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Time dependent signatures: Moisture content interpretation in well logging applications with a D-T neutron generator
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Data-driven acoustic measurement of moisture content in flowing biomass
Measuring the moisture content in flowing biomass is critical to processes such as liquid biofuel conversion, such as biogasoline, biodiesel, bio jet kerosene, etc. However, biomass tends to flow in aggregates, which results in significant inhomogeneities in the amount of biomass flowing in front of a sensor at a given time, and there can be significant overlap in the material properties of dry vs wet biomass, leading to poor signal-to-noise ratio. We present a technique for identifying biomass moisture content using a series of acoustic pitch-catch measurements to quantify the sound speed and acoustic amplitude through the biomass, in conjunction with classical machine learning techniques, including Naive Bayes, Random Forest, and K-Nearest Neighbors classification. We amplify the differences between the acoustic measurements in different moisture levels by collecting a series of pulse-echo measurements, which we sort in order of ascending sound speed. We test the accuracy of the technique on experimentally-prepared batches of corn stover biomass with specified moisture levels and measure the average error in the estimated moisture level as a function of the number of pitch-catch measurements used. We observe average estimation errors as low as 6.7% by increasing the number of measurements and optimizing the hyperparameters. This work presents a novel method determining moisture content in flowing biomass with inhomogeneous flow. Additionally, this technique has application in optimizing biomass conversion processes, as well as other fields including, paper production, natural fiber processing, and mineral extraction.
Measuring the Moisture Content of Wood Sheathing with Continuous Wave Radars
Radars were studied for measuring the moisture content of wood-based materials because of their non-destructive nature and their ability to measure the moisture content of several layers at once. These convenient characteristics enable a quick and non-invasive method to find areas of high moisture content in building envelopes so that problems can be fixed before the structure degrades. The need to operate the radar at millimeter ranges required the development of new techniques and methods for analyzing and calculating the moisture content of individual layers of building material. The techniques are providing accurate results for oriented strand board, and efforts are continuing for investigating other construction materials, meeting FCC requirements, and building a system that will be easy to deploy.
Data Acquisition System Selection and Calibration of Resistive Moisture Content Measurements for Large-Scale Field Studies in Cold Climate Residential Building Envelope Performance
The residential building stock built before the energy codes were enforced has several significant inefficiency problems in terms of insulation and air leakage. To decrease these inefficiencies, building retrofits are necessary. However, if the envelope is not appropriately designed, excessive accumulation of moisture content and thus mold formation and decay inside the envelope layers can be a vital problem. This risk becomes higher, especially in extreme climate conditions such as cold winters and hot and humid summers as in some northern regions of the U.S. Field studies are essential to test the long-term hygrothermal performance of building envelopes. Although in-situ temperature, RH, and heat flux measurements are straightforward, moisture content measurements are cumbersome. Mainly, because of the heterogeneous nature of the wood materials, deviations and nonuniformities within the materials are unavoidable. Resistance measurements are one of the oldest methods used to measure the moisture content of wood and other building materials. In large-scale studies, it is commonly preferred to use multi-purpose data acquisition systems (DAQ) and custom-made or prefabricated moisture pins to measure the electrical resistance (and thus moisture content) of critical building materials. These multi-purpose DAQ systems generally provide lower costs and offer more flexibility. However, these systems require calibration and fine-tuning to achieve accurate moisture content measurements. A large-scale, two-year-long field study was conducted in northern Minnesota to monitor the hygrothermal performance of residential retrofit wall systems in cold climates. Two base case walls and sixteen different wall treatments were tested. Moisture contents were measured at various layers in each wall treatment using 85 sets of moisture pins. This paper focuses on the overall approach, fabrication, and calibration methodology for the combination of custom-made moisture pins and a multi-purpose DAQ. The aim is to directly use the low-excitation multi-purpose DAQ without any extra voltage regulator. A half-bridge circuit is used to measure wood resistance with 4V excitation voltage and 100 kΩ and 500 kΩ reference resistors. The system is calibrated for four different materials: Douglas fir, lodgepole pine, western red cedar, and oriented strand board (OSB). Calibration experiments were done under controlled conditions in 50% and 65% RH test chambers. Resistance-based moisture content calibration curves are obtained for each species. Results show that higher reference resistors provided better calibration curves for lower excitation voltages.
