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Carpenter, Daniel

Publications and source records attributed to Carpenter, Daniel.

8 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Design of an Integrated Solids Handling System to Maximize Syngas Process Reliability (Cooperative Research and Development Final Report)

The National Renewable Energy Laboratory (NREL), in partnership with Wonderful Renewable Energy (WRE) and Idaho National Laboratory (INL), plans to develop a general methodology for designing integrated biorefinery solids preprocessing, handling, and feeding systems based on the chemical, physical, and mechanical attributes of the starting biomass material. This attribute-driven approach will include detailed feedstock property measurements, iterative computational modeling, and bench-scale testing to design systems for preprocessing, handling, and reactor in-feed, up to and including the selection of the conversion reactor. The initial tests and system design will be conducted using waste material from almond and pistachio growing and production operations (shells, hulls, and wood), targeting the conversion of this material to syngas for electricity production. The methodology will then be generalized to other feedstocks. The purpose of this project is to design an integrated solids handling system to maximize the process reliability of converting almond and pistachio waste to electricity. The design methodology and workflow developed from this example will then be applied to the Feedstock Conversion Interface Consortium (FCIC) benchmark loblolly pine residues, thus demonstrating the robustness of the overall design approach and providing insight and guidance for future conversion systems. V-Grid Energy Systems was brought on as a subcontractor to provide gasifiers and labor to complete gasifier runs.

09 BIOMASS FUELS↗
DOE OSTI2021

Multiscale CFD simulation of biomass fast pyrolysis with a machine learning derived intra-particle model and detailed pyrolysis kinetics

Coupling particle and reactor scale models is as essential as reactor fluid dynamics and particle motion for accurate Computational Fluid Dynamic (CFD) simulations of biomass fast pyrolysis reactors due to intraparticle heat transfer and chemical reactions controlling conversion time and product distributions. Direct online coupling of a particle model with a reactor model is computationally expensive, while offline coupling is case-dependent. In this research, solutions from a series of particle pyrolysis simulations were regressed with Artificial Neural Network (ANN). Furthermoer, this machine learning-derived model predicted the same temperature and conversion profiles compared with particle resolved simulation while the isothermal approach overpredicted the temperature by 130 K and underpredicted the conversion time by 30 s. The ANN model was then integrated into CFD simulations of fluidized bed biomass fast pyrolysis with varied feedstocks via coupling PyTorch and MFiX. The averaged error of simulation predicted bio-oil yields with four feedstocks is 6.4%. This multi-scale approach provides an efficient tool for the coupled particle and reactor scale simulations of biomass pyrolysis.

09 BIOMASS FUELS↗
DOE OSTI2021

A simplified integrated framework for predicting the economic impacts of feedstock variations in a catalytic fast pyrolysis conversion process

Feedstock attributes of lignocellulosic biomass, such as particle size, compositional makeup, and moisture content, can vary substantially even within pre-processed materials and have a significant effect on conversion in fast pyrolysis-based processes. However, the economic impacts of these attributes are not well understood. To address this, biomass deconstruction phenomena captured with a versatile particle-scale simulation were linked to techno-economic impacts via reduced-order models. Parametric analysis of the particle-scale model, which was validated using literature data, was used in combination with multiple linear regression models to develop correlations between feedstock attributes and yields of pyrolysis oil, gas, and char. Yields were then correlated with the minimum fuel selling price (MFSP) using a techno-economic model, bridging the gap between physics-based biomass conversion simulations and predictions of MFSP for a catalytic fast-pyrolysis process. Empirical correlations derived from the literature regarding the impact of mineral matter (ash) on oil yield were also considered. The model correlations deployed in the integrated framework capture the impacts of variation in feedstock attributes on the MFSP. Variations in ash were shown to have the biggest impact, varying MFSP by -13%/+22% due to catalytic effects and lower relative amounts of convertible lignocellulosic material. It was also found that, if ash can be controlled to low levels, the increased extractives in forest residues can help compensate for some yield losses associated with increased ash. As a result, other inputs considered (particle size, moisture content, and reactor temperature) had relatively negligible effects on process economics within the ranges analyzed considering particle-scale effects alone.

