Systems Engineering Commons^™

High-Level Requirements For Conceptual Design Of Bridge Deflection Measurement System Using Model-Based Systems Engineering, Mariana Villalabeitia Arenas

Theses and Dissertations

Bridges are essential in the infrastructure transportation system. Repairs and maintenance are the key activities to keep them safe for use. Over the years, the evolution of technology has been applied to improve the way bridges are designed, built, monitored, inspected, and repaired. Nevertheless, there is still a gap between the research efforts and the application of this knowledge in the practical field of bridge inspections. Model-based Systems Engineering is a formalized methodology in the system design that is centered around the model throughout all the life cycle stages of a system, supporting the requirements, design, analysis, verification, and validation …

Causal Modeling Framework For Nuclear Power Plant Licensing Process, Lauren Kimberly Kiser

Theses and Dissertations

Interests in clean energy revived the nuclear power industry. For the first time in decades, innovative technologies and plant designs are being considered by regulatory agencies. This dissertation explores a Bayesian Network and AHP approach to causal modeling of the Combined License review process for new nuclear power plants (NPP). Historically lengthy and expensive, NPP licensing is critical to ensuring safe operation of the plants. With this comes a high standard for applicants to reach that can result in multiple revision cycles and long review times. New plant designs and fluctuating public support lead to a complex and dynamic series …

Modeling The Impact Of Scheduling Risks On Multi-Team Agile Projects, Bria Marie Booth

Theses and Dissertations

Agile project management allows for a quick response to a changing project environment. This opens possible avenues for new opportunities, but also may expose ongoing projects to previously unknown or unexpected threats. Risks must be continuously monitored as a product is worked on to avoid lost potential. This paper will propose a discrete event simulation model that multi-team projects may use to predict the impact to the project’s schedule. Using discrete event simulation early in the project’s planning cycle offers a greater understanding of the possible or probable impact of risks on the schedule. This would help to prepare project …

Geometric Inference In Machine Learning: Applications Of Fisher Information For Model Selection And Other Statistical Applications, Trevor Herntier

Theses and Dissertations

We consider the problem of model selection using the Minimum Description Length (MDL) criterion for distributions with parameters on the hypersphere. Model selection algorithms aim to find a compromise between goodness of fit and model complexity. Variables often considered for complexity penalties involve number of parameters, sample size and shape of the parameter space, with the penalty term often referred to as stochastic complexity. Because Laplace approximation techniques yield inaccurate results for curved spaces, existing criteria incorrectly penalize complexity. We demonstrate how the use of a constrained Laplace approximation on the hypersphere yields a novel complexity measure that more accurately …

Towards Developing A Digital Twin Implementation Framework For Manufacturing Systems, Jonatan H. Loaiza

Theses and Dissertations

This research studies the implementation of digital twins in manufacturing systems. Digital transformation is relevant due to changing manufacturing techniques and user demands. It brings new business opportunities, changes organizations, and allows factories to compete in the digital era. Nevertheless, digital transformation presents many uncertainties that could bring problems to a manufacturing system. Some potential problems are loss of data, cybersecurity threats, unpredictable behavior, and so on. For instance, there are doubts about how to integrate the physical and virtual spaces. Digital twin (DT) is a modern technology that can enable the digital transformation of manufacturing companies. DT works by …

A Framework For The Verification And Validation Of Artificial Intelligence Machine Learning Systems, Swala B. Burns

Theses and Dissertations

An effective verification and validation (V&V) process framework for the white-box and black-box testing of artificial intelligence (AI) machine learning (ML) systems is not readily available. This research uses grounded theory to develop a framework that leads to the most effective and informative white-box and black-box methods for the V&V of AI ML systems. Verification of the system ensures that the system adheres to the requirements and specifications developed and given by the major stakeholders, while validation confirms that the system properly performs with representative users in the intended environment and does not perform in an unexpected manner. Beginning with …

Technical Report On: Anchoring Sagittal Plane Templates In A Spatial Quadruped, Timothy M. Greco, D. E. Koditschek

Technical Reports (ESE)

This technical report provides a more thorough treatment of the proofs and derivations in the authors' paper "Anchoring Sagittal Plane Templates in a Spatial Quadruped." The description of the anchoring controller is reproduced here without abridgement, and additional appendices provide a clearer account of the implementation details.

