Browsing by Author "Cale, James, committee member"

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Open Access
A systems engineering approach to community microgrid electrification and sustainable development in Papua New Guinea
(Colorado State University. Libraries, 2019) Anderson, Alexander A., author; Suryanarayanan, Siddharth, advisor; Cale, James, committee member; Zimmerle, Dan, committee member; Chen, Suren, committee member
Electrification of remote communities worldwide represents a key necessity for sustainable development and advancement of the 17 United Nations Sustainable Development Goals (SDGs). With over 1 billion people still lacking access to electricity, finding new methods to provide safe, clean, reliable, and affordable energy to off-grid communities represents an increasingly dynamic area of research. However, traditional approaches to power system design focused exclusively on traditional metrics of cost and reliability do not provide a sufficiently broad view of the profound impact of electrification. Installation of a single microgrid is a life-changing experience for thousands of people, including both residents who receive direct electricity service and numerous others who benefit from better education, new economic opportunities, incidental job creation, and other critical infrastructure systems enabled by electricity. Moreover, an electrification microgrid must directly satisfy community needs, be sensitive to local environmental constraints, mitigate possible risks, and plan for at least a decade of sustainable operations and maintenance. These considerations extend beyond the technical and optimization problems typically addressed in microgrid design. An enterprise system-of-systems framework for microgrid planning considering technical, economic, environmental, and social criteria is developed in response to the need for a comprehensive methodology for planning of community electrification projects. This framework spans the entire systems engineering discipline and incorporates elements from project management, risk management, enterprise architecture, numerical optimization, and multi-criteria decision-making, and sustainable development theory. To support the creation of the systems engineering framework, a comprehensive survey of multi-objective optimization formulations for planning and dispatch of islanded microgrids was conducted to form a baseline for further discussion. This survey identifies that all optimizations studies of islanded microgrids are based on formulations selecting a combination of 16 possible objective functions, 14 constraints, and 13 control variables. A sufficient group of decision-making elicitees are formed from the group of nearly 250 publications surveyed to create a comprehensive optimization framework based on technical, economic, environmental, and social attributes of islanded microgrids. This baseline enables the formulation of a flexible, computationally lightweight methodology for microgrid planning in consideration of multiple conflicting objectives using the simple multi-attribute ranking technique exploiting ranks (SMARTER). Simultaneously, the identified technical, economic, environmental, and social decision criteria form a network of functional, operational, and performance requirements in an enterprise system-of-systems structure that considers all stakeholders and actors in the development of community electrification microgrids. This framework considers community capacity building and sustainable development theory as a hierarchical structure, where each layer of the hierarchy is mapped both to a set of organizational, financial, and physical subsystems and to a corresponding subset of the 17 SDGs. The structure presents the opportunity not only to integrate classical project management and risk management tools, but also to create a new lifecycle for planning, funding, executing, and monitoring multi-phase community infrastructure projects. Throughout the research, a case study of the Madan Community in Jiwaka Province, Papua New Guinea is used to demonstrate the systems engineering concepts and tools developed by the research. The community is the center of multi-phase community capacity building project addressing critical needs of the deep rural community, including electricity, education, water, sanitation, healthcare, and economic opportunities. The researcher has been involved as a pro-bono consultant for the project since 2013 and helped raise over $1M USD in infrastructure materials, equipment, and consulting. The structure of the community-based organization and numerical optimization of a series of islanded microgrids are used to illustrate both the system-of-systems hierarchy and microgrid planning techniques based on both single-objective optimization using linear programming and the SMARTER methodology for consideration of multiple qualitative and quantitative decision criteria.
