Theses and Dissertations

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Open Access
Development and quasi-experimental study of the Scrum model-based system architecture process (sMBSAP) for agile model-based software engineering
(Colorado State University. Libraries, 2023) Huss, Moe, author; Herber, Daniel R., advisor; Borky, John M., advisor; Miller, Erika, committee member; Mallette, Paul, committee member
Model-Based Systems Engineering (MBSE) is an architecture-based software development approach. Agile, on the other hand, is a light system development approach that originated in software development. To bring together the benefits of both approaches, this research is divided into two stages. The first stage proposes an integrated Agile MBSE approach that adopts a specific instance of the Agile approach (i.e., Scrum) in combination with a specific instance of an MBSE approach (i.e., Model-Based System Architecture Process — "MBSAP") to create an Agile MBSE approach called the integrated Scrum Model Based System Architecture Process (sMBSAP). The proposed approach was validated through an experimental study that developed a health technology system over one year, successfully producing the desired software product. This work focuses on determining whether the proposed sMBSAP approach can deliver the desired Product Increments with the support of an MBSE process. The interaction of the Product Development Team with the MBSE tool, the generation of the system model, and the delivery of the Product Increments were observed. The results showed that the proposed approach contributed to achieving the desired system development outcomes and, at the same time, generated complete system architecture artifacts that would not have been developed if Agile had been used alone. Therefore, the first contribution of this stage lies in introducing a practical and operational method for merging Agile and MBSE. In parallel, the results suggest that sMBSAP is a middle ground that is more aligned with federal and state regulations, as it addresses the technical debt concerns. The second stage of this research compares Reliability of Estimation, Productivity, and Defect Rate metrics for sprints driven by Scrum versus sMBSAP through the experimental study in stage 1. The quasi-experimental study conducted ten sprints using each approach. The approaches were then evaluated based on their effectiveness in helping the Product Development Team estimate the backlog items they can build during a time-boxed sprint and deliver more Product Backlog Items (PBI) with fewer defects. The Commitment Reliability (CR) was calculated to compare the Reliability of Estimation with a measured average Scrum-driven value of 0.81 versus a statistically different average sMBSAP-driven value of 0.94. Similarly, the average Sprint Velocity (SV ) for the Scrum-driven sprints was 26.8 versus 31.8 for the MBSAP-driven sprints. The average Defect Density (DD) for Scrum-driven sprints was 0.91, while that of sMBSAP-driven sprints was 0.63. The average Defect Leakage (DL) for Scrum-driven sprints was 0.20, while that of sMBSAP-driven sprints was 0.15. The t-test analysis concluded that the sMBSAP-driven sprints were associated with a statistically significant larger mean CR, SV , DD, and DL than that of the Scrum-driven sprints. The overall results demonstrate formal quantitative benefits of an Agile MBSE approach compared to Agile alone, strengthening the case for considering Agile MBSE methods within the software development community. Future work might include comparing Agile and Agile MBSE methods using alternative research designs and further software development objectives, techniques, and metrics. Future investigations may also test sMBSAP with non-software systems to validate the methodology across other disciplines.
Open Access
Optimizing designer cognition relative to generative design methods
(Colorado State University. Libraries, 2023) Botyarov, Michael, author; Miller, Erika, advisor; Bradley, Thomas, committee member; Forrest, Jeffrey, committee member; Moraes, Marcia, committee member; Simske, Steve, committee member; Radford, Donald, committee member
Generative design is a powerful tool for design creation, particularly for complex engineering problems where a plethora potential design solutions exist. Generative design systems explore the entire solution envelope and present the designer with multiple design alternatives that satisfy specified requirements. Although generative design systems present design solutions to an engineering problem, these systems lack consideration for the human element of the design system. Human cognition, particularly cognitive workload, can be hindered when presented with unparsed generative design system output, thereby reducing the efficiency of the systems engineering life cycle. Therefore, the objective of this dissertation was to develop a structured approach to produce an optimized parsing of spatially different generative design solutions, derived from generative design systems, such that human cognitive performance during the design process is improved. Generative design usability foundation work was conducted to further elaborate on gaps found in the literature in the context of the human component of generative design systems. A generative design application was then created for the purpose of evaluating the research objective. A novel generative design solution space parsing method that leverages the Gower distance matrix and partitioning around medoids (PAM) clustering method was developed and implemented in the generative design application to structurally parse the generative design solution space for the study. The application and associated parsing method were then used by 49 study participants to evaluate performance, workload, and experience during a generative design selection process, given manipulation of both the quantity of designs in the generative design solution space and filtering of parsed subsets of design alternatives. Study data suggests that cognitive workload is lowest when 10 to 100 generative design alternatives are presented for evaluation in the subset of the overall design solution space. However, subjective data indicates a caution when limiting the subset of designs presented, since design selection confidence and satisfaction may be decreased the more limited the design alternative selection becomes. Given these subjective considerations, it is recommended that a generative design solution space consists of 50 to 100 design alternatives, with the proposed clustering parsing method that considers all design alternative variables.
