This study demonstrates a failure identification methodology applied to a preprocessing facility generating conversion-ready feedstocks from biomass meeting conversion process critical quality attribute (CQA) specifications. Failure Modes and Effects Analysis (FMEA) was used as an industrially relevant risk analysis approach to evaluate a logging residue preprocessing system to prepare feedstock for pyrolysis conversion. Risk evaluations considered both system-level and operation unit-level assessments considering process efficiency, product quality, cost, sustainability, and safety. Key outputs included estimations of semi-quantitative risk scores for each failure, identification of the failure impacts, identification of failure causes associated with material attributes and process parameters, ranking success rates of failure detection methods, and speculation of potential mitigation strategies for decreasing failure risk scores. Results showed that deviations from moisture specifications had cascading consequences for other CQAs along with process safety implications. Failures linked to fixed carbon specifications carried the highest risk scores for product quality and process efficiency impacts. As increased throughput can be inversely related to meeting product quality specifications; achieving throughput and other material-based CQAs simultaneously will likely require system optimization or prioritization based on system economics. Ultimately, this work successfully demonstrates FMEA as a risk analysis approach for other bioenergy process systems.

The U.S. Department of Energy (DOE) promotes the production of advanced liquid transportation fuels from lignocellulosic biomass by funding fundamental and applied research that advances the State of Technology (SOT). As part of its involvement with this mission, Idaho National Laboratory (INL) completes an annual SOT report for biomass feedstock logistics. This report summarizes supply system impacts of Bioenergy Technologies Office (BETO)-funded research and development efforts at INL and INL collaboration with external partners (e.g. Forest Concepts, Purdue University ) that lead to improvements in feedstock supply systems. These include improvements to and observed performance of innovative harvest and collection methods, storage technologies, transportation and handling approaches, and advanced preprocessing technologies. Biomass quality and variability, and the interface between feedstock quality and conversion performance are key drivers in addition to delivered feedstock cost. In this report, we estimate the benefits of R&D technology improvements to individual supply system unit operations and present the status of feedstock logistics technology development for converting herbaceous biomass into biofuels. These analyses are supported by experimental data where possible and help to align the SOT relative to the cost goals defined in the Multi-Year Plan. The 2021 Herbaceous SOT incorporates an advanced biomass fractionation systemmore » for separating anatomical fractions (e.g. leaf, stem, husk, and cob) of delivered corn stover, thus, to maximize the goal of reducing extrinsic ash and improving carbohydrate content in the pre-processed biomass. The air classification in the fractionation system is supported by a Spudnik Air separator, which is a large-scale equipment that can efficiently remove soil contaminant (about 25%) and separate high ash content tissue such as leaf and husks. By eliminating extrinsic ash in biomass and the high ash content fractions, we have reduced ash content of three-pass corn stover from 11.20% to 6.00%, and increased carbohydrate content from 56.80% to 60.16%. This technical improvement has allowed us to eliminate two-pass corn stover from the biomass supply curve, therefore largely reduced the harvesting and collection cost, and transportation costs within the feedstock logistics system. In addition, the second stage hammer mill was replaced with rotary shear, which is less sensitive to moisture content than hammer milling and has higher throughput with lower energy consumption. The reduced energy consumption has also contributed to the modeled cost reduction. The 2021 nth-plant Herbaceous SOT predicts a modeled delivered feedstock cost of $78.21/dry ton (2016$), this is a $0.54/dry ton (2016$) decrease from the 2020 Herbaceous SOT nth-Supply case cost. Technology improvements that contributed to this modeled cost reduction include reduced cost in the feedstock harvesting, collection and transportation cost caused by eliminating two-pass corn stover, and reduced energy consumption cost by replacing the hammer mill with rotary shear. A preliminary greenhouse gas emissions (GHG) assessment was completed by scaling the 2020 Herbaceous nth-plant GHG data from the 2020 Greenhouse Gases, Regulated Emissions, and Energy use in Transportation model (GREET) , shows a decrease of 9.77 kg CO2e/ton from the 2020 SOT (77.48 kg CO2e/ton in the 2020 Herbaceous Feedstock SOT to 67.71 kg CO2e/ton in the 2020 Herbaceous Feedstock SOT). This net reduction is attributed to reduced transportation distances for biomass delivery from field to depot, and reduced energy consumption by using rotary shear, and will be updated once Argonne National Laboratory has completed their Supply Chain Sustainability Analysis for the 2021 SOTs. In the 1st-plant analysis of the 2021 Herbaceous SOT system, the average throughput was 2,044 dry tons/day or 92.7% of the name plate capacity. During the simulation the daily throughput ranged from 848.1 dry tons/day to 2,338 dry tons/day, which equates to 38.5% to 106% of the daily nameplate capacity. After the year of operation 715,400 tons (98.33% of the annual nameplate capacity) of preprocessed feedstock were produced; the variability in throughput was primarily caused by equipment failures in the system. Failures due to wear were the largest cause of disruption within the system, accounting for 70.04% of the failures and 91.28% of the total downtime. Previously, moisture related failures were the cause of the majority of downtime, but new storage strategies and equipment (bale dryer for the first 25% of stover harvested) data from the Biomass Storage project (WBS 1.2.1.1) led to the elimination of moisture related downtime. Ultimately the system on-stream time was 87.65% during the simulation period. Considering the operational delays and material losses in the system, the average cost per ton of biomass was $82.34/dry ton, with a range from $72.24/dr « less