Open Access
Control design for generator of nonlinear high frequency plasma system
(Colorado State University. Libraries, 2021) Vora, Prajay, author; Young, Peter, advisor; Zimmerle, Daniel, committee member; Cale, James, committee member
This document aims to develop control systems for a generator of a nonlinear high frequency plasma system. Initial modelling was done by Advanced Energy Industries, Inc. (AE) which was passed on to Colorado State University environment for further research into developing controllers for this special model. This thesis documents all the work done by Colorado State University till Summer of 2020. The first phase of the collaboration included finding metrics for the feedback system with the nonlinear load modelled by AE. The metrics serve for better understanding of the modelling and also to generate effective control criteria suited to AE requirements. AE required for the user defined wave-forms to be tracked in an average sense without significantly changing the real time tracking criteria. This tradeoff was also addressed while developing metrics. A preliminary approach for control design was a PID controller to study its effects in a nonlinear environment. A robust control approach called H∞ loop-shaping is the primary control design developed by CSU for this specific application. The nonlinear system was approximated with a transfer function and the controller developed for that approximation. The purpose of the approximation is to generate a controller that is highly robust considering the uncertainties in high frequency plasma loads. The metrics discussed above are used for confirming the efficiency of the controllers. Controller design was the second phase of the project. Finally, in phase three, Nelder-Mead optimization was used to generalize the H∞ controller for various generator and set-point specifications. A system identification processes was also developed consisting of curve fit models for the nonlinear load. This was done with a view to the future for classifying different loads and plasma to develop customised controllers.
Open Access
Development of a human factors hazard model for use in system safety analysis
(Colorado State University. Libraries, 2021) Birch, Dustin Scott, author; Bradley, Thomas, advisor; Miller, Erika, committee member; Cale, James, committee member; Ozbek, Mehmet, committee member
Traditional methods for Human Reliability Analysis (HRA) have been developed with specific applications or industries in mind. Additionally, these methods are often complicated, time consuming, costly to apply, and are not suitable for direct comparison amongst themselves. The proposed Human Factors Hazard Model (HFHM) utilizes the established and time-tested probabilistic analysis tools of Fault Tree Analysis (FTA) and Event Tree Analysis (ETA), and integrates them with a newly developed Human Error Probability (HEP) predictive tool. This new approach is developed around Performance Shaping Factors (PSFs) relevant to human behavior, as well as specific characteristics unique to a system architecture and its corresponding operational behavior. This updated approach is intended to standardize, simplify, and automate the approach to modeling the likelihood of a mishap due to a human-system interaction during a hazard event. The HFHM is exemplified and automated within a commercial software tool such that trade and sensitivity studies can be conducted and validated easily. The analysis results generated by the HFHM can be used as a standardized guide to SE analysts as a well as design engineers with regards to risk assessment, safety requirements, design options, and needed safety controls within the system architecture. Verification and evaluation of the HFHM indicate that it is an effective tool for HRA and system safety with results that accurately predict HEP values that can guide design efforts with respect to human factors. In addition to the development and automation of the HFHM, application within commonly used system safety Hazard Analysis Techniques (HATs) is established. Specific utilization of the HFHM within system or subsystem level FTA and Failure Mode and Effects Analysis (FMEA) is established such that human related hazards can more accurately be accounted for in system design safety analysis and lifecycle management. Lastly, integration of the HFHM within Model-Based System Engineering (MBSE) emphasizing an implementation into the System Modeling Language (SysML) is established using a combination of existing hazard analysis libraries and custom designed libraries within the Unified Modeling Language (UML). The FTA / ETA components of the hazard model are developed within SysML partially utilizing the RAAML (Risk Analysis and Assessment Modeling Language) currently under development by the Object Management Group (OMG), as well as a unique recursive analysis library. The SysML model successfully replicates the probabilistic calculation results of the HFHM as generated by the native analytical model. The SysML profiles developed to implement HFHM have application in integration of conventional system safety analysis as well as requirements engineering within lifecycle management.
