Mechanical Engineering Commons^™

Unveiling The Hidden Threat: How Wireless Networks Fuel Serious Cyber Attacks, Ibtesam Jomaa Hawi

Al-Esraa University College Journal for Engineering Sciences

The spread of wireless networks has led to an increase in serious cyber attacks due to their weak architecture. This article focuses on reevaluating cybersecurity in wireless network technology by integrating statistical information detection methods and artificial intelligence (AI) algorithms. To construct a wireless networking scenario that accurately reflects real-life conditions, we created a data fabrication that included four pre-existing anomalies as well as four newly introduced anomalies. The synthetic dataset created from these generation processes contains 20 thousand distinguishable values, which are later divided into training and validation sets. Using the strategy described before, we began to analyze the …

Development Of A Rule-Based Monitoring System For Autonomous Heavy Equipment Safety, Amirpooya Shirazi

Department of Construction Engineering and Management: Dissertations, Theses, and Student Research

Roadway construction work zones are constantly exposed to interactions among construction equipment, workers, and vehicles. Furthermore, ensuring safety in these areas is considered a challenging task due to the complexity of the environment. As shown in the rising trend of fatal accidents in roadway work zones, current OSHA regulations in construction safety are insufficient in effectively detecting unsafe situations and mitigating the risks. Furthermore, best practices, such as internal traffic control planning (ITCP), exhibit critical limitations requiring continuous monitoring of active work zones as well as adjustments to the site coordination plans due to the dynamic nature of work zone …

Digital Twin In Military Ground Vehicles: Design And Predictive Maintenance, Conner W. Eddy

All Theses

Digital twin technology builds upon virtual engineering models, computer simulation, and real-time field data streaming to enable next-generation designs and predictive maintenance. A digital twin is a computer-based high-fidelity collection of models that predicts the performance of dynamic systems per operating cycles, input feature parameters, and data communication from a physical plant. Product Lifecycle Management (PLM) is growing in importance and is central to virtual design processes where the digital twin toolset fits into this emerging architecture. The product design process can be advanced using digital twin resources by eliminating the need for, and cost from, continual physical prototyping, reliability …

Ai-Based Bridge And Road Inspection Framework Using Drones, Hovannes Kulhandjian

Mineta Transportation Institute

There are over 590,000 bridges dispersed across the roadway network that stretches across the United States alone. Each bridge with a length of 20 feet or greater must be inspected at least once every 24 months, according to the Federal Highway Act (FHWA) of 1968. This research developed an artificial intelligence (AI)-based framework for bridge and road inspection using drones with multiple sensors collecting capabilities. It is not sufficient to conduct inspections of bridges and roads using cameras alone, so the research team utilized an infrared (IR) camera along with a high-resolution optical camera. In many instances, the IR camera …

Neuroevolution Application To Collaborative And Heuristics-Based Connected And Autonomous Vehicle Cohort Simulation At Uncontrolled Intersection, Frederic Jacquelin, Jungyun Bae, Bo Chen, Darrell Robinette

Michigan Tech Publications, Part 2

Artificial intelligence is gaining tremendous attractiveness and showing great success in solving various problems, such as simplifying optimal control derivation. This work focuses on the application of Neuroevolution to the control of Connected and Autonomous Vehicle (CAV) cohorts operating at uncontrolled intersections. The proposed method implementation’s simplicity, thanks to the inclusion of heuristics and effective real-time performance are demonstrated. The resulting architecture achieves nearly ideal operating conditions in keeping the average speeds close to the speed limit. It achieves twice as high mean speed throughput as a controlled intersection, hence enabling lower travel time and mitigating energy inefficiencies from stop-and-go …

Patient Movement Monitoring Based On Imu And Deep Learning, Mohsen Sharifi Renani

Electronic Theses and Dissertations

Osteoarthritis (OA) is the leading cause of disability among the aging population in the United States and is frequently treated by replacing deteriorated joints with metal and plastic components. Developing better quantitative measures of movement quality to track patients longitudinally in their own homes would enable personalized treatment plans and hasten the advancement of promising new interventions. Wearable sensors and machine learning used to quantify patient movement could revolutionize the diagnosis and treatment of movement disorders. The purpose of this dissertation was to overcome technical challenges associated with the use of wearable sensors, specifically Inertial Measurement Units (IMUs), as a …

Development Of A Modular Agricultural Robotic Sprayer, Paolo Rommel P. Sanchez

Theses and Dissertations

Precision Agriculture (PA) increases farm productivity, reduces pollution, and minimizes input costs. However, the wide adoption of existing PA technologies for complex field operations, such as spraying, is slow due to high acquisition costs, low adaptability, and slow operating speed. In this study, we designed, built, optimized, and tested a Modular Agrochemical Precision Sprayer (MAPS), a robotic sprayer with an intelligent machine vision system (MVS). Our work focused on identifying and spraying on the targeted plants with low cost, high speed, and high accuracy in a remote, dynamic, and rugged environment. We first researched and benchmarked combinations of one-stage convolutional …

