James Wooten

Co-gasification of hardwood chips and crude glycerol in a pilot scale downdraft gasifier.

Seeking appropriate approaches to utilize the crude glycerol produced in biodiesel production is very important for the economic viability and environmental impacts of biodiesel industry. Gasification may be one of options for addressing this issue. Co-gasification of hardwood chips blending with crude glycerol in various loading levels was undertaken in the study involving a pilot scale fixed-bed downdraft gasifier. The results indicated that crude glycerol loading levels affected the gasifiers performance and the quality of syngas produced. When crude glycerol loading level increased, the CO, CH(4), and tar concentrations of the syngas also increased but particle concentration decreased. Though further testing is suggested, downdraft gasifiers could be run well with hardwood chips blending with liquid crude glycerol up to 20 (wt%). The syngas produced had relatively good quality for fueling internal combustion engines. This study provides a considerable way to utilize crude glycerol.

IMAGE-BASED SWEETPOTATO YIELD AND GRADE MONITOR

An image-based system for monitoring yield and grade of sweetpotatoes was developed. Estimates of weight werebased on multiple-linear regression and neural networks, while grade classifications were based on linear discriminant analysisand neural networks. Sweetpotato features considered were pixel area, polar moment of inertia, rectangular height and width,and length of major and minor axes. The system was tested on stationary sweetpotatoes in the laboratory. Its estimates ofsweetpotato weights were highly correlated (R2 = 0.96) with actual weights, and grade classifications of marketable sweetpotatoeswere over 90% accurate. The system was also tested on sweetpotatoes moving on a harvester’s conveyor belt in the field. In thisportion of the study, estimates of sweetpotato weights were still highly correlated (R2 = 0.91), albeit not as strongly, with actualweights. Grade classifications during harvesting were less accurate (R2 = 0.73 in the best case) than in the laboratory.

Evaluation of Syngas Storage Under Different Pressures and Temperatures

The objective of this research was to study the syngas storage characteristics in terms of any variation in composition of H2, CO, CH4, CO2, and N2 under two pressures (2758 and 8274 kPa) and three temperatures (-288K, 288K, and 318K). We also evaluated tar, particulate, and moisture content of the stored syngas. Syngas generated from a down-drift gasifier using 95% hardwood chips as the feedstock contained an average of 17.0% H2, 23.9% CO, 1.4% CH4, 11.0% CO2, and 46.7% N2. The compositional elements of the stored syngas under different pressures and temperatures were periodically determined for a three-week period of storage. The statistic model of a single-factor experiment with repeated measures on treatments was used to perform the data analysis with the SAS program. Statistic analysis revealed that the temperature range from -288 to 318K had no effects statistically on the major syngas composition at the tested pressures. Pressures up to 8274 kPa had no effects statistically on the major syngas composition at the tested temperatures. The variations of the syngas components measured were probably due to analysis and instrumental errors. At both pressures, the CO composition had a bigger variation than other components and, as the temperature varied, the CO composition varied more than the other components. Mechanisms of the relatively bigger variation of the CO concentration were not fully understood and may be partially contributed to the pressure and temperature variations. Tars were detected in the storage cylinders after washing with acetone solution, which indicated that the tars were deposited on the inside wall of each storage cylinder. The amount of tars was correlated with the temperature. The low storage temperature precipitated more tars under pressure during storage. Thus this study showed that syngas could be stored with no major adverse affects caused by temperatures of -15°C to 45°C. Also, pressures up to 8274 kPa had no effect on syngas composition at the tested temperatures. Additional studies should be conducted on deposition of tars at low temperatures during storage, condensation of heavy hydrogen carbons, quantification of tar deposited on the storage surface, and deterioration of the storage surface (especially when sulfur compounds exit in syngas).

A Comparison of Regression and Regression-kriging for Soil Characterization Using Remote Sensing Imagery

In precision agriculture regression has been used widely to quantify the relationship between soil attributes and other environmental variables. However, spatial correlation existing in soil samples usually makes the regression model suboptimal. In this study, a regression-kriging method was attempted in relating soil properties to the remote sensing image of a cotton field near Vance, Mississippi. The regression-kriging model was developed and tested by using 273 soil samples collected from the field. The result showed that by properly incorporating the spatial correlation information of regression residuals, the regression-kriging model generally achieved higher prediction accuracy than the stepwise multiple linear regression model. Most strikingly, a 50% increase in prediction accuracy was shown in Na. Potential usages of regression-kriging in future precision agriculture applications include real-time soil sensor development and digital soil mapping.

Experimental Study of a Downdraft Gasifier

In order for biomass gasification to be successfully implemented to provide energy or raw material for the chemical industry, the quality of synthesis gas (syngas) produced is critical. To examine the effects of operational parameters on syngas quality and biomass conversion rate, an experimental study of hardwood chip gasification in a downdraft gasifier system was conducted. This gasifier was run under various conditions to produce syngas, which had an average low heating value of 5.79 ± 0.52 MJ/ Nm3, tar concentration of 14.06 ± 8.54 mg/Nm³, particulate(>0.7im) concentration of 3.05 ± 1.79 mg/Nm³, hardwood chip conversion rate of 2.37±0.24 Nm³/kg, and carbon conversion rate of 98.01 ± 0.53%. This syngas is of acceptable quality to be used as a fuel source for internal combustion engine operations. The gasifier’s grate temperature had no evident effects on syngas quality and conversion rate within a range of 740 to 817 oC. The particulate contents in pre-filtered syngas significantly increased when the gas flow rate changed from 36 to 56 Nm3/h. When the moisture content of hardwood chips increased, tar content of post-filtered syngas significantly increased, and carbon monoxide content significantly decreased.

