New insights into the mechanisms of carbon dioxide mineralization by portlandite
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Engineering↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Techno‐economic assessment of single‐stream feedstock logistics supply chain for corn stover and grain
Abstract The state‐of‐technology for corn stover harvest is a multi‐pass system that collects the stover after grain harvest. An alternative is a single‐stream system where the grain and stover are harvested as a bulk material co‐stored and preserved by anerobic fermentation, and finally, co‐transported to a biorefinery. In the present work, four single‐pass whole‐plant bulk systems were compared with a conventional multi‐pass bale system. The single‐stream systems consisted of the harvest of corn grain and a portion of the stover fraction. Four machine configurations were simulated. This work predicted that a multi‐pass bale system would result in a material cost of 111.80 $2021 Mg –1 stover DM delivered to the biorefinery gate. Alternatively, the lowest cost single‐stream system was the self‐propelled forage harvester (SPFH) configured with the whole‐plant header, which delivered feedstock for 74.76 $2021 Mg stover DM –1 . In addition to machine configuration, a sensitivity analysis was performed to understand important drivers of feedstock cost. These analyses revealed that feedstock cost increased with moisture content, fertilizer price, and biorefinery size, and decreased with harvest season length, crop yield, and grower participation. This work demonstrated that single‐stream systems could reduce corn stover feedstock costs in comparison with state‐of‐technology systems. © 2022 The Authors. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley & Sons Ltd.
09 BIOMASS FUELS↗
River–aquifer interactions enhancing evapotranspiration in a semiarid riparian zone: A modelling study
The hydrologic flows across the river–aquifer interface play an important role in groundwater dynamics and biogeochemical reactions within the subsurface; however, little is known about the effects of river–aquifer interactions on land surface processes. In this study, we developed a fully coupled three-dimensional (3D) land surface and subsurface model at a high resolution (~1 km) that accounts for high-frequency hydrologic exchange flow conditions to investigate how river–aquifer interactions modulate surface water budgets in the Upper Columbia-Priest Rapids watershed, a typical semiarid watershed located in the northwestern United States where river stage fluctuates in response to reservoir releases changing. Our results show that the spatiotemporal dynamics of river–aquifer interactions are highly heterogeneous, driven mainly by river-stage fluctuations. Adding 6.64 × 10 6 m 3 year –1 of water over the watershed from the river to groundwater owing to the lateral flow, river–aquifer interactions led to an increase in soil evaporation and transpiration supplied by higher soil moisture content, particularly in deeper subsurface. In a hypothetic future scenarios where a 5-m rise in river stage was assumed, the hydrologic flow exchange rates were intensified, resulting in higher surface water over the entire watershed. Overall, lateral flow induced by river–aquifer exchanges leads to an increase in evapotranspiration of ~75% in the historical period and of ~83% in the hypothetical future scenario. Finally, our study demonstrates the potential of coupled model as an effective tool for understanding river–aquifer–land surface interactions, and indicates that river–aquifer interactions fundamentally alter the water balance of the riparian zone for the semiarid watershed and will likely become more frequent and intense in the future under the effects of climate change.
54 ENVIRONMENTAL SCIENCES↗
A comprehensive review on valorization of chestnut processing wastes into bio‐based composites and bioplastics
Abstract This review examines the characterization and utilization of chestnut processing wastes (35%) in the production of bioplastics and biocomposites. In this review, a Web of Science search without any publishing year restriction on the biochemical compositions of all the components of Castanea sativa . The obtaining of bioplastics and biocomposites based on C. sativa was reviewed. First, it highlights the biochemical composition and antioxidant properties of chestnut fruit, shell, burrs, leaves, flowers, and wood focusing on the most important compounds, such as phenolic acids, flavonoids, carbohydrates, Klason lignin, cellulose, and glucan, which can enhance the properties of these materials. Then the review covers using several chestnut extracts and fillers in bioplastics production through solvent casting technique. The mechanical, structural, bioactive properties, and moisture content were optimized through the composition and production. The color, UV absorption, antioxidant, and antimicrobial activity were also discussed. Biocomposites reinforced with chestnut burs, shells, or wood flour increased the intended properties. The enhancements in tensile strength, elastic modulus, and the effects of a pre‐treatment were evaluated. Additionally, it discusses material recovery, recycling, and reuse, particularly how it affects the biodegradability of composites incorporating chestnut waste residues. Highlights Chestnut fruit, shells, and burrs are rich in starch, lignin, and cellulose. The waste of chestnut processing can be used in bioplastics and biocomposites. Chestnut‐based films and biocomposites exhibit promising mechanical properties. The antimicrobial activity, making films, and composites proper for food packaging. New techniques boost performance, offering alternatives to conventional plastics.