Modeling the Moisture Content and Dry Matter Loss in Dynamic Woody Biomass Storage Piles with Variable Extraction
The urgent need to mitigate climate change has spurred significant interest in renewable energy sources. This paper explores the storage and processing of woody biomass for biofuel production, considering the dynamic nature of biomass piles in real-world scenarios. A model has been developed to analyze moisture content changes and dry matter loss in woody biomass stored in piles prior to processing, taking into account varying extraction methods and environmental conditions. Case studies that examine the effects of different unpiling methods (FIFO, LIFO, and homogeneous) on moisture content and dry matter loss under various feedstock arrival rates and weather conditions are presented. Results indicate that unpiling methods significantly impact moisture content, with LIFO typically resulting in higher moisture content due to the utilization of fresher feedstock. Dry matter loss increases with pile size and time, emphasizing the importance of accurate modeling for assessing carbon emissions and feedstock quality. Furthermore, the model highlights the importance of process loading order and extraction methods in biomass storage, suggesting potential cost benefits associated with decreased moisture content. The difference between different extraction methods could vary the moisture content in the feedstock reaching the biofuel process by as much as 37.6%, however dry matter loss varies minimally for realistic pile changes. Overall, this research contributes to a better understanding of biomass storage dynamics and informs sustainable biofuel production practices.
The microbiome structure of decomposing plant leaves in soil depends on plant species, soil pore sizes, and soil moisture content
Microbial communities are known as the primary decomposers of all the carbon accumulated in the soil. However, how important soil structure and its conventional or organic management, moisture content, and how different plant species impact this process are less understood. To answer these questions, we generated a soil microcosm with decomposing corn and soy leaves, as well as soil adjacent to the leaves, and compared it to control samples. We then used high-throughput amplicon sequencing of the ITS and 16S rDNA regions to characterize these microbiomes. Leaf microbiomes were the least diverse and the most even in terms of OTU richness and abundance compared to near soil and far soil, especially in their bacterial component. Microbial composition was significantly and primarily affected by niche (leaves vs. soil) but also by soil management type and plant species in the fungal microbiome, while moisture content and pore sizes were more important drivers for the bacterial communities. The pore size effect was significantly dependent on moisture content, but only in the organic management type. Overall, our results refine our understanding of the decomposition of carbon residues in the soil and the factors that influence it, which are key for environmental sustainability and for evaluating changes in ecosystem functions.
Dynamic Life-Cycle Analysis of Fast Pyrolysis Biorefineries: Impacts of Feedstock Moisture Content and Particle Size
The commercialization of biorefineries has been met with significant obstacles due to the technical difficulties of handling solid biomass feedstocks, which are highly variable in physical properties and chemical compositions. An understanding of the principles of unit operations along the supply chain is key to the success of the biofuel industry. This study applies a dynamic life-cycle analysis (DLCA) methodology by developing quantitative relationships between the inputs and outputs for each unit operation based on scientific understanding of the causal effects. Using the DLCA, we assessed system sustainability of drop-in fuel production from fast pyrolysis of pine residues followed by hydro-processing. Life-cycle greenhouse gas (GHG) emissions were calculated for 4641 runs involving two key feedstock parameters: moisture content after field drying and particle size of the feed to pyrolyzer. Moisture contents varied between 25% and 35%, while particle sizes varied between 0.5 and 5 mm in these runs. The life-cycle GHG emissions of these cases vary from 22 to 40 g/MJ. Close examination of each unit operation's contribution to the total GHG emissions reveals that low moisture content after field drying produces savings in energy consumption during feedstock transportation and on-site drying. However, although small particle size leads to overall higher fuel yield, it also requires a significant amount of energy for feedstock size reduction and fuel production. The energy penalty outweighs the benefit of increased fuel yields, especially when fine particles (<1 mm) are used for pyrolysis; thus, small particle size leads to increased GHG emissions overall. The results highlight the trade-offs between the energy demand for preprocessing and the conversion yields, which can be addressed with DLCA.
