Browsing by Author "Daily, Jeremy, committee member"

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Open Access
Computer-aided engineering and design of internal combustion engines to support operation on non-traditional fuels
(Colorado State University. Libraries, 2020) Valles Castro, Miguel, author; Windom, Bret C., advisor; Marchese, Anthony J., committee member; Daily, Jeremy, committee member
Traditional fuels like gasoline and diesel make up ~37 % of the US energy production; because of that, they are rapidly depleting their finite resources. These traditional fuels are also primary contributors to greenhouse gases, global warming, and particulate matter, which are bad for the environment and human beings. For that reason, research in non-traditional fuels (e.g., Carbon neutral biofuels, low GHG emitting gaseous fuels including NG and hydrogen) that achieve greater if not similar efficiencies compared to traditional fuels is gaining traction. On top of that, emission requirements are becoming even more strenuous. Engineers must find new ways to investigate non-traditional fuels and their performance in internal combustion engines while permitting the engine-fuel system's low-cost design. This being the case, Computer-Aided Engineering (CAE) tools like Computational Fluid Dynamics (CFD) and chemical kinetics solvers are being taken advantage of to assist in the research of these non-traditional fuel applications. This thesis describes the use of CONVERGE CFD to investigate two different non-traditional fuel applications, namely, the retrofitting of a premixed gasoline two-stroke spark-ignited (SI) engine to function with multiple injections of JP-8 fuel and to retrofit a diesel compression-ignited engine into a premixed anode tail-gas SI engine. The first application described herein uses a solid oxide fuel cell "Anode Tail-gas," which has similar syngas characteristics in a spark-ignited engine. Anode Tail-gas is a byproduct from an underutilized Metal Supported Solid Oxide Fuel Cell (MS-SOFC) used in a high efficiency distributed power (~100 kWe) system. Gas turbines or reciprocating ICEs typically drive distributed power systems of this capacity because they can quickly react to change in demand but traditionally have lower thermal efficiencies than a large-scale Rankine cycle plant. However, with the MS-SOFC, it may be possible to design a 125 kWe system with 70 % efficiency while keeping the system cost-competitive (below $1000/kW). The system requires a ~14 kW engine that can operate at 35 % efficiency with the highly dilute (17.7% H2, 4.90 % CO, 0.40% CH4, 28.3 % CO2, 48.7 % H2O) Anode Tail-gas to meet these lofty targets. CAE approaches were developed and used to identify high-efficiency operation pathways with the highly diluted anode tail-gas fuel. The fuel was first tested and modeled in a Cooperative Fuel Research (CFR) engine to investigate the anode tail gas's combustibility within an IC engine and to provide validation data with highly specified boundary conditions (Compression Ratio (CR), fuel compositions, intake temperature/pressure, and spark timing). A chemical mechanism was selected through CAE tools to represent the highly diluted fuel combustion best based on the CFR data. Five experimental test points were used to validate the CFD model, which all were within a maximum relative error of less than 8 % for IMEP and less than 4 crank angle degrees for CA10 and CA50. The knowledge gained from the CFR engine experiments and associated model validation helped direct the design of a retrofitted Kohler diesel engine to operate as a spark-ignited engine on the anode tail gas fuel. CFD Investigations into spark plug and piston bowl designs were performed to identify combustion chamber design improvements to boost the Kohler engine's efficiency. Studies revealed that piston designs incorporating small clearance heights, large squish areas, and deep bowl depths could enhance efficiency by 5.41 pts with additional efficiency gain possible through piston rotation. The second fuel investigation was a jet propellant fuel called "JP-8," which was deemed non-tradition when used in a two-stroke UAV engine to satisfy the military's single fuel policy requirements. The JP-8 fuel proved challenging in this application due to its significantly lower octane number and volatility than gasoline and experienced knock when used as a homogeneous premixed mixture within the simulated UAV platform. Although with CFD modeling, it was possible to reduce the severity of knock by using eight rapid direct injections of JP-8 at 20 µm diameter droplets. With further investigation, it might be possible to reduce further the severity of knock using CFD through more advanced injection strategies.
