Matching Items (29)

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Complex Systems Approach for Simulation & Analysis of Socio-Technical Infrastructure Systems - An Empirical Demonstration

Description

Over the past century, the world has become increasingly more complex. Modern systems (i.e blockchain, internet of things (IoT), and global supply chains) are inherently difficult to comprehend due to

Over the past century, the world has become increasingly more complex. Modern systems (i.e blockchain, internet of things (IoT), and global supply chains) are inherently difficult to comprehend due to their high degree of connectivity. Understanding the nature of complex systems becomes an acutely more critical skill set for managing socio-technical infrastructure systems. As existing education programs and technical analysis approaches fail to teach and describe modern complexities, resulting consequences have direct impacts on real-world systems. Complex systems are characterized by exhibiting nonlinearity, interdependencies, feedback loops, and stochasticity. Since these four traits are counterintuitive, those responsible for managing complex systems may struggle in identifying these underlying relationships and decision-makers may fail to account for their implications or consequences when deliberating systematic policies or interventions.

This dissertation details the findings of a three-part study on applying complex systems modeling techniques to exemplar socio-technical infrastructure systems. In the research articles discussed hereafter, various modeling techniques are contrasted in their capacity for simulating and analyzing complex, adaptive systems. This research demonstrates the empirical value of a complex system approach as twofold: (i) the technique explains systems interactions which are often neglected or ignored and (ii) its application has the capacity for teaching systems thinking principles. These outcomes serve decision-makers by providing them with further empirical analysis and granting them a more complete understanding on which to base their decisions.

The first article examines modeling techniques, and their unique aptitudes are compared against the characteristics of complex systems to establish which methods are most qualified for complex systems analysis. Outlined in the second article is a proof of concept piece on using an interactive simulation of the Los Angeles water distribution system to teach complex systems thinking skills for the improved management of socio-technical infrastructure systems. Lastly, the third article demonstrates the empirical value of this complex systems approach for analyzing infrastructure systems through the construction of a systems dynamics model of the Arizona educational-workforce system, across years 1990 to 2040. The model explores a series of dynamic hypotheses and allows stakeholders to compare policy interventions for improving educational and economic outcome measures.

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Date Created
  • 2020

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Data Analysis and Experimental Design for Accelerated Life Testing with Heterogeneous Group Effects

Description

In accelerated life tests (ALTs), complete randomization is hardly achievable because of economic and engineering constraints. Typical experimental protocols such as subsampling or random blocks in ALTs result in a

In accelerated life tests (ALTs), complete randomization is hardly achievable because of economic and engineering constraints. Typical experimental protocols such as subsampling or random blocks in ALTs result in a grouped structure, which leads to correlated lifetime observations. In this dissertation, generalized linear mixed model (GLMM) approach is proposed to analyze ALT data and find the optimal ALT design with the consideration of heterogeneous group effects.

Two types of ALTs are demonstrated for data analysis. First, constant-stress ALT (CSALT) data with Weibull failure time distribution is modeled by GLMM. The marginal likelihood of observations is approximated by the quadrature rule; and the maximum likelihood (ML) estimation method is applied in iterative fashion to estimate unknown parameters including the variance component of random effect. Secondly, step-stress ALT (SSALT) data with random group effects is analyzed in similar manner but with an assumption of exponentially distributed failure time in each stress step. Two parameter estimation methods, from the frequentist’s and Bayesian points of view, are applied; and they are compared with other traditional models through simulation study and real example of the heterogeneous SSALT data. The proposed random effect model shows superiority in terms of reducing bias and variance in the estimation of life-stress relationship.

The GLMM approach is particularly useful for the optimal experimental design of ALT while taking the random group effects into account. In specific, planning ALTs under nested design structure with random test chamber effects are studied. A greedy two-phased approach shows that different test chamber assignments to stress conditions substantially impact on the estimation of unknown parameters. Then, the D-optimal test plan with two test chambers is constructed by applying the quasi-likelihood approach. Lastly, the optimal ALT planning is expanded for the case of multiple sources of random effects so that the crossed design structure is also considered, along with the nested structure.

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Date Created
  • 2017

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Modeling and H-Infinity Loop Shaping Control of a Vertical Takeoff and Landing Drone

Description

VTOL drones were designed and built at the beginning of the 20th century for military applications due to easy take-off and landing operations. Many companies like Lockheed, Convair, NASA and

VTOL drones were designed and built at the beginning of the 20th century for military applications due to easy take-off and landing operations. Many companies like Lockheed, Convair, NASA and Bell Labs built their own aircrafts but only a few from them came in to the market. Usually, flight automation starts from first principles modeling which helps in the controller design and dynamic analysis of the system.

