Master of Science / Department of Biological & Agricultural Engineering / Ronaldo G. Maghirang / Particulate matter (PM) emissions from open beef cattle feedlots depend heavily on the level of water on the pen surface. Wet pen surfaces are able to keep PM emissions low, while dry surfaces have much higher rates of emission. Current research shows that 20-25% surface water content is a critical threshold for minimizing PM emissions from open cattle feedlots. The amount of water on the pen surface will also dictate the level of gaseous emissions, such as ammonia, nitrous oxide, and hydrogen sulfide. Traditional methods of measuring pen surface water are not sufficient within a dense cattle feedlot and cannot provide a continuous method of measurement unattended. The process of using infrared thermometry and meteorological variables to remotely sense surface water provides an inexpensive, ground level approach. Testing in laboratory, outdoor, and feedlot conditions was conducted to analyze the potential of using the thermal inertia remote sensing approach. This approach involved continuous measurement of weighted soil water content, surface temperature of the soil, air temperature, solar radiation, wind speed, and relative humidity. Controlled laboratory testing performed the best at predicting soil water content from the difference in soil surface and air temperature, with the coefficient of determination (R2) at 0.91 for a Smolan silt loam and 0.83 for dry feedlot soil. Outdoor testing achieved mixed results with R2 values only as high as 0.38 for 10-cm soil layer and 0.67 for 5-cm soil layer. Testing in a cattle feedlot with dry, loose manure layer proved to be imprecise, but was able to differentiate surface water levels varying from 4.1% to 9.1% wet basis.

Master of Science / Department of Biological & Agricultural Engineering / Ronaldo G. Maghirang / Military training lands can be significant sources of fugitive dust emissions due to wind erosion. This study was conducted to determine dust emission potential of soils due to wind erosion as affected by off-road military vehicle disturbance. Multi-pass traffic experiments using two types of vehicles (i.e., wheeled and tracked) were conducted on six soil textures at four military training facilities: Fort Riley, KS; Fort Benning, GA; Yakima Training Center, WA; and White Sands Missile Range (WSMR), NM. Prior to and after the preselected number of vehicle passes, soil samples at three locations were collected with minimum disturbance into trays. Adjacent to the location where tray samples were collected, a Portable In-Situ Wind Erosion Lab (PI-SWERL) was used to measure dust emission potential. The tray samples were tested in a laboratory wind tunnel (with sand abrader) for dust emission potential using a GRIMM aerosol spectrometer and gravimetric method with filters. Comparison of the PI-SWERL (with DustTrak™ dust monitor) and wind tunnel (with GRIMM aerosol spectrometer) measurement results showed significant difference in measured values but high correlation, particularly for soils with high sand content. Wind tunnel tests results showed that sampling locations significantly affected dust emissions for the tracked vehicles but not for the light-wheeled and heavy-wheeled vehicles. Also, soil texture, number of vehicle passes, and vehicle type significantly affected dust emissions. For the light-wheeled vehicles, dust emissions increased as the number of vehicle passes increased. From undisturbed conditions to 10 vehicle passes, there was a significant (P<0.05) increase in dust emissions (297%) on average for all light-wheeled vehicle tests. From 10 to 25 passes and 25 to 50 passes, an additional 52% and 62% increments were observed. For the tracked vehicle, for the straight section sampling location, dust emission increased as the number of vehicle passes increased. However, for the curve section, dust emissions at any level of pass were significantly higher than initial condition; beyond the first pass, no significant increase was observed.