Open Access
Avoiding technical bankruptcy in system development: a process to reduce the risk of accumulating technical debt
(Colorado State University. Libraries, 2023) Kleinwaks, Howard, author; Bradley, Thomas, advisor; Batchelor, Ann, advisor; Marzolf, Gregory, committee member; Wise, Daniel, committee member; Turner, John F., committee member
The decisions made early in system development can have profound impacts on later capabilities of the system. In iterative systems development, decisions made in each iteration produce impacts on every future iteration. Decisions that have benefits in the short-term may damage the long-term health of the system. This phenomenon is known as technical debt. If not carefully managed, the buildup of technical debt within a system can lead to technical bankruptcy: the state where the system development can no longer proceed with its lifecycle without first paying back some of the technical debt. Within the schedule constrained development paradigm of iteratively and incrementally developed systems, it is especially important to proactively manage technical debt and to understand the potential long-term implications of decisions made to achieve short-term delivery goals. To enable proactive management of technical debt within systems engineering, it is first necessary to understand the state of the art with respect to the application of technical debt methods and terminology within the field. While the technical debt metaphor is well-known within the software engineering community, it is not as well known within the systems engineering community. Therefore, this research first characterizes the state of technical debt research within systems engineering through a literature review. Next, the prevalence of the technical debt metaphor among practicing systems engineers is established through an empirical survey. Finally, a common ontology for technical debt within systems engineering is proposed to enable clear and concise communication about the common problems faced in different systems engineering development programs. Using the research on technical debt in systems engineering and the ontology, this research develops a proactive approach to managing technical debt in iterative systems development by creating a decision support system called List, Evaluate, Achieve, Procure (LEAP). The LEAP process, when used in conjunction with release planning methods, can identify the potential for technical debt accumulation and eventually technical bankruptcy. The LEAP process is developed in two phases: a qualitative approach to provide initial assessments of the state of the system and a quantitative approach that models the effects of technical debt on system development schedules and the potential for technical bankruptcy based on release planning schedules. Example applications of the LEAP process are provided, consisting of the development of a conceptual problem and real applications of the process at the Space Development Agency. The LEAP process provides a novel and mathematical linkage of the temporal and functional dependencies of system development with the stakeholder needs, enabling proactive assessments of the ability of the system to satisfy those stakeholder needs. These assessments enable early identification of potential technical debt, reducing the risk of negative long-term impacts on the system health.
Open Access
Systems engineering assessment and experimental evaluation of quality paradigms in high-mix low-volume manufacturing environments
(Colorado State University. Libraries, 2023) Normand, Amanda, author; Bradley, Thomas, advisor; Miller, Erika, committee member; Vans, Marie, committee member; Zhao, Jianguo, committee member; Sullivan, Shane, committee member
This research aimed to evaluate the effectiveness of applying industrial paradigm application in high-mix low-volume manufacturing (HMLV) environments using a Systems Engineering approach. An analysis of existing industrial paradigms was conducted and then compared to a needs analysis for a specific HMLV manufacturer. Several experiments were selected for experimental evaluation, inspired by the paradigms, in a real-world HMLV manufacturing setting. The results of this research showed that a holistic approach to paradigm application is essential for achieving optimal performance, based on cost advantage, throughput, and flexibility, in the HMLV manufacturing environment. The findings of this research study provide insights into the importance of considering the entire manufacturing system, including both technical and human factors, when evaluating the effectiveness of industrial paradigms. Additionally, this research highlights the importance of considering the unique characteristics of HMLV manufacturing environments, such as the high degree of variability and frequent changes in product mix in designing manufacturing systems. Overall, this research demonstrates the value of a systems engineering approach in evaluating and implementing industrial paradigms in HMLV manufacturing environments. The results of this research provide a foundation for future research in this field and can be used to guide organizations in making informed decisions about production management practices in HMLV manufacturing environments.
Open Access
The next generation space suit: a case study of the systems engineering challenges in space suit development
(Colorado State University. Libraries, 2023) Cabrera, Michael A., author; Simske, Steve, advisor; Marzolf, Greg, committee member; Miller, Erika, committee member; Delgado, Maria, committee member
The objective for a NASA contractor, the performing organization in this case study, is to develop and deliver the next generation space suit to NASA, the customer in this case study, against a radically different level of customer expectation from previous years. In 2019, the administration had proposed a return to the moon, thus transforming and changing the system context of the current, next generation space suit in addition to pushing schedule expectations forward two years. The purpose of this dissertation will serve as a case study in two specific areas with qualitative and quantitative analyses regarding a new process and approach to (i) project lifecycle development and (ii) requirements engineering with the intent that if utilized, these tools may have contributed to improvements across the project in terms of meeting cost, scope, budget and quality while appropriately accounting for risk management. The procedure entails a research method in which the current state of the project, current state of the art, and the identified systems engineering challenges are evaluated and iterative models are tempered through development by continual improvements by engineering evaluation of engineers on the project. The current results have produced (i) a prototype project lifecycle development method via agile, Lean and Scrum hybrid implementations into a Traditional Waterfall framework and (ii) a prototype requirements engineering scorecard with implementations of FMEA and quantitative analysis to determine root cause identification.
