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Tube bending is a widely used manufacturing process in the aerospace, automotive, and other industries. During tube bending, considerable in-plane distortion and thickness variation occurs. The thickness increases at the intrados (surface of tube in contact with the die) and it reduces at the extrados (outer surface of the tube). In some cases, when the bend die radius is small, wrinkling occurs at the intrados. In industry a mandrel is used to eliminate wrinkling and reduce distortion. However, in the case of a close bend die radius, use of a mandrel should be avoided as bending with the mandrel increases the thinning of the wall at the extrados, which is undesirable in the manufacturing operation. The present research focuses on additional loadings such as axial force and internal pressure which can be used to achieve better shape control and thickness distribution of the tube. Based on plasticity theories, an analytical model is developed to predict cross section distortion and thickness change of tubes under various loading conditions. Results from both the FEA and analytical model indicated that at the intrados the increase in thickness for bending with internal pressure and bending with combined axial pull and internal pressure was nearly the same. But in the case of bending with the combination of axial pull and internal pressure there was a significant reduction of thickness at the extrados. A parametric study was conducted for the case of bending with combined internal pressure and axial pull and it was seen that with proper selection of the pressure and axial pull wrinkling can be eliminated, thickness distribution around the tube can be optimized, and cross section distortion of the tube can be reduced. Predictions of the analytical model are in good agreement with finite element simulations and published experimental results. The model can be used to evaluate tooling and process design in tube bending.

D-Wave — Quantum computation is based on a very compelling idea: that physics, and physics alone, ultimately determines what can be computed, and how efficiently. Changing the laws of physics relevant for a computing device can open up new possibilities for manipulating information, allowing better algorithms that could transform the way we live. Quantum computation has, up until very recently, been the province of basic research. It is clear that the extreme difficulty and complexity of converting this basic science into useful technology cannot occur within a basic research environment. Here I will describe the conceptual framework behind D-Wave’s organization and technology development model, and compare and contrast this approach to other possible models.

Our goal in physics courses is to teach students to think about and solve physics problems like a physicist. But what does that really mean? I will discuss research on identifying those unique components of how a physicist thinks that distinguish their thinking from that of mere mortals. I will also discuss how these particular components of thinking can be better measured and taught. Audio begins at minute 09:10

Nuclear theory today aims at a comprehensive understanding of properties of nuclides in the whole nuclear chart. A number of challenges are encountered by theorists along the road of accomplishing this goal. Recent progresses in many fronts lead to a renaissance of nuclear physics. Advances in effective field theory provide us with a tool to derive nuclear forces starting from the fundamental theory of Quantum-Chromo-Dynamics: two- and three-body forces among nucleons arise naturally and consistently with each other. This complex nature of the nuclear force generates a broad diversity of phenomena, especially in nuclei far from stability. A fascinating example is the arising of halo nuclear structures leading to extremely large radial extensions. Owing to their short lifetimes, most of these nuclei do not naturally exist on Earth. To be studied they must be synthesized in the laboratory, at the so-called radioactive beam facilities, like TRIUMF. Measurements provide a test of the predictive power of theoretical models. Nowadays, thanks to the advent of high performance computing, new ab-initio methods for the solution of the quantum many-body problem become available. Exotic properties of nuclei can be derived directly from the interaction among protons and neutrons. Furthermore, the investigation of astrophysical implications of nuclear processes, e.g. in the nucleosynthesis of elements is another key aspect in nuclear theory. This synergy between nuclear physics and astrophysics makes the scenario even more exciting. I will discuss some advances in the field with emphasis on future perspective. Audio begins at minute 45:38

Dark Matter and Dark Energy are accepted as legitimate constituents of our Universe. In this talk I will review the numerous observational evidences supporting the existence of the dark side of the Universe, which is why cosmologists claim shamelessly that 95% of the Universe is made of something they do not know the nature of. I will then discuss many of the hypothetical physical origins for Dark Matter and Dark Energy and outline the major research directions now undertaken in order to test the various possible ideas. Audio begins at 01:19:30.

Fractals are patterns that repeat at many magnifications. These intricate patterns are found throughout nature, ranging from clouds, rivers and lightning through to our brains, blood vessels and lungs. Due to their prevalence in nature and their growing impact on cultures around the world, fractals have assumed a rapidly expanding role across the sciences and arts. In this talk, I will explore some of the intriguing properties of fractals by taking a meandering walk through the research disciplines I have worked in. These will include nano-electronic circuits, Antarctic ice-shelves, brain structure and artworks. I hope to show a common theme - that quantification of their underlying fractal geometry provides an enhanced understanding well beyond the traditional qualitative views of these diverse systems.

The advent of electricity market deregulation has placed great emphasis on the availability of information, the analysis of this information, and the subsequent decision-making to optimize system operation in a competitive environment. This creates a need for better ways of correlating the market activity with the physical grid operating states in real time and sharing such information among market participants. Choices of command and control actions may result in different financial consequences for market participants and severely impact their profits. This work provides a solution, the Intelligent Economic Alarm Processor to be implemented in a control center to assist the grid operator in rapidly identifying the faulted sections and market operation management. The task of fault section estimation is difficult when multiple faults, failures of protection devices, and false data are involved. A Fuzzy Reasoning Petri-nets approach has been proposed to tackle the complexities. In this approach, the fuzzy reasoning starting from protection system status data and ending with estimation of faulted power system section is formulated by Petri-nets. The reasoning process is implemented by matrix operations. Next, in order to better feed the FRPN model with more accurate inputs, the failure rates of the protections devices are analyzed. A new approach to assess the circuit breaker’s life cycle or deterioration stages using its control circuit data is introduced. Unlike the traditional “mean time” criteria, the deterioration stages have been mathematically defined by setting up the limits of various performance indices. The model can be automatically updated as the new real-time condition-based data become available to assess the CB’s operation performance using probability distributions. The economic alarm processor module is discussed in the end. This processor firstly analyzes the fault severity based on the information retrieved from the fault section estimation module, and gives the changes in the LMPs, total generation cost, congestion revenue etc. with electricity market schedules and trends. Then some suggested restorative actions are given to optimize the overall system benefit. When market participants receive such information in advance, they make estimation about the system operator's restorative action and their competitors' reaction to it.

Fault location is very important for distribution systems, and quickly identifying the fault and restoring the system can help reduce the outage time and make the system more reliable. In this thesis, a method for locating faults on distribution systems is introduced to quickly identify the faulted feeder sections by using the overcurrent information from the switches in the system. Fuzzy logic is utilized. The proposed method can quickly and accurately locate faulted sections with different fault locations, fault types and fault resistances. The method is applicable to cases with single-faults or multi-faults, and is applicable to networks with multi-sources. The case study has demonstrated the effectiveness of the proposed method.

The domestic production activities deduction (DPAD) was created to incentivize U.S. firms to produce within the U.S. and thereby increase domestic investing. I test whether the DPAD is a large enough incentive for firms to invest in the U.S. I used a simulation, and I found that without the DPAD incentive the firms never chose to produce within the U.S. With the DPAD incentive, only firms with relatively low costs of labor will produce domestically. These firms are rare and will not have a large impact on domestic investment and these firms increasing their production in the U.S. will not have a large impact on our employment rates. Therefore, the U.S. government is losing out on tax revenue without a large benefit to the economy. I also analyzed the DPAD at the state level. Currently 25 states allow the DPAD, but since it is a broad domestic deduction, these states might not be gaining the benefit of increased investing in their own state. Through a separate simulation and ANOVA tests on archival data, I found that states do not benefit from the DPAD.