A plm implementation for aerospace systems engineering-conceptual rotorcraft design

The thesis will discuss the Systems Engineering phase of an original Conceptual Design Engineering Methodology for Aerospace Engineering-Vehicle Synthesis. This iterative phase is shown to benefit from digitization of Integrated Product&Process Design (IPPD) activities, through the application of Product Lifecycle Management (PLM) technologies. Requirements analysis through the use of Quality Function Deployment (QFD) and 7 MaP tools is explored as an illustration. A "Requirements Data Manager" (RDM) is used to show the ability to reduce the time and cost to design for both new and legacy/derivative designs. Here the COTS tool Teamcenter Systems Engineering (TCSE) is used as the RDM. The utility of the new methodology is explored through consideration of a legacy RFP based vehicle design proposal and associated aerospace engineering. The 2001 American Helicopter Society (AHS) 18th Student Design Competition RFP is considered as a starting point for the Systems Engineering phase. A Conceptual Design Engineering activity was conducted in 2000/2001 by Graduate students (including the author) in Rotorcraft Engineering at the Daniel Guggenheim School of Aerospace Engineering at the Georgia Institute of Technology, Atlanta GA. This resulted in the "Kingfisher" vehicle design, an advanced search and rescue rotorcraft capable of performing the "Perfect Storm" mission, from the movie of the same name. The associated requirements, architectures, and work breakdown structure data sets for the Kingfisher are used to relate the capabilities of the proposed Integrated Digital Environment (IDE). The IDE is discussed as a repository for legacy knowledge capture, management, and design template creation. A primary thesis theme is to promote the automation of the up-front conceptual definition of complex systems, specifically aerospace vehicles, while anticipating downstream preliminary and full spectrum lifecycle design activities. The thesis forms a basis for additional discussions of PLM tool integration across the engineering, manufacturing, MRO and EOL lifecycle phases to support business management processes.M.S.Committee Chair: Schrage, Daniel P.; Committee Member: Costello, Mark; Committee Member: Wilhite, Alan, W

Automated Network Exploitation Utilizing Bayesian Decision Networks

Computer Network Exploitation (CNE) is the process of using tactics and techniques to penetrate computer systems and networks in order to achieve desired effects. It is currently a manual process requiring significant experience and time that are in limited supply. This thesis presents the Automated Network Discovery and Exploitation System (ANDES) which demonstrates that it is feasible to automate the CNE process. The uniqueness of ANDES is the use of Bayesian decision networks to represent the CNE domain and subject matter expert knowledge. ANDES conducts multiple execution cycles, which build upon previous action results. Cycles begin by modeling the current belief state using Bayesian decision networks. ANDES uses these networks to select and execute an expected best action. Observed results are used to update the systems current belief state before the next cycle begins. ANDES was tested in a live-execution event, taking place within a virtual network environment. ANDES successfully performed a series of information gathering and remote exploit actions, across multiple network hosts to gain access to the target

Demonstration of Universal Parametric Entangling Gates on a Multi-Qubit Lattice

We show that parametric coupling techniques can be used to generate selective entangling interactions for multi-qubit processors. By inducing coherent population exchange between adjacent qubits under frequency modulation, we implement a universal gateset for a linear array of four superconducting qubits. An average process fidelity of $\mathcal{F}=93\%$ is estimated for three two-qubit gates via quantum process tomography. We establish the suitability of these techniques for computation by preparing a four-qubit maximally entangled state and comparing the estimated state fidelity against the expected performance of the individual entangling gates. In addition, we prepare an eight-qubit register in all possible bitstring permutations and monitor the fidelity of a two-qubit gate across one pair of these qubits. Across all such permutations, an average fidelity of $\mathcal{F}=91.6\pm2.6\%$ is observed. These results thus offer a path to a scalable architecture with high selectivity and low crosstalk

Terrestrial laser scanning for building information modelling (BIM) development and application

Terrestrial laser scanners (TLS) offer the ability to collect highly accurate high density 3D point clouds. This dissertation looks into errors evident in TLS scans, such as edge effects, ranging errors, noise, and effect of surface reflectivity with the project scanner (which is a Trimble TX5). It then goes on to analyse the magnitude of these errors and ultimately concludes that the TLS is a suitable tool for use in Building Information Modelling (BIM) It then analyses the suitability of the Revit add-on called Scan To Bim for use in creating Revit elements from TLS point clouds, and concludes that care needs to be taken, and identifies more research is required to determine accurate methods. It also highlights the difficulties inherent in creating complex building elements such as columns, windows, doors, and ducting which are many and varied

Synchrotron Radiation Induced X-Ray Microanalysis: A Realistic Alternative for Electron- and Ion-Beam Microscopy?

