Effects of the Moisture Content on the Flow Behavior of Milled Woody Biomass
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Unit operations for the MSW sorting process include shredding, magnets for ferrous separation, screening, air classification, eddy current for non-ferrous separation, and near-infrared detection for plastic recovery. The MIXCINC module within Aspen Plus was selected to handle mixed solid streams containing inert (metals and glass) and non-conventional materials (paper, plastics, biomass, organic waste). The Peng-Robinson equation of state with Boston-Mathias modifications was applied to predict properties for a nonconventional solids mix. Enthalpy and density of the non-conventional materials were defined using non-conventional material properties.
Chemical and physical heterogeneity in biomass feedstocks such as agricultural or forestry residues is due to substantial differences in plant tissue types. These differences can contribute significant challenges to handling, preprocessing, and conversion in biorefining processes. An understanding of this chemical and physical heterogeneity can be used to inform fractionation technologies that could facilitate more streamlined processing and potentially be employed to yield multiple co-product streams for a single feedstock. In this chapter, the motivation and scope of biomass fractionation is first outlined. Physical and chemical properties of biomass feedstocks, along with their distribution and diversity within plants, are next discussed with respect to how these differences can be exploited in a fractionation process. A summary of some of the key physical principles that allow for fractionation is next covered along with how these physical principles are exploited in equipment designs. Examples from the literature are briefly discussed that highlight how these approaches can be employed to achieve processing objectives. Several case studies on physical fractionation of corn stover and forestry residues are presented that illustrate how integrated fractionation processes could be employed. Lastly, prospects and potential economic drivers for adoption of biomass fractionation technologies are discussed.
Chemical and physical heterogeneity in biomass feedstocks such as agricultural or forestry residues is due to substantial differences in plant tissue types. These differences can contribute significant challenges to handling, preprocessing, and conversion in biorefining processes. An understanding of this chemical and physical heterogeneity can be used to inform fractionation technologies that could facilitate more streamlined processing and potentially be employed to yield multiple co-product streams for a single feedstock. In this chapter, the motivation and scope of biomass fractionation is first outlined. Physical and chemical properties of biomass feedstocks, along with their distribution and diversity within plants is next discussed with respect to how these differences can be exploited in a fractionation process. A summary of some of the key physical principles that allow for fractionation is next covered along with how these physical principles are exploited in equipment designs. Examples from the literature are briefly discussed that highlight how these approaches can be employed to achieve processing objectives. Several case studies on physical fractionation of corn stover and forestry residues are presented that illustrate how integrated fractionation processes could be employed. Finally, prospects and potential economic drivers for adoption of biomass fractionation technologies are discussed.
Consistent and reliable preprocessing, conveyance, and reactor in-feed systems, particularly for low-cost waste feedstocks, remains a major technical challenge for the emerging Bioeconomy. By identifying critical biomass attributes and connecting them to flow and conversion behavior, science-driven system designs can address these often-overlooked solids handling challenges. The Wonderful Company (TWC) is the world's largest almond and pistachio grower, generating 250,000 dry tons/year of waste material including hulls, shells, and wood (>5 million tons/year industry wide in the U.S.). This project seeks to turn this environmental and economic liability into a sustainable and profitable resource, targeting conversion via gasification to syngas for electricity and bio-char, by addressing related material handling and feeding challenges. Based on optimized preprocessing strategies, bulk material flow, and thermal conversion properties, an overall system design will be developed. The methodology will be tested with FCIC's benchmark loblolly pine residues, to demonstrate the robustness of the overall approach and provide insight and guidance for future systems. The project will culminate in extended field trials to demonstrate an improved continuous feeding system with a commercial biomass-to-electricity gasifier vendor, and an economic analysis demonstrating a reduction in electricity production costs by maximizing on-stream time while minimizing preprocessing and CapEx costs.
Biomass liquefaction improves corn-stover slurry transport within a biorefinery, and reduces challenges associated with solids handling. Slurries, formed with yield stresses (i.e., viscosities) that are low enough to facilitate pumping from one unit operation to the next, and that enable mixing at reasonable power inputs in large fermentation vessels, enable scaling of cellulose fermentations. Three liquefaction methods: enzyme, enzyme mimetic, and a hybrid approach were analyzed by a combination of techno-economic and life-cycle analyses, resulting in an assessment of cost-effectiveness and environmental impact. Of the three scenarios, enzyme-based processes emerged as the most efficient, both in cost and emissions reduction (gCO2-equivalent/kg slurry).
