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Ciesielski, Peter N. (ORCID:0000000333609210)

Publications and source records attributed to Ciesielski, Peter N. (ORCID:0000000333609210).

Characterizing Biomass Feedstock Transport Properties Using State of the Art Imaging and Computational Techniques

The microstructure of lignocellulosic biomass determines heat and mass transfer during conversion processes. We present a novel method for characterizing the transport properties of biomass using advanced imaging and computational techniques. The microstructure of two woody feedstocks, red oak and Douglas fir, before and after pyrolysis, is revealed using X-ray computed tomography (XCT). Transport properties are calculated from the XCT images, and principal permeability tensors are calculated using an immersed boundary-based finite volume solver to model gas flow through the geometries. We observe that the permeabilities of native biomass are distinctly anisotropic, however, this anisotropy is greatly reduced after pyrolysis.

adaptive mesh refinement↗

Mesoflow: An Open-Source Reacting Flow Solver for Catalysis at Mesoscale

We present the capabilities and software performance metrics of our open-source continuum solver for catalysis, Mesoflow, developed specifically for modeling transport and chemistry at the mesoscale. Our solver utilizes Cartesian block-structured adaptive mesh refinement to resolve complex catalyst surface morphologies directly obtained from X-ray tomography data. An immersed boundary based formulation enables rapid representation of complex geometries prevalent in most mesoporous catalyst interfaces. The solver is developed on top of open-source performance portable library, AMReX, providing parallel execution capabilities on current and upcoming high-performance-computing (HPC) architectures. Our flexible software framework enables integration of complex chemical mechanisms at heterogenous interfaces and time-split algorithms for circumventing highly disparate reaction and flow time-scales. Our current studies indicate a ten-fold performance gain by using graphics-processing-units (GPUs) compared to a single processor for representative problem sizes (2 million cell mesh). We will also present a brief introduction on how to build and use this software for application problems pertaining to catalytic upgrading and gas transport within porous catalyst particles.

adaptive meshing↗

CFD-DEM Modeling of Autothermal Pyrolysis of Corn Stover with a Coupled Particle- and Reactor-Scale Framework

Autothermal operation of fast pyrolysis is an efficient process-intensification technique wherein exothermic oxidation reactions are used to overcome the heat-transfer bottleneck of conventional pyrolysis. The development of accurate, reliable modeling toolsets is imperative to generating a deeper understanding of biomass autothermal pyrolysis systems to support scale-up and industrial deployment. This modeling effort describes the development of single-particle and reactor models which incorporate detailed reaction schemes and simultaneous exothermic oxidation reactions. The particle-scale model was parameterized for corn stover feedstock with particle morphology, density, ash content, and biopolymer composition, all of which impact the emergent conversion characteristics during pyrolysis. Results were then used to parameterize a reactor-scale autothermal pyrolysis model, which was developed using a coarse-grained computational fluid dynamic-discrete element method. The simulation results compared well with experimental results, with the predicted bio-oil, light gas, and biochar yield within 3.0 wt% of the experimental yields. Further analyses were performed to test the influence of equivalence ratio, biomass injection position, and particle size distribution on autothermal pyrolysis. The analysis of the physio-chemical properties of the fluid and solid phase inside the reactor and at the reactor outlet help reveal important process interactions of autothermal pyrolysis.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗

Minimizing Oxygen Permeability in Chitin/Cellulose Nanomaterial Coatings by Tuning Chitin Deacetylation

The demand for packaging materials with low gas permeabilities is increasing, but commonly used petroleum-derived single-use plastics are not renewable, biodegradable, or easy to recycle. Nanomaterials composed of chitin and cellulose, which are abundant in nature, have high crystallinities and low oxygen permeabilities (OP), providing a viable alternative. In this work, we explore how deacetylation conditions of crab shell chitin can be used to tune the charge and size of resulting chitin nanowhiskers (ChNWs) and the resulting OP of layered film structures. Three deacetylation factors, the concentration of sodium hydroxide (%NaOH), temperature (T), and reaction time, were explored using a three-factor three-level Taguchi design with an orthogonal array. Furthermore, the resulting ChNW suspensions were sequentially spray-coated with suspensions of cellulose nanocrystals (CNCs) onto cellulose acetate (CA) films to form a multilayer structure. We show that ChNWs prepared under more aggressive deacetylation conditions inside the original orthogonal array (higher %NaOH, T, and time) had shorter lengths but the surface charge was significantly influenced only by more aggressive deacetylation outside of the original design conditions. With only ~10% decrease in the ultimate tensile strength and no significant loss in failure strain, the ChNW-CNC coating resulted in ~20% decrease in WVTR in comparison to uncoated CA films. The optimization of process conditions resulted in CA-ChNW-CNC films with a 91-99% decrease in OP (132-16.7 cm 3 ∙μm/m 2 /day/kPa versus 1553 cm3∙μm/m2/day/kPa for uncoated CA).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impacts of Anisotropic Porosity on Heat Transfer and Off-Gassing during Biomass Pyrolysis

