George M. Bollas

Characteristics and origin of char and coke from fast and slow, catalytic and thermal pyrolysis of biomass and relevant model compounds

Char and coke from biomass catalytic pyrolysis have different origins. They cannot be lumped as one since they occupy different locations on the catalyst surface and, thus, contribute differently to catalyst deactivation. In this study, catalyst (ZSM-5) deactivation in the perspective of comparison of char and coke from pyrolysis of different biomass types is investigated. Pine sawdust, glucose, and cellulose are used as feedstocks in the pyrolysis experiments. Biomass char and coke samples produced via slow and fast, thermal and catalytic pyrolysis are characterized with respect to their overall content, oxidation reactivity, catalyst surface area, pore size distribution changes, bonding groups and their effect on catalyst performance. In particular, it is shown that char forms as an external layer on the catalyst surface and in its macropores, whereas coke forms inside the zeolite micropores via hydrogen transfer and addition reactions. The catalyst effect on glucose and pine slow catalytic pyrolysis is minor compared with that on cellulose slow catalytic pyrolysis, due to macropore blocking by char formation. In fast catalytic pyrolysis, catalyst deactivation is mainly attributed to micropore blocking by coke formation. Char and coke are shown to coexist on the catalyst surface after fast catalytic experiments, with the char content after glucose fast catalytic pyrolysis being 30 wt% of the total solid residue. The origins of char and coke in the cellulose, hemicellulose and lignin components of pine are identified and mechanisms for their formation are proposed.

Catalytic pyrolysis of miscanthus × giganteus in a spouted bed reactor.

A conical spouted bed reactor was designed and tested for fast catalytic pyrolysis of miscanthus × giganteus over Zeolite Socony Mobil-5 (ZSM-5) catalyst, in the temperature range of 400-600 °C and catalyst to biomass ratios 1:1-5:1. The effect of operating conditions on the lumped product distribution, bio-oil selectivity and gas composition was investigated. In particular, it was shown that higher temperature favors the production of gas and bio-oil aromatics and results in lower solid and liquid yields. Higher catalyst to biomass ratios increased the gas yield, at the expense of liquid and solid products, while enhancing aromatic selectivity. The separate catalytic effects of ZSM-5 catalyst and its Al2O3 support were studied. The support contributes to increased coke/char formation, due to the uncontrolled spatial distribution and activity of its alumina sites. The presence of ZSM-5 zeolite in the catalyst enhanced the production of aromatics due to its proper pore size distribution and activity.

Investigation of in situ and ex situ catalytic pyrolysis of miscanthus × giganteus using a PyGC–MS microsystem and comparison with a bench-scale spouted-bed reactor

The objective of the present work is to explore the particularities of a micro-scale experimental apparatus with regards to the study of catalytic fast pyrolysis (CFP) of biomass. In situ and ex situ CFP of miscanthus × giganteus were performed with ZSM-5 catalyst. Higher permanent gas yields and higher selectivity to aromatics in the bio-oil were observed from ex situ CFP, but higher bio-oil yields were recorded during in situ CFP. Solid yields were comparable across both configurations. The results from in situ and ex situ PyGC were also compared with the product yields and selectivities obtained using a bench-scale, spouted-bed reactor. The bio-oil composition and overall product distribution for the PyGC ex situ configuration more closely resembled that of the spouted-bed reactor. The coke/char from in situ CFP in the PyGC was very similar in nature to that obtained from the spouted-bed reactor.

The effect of temperature, heating rate, and ZSM-5 catalyst on the product selectivity of the fast pyrolysis of spent coffee grounds

Spent coffee grounds (SCG) are a continuously produced and abundant biomass resource that is rich in fixed carbon and underutilized. In this study, fast pyrolysis was employed as a method of upgrading this waste product into higher value chemicals and commodities. The effect of catalytic upgrading via a ZSM-5 catalyst on the pyrolysis product was investigated at two heating rates and three different pyrolysis temperatures. The ZSM-5 catalyst was explored as the means to increase the selectivity to deoxygenated olefins and aromatic products. The liquid products from the pyrolysis of SCG were predominantly fatty acids, linear hydrocarbons, furans, phenols, ketones, and aromatic hydrocarbons. The ZSM-5 catalyst was seen to decrease selectivity to linear hydrocarbons and furans, and enhance selectivity to aromatic hydrocarbons and CO. Increasing the pyrolysis temperature was seen to decrease selectivity to fatty acids, and increase selectivity to aromatic and linear hydrocarbons.

Using hybrid neural networks in scaling up an FCC model from a pilot plant to an industrial unit

The scaling up of a pilot plant fluid catalytic cracking (FCC) model to an industrial unit with use of artificial neural networks is presented in this paper. FCC is one of the most important oil refinery processes. Due to its complexity the modeling of the FCC poses great challenge. The pilot plant model is capable of predicting the weight percent of conversion and coke yield of an FCC unit. This work is focused in determining the optimum hybrid approach, in order to improve the accuracy of the pilot plant model. Industrial data from a Greek petroleum refinery were used to develop and validate the models. The hybrid models developed are compared with the pilot plant model and a pure neural network model. The results show that the hybrid approach is able to increase the accuracy of prediction especially with data that is out of the model range. Furthermore, the hybrid models are easier to interpret and analyze.