Open Access
Using above-ground downwind methane and meteorological measurements to estimate the below-ground leak rate of a natural gas pipeline
(Colorado State University. Libraries, 2023) Cheptonui, Fancy, author; Riddick, Stuart N., advisor; Zimmerle, Daniel J., advisor; Fischer, Emily, committee member
Natural gas (NG) leaks from below-ground pipelines present a safety, economic, and environmental hazard, and triaging the severity of leaks remains a significant issue for pipeline operators. Typically, operators conduct walking surveys using hand-held methane (CH4) detectors which output CH4 concentrations to indicate the location of a leak, but quantification often requires excavation of the pipeline. Industry-standard CH4 detectors are lower-cost and have a higher detection threshold and lower precision than optical-cavity CH4 analyzers typically used to quantify emissions. It remains unclear whether coarser CH4 concentration measurements could be used to identify the large leaks that require immediate response. To explore the utility of industry-standard detectors, above-ground downwind CH4 concentration measurements made by the detectors as input to a novel modeling framework, the ESCAPE-1 model were used to estimate the leak rates from below-ground NG pipelines. Controlled below-ground emission experiments were conducted to test this approach over a range of environmental conditions. Using 10-minute averaged CH4 mixing/meteorological data and filtering out low wind/Pasquill Gifford Stability Class (PGSC) A events, the ESCAPE-1 model estimates small distribution leaks (0.2 kg CH4 h-1) to within -31 to +75% (95% CI), and medium distribution leaks (0.8 kg CH4 h-1) to within -73 to +92%(95% CI) of the actual leak rate. When averaged over a longer period (more than 3 hours of data), the average calculated leak rate was an overestimate of 55% for the small (0.2 kg CH4 h-1) leak and an underestimate of 6% for a medium distribution leak (0.8 kg CH4 h-1). Results suggest that as the wind speed increases, or the atmosphere becomes more stable both accuracy and precision of the leak rate calculated by the ESCAPE-1 model decreases. This is likely the result of a trade-off between the high enough wind to move the gas but not high enough that the plume becomes collimated and less homogenous. Optimizing this approach for oil and gas industry applications, this study suggests that CH4 mixing ratios measured by industry-standard CH4 detectors lasting at least 3 hours could be used as a guide to prioritize NG leak repair by estimating the below-ground leak rate from a pipeline within reasonable uncertainty bounds (±55%) in favorable atmospheric conditions.
Open Access
Leveraging operational use data to inform the systems engineering process of fielded aerospace defense systems
(Colorado State University. Libraries, 2023) Eddy, Amy, author; Daily, Jeremy, advisor; Marzolf, Gregory, committee member; Miller, Erika, committee member; Wise, Daniel, committee member
Inefficiencies in Department of Defense (DoD) Acquisition processes have been pervasive nearly as long as the DoD has existed. Stakeholder communication issues, funding concerns, large and overly complex organizational structures all play a role in adding challenges to those tasked with fielding, operating, and sustaining a complex aerospace defense system. As legacy defense systems begin to age, logistics and other supportability element requirements may change over time. While research literature supports the evidence that many stakeholders and senior leaders are aware of the issues and the DoD faces the impact those issues cause to mission performance, most research and attempts to improve the performance issues have been focused on high level restructuring of organizations or policy, processes, and procedures. There has been little research dedicated to identifying ways for working level logisticians and systems engineers to improve performance by leveraging operational use data. This study proposes a practical approach for working level logisticians and engineers to identify relationships between operational use data and supply performance data. This research focuses on linking negative aircraft events (discrepancies) to the supply events (requisitions) that result in downtime. This approach utilizes standard statistical methods to analyze operations, maintenance, and supply data collected during the Operations and Sustainment (O&S) phase of the life cycle. Further, this research identifies methods consistent with industry systems engineering practices to create new feedback loops to better inform the systems engineering life cycle management process, update requirements, and iterate the design of the enterprise system as a holistic entity that includes the physical product and its supportability elements such as logistics, maintenance, facilities, etc. The method identifies specific recommendations and actions for working level logisticians and systems engineers to prevent future downtime. The method is practical for the existing DoD organizational structure, and uses current DoD processes, all without increasing manpower or other resource needs.