The pore structure of biogenic materials imbues the ability to deliver water and nutrients through a plant from root to leaf. This anisotropic pore granularity can also play a significant role in processes such as biomass pyrolysis that are used to convert these materials into useful products like heat, fuel, and chemicals. Evolutions in modeling of biomass pyrolysis as well as imaging of pore structures allow for further insights into the concerted physics of phase change-induced off-gassing, heat transfer, and chemical reactions. In this work, we report a biomass single particle model which incorporates these physics to explore the impact of implementing anisotropic permeability and diffusivity on the conversion time and yields predicted for pyrolysis of oak and pine particles. Simulation results showed that anisotropic permeability impacts predicted conversion time more than 2 times when the Biot number is above 0.1 and pyrolysis numbers (Py 1 , Py 2 ) are less than 20. Pore structure significantly impacts predicted pyrolytic conversion time (>8 times) when the Biot number is above 1 and the pyrolysis number is below 1, i.e., the “conduction controlled” regime. Therefore, these nondimensional numbers reflect that when internal heat conduction limits pyrolysis performance, internal pyrolysis off-gassing further retards effective heat transfer rates as a closely coupled phenomenon. Overall, this study highlights physically meaningful opportunities to improve particle-scale pyrolysis modeling and experimental validation relevant to a variety of feedstock identities and preparations, guiding the future design of pyrolyzers for efficient biomass conversion.

09 BIOMASS FUELS↗

Predicting Thermal Excursions During in situ Oxidative Regeneration of Packed Bed Catalytic Fast Pyrolysis Catalyst

Ex situ catalytic fast pyrolysis (CFP) uses a secondary reactor to upgrade biomass pyrolysis vapors to stabilized CFP oils with reduced oxygen content. In one configuration, the secondary reactor is operated as a packed-bed swing reactor system which allows coke-deactivated beds to be decarbonized in situ while other beds remain online for vapor upgrading. In situ decarbonization must be done carefully to avoid irreversible deactivation and/or physical degradation of catalyst pellets. Given that packed bed reactors are well known to have poor heat transfer characteristics, this is a critical issue impacting scaleability and commercial viability of the technology. To predict thermal excursions during regeneration, finite element computational models have been built to assist in scaling up oxidative decarbonization of a Pt/TiO2 CFP catalyst (0.5 mm spheres) from a bench scale packed bed with 100 g of catalyst to a pilot scale packed bed with 2 kg of catalyst and internal cooling tubes. Based on transient measurements of outlet temperature and effluent CO2 concentration, and using an assumed coke profile and activation energy, this paper demonstrates that specific combinations of effective thermal conductivity and wall heat transfer coefficient can fit bench scale oxidative regeneration data equally well. For the upscaled 2 kg bed, four bench-scale “best fit” parameter pairs give different predictions for location and magnitude of thermal excursions, with the maximum computed bed temperature gradients ranging from 30 °C cm-1 to as high as 3000 °C cm-1. The larger the fraction of heat removal by conduction through the cooling tubes, the greater the differences between the parameter pairs. The modelling results presented in this paper cast doubt on the industrial viability of the proposed combination of catalyst, bed and regeneration process, and point to the need for alternate reactor designs. However, there is considerable uncertainly in some of the key model parameters. The reliability of model predictions can be increased by adding more temperature measurements at key bed locations, testing additional variations in process conditions, performing careful bed dissections to determine the true coke profile, and perhaps most importantly, directly measuring the effective thermal conductivity of the catalyst pellets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tailorable Cellulose II Nanocrystals (CNC II) Prepared in Mildly Acidic Lithium Bromide Trihydrate (MALBTH)