In this project, a VTOL drone with a shape similar to a Convair XFY-1 is studied and the primary focus is stabilizing and controlling the flight path of the drone in
its hover and horizontal flying modes. The model of the plane is obtained using first principles modeling and controllers are designed to stabilize the yaw, pitch and roll rotational motions.

The plane is modeled for its yaw, pitch and roll rotational motions. Subsequently, the rotational dynamics of the system are linearized about the hover flying mode, hover to horizontal flying mode, horizontal flying mode, horizontal to hover flying mode for ease of implementation of linear control design techniques. The controllers are designed based on an H∞ loop shaping procedure and the results are verified on the actual nonlinear model for the stability of the closed loop system about hover flying, hover to horizontal transition flying, horizontal flying, horizontal to hover transition flying. An experiment is conducted to study the dynamics of the motor by recording the PWM input to the electronic speed controller as input and the rotational speed of the motor as output. A theoretical study is also done to study the thrust generated by the propellers for lift, slipstream velocity analysis, torques acting on the system for various thrust profiles.

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Date Created
  • 2018

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How to Think About Resilient Infrastructure Systems

Description

Resilience is emerging as the preferred way to improve the protection of infrastructure systems beyond established risk management practices. Massive damages experienced during tragedies like Hurricane Katrina showed that risk

Resilience is emerging as the preferred way to improve the protection of infrastructure systems beyond established risk management practices. Massive damages experienced during tragedies like Hurricane Katrina showed that risk analysis is incapable to prevent unforeseen infrastructure failures and shifted expert focus towards resilience to absorb and recover from adverse events. Recent, exponential growth in research is now producing consensus on how to think about infrastructure resilience centered on definitions and models from influential organizations like the US National Academy of Sciences. Despite widespread efforts, massive infrastructure failures in 2017 demonstrate that resilience is still not working, raising the question: Are the ways people think about resilience producing resilient infrastructure systems?

This dissertation argues that established thinking harbors misconceptions about infrastructure systems that diminish attempts to improve their resilience. Widespread efforts based on the current canon focus on improving data analytics, establishing resilience goals, reducing failure probabilities, and measuring cascading losses. Unfortunately, none of these pursuits change the resilience of an infrastructure system, because none of them result in knowledge about how data is used, goals are set, or failures occur. Through the examination of each misconception, this dissertation results in practical, new approaches for infrastructure systems to respond to unforeseen failures via sensing, adapting, and anticipating processes. Specifically, infrastructure resilience is improved by sensing when data analytics include the modeler-in-the-loop, adapting to stress contexts by switching between multiple resilience strategies, and anticipating crisis coordination activities prior to experiencing a failure.

Overall, results demonstrate that current resilience thinking needs to change because it does not differentiate resilience from risk. The majority of research thinks resilience is a property that a system has, like a noun, when resilience is really an action a system does, like a verb. Treating resilience as a noun only strengthens commitment to risk-based practices that do not protect infrastructure from unknown events. Instead, switching to thinking about resilience as a verb overcomes prevalent misconceptions about data, goals, systems, and failures, and may bring a necessary, radical change to the way infrastructure is protected in the future.

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Date Created
  • 2018

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From Design Principles to Principles of Design: Resolving Wicked Problems in Coupled Infrastructure Systems Involving Common-Pool Resources

Description

Design is a fundamental human activity through which we attempt to navigate and manipulate the world around us for our survival, pleasure, and benefit. As human society has evolved, so

Design is a fundamental human activity through which we attempt to navigate and manipulate the world around us for our survival, pleasure, and benefit. As human society has evolved, so too has the complexity and impact of our design activities on the environment. Now clearly intertwined as a complex social-ecological system at the global scale, we struggle in our ability to understand, design, implement, and manage solutions to complex global issues such as climate change, water scarcity, food security, and natural disasters. Some have asserted that this is because complex adaptive systems, like these, are moving targets that are only partially designed and partially emergent and self-organizing. Furthermore, these types of systems are difficult to understand and control due to the inherent dynamics of "wicked problems", such as: uncertainty, social dilemmas, inequities, and trade-offs involving multiple feedback loops that sometimes cause both the problems and their potential solutions to shift and evolve together. These problems do not, however, negate our collective need to effectively design, produce, and implement strategies that allow us to appropriate, distribute, manage and sustain the resources on which we depend. Design, however, is not well understood in the context of complex adaptive systems involving common-pool resources. In addition, the relationship between our attempts at control and performance at the system-level over time is not well understood either. This research contributes to our understanding of design in common-pool resource systems by using a multi-methods approach to investigate longitudinal data on an innovative participatory design intervention implemented in nineteen small-scale, farmer-managed irrigation systems in the Indrawati River Basin of Nepal over the last three decades. The intervention was intended as an experiment in using participatory planning, design and construction processes to increase food security and strengthen the self-sufficiency and self-governing capacity of resource user groups within the poorest district in Nepal. This work is the first time that theories of participatory design-processes have been empirically tested against longitudinal data on a number of small-scale, locally managed common-pool resource systems. It clarifies and helps to develop a theory of design in this setting for both scientific and practical purposes.