Open Access
Evaluating micromobility adoption, perception, and implementation
(Colorado State University. Libraries, 2024) Pourfalatoun, Shiva, author; Gallegos, Erika, advisor; Daily, Jeremy, committee member; Simske, Steve, committee member; Bradley, Thomas, committee member; Jin, Ziyu, committee member
Micromobility, a term that encompasses compact and efficient transportation modes such as bicycles and scooters, has rapidly emerged as an important element of urban mobility. These small, often electrically-powered vehicles offer a versatile solution to urban congestion and provide an eco-friendly alternative to traditional transportation modes. Particularly, shared bicycles and e-scooters have become popular due to their convenience and accessibility, offering significant benefits but also presenting new challenges in urban planning and traffic management. This transition in urban transport paradigms raises several pertinent questions about user behaviors, preferences, and the interplay of various socio-psychological factors. This dissertation aims to explore three key aspects of micromobility. The first research question investigates the differences between shared e-scooter users and non-users, along with the factors influencing their decisions regarding e-scooter usage. The second question examines the shift in micromobility preferences and perceptions before, during, and after the COVID-19 pandemic, focusing on how these changes correlate with different quarantine behaviors. The third and final question delves into the interactions between drivers, bicyclists, and pedestrians, analyzing how drivers' risk-taking propensity and emotional intelligence influence these interactions. Each of these questions is approached through specific methodological frameworks, employing a mix of statistical analyses and behavioral observations to provide insights into the evolving dynamics of urban mobility. The findings from this research provide a systematic approach to integrating micromobility, by understanding at the individual level the factors that effect decision-making on usage, as well as interaction effects with other road users that impact safety.
Open Access
Factors influencing driver response toward an instrument cluster cyberattack: experience, awareness, and training
(Colorado State University. Libraries, 2025) Lanigan, Trevor F., author; Gallegos, Erika, advisor; Daily, Jeremy, committee member; Nelson, Niccole, committee member
Commercial Motor Vehicles (CMVs) and the trucking industry are often referred to as the backbone to the supply chain in the United States. With this has come efforts to modernize heavy vehicles just like their passenger vehicle counterparts in order to improve the safety, performance, and efficiency of the transportation of goods and materials. However, the introduction of advanced cyber-physical systems in heavy vehicles makes available a new vulnerability not previously encountered: cyberattacks. The objective of this thesis is to (1) evaluate drivers' responses to an unexpected cyberattack, (2) evaluate how awareness of the cybersecurity threat on their vehicle influences driver behavior, and (3) evaluate how the provision of a cyberattack response protocol influences driver performance. An on-road driving study with 50 participants was conducted to measure drivers' response to an unexpected cyberattack while operating a medium heavy-duty vehicle (GVWR 26,000lbs; Class 6). Each participant was randomly assigned to one of three experimental groups which received varying levels of information prior to the start of the drive. The Control group received no information regarding a possible cyberattack threat on their vehicle. The Aware group received a warning regarding a possible cyberattack threat on their vehicle. The Aware + Protocol group received the same warning as the Aware group along with a basic cyberattack response protocol. Within each group, six to seven of the participants were professional drivers (e.g., commercial truck driver, firefighter, bus driver), while the remaining 10 to 11 participants in each group were standard licensed drivers. Each of the participants experienced the same driving route and cyberattack scenario with regard to type, location, timing, and execution. Participant driving responses were measured using data collected from the vehicle CAN bus, and Racelogic VBOX3i GNSS and IMU sensors. Participant physiological responses (heart rate and electrodermal activity) were measured using an Empatica E4 wearable. Additionally, participants completed a survey at the end of the experimental session to assess their driving experience, risk taking tendencies, and interpretation of the cyberattack. The findings highlight the essential role of awareness and response protocols in enhancing a driver's response to an unexpected vehicle cyberattack. The Aware + Protocol group achieved a 100\% stop rate among both Standard and Professional drivers, showcasing the transformative impact of awareness and clear response guidelines compared to the Control group stop rate of 9\% for Standard and 83\% for Professional drivers. The Aware + Protocol group also traveled the shortest distance during the cyberattack, with Standard drivers covering 224 meters (0.139 miles) and Professional drivers 254 meters (0.158 miles), compared to the Control group's 828 meters (0.514 miles) for Standard drivers and 520 meters (0.323 miles) for Professional drivers. Furthermore, the Aware + Protocol group demonstrated the shortest reaction times, averaging 7.53 seconds, versus 16.12 seconds in the Aware group and 30.29 seconds in the Control group. These results emphasize that awareness alone is insufficient; explicit instructions significantly enhance drivers' ability to respond promptly and effectively to cybersecurity threats. By informing drivers and providing response protocols, their ability to respond appropriately to cyberattacks can be significantly improved. This information can be applied in several practical ways, such as developing cyberattack response training programs for all drivers, especially those operating heavy vehicles. Additionally, public service announcements and in-vehicle alerts could be effective in increasing awareness of cyberattack vulnerabilities. Public service announcements broadcasted through various media channels can inform a wide audience about the risks of vehicle cyberattacks and inform drivers on how to recognize and respond to such threats. In-vehicle alerts can offer real-time information and instructions, guiding drivers on immediate actions to take when a cybersecurity threat is detected.