Compression feed screws are commonly used in biorefineries for the continuous feeding of biomass feedstock into reactors. Developing methods to assess the feasibility of feeding granular materials in a compression feed screw is critical for reducing solids handling issues during operation. A laboratory-scale compression feed screw has been built to measure critical process parameters of the feeding operation, namely the driving torque and the mass flow rate. The process parameters of two granular materials, microcrystalline cellulose Avicel PH-200 and milled corn stover are measured using the laboratory-scale feeder. The results show that a larger torque is required to feed corn stover than Avicel PH-200, even though the former consists of more compressible particles. Further, the device can capture real-time fluctuations in the process parameters during operation. Here, the laboratory-scale feeder can be used to compare the feeding of different granular materials and the measured parameters can be used to validate predictive models for a compression screw feeding process.
Increasing the production and use of biofuels is a national objective for renewable, cleaner energy. A primary objective of the Department of Energy’s Bioenergy Technologies Office (BETO) Feedstock-Conversion Interface Consortium (FCIC) is to address the operational, safety, throughput, and yield of bio-refineries to revolutionize biomass processing with the goal to make bio-derived fuels cost-competitive with fossil fuels. One of the main hurdles is increasing the operational reliability of the bio-refineries. Bio-refineries convert the biomass, such as corn stover, into ethanol. Corn stover is composed of the non-edible stalks, leaves, cobs, and husks left over from harvesting. This material is known for having poor processing properties for bulk solids handling and transport. These properties, such as moisture content, cause costly system plugging and downtime at bio-refineries which limit biofuel from being cost-competitive with diesel and gasoline fuels.
The variations in feedstock characteristics, such as moisture and particle size distribution, lead to an inconsistent flow of feedstock from the biomass pre-processing system to the reactor in-feed system. These inconsistencies result in low on-stream times at the reactor in-feed equipment. This research develops an optimal process control method for a biomass pre-processing system comprised of milling and densification operations to provide the consistent flow of feedstock to a reactor's throat. This method uses a mixed-integer optimization model to identify optimal bale sequencing, equipment in-feed rate, and buffer location and size in the biomass pre-processing system. This method, referred to as the hybrid process control (HPC), aims to maximize throughput over time. We compare HPC with a baseline feed forward process control. Our case study based on switchgrass finds that HPC reduces the variation of a reactor's feeding rate by up to 100% without increasing the operating cost of the biomass pre-processing system for biomass with moisture ranging from 10 to 25%. Additionally, HPC reduces the cost of processing biomass by 0.36%–2.22%, and reduces processing time by 0.35%-2.24%. Furthermore, a biorefinery can adapt HPC to achieve its design capacity.
Willow and poplar short rotation woody crops (SRWC) have shown promise with regards to environmental benefits and rural development but wide adoption lags due to underdeveloped markets and supply systems. High costs associated with harvesting, handling and transportation (40-60% of delivered cost) have impeded expansion. A better understanding of these systems will create opportunities to improve efficiency, reduce costs, and realize environmental benefits and impacts. The project’s goal was to lower the delivered cost of hybrid poplar in the Northwest and willow in the Northeast by optimizing harvesting and logistics supply systems while maintaining or improving biomass quality along the supply chain. Over 3,400 Mg of biomass and 300 ha of willow and poplar were monitored over a range of crop and field conditions. Feedstock quality as affected by storage and preprocessing were shown to improve or maintain feedstock quality. Modeled harvesting costs ranged from $38–61 Mg -1 dry; when including delivery and preprocessing feedstock costs ranged between $79-83 Mg -1 dry for willow and $106-116 Mg -1 dry for poplar. Costs for willow minimized when hot water extraction and high-moisture densification preprocessing were used. Models also suggest that social and regional factors could further reduce costs. Results will give guidance to feedstock growers, harvesting and logistic operations, biorefinery project developers, and policy makers developing SRWC to support a growing bioeconomy.
The properties of lignocellulosic biomass, such as bulk physical, thermal, and mechanical properties, as well as the mobility of enzymes or catalysts, are largely affected by porosity, pore structures, and pore size distribution. While X-ray computed tomography (CT) has been introduced to effectively produce 3D volumetric images of material microstructure, a quantitative porosity analysis from the 3D images has never been done. This work introduces a first-of-its-kind X-ray CT-based quantitative porosity analysis method and applies the developed toolkit to characterize the internal porosity distribution of loblolly pine. A sample loblolly pine chip was scanned by a nano-resolution X-ray CT system and digitally reconstructed after a sequence of image processing operations. Here, a comprehensive porosity analysis was then performed to quantify the envelope porosity, the spatial distribution of local porosity, and the directional porosity. Solutions to the various challenges in image processing, porosity calculation, and large data handling are provided.