BIOMASS FUELS↗
DOE OSTI2021

Multiscale Catalytic Fast Pyrolysis of Grindelia Reveals Opportunities for Generating Low Oxygen Content Bio-Oils from Drought Tolerant Biomass

Grindelia squarrosa (curlycup gumweed) biomass possesses unique biochemistry, cell wall composition, and leaf architecture tailored for prolific growth in arid and semiarid climates. Most notably, this plant has developed high levels of extractable resins that have high effective H/C eff ratios ((mol H - 2 x mol O)/mol C), which is hypothesized to lead to low coke formation during catalytic fast pyrolysis (CFP) over the ZSM-5 catalyst. In microscale experiments with high ZSM-5 loadings (biomass-to-catalyst mass ratio (B/C) ~ 0.1), in situ CFP generated high yields of aromatic hydrocarbons (30% carbon yield) while ex situ CFP favored aliphatic hydrocarbons (25% carbon yield). The difference between the two configurations was attributed to the constant catalyst temperature during ex situ CFP. Deactivation leading to partially deoxygenated vapor products occurred rapidly until B/C ≤ 0.5 by the adsorption of organic species blocking access to acid sites inside the micropores of the catalyst. This was followed by more gradual deactivation leading to primary vapor breakthrough, which we attribute to coke formation on acid sites on the external surface of ZSM-5 crystallites. Noncatalytic fast pyrolysis of Grindelia in a bench scale reactor produced oils with oxygen content (18 wt % on dry basis) and carbon yield (33%) comparable to those of CFP of woody biomass. The CFP of Grindelia further reduced the oxygen content to 7 wt % for in situ CFP and 4 wt % for ex situ CFP at B/C of 2-3. The good deoxygenation was attributed to a combination of a high H/C eff ratio and overall better quality of the pyrolysis vapors that were passed over the ZSM-5 catalyst. The high inorganic content of the Grindelia likely catalyzed pyrolysis to remove oxygenated coke precursors. This integrated CFP study demonstrated that Grindelia could be an important feedstock for generating stabilized noncatalytic and CFP oils for downstream processing into fuels and/or extraction of high-value chemicals. The preprocessing of this feedstock will be required to remove inorganics, which cause an irreversible deactivation of ZSM-5.

BIOMASS FUELS↗
DOE OSTI2021

Advanced spectrometric methods for characterizing bio-oils to enable refineries to reduce fuel carbon intensity during co-processing

A promising approach for supplementing petroleum-derived fuels to support reductions in green-house gas emissions is to convert abundant biomass feedstocks into renewable carbon-rich oils using pyrolysis. However, the resultant bio-oils contain various oxygenated compounds that can impart acidity, chemical and thermal instability, and immiscibility with petroleum derived fuels, necessitating further upgrading to derive fuel blendstocks. Co-processing bio-oils and petroleum-derived liquids in existing refineries is a potentially near-term, cost-effective approach for upgrading bio-oils while reducing refinery carbon intensities. However, one cause for hesitation in co-processing bio-oils is limited comprehensive characterization and speciation of the bio-oil components. Advanced analytical techniques are currently under investigation to enable identification of elusive species in bio-oils, enabling researchers to develop strategies to mitigate catalyst deactivation agents and contaminants. This review provides a brief overview of several analytical methods commonly used to analyze bio-oils and their limitations. In addition, advanced techniques currently under development are discussed to further elucidate bio-oil components that may limit its end use. This will help inform the technical and economic feasibility of co-processing bio-oils with petroleum-derived liquids, therefore, improving the overall downstream processes for biofuels blendstock production.

09 BIOMASS FUELS↗
DOE OSTI2020

Pilot plant reliability metrics for grinding and fast pyrolysis of woody residues

Here we report on the effects of loblolly pine residue variability on material throughput, pilot plant uptime, operator intervention, product yield, and product quality for grinding, fast pyrolysis, and hydrotreating operations. Preprocessing throughput using a hammer mill varied between 31-48% of nameplate capacity (5 tons/hr). Grinder overloads in the size reduction step were more prevalent for lower ash and higher moisture materials. Fast pyrolysis throughput varied between 57-72% of nameplate capacity (20 kg/hr) and bio-oil yields varied between 46-53% (feedstock carbon to oil, dry basis). During fast pyrolysis operations, downtime was caused by bridging in the feed and char removal systems and plugging in the condensation system. Cohesion of feedstock and char leading to system plugging was less frequent for higher ash feedstocks, and differences in condenser plugging behavior between high and low ash feedstocks were observed. The catalyst stability of the bio-oil stabilization step was strongly dependent on the sulfur content in the bio-oil, which was higher for the high-ash residue oils. Lower moisture content in the starting biomass was consistent with lower sulfur content in bio-oil. Yields and properties of hydrotreated fuel products showed minimal deference among the bio-oils.

Klinger, Jordan↗