Open Access
Sediment management alternatives analysis in the Louisiana deltaic plain
(Colorado State University. Libraries, 2023) Heap, David A., author; Young, Peter, advisor; Zimmerle, Daniel, committee member; Grigg, Neil, committee member; Ross, Matthew, committee member
While coastal communities around the world are under threat from rising sea levels, those of Southeast Louisiana are some of the most threatened. Including subsidence, the region could potentially see rates of net sea level rise up to ten times the global mean. There is no shortage of causes for how this situation has come to pass. A Systems Engineering solution needs to be multi-faceted, similar to how the problem was created:- Climate change: like any coastal area, the region has to make hard decisions on how to handle a changing climate, but those choices have significant ramifications for the entire U.S. population, as significant commerce passes through the regional ports in the form of agriculture, oil/gas, petrochemicals, and the fishing industry. - Engineered factors: by controlling the flow of the Mississippi River with the intent of flood protection through the use of levees, floodwalls, and spillways, humans have inhibited the natural processes that could rebuild the wetlands and natural protection barriers. - River navigation: similarly, the locks and dams that allow maritime traffic have trapped the sediment that historically would have flowed down to the delta and built more land buffers against the sea. - Industrial infrastructure: with thousands of miles of navigation channels and pipelines, the wetlands have been cut up into non-natural bodies of water, allowing hurricanes and saltwater intrusion unabated access to delicate ecosystems. - Environmental damage: over 100 years of industrial development, combined with numerous environmental disasters, has compromised the health of the ecosystem. - Invasive species: whether intentionally introduced or not, non-native species, both flora and fauna alike, have wreaked havoc on native populations and weakened deltaic processes. - Stakeholder coordination: with dozens of local, state, and federal government agencies and nonprofit organizations, it is nearly impossible to make everyone happy. - Limited resources: there is a funding gap between the budget needed to implement a successful strategy and what is expected to be available if the status quo is maintained. While there are multiple methods employed to improve coastal resilience, a core strategy as defined by Louisiana's 2023 Coastal Master Plan is the introduction of sediment. The plan suggests two main alternatives of sediment management, that of the Major Diversions and Dredged Sediment. In this work, these two traditional alternatives are considered, and a new proposed approach is introduced, that of Micro Diversions, a concept developed in prior work by the author. All three approaches are described, analyzed, modeled, and compared against each other to determine which would be the most cost effective and appropriate for investment by coastal stakeholders. The compared metric is Cost Benefit over a 50-year time horizon, calculated using the Life Cycle Cost and Net Benefit variables from each alternative. Inherent in the Systems Engineering approach is that the cost variables consider the time value of money. The Major Diversion variables were taken from the stated goals in the Master Plan. The Dredged Sediment variables were forecasted from historical trends on recently completed and/or approved projects. The Micro Diversion variables were formulated from hydrologic software modeling of a limited system and expanded to compare in size to the other alternatives. At a Cost Benefit of $61,773 per acre, the Major Diversion alternative was evaluated to be a better investment than Dredged Sediment or Micro Diversions ($67,300 and $88,206 respectively). Because coastal conditions can change over time, and that the inputs to these alternatives can likewise change, it is suggested to view solutions with a systems-level approach, with the potential to implement complementary alternatives.
Open Access
Optimizing text analytics and document automation with meta-algorithmic systems engineering
(Colorado State University. Libraries, 2023) Villanueva, Arturo N., Jr., author; Simske, Steven J., advisor; Hefner, Rick D., committee member; Krishnaswamy, Nikhil, committee member; Miller, Erika, committee member; Roberts, Nicholas, committee member
Natural language processing (NLP) has seen significant advances in recent years, but challenges remain in making algorithms both efficient and accurate. In this study, we examine three key areas of NLP and explore the potential of meta-algorithmics and functional analysis for improving analytic and machine learning performance and conclude with expansions for future research. The first area focuses on text classification for requirements engineering, where stakeholder requirements must be classified into appropriate categories for further processing. We investigate multiple combinations of algorithms and meta-algorithms to optimize the classification process, confirming the optimality of Naïve Bayes and highlighting a certain sensitivity to the Global Vectors (GloVe) word embeddings algorithm. The second area of focus is extractive summarization, which offers advantages to abstractive summarization due to its lossless nature. We propose a second-order meta-algorithm that uses existing algorithms and selects appropriate combinations to generate more effective summaries than any individual algorithm. The third area covers document ordering, where we propose techniques for generating an optimal reading order for use in learning, training, and content sequencing. We propose two main methods: one using document similarities and the other using entropy against topics generated through Latent Dirichlet Allocation (LDA).
Open Access
MBSAP application to UAV-based wildfire detection and communication
(Colorado State University. Libraries, 2023) Crawford, Setrige W., author; Eftekhari Shahroudi, Kamran, advisor; Borky, Mike, committee member; Kreidenweis-Dandy, Sonia, committee member; Bradley, Thomas, committee member; Herber, Daniel, committee member
By applying the concepts of the Model Based Systems Architecture Process [90] we were able to link stakeholder needs and operational scenarios (Use Cases) to the preliminary design validation of an autonomous hybrid electric/ gas turbine UAV (H-UAV) intended for wildfire detection and communication. The salient stakeholder requirements were captured, operational scenarios identified, trade study was completed, competing architectures were interlinked to a design exploration (DSE) and preliminary airframe sizing, where a user could probe the bounds of design variables in a probabilistic manner to reveal all necessary sensitives and confirm system behaviors were consistent with stakeholder requirements (spiral verification and validation). This thesis takes the reader through this method and the development of each viewpoint, using Cameo Systems Modeler, starting with the Operational Viewpoint, then refinement to the Logical viewpoint and finally development of the Physical Viewpoint. Emphasized, is the use of a coupled architecture model (digital twin – virtual prototype) to confirm system behaviors against requirements and to graphically display system sensitivities. The deeper details of the DSE method and the trade study were previously published [119]. This paper focuses more on the MBSAP approach, the MBSE artifacts and reflects on the benefits of an interlinked model.[7] The method developed affords the researcher a set of tools to efficiently converge on an affordable system solution which meets stakeholder needs and operational requirements for a locally owned and operated wildfire detection and communication system. Further, the MBSAP method is systems agnostic in that. the approach, yields equally effective results whether applied to more software intensive systems, or more mechanical aerospace system (H-UAV) instantiations.