Artificial Intelligence, Controls, And Sensor Fusion For Optimization And Modeling Of Space Missions And Particle Accelerators, Reza Pirayeshshirazinezhad

Mechanical Engineering ETDs

This PhD dissertation is devoted to developing artificial intelligence (AI) applications for space missions and particle accelerators considering constraints on the computational resources. The space mission studied in this research, the Virtual Telescope for X-ray Observations (VTXO), is the mission exploiting 2 6U-CubeSats operating in a precision formation. The goal of the VTXO project is to develop a space-based, X-ray imaging telescope with high angular resolution precision. VTXO space mission is designed and the mission is optimized to increase the performance of the mission. Trajectory optimization with AI, hybrid control, control algorithms, and high performance computing are all used to …

An Artificial Intelligence Approach To Fatigue Crack Length Estimation From Acoustic Emission Waves In Thin Metallic Plates, Joseph Chandler Garrett, Hanfei Mei, Victor Giurgiutiu

Faculty Publications

The acoustic emission (AE) technique has become a well-established method of monitoring structural health over recent years. The sensing and analysis of elastic AE waves, which have involved piezoelectric wafer active sensors (PWAS) and time domain and frequency domain analysis, has proven to be effective in yielding fatigue crack-related information. However, not much research has been performed regarding (i) the correlation between the fatigue crack length and AE signal signatures and (ii) artificial intelligence (AI) methodologies to automate the AE waveform analysis. In this paper, this crack length correlation is investigated along with the development of a novel AE signal …

Emissivity Prediction Of Functionalized Surfaces Using Artificial Intelligence, Greg Acosta, Andrew Reicks, Miguel Moreno, Alireza Borjali, Craig Zuhlke, Mohammad Ghashami

Department of Mechanical and Materials Engineering: Faculty Publications

Tuning surface emissivity has been of great interest in thermal radiation applications, such as thermophotovoltaics and passive radiative cooling. As a low-cost and scalable technique for manufacturing surfaces with desired emissivities, femtosecond laser surface processing (FLSP) has recently drawn enormous attention. Despite the versatility offered by FLSP, there is a knowledge gap in accurately predicting the outcome emissivity prior to fabrication. In this work, we demonstrate the immense advantage of employing artificial intelligence (AI) techniques to predict the emissivity of complex surfaces. For this aim, we used FLSP to fabricate 116 different aluminum samples. A comprehensive dataset was established by …

Predictive Computational Materials Modeling With Machine Learning: Creating The Next Generation Of Atomistic Potential Using Neural Networks, Mashroor Shafat Nitol

Theses and Dissertations

Machine learning techniques using artificial neural networks (ANNs) have proven to be effective tools to rapidly mimic first principles calculations. These tools are capable of sub meV/atom accuracy while operating with linear scaling with respect to the system size. Here novel interatomic potentials are constructed based on the rapid artificial neural network (RANN) formalism. This approach generates precise force fields for various metals that have historically been difficult to describe at the atomic scale. These force fields can be utilized in molecular dynamics simulations to provide new physical insights. The RANN formalism, which is incorporated into a LAMMPS molecular dynamics …

Airfoil Flow Optimized Control With An Upstream Cylinder, Nicole Steiner

Fall Student Research Symposium 2021

The purpose of this research is to optimize the aerodynamic performance of an airfoil with an upstream cylinder by neural network artificial intelligence. The effects of an upstream oscillating cylinder on the aerodynamic performance of an airfoil are also studied. This paper reports the effects oscillating frequency of the cylinder and the Reynolds number on the lift/drag ratio of the airfoil. The frequency has a complicated correlation with the lift/drag ratio, while the Reynolds number is found to have a positive correlation with the lift/drag ratio. The optimized case is found to have a lift/drag ratio of 1.7319, which is …

Real-Time Material State Assessment Of Composites Using Artificial Intelligence And Its Challenges, Muthu Ram Prabhu Elenchezhian

Mechanical and Aerospace Engineering Dissertations

Over several decades of careful experimental investigation and exhaustive development of discrete damage analysis methods including integrated computational mechanics methods, our community knows a great deal about how discrete defects such as matrix cracks and defect growth (e.g. delamination) can be predicted in structural composites. For many practical situations controlled by laminated multiaxial composite structures, the loss of performance and “sudden death” end of life is controlled by defect coupling which becomes a precursor to fracture plane development. These interaction sequences are highly dependent on local details of manufacture, design configurations, and loading for a given application material and influenced …

Human-Robot Interaction For Assistive Robotics, Jiawei Li

Dissertations

This dissertation presents an in-depth study of human-robot interaction (HRI) withapplication to assistive robotics. In various studies, dexterous in-hand manipulation is included, assistive robots for Sit-To-stand (STS) assistance along with the human intention estimation. In Chapter 1, the background and issues of HRI are explicitly discussed. In Chapter 2, the literature review introduces the recent state-of-the-art research on HRI, such as physical Human-Robot Interaction (HRI), robot STS assistance, dexterous in hand manipulation and human intention estimation. In Chapter 3, various models and control algorithms are described in detail. Chapter 4 introduces the research equipment. Chapter 5 presents innovative theories and …