High-moisture pelleting of corn stover using pilot- and commercial-scale systems: Impact of moisture content, L / D ratio and hammer mill screen size on pellet quality and energy consumption
Here, high-moisture pelleting of corn stover was tested in pilot- and commercial-scale systems. For the pilot-scale study, a 6.35 mm screen size hammer mill ground corn stover was reconditioned to moisture between 14 and 29.6% (w.b.), and 5, 7 and 9 L/D ratio pellet die were used. At 29% corn stover moisture content and L/D ratios of 5 and 9, the bulk density and durability of the pellets were ≤450 kg/m 3 and <90% and >540 kg/m 3 and >90%, respectively. Increasing the feedstock moisture and L/D ratio increased the pelleting energy. Increasing the hammer mill screen size to 11.11 mm reduced the bulk density but not the durability. The response surface models adequately described the pelleting process (R 2 ≥ 0.88), and analysis of variance showed a strong interaction between the process variables and pellet properties. Commercial-scale testing of high-moisture pelleting using 6.35 mm ground corn stover bales in the moisture range 24–26% (w.b.) produced pellets with a density of >675 kg/m 3 and durability of >98%, whereas increasing the hammer mill screen size to 11.11 mm reduced the bulk density by about 100 kg/m 3 but not the durability. The energy consumption of the commercial-scale unit operations for the high-moisture pelleting process was in the range 98–124 kW h/ton, which is 64–72% less energy than conventional pelleting that requires energy about 350 kW h/ton for biomass drying from 30% (w.b.) to 10% (w.b.) moisture content before pelleting. Pellets produced using high-moisture pelleting met International Organization for Standardization and Pellets Fuel Institute international standards. Published 2023. This article is a U.S. Government work and is in the public domain in the USA.
Dead Fuel Moisture Content Reanalysis Dataset for California (2000–2020)
This study presents a novel reanalysis dataset of dead fuel moisture content (DFMC) across California from 2000 to 2020 at a 2 km resolution. Utilizing a data assimilation system that integrates a simplified time-lag fuel moisture model with 10-h fuel moisture observations from remote automated weather stations (RAWS) allowed predictions of 10-h fuel moisture content by our method with a mean absolute error of 0.03 g/g compared to the widely used Nelson model, with a mean absolute error prediction of 0.05 g/g. For context, the values of DFMC in California are commonly between 0.05 g/g and 0.30 g/g. The presented product provides gridded hourly moisture estimates for 1-h, 10-h, 100-h, and 1000-h fuels, essential for analyzing historical fire activity and understanding climatological trends. The methodology presented here demonstrates significant advancements in the accuracy and robustness of fuel moisture estimates, which are critical for fire forecasting and management.
Rheological effects of moisture content on the anatomical fractions of loblolly pine (Pinus taeda)
Here, this study focused on assessing the influence of moisture content on the rheological properties of different anatomical fractions of pine residue using the FT4 powder rheometer. Moisture content exhibited some influence on the 2 mm bark and needle fractions, increasing their cohesion, angle of internal friction, unconfined yield strength, and major principal stress. Stem and whole, on the other hand, presented minimal changes upon moisture introduction. All 4 mm fractions did not show many changes in their rheological properties with moisture introduction, which can be due to less particle-particle interactions and consequently reducing any liquid bridging the particles might undergo; however, they were shown to have a more unpredictable behavior compared to the 2 mm analogues (i.e., higher standard deviation) which can be due to a higher degree of particle-interlocking. Out of the three fractions, needle presented the poorest rheological properties for flowability in addition to being susceptible by moisture, unlike other fractions.
