Browsing by Author "Baker, Daniel, committee member"

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Open Access
Analysis of simulated dilute anode tail-gas combustion characteristics on a CFR engine
(Colorado State University. Libraries, 2020) Balu, Alexander, author; Olsen, Daniel, advisor; Windom, Bret, committee member; Baker, Daniel, committee member
Recent innovations in metal-supported solid oxide fuel cells (MS-SOFC) have increased the longevity and reliability of fuel cells. These innovations drive the desire to create power generating systems that combine different ways of extracting power from a fuel to increase overall fuel conversion efficiency. This investigation assesses the feasibility of operating an internal combustion engine (ICE) with the anode tail-gas, which is a blend of H2, CO, CO2, H2O, and CH4, exhausted by a metal-supported solid oxide fuel cell (MS-SOFC). This engine would be used to support the fuel cell balance of plant equipment, including a compressor and expander, and produce excess electrical power. Seven variations of the expected anode tail-gas blends were determined by varying the dewpoint temperature of the fuel. In three of the test blends, CO2 replaced the water content of the fuel to allow for initial feasibility testing without the capital investment required to simulate the tail-gas with steam injection. Gas blends are tested by combining separate flows of each constituent, and combustion is tested using a Cooperative Fuel Research (CFR) engine. Compression ratio (CR), spark timing, intake manifold temperature (IMT), and boost pressure were manipulated to obtain optimal operating conditions. All test blends produced power and reached stable engine operation. Response surface method (RSM) optimization was used to experimentally optimize operating parameters and determine the maximum achievable efficiency utilizing the CFR engine. Initial feasibility testing performed on test blends with CO2 in place of water showed that all combinations successfully produced power in the engine. The mixture with the highest levels of CO2 was problematic and required an increased CR of 14.4:1, advanced timing of 40° before top dead center (BTDC), and an increased IMT of 70℃. All CO2 test blends operated at brake efficiencies ranging from 12-17% during initial testing. After the feasibility of this project was determined, a steam generator and steam flow meter were installed and used to fully simulate the anode tail-gas blends with steam injection. All fully simulated anode tail-gas blends produced power in the engine, although the blend with the most water content caused operational problems with the CFR engine test stand. These problems were caused by large amounts of water entering the engine lube oil system. RSM optimization was performed on the most viable test blends which had steam injection to 40℃ and 90℃ fuel dewpoint temperatures. During optimization, the 40℃ and 90℃ dewpoint temperature blend brake efficiency increased from 20% to 22.2%, and 17% to 22.3%, respectively. This study determined that ICE operation on dilute anode tail-gas is possible. Anode tail-gas combustion data was collected and used to inform engine and combustion models to facilitate prototype engine development for further testing.
Open Access
Controls on and trends in sediment and particulate organic matter storage by instream wood in north Saint Vrain Creek, Colorado
(Colorado State University. Libraries, 2017) Pfeiffer, Andrew, author; Wohl, Ellen, advisor; Rathburn, Sara, committee member; Baker, Daniel, committee member
Sediment and particulate organic matter (POM) retained by wood within the bankfull channel were evaluated for 58 stream reaches at the headwaters of North Saint Vrain Creek, Colorado. Wood-induced storage in headwater regions is hypothesized to be important in buffering downstream transport of material. However, the magnitude of storage has not been thoroughly investigated in relation to different potential control variables (e.g., wood volume, channel gradient, channel confinement, and riparian basal area) and spatial scales (jam, reach, and drainage basin) of control. Multiple and single variable linear regressions informed results. On the jam scale, no relationship was observed between storage and visually estimated jam porosity and permeability. In contrast, the reach-scale volume of stored coarse sediment (gravel, cobble) responds strongly to reach-scale wood volume. Reach-scale fine sediment (sand and finer) volume responds most strongly to wood piece characteristics (average piece length/average channel width and longitudinal spacing) and reach-scale coarse sediment storage. POM storage was most strongly related to riparian controls (channel confinement and riparian forest basal area). These results were translated into a drainage basin-scale analysis in ArcGIS. Despite comprising 14% of the stream network, third-order reaches were found to store 41% of total estimated coarse sediment, 34% of total wood, and 23% of total fine sediment. Large logjams likely exert a high cumulative storage effect in a relatively small portion of the watershed. In contrast, 60% of estimated total POM storage occurs in first-order streams (47% of network stream length). Low transport capacity in these small streams retains highly mobile POM and lateral roots from the nearby riparian forest may serve as retention structures. These results indicate that wood exerts different geomorphic effects depending on its location within the stream network. From a management perspective, road building and campsite development should avoid impacts to first-order streams, as they are important to overall drainage basin POM retention. Third-order streams are hotspots of wood, coarse sediment, and fine sediment; promoting or allowing wood recruitment processes in these areas can facilitate high sediment retention and buffering of downstream transport.