Open Access
Navigating the maze: the effectiveness of manufacturer support in applying user-controlled security and privacy features
(Colorado State University. Libraries, 2025) Shorts, Kelvin R., author; Simske, Steve, advisor; Daily, Jeremy, committee member; Vans, Marie, committee member; Reisfeld, Brad, committee member
Internet of Things (IoT) technologies have reshaped the home computer environment by offering extraordinary levels of convenience, automation, and efficiency. With technologies ranging from thermostats that adjust for cost savings to water leak detectors that protect homes from costly water damage, IoT devices in the residential space are here to stay. Collectively, these interconnected devices targeted for the consumer home environment are commonly referred to as a "smart home". Despite the many capabilities that smart home IoT technologies offer, many consumers/end-users are still struggling with effectively securing their internet-connected devices, safeguarding personal data, and ensuring that their smart home network remains secure from potential threats. The responsibility for safeguarding smart home IoT devices is shared by both manufacturers and consumers/end-users; however, the extent to which manufacturers are providing clear, comprehensive, and accessible guidance to assist consumers/end-users with safeguarding IoT devices remains unclear. This research study explores the level of support provided by smart home IoT manufacturers in applying user-controlled security and privacy features. User-controlled security and privacy features are settings within an IoT device that only the end-user can adjust (e.g. passwords, multi-factor authentication, device permissions, data backup, etc.). A systems engineering–focused, mixed-methods approach was adopted to evaluate how effectively smart home IoT manufacturers guide and assist consumers in understanding, implementing, and maintaining user-controlled security and privacy features in their smart home IoT devices and systems. The study unfolds across four systems engineering phases: (1) Requirements Analysis, (2) Usability Testing, (3) Focus Group Technical Deep Dive, and (4) Recommendations and Future Implementations. A review of smart home IoT device manuals, online resources, and other manufacturer-provided materials established a baseline for how well the reference material aligned with cybersecurity industry standards, best practices, and recommendations. Through structured surveys, proficiency tests, and qualitative focus group technical deep dive feedback, the study identified gaps in smart home IoT manufacturers' guidance that compromise users' ability to configure essential security settings. Employing systems engineering principles, this research study underscored the importance of user-centric design and comprehensive security and privacy guidance to help bridge the gap between cybersecurity best practices and a diverse consumer/end- user skill base.
Open Access
Operational conditions for an internal combustion engine in a SOFC-ICE hybrid power generation system
(Colorado State University. Libraries, 2025) Reyes-Flores, Victor A., author; Bandhauer, Todd, advisor; Olsen, Daniel B., committee member; Daily, Jeremy, committee member
Hybrid power generation systems utilizing pressurized solid oxide fuel cells (SOFC) have gained considerable attention recently as an effective solution to the increasing demand for cleaner electricity sources. Among the various hybridization options, gas turbines (GT) and internal combustion engines (ICE) running on off SOFC tail gas have been prominent. Although spark ignition (SI) tail gas engines have received less focus, they show significant potential for stationary power generation, particularly due to their ability to control combustion. This research experimentally characterized an SI engine fueled by simulated SOFC anode gas across a range of variations with fuel cell loads. The study aimed to optimize the engine operating conditions for each fuel blend and establish operational conditions that would sustain maximum performance. The results showed efficiencies as high as 31.4% at 1600 rpm, with a 17:1 compression ratio, equivalence ratio (φ) = 0.75, and a boost pressure of 165 kPa with low NOx emissions. The study also emphasizes the benefits of optimizing boost supply to minimize parasitic loads and improve brake thermal efficiency (BTE). Additionally, installing a catalytic oxidizer would enable the system to comply with new engine emission regulations. A proposed control scheme for automation includes regulating engine power by controlling the boost of the supercharger at a fixed throttle position.