Embargo
Situational strategic awareness monitoring surveillance system (SSAMSS)
(Colorado State University. Libraries, 2023) Maldonado, Kenly R., author; Simske, Steven J., advisor; Miller, Erika, committee member; Herber, Daniel, committee member; Dandy, David, committee member
This dissertation takes a Systems Engineering approach for the development of a cost-effective, deployable remote sensing materials safeguarding system. This co-called system-of-systems undergoes the major portions of the Systems Engineering development process to assure with confidence that a Situational Strategic Awareness Monitoring Surveillance System (SSAMSS) is a competitive product considered for actual development. The overall assessment takes a strategic approach by using selective tools to create, confirm and consider whether SSAMSS as a product idea ultimately should be developed into an actual prototypical Model (Engineering Model). Although the dissertation explores whether a prototype should be considerate with confidence and risk consideration it does not actually dive into the physical development of the model due to limited time and actual funding. Through the Systems Engineering V-Model, SSAMSS as a product and enterprise is vetted from the customer needs analyses through unit testing (the bottom of the V-model). This is the point where an actual customer would decide to continue the to incorporate SSAMSS into integration and testing, prototype to operations, maintenance, and retirement. Through simulations, assessment, and analysis it has been determined that SSAMSS as a product and enterprise is a viable option to supersede current material safeguarding systems that are competitive in the marketplace today.
Open Access
An enterprise system engineering analysis of KC-46A maintenance program decision-making
(Colorado State University. Libraries, 2023) Blond, Kyle E., author; Bradley, Thomas, advisor; Ender, Tommer, committee member; Conrad, Steven, committee member; Herber, Daniel, committee member; Ozbek, Mehmet, committee member
The KC-46A Pegasus is a United States Air Force (USAF) tanker, transport, and medical evacuation commercial derivative aircraft based on the Boeing 767. It is a top acquisition priority to modernize the USAF's refueling capabilities and is governed by a lifecycle sustainment strategy directed by USAF commercial variant policies aligned to Federal Aviation Administration (FAA) policy. While this strategy provides robust mechanisms to manage the KC-46A's performance during its operations and support phase, opportunity exists for the KC-46A sustainment enterprise to better achieve reliability, availability, maintainability, and cost (RAM C) objectives through enhancing KC-46A maintenance program decision making in the context of USAF and FAA policies. This research characterizes the KC-46A maintenance program as an industrial enterprise system governing the maintenance, repair, overhaul, and modification of KC-46A aircraft. Upon this basis, enterprise systems engineering (ESE) characterizes the KC-46A maintenance program and identifies decision making improvement opportunities in its management. Canonical ESE viewpoints are tailored to abstract the organizations, processes, and information composing KC-46A maintenance program decision making and model how decision support methods can better achieve KC-46A sustainment enterprise objectives. A decision making framework then evaluates the RAM C performance of KC-46A maintenance tasks as part of the KC-46A Continued Analysis and Surveillance System (CASS) program. The framework's heuristics classify the compliance, effectiveness, and optimality of a maintenance task to prescribe KC-46A CASS responses. A rule based expert system applies this framework and serves as the knowledge engine for the KC-46A CASS decision support system referred to as the "Pegasus Fleet Management Tool." A focus group of KC-46A sustainment experts evaluated the framework and produced consensus that it advances the state of the art in KC-46A maintenance program decision making. A business case analysis roadmaps the programmatic and technical activities required to implement the framework in PFMT and improve KC-46A sustainment.