Open Access
Evaluation of controlled end gas auto ignition with exhaust gas recirculation in a stoichiometric, spark ignited, natural gas engine
(Colorado State University. Libraries, 2020) Bayliff, Scott Michael, author; Olsen, Daniel B., advisor; Windom, Bret, committee member; Baker, Daniel, committee member
Many stationary and heavy-duty on-road natural gas fueled engines today operate under stoichiometric conditions with a three-way catalyst. The disadvantage of stoichiometric natural gas engines compared to lean-burn natural gas and diesel engines is lower efficiency, resulting primarily from lower power density and compression ratio. Exhaust gas recirculation (EGR) coupled with advanced combustion controls can enable operation with higher compression ratio and power density, which yields higher efficiency. This also results in engine operation between the limits of knock and misfire. Operation between these limits has been named controlled end gas auto-ignition (C-EGAI) and can be used to improve the brake efficiency of the engine. Various methods of cylinder pressure-based knock quantification were explored to implement C-EGAI. The indicated quantification methods are used for the implementation of a control scheme for C-EGAI with a relation to the fractional heat release due to auto-ignition. A custom EGR system was built and the effect of EGR on the performance of a stoichiometric, spark ignited, natural gas engine is evaluated. C-EGAI is implemented and the optimal parameters are determined for peak performance under EGR and C-EGAI conditions. In this study, knock detection is used for the recognition, magnitude, and location of the auto-ignition events. Cylinder pressure-based knock detection was the primary method for determining the occurrence and location of knock but was also used for implementing the ignition control scheme for controlled end gas auto-ignition. The combustion intensity metric (CIM) enabled parametric ignition timing control which allowed for the creation of a relationship between fractional heat release due to auto-ignition and CIM. Both exhaust gas recirculation and controlled end gas auto-ignition were analyzed with a cooperative fuel research (CFR) engine modified for boosted fuel/air intake. The data was interpreted to provide a proper evaluation of unique analytical methods to quantify the results of C_EGAI and characterize the live auto-ignition events. The control variables for this method of C-EGAI were optimized with EGR conditions to generate the point of peak performance on the CFR engine under stoichiometric, spark ignited, natural gas conditions.
Open Access
Expanding the knock/emissions limits for the realization of ultra-low emissions, high-efficiency heavy-duty natural gas engines
(Colorado State University. Libraries, 2023) Rodriguez Rueda, Juan Felipe, author; Olsen, Daniel B., advisor; Windom, Bret, committee member; Baker, Daniel, committee member; Quinn, Jason, committee member
Heavy-duty on-highway natural gas (NG) engines are a promising alternative to diesel engines to reduce greenhouse gas and harmful pollutant emissions if the limitations (knock and misfire) for achieving diesel-like efficiencies are addressed. This study shows innovative technologies for developing high-efficiency stoichiometric, spark-ignited (SI) natural gas engines. To develop the base knowledge required to reach the desired efficiency, a Single Cylinder Engine (SCE) is the most effective platform for acquiring reliable and repeatable data. An SCE test cell was developed using a Cummins 15-liter six-cylinder heavy-duty engine block modified to fire one cylinder (2.5-liter displacement). A Woodward Large Engine Control Module (LECM) is integrated to permit real-time advanced combustion control implementation. Fixed location of 50% burn and Controlled End Gas Auto-Ignition (C-EGAI) were used to define the ignition timing. C-EGAI allows operation with an optimized fraction of end gas auto-ignition combustion. Intake and exhaust characteristics, fuel composition, and exhaust gas recirculated substitution rate (EGR) are fully adjustable. A high-speed data acquisition system acquires in-cylinder, intake, and exhaust pressure for combustion analysis. Further development includes advanced control methodologies to maintain stable operation and higher dilution tolerance. Controlled end-gas autoignition (C-EGAI) is used as a combustion control strategy to improve efficiency. A Combustion Intensity Metric (CIM) is used for ignition control while operating the engine under C-EGAI. During the baseline testing of the developed SCE test cell, effective control of intake manifold pressure, exhaust manifold pressure, engine equivalence ratio, speed, torque, jacket water temperature, and oil temperature was demonstrated. The baseline testing shows reliable and