Silva, Simão B. [REQUIMTE/LAQV, ISEP, Polytechnic ↗
Vacuum-assisted extrusion to reduce internal porosity in large-format additive manufacturing
Large-scale 3D printing of polymer composite structures has gained popularity and seen extensive use over the last decade. Much of the research related to improving the mechanical properties of 3D-printed parts has focused on exploring new materials and optimizing print parameters to improve geometric control and minimize voids between printed beads. However, porosity at the microstructural level (within the printed bead) has been much less studied although it is almost universally observed at levels of 4 %-10 % when using fiber reinforced materials. This study introduces a vacuum-assist approach that minimizes internal porosity by removing ambient air from the interstitial space between pellets in the hopper and acts as a negative pressure vent for gases that evolve during the initial stages of single-screw extrusion. Vacuum-assisted extrusion was able to reduce porosity below 2 % across a wide range of processing parameters, moisture content, fiber reinforcements, and printing platforms. Specifically, when printing on a large-format extruder (Strangpresse Model-30), the vacuum-assisted extrusion reduced internal porosity by 35–75 % compared to conventional non-vacuum extrusion, and only pores with length scale > 2 microns are affected. The success of this approach prompted the design of a patent-pending continuous vacuum hopper relevant for large-scale 3D printing on commercial systems.
36 MATERIALS SCIENCE↗
Validated model of a thermoelectric heat pump clothes dryer using secondary pumped loops
The energy associated with clothes drying makes up 4% of the total residential electrical energy consumption in the US. The cost is high since most clothes dryers use electric resistance heating which is inexpensive but also energy inefficient. State-of-the-art vapor-compression heat pump clothes dryers offer significant energy savings but have limited market penetration in the US. Here, a new configuration of clothes dryer was studied that utilizes a solid-state thermoelectric heat pump with pumped secondary water loops and conventional fin-and-tube water-to-air heat exchangers. Experimental results are presented for the thermoelectric dryer prototype with a combined energy factor of 6.89 lb BDW /kWh (specific moisture extraction rate of 1.71 kg w /kWh) and a dry time of 84 min for a standard load size of 8.45 lb (3.83 kg) with 57.5% starting moisture content. This is a 85% energy efficiency improvement over baseline electric resistance dryers. The efficiency and drying time results achieved are similar to vapor compression heat pump dryers. Compared to previous air-based thermoelectric clothes dryers, the energy efficiency has been increased by 6%, but drying time has been reduced by as much as 47% using secondary pumped loops and separate heat exchangers, which represents a significant advancement in the technology. In addition to the experimental prototype, a model was also developed to study the performance. The model was validated against experimental prototype data and used to identify the range of performance (dry time and efficiency) that could be expected of the design.