Impacts of caking on corn stover – An assessment of moisture content and consolidating pressure
Caking or time consolidation of powders is a serious problem which can hinder productivity and overall feasibility of various industrial processes. Here this study focuses on the impacts moisture content and consolidating pressures can have on 2 mm corn stover samples after undergoing a drying treatment at different times. Individually, moisture content and consolidating pressure did not exhibit any significant changes throughout the modified variable flow rate tests using the FT4 powder rheometer. However, applying both variables simultaneously yielded higher-than-usual energy outputs from the corn stover, indicative of biomass agglomeration due to the moisture and its subsequent evaporation while under pressure via the induced consolidating pressure. However, despite the increase in energy usage, time dried did not have a direct effect and demonstrated no trend.
Validation and moisture content sensitivity analysis of cross-laminated timber wall assemblies in EnergyPlus
Cross-laminated timber buildings are becoming more common in North America, with many numerical studies showing potential energy savings. However, no studies have validated any EnergyPlus heat transfer algorithms or quantified their accuracy in simulating CLT in building envelopes. This study empirically validates the heat flux predictions for each of EnergyPlus's heat transfer algorithms (Conduction Transfer Functions (CTF), Effective Moisture Penetration Depth (EMPD), Conduction Finite Difference (CondFD), and Heat and Moisture Transfer (HAMT)) for two different CLT ply thicknesses with both summer and winter boundary conditions measured in controlled lab experiments. It also evaluates the model sensitivity of heat flux and heating and cooling loads to moisture content. The 1D validation shows that the HAMT model is the most accurate among all algorithms. All EnergyPlus's heat flux predictions are accurate independent of CLT plate thickness for summer conditions. However, the three constant property algorithms (CTF, EMPD, and CondFD) underpredict heat flux throughout the whole day during winter conditions. The 1D sensitivity analysis indicates that elevated moisture content can increase peak heat fluxes through the material by up to 20 %. Finally, the whole building model sensitivity analysis shows increased heating load and slight cooling load variation due to increased moisture content when using constant property models. The analysis shows significantly lower peak thermal demand (7 % lower heating and 6 % lower cooling) and monthly thermal load (8 % less cooling and 6 % less heating) predictions when using HAMT vs a constant property model.
Data and scripts associated with “Moisture content modulates DOM thermodynamic regulation of oxygen consumption in drying streambed sediments”
This data package is associated with the publication “Moisture content modulates DOM thermodynamic regulation of oxygen consumption in drying streambed sediments” published in Scientific Reports (Garayburu-Caruso et al., 2026). The package contains processed data products and scripts used to quantify how drying and re-inundation of riverbed sediments influence dissolved organic matter (DOM) thermodynamic properties and their relationship with sediment oxygen (O₂) consumption across 33 stream sites in the contiguous United States. The data package contains DOM thermodynamic metrics (e.g., Gibbs free energy of carbon oxidation and thermodynamic efficiency), and O₂ consumption along with watershed-scale climate and land-cover metrics used as explanatory variables in the analyses. Underlying unprocessed and processed ultrahigh-resolution mass spectrometry data, oxygen consumption rates from laboratory moisture-manipulation experiments, within-sample environmental properties, sediment moisture content and contextual field measurements are archived separately at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2428003 (Laan et al., 2024) and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1923689 (Forbes et al.,2023). A preliminary version of this data package was published in February 2026 at the time of manuscript submission. It was updated in June 2026, at the time of manuscript acceptance, to include the finalized data and additional metadata (readme, data dictionary, and file level metadata). For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. At the top level, the data package is organized into five main folders: (1) Data, (2)Figures, (3) Map, (4) GAM_Reulsts, and (5) src. The Data folder contains analysis-ready tabular files with oxygen consumption rates, DOM thermodynamic properties by site and treatment, site-level environmental variables, watershed-scale metrics, and other derived variables referenced in the manuscript. The Figures folder contains static image files associated with the main text and supplemental figures, while the Map folder includes spatial data and map-layer files used to create the sampling-location map. The GAM results folder contains the results for each of the general additive model (GAM).The src folder contains R scripts used to perform data processing, statistical analyses (including clustering, generalized additive models, and threshold analysis), and figure generation. This data package is associated with a GitHub repository found at https://github.com/WHONDRS-Hub/ECA_DOM_Thermodynamics.