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
Using controlled subsurface releases to investigate the effect of leak variation on above-ground natural gas detection
(Colorado State University. Libraries, 2023) Mbua, Mercy W., author; Riddixk, Stuart N., advisor; Zimmerle, Daniel J., advisor; Fischer, Joseph von, committee member
Leaks from underground natural gas (NG) pipelines pose safety and environmental concerns. Pipeline leak detection generally relies on measuring surface methane (CH4) enhancements during walking surveys and/or mobile surveys that attempt to identify CH4 plumes downwind of the pipeline. The likelihood of plume detection is dependent on the above-ground CH4 plume width. The size and shape of the plume is primarily dependent on environmental conditions but could also be complicated by leak characteristics. To investigate the effect of leak characteristics on CH4 plume width, this study uses controlled release experiments to observe above-ground plume width changes with changes in the gas composition, leak rate, and leak depth. Results show that plume width generally decreases with increased NG density, decreased leak rate and increases with depth between 0.6 and 0.9 m, but the above surface plume is undetectable above the background for leaks 1.8 m deep. The study established that the effect of adding heavy hydrocarbons to the NG mixture on plume width is equivalent to the effect of increased leak rate and depth on plume width multiplied by -0.04 and -0.89, respectively, with overall relative uncertainty of -42/ +14 %. This shows that reported leaks in areas with heavier hydrocarbons could currently be missed or underestimated. Further, this study shows that leaks from pipelines laid in covers meeting the Colorado Oil and Gas Conservation Commission minimum depth requirement of 0.9 m could be easier to detect compared to those buried at depths less than the minimum depth. Applying the findings to a real-world scenario, the study illustrates that a successful leak survey protocol tuned to NG leaks from Fayetteville shale (0.66 g/L NG density) may result in missed detections in the Permian, where NG is heavier (1.01 g/L) due to higher percentages of heavy hydrocarbons. Overall, this study illustrates that leak survey protocols for flowlines and gathering lines should be different from distribution pipelines and tailored to the compositions of the transported NG to report emissions accurately.
Open Access
Application of systems engineering principles in the analysis, modeling, and development of a DoD data processing system
(Colorado State University. Libraries, 2023) Fenton, Kevin P., author; Simske, Steven J., advisor; Bradley, Thomas, committee member; Carlson, Ken, committee member; Atadero, Rebecca, committee member
In support of over 1000 military installations worldwide, the Department of Defense (DoD) has procured contracts with thousands of vendors that supply the military with hazardous materials constituting billions of dollars of defense expenses in support of facility and asset maintenance. These materials are used for a variety of purposes ranging from weapon system maintenance to industrial and facility operations. In order to comply with environmental, health, and safety (EHS) regulations, the vendors are contractually obligated to provide Safety Data Sheets (SDSs) listing EHS concerns compliant with the requirements set forth by the United Nations Globally Harmonized System of Classification and Labeling of Chemicals (GHS). Each year chemical vendors provide over 100 thousand SDSs in a PDF or hard copy format. These SDSs are then entered manually by data stewards into the DoD centralized SDS repository – the Hazardous Material Management Information System (HMIRS). In addition, the majority of these SDS are also loaded separately by separate data stewards into downstream environmental compliance systems that support specific military branches. The association between the vendor-provided SDSs and the materials themselves was then lost until the material reaches an installation at which point personnel must select the SDS associated to the hazardous material within the service-specific hazardous material tracking system. This research applied systems engineering principles in the analysis, modeling, and development of a DoD data processing system that could be used to increase efficiency, reduce costs, and provide an automated solution not only to data entry reduction but in transitioning and modernizing the hazard communication and data transfer towards a standardized approach. Research for the processing system covered a spectrum of modern analytics and data extraction techniques including optical character recognition, artificial neural networks, and meta-algorithmic processes. Additionally, the research covered potential integration into existing DoD framework and optimization to solve many long-standing chemical management problems. While the long-term focus was for chemical manufacturers to provide SDS data in a standardized machine-encoded format, this system is designed to act as a transitionary tool to reduce manual data entry and costs of over $3 million each year while also enhancing system features to address other major obstacles in the hazard communication process. Complexities involved with the data processing of SDSs included multi-lingual translation needs, image and text recognition, periodic use of tables, and while SDSs are structured with 16 distinct sections – a general lack of standardization on how these sections were formatted. These complexities have been addressed using a patent-pending meta-algorithmic approach to produce higher data extraction yields than what an artificial neural network can produce alone while also providing SDS-specific data validation and calculation of SDS-derived data points. As the research progressed, this system functionality was communicated throughout the DoD and became part of a larger conceptual digital hazard communication transformation effort currently underway by the Office of the Secretary of Defense and the Defense Logistics Agency. This research led to five publications, a pending patent, an award for $280,000 for prototype development, and a project for the development of this system to be used as one of the potential systems in a larger DoD effort for full chemical disclosure and proactive management of not only hazardous chemicals but potentially all DoD-procured products.
Embargo
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.