42 ENGINEERING↗
Thermoelectric heating and cooling–integrated dishwasher with thermal energy storage
Household dishwashers must address several performance goals: maximize washing and drying performance, while minimizing cycle duration, energy consumption, and water consumption. This study develops and examines a novel thermoelectric heating and cooling (TEHC) system with thermal energy storage applied to a household dishwasher (DW), aiming to improve the energy and drying performance of a commercially-available dishwasher while maintaining its washing performance, water consumption, and cycle duration. Experimental testing conducted on the novel TEHC-DW system demonstrates an 8.7% reduction in total energy consumption, lowering the per-cycle usage to 0.952 kWh, and a 40% reduction in energy consumption for internal water heating. The novel TEHC-DW system also demonstrates better drying performance, shortening the drying time by 42% to reach the same remaining moisture content as a commercially-available system. In addition, a resistance-capacitance network model is developed that predicts total drying time, total energy consumption, and the highest temperature reached in the tub (53.4 °C). The model accuracy is validated with experimental data (within ±1 K), and the model functions as a design tool via a parametric study to evaluate the next-generation design and the effect of the number of thermoelectric modules and thermoelectric driving force (i.e., current). Overall, this study demonstrates the potential for TEHC technology to improve energy efficiency and drying performance in household dishwashers.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Predicting the evolution of biomass bulk density through feedstock preprocessing: Discrete element modeling, regression analysis, and pilot-scale validation
Bulk density is an important material property of biomass feedstocks, influencing handling, storage, transport costs, and conversion efficiency. In this study, predictive regression models for loose and tapped bulk densities of Alamo and Cave-in-Rock switchgrass are developed using a comprehensive dataset generated via calibrated bonded-sphere discrete element method (DEM) simulations. Here, a key contribution of this study is the use of a DEM-based approach, which correlates density with moisture content and particle size distribution parameters and enables analysis across a continuous particle size range, overcoming limitations of purely experimental data. For comparison, regression models are also developed using only experimental data from pilot-scale runs at the Biomass Feedstock National User Facility at Idaho National Laboratory. Validation against pilot-scale data showed reasonable prediction accuracy for both model types, particularly for smaller particle sizes (post-secondary grinding). While the experimental model showed slightly better performance matching the validation data in some cases, the DEM-based model benefits from a much larger dataset, reduced predictor multicollinearity, and continuous parameter coverage, highlighting the utility of validated simulation models for developing robust predictive tools for biomass preprocessing applications.
09 - BIOMASS FUELS↗
A new phenomenological model to describe root-soil interactions based on percolation theory
In his paper on net primary productivity of terrestrial communities predicted from climatological data, Rosenzweig (1968) argued that variability in productivity is well accounted for by (evapo)-transpiration, and that water from transpiration is, on global scales, the most variable component in the photosynthesis reaction. The goal of this paper is to investigate whether variability in plant growth on local scales and within species is primarily related to transpiration under several scenarios including different terrain curvature, slope aspect, soil characteristics, and climate ranges. Here, we test the hypothesis that this relationship exists because root growth into the surface soil layers (0–2 m) tends to follow paths with minima in resistance, which in turn maximizes water flow and nutrient delivery rates that regulate growth. The set of all connected paths with individual pore-to-pore flow resistances less than a critical, percolating, value forms a cluster with mass fractal dimensionality, d f . We propose that roots follow paths through the 2D percolation cluster, defining the set of all optimal flow paths, making the 2D value of d f from percolation relevant to root fractal dimensionality. The tortuosity of such optimal paths as defined in percolation theory should then relate root length to root radial extent, linking the parameters of root tortuosity and plant productivity. Our analysis of large data sets across species implies that root radial extent and tree height are both proportional to cumulative transpiration until trees approached maximum height, and their growth rates are proportional to the transpiration rate, not to the moisture content. Local variations in tree height as functions of the variables investigated appear generally consistent with deduced variations in transpiration. Here this correlation is investigated more closely in the context of studies addressing individual tree species.
54 ENVIRONMENTAL SCIENCES↗
Optimization of harvest and logistics for multiple lignocellulosic biomass feedstocks in the northeastern United States
A mixed-integer linear programming model was developed to optimize the multiple biomass feedstock supply chains, including feedstock establishment, harvest, storage, transportation, and preprocessing. The model was applied for analyses of multiple biomass feedstocks at county level for 13 states in the northeastern United States. In the base case with a demand of 180,000 dry Mg/year of biomass, the delivered costs ranged from $\$67.90$ to $\$86.97$ per dry Mg with an average of $\$79.58$ /dry Mg. The biomass delivered costs by county were from $\$67.90$ to 150.81 per dry Mg across the northeastern U.S. Considered the entire study area, the delivered cost averaged $\$85.30$ /dry Mg for forest residues, $\$84.47$ /dry Mg for hybrid willow, $\$99.68$ for switchgrass and $\$97.87$ per dry Mg for Miscanthus. Seventy seven out of 387 counties could be able to deliver biomass at $84 per dry Mg or less a target set by US DOE by 2022. A sensitivity analysis was also conducted to evaluate the effects of feedstock availability, feedstock price, moisture content, procurement radius, and facility demand on the delivered cost. Lastly, our results showed that procurement radius, facility capacity, and forest residue availability were the most sensitive factors affecting the biomass delivered costs.
