Clarifications of a Datum Axis or Centerplane Specifying in Maximum Material Condition of Geometric Dimensioning and Tolerancing

Engineering and Engineering Technology students and professionals learning the processes and standards in computer-aided design (CAD) and computer-aided manufacturing (CAM) should learn and understand the methodology of geometric dimensioning and tolerancing (GD&T) to describe the intent and requirements for part and assembly geometries. Correct application of GD&T ensures that the part and assembly geometry defined on the drawing will have the desired form and fit (within limits) and function as intended. One learning difficulty in understanding GD&T is the concept of defining a datum axis or center plane using Maximum Material Condition (MMC). To overcome this difficulty, a new approach is presented that uses a modifier ○V (Virtual Condition) instead of ○M (MMC). A thorough rationalization of using ○V in datum axis specification is discussed. The paper also provides a convenient table on how to use this modifier

Quantum kinetic approach to the calculation of the Nernst effect

We show that the strong Nernst effect observed recently in amorphous superconducting films far above the critical temperature is caused by the fluctuations of the superconducting order parameter. We employ the quantum kinetic approach for the derivation of the Nernst coefficient. We present here the main steps of the calculation and discuss some subtle issues that we encountered while calculating the Nernst coefficient. In particular, we demonstrate that in the limit T=0 the contribution of the magnetization ensures the vanishing of the Nernst signal in accordance with the third law of thermodynamics. We obtained a striking agreement between our theoretical calculations and the experimental data in a broad region of temperatures and magnetic fields.Comment: 24 pages, 13 figure

Implementing Mechatronics Design Methodology in Mechanical Engineering Technology Senior Design Projects at the Old Dominion University

In recent years, the nature of engineering design has changed due to advances in embedded system design and computer technologies. It is rare to engineer a purely mechanical design that does not incorporate electrical and electronic components. Mechanical engineers and mechanical engineering technologists must possess a multi-disciplinary knowledge with the understanding of both mechanical and electrical systems. For this purpose, undergraduate programs in engineering technology have added mechatronics courses to their curriculum. Mechatronics is a design process that is multi-disciplinary in nature and integrates principles of many engineering disciplines including, but not limited to, mechanical engineering, electrical engineering, and controls engineering. These courses typically incorporate problem-based learning and project-based pedagogy to effectively build the student’s knowledge and understanding. Old Dominion University’s Mechanical Engineering Technology (ODU MET) program offers undergraduate courses related to Advanced Manufacturing including Robotics; Automation; Lean Manufacturing; Computer Integrated Manufacturing; and Advanced Manufacturing Processes. Recently, two new courses related to mechatronics were added to the same focus area. In addition, ODU MET program has placed an increased emphasis on mechatronics for students’ senior design projects. This paper highlights the benefits of including mechatronics in the ODU MET curriculum and presents several recent senior design projects that showcase how the student has incorporated multi-disciplinary principles into the design and build of a functional mechatronic device. By embedding these experience into their senior design project, students are exposed to other engineering technology areas, learn the terminology of other professions, and feel more confident to join the workforce with the cross-disciplinary skills needed to be successful

LAS BATALLAS FESTIVAS DE ESPANA

Serving individual customer needs at reasonable prices can be a profitable target market in high-wage countries. The dilemma between scale and scope-oriented production is one major research topic within the Cluster of Excellence "Integrative Production Technology for High-Wage Countries" at the RWTH Aachen University. One main objective of this project is to bridge the existing gap between individual manufacturing and mass production. Modularization is a widely accepted approach in tool-based manufacturing processes. In this paper, we propose a flexible design methodology for modular tools and dies. The methodology will assist the design engineer in setting up a series of modularized tools in a conceptually closed manner. The described methodology covers modularization in a broad sense, i.e. it includes hardware modularization as well as modularization of the construction process. The methodology consists of three phases: initiation, analysis and design phase

Multimodal single-molecule microscopy with continuously controlled spectral resolution

Color is a fundamental contrast mechanism in fluorescence microscopy, providing the basis for numerous imaging and spectroscopy techniques. Building on spectral imaging schemes that encode color into a fixed spatial intensity distribution, here, we introduce continuously controlled spectral-resolution (CoCoS) microscopy, which allows the spectral resolution of the system to be adjusted in real-time. By optimizing the spectral resolution for each experiment, we achieve maximal sensitivity and throughput, allowing for single-frame acquisition of multiple color channels with single-molecule sensitivity and 140-fold larger fields of view compared with previous super-resolution spectral imaging techniques. Here, we demonstrate the utility of CoCoS in three experimental formats, single-molecule spectroscopy, single-molecule Förster resonance energy transfer, and multicolor single-particle tracking in live neurons, using a range of samples and 12 distinct fluorescent markers. A simple add-on allows CoCoS to be integrated into existing fluorescence microscopes, rendering spectral imaging accessible to the wider scientific community