Synchrotron radiation induced X-ray micro fluorescence analysis (μ-SRXRF) is compared with more conventional microanalytical techniques such as secondary ion microscopy (SIMS) and electron probe X-ray microanalysis (EPXMA) for two typical microanalytical applications. μ-SRXRF and EPXMA are employed for the analysis of individual particles, showing the complementary character of both techniques. By means of element mapping of trace constituents in a heterogeneous feldspar material, the strong and weak points of μ-SRXRF in comparison to EPXMA and SIMS are illustrated. The most striking difference between μ-SRXRF and the other two microanalytical methods is the ability of SRXRF to probe deep into the investigated material, whereas SIMS and EPXMA only investigate the upper surface of the material. The possibilities of μ-SRXRF using radiation from bending magnets of third generation synchrotron rings are briefly discussed. μ-SRXRF is considered to be a valuable method for the analysis of major, minor and trace elements which can be used profitably m parallel with electron-and ion-beam methods

Vacuum heat treatments of titanium porous structures

Additive manufacturing (AM) of Ti-6Al-4V enables rapid fabrication of complex parts, including porous lattices which are of interest for aerospace, automotive, or biomedical applications, however currently the fatigue resistance of these materials is a critical limitation. Engineering the alloy microstructure provides a promising method for increasing fatigue strength, but conventional heat treatment procedures are known to produce atypical results for AM and porous samples, and must therefore be optimised for these materials. Using vacuum heat treatment, microstructures comparable to those observed for conventional wrought and heat treated alloys were achieved with porous AM Ti-6Al-4V. Fine lamellar microstructures were produced using sub-transus heat treatment at 920 °C, while coarse lamellar microstructures were produced using super-transus heat treatment at 1050 °C or 1200 °C. Increasing the heat treatment temperature increased the elastic modulus from 2552 ± 22 MPa to a maximum of 2968 ± 45 MPa, due to strut sintering increasing the effective strut thickness, and removal of prior β-grain orientation. Heat treatment eliminated the brittle α’ martensite phase in favour of an α + β mixture, where the phase boundaries and β-phase provide greater resistance to crack propagation. Super-transus heat treatments increased the α-lath size which typically reduces crack propagation resistance, however strut sintering reduced surface crack initiation sites, increasing the fatigue strength by 75% from 4.86 MPa for the as-built material to a maximum of 8.51 MPa after 1200 °C heat treatment. This work demonstrates that vacuum heat treatment is effective at tuning the micro- and macro-structure of porous AM Ti-6Al-4V, thereby improving the crucial fatigue resistance

Risk-Based Safety Scoping of Adversary-Centric Security Testing on Operational Technology

Due to the recent increase in cyber attacks targeting Critical National Infrastructure, governments and organisations alike have invested considerably into improving the security of their underlying infrastructure, commonly known as Operational Technology (OT). The use of adversary-centric security tests such as vulnerability assessments, penetration tests and red team engagements has gained significant traction due to these engagements' goal to emulate threat actors in preparation for genuine cyber attacks. Challenges arise, however, when performing security tests on these as the nature of OT results in additional safety and operational risk needing to be considered. This paper proposes a framework for incorporating the assessment of safety and operational risks within an overall scoping methodology for adversary-centric security testing in OT environments. Within this framework, we also propose a hybrid testing model derived from the Purdue Enterprise Reference Architecture and the Defense in Depth model to identify and quantify safety and operational risk at a per-layer level, separating high and low-risk layers and being subsequently used for defining rules of engagement. As a result, this framework can aid vendors and clients in appropriately scoping adversary-centric security tests so that depth-of-testing is maximised while minimising the risk to safety and to the operational process. The framework is then evaluated through a qualitative study involving industry experts, confirming the framework's validity for implementation in practice

Artificial Intelligence and Machine Learning for Quantum Technologies

In recent years, the dramatic progress in machine learning has begun to impact many areas of science and technology significantly. In the present perspective article, we explore how quantum technologies are benefiting from this revolution. We showcase in illustrative examples how scientists in the past few years have started to use machine learning and more broadly methods of artificial intelligence to analyze quantum measurements, estimate the parameters of quantum devices, discover new quantum experimental setups, protocols, and feedback strategies, and generally improve aspects of quantum computing, quantum communication, and quantum simulation. We highlight open challenges and future possibilities and conclude with some speculative visions for the next decade

The Intellectual Property Implications of the Development of Industrial 3D Printing

This commissioned project/report for the European Commission explores the IP Implications of the Development of Industrial 3D Printing from a European perspective. The report aims to enhance the European business sector and foster innovation. Through a legal and empirical analysis, involving qualitative data drawn from interviews with 41 industry stakeholders, the findings from the project demonstrates the areas which needed to be addressed – and resolved. Being the first large-scale empirical project of its kind, the report delves into the heart of EU IP regulation and makes policy recommendations for all aspects of IP whilst also providing recommendations for industry. The report was authored by a team of national and international researchers including a team of academics and practitioners and consisted of Lead Author, Dinusha Mendis together with partners from UK (Julie Robson, Phill Dickinson), Austria (Maria del Carmen Calatrava-Moreno and Alfred Radeur); Finland (Rosa Ballardini); and Germany (Jan Nordemann and Hans Brorsen)