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Date Created
  • 2018

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Model predictive control for resilient operation of hybrid microgrids

Description

This dissertation develops advanced controls for distributed energy systems and evaluates performance on technical and economic benefits. Microgrids and thermal systems are of primary focus with applications shown for residential,

This dissertation develops advanced controls for distributed energy systems and evaluates performance on technical and economic benefits. Microgrids and thermal systems are of primary focus with applications shown for residential, commercial, and military applications that have differing equipment, rate structures, and objectives. Controls development for residential energy heating and cooling systems implement adaptive precooling strategies and thermal energy storage, with comparisons made of each approach separately and then together with precooling and thermal energy storage. Case studies show on-peak demand and annual energy related expenses can be reduced by up to 75.6% and 23.5%, respectively, for a Building America B10 Benchmark home in Phoenix Arizona, Los Angeles California, and Kona Hawaii. Microgrids for commercial applications follow after with increased complexity. Three control methods are developed and compared including a baseline logic-based control, model predictive control, and model predictive control with ancillary service control algorithms. Case studies show that a microgrid consisting of 326 kW solar PV, 634 kW/ 634 kWh battery, and a 350 kW diesel generator can reduce on-peak demand and annual energy related expenses by 82.2% and 44.1%, respectively. Findings also show that employing a model predictive control algorithm with ancillary services can reduce operating expenses by 23.5% when compared to a logic-based algorithm. Microgrid evaluation continues with an investigation of off-grid operation and resilience for military applications. A statistical model is developed to evaluate the survivability (i.e. probability to meet critical load during an islanding event) to serve critical load out to 7 days of grid outage. Case studies compare the resilience of a generator-only microgrid consisting of 5,250 kW in generators and hybrid microgrid consisting of 2,250 kW generators, 3,450 kW / 13,800 kWh storage, and 16,479 kW solar photovoltaics. Findings show that the hybrid microgrid improves survivability by 10.0% and decreases fuel consumption by 47.8% over a 168-hour islanding event when compared to a generator-only microgrid under nominal conditions. Findings in this dissertation can increase the adoption of reliable, low cost, and low carbon distributed energy systems by improving the operational capabilities and economic benefits to a variety of customers and utilities.

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Date Created
  • 2019

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Inflatable parabolic reflectors for small satellite communication

Description

CubeSats offer a compelling pathway towards lowering the cost of interplanetary exploration missions thanks to their low mass and volume. This has been possible due to miniaturization of electronics

CubeSats offer a compelling pathway towards lowering the cost of interplanetary exploration missions thanks to their low mass and volume. This has been possible due to miniaturization of electronics and sensors and increased efficiency of photovoltaics. Interplanetary communication using radio signals requires large parabolic antennas on the spacecraft and this often exceeds the total volume of CubeSat spacecraft. Mechanical deployable antennas have been proposed that would unfurl to form a large parabolic dish. These antennas much like an umbrella has many mechanical moving parts, are complex and are prone to jamming. An alternative are inflatables, due to their tenfold savings in mass, large surface area and very high packing efficiency of 20:1. The present work describes the process of designing and building inflatable parabolic reflectors for small satellite radio communications in the X band.

Tests show these inflatable reflectors to provide significantly higher gain characteristics as compared to conventional antennas. This would lead to much higher data rates from low earth orbits and would provide enabling communication capabilities for small satellites in deeper space. This technology is critical to lowering costs of small satellites while enhancing their capabilities.

Principle design challenges with inflatable membranes are maintaining accurate desired shape, reliable deployment mechanism and outer space environment protection. The present work tackles each of the mentioned challenges and provides an

understanding towards future work. In the course of our experimentation we have been able to address these challenges using building techniques that evolved out of a matured understanding of the inflation process.

Our design is based on low cost chemical sublimates as inflation substances that use a simple mechanism for inflation. To improve the reliability of the inflated shape, we use UV radiation hardened polymer support structures. The novelty of the design lies in its simplicity, low cost and high reliability. The design and development work provides an understanding towards extending these concepts to much larger deployable structures such as solar sails, inflatable truss structures for orbit servicing and large surface area inflatables for deceleration from hypersonic speeds when re-entering the atmosphere.