09 BIOMASS FUELS↗
4D electrical resistivity tomography for assessing the influence of vegetation and subsurface moisture on railway cutting condition
Instability of slopes, embankments, and cuttings on the railway network is increasingly prevalent globally. Monitoring vulnerable infrastructure aids in geotechnical asset management, and improvements to transport safety and efficiency. Here, we examine the use of a novel, near-real-time Electrical Resistivity Tomography (ERT) monitoring system for assessing the stability of a railway cutting in Leicestershire, United Kingdom. In 2015, an ERT monitoring system was installed across a relict landslide (grassed) and an area of more stable ground on either side (wooded), to monitor changes in electrical resistivity through time and space, and to assess the influence of different types of vegetation on the stability of transportation infrastructure. Two years of 4-Dimensional ERT monitoring results are presented here, and petrophysical relationships developed in the laboratory are applied to calibrate the resistivity models in order to provide an insight into hydrogeological pathways within a railway cutting. The influence of vegetation type on subsurface moisture pathways and on slope stability is also assessed – here we find that seasonal subsurface changes in moisture content and soil suction are exacerbated by the presence of trees (wooded area). This results in shrink-swell behaviour of the clays comprising the railway cutting, resulting in fissuring and a reduction in shear strength, leading to instability. As such, it is proposed that on slopes comprised of expansive soils, grassed slopes are beneficial for stability. Insights into the use of 4-D ERT for monitoring railway infrastructure gained from this study may be applied to the monitoring of critical geotechnical assets elsewhere.
58 GEOSCIENCES↗
Spatial and temporal characterization of municipal solid waste based on resource recovery pathways
This study presents a two-year, quarterly assessment of MSW across four source sectors (residential, schools, restaurants, and grocery stores) from sixteen sites across five U.S. states. MSW was manually sorted into 27 categories and aggregated into pathway fractions: high-moisture (HM) organics, low-moisture (LM) organics, recyclable (RC) materials, and residuals for disposal. Organics represented 89 % of the MSW stream. The largest fraction was HM organics consisting of food waste (31 %) and yard waste (3 %), with large coefficient of variations (CV), 79 and 278 %, respectively, reflecting high seasonal and site variability that varied significantly (p < 0.01) across sampling periods. The HM fraction showed properties favorable for anaerobic digestion, with moisture content ranging from 56 to 95 % and volatile solids ranges of 86-95 %. In contrast, the LM and RC fractions remained more stable (plastics CV = 41 %; paper CV = 53 %) with heating values up to 26.9 MJ/kg across sources, reflecting suitability for gasification. Microstructural analysis revealed less porosity in residential waste sampled at the landfill, which can influence preprocessing efficiency and microbial accessibility. Pathway informed allocations showed that 35 % of MSW is suitable for anaerobic digestion, 36 % for gasification, and 18 % for recycling, leaving 11 % requiring landfill disposal. These results provide quantitative evidence to determine feedstock allocation, waste-to-energy system design, and the development of data-driven sustainability and resource recovery strategies within a circular bioeconomy.