consistent results for engine thermal efficiency, indicated mean effective pressure (IMEP), and coefficient of variance of the IMEP over a wide range of operating conditions. High Brake Thermal Efficiency (BTE) was achieved using improved hardware and a high EGR rate. Due to the correlation of CIM to the fraction of EGAI (f-EGAI), CIM was used as the reference variable to implement C-EGAI. Achieving conditions of C-EGAI allowed for the utilization of high EGR at high IMEP without inducing knock. The operation of the engine under these conditions showed peak brake thermal efficiency above 46% using an EGR ratio of 30% The work described proves the concept of using new and innovative control algorithms and CFD-optimized combustion chamber designs, allowing ultra-high efficiency and low emissions for NG ICE's heavy-duty on-road applications.
Open Access
Geographically-resolved life cycle assessment and techno-economic analysis of engineered climate solutions with an innovative framework for decision support
(Colorado State University. Libraries, 2024) Greene, Jonah Michael, author; Quinn, Jason C., advisor; Reardon, Kenneth, committee member; Coburn, Tim, committee member; Baker, Daniel, committee member
The urgent challenge of addressing climate change requires a thorough evaluation of engineered solutions to ensure they are both economically viable and environmentally sustainable. This dissertation performs a comprehensive assessment of two key climate technologies: microalgae biorefineries for biofuel production and anaerobic digestion (AD) systems for reducing greenhouse gas (GHG) emissions on dairy farms. Using high-resolution life cycle assessment (LCA) and techno-economic analysis (TEA), it provides detailed insights into the sustainability performance of these technologies. In addition, this work goes further by introducing a decision-support framework that improves the interpretation of LCA and TEA results, enhancing decision-makers' ability to form sustainable policies and implement actionable outcomes that drive the transition to green energy solutions. The first segment of this dissertation integrates high-resolution thermal and biological modeling with LCA and TEA to evaluate and compare two different microalgae biorefinery configurations targeting renewable diesel (RD) and sustainable aviation fuel (SAF) production in the United States. A dynamic engineering process model captures mass and energy balances for biomass growth, storage, dewatering, and conversion with hourly resolution. These configurations support facilities in remote areas and cultivation on marginal lands, enabling large-scale biofuel production. The two pathways under examination share identical biomass production and harvesting assumptions but differ in their conversion processes. The first pathway evaluates hydrothermal liquefaction (HTL) to produce RD, while the second explores the Hydroprocessed Esters and Fatty Acids (HEFA) process to produce SAF. Results indicate that the Minimum Fuel Selling Price (MFSP) for RD could decrease from $3.70-$7.30 to $1.50-$4.10 per liter of gasoline equivalent, and for SAF from $9.90-$19.60 to $2.20-$7.30 per liter under future scenarios with increased lipid content and reduced CO2 delivery costs. Optimization analyses reveal pathways to achieve an MFSP of $0.75 per liter and 70% GHG emissions reductions compared to petroleum fuels for both pathways. Additional analysis covers the water footprint, land-use change emissions, and other environmental impacts, with a focus on strategic research and development investments to reduce production costs and environmental burdens from microalgae biofuels. Beyond renewable transportation fuels, achieving a sustainable energy future will require innovations in the circular economy, such as waste-to-energy systems that reduce GHG emissions while simultaneously producing renewable energy. Accordingly, the second segment of this dissertation examines the GHG reduction potential of adopting AD technology on large-scale dairy farms across the contiguous United States. Regional and national GHG reduction estimates were developed through a robust life cycle modeling framework paired with sensitivity and uncertainty analyses. Twenty dairy configurations were modeled to capture key differences in housing and manure management practices, applicable AD technologies, regional climates, storage cleanout schedules, and land application methods. Monte Carlo uncertainty bounds suggest that AD adoption could reduce GHG emissions from the large-scale dairy industry by 2.45-3.52 million metric tons (MMT) of CO2-equivalent (CO2-eq) per year when biogas is used solely in renewable natural gas programs, and as much as 4.53-6.46 MMT of CO2-eq per year when combined heat and power is implemented as an additional biogas use case. At the farm level, AD