Open Access
Physical validation of predictive acceleration control on a parallel hybrid electric vehicle
(Colorado State University. Libraries, 2022) White, Samantha M., author; Bradley, Thomas, advisor; Quinn, Jason, committee member; Daily, Jeremy, committee member; Windom, Bret, committee member
Previous research has been conducted towards the development of predictive control strategies for Hybrid Electric Vehicles (HEVs). These methods have been shown to be effective in reducing fuel consumption in simulation, but no physical validation has been conducted. This is likely due to the fundamental "curses" of dynamic programming mostly the "curse of dimensionality" wherein the run-time needed to generate the optimal solution renders the method unfit as a real-time control. Predictive Acceleration Event (PAE) control combats the run-time issues associated with dynamic programming based control methods by pre-computing the optimal solutions for common Acceleration Events (AEs). This method was physically implemented on a 2019 Toyota Tacoma that was converted into a Parallel-3 (P3) HEV with limited information on the vehicle, including a reduced access to the vehicle's Controller Area Network (CAN) bus. Results from on-track testing indicate a Fuel Economy (FE) improvement in the range of 7% is possible to achieve using PAE control in the real world. To the author's knowledge this is the first time that this type of testing has ever been implemented on a vehicle in the real world.
Open Access
Resiliency analysis of mission-critical systems using formal methods
(Colorado State University. Libraries, 2025) Abdelgawad, Mahmoud A., author; Ray, Indrakshi, advisor; Malaiya, Yashwant, committee member; Sreedharan, Sarath, committee member; Daily, Jeremy, committee member
Mission-critical systems, such as navigational spacecraft and drone surveillance systems, play a crucial role in a nation's safety and security. These systems consist of heterogeneous systems that work together to accomplish critical missions. However, they are susceptible to cyberattacks and physical incidents that can have devastating consequences. Thus, missions must be designed so that mission-critical systems can withstand adverse events and continue to operate effectively, even with the occurrence of adverse events. In other words, critical mission engineers must specify, analyze, and anticipate potential threats, identify where adverse events may occur, and develop mitigation strategies before deploying a mission-critical system. This work presents an end-to-end methodology for analyzing the resiliency of critical missions. The methodology first specifies a mission in the form of a workflow. The mission workflow is then converted into a formal representation using Colored Petri Nets (CPN). Threat models are also extracted from the mission specification to tackle the CPN mission with various attack scenarios. These threat models are represented as CPN attacks. The methodology exploits the state transitions of the CPN mission attached to CPN attacks to analyze the resiliency of the mission. The analysis identifies which states the mission succeeds, fails, and is incomplete. We established a mission for a mission-critical formation consisting of a military vehicle and two route reconnaissance drones that collaborate to monitor a national border and respond promptly to physical threats. The effectiveness of the methodology is demonstrated in identifying vulnerabilities, modeling adversarial conditions, and evaluating mission continuity under disruptions. The result shows how to refine the mission to enhance the resilience of such formations. The findings contribute to the early-stage resilience analysis framework and help address the limitations associated with manual verification of mission-critical systems.