Remote sensing and weather information in cotton yield prediction

If farmers could predict yield on a spatially variable basis, they could better understand risks and returns in applying costly inputs such as fertilizers, etc. To this end, several remotely sensed images of a cotton field were collected during the 2002 growing season, along with daily high and low temperatures. Image data were converted to normalized-difference vegetation index (NDVI), and temperature data were used to normalize NDVI changes over periods between image collections. Remote-sensing and weather data were overlaid in a geographic information system (GIS) with data from the field: topography, soil texture, and historical cotton yield. All these data were used to develop relationships with yield data collected at the end of the 2002 season. Stepwise regression was conducted at grid-cell sizes from 10 m square (100 m2) to 100 m square (10,000 m2) in 10-m increments. Relationships at each cell size were calculated with data available at the beginning of the season, at the first image date, at the second image date, and so on. Stepwise linear regression was used to select variables at each date that would constitute an appropriate model to predict yield. Results indicated that, at most dates, model accuracy was highest at the 100-m cell size. Remotely sensed data combined with weather data contributed much information to the models, particularly with data collected within 2.5 months of planting. The most appropriate model had an R2 value of 0.63, and its average prediction error was about 0.5 bale/ha (0.2 bale/ac, or roughly 100 lb/ac).

Additives in biomass pellets for improvements in physical properties

Abstract. This study‘s primary objective was to show the impact of different additives on southern yellow pine biomass pellet properties including the energy consumed in production, durability, and BTU content. A pneumatic pelleting device was constructed to allow more precise production of each pellet, while mimicking industry‘s machinery. A specific moisture and temperature was selected to obtain optimum quality before additives were used. Statistical analysis showed that additives had a significant effect on each of the three tested parameters. The energy consumption results showed that corn starch at 4 wt% consumed the least mean amount of energy for production, 3358.67 kJ/kg. Durability results revealed that corn starch at a 4 wt% had the highest mean retained material at 90.527%. BTU content results showed fractionated bio oil at a 4 wt% had the highest mean content of 9182.487 BTU/lb.

Scale-Up of Liquid Hydrocarbon Production using Gasified Biomass

This study showed that liquid hydrocarbons could be successfully created while also effectively controlling temperature using a proportional-integral-derivative (PID) control system in a scaled-up reactor system. A stainless steel tube reactor that measured 2 feet long with a 1.689 inch inside diameter was used to conduct the experiments. Tests were run at a gas hourly space velocity (GHSV) of 500 h-1 (1.4 SLPM) with a catalyst bed volume of 175 mL (93.6g) and a bed height of 4.8 inches. Syngas was subjected to 330o C at 1000 psi, 300o C at 800 psi, 300o C at 600 psi, and 300o C at 500 psi; while the producer gas was tested at 300o C at 1000 psi. An iron-based bi-functional catalyst that converted the syngas to liquid hydrocarbons in one step was used with (Airgas) synthesis gas and producer gas composed of approximately 18% H2, 23% CO, 11% CO2, 2% CH4, and 46% N2. The similar mole percentages from the store bought syngas (Airgas syngas) was used to mimic the producer gas from our particular downdraft gasifier, but the producer gas included 1% O2. Results indicated that the hydrogen conversion ranged from approximately 71% to 85% for all the tests while the conversion of CO ranged from approximately 87% to 96%. The heat generated was able to be properly controlled, and liquid hydrocarbons were successfully created from the producer gas and the store bought syngas.

Liquid Hydrocarbon Production over Mo/HZSM-5 Using Gasified Biomass

Gasified woody biomass (producer gas) has been converted over a Mo/HZSM-5 catalyst to produce gasoline-range hydrocarbons. The effect of contaminants in the producer gas shows that key retardants in the system include ammonia and oxygen. The production of gasoline-range hydrocarbons derived from producer gas has been studied and compared with the gasoline-range hydrocarbon production from two control syngas mixes. Certain mole ratios of syngas mixes were introduced to the system to evaluate whether or not the heat created from the exothermic reaction could be properly controlled. Contaminate-free syngas composed of 40% H2, 20% CO, 12% CO2, 2% CH4, and 26 % N2 was used to determine hydrocarbon production with similar mole values of the producer gas. Contaminate-free syngas composed of 19% H2, 20% CO, 12% CO2, 2% CH4, and 47 % N2 was also used to test an ideal contaminate-free synthesis gas situation to mimic our particular downdraft gasifier. Producer gas composed of 19% H2, 20% CO, 12% CO2, 2% CH4, 46 % N2, and 1% O2 was used in this study to determine the feasibility of using producer gas to create gasoline-range hydrocarbons. It was determined that after removing the ammonia, other contaminants poisoned the catalyst and retarded the hydrocarbon production process as well. This study was used to determine the feasibility of using raw producer gas to create gasoline-range hydrocarbons with a Mo/HZSM-5 catalyst which is active and selective for the direct synthesis of gasoline-range branched and cyclized alkanes as well as aromatic compounds.

Catalytic Conversion of Biomass-derived Syngas to Gasoline Range Hydrocarbons

Catalytic conversion of biomass-derived syngas (bio-syngas) into gasoline range hydrocarbons has been regarded as one of potential routes to utilize biomass. In this route, biomass is firstly converted into bio-syngas through biomass gasification. Then bio-syngas is catalytically converted into transportation fuels or chemicals. In this paper, catalytic synthesis of gasoline range hydrocarbons by using model syngas similar to bio-syngas has been carried out over Mo/HZSM-5 catalysts. Different system temperatures were adopted in the experiments to figure out the effects of reaction parameters. The products were analyzed by GC and GC-MS. The catalysts were characterized by SEM-EDS and TEM. The results showed that Mo/HZSM-5 was active in model bio-syngas.