Effect of Moisture Content on Shear Properties of Boron Carbide (B4C) Powder
Effect of Moisture Content on Shear Properties of Boron Carbide (B4C) Powder
EFFECT OF MOISTURE CONTENT ON SHEAR PROPERTIES OF BORON CARBIDE (B4C) POWDER
EFFECT OF MOISTURE CONTENT ON SHEAR PROPERTIES OF BORON CARBIDE (B4C) POWDER
Dual frequency comb spectroscopy of solid fuel pyrolysis and combustion: Quantifying the influence of moisture content in Douglas fir
As the fire research community develops multi-scale models to predict the spread of wildland fires, there is a need for well-controlled, small-scale experiments which provide benchmark data and fundamental understanding of the effects of key parameters on the combustion of wildland fuels. Here, we implement a unique suite of non-intrusive, quantitative diagnostics that simultaneously measure mass loss, surface temperature, in situ gas temperature and water vapor concentration, including the first implementation of dual frequency comb spectroscopy for the study of solid fuels. As a demonstration, we examine the effect of fuel moisture content on the burning of Douglas fir wood samples that are ignited under constant radiative heat flux from a cone calorimeter to provide benchmark data for multi-scale models. Peak flame temperatures 3 mm above the sample surface measured with the dual frequency comb laser spectrometer are in excess of 1200 K. The flame temperature decreases by over 150 K as fuel moisture content increases from 0.7% to 40%. This work demonstrates a platform for simultaneous, quantitative measurements of well-controlled small-scale experiments which provide benchmark data for the development of advanced modeling and simulations capable of capturing the complex physics present in wildland fire systems.
Throughfall-Reduction Drying Effects on Forest Floor Plant Tissue Biomass (Oi+Oe soil horizons) and Moisture Content in Four Lowland Panamanian Forests
Objectives: Climatic drying is predicted for many tropical forests, yet effects on soil properties across moisture and soil gradients within tropical forests remain poorly characterized, hampering predictions of forest-climate feedbacks. We hypothesized that drying would suppress soil CO2 fluxes (i.e., respiration) in already-drier tropical forests by further reductions in soil moisture, but increases CO2 fluxes in wetter tropical forests by alleviating anaerobiosis and soil saturation. We measured soil CO2 fluxes, soil moisture, soil temperature, and forest floor biomass during wet-dry cycles (2015 – 2022) in four Panamanian forests that vary in rainfall and soil fertility. We also surveyed all tree species and identified to species in 2018 and 2019.Results: We found that soil moisture peaked in the wet season and declined in the dry season. Measured soil CO2 fluxes declined in the dry season and peaked in the early wet season ahead of peak soil moisture, resulting in a lower soil moisture optimum for respiration than previously modeled. Forest floor biomass peaked in the dry season, in contrast. Chronic throughfall exclusion also suppressed soil moisture across the four forests to 20cm depths, and also initially suppressed soil CO2 fluxes across forests. There was sustained suppression of soil CO2 fluxes after four years in the wettest forest only (-28 ± 4% during the dry season), but elevated soil CO2 fluxes in a fertile forest after four years (+75 ± 28% during the late wet season). The unexpected negative drying effect in the wettest, most infertile forest could have resulted from reduced vertical flushing of nutrients into soils, as the drying effect increased with time. Including hydro-nutrient interactions in ecosystem models could improve predictions of tropical forest-climate feedbacks (results presented in Cusack et al. 2023). Datasets included: Datasets included here include .csv and .xls files for forest floor biomass (equivalent to the Oi+Oe soil horizons), and a subset include forest floor biomass moisture content (weight/weight) in the study plots. There is also a .kml file that includes coordinates for all 32 plots included in the study of four forests (n = 4 throughfall reduction and n = 4 control plots per site). No special software is needed to open these files.