Doctor of Philosophy / Department of Biological & Agricultural Engineering / James K. Koelliker / This research provides a deterministic model of in-vessel composting, based on Monod’s growth kinetics, to mirror biological-mixture decomposition. Existing models predict temperature curves assuming a single temperature-range organism, using a soluble (simple sugar) substrate, with bacteria as the microorganism, and they ignore the different temperature range environments that impact the growth rates of mesophilic and thermophilic microorganisms. The new computer-simulated model, written in MATLAB® by The MathWorks, has six unique features. First, three major carbon chain substrate groups are utilized: soluble, hemicellulose/cellulose, and lignin. An additional substrate group is used for inert substrates. Second, three major microorganism groups are utilized: bacteria for soluble substrate, actinomycetes for cellulose substrate, and fungi for lignin substrate. Third, two temperature-range microorganisms are included: mesophilic and thermophilic. Fourth, the model accounts for the death of microorganisms as the temperature transitions between the temperature ranges. Most of the dead cellular mass is returned to soluble substrate for reutilization and a portion is considered resistant to biological decomposition and is added into the lignin substrate. Fifth, stoichiometric equations account for substrate and microorganism compositions, oxygen and nitrogen requirements, and carbon dioxide and water production. Sixth, the relationship between biological activity and water is better defined. Experimental research was conducted to validate the model. Laboratory analysis distinguished the substrate types. The results indicate the model did differentiate between different levels of substrate types, and the mesophilic and thermophilic microorganism types. Also, the model did differentiate between the bacteria, actinomycetes and fungi. The influence was small, however, because of the different maximum growth rates of the three types of microorganisms. Returning dead microbes to the substrate pools as a result of temperature transitions affected the model results positively. Additional research is needed to account for the influence of volume reduction, develop a better microbial growth curve, include particle size influence, add temporal temperature fluctuations to the external boundary conditions, incorporate pH and nitrogen availability, and develop a three-dimensional model. KEY WORDS. Aerobic composting, mathematical composting model, substrate types, microorganism types, microorganism temperature range, mesophilic, thermophilic, microbial death utilization, moisture composting relationship.

Doctor of Philosophy / Department of Biological & Agricultural Engineering / James K. Koelliker / Over the past decades, it has been observed that the streamflow characteristics in the Great Plains rivers have substantially changed. These changes have affected and will continue to affect the management decisions within the watershed. This study was undertaken to document the changes for some unregulated streams in Kansas, characterize the streams in terms of some hydrologic indices, and identify the probable factors influencing the changes. Fourteen unregulated streams with 60 or more years of daily discharge data geographically distributed across the state were used. The analysis focused on hydrologic indices judged to be relevant to the lotic ecosystem. The state was divided into four regions, representing roughly the northwest, southwest, northeast and southeast sections of the state. Log Pearson III method was used for computing flow probabilities, Mann-Kendall test in conjunction with Sen’s slope estimator was used for trend analysis, whereas the indicators of hydrologic alterations software was used to generate most hydrologic indices. Several factors believed to affect the streamflow were identified, and their influence was modeled over time. A multi-variate statistical model was run. Results show that there is substantial difference in the streamflow characteristics between the western and eastern regions. Many streamflow aspects have changed over time, and a number of them show significant and important change. Most streams in western Kansas have longer and more frequent dry periods. Potential recharge rate, land use, water use, soil and water conservation practices, and soil type were significant factors influencing the median to very low flow, but the effect varied among the regions. Results of this study could be useful to decision makers, water users, watershed stakeholders, and environmental conservation advocates in addressing problems and concerns related to stream and river management.

Master of Science / Department of Biological & Agricultural Engineering / Naiqian Zhang / Four permittivity probes have been developed and tested to measure contaminants in water and in biodiesel fuel. An impedance meter was also used to measure the same contaminants. The pollutants measured in water were nitrate salts (potassium nitrate, calcium nitrate, and ammonium nitrate) and atrazine. The contaminants measured in biodiesel were water, glycerol, and glyceride. Each sensor measured the gain and phase of a sample with a known concentration of one of these pollutants. The resulting signals were analyzed using stepwise regression, partial least squares regression, artificial neural network, and wavelet transformation followed by stepwise regression to predict the concentration of the contaminant using changes in the gain and phase data measured by the sensor. The same methods were used to predict the molecular weight of the nitrate salts. The reliability of the probes and the regression methods were compared using the coefficient of determination and the root mean square error. The frequencies selected using stepwise regression were studied to determine if any frequencies were more useful than others in detecting the contaminants. The results showed that the probes were able to predict the concentration and the molecular weight of nitrates in water very accurately, with R2-values as high as 1.00 for the training data and 0.999 for the validation data for both concentration predictions and molecular weight predictions. The atrazine measurements were somewhat promising, the training R2-values were as high as 1.00 in some cases, but there were many low validation values, often below 0.400. The results for the biodiesel tests were also good; the highest training R2-value was 1.00 and the highest validation R2-value was 0.966.