Anchoring Sagittal Plane Templates In A Spatial Quadruped, Timothy M. Greco, Daniel E. Koditschek

Departmental Papers (ESE)

This paper introduces a new controller that stabilizes the motion of a spatial quadruped around sagittal-plane templates. It enables highly dynamic gaits and transitional maneuvers formed from parallel and sequential compositions of such planar templates in settings that require significant out-of-plane reactivity. The controller admits formal guarantees of stability with some modest assumptions. Experimental results validate the reliable execution of those planar template-based maneuvers, even in the face of large lateral, yaw, and roll incurring disturbances. This spatial anchor, fixed in parallel composition with a variety of different parallel and sequential compositions of sagittal plane templates, illustrates the robust portability …

Ads-B Classification Using Multivariate Long Short-Term Memory–Fully Convolutional Networks And Data Reduction Techniques, Sarah Bolton, Richard Dill, Michael R. Grimaila, Douglas Hodson

Faculty Publications

Researchers typically increase training data to improve neural net predictive capabilities, but this method is infeasible when data or compute resources are limited. This paper extends previous research that used long short-term memory–fully convolutional networks to identify aircraft engine types from publicly available automatic dependent surveillance-broadcast (ADS-B) data. This research designs two experiments that vary the amount of training data samples and input features to determine the impact on the predictive power of the ADS-B classification model. The first experiment varies the number of training data observations from a limited feature set and results in 83.9% accuracy (within 10% of …

Extended Version Of Stability Of A Groucho-Style Bounding Run In The Sagittal Plane, Jeff Duperret, D. E. Koditschek

Technical Reports (ESE)

This paper develops a three degree-of-freedom sagittal-plane hybrid dynamical systems model of a Groucho-style bounding quadrupedal run. Simple within-stance controls using a modular architecture yield a closed form expression for a family of hybrid limit cycles that represent bounding behavior over a range of user-selected fore-aft speeds as a function of the model's kinematic and dynamical parameters. Controls acting on the hybrid transitions are structured so as to achieve a cascade composition of in-place bounding driving the fore-aft degree of freedom, thereby decoupling the linearized dynamics of an approximation to the stride map. Careful selection of the feedback channels used …

Digitization And Automation Of Rapidly Changing Business Processes In Small And Medium-Sized Organizations, Syed Waqas Ahmed

MSCS Research Projects/Theses

Enterprise Resource Planning Systems (ERPs) are often seen as the backbones of the business industry. ERPs such as SAP and other modern solutions are providing a paperless and often automated environment within organizations for the past few decades. However, with the rise of startups and agile methodologies, business processes are now being rapidly introduced in these young companies. ERPs and other solutions are unable to keep up with the rapid introduction of new business processes and updates made to older processes. To meet these requirements, the ERPs are supported by paper-based forms or other alternative business processes. The inability of …

Twisting Spine Or Rigid Torso: Exploring Quadrupedal Morphology Via Trajectory Optimization, J. Diego Caporale, Zeyuan Feng, Shane Rozen-Levy, Aja Mia Carter, Daniel E. Koditschek

Departmental Papers (ESE)

Modern legged robot morphologies assign most of their actuated degrees of freedom (DoF’s) to the limbs and designs continue to converge to twelve DoF quadrupeds with three actuators per leg and a rigid torso often modeled as a Single Rigid Body (SRB). This is in contrast to the animal kingdom, which provides tantalizing hints that core actuation of a jointed torso confers substantial benefit for efficient agility. Unfortunately, the limited specific power of available actuators continues to hamper roboticists’ efforts to capitalize on this bio-inspiration. This paper presents the initial steps in a comparative study of the costs and benefits …

Like You Search, Gipson Bachman

LMU/LLS Theses and Dissertations

As consumers continue to make their purchases solely online without visiting brick-and-mortar stores, they increasingly look for ways to “touch, feel and try on” products without actually doing so. We believe social media influencers provide a way to do this, with the influencers themselves acting as “stand-ins” for consumers in their place. Finding influencers that look like you in 2022 sounds like it would be easy, but it isn’t. Until now.