technology may reduce GHG emissions from manure management systems by 58.1-79.8%, depending on the region. The study highlights the regional variations in GHG emissions from manure management strategies, alongside the challenges and opportunities surrounding broader AD adoption. It is vital to confirm that engineered climate solutions offer real improvements and to identify key enhancements needed to replace existing technologies. This process hinges on effective policy and decision-making. To address these challenges, the final segment of this dissertation introduces the Environmental Comparison and Optimization Stakeholder Tool for Evaluating and Prioritizing Solutions (ECO-STEPS). ECO-STEPS offers a decision-support framework that utilizes outputs from LCA and TEA to help decision-makers evaluate and prioritize engineered climate solutions based on economic viability, environmental impacts, and resource use. The tool's framework combines stakeholder rankings for key sustainability criteria with diverse statistical weighting methods, offering decision support aligned with long-term sustainability goals across various technology sectors. Applied to a biofuels case study, ECO-STEPS compares algae-based RD, soybean biodiesel (BD), corn ethanol, and petroleum diesel, using an expert survey to determine criteria rankings. Results indicate that soybean BD is a strong near-term solution for the biofuels sector, given its economic viability and relatively low environmental impacts. In contrast, corn ethanol, while economically competitive, demonstrates poor environmental performance across multiple sustainability themes. Algae-based RD emerges as a promising long-term option as ongoing research and development reduce costs. The results of this case study illustrate that ECO-STEPS provides a flexible and comprehensive framework for stakeholders to navigate complex decision-making processes in the pursuit of sustainable climate solutions. In conclusion, the integration of high-resolution LCA, TEA, and a stakeholder-driven decision-support framework in this dissertation presents a comprehensive approach to evaluating engineered climate solutions. The results from these studies provide geographically resolved insights into the sustainability performance of key climate technologies, offering actionable pathways for optimizing biofuel production, reducing GHG emissions, and supporting sustainable decision-making to advance the transition to a green economy.
Open Access
Hydrologic and hydraulic response to wildfires in the upper Cache la Poudre watershed using a SWAT and HEC-RAS model cascade
(Colorado State University. Libraries, 2015) Havel, Aaron, author; Arabi, Mazdak, advisor; Baker, Daniel, committee member; Wohl, Ellen, committee member
The enhanced possibility of catastrophic wildfires in the western USA and other regions around the world has increased the need to evaluate the effects of wildfire on the hydrology of watersheds and the hydraulic behavior of rivers. Understanding the effects of wildfires is vital in water-resources management and for public safety especially in regions where communities depend on surface water supply. Similarly, areas adjacent to river systems may be at risk of increased flooding due to wildfires in their upstream watersheds. Effects of wildfires on hydrologic fluxes in watersheds and rivers have been extensively studied; but, characterization of responses to wildfires is difficult due to the spatial variability of post-wildfire conditions. At the watershed scale, hydrologic responses comprise a network of complex nonlinear interactions. Hence, comprehensive watershed models serve as a useful tool to understand these relationships. Watershed models commonly lack the ability to represent channel geometry and channel process with sufficient spatial frequency. Thus, a hydrologic and hydraulic model cascade provides a bridge between the nonlinear interactions of the uplands and the river responses at the channel scale. The overall goal of this study is to examine the spatial variability of the effects of the 2012 High Park and Hewlett wildfires that occurred within the headwaters of the Cache la Poudre River located in northern Colorado, USA. Two commonly used models were calibrated and used in combination. First, the Soil and Water Assessment Tool (SWAT) was used to evaluate the hydrologic responses of the upper Cache la Poudre watershed to the wildfire events. Subsequently, the results from the SWAT model were used as inputs for the hydraulic model Hydrologic Engineering Center River Analysis System (HEC-RAS) to simulate channel hydraulics along 42.5 km of the upper Cache la Poudre River. The baseline SWAT model was established to simulate the hydrology of the study area between the years 2000 and 2014. This model accounts for wildfires by modifying