Doctor of Philosophy / Department of Biological & Agricultural Engineering / Mark E. Casada / Ronaldo G. Maghirang / The United States grain handling infrastructure is facing major challenges to meet worldwide customer demands for wholesome, quality, and safe grains and oilseeds for food and feed. Several challenges are maintaining grain quality during handling; reducing dust emissions for safety and health issues; growing shift from commodity-based to specialty (trait-specific) markets; proliferation of genetically modified crops for food, feed, fuel, pharmaceutical, and industrial uses; and threats from biological and chemical attacks. This study was conducted to characterize the quality of grain and feed during bucket elevator handling to meet customer demand for high quality and safe products. Specific objectives were to (1) determine the effect of repeated handling on the quality of feed pellets and corn; (2) characterize the dust generated during corn and wheat handling; (3) develop and evaluate particle models for simulating the flow of grain during elevator handling; and (4) accurately simulate grain commingling in elevator boots with discrete element method (DEM). Experiments were conducted at the research elevator of the USDA-ARS Center for Grain and Animal Health Research (CGAHR) to determine the effect of repeated handling on the quality of corn-based feed pellets and corn. Repeated handling did not significantly influence the durability indices of feed pellets and corn. The feed pellets, however, had significantly greater breakage (3.83% per transfer) than the corn (0.382% per transfer). The mass of particulate matter < 125 μm was less for feed pellets than for corn. These corn-based feed pellets can be an alternative to corn in view of their handling characteristics. Another series of experiments was conducted in the same elevator to characterize the dust generated during corn and wheat handling. Dust samples were collected from the lower and upper ducts upstream of the cyclones in the elevator. Handling corn produced more than twice as much total dust than handling wheat (185 g/t vs. 64.6 g/t). Analysis of dust samples with a laser diffraction analyzer showed that the corn samples produced smaller dust particles, and a greater proportion of small particles, than the wheat samples. Published data on material and interaction properties of selected grains and oilseeds that are relevant to DEM modeling were reviewed. Using these material and interaction properties and soybeans as the test material, the DEM fundamentals were validated by modeling the flow of soybean during handling with a commercial software package (EDEM). Soybean kernels were simulated with single- and multi-sphere particle shapes. A single-sphere particle model best simulated soybean kernels in the bulk property tests. The best particle model had a particle coefficient of restitution of 0.6; particle static friction of 0.45 for soybean-soybean contact (0.30 for soybean-steel interaction); particle rolling friction of 0.05; normal particle size distribution with standard deviation factor of 0.4; and particle shear modulus of 1.04 MPa. The single-sphere particle model for soybeans was implemented in EDEM to simulate grain commingling in a pilot-scale bucket elevator boot using 3D and quasi-2D models. Pilot-scale boot experiments of soybean commingling were performed to validate these models. Commingling was initially simulated with a full 3D model. Of the four quasi-2D boot models with reduced control volumes (4d, 5d, 6d, and 7d; i.e., control volume widths from 4 to 7 times the mean particle diameter) considered, the quasi-2D (6d) model predictions best matched those of the initial 3D model. Introduction of realistic vibration motion during the onset of clear soybeans improved the prediction capability of the quasi-2D (6d) model. The physics of the model was refined by accounting for the initial surge of particles and reducing the gap between the bucket cups and the boot wall. Inclusion of the particle surge flow and reduced gap gave the best predictions of commingling of all the tested models. This study showed that grain commingling in a bucket elevator boot system can be simulated in 3D and quasi-2D DEM models and gave results that generally agreed with experimental data. The quasi-2D (6d) models reduced simulation run time by 29% compared to the 3D model. Results of this study will be used to accurately predict impurity levels and improve grain handling, which can help farmers and grain handlers reduce costs during transport and export of grains and make the U.S. grain more competitive in the world market.