Open Access
Efficiency of AC vs. DC distribution systems in commercial buildings
(Colorado State University. Libraries, 2022) Santos, Arthur Felício Barbaro dos, author; Young, Peter, advisor; Zimmerle, Daniel, advisor; Cale, James, committee member; Clark, Maggie, committee member
Decarbonization and modernization of the grid, electrification of transportation, and energy storage are some of the trends pushing towards the significant growth of power electronics in the past few decades. The massive application of such devices has increased the interest in direct current (DC) power distribution as an alternative to the conventional alternating current (AC) distribution systems in residential and commercial buildings. This increase in non-linear loads, however, substantially increases current harmonics, which compromises the lifespan, efficiency, and/or operability of distribution components, such as transformers and protection equipment. Additionally, when comparing the efficiency of AC vs. DC distribution systems, the literature is often based on simulation studies rather than real measured data. In this regard, this study focuses on three major topics: a) Harmonic cancellation within building circuits; b) Endpoint use efficiency comparison for AC and DC in-building distribution systems; and c) A cautionary note on using smart plugs for research data acquisition. The analyses are based on recorded power consumption data from office-based appliances, made by smart plugs, combined with detailed characterization of sampled Miscellaneous Electric Loads (MELs') power converters. While harmonic cancellation studies often assume that AC converters operate across their rated power range, measured realistic power profiles reported in this work show that MELs operate below 40% of rated power the majority of the time when not in standby mode. This makes the harmonic cancellation significantly lower than that predicted when using full-range power assumptions, which could provide incorrect guidance to building design engineers. In contrast, increased diversity of MELs increases harmonic cancellation. Blending typical office loads with lighting, for instance, improves the harmonic cancellation to near the levels predicted by traditional methods. Regarding the endpoint efficiency of AC and DC distribution systems, no systematic efficiency advantage was found, when endpoint AC/DC converters were compared to a similar, commercially available, DC/DC converter powering the same load profile. That goes in the opposite direction of prior studies, which estimate converters' efficiency based on datasheet information or the efficiency at rated load.
Open Access
High efficiency air delivery system for solid oxide fuel cell power generation
(Colorado State University. Libraries, 2024) Mitchel, Lars Jared-Brian, author; Bandhauer, Todd M., advisor; Windom, Bret C., committee member; Cale, James, committee member
Distributed power generation systems can be used in the electric grid to reduce peak loads, raise power quality, and reduce/eliminate transmission losses. One distributed energy system with distinct advantages is a Solid Oxide Fuel Cell (SOFC) integrated with an Internal Combustion Engine (ICE) which has the capability to operate at electric efficiencies as high as 70%. This research aimed to produce and test a high efficiency air delivery system that supports the SOFC-ICE to generate power on the scale of 80 kW. The air balance of plant (BOP) system utilized low speed scroll-type rotating compressors and brazed plate and frame heat exchangers for efficient preheating. The scroll compressors were modeled in GT-Suite and the remaining air BOP system was modeled with thermodynamic and heat transfer equations. Then testing was done on the compressors and heat exchangers to validate the model so that the air BOP system performance could be accurately predicted within a range of conditions. Both compressors were run from a range of 20 g/s to 60 g/s with the heat through the system being swept from 100°C to 600°C which yielded compressor efficiencies over 60% and heat exchanger effectiveness over 0.90. The validated model was then used to make predictions about system performance at on and off-design conditions.
Open Access
Measuring disagreement in segments of the cybersecurity profession as a means of identifying vulnerabilities
(Colorado State University. Libraries, 2022) Scalco, Aleksandra, author; Simske, Steven J., advisor; Cale, James, committee member; Herber, Daniel, committee member; Dik, Bryan J., committee member
Disagreement exists among different groups of professionals about remediation of control system vulnerability due to discrepancies in engineering practice, paradigms, processes, and culture. Quantification of agreement among professionals is needed to increase understanding of areas where divergence arises. This need to quantify agreement is particularly among control system Operational Technology (OT) and business enterprise Information Technology (IT) professions. The control system OT workforce does not fully understand the relative vulnerability of each element of its system. Likewise, the business enterprise IT workforce does not widely understand control system assets that control critical infrastructure to achieve cybersecurity assurance. This disagreement among professionals leads to misalignment, which results in vulnerability. Similarly, known vulnerability can inform alignment and bring about agreement among professionals. The exposure induced by misalignment may be greater than innate system design vulnerability. This research introduces an analytical model and methodology for measuring multi-concern assurance among different groups of professions through the statistical uncertainty analysis of Likert and semantic differential scales used for interpreting the scores to identify specific areas of vulnerability.