Nernst-Ettingshausen effect in two-component electronic liquids

A simple model describing the Nernst-Ettingshausen effect (NEE) in two-component electronic liquids is formulated. The examples considered include graphite, where the normal and Dirac fermions coexist, superconductor in fluctuating regime, with coexisting Cooper pairs and normal electrons, and the inter-stellar plasma of electrons and protons. We give a general expression for the Nernst constant and show that the origin of a giant NEE is in the strong dependence of the chemical potential on temperature in all cases

Nernst effect as a probe of superconducting fluctuations in disordered thin films

In amorphous superconducting thin films of $Nb_{0.15}Si_{0.85}$ and $InO_x$, a finite Nernst coefficient can be detected in a wide range of temperature and magnetic field. Due to the negligible contribution of normal quasi-particles, superconducting fluctuations easily dominate the Nernst response in the entire range of study. In the vicinity of the critical temperature and in the zero-field limit, the magnitude of the signal is in quantitative agreement with what is theoretically expected for the Gaussian fluctuations of the superconducting order parameter. Even at higher temperatures and finite magnetic field, the Nernst coefficient is set by the size of superconducting fluctuations. The Nernst coefficient emerges as a direct probe of the ghost critical field, the normal-state mirror of the upper critical field. Moreover, upon leaving the normal state with fluctuating Cooper pairs, we show that the temperature evolution of the Nernst coefficient is different whether the system enters a vortex solid, a vortex liquid or a phase-fluctuating superconducting regime.Comment: Submitted to New. J. Phys. for a focus issue on "Superconductors with Exotic Symmetries

End-to-end Interpretable Learning of Non-blind Image Deblurring

Non-blind image deblurring is typically formulated as a linear least-squares problem regularized by natural priors on the corresponding sharp picture's gradients, which can be solved, for example, using a half-quadratic splitting method with Richardson fixed-point iterations for its least-squares updates and a proximal operator for the auxiliary variable updates. We propose to precondition the Richardson solver using approximate inverse filters of the (known) blur and natural image prior kernels. Using convolutions instead of a generic linear preconditioner allows extremely efficient parameter sharing across the image, and leads to significant gains in accuracy and/or speed compared to classical FFT and conjugate-gradient methods. More importantly, the proposed architecture is easily adapted to learning both the preconditioner and the proximal operator using CNN embeddings. This yields a simple and efficient algorithm for non-blind image deblurring which is fully interpretable, can be learned end to end, and whose accuracy matches or exceeds the state of the art, quite significantly, in the non-uniform case.Comment: Accepted at ECCV2020 (poster

Fluctuations of the superconducting order parameter as an origin of the Nernst effect

We show that the strong Nernst signal observed recently in amorphous superconducting films far above the critical temperature is caused by the fluctuations of the superconducting order parameter. We demonstrate a striking agreement between our theoretical calculations and the experimental data at various temperatures and magnetic fields. Besides, the Nernst effect is interesting not only in the context of superconductivity. We discuss some subtle issues in the theoretical study of thermal phenomena that we have encountered while calculating the Nernst coefficient. In particular, we explain how the Nernst theorem (the third law of thermodynamics) imposes a strict constraint on the magnitude of the Nernst effect.Comment: 6 pages, 5 figures, extended versio

Nonlinear Lattice Waves in Random Potentials

Localization of waves by disorder is a fundamental physical problem encompassing a diverse spectrum of theoretical, experimental and numerical studies in the context of metal-insulator transition, quantum Hall effect, light propagation in photonic crystals, and dynamics of ultra-cold atoms in optical arrays. Large intensity light can induce nonlinear response, ultracold atomic gases can be tuned into an interacting regime, which leads again to nonlinear wave equations on a mean field level. The interplay between disorder and nonlinearity, their localizing and delocalizing effects is currently an intriguing and challenging issue in the field. We will discuss recent advances in the dynamics of nonlinear lattice waves in random potentials. In the absence of nonlinear terms in the wave equations, Anderson localization is leading to a halt of wave packet spreading. Nonlinearity couples localized eigenstates and, potentially, enables spreading and destruction of Anderson localization due to nonintegrability, chaos and decoherence. The spreading process is characterized by universal subdiffusive laws due to nonlinear diffusion. We review extensive computational studies for one- and two-dimensional systems with tunable nonlinearity power. We also briefly discuss extensions to other cases where the linear wave equation features localization: Aubry-Andre localization with quasiperiodic potentials, Wannier-Stark localization with dc fields, and dynamical localization in momentum space with kicked rotors.Comment: 45 pages, 19 figure