Preparing cellulose II nanocrystals (CNC II) requires a polymorph transformation of natural cellulose I feedstocks. The transformation is usually achieved via a process such as mercerization or dissolution–regeneration. This study demonstrated a new method to prepare CNC II directly from bleached kraft pulp (BKP, a commercially available cellulose I feedstock) in a mildly acidic lithium bromide trihydrate (MALBTH) system, a concentrated (~61 wt%) solution of LiBr in water with a very low concentration (2.5 mM) of sulfuric acid. First, the BKP was treated in the MALBTH system to generate a cellulose II hydrolysis solid residue (CHR) with a yield of 64–86%, during which the selective hydrolysis of disordered cellulose and the polymorph transformation were completed simultaneously. Then, subsequent oxidation of the CHR by ammonium persulfate (APS, 0.1–0.6 M) resulted in the CNC II with high yield (up to 62%), high crystallinity (over 90%), rich surface carboxyl group (0.3–1.2 mmol g-1 cellulose), excellent colloidal stability (up to -59 mV zeta potential), and high thermal stability. The CNC II had a tunable length (26–57 nm), determined by the conditions of the MALBTH hydrolysis and the APS oxidation, but similar lateral dimension (8–10 nm). The characterization of the CHR by wide-angle X-ray diffraction and Fourier transform infrared spectroscopy verified the polymorphic transformation from cellulose I to II during the MALBTH treatment. The swelling of the BKP in the MALBTH enabled cellulose crystallites to slide and reassemble, which completed the rearrangement of cellulose chains from parallel to anti-parallel conformation (polymorph transformation from cellulose I to II). This study provided an efficient and green method to produce cellulose II nanocrystals with controllable aspect ratios via the simultaneous hydrolysis and polymorph transformation of cellulose I feedstocks.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Assessment of a Detailed Biomass Pyrolysis Kinetic Scheme in Multiscale Simulations of a Single-Particle Pyrolyzer and a Pilot-Scale Entrained Flow Pyrolyzer

A detailed biomass pyrolysis kinetic scheme was assessed in the multiscale simulations of a single-particle pyrolyzer with slow pyrolysis and a pilot-scale entrained flow pyrolyzer with fast pyrolysis. The detailed kinetic scheme of biomass pyrolysis developed by the CRECK group consists of 32 reactions and 58 species. A multiscale simulation model was developed, where the CRECK kinetics was employed to simulate biomass pyrolysis reactions, a one-dimensional particle model was utilized to simulate the intraparticle transport phenomena, and the particle-in-cell (PIC) model was employed to simulate the hydrodynamics. The multiscale model was first applied to simulate a single-particle pyrolysis experiment. The simulation with nonisothermal particles matched the experimental data better than the simulation with isothermal particles. Then the multiscale model was applied to simulate the pilot-scale entrained flow pyrolyzer. In this case, the simulation with isothermal particles matched the experimental data better than the simulation with nonisothermal particles. The reason for this difference might be that the kinetics itself already partially included the intraparticle transport effect as it was fitted using both TGA data (slow pyrolysis of small size biomass) and fluidized bed data (fast pyrolysis of relatively large size biomass). This study provides some insights into biomass pyrolysis kinetics development and pyrolyzer multiscale simulation for a future study.

09 BIOMASS FUELS↗

An Adaptive-Mesh-Refinement Based Computational Tool for Simulating Catalysis at Mesoscale

In this work, we present a computational tool for mesoscale applications using open-source exascale- computing compatible adaptive-mesh-refinement (AMR) library, AMReX [2]. AMReX is software library that enables development of application solvers with block-structured Cartesian AMR. Our tool has capabilities to include realistic geometry representation, chemical species transport, reactions and thermodynamics that are critical for capturing mesoscale physics. A significant achievement is the ability of our solver to automatically import electron microscopy data in the form of a stereolithography (STL) or pixelated file format (mrc, tiff) without undergoing the tedious task of unstructured mesh generation. This feature allows for rapid simulation of catalyst particles with complex morphologies using an immersed-boundary formulation. The use of AMR allows for higher resolutions at catalyst surface interfaces, which in turn provides an accurate description of surface reactions and transport. Our solver uses a hybrid distributed and shared memory parallelism (OpenMP/GPU-based) with which strong scaling up to 10,000 processors for realistic catalyst particle simulations have been demonstrated.

BIOMASS FUELS,MATHEMATICS AND COMPUTING↗