of the fluidized beds are in these cases limited by partial or complete de-fluidization. In order to study the agglomeration tendency of grass pellets at defined operating conditions, controlled agglomerations tests are performed in a laboratory scaled 20 kW bubbling fluidized bed reactor. The effect of the ratio between the superficial fluidization velocity (u0) and the minimum fluidization velocity (umf) on the agglomeration tendency for grass pellets is reported. The results show that agglomeration in the bed can be recognized by fluid dynamic disturbances in the bed, and if not counteracted, de-fluidization will occur. The ratio u0/umf influences the agglomeration tendency and the de-fluidization of bed. As the ratio u0/umf increases, the agglomeration tendency and the de-fluidization time decreases. The de-fluidization temperature was not influenced by the changes in the superficial velocity ratio

CPFD model for prediction of flow behavior in an agglomerated fluidized bed gasifier

Renewable energy sources have significant potential for limiting climate change and reducing greenhouse gas emissions due to the increased global energy demand. Fluidized bed gasification of biomass is a substantial contribution to meeting the global energy demand in a sustainable way. however, ash-related problems are the biggest challenge in fluidized bed gasification of biomass. bed agglomeration is a result of interaction between the bed material and alkali metals present in the biomass ash. The agglomerates interfere with the fluidization process and might result in total de-fluidization of the bed. The study focuses on ash challenges related to the fluidization behavior in gasification of biomass. a model is developed and verified against results from previous performed experiments in a cold flow model of a bubbling fluidized bed. The commercial computational particle fluid dynamics (CPFD) software barracuda Virtual reactor is used for the computational study. The simulations show that the CPFD model can predict the fluidization process of an agglomerated fluidized bed gasifier

Computational modeling of fluidized bed behavior with agglomerates

Fluidized bed reactors can be used for biomass gasification. The product from biomass gasification is syngas, which can be used for production of bio oil. The main challenge when using fluidized bed for gasification is ash melting and agglomeration of the bed material. Agglomeration of the bed material influences on the flow behavior in the fluidized bed reactor and thus affects the gasification efficiency. A Computational Particle Fluid Dynamic (CPFD) model is developed to predict the flow behavior in a fluidized bed gasifier. The CPFD model was validated against experimental data from a cold fluidized bed. The model was then tested against the results from a biomass gasifier, and a few modifications were needed. Glickman’s scaling parameters were used to scale up from a lab-scale to a full-scale gasifier. Simulations using the modified model were performed to study the flow behavior in a full-scale gasifier with agglomerates. It was found that the CPFD model is capable of predicting the effect of agglomerates on flow behavior in a fluidized bed gasifier

Study of agglomeration in fluidized bed gasification of biomass using CPFD simulations

Fluidized beds have been widely applied for the gasification of biomass. However, at high temperatures ash melting and subsequently bed agglomeration may occur. When biomass is used for thermal conversion processes, inorganic alkali components present in the biomass fuels can be responsible for major problems. Understanding the ash melting and agglomeration in various gasification temperatures is crucial to optimize the design and operation conditions of a fluidized bed gasifier. This study focuses on the ash melting and the agglomeration process in a bubbling fluidized bed biomass gasification reactor. Using standard techniques, ashmelting analyses were performed to determine the initial agglomeration temperature in laboratory prepared ash samples from woodchips from Austria. Computational Particle Fluid Dynamic (CPFD) simulations were carried out using the commercial CPFD software package Barracuda Virtual Reactor (VR). The results show that the fluid dynamics gives important indications of unwanted agglomeration processes in a biomass gasification in a bubbling fluidized bed

Method of identifying an operating regime in a bubbling fluidized bed gasification reactor

This work presents a new method for identifying the bubbling regime of a fluidized bed gasification reactor. The method has been developed using experimental measurements and a computational model. Pressure drops are measured in experiments, and pressure drop as well as solid volume fraction fluctuations are calculated by implementing the model. experiments are carried out with sand and limestone particles of mean diameter 346 µm and 672 µm, respectively. A computational particle fluid dynamics (CPFD) model has been developed for the reactor and implemented using a commercial CPFD software Barracuda VR. The model is validated against experimental measurements. The validated model is used to analyse the fluctuation of pressure drop and solid volume fraction as a function of superficial air velocity. The change in standard deviation of pressure drop and solid volume fraction fluctuation is used to predict the transition from one regime to another. The method can be used in the design and operation of a bubbling fluidized bed gasification reactor. The results show that the minimum fluidization velocity for sand and limestone are 0.135 m/s and 0.36 m/s, respectively and are independent of the particle aspect ratio. Both types of particle beds make the transition into bubbling regime as soon as they get fluidized. The bed aspect ratios have almost no effect on the onset of bubbling fluidization regime. The slugging velocity decreases with increasing aspect ratio for both types of particles. The operating range of the bubbling fluidized bed for sand particle is 0.2–0.4 m/s and 0.5–0.8 m/s for the limestone particles