Open Access
Modeling and design of a power boosted turbo-compression cooling system
(Colorado State University. Libraries, 2021) Roberts, Nickolas Richard, author; Bandhauer, Todd M., advisor; Quinn, Jason C., committee member; Cale, James, committee member
Waste heat recovery technologies have the potential to reduce fuel consumption and address increased electricity and cooling demands in shipboard applications. Existing thermally driven power and cooling technologies are simply too large to be installed on ships where space for new equipment is extremely limited. This study addresses major shipboard challenges through the modeling and design of a volume optimized turbo-compression cooling system (TCCS). The TCCS is driven by low-grade waste heat in the shipboard diesel generator set jacket water and lubrication oil and was designed to be a drop-in replacement of electric chiller systems. A case study of a marine diesel generator set and electric chiller is presented, including annual engine loading and seawater temperature profiles. Three TCCS integration options and five working fluids (R134a, R1234ze(E), R1234yf, R245fa, R515a) were evaluated over the range of case study conditions using a fixed heat exchanger effectiveness thermodynamic model. The hybrid thermally and electricity driven "power boosted" TCCS reduced electricity consumption for cooling by over 100 kWe. Plate and frame heat exchanger models were used to size and optimize the system to fit within the volume of a commercial centrifugal chiller of equal cooling capacity. The system used R134a, provided 200-tons of cooling, and had an electric coefficient of performance (COP) of 9.84 at the design conditions. Optimized heat exchanger and pipe geometries were fixed, and the model was run over the range of case study conditions to determine annual fuel savings of 92.1 mt yr-1 and a weighted average generator set power density improvement of 11.0%. Heat exchangers, turbomachinery, and piping were solid modeled to demonstrate that the system fits within the required footprint (40.6 ft2) and volume (267 ft3). The designed system was estimated to cost $295,036 in equipment and $442,554 in total installed costs. The resulting payback period was 5.77 years while operating for only 3,954 hours per year. Over a 15-year period, the net present value and internal rate of return were $176,734 and 16%, respectively.
Open Access
Novel assessments of country pandemic vulnerability based on non-pandemic predictors, pandemic predictors, and country primary and secondary vaccination inflection points
(Colorado State University. Libraries, 2024) Vlajnic, Marco M., author; Simske, Steven, advisor; Cale, James, committee member; Conrad, Steven, committee member; Reisfeld, Bradley, committee member
The devastating worldwide impact of the COVID-19 pandemic created a need to better understand the predictors of pandemic vulnerability and the effects of vaccination on case fatality rates in a pandemic setting at a country level. The non-pandemic predictors were assessed relative to COVID-19 case fatality rates in 26 countries and grouped into two novel public health indices. The predictors were analyzed and ranked utilizing machine learning methodologies (Random Forest Regressor and Extreme Gradient Boosting models, both with distribution lags, and a novel K-means-Coefficient of Variance sensitivity analysis approach and Ordinary Least Squares Multifactor Regression). Foundational time series forecasting models (ARIMA, Prophet, LSTM) and novel hybrid models (SARIMA-Bidirectional LSTM and SARIMA-Prophet-Bidirectional LSTM) were compared to determine the best performing and accurate model to forecast vaccination inflection points. XGBoost methodology demonstrated higher sensitivity and accuracy across all performance metrics relative to RFR, proving that cardiovascular death rate was the most dominant predictive feature for 46% of countries (Population Health Index), and hospital beds per thousand people for 46% of countries (Country Health Index). The novel K-means-COV sensitivity analysis approach performed with high accuracy and was successfully validated across all three methods, demonstrating that female smokers was the most common predictive feature across different analysis sets. The new model was also validated with the Calinski-Harabasz methodology. Every machine learning technique that was evaluated showed great predictive value and high accuracy. At a vaccination rate of 13.1%, the primary vaccination inflection point was achieved at 83.27 days. The secondary vaccination inflection point was reached at 339.31 days at the cumulative vaccination rate of 67.8%. All assessed machine and deep learning methodologies performed with high accuracy relative to COVID-19 historical data, demonstrated strong forecasting value, and were validated by anomaly and volatility detection analyses. The novel triple hybrid model performed the best and had the highest accuracy across all performance metrics. To be better prepared for future pandemics, countries should utilize sophisticated machine and deep learning methodologies and prioritize the health of elderly, frail and patients with comorbidities.