land use/land cover inputs and corresponding parameters during simulations. Daily streamflow data were used for model calibration and testing. Using the calibrated baseline model, no-wildfire and wildfire scenarios were created. The two scenarios were then compared for changes in average annual total runoff volume, water budgets, and full streamflow statistics at the watershed and sub-basin scales. Then a HEC-RAS model was developed to simulate the hydraulic responses of the stream network using streamflows for various floods extracted from the two SWAT scenarios. High resolution DEM data and surveyed water surface elevations are used for model calibration and testing, respectively. Channel hydraulic behavior including flood inundation area, streamflow velocities, and channel shear stress were compared for the two scenarios at the channel scale. At the watershed scale, wildfire conditions have little effect on the hydrologic responses, but at the sub-basin scale a total runoff increase up to 75 percent between scenarios was found. Generally, wildfire affected water budgets showed more surface runoff versus subsurface runoff, suggesting a decrease in infiltration rates under post-wildfire conditions. Flow-duration curves developed using full streamflow statistics for burned sub-basins show that less frequent streamflows become greater in magnitude leading to ecosurplus values up to 0.279. Also, simulations revealed that there is a strong and significant (R2 > 0.8 and p < 0.001) positive correlation between runoff increase and percentage of burned area upstream. Streamflow increases were between 2 and 14 percent depending on the reach’s proximity to the wildfire and the flood. Lastly, along the main stem only slight increases in flood area, average cross section velocity, and shear stress as a result of wildfire were observed in the simulations. The results have important implications on improving post-wildfire water resources management.
Open Access
Predictive modeling and testing of a diesel derived solid oxide fuel cell tail gas spark-ignition engine
(Colorado State University. Libraries, 2020) Countie, Matthew, author; Olsen, Daniel, advisor; Windom, Brett, committee member; Baker, Daniel, committee member
Solid oxide fuel cell systems are being developed with total system efficiency targets over 70%. One approach is to provide excess fuel to the solid oxide fuel cell and develop an engine to provide power for mechanical and electrical equipment using exhaust gas from the fuel cell anode (tailgas). This tailgas contains hydrogen, carbon monoxide, methane, water, and carbon dioxide. Compared to natural gas the tailgas fuel has suppressed flame speeds, an extremely small lower heating value, and a low air-fuel ratio due to the presence of large amounts of oxidation products. A predictive model created in GT-Power was used to design an engine that can produce 14kW on tailgas fuel with a brake efficiency η>30%. The model base is an existing Kohler diesel engine. The diesel engine was modeled in GT-Power and validated to within 1% at the anticipated operating point. Using custom combustion models developed from testing several different tailgas blends in a CFR engine, several different engine conversions were modeled to explore different pathways to 30% brake efficiency. Design variations include Miller cycles, turbocharging, compression ratio, and fuel pre-treatment to increase reactivity. Once design parameters were established, an operation envelope was created to identify knock limits and maximum brake efficiency timing. These models helped guide the development of a physical prototype engine that was built and installed at the CSU Powerhouse Energy Campus. The prototype engine ran with simulated anode tailgas up to a maximum power level of 7.42 kW and a maximum brake efficiency of 27.34%, achieving 53% of the load target, and 91% of the efficiency target. The timings identified by GT-Power to be the point of maximum brake efficiency and knock initiation were tested at four different speeds on the prototype engine. After data collection, using the experimental power, engine speed, and ignition timing as initial conditions, the model is rerun. The accuracy of the models' prediction capability is tested by using these initial conditions to generate additional model output to compare with measured data. At low speeds and advanced ignition timings, the model matched well, within 10% on almost all metrics, but at retarded timings and high engine speeds, the model began to deviate in most parameters, especially overpredicting exhaust temperature and pressure. The discrepancies between model results and experimental data are discussed in detail. Model and experimental data matched well at advanced timings and low speeds, but deviated significantly at retarded timings and high speeds.