Open Access
Secure remote sensor simulator for heavy vehicle electronic control units
(Colorado State University. Libraries, 2022) Gannavarapu, Ram Rohit, author; Chong, Edwin, advisor; Pasricha, Sudeep, committee member; Daily, Jeremy, committee member
Heavy Vehicle Event Data Recorders (HVEDRs) have the capability to record crash-related data and are valuable tools for traffic crash investigators. The data extracted from HVEDRs contain information to help reconstruct the driver's behaviors and determine the events leading to a crash. Data extraction is commonly performed using diagnostic tools when the electronic control unit (ECU) with the HVEDR is available on the vehicle's network. In the cases where the electrical system of the vehicle is compromised, the ECU is often removed and connected to a harness for power and communications. These harnesses are not designed to preserve fault codes or diagnostic trouble codes which can result in overwriting data related to a particular crash event. This thesis describes the open-source hardware and software design of a remotely accessible sensor simulator used to create a fault-free environment for a bench download of an HVEDR. The sensor simulator device reduces the chance of any alteration of the original fault code data inside the HVEDRs by emulating the presence of actuators and sensors to the ECU. It does this using analog voltage outputs, pulse-width modulated signals, digital potentiometers, and CAN messages. The settings for these are adjustable remotely through a web-based interface. A contribution of the thesis focuses on a process to increase the security posture of the embedded IoT devices wherein it utilizes a hardware security module to offload cryptography operations. The hardware security module was also used for secure key storage and implement Elliptic Curve Digital Signature Algorithm (ECDSA) to sign and verify messages for integrity, which is a key process in Transport layer security (TLS). The device also securely connects to a cloud infrastructure using TLS, enabling investigators to operate these devices remotely using a web-based graphical user interface. Secure remote access enables further research and investigation of heavy vehicle electronic systems.
Open Access
Systems and operational modeling and simulation to address research gaps in transportation electrification
(Colorado State University. Libraries, 2023) Rabinowitz, Aaron I., author; Bradley, Thomas, advisor; Daily, Jeremy, committee member; Pasricha, Sudeep, committee member; Weinberger, Chris, committee member
Transportation electrification is increasingly thought of as a necessity in order to mitigate the negative effects of climate change and this has recently resulted in large investments, within the US and globally, into green transportation technology. In order to ensure that the electrification transition of the transportation sector is carried out in an efficient and effective manner, it is important to address key research gaps. The proposed research involves addressing 4 important research gaps related to electrification in the transportation sector. The four research gaps addressed are quantifying the energetic benefits which may be achieved via the use of Connected Autonomous Vehicle (CAV) technology to enable optimal operational and dynamic control in Electric Vehicles (EVs), the quantification of the operational inconvenience experienced by Battery Electric Vehicle (BEV) users compared to Internal Combustion Vehicle (ICV) users for given infrastructural parameters, and quantification of the potential economic competitiveness of BEVs for Heavy Duty (HD) Less Than Truckload (LTL) fleets. The identified research gaps are addressed via quantitative, data-based, and transparent modeling and simulation. In the first two cases, comprehensive simulation experiments are conducted which show both the potential energetic improvements available as well as the best methods to achieve these improvements. In the second case, a novel method is developed for the quantification of operational inconvenience due to energizing a vehicle and an empirical equation is derived for estimating said inconvenience based on vehicular and infrastructural parameters. The empirical equation can be deployed on a geo- spatial basis in order to provide quantitative measures of BEV inequity of experience. In the last case a novel, data-driven simulation based Total Cost of Ownership (TCO) model for class 8 BEV tractors is developed and used to project economic competitiveness in the near and medium term future. Findings from the proposed research will provide critical information for industry and policy-makers in their mission to enable an efficient and equitable transportation future.
Open Access
Techniques in reactive to proactive obsolescence management for C5ISR systems
(Colorado State University. Libraries, 2023) Chellin, Matthew D., author; Miller, Erika, advisor; Daily, Jeremy, committee member; Herber, Daniel, committee member; Simske, Steven, committee member; Prawel, David, committee member
Obsolescence is a significant challenge for the Command, Control, Communications, Computers, Cyber, Intelligence, Surveillance and Reconnaissance (C5ISR) community. Obsolescence can negatively affect a C5ISR system's cost, schedule, performance, and readiness. This research examines the challenge of obsolescence for C5ISR systems by focusing on the U.S. Army at Aberdeen Proving Ground, Maryland and their industry partners. The objective of this research is to synthesize insights from the experiences of government and industry practitioners that mitigate diminishing manufacturing sources and material shortages (DMSMS) challenges into mitigation techniques. The obsolescence mitigation areas described in this research include proactive and reactive obsolescence mitigation, obsolescence mitigation methods, and the importance of DMSMS contracting language. This research also offers approaches grounded in practitioner experiences to mitigate obsolescence through a proactive obsolescence management model, risk mitigation framework, metrics, modeling & simulation, and systems thinking methods. The combination of the models, methods, and approaches discussed from this research have the potential to achieve greater system readiness, more availability, better maintainability, and lower costs for C5ISR systems.