09 BIOMASS FUELS↗
Interpreting the spatial distribution of soil properties with a physically-based distributed hydrological model
Digital soil maps are commonly data-driven as the development of physically-based models for soil mapping is difficult due to the complexity of soils. However, physically-based hydrologic models have been successful in simulating water dynamics. Since water movement is a major driver of pedogenesis, the physical rules that govern water movement might help explain and predict the spatial variation of soil properties. Here, we demonstrate the novel use of a physically-based, distributed hydrologic model to inform the spatial distribution of soil properties. The Distributed Hydrology Soil Vegetation Model (DHSVM) was utilized to simulate soil moisture content (SM) and water table depth (WTD) in two hillslope catchments under pasture and forest management wherein hydrologic model outputs were then compared with soil properties measured in situ. SM sensors and wells were installed in both catchments to validate simulations of soil water movement via Nash-Sutcliffe Efficiency (E). In-situ observations were made at 87 sites within both catchments to study the connection between simulated water movement (SM and WTD) and observed soil properties, namely the depth and thickness of the argillic (Bt), fragic (Btx), and C horizons, and the depth of redoximorphic features. The simulated time series of SM and WTD were also clustered per season using Dynamic Time Warping (DTW), which identified similarity among time series at varying timescales. Model validation suggested that simulations of surficial SM (0–20 cm) were reasonable (E = 0.45), however, simulated subsurface SM (45–60 cm) and WTD were not sufficiently accurate. The thickness of Btx horizons were spatially grouped into different populations by SM clusters from every season except spring. For the other properties, only SM dynamics of specific seasons grouped into significantly different populations, suggesting that the explanatory power of simulated water movement varies seasonally and was greater during winter. Here, we show clusters of simulated SM separated soil properties into statistically different populations, showing that hydrologic models could inform areas that followed different water dynamics related to pedogenic trajectories and related biogeochemical processes not necessarily simulated by the model. As such, physically-based modeling of water dynamics can, therefore, inform and advance digital soil mapping by linking water movement patterns stemming from hydrologic model outputs to spatial patterns of soil properties and pedogenesis.
54 ENVIRONMENTAL SCIENCES↗
The effect of moisture on hydrocarbon-based solvent liquefaction of pine, cellulose and lignin
In this report we examined the effect of moisture on the solvent liquefaction of loblolly pine, cellulose, and lignin in tetralin at 280 °C and pressures ranging from 15 to 70 bar. Solvent liquefaction experiments were conducted in a quasi-batch reactor capable of continuous pressure control and external vapor condensation. Moisture was varied by the controlled addition of de-ionized water. Control over the system pressure subsequently impacted the removal of water vapor from the reactor. Liquid yield decreased by 25, 21, and 35 wt%, for pine, cellulose, and lignin, respectively, when moisture content was increased from 1 to 50 wt% at 42 bar. Humins were observed in the solid residue from liquefaction of wet cellulose. Wet lignin yielded a substantial amount of solid residue compared to dry lignin with a corresponding decrease in total phenolic monomer production. It was concluded that the ionic dissociation of water was an important factor in loss of liquid yield in the presence of water. Although water was less than 20 wt% of the solvent loading in these experiments, it strongly influenced the liquefaction of biomass and biomass components.
09 BIOMASS FUELS↗
Synergistic cellulase–xylanase formulations for enhanced dewatering and fiber bonding toward energy-efficient and sustainable paper and packaging production
A mechanistic understanding of the synergistic effects of enzymes on cellulosic fibers dewatering and fiber bonding is essential for advancing energy-efficiency and lightweight production of paper and packaging materials. This study investigates the impact of varying cellulase and xylanase formulations on equilibrium moisture content (EMC) after pressing and tensile strength of cellulosic fiber webs using a factorial experimental design. Nine custom enzyme formulations were evaluated at controlled dosages ranging from ∼20 to 76 FPU/mL cellulase and ∼500–1130 IU/mL xylanase. Response surface modeling revealed a significant synergy, particularly at 20–40 FPU/mL cellulase combined with ≥ 1000 IU/mL xylanase. Under these conditions, EMC decreased by up to 3.6% compared with the untreated refined control, while tensile index gains of up to 16% were statistically significant for optimized blends (p < 0.05). The interaction between cellulase and xylanase was also