A Computer-Aided Tool for the Simulation and Optimization of the Combined HDS–FCC Processes

A computer-aided tool for the simulation, optimization and analysis of the combined operation of the hydrodesulphurization (HDS) and fluid catalytic cracking (FCC) processes in an oil refinery is presented. The optimization of these processes is an important yet difficult engineering task, because of the complexity in the integration of the two units, the large number of interacting variables, the product quality specifications and the financial benefits associated. The proposed tool is developed in a user-friendly Visual Basic environment and operates in two different modes: the modelling-prediction mode and the optimization-sensitivity analysis mode. The modelling of the processes is based on short form’ models, which were created following statistical and neural network approaches. This kind of model usually has short computing time requirements, which is critical for the optimization mode. The optimization algorithm is based on a financial objective function with a flexible form, which gives the user the option to explore a variety of scenarios. Industrial runs have verified the modelling accuracy of the tool. The optimization scenarios examined include the contemporary needs of modern refineries for LPG and gasoline maximization, subject to strict quality specifications. The demonstration of this tool aims to give an insight into the system dependencies and add knowledge on the possibility of a more profitable operation of such a complex process.

Supervisory Control for Resilient Chiller Plants Under Condenser Fouling

This paper presents a supervisory control strategy for resilient chiller plants in the presence of condenser fouling. Fouling results in off-nominal performance of chiller parameters, such as increased refrigerant mass flow rate, compressor motor speed, discharge pressure, and discharge temperature. These effects further lead to faster deterioration of condenser pipes and tubes, and increase the risk of early motor failures. Thus, the main objective of this paper is to provide resilience, i.e., to bring the system parameters back to normalcy, and thereby protect the system from the adverse effects of fouling and improve its life expectancy while ensuring energy efficiency and meeting the desired cooling load. The supervisory control strategy presented here incorporates fault detection and diagnosis (FDD) and resilient control for mitigating the effects of condenser fouling. A computationally efficient and robust FDD scheme enables the estimation of the condenser fouling level using optimal sensor selection and statistical classifiers, thus facilitating condition-based maintenance. On the other hand, the resilient control scheme enables redistribution of load between chillers in order to reduce the load on faulty equipment in an energy-efficient manner, while still providing the required overall cooling load. The performance of this method is tested and validated using a high-fidelity chiller plant model and the proposed strategy is shown to diagnose condenser fouling with a high accuracy and effectively mitigate the effects of fouling at low computational cost. It is shown that the supervisory controller is able to meet the desired building load requirements at lower energy consumption, as compared with no supervisory control.

Model and Parameter Identification in Phase Equilibria

Abstract A formulation for parameter estimation with activity coefficient models is presented based on bilevel programs with nonconvex lower-level programs. The resulting mathematical formulation is solved numerically to global optimality with a deterministic algorithm. The formulation proposed overcomes limitations of state-of-the-art methods for parameter estimation in liquid-liquid equilibria and vapor-liquid(-liquid) equilibria, which result in qualitative and quantitative errors. The following elements of the method described are the main differences from existing methods: (i) necessary and sufficient stability criteria are imposed (as opposed to necessary only); (ii) additional constraints are introduced to ensure the experimentally observed number of phase splits and phases in each phase split; (iii) the best possible fit is guaranteed numerically.

Feed conversion targeting in an FCC pilot plant using a non-linear MPC strategy

The main objective of this work is the development of an advanced control scheme for the fluid catalytic cracking (FCC) pilot plant (PP) operated in the Chemical Process Engineering Research Institute (CPERI). This pilot plant is used for catalyst benchmarking, a very demanding procedure, that requires unit operation within a predefined span in order to match the industrial standards. For the tight, robust and efficient control of the FCC pilot plant a non-linear model predictive control (MPC) strategy is implemented, along with an extended Kalman filter (EKF) for state and parameter estimation.

Efficiency Analysis of Chemical-looping Fixed Bed Reactors integrated in Combined Cycle Power Plants

Abstract In this work, dynamic modeling is used as a tool to analyze the performance of chemical-looping combustion (CLC) integrated with combined cycle (CC) power plants. Fixed bed CLC reactors are incorporated into CC power plants. Efficiency improvements are achieved by optimizing the process design and managing CLC operating strategies. Specifically, this work presents the effect of operating variables on the performance of CLC-CC. The optimal CLC-CC power plant model has a time-averaged efficiency of 51.84%, power output of 223.6 MW, and CO2 capture efficiency of 96%. The main factor that limits plant efficiency is the maximum reactor temperature, which is constrained by the materials of oxygen carriers. Moreover, it is shown that the impact of the temperature of air fed to the CLC heat removal stage and the pressure ratio are more significant than other process variables.