Open Access
Cislunar system of systems architecture evaluation and optimization
(Colorado State University. Libraries, 2023) Duffy, Laura, author; Adams, Jim, advisor; Sega, Ronald M., committee member; Herber, Daniel R., committee member; Fankell, Douglas, committee member
Cislunar space is the next frontier of space exploration, but a sustainable architecture is lacking. Cislunar space is considered a complex system of systems because it consists of multiple independent systems that work together to deliver unique capabilities. The independent systems of the cislunar system of systems include the communications, navigation, and domain awareness systems. Additionally, the methodology to design, evaluate and optimize a complex system of systems has not been published. To close the gap, a comprehensive needs analysis is performed for cislunar space. Next, model-based systems engineering is used to design the cislunar system of systems. The cislunar architectures are designed in terms of constellations and payloads. The architectures are each evaluated in terms of cost and performance. An appropriate optimization algorithm is found for the system of systems, and the results of the optimization are evaluated using multiple techniques for comparison. A literature review is included on the topics of cislunar architectures, system of systems, model-based systems engineering, system architecture evaluation, and system architecture optimization. During the research of cislunar architectures, a needs analysis is completed which identifies the three primary missions planned for cislunar space and eight supporting functions to provide the infrastructure for the primary missions. The primary missions identified include science, commerce, and defense. The eight supporting functions identified include transportation, communication, domain awareness, service, energy, shelter, and control. Technologies and programs are identified for each supporting function, included gaps in needed technology or programs. For the evaluation and optimization of the system of systems, the supporting functions are down-selected to include only the three necessary supporting functions for any operations in cislunar space: communications, navigation, and domain awareness. A system architecture is developed using Systems Modeling Language in Cameo Systems ModelerTM. The model is designed using the Model-based Systems Architecture Process which includes the design of the Operational Viewpoint, Logical/Functional Viewpoint, and Physical Viewpoint. The Operational Viewpoint includes structural, behavioral, data, and contextual perspectives. The Logical/Functional Viewpoint includes structural, behavioral, data, and contextual perspectives. The Physical Viewpoint includes design, standards, data, and contextual perspectives. Each of these perspectives are represented in the form of Cameo Systems ModelerTM diagrams or tables. Diagrams include block definition diagrams, internal block diagrams, use case diagrams, activity diagrams, and sequence diagrams. Additional modeling concepts beyond the Model-based Systems Architecture Process are included in the Cameo Systems ModelerTM model and analysis of the model. These topics include allocating requirements, stereotypes, patterns in architecture decisions, architecture optimization, verification, validation, complexity, and open systems architecture. Cislunar constellations and payloads are designed which account for the cislunar physical environment. Six constellations are designed to be included in the optimization algorithm. These constellations include Lagrange light, Lagrange medium, Lagrange heavy, Earth-based, Earth plus Moon, and Earth plus Lagrange. These constellations essentially represent the location of the bus while the payloads provide the functionality of the system. Payloads are designed for the supporting functions deemed essential for a basic cislunar infrastructure, which are communications, navigation, and domain awareness. The optimization algorithm runs through each possible combination of payload and bus, including any opportunities to integrate multiple payloads on a single bus. The total number of possible architecture combinations for the optimization algorithm is 288. The payload sensors are modeled in Systems Tool Kit and evaluated for physical performance. Additionally, each payload and bus possibility are evaluated for cost using the Unmanned Space Vehicle Cost Model and professional estimates. The performance and cost metrics are used in the optimization algorithm. The optimization algorithm uses multi-objective optimization with an integer linear program. The result of the optimization algorithm is a pareto front of the highest-performance, lowest-cost architectures. The architectures along the pareto front are evaluated using multi-criteria decision making with and without evidential reasoning to find the "best" architecture. A Kiviat chart assessment is also performed, though this method is shown to not be practical for the cislunar application. The model and conclusions of the dissertation are validated using a variety of industry-accepted techniques. The cislunar architectures are validated via peer-review. The performance evaluations are validated via a validated physics model. The cost evaluations are validated by a validated cost-model when possible and by peer-review. The optimization algorithm is validated by comparison to a manual optimization method. The Cameo Systems ModelerTM model is validated using validation techniques internal to the tool. Suggestions for future work are presented. Future work could include fully integrating the Cameo Systems ModelerTM model with the Systems Tool Kit model, providing improved cost estimates, using alternative optimization parameters, adding supporting functions as they are identified, evaluating the architectures using additional metrics, evaluating additional constellations, applying integration at the functional level, or assessing non-homogenous requirements.
Embargo
Determining systems engineering value in competitive bids
(Colorado State University. Libraries, 2023) Dawson, Sandra Lynn, author; Batchelor, Ann, advisor; Arenson, David, committee member; Adams, James, committee member; Simske, Steve, committee member; Wise, Dan, committee member
Corporations need a methodology to determine existing and new Systems Engineering (SE) effort costs in a more relevant context through deepening its connection within the competitive bidding process. The impact of Digital Engineering (DE) on SE within competitive bids is evolving as the industry is maturing its DE transition and implementation. The state of the field does not consider the impact of the current transition from traditional document-based SE (TDSE) to digital engineering (DE) and the impact on SE value. This paper examines the effectiveness of the SE costing models that are available in the literature by introducing a process to compare completed projects using metrics of actual SE hours expended and project performance against recommended SE effort and project results. Analysis of this comparison provides justification for SE effort bid ranges and associated project results. This research endeavors to enable a more holistic and SE-centric view of SE costing with considerations of project characteristics and the ongoing DE transition. Finally, this research provides a new framework for the analysis results and references useful in the bidding of SE projects where SE bid options can be associated with project performance, DE transition progress, and references relevant to the competitive bid approach. By applying systems thinking, using feedback loops and data from multiple organizations, understanding SE-DE impact, and empowering engineers in the DE transition, these research results enable data-driven decisions to determine SE value in competitive bids and to optimize SE using risk management. Following this process and using an organization's data (for competitive bids and projects) will yield results specific to competitive bids, bid technical approach, and DE transition progress. These results are communicated to the competitive bids teams using a SE focused framework.