Iso 9001:2015 Risk-Based Thinking: A Framework Using Fuzzy-Support Vector Machine, Ralph Sherwin A. Corpuz

Makara Journal of Technology

Risk-based thinking (RBT) is one of the distinct new features of the International Organization for Standardization 9001:2015. Interestingly, the standard does not prescribe any tools. Hence, organizations are puzzled as to the extent of conformance. Some organizations have adopted formal tools. However, these tools seem insufficient in linking the standard into an evidence-based decision support system. To resolve gaps in RBT implementation, this paper proposes a framework based on fuzzy inference system (FIS) and support vector machine (SVM) to automate risk analysis and evaluation, proposal and verification of action plans, and prediction of the feasibility of risks and opportunities according …

Machine Learning In Manufacturing: Review, Synthesis, And Theoretical Framework, Ajit Sharma, Zhibo Zhang, Rahul Rai

Business Administration Faculty Research Publications

There has been a paradigmatic shift in manufacturing as computing has transitioned from the programmable to the cognitive computing era. In this paper we present a theoretical framework for understanding this paradigmatic shift in manufacturing and the fast evolving role of artificial intelligence. Policy, Strategic and Operational implications are discussed. Implications for the future of strategy and operations in manufacturing are also discussed. Future research directions are presented.

Feasible Form Parameter Design Of Complex Ship Hull Form Geometry, Thomas L. Mcculloch

University of New Orleans Theses and Dissertations

This thesis introduces a new methodology for robust form parameter design of complex hull form geometry via constraint programming, automatic differentiation, interval arithmetic, and truncated hierarchical B- splines. To date, there has been no clearly stated methodology for assuring consistency of general (equality and inequality) constraints across an entire geometric form parameter ship hull design space. In contrast, the method to be given here can be used to produce guaranteed narrowing of the design space, such that infeasible portions are eliminated. Furthermore, we can guarantee that any set of form parameters generated by our method will be self consistent. It …

The Contextable: Building And Testing An Intelligent, Context-Aware Kitchen Table, Daniel Matthew Hoopes

Theses and Dissertations

The purpose of this thesis was to design and evaluate The ContexTable, a context-aware system built into a kitchen table. After establishing the current status of the field of context-aware systems and the hurdles and problems being faced, a functioning prototype system was designed and built. The prototype makes it possible to explore established, untested theory and novel solutions to problems faced in the field.

Design And Design Centers In Engineering Education, Clive L. Dym

All HMC Faculty Publications and Research

This paper is intended to be the opening salvo of the workshop, Computing Futures in Engineering Design (Dym, 1997). Thus, I want to take this privileged moment to ask you to think with me about the role of design in engineering. In particular, I want to reflect upon how design is articulated and how design is taught; about the role of design in engineering education and in the practice of engineering; and about the role that could be played locally and, perhaps, nationally by a center devoted to design education. Because I teach here at Harvey Mudd College (HMC), …

Uses And Applications Of Artificial Intelligence In Manufacturing, Manojkumar H. Desai

Theses

The purpose of the THESIS is to provide engineers and personnels with a overview of the concepts that underline Artificial Intelligence and Expert Systems. Artificial Intelligence is concerned with the developments of theories and techniques required to provide a computational engine with the abilities to perceive, think and act, in an intelligent manner in a complex environment.

Expert system is branch of Artificial Intelligence where the methods of reasoning emulate those of human experts. Artificial Intelligence derives it's power from its ability to represent complex forms of knowledge, some of it common sense, heuristic and symbolic, and the ability to …

Knowledge-Based Support For Management Of Concurrent, Multidisciplinary Design, Raymond E. Levitt, Yan Jin, Clive L. Dym

All HMC Faculty Publications and Research

Artificial intelligence (AI) applications to design have tended to focus on modeling and automating aspects of single discipline design tasks. Relatively little attention has thus far been devoted to representing the kinds of design 'metaknowledge' needed to manage the important interface issues that arise in concurrent design, that is, multidisciplinary design decision-making. This paper provides a view of the process and management of concurrent design and evaluates the potential of two AI approaches—blackboard architectures and co-operative distributed problem-solving (CDPS)—to model and support the concurrent design of complex artifacts. A discussion of the process of multidisciplinary design highlights elements of both …

Issues In The Design And Implementation Of Expert Systems, Clive L. Dym

All HMC Faculty Publications and Research

This article discusses the issues that arise in the design and implementation of expert systems. These issues include: task selection; the stages of development of expert system projects; knowledge acquisition; languages and tools; development and run-time environments; and organizational and institutional issues. The article closes with some speculation about the future development of expert systems.