The U.S. Department of Energy promotes production of advanced liquid transportation fuels from lignocellulosic biomass by funding fundamental and applied research that advances the state of technology (SOT). As part of its involvement with this overall mission, Idaho National Laboratory completes annual SOT reports for nth-plant biomass feedstock logistics. The purpose of the SOTs is to provide the status of feedstock supply system technology development for biomass to biofuels, based on actual data and experimental results relative to technical targets and cost goals from specific design cases. Conventional feedstock supply systems need to be modified to meet the demands of conversion pathways, specifically to have the ability to adjust the quality of the materials. Advanced systems incorporate innovative methods of material handling, processing and supply chain configuration. In advanced designs, variability of the feedstock can be reduced to produce feedstocks of a uniform format, moving toward biomass commoditization. Against this backdrop, the 2021 Woody SOT for low-ash woody feedstocks utilizes feedstock fractionation by incorporating technologies that can separate the biomass by its fractions (wood, bark, needle, and extrinsic ash) to reduce impurities and attempt to maximize the retention of usable biomaterials that satisfy downstream quality considerations. By using a seriesmore » of air classification steps the process is able to reduce the extrinsic ash in forest residues. The forest residues are then blended with clean-pine chips in a 50-50 mix to prepare the feedstock for the desired conversion pathway. The Nth plant analysis estimated the delivered cost for feedstock at $75.87 (2016$) which represents an increase of $8.84 compared to cost estimate for the 2020 Woody SOT supply system for the CFP pathway. However, the quality requirements in the 2021 Woody SOT for low-ash feedstocks was more stringent at =1.00 wt% ash compared to =1.75 wt% in the previous year. Similarly, the GHG emissions for the Nth plant analysis were estimated at 171.71 kgCO2e/dry ton, compared to 163.50 kgCO2e/dry ton in the 2020 Woody SOT, an increase of 8.21 kgCO2e/dry ton attributed to preprocessing. In the first plant analysis of the 2021 SOT system, the average throughput was approximately 2101 dry tons/day or 95.27% of the name plate capacity. During the simulation the daily throughput ranged from 1146 dry tons/day to 2163 dry tons/day, 51.97% to 98.10% of the daily nameplate capacity. After the year of operation 735,541 tons (101.45% of yearly nameplate) of processed feedstock were produced in total. The variability in throughput is primarily caused by equipment failures in the system. Extrinsic ash emerges as a pinch point for system performance as it contributes to a majority of equipment failures. Furthermore, steps undertaken to reduce the quantity of extrinsic ash in the feedstock face challenges, especially in the form of reduced efficiency of soil removal in air classification – which are exacerbated at higher levels of moisture in the incoming material. Failures due to wear was the largest cause of disruption within the system accounting for 52.78% of the failures and 36.21% of the total downtime. Ultimately the system was on stream for 90.98% during the simulation period. The production cost of the system averages $82.29/dry ton. The costs ranged from a minimum of $72.83/dry ton to a maximum of $727.38/dry ton. When losses are considered the costs increase to an average of $86.93/dry ton with a minimum of $77.18/dry ton and a maximum of $741.91. When compared to the ideal nth-plant cost, the average cost from the first plant analysis $11.06/dry ton greater than the n-th plant estimate. While the nth-plant analysis assumes a constant quality feedstock, the first plant analysis utilizes variability in the material to assess the impact. In the first plant analysis, it is assumed that any material that does not meet the base quality specifications of = 50.51 wt% carbon and = 1.0 wt% ash is discarded. From this simulation, only 76.72% of the material met the defined quality specification, requiring the disposal of 23.28% of the biomass. The material that is discarded due to quality, represents an additional cost that must be accounted for in the total cost of the material. When the cost is fully burdened considering system disruptions, material lost during operation, as well as material removed for quality considerations the average cost per ton of biomass was $113.28/dry ton, with a range from $103.59/dry ton to $767.83/dry ton. The resulting Overall Operating Effectiveness (OOE) for the system, from the simulation, was found to be 77.87%. A feedstock performance factor of 76.72% and a fully burdened cost that is $37.41/dry ton higher than the estimated n-th plant cost suggest that additional technology development is needed to further address the variability of quality within the feedstock and improvem « less

Bioenergy has been globally recognized as one of the sustainable alternatives to fossil fuels. An assured supply of biomass feedstocks is a crucial bottleneck for the bioenergy industry emanating from uncertainties in land-use changes and future prices. Analytical approaches deriving from geographical information systems (GIS)-based analysis, mathematical modeling, optimization analyses, and empirical techniques have been widely used to evaluate the potential for bioenergy feedstock. In this study, we propose a three-phase methodology integrating fuzzy logic, network optimization, and ecosystem services assessment to estimate potential bioenergy supply. The fuzzy logic analysis uses multiple spatial criteria to identify suitable biomass cultivating regions. We extract spatial information based on favorable conditions and potential constraints, such as developed urban areas and croplands. Further, the network analysis uses the road network and existing biorefineries to evaluate feedstock production locations. Our analysis extends previous studies by incorporating biodiversity and ecologically sensitive areas into the analysis, as well as incorporating ecosystem service benefits as an additional driver for adoption, ensuring that biomass cultivation will minimize the negative consequences of large-scale land-use change. We apply the concept of assessing the potential for switchgrass-based bioenergy in Missouri to the proposed methodology.

Researchers make hundreds of decisions about data collection, preparation, and analysis in their research. We use a many-analysts approach to measure the extent and impact of these decisions. Two published causal empirical results are replicated by seven replicators each. We find large differences in data preparation and analysis decisions, many of which would not likely be reported in a publication. No two replicators reported the same sample size. Statistical significance varied across replications, and for one of the studies the effect's sign varied as well. The standard deviation of estimates across replications was 3-4 times the typical reported standard error.