Open Access
Lifecycle assessment modeling and encouraging reuse in the corrugated packaging industry using persuasion and operant conditioning
(Colorado State University. Libraries, 2023) Ketkale, Harshwardhan, author; Simske, Steve, advisor; Miller, Erika, committee member; Conrad, Steve, committee member; Cleary, Anne, committee member
Greenhouse gas emission is a major contributor to climate change and global warming. Many sustainability efforts are aimed at reducing greenhouse gas emissions. These include recycling and the use of renewable energy. In the case of recycling, the general population is typically required to at least temporarily store, and possibly haul, the materials rather than simply throwing them away. This effort from the general population is a key aspect of recycling, and in order for recycling to work, some investment of time and effort is required by the public. In the case of corrugated cardboard boxes, it has been observed that there is less motivation for the general population to recycle them. Also, the manufacturing of a product such as a corrugated cardboard box (CCB) includes the extraction of a variety of raw materials in addition to supply chain efforts to get the raw materials to the industry. The extraction of raw material and its supply chain as well as the unproper end of lifecycle phase can significantly impact the carbon emission of a product over its lifecycle. This research explores different means of motivating people to reuse, and not just recycle, with different types of incentives. It addresses the use of persuasion techniques and operant conditioning techniques together to incentivize the general population to adopt sustainable efforts. Further, this study makes an attempt to segment the general population based on age, gender, persuasion preferences, operant condition preferences, personality types, awareness of environment/climate change as well as current recycling effort of the participants to use different forms of incentives and motivational work unlike any approaches found in the literature review. Four types of persuasion techniques and four types of operant conditioning are combined to give 16 different types of incentives. Three online surveys are conducted, and their data are analyzed (using entropy, Hamming distance, t-test, chi-square, and ANOVA). The results indicate that "positive reinforcement + ethos" is a cost-effective way to incentivize the general population. This study also conducts a Lifecycle Assessment (LCA) that gives the carbon emission of each phase of the product and a quantitative estimate of the overall product carbon footprint and its effect on the environment. This gives impetus to recommendations for improving the phases of the lifecycle to minimize carbon emissions. This research uses LCA to evaluate the carbon emission in each phase of the lifecycle of a typical 1 kg corrugated cardboard box in the United States. Carbon emission for the proposed "reuse" phase is also calculated, and the results are compared. To examine if the incremental cost of reusing the CCBs is less than the environmental and economic cost of reducing the extraction and supply chain of raw materials, this study explores the economic feasibility of the proposed "reuse" method that incentivizes the general population to reuse the CCBs instead of recycling or landfilling them. Economic tools such as willingness-to-pay vs. marginal cost curves and benefit-cost analyses are used to evaluate economic feasibility. The results indicate that the "reuse" method for CCBs is economically and environmentally feasible. It also supports the approach of using analytics, economics, and LCA to create a model that can be used for other products and processes as an evaluative process to determine if businesses can benefit from the reduction (or removal) of material extraction costs from the supply chain. The results of this study can be applied to a wide range of applications such as solar panels, incentives for vaccination, and other areas wherein sustainability-centric behavior is encouraged.
Embargo
Modeling and simulation to investigate the electrification potential of medium- and heavy-duty vehicle fleets
(Colorado State University. Libraries, 2023) Trinko, David A., author; Bradley, Thomas H., advisor; Quinn, Jason C., committee member; Simske, Steven, committee member; Hurrell, James, committee member
This project involves developing and integrating new modeling tools to simulate the dynamics of electric medium- and heavy-duty fleet vehicle adoption. A technical and economic modeling tool, combining a data-driven hardware cost model with a cost-optimal charging strategy microsimulation, enables tailored analysis of the costs and benefits of electrifying individual fleets. Next, a novel text synthesis process, applied to a curated corpus of literature, quantifies trade-offs between technical, economic, and other factors in the fleet vehicle procurement decision. The outcomes of these tasks combine with knowledge from recent literature on fleet decision processes to specify the vehicle procurement model used by fleets in an agent-based model of the medium- and heavy-duty electric vehicle market. This model embodies an especially disaggregated approach to adoption modeling, internalizing factors and dynamics that conventional adoption models externalize. In particular, explicitly modeling the formation and diffusion of opinions among agents enables experiments that conventional models cannot support. Demonstrations show, for example, that increasing the extent of interactions between populations with different proclivities to electric vehicles has an asymmetrical outcome. High-proclivity electric vehicle adoption is generally unaffected as interactions increase, but low-proclivity adoption is accelerated. By representing individual fleets' requirements and costs at a high level of detail, incorporating an adoption decision model informed by a wide body of empirical research, and broadening the array of variables and dynamics available for experimentation, this integrated model offers a new way to understand the urgent challenge of eliminating emissions from the most emissions-intensive transportation sectors.