Open Access
Techno-economic and life cycle assessment of a novel offshore macroalgae biorefinery
(Colorado State University. Libraries, 2019) Greene, Jonah M., author; Quinn, Jason C., advisor; Baker, Daniel, committee member; Petro, John, committee member
Innovative and effective solutions to providing renewable fuels represent a critical need. The cultivation and conversion of salt water macroalgae into liquid transportation fuels may offer a viable alternative to petroleum-based diesel, but the potential of this technology in terms of economic feasibility and environmental impact has not been thoroughly investigated. This work evaluates the sustainability of a free-floating macroalgae cultivation to fuel concept. While free-floating biomass cultivation structures may offer solutions for reducing infrastructure requirements and expenses, extreme ocean conditions pose great risks and unknowns. This study focuses on emerging technologies for large scale cultivation and harvesting of macroalgae biomass including drone assisted seeding and harvesting operations, recycled carbon fiber long-lines with sensor equipped buoys, and adhesive spore seeding methods. The harvested biomass is then converted to fuels through hydrothermal liquefaction. Three different system pathways have been explored to determine the impacts of the various emerging technologies on the sustainability of the system and provide direction for future research and development. Results from the techno-economic analysis show a baseline minimum fuel selling price of $6.38 per Gallon of Gasoline Equivalent (GGE) with a range from $5.10 GGE-1 to $11.00 GGE-1 based on optimistic and conservative assumptions regarding biomass yield, length of the growing season, and technology readiness level. The 90% confidence interval from the Monte Carlo Analysis performed by varying the top 10 high-impact parameters, suggests a range of $6.02 GGE-1 to $11.17 GGE-1 for the baseline pathway. The well-to-wheel life cycle assessment (LCA) shows net greenhouse gas emissions of 22 gCO2-eq MJ-1 for the baseline pathway and a range of 18 to 32 gCO2-eq MJ-1 for the optimistic and conservative pathways, respectively. The Monte Carlo LCA results show a range of 19 to 27 g CO2-eq MJ-1 based on the 90% confidence interval. Discussion focuses on the feasibility of the various technologies and utilizes results from the analysis to weigh the risks and rewards associated with the proposed concept, in an effort to guide research and development for macroalgal cultivation and conversion systems.
Open Access
Uncertainty and sensitivity in a bank stability model: implications for estimating phosphorus loading
(Colorado State University. Libraries, 2015) Lammers, Roderick William, author; Bledsoe, Brian P., advisor; Baker, Daniel, committee member; Wohl, Ellen, committee member
Eutrophication of aquatic ecosystems is one of the most pressing water quality concerns in the U.S. and around the world. Bank erosion has been largely overlooked as a source of nutrient loading, despite field studies demonstrating that this source can account for the majority of the total phosphorus budget of a watershed. Substantial effort has been made to develop mechanistic models to predict bank erosion and instability in stream systems; however, these models do not account for inherent natural variability in input values. Providing only single output values with no quantification of associated uncertainty can complicate management decisions focused on reducing bank erosion and nutrient loading to streams. To address this issue, uncertainty and sensitivity analyses were performed on the Bank Stability and Toe Erosion Model (BSTEM), a mechanistic model developed by the USDA-ARS that simulates both mass wasting (stability) and fluvial erosion of streambanks. Sensitivity analysis results indicate that variable influence on model output can vary depending on assumed input distributions. Generally, bank height, soil cohesion, and plant species were found to be most influential in determining stability of clay (cohesive) banks. In addition to these three inputs, groundwater elevation, stream stage, and bank angle were also identified as important in sand (non-cohesive) banks. Slope and bank height are the dominant variables in fluvial erosion modeling, while erodibility and critical shear stress are relatively unimportant. However, the threshold effect of critical shear stress (determining whether erosion occurs) was not explicitly accounted for, possibly explaining the relatively low sensitivity indices for this variable. Model output distributions of sediment and phosphorus loading rates corresponded well to ranges published in the literature, helping validate both model performance and selected ranges of input values. In addition, a probabilistic modeling approach was applied to data from a watershed-scale sediment and phosphorus loading study on the Missisquoi River, Vermont to quantify uncertainty associated with these published results. While our estimates indicated that bank erosion was likely a significant source of sediment and phosphorus to the watershed in question, the uncertainty associated with these predictions indicates that they should probably be considered order of magnitude estimates only.