significant for the tensile response (p = 0.010). Protein efficiency analysis showed that optimized formulations containing 30–40% less protein outperformed the commercial benchmark. The nonlinear synergy between cellulase and xylanase is attributed to their complementary substrate specificities. Endoglucanase- and β‑glucosidase‑rich cellulases hydrolyze internal β‑1,4‑glycosidic bonds in amorphous cellulose, loosening fiber walls and increasing flexibility, while xylanases target hemicellulose, primarily xylan-rich domains, enhancing porosity and improve cellulase accessibility. Tailoring enzyme formulations at low loadings overcomes traditional trade-offs between strength and dewatering, enabling cost-effective, energy-efficient, low-carbon solutions for sustainable packaging and hygiene products.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Advancing process-based flood frequency analysis for assessing flood hazard and population flood exposure
Recent studies have showcased the use of process-based hydrological models with Stochastic Storm Transposition (SST) techniques to conduct Flood Frequency Analysis (FFA). This framework, referred hereby FFA-SST, has proved to be a robust strategy to estimate peak flows of specific annual exceedance probability (e.g., 100-year peak flow) that can reflect natural and anthropogenic disturbances, including changes in land use and meteorological patterns. With the objective of advancing the FFA-SST framework, this study presents for the first time the use of an Integrated Surface-Subsurface Hydrological Model (ISSHM) to conduct FFA-SST by extending the analysis from peak flow responses to flood extent, enabling a unique view and analysis of flood hazard and population flood exposure at the basin scale. As a proof-of-concept, we used the ISSHM, Advanced Terrestrial Simulator (Amanzi-ATS) model, and the SST model, RainyDay, to conduct FFA-SST by simulating the flood response to 5,000 annual synthetic storm events in a 2,227 $km^2$ Southeast Texas watershed. We demonstrate that ATS, without site-specific calibration, provides a robust process-based representation of peak flows, flood extent, streamflow, evapotranspiration, soil moisture content, and water storage changes. Our results and analyses, covering frequency curves up to a 500-year return period for peak flows, basin inundation fractions, and the number of people exposed to flooding, offer a unique perspective to analyze flood impacts across spatial scales. Overall, this study provides critical insights for flood risk management by extending the FFA-SST framework to include both flood hazard and population flood exposure analyses at the basin scale. Such an approach will empower stakeholders and disaster emergency agencies with a more comprehensive understanding of flood impacts across the entire basin domain, facilitating informed decision-making for flood risk assessment and management.
58 GEOSCIENCES↗
Water vapor transmission rate measurement for moisture barriers using infrared imaging
Here, in this work, we demonstrate a spatially resolved imaging methodology for water vapor transmission rate (WVTR) testing that relies on quantified infrared characterization at water absorption bands. This technique is validated using a moisture barrier on a polymer substrate via calibration of the infrared image intensity with moisture content in the polymer substrate from images taken at different times. The method is compared to existing state of the art techniques such as membrane permeation measurement with coulometric phosphorous pentoxide sensor and optical calcium film testing. This fast, non-destructive and in-situ method enables defect visualization and shows the WVTR with a sensitivity limit of 5·10 –5 g/m 2 /day.
47 OTHER INSTRUMENTATION↗
A High-Performance Discrete-Element Framework for Simulating Flow and Jamming of Moisture Bearing Biomass Feedstocks
We developed and verified a high-performance open-source discrete element method (DEM) solver with simultaneously-supported feedstock-specific interaction models, including bonded-sphere, liquid bridge, cohesion, and non-linear contact models. Our solver uses parallel data structures on hybrid central and graphics processing unit (CPU/GPU) architectures, with favorable strong scaling performance observed for large problem sizes comprised of (100 M particles), and 4X single-node GPU speedup. The particles for corn stover feedstock were conceptualized and calibrated based on experimental measurements and results. Sensitivity analyses demonstrate that the mass flow rate from a wedge hopper is governed primarily by moisture content, friction coefficient, and cohesion energy density. The model is used to reproduce experimentally observed hopper jamming results, highlighting that the experimental no-flow trends can only be achieved by using non-spherical particles, liquid bridge and cohesion models, highlighting the importance of using concurrent feedstock specialized models for the effective representation of biomass material handling problems.
bioenergy↗