This research is motivated by the challenges faced during biomass processing in bioenergy plants. It has been observed that variations in biomass characteristics, such as moisture, ash, and carbohydrate contents cause variations in feeding of the system which led to underutilization of equipment and the reactor. The objective of this research is to ensure a continuous flow of biomass to the reactor in plants that use the biochemical conversion process to generate liquid fuels. The overall goal is to lower the cost of producing biofuels, which could lead to improving US’s energy independency and growing US’s rural economy. The research team developed analytical models, such as discrete element method (DEM) models and mathematical models. The DEM models are unit-level models that explicitly capture biomass characteristics and quantify the impacts of biomass characteristics on bulk material properties and the performance of specific equipment. The mathematical models are system-level models that capture the impacts of system infeed rate, equipment processing rate, storage location and capacity, and biomass characteristics on system throughput. The functional relations predicting the bulk material properties from DEM models are incorporated to the mathematical models. The models developed were validated and evaluated using data collected at Idaho National Laboratory’s biomass processing facility. Via these models, we identified process control strategies that ensure a continuous flow of biomass to the reactor, while meeting the requirements of biochemical conversion process. Our analysis indicates that sequencing of biomass bales based on moisture level, and carbohydrate contents could have a positive impact on reducing processing time and inventory level and increasing throughput rate. Short bale sequences that repeat frequently, seem to have the greatest impact on improving system’s performance. Based on our experiments, the total annual system operating costs reduced by 20-30%, and the maximum inventory level reduced by 3 to 4 times. The operating costs include the annual equipment amortization cost and processing cost. The implementation of the models developed requires the use of standardized bale format, Radio Frequency Identification technology, sensing and real time monitoring of material attributes, automated material handling equipment, and automated process control. The scope of the model proposed can be extended to include the whole supply chain. The supply chain models help identify how many bales of different biomass feedstock to purchase given biomass availability in the region, biomass price and quality, and the biomass processing capabilities of the biorefinery. Thus, the outcomes of supply chain models can be used to inform the design of long-term contracts among farmers and the biorefinery.
A novel biomass production system, integrating the co-harvesting and co-storage of moist corn grain and stover, promises a reduction in delivered feedstock costs. In this innovative method, the dry grain traditionally utilized for feed or biofuel production will now be processed at a considerably greater moisture content. The adoption of this approach may necessitate a substantial redesign of existing material handling infrastructure to effectively accommodate the handling and storage of moist grain after processing by milling or grinding. A comprehensive study was conducted to quantify the physical properties of this grain after processing with a knife processor or a hammermill. The geometric mean particle size, bulk and tapped density, sliding angle, material coefficient of friction, and discharged angle of repose were quantified. Five grain treatments, either fermented or unfermented, and having different moisture contents, were used. After processing, the moist, fermented ground grain exhibited a significantly smaller particle size compared to the dry grain. Additionally, both moist processed grains resulted in a decreased bulk density and increased material sliding angle, friction coefficient, and angle of repose. The examined metrics collectively suggest that handling, mixing, and storing moist ground grain will pose significant challenges compared to conventional dry ground grain. This increased difficulty may lead to substantially higher costs, a crucial factor that must be carefully considered when evaluating the overall economics of implementing this new biomass production system using combined harvesting and storage of corn grain and stover.
The long-term strategy of the United States targets reaching economy-wide net-zero emissions by 2050 and a carbon-neutral electricity grid by 2035 (U.S. Department of State and U.S. Executive Office of the President, 2021). Meeting these targets would require considerable changes to the energy system. Some key characteristics of illustrative net-zero energy systems include increased penetration of renewable energy and carbon sources, use of CO2 capture and storage (CCS) in hard-to-abate sectors, and a greater role for energy carriers such as electricity and hydrogen (Davis et al, 2018). Another common feature of such energy systems is the need for carbon dioxide removal (CDR) approaches (Horowitz et al, 2022). Across all these characteristics of net-zero energy systems, bioenergy and biomass feedstock is anticipated to play an important role. Biomass feedstock serves as a renewable carbon source. This can enable conversion of such feedstock into fuels and energy carriers for hard-to-abate sectors such as aviation. Indeed, the U.S. Government has a target to meet all jet fuel demand by 2050 from sustainable aviation fuel (SAF), where biofuel pathways are likely to have an important role (EERE, 2020). Bioenergy is also highly versatile with the possibility to convert feedstock into electricity, hydrogen, liquid fuels, heat or high-value products, based on biomass type, demand and technology availability (Clarke et al, 2022). Combination of bioenergy with CCS can also nominally deliver CDR (Fuhrman et al, 2023). As such, the share of bioenergy is expected to grow by at least five time across scenarios studied for the long-term strategy of the U.S. between 2020 and 2050 (Horowitz et al, 2022). Notwithstanding the role of bioenergy in the energy systems, its deployment, costs and scalability are influenced by a number of factors. Some of these factors pertain to policy interventions such as imposition of a binding decarbonization target either at an economy-wide level or the sectoral level. Resource availability and type of biomass feedstock also varies considerably across regions. From a technological perspective, the readiness of bioenergy conversion pathways is subject to high variability. This influences the costs of deployment. Moreover, the sourcing of feedstock, grid carbon intensity, and co-product handling approaches all affect the life cycle efficacy of bioenergy. The latter, in turn, is particularly important in determining the extent to which bioenergy with CCS or BECCS can effectively deliver CDR (Fajardy and Mac Dowell, 2017).