Open Access
Some efficient open-loop control solution strategies for dynamic optimization problems and control co-design
(Colorado State University. Libraries, 2021) Sundarrajan, Athul Krishna, author; Herber, Daniel R., advisor; Cale, James, committee member; Venayagamoorthy, Karan, committee member
This thesis explores strategies to efficiently solve dynamic optimization (DO) and control codesign (CCD) problems that arise in early-stage system design studies. The task of design optimization of dynamic systems involves identifying optimal values of the physical elements of the system and the inputs to effectively control the dynamic behavior of the system to achieve peak performance. The problem becomes more complex when designing multidisciplinary systems, where the coupling between disciplines must be accounted for to achieve optimal performance. Developing tools and strategies to efficiently and accurately solve these problems is needed. Conventional design practices involve sequentially optimizing the plant parameters and then identifying a control scheme for the given plant design. This sequential design procedure does not often produce system-level optimal solutions. Control co-design or CCD is a design paradigm that seeks to find system-level optimal design through simultaneous optimization of the plant and control variables. In this work, both the plant and controls optimization are framed as a integrated DO problem. We focus on a class of direct methods called direct transcription (DT) to solve these DO problems. We start with a subclass of nonlinear dynamic optimization (NLDO) problems for the first study, namely linear-quadratic dynamic optimization problems (LQDO). For this class of problems, the objective function is quadratic, and the constraints are linear. Highly efficient and accurate computational tools have been developed for solving LQDO problems on account of their linear and quadratic problem elements. Their structure facilities the development of automated solvers. We identify the factors that enable creating these efficient tools and leverage them towards solving NLDO problems. We explore three different strategies to solve NLDO problems using LQDO elements, and analyze the requirements and limits of each approach. Though multiple studies have used one of the methods to solve a given CCD problem, there isa lack of investigations identifying the trade-offs between the nested and simultaneous CCD, two commonly used methods. We build on the results from the first study and solve a detailed active suspension design using both the nested and simultaneous CCD methods. We look at the impact of derivative methods, tolerance, and the number of discretization points on the solution accuracy and computational times. We use the implementation and results from this study to form some heuristics to choose between simultaneous and nested CCD methods. A third study involves CCD of a floating offshore wind turbine using the levelized cost of energy (LCOE) as an objective. The methods and tools developed in the previous studies have been applied toward solving a complex engineering design problem. The results show that the impact of optimal control strategies and the importance of adopting an integrated approach for designing FOWTs to lower the LCOE.
Open Access
Structural health monitoring in adhesively bonded composite joints
(Colorado State University. Libraries, 2024) Caldwell, Steven, author; Radford, Donald W., advisor; Simske, Steven, committee member; Cale, James, committee member; Adams, Henry, committee member
Composite bonded aircraft structure is a prevalent portion of today's aircraft structural composition. Adequate bond integrity is a critical aspect of the fabrication and operational service life of aircraft structure. Many of these structural bonds are critical for flight safety. Thus, a major concern is related to the assurance of quality in the structural bond. Over the last decade, non-destructive bond evaluation techniques have improved but still cannot detect a structurally weak bond that exhibits full adherend/adhesive contact. Currently, expensive, and time-consuming structural proof testing is required to verify bond integrity. The objective of this work is to investigate the feasibility of bondline integrity monitoring via piezoelectric sensors embedded in the composite joint. Initially, a complex composite joint, the Pi preform, was analytically evaluated for health monitoring viability, with the results showing promising capability. Subsequently, due to experimental complexities, a simple, state-of-the-art composite single lap shear joint is selected for experimentation and analysis to measure and quantify the effect of incorporating a sensor within the bondline to evaluate and expand on the ability of the embedded sensor to monitor and assess the joint integrity. Simple flatwise tension joints are also studied to investigate an orthogonal loading direction through the sensor. The experimental results indicate that the embedded piezoelectric sensors can measure a change in the joint before the integrity degrades and fails on subsequent loadings, resulting in a novel approach for prognostic performance evaluation without detrimentally affecting the performance of the structural joint.