Doctor of Philosophy / Department of Biological & Agricultural Engineering / Naiqian Zhang / Soil surface roughness is a major factor influencing soil erosion by wind and water. Studying surface roughness requires accurate Digital Elevation Model (DEM) data. A vehicle-based laser measurement system was developed to generate high-resolution DEM data. The system consisted of five units: a laser line scanner to measure the surface elevation, a gyroscope sensor to monitor the attitude of the vehicle, a real-time kinematic GPS to provide the geographic positioning, a frame-rail mechanism to support the sensors, and a data-acquisition and control unit. A user interface program was developed to control the laser system and to collect the sensors data through a field laptop. Laboratory experiments were conducted to evaluate the performance of the laser sensor on different type of targets. The results indicated that the laser measurement on a white paper had the least variability than that on other targets. The laser distance measurement was calibrated using the data acquired on the white paper. Static accuracy tests of the gyroscope sensor on a platform that allowed two-axis rotations showed that angle measurement errors observed in combined pitch/roll rotations were larger than those in single rotations. Within ±30° of single rotations, the measurement errors for pitch and roll angles were within 0.8° and 0.4°, respectively. A model to study the effect of attitude measurement error on elevation measurement was also developed. DEM models were created by interpolating the raw laser data using a two-dimensional, three-nearest neighbor, distance-weighted algorithm. The DEM models can be used to identify shapes of different objects. The accuracy of the laser system in elevation measurement was evaluated by comparing the DEM data generated by the laser system for an unknown surface with that generated by a more accurate laser system for the same surface. Within four replications, the highest correlation coefficient between the measured and reference DEMs was 0.9371. The correlation coefficients among the four replications were greater than 0.948. After a median threshold filter and a median filter were applied to the raw laser data before and after the interpolation, respectively, the correlation coefficient between the measured and reference DEMs was improved to 0.954. Correlation coefficients of greater than 0.988 were achieved among the four replications. Grayscale images, which were created from the intensity data provided by the laser scanner, showed the potential to identify crop residues on soil surfaces. Results of an ambient light test indicated that neither sunlight nor fluorescent light affected the elevation measurement of the laser system. A rail vibration test showed that the linear rail slightly titled towards the laser scanner, which caused small variations in the pitch angle. A preliminary test on a bare soil surface was conducted to evaluate the capability of the laser system in measuring the DEM of geo-referenced surfaces. A cross-validation algorithm was developed to remove outliers. The results indicated that the system was capable of providing geo-referenced DEM data.

Doctor of Philosophy / Department of Biological and Agricultural Engineering / Naiqian Zhang / An optical sensor for determining water velocity in natural open channels like creeks and rivers has been designed and tested. The sensor consists of a plastic body which is shaped so that water flows through a U-shaped channel into which are mounted LEDs and matching phototransistors at various angles. A small amount of dye is injected into the water just upstream of two sets of LEDs and phototransistors which are spaced 4 cm apart. The time delay between the dye’s effects on these signals depends on water velocity and is determined using a biased cross correlation calculation. In addition to providing velocity, the LEDs and phototransistors can also be used to estimate soil sediment concentration. A previous version of the sensor was tested in enclosed flow to confirm that the general design of the sensor, including LEDs, phototransistors, dye and electronics, would indeed work to detect the velocity of water flowing through the sensor. Although the conditions for the test were unlike those experienced in natural open channels, the ability to catch all the fluid flowing through the sensor provided a simple confirmation of the velocity estimate that was not available in field settings. Further testing in the field then confirmed that the sensor worked in the field but also identified several areas needing improvement. Computational fluid dynamics was used to improve the sensor body. The electronics and program running the sensor were also redesigned. After making these improvements, a new version of the sensor was produced. The testing of the new version of the sensor confirmed its ability to accurately detect velocity in natural open channels. The velocity measurements from this sensor were compared to the commercially available Flowtracker velocity sensor. A regression analysis on the measurements from the two sensors found that the velocity measurements from each sensor were nearly identical across a range of velocities. Other tests established that the electronics and programming running the sensor performed as designed. The development and testing of this sensor has resulted in a system which works in natural open channels like creeks and rivers.