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Date Created
  • 2015

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Synchrony: biometric indication of team cognition

Description

The goal of this experiment is to observe the relation between synchrony and performance in 3-person teams in a simulated Army medic training environment (i.e., Monitoring Extracting and Decoding Indicators

The goal of this experiment is to observe the relation between synchrony and performance in 3-person teams in a simulated Army medic training environment (i.e., Monitoring Extracting and Decoding Indicators of Cognitive workload: MEDIC). The cardiac measure Interbeat-Interval (IBI) was monitored during a physically oriented, and a cognitively oriented task. IBI was measured using NIRS (Near-Infrared Spectrology), and performance was measured using a team task score during a balance board and puzzle task. Synchrony has not previously been monitored across completely different tasks in the same experiment. I hypothesize that teams with high synchrony will show high performance on both tasks. Although no significant results were discovered by the correlational analysis, a trend was revealed that suggests there is a positive relationship between synchrony and performance. This study has contributed to the literature by monitoring physiological measures in a simulated team training environment, making suggestions for future research.

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Date Created
  • 2016

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Self-organizing Coordination of Multi-Agent Microgrid Networks

Description

This work introduces self-organizing techniques to reduce the complexity and burden of coordinating distributed energy resources (DERs) and microgrids that are rapidly increasing in scale globally. Technical and financial evaluations

This work introduces self-organizing techniques to reduce the complexity and burden of coordinating distributed energy resources (DERs) and microgrids that are rapidly increasing in scale globally. Technical and financial evaluations completed for power customers and for utilities identify how disruptions are occurring in conventional energy business models. Analyses completed for Chicago, Seattle, and Phoenix demonstrate site-specific and generalizable findings. Results indicate that net metering had a significant effect on the optimal amount of solar photovoltaics (PV) for households to install and how utilities could recover lost revenue through increasing energy rates or monthly fees. System-wide ramp rate requirements also increased as solar PV penetration increased. These issues are resolved using a generalizable, scalable transactive energy framework for microgrids to enable coordination and automation of DERs and microgrids to ensure cost effective use of energy for all stakeholders. This technique is demonstrated on a 3-node and 9-node network of microgrid nodes with various amounts of load, solar, and storage. Results found that enabling trading could achieve cost savings for all individual nodes and for the network up to 5.4%. Trading behaviors are expressed using an exponential valuation curve that quantifies the reputation of trading partners using historical interactions between nodes for compatibility, familiarity, and acceptance of trades. The same 9-node network configuration is used with varying levels of connectivity, resulting in up to 71% cost savings for individual nodes and up to 13% cost savings for the network as a whole. The effect of a trading fee is also explored to understand how electricity utilities may gain revenue from electricity traded directly between customers. If a utility imposed a trading fee to recoup lost revenue then trading is financially infeasible for agents, but could be feasible if only trying to recoup cost of distribution charges. These scientific findings conclude with a brief discussion of physical deployment opportunities.

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Date Created
  • 2019

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Creating Social Value of Energy at the Grassroots: Investigating the Energy-Poverty Nexus and Co-Producing Solutions for Energy Thriving

Description

Energy projects have the potential to provide critical services for human well-being and help eradicate poverty. However, too many projects fail because their approach oversimplifies the problem to energy poverty:

Energy projects have the potential to provide critical services for human well-being and help eradicate poverty. However, too many projects fail because their approach oversimplifies the problem to energy poverty: viewing it as a narrow problem of access to energy services and technologies. This thesis presents an alternative paradigm for energy project development, grounded in theories of socio-energy systems, recognizing that energy and poverty coexist as a social, economic, and technological problem.

First, it shows that social, economic, and energy insecurity creates a complex energy-poverty nexus, undermining equitable, fair, and sustainable energy futures in marginalized communities. Indirect and access-based measures of energy poverty are a mismatch for the complexity of the energy-poverty nexus. The thesis, using the concept of social value of energy, develops a methodology for systematically mapping benefits, burdens and externalities of the energy system, illustrated using empirical investigations in communities in Nepal, India, Brazil, and Philippines. The thesis argues that key determinants of the energy-poverty nexus are the functional and economic capabilities of users, stressors and resulting thresholds of capabilities characterizing the energy and poverty relationship. It proposes ‘energy thriving’ as an alternative standard for evaluating project outcomes, requiring energy systems to not only remedy human well-being deficits but create enabling conditions for discovering higher forms of well-being.

Second, a novel, experimental approach to sustainability interventions is developed, to improve the outcomes of energy projects. The thesis presents results from a test bed for community sustainability interventions established in the village of Rio Claro in Brazil, to test innovative project design strategies and develop a primer for co-producing sustainable solutions. The Sustainable Rio Claro 2020 initiative served as a longitudinal experiment in participatory collective action for sustainable futures.

Finally, results are discussed from a collaborative project with grassroots practitioners to understand the energy-poverty nexus, map the social value of energy and develop energy thriving solutions. Partnering with local private and non-profit organizations in Uganda, Bolivia, Nepal and Philippines, the project evaluated and refined methods for designing and implementing innovative energy projects using the theoretical ideas developed in the thesis, subsequently developing a practitioner toolkit for the purpose.

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Created

Date Created
  • 2020