Liquid slurries at high loadings (pumpable slurries) are critical to handle the streams between the unit operations in a biorefinery. Their liquefaction potential was initially tested with a small-scale method using 3FPU Ctec-2 /g dry biomass, and results were confirmed in 1L bioreactors experiments. Liquid slurries of cobs were observed in small scale tests (based on visual appearance, and reducing sugars released). Results were confirmed in 1L bioreactors under similar experimental conditions. Yield stress value in bioreactor was 34 ± 6Pa at 96 h, and glucan and xylan conversion to glucose and xylose, respectively, were 41 and 21%. In addition, work has been initiated with liquefaction of other pelleted corn stover fractions: Husk/Leaf (A),Husk (B), Stems (D) and controls (whole corn stover; F and G). Compositional analysis of the pellets showed glucan content (%) in the samples ranged from 31.9 to 36.1, xylan from 19.1 to 20.9, total lignin 13.1 to 18.8,and total ash 1.73 to 10.19. The moisture content ranged from 6.21 to 11.66%. Given these similar characteristics, we also examined liquefaction of these other samples, and they also showed that liquid slurries are possible. Work is continuing to define favourable conditions for liquid slurries formation.
The project aims to study wet, anaerobic storage to mitigate seasonal variation in algae productivity to reduce the risk of feedstock loos prior to conversion and to study how to enable the storage period to be used to add value to algae biomass without affecting the final fuel's yield or quality. This project will take the approach of engaging in stability research that addresses seasonal variability in production and that which provides opportunities to add value to algae biomass prior to conversion as well as to gain a fundamental understanding of post-harvest algae physiology to support cultivation gains.
Accurate simulation of crop water use (evapotranspiration, ET) can help crop growth models to assess the likely effects of climate change on future crop productivity, as well as being an aid for irrigation scheduling for today's growers. To determine how well maize (Zea mays L.) growth models can simulate ET, an initial inter-comparison study was conducted in 2019 under the umbrella of AgMIP (Agricultural Model Inter-Comparison and Improvement Project). Herein, we present results of a second inter-comparison study of 41 maize models that was conducted using more comprehensive datasets from two additional sites - Mead, Nebraska, USA and Bushland, Texas, USA. There were 20 treatment-years with varying irrigation levels over multiple seasons at both sites. ET was measured using eddy covariance at Mead and using large weighing lysimeters at Bushland. A wide range in ET rates was simulated among the models, yet several generally were able to simulate ET rates adequately. The ensemble median values were generally close to the observations, but a few of the models sometimes performed better than the median. Many of the models that did well at simulating ET for the Mead site did poorly for drier, windy days at the Bushland site, suggesting they need to improve how they handle humidity and wind. Additional variability came from the approaches used to simulate soil water evaporation. Fortunately, several models were identified that did well at simulating soil water evaporation, canopy transpiration, biomass accumulation, and grain yield. These models were older and have been widely used, which suggests that a larger number of users have tested these models over a wider range of conditions leading to their improvement. These revelations of the better approaches are leading to model improvements and more accurate simulations of ET.
Fractionating whole-plant corn (WPC) in a single-pass harvesting system requires studies on the WPC-to-equipment interaction for improved property control, as well as mechanical and air-driven separation processes compared to the traditional multi-pass grain and stover harvesting system. The discrete element method (DEM) technique has the potential to simulate WPC mechanical fractionation and support simulation-based design of WPC separation processes. In this study, methods to develop DEM particle models of WPC (kernel, cob, stalk, and husk) and their material properties for simulating mass fractionation using the ASABE standard mechanical shaker were proposed. Measurement was done on the axial dimensions (major, intermediate, and minor) and mass of each WPC type (mean sample size is 56), sampled from single-pass harvesting. Applying gaussian multivariate regression and bootstrapping re-sampling techniques, a DEM particle approximate to each WPC was developed. Sensitivity analysis of the DEM Young‘s modulus, Poisson‘s ratio, and interaction parameters of coefficient of restitution, coefficient of rolling friction, and coefficient of static friction on mass fraction was performed after 156 ASABE sieve-shaking DEM simulation runs, generated using Latin Hypercube Design (LHD) design of experiment (DOE) from 19 DEM material parameters. DEM simulation using Hertz-Mindlin with flexible bond contact laws and DOE optimized material properties successfully reproduced the mass fractions retained in ASABE sieves at 9.8% mean relative error and a coefficient of determination of R2 = 0.87. Here, the DEM methodology developed for mechanical WPC mass fractionation could be deployed to perform virtual design of feedstock handling equipment and performance analysis of mechanical fraction systems.