Master of Science / Department of Biological and Agricultural Engineering / Donghai Wang / Biomass torrefaction is an important preprocessing step in improving biomass quality, specifically in terms of physical properties and chemical composition. The objective of this research was to study effects of torrefaction as a pretreatment method on chemical and elemental compositions and thermal properties of Conservation Reserve Program (CRP) biomass. Most CRP grasslands are a mixture of native grasses, and in the state of Kansas, species including indiangrass, big bluestem, little bluestem, sideoats grama, and switchgrass comprise a majority of CRP grounds. Pure forms of big bluestem biomass were analyzed and compared with a mixture of the species that make up CRP lands. Two strategies for torrefaction were tested: one with a pre-dry step and one without. After torrefaction, big bluestem and CRP biomass showed an increase in energy density, making the biomass more attractive as a biofuel source than raw biomass. Big bluestem also showed slightly higher calorific values than that of CRP biomass. The torrefaction process had a significant effect on chemical composition and elemental composition of the biomass. Carbon content increased and oxygen content decreased as torrefaction temperature increased. Glucan and xylose decreased and lignin increased as torrefaction temperature increased. Pre-drying biomass before torrefaction is beneficial to torrefaction of biomass with high moisture content because moisture removal leads to less dry matter loss while maintaining the same calorific value.

Master of Science / Department of Biological and Agricultural Engineering / Ronaldo G. Maghirang / Military installations in the United States may be large sources of fugitive dust emissions. Off-road vehicle training can contribute to air quality degradation resulting from increased wind erosion events as a result of soil disruption; however, limited information exists regarding the impacts of off-road vehicle maneuvering. This study was conducted to determine the effects of soil texture and intensity of training with off-road vehicles on fugitive dust emission potential due to wind erosion at military training installations. Multi-pass trafficking experiments, involving wheeled and tracked military vehicles (i.e., M1A1 Abrams tank, M925A1 water tanker and various HMMWV models), were conducted at three military training facilities with different climate and soil texture (i.e., Fort Riley, KS; Fort Benning, GA; and Yakima Training Center, WA). Dust emissions were measured on site using a Portable In-Situ Wind Erosion Laboratory (PI-SWERL) coupled with a DustTrak™ dust monitor. In addition, a top layer of soil was collected in trays and tested in a laboratory wind tunnel for dust emission potential. In wind tunnel testing, the amount of emitted dust was measured using glass-fiber filters through high-volume samplers. Also, the particle size distribution and concentration of the emitted dust were measured using a GRIMM aerosol spectrometer. Comparison of the PI-SWERL (with DustTrak™ dust monitor) and wind tunnel test (with GRIMM aerosol spectrometer) results showed significant difference and little correlation. Also, comparison of the filter and GRIMM aerosol spectrometer data showed significant difference but high correlation. The dust emission potential (as measured with the GRIMM spectrometer) was significantly influenced by soil texture, vehicle type and number of passes. For the light-wheeled vehicle, total dust emissions increased from 66 mg m-2 for undisturbed soil to 304 mg m-2 (357%) and 643 mg m-2 (868%) for 10 and 50 passes, respectively. For the tracked vehicle, an average increase in total dust emission of 569% was observed between undisturbed conditions and 1 pass, with no significant increase in emissions potential beyond 1 pass. For the heavy-wheeled vehicle, emissions increased from 75 mg m-2 for undisturbed soil to 1,652 mg m-2 (1,369%) and 4,023 mg m-2 (5,276%) for 10 and 20 passes, respectively. Soil texture also played an important role in dust emission potential. For all treatment effects, there was a 1,369% difference in emissions between silty clay loam soil and loamy sand soil.