LIKE YOU aims to answer this gap in the market by creating a proprietary search engine that, through answering a few questions, recommends a list of influencers that can …

Fugacity-Based Lattice Boltzmann Method For Multicomponent Multiphase Systems, Muzammil Soomro, Luis F. Ayala, Cheng Peng, Orlando M. Ayala

Engineering Technology Faculty Publications

The free-energy model can extend the lattice Boltzmann method to multiphase systems. However, there is a lack of models capable of simulating multicomponent multiphase fluids with partial miscibility. In addition, existing models cannot be generalized to honor thermodynamic information provided by any multicomponent equation of state of choice. In this paper, we introduce a free-energy lattice Boltzmann model where the forcing term is determined by the fugacity of the species, the thermodynamic property that connects species partial pressure to chemical potential calculations. By doing so, we are able to carry out multicomponent multiphase simulations of partially miscible fluids and generalize …

Model Based Systems Engineering Approaches To Chemicals And Materials Manufacturing, Quang Le

Theses and Dissertations

Model-based systems engineering (MBSE) is part of a long-term trend toward model-centric approaches adopted by many engineering disciplines. This work establishes the need for an MBSE approach by reviewing the importance, complexity, and vulnerability of the U.S. chemical supply chains. The origins, work processes, modeling approaches, and supporting tools of the systems engineering discipline (SE) are discussed, along with the limitations of the current Process Systems Engineering (PSE) framework. The case is made for MBSE as a more generalizable and robust approach. Systems modeling strategies for MBSE are introduced, as well as a novel MBSE method that supports the automation …

Development Of Directed Randomization For Discussing A Minimal Security Architecture, Henrique Oyama, Dominic Messina, Keshav Kasturi Rangan, Akkarakaran Francis Leonard, Kip Nieman, Helen Durand, Katie Tyrrell, Katrina Hinzman, Michael Williamson

Chemical Engineering and Materials Science Faculty Research Publications

Strategies for mitigating the impacts of cyberattacks on control systems using a control-oriented perspective have become of greater interest in recent years. Our group has contributed to this trend by developing several methods for detecting cyberattacks on process sensors, actuators, or both sensors and actuators simultaneously using an advanced optimization-based control strategy known as Lyapunov-based economic model predictive control (LEMPC). However, each technique comes with benefits and limitations, both with respect to one another and with respect to traditional information technology and computer science-type approaches to cybersecurity. An important question to ask, therefore, is what the goal should be of …

Investigating Applications Of Deep Learning For Diagnosis Of Post Traumatic Elbow Disease, Hugh James

McKelvey School of Engineering Theses & Dissertations

Traumatic events such as dislocation, breaks, and arthritis of musculoskeletal joints can cause the development of post-traumatic joint contracture (PTJC). Clinically, noninvasive techniques such as Magnetic Resonance Imaging (MRI) scans are used to analyze the disease. Such procedures require a patient to sit sedentary for long periods of time and can be expensive as well. Additionally, years of practice and experience are required for clinicians to accurately recognize the diseased anterior capsule region and make an accurate diagnosis. Manual tracing of the anterior capsule is done to help with diagnosis but is subjective and timely. As a result, there is …

Practical Requirements Elicitation In Modern Product Development: A Multi-Case Study In Discontinuous Innovation, Michael King

Theses and Dissertations

Practical modern product development, specifically rapid, lean efforts to create new disrupting or specialized products, face constraints that require modified requirements elicitation (RE) techniques. Requirements elicitation conventions have not been updated to address the challenges of these approaches, and industry practitioners lack the tools to select the most efficient techniques. This study examines the RE approaches performed by three resource-limited teams conducting discontinuous new product development through a multi-case study to identify gaps between the literature and practice, with suggestions to fill them. Our findings suggest modern RE practices and challenges closely reflect those found by studies on RE in …

Context-Aware Collaborative Neuro-Symbolic Inference In Internet Of Battlefield Things, Tarek Abdelzaher, Nathaniel D. Bastian, Susmit Jha, Lance Kaplan, Mani Srivastava, Venugopal Veeravalli

ACI Journal Articles

IoBTs must feature collaborative, context-aware, multi-modal fusion for real-time, robust decision-making in adversarial environments. The integration of machine learning (ML) models into IoBTs has been successful at solving these problems at a small scale (e.g., AiTR), but state-of-the-art ML models grow exponentially with increasing temporal and spatial scale of modeled phenomena, and can thus become brittle, untrustworthy, and vulnerable when interpreting large-scale tactical edge data. To address this challenge, we need to develop principles and methodologies for uncertainty-quantified neuro-symbolic ML, where learning and inference exploit symbolic knowledge and reasoning, in addition to, multi-modal and multi-vantage sensor data. The approach features …

Report On The Icra’22 Workshop On Lethal Autonomous Weapons, Daniel E. Koditschek, Lisa J. Miracchi, Jesse Hamilton

Technical Reports (ESE)

No abstract provided.