Developing Future Aviation Leaders: Advice from Today’s Leaders!

Because of their technical achievements, aviation personnel frequently find themselves in positions of influence or leadership in the community. The soft skills, which aid in the transition from a highly technical career to the intangible tasks of leadership, may have been neglected, thus making their new role even more difficult. Utilizing the findings of a qualitative study and a series of interviews with successful aviation leaders of Oklahoma, this paper addresses specific recommendations from today\u27s leaders for filling the gap between the technical and soft skills required for effective leadership. Increased emphasis on communications curricula, development of decision-making and critical thinking skills, expansion of curricula related to global communications and strategies, and improvement of student focus and instructional methods were recommended by today\u27s leaders for enhancing 21st Century aviation leadership skills

Randomized Dynamic Mode Decomposition

This paper presents a randomized algorithm for computing the near-optimal low-rank dynamic mode decomposition (DMD). Randomized algorithms are emerging techniques to compute low-rank matrix approximations at a fraction of the cost of deterministic algorithms, easing the computational challenges arising in the area of `big data'. The idea is to derive a small matrix from the high-dimensional data, which is then used to efficiently compute the dynamic modes and eigenvalues. The algorithm is presented in a modular probabilistic framework, and the approximation quality can be controlled via oversampling and power iterations. The effectiveness of the resulting randomized DMD algorithm is demonstrated on several benchmark examples of increasing complexity, providing an accurate and efficient approach to extract spatiotemporal coherent structures from big data in a framework that scales with the intrinsic rank of the data, rather than the ambient measurement dimension. For this work we assume that the dynamics of the problem under consideration is evolving on a low-dimensional subspace that is well characterized by a fast decaying singular value spectrum

Nonlinear model order reduction via dynamic mode decomposition

We propose a new technique for obtaining reduced order models for nonlinear dynamical systems. Specically, we advocate the use of the recently developed dynamic mode decomposition (DMD), an equation-free method, to approximate the nonlinear term. DMD is a spatio-temporal matrix decomposition of a data matrix that correlates spatial features while simul-taneously associating the activity with periodic temporal behavior. With this decomposition, one can obtain a fully reduced dimensional surrogate model and avoid the evaluation of the nonlinear term in the online stage. This allows for a reduction in the computational cost and, at the same time, accurate approximations of the problem. We present a suite of numerical tests to illustrate our approach and to show the e ectiveness of the method in comparison to existing approaches

Randomized model order reduction

The singular value decomposition (SVD) has a crucial role in model order reduction. It is often utilized in the offline stage to compute basis functions that project the high-dimensional nonlinear problem into a low-dimensional model which is then evaluated cheaply. It constitutes a building block for many techniques such as the proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD). The aim of this work is to provide an efficient computation of low-rank POD and/or DMD modes via randomized matrix decompositions. This is possible due to the randomized singular value decomposition (rSVD) which is a fast and accurate alternative of the SVD. Although this is considered an offline stage, this computation may be extremely expensive; therefore, the use of compressed techniques drastically reduce its cost. Numerical examples show the effectiveness of the method for both POD and DMD

21st Century Aerospace and the Power of Human Communication Skills

Aviation played a vital and dynamic role in 20th Century technical and social progress. That role has always represented power and continues to do so as it expands to meet the challenges of aerospace power in the 21st Century. Human communication skills are the transmission vehicle that allows aviation/aerospace information to be converted to the power of usage in this highly specialized and dynamic field. Utilizing the advice gleaned from the literature and studies pertinent to the importance of communications skills in a variety of occupations, this presentation discusses the perceived deficit in communications training for aviation students and further explores the importance of developing those skills for 21st Century aerospace leadership

Target-Normal Single Spin Asymmetries Measured with Positrons

Two-photon exchange and the larger class of hadronic box diagrams are difficult to calculate without a large degree of model-dependence. At the same time, these processes are significant radiative corrections in parity-violating electron scattering, in neutron decay, and may even be responsible for the proton's form factor ratio discrepancy. New kinds of experimental data are needed to help constrain models and guide future box-diagram calculations. The target-normal single spin asymmetry, $A_n$, formed with an unpolarized beam scattering from a target that is polarized normal to the scattering plane, is sensitive to the imaginary part of the two-photon exchange amplitude, and can provide a valuable constraint. A measurement with both electrons and positrons can reduce sources of experimental error, and distinguish between the effects of two-photon exchange and those of time-reversal symmetry violation. This article describes a proposed experiment in Hall A, using the new Super Big-Bite Spectrometer that can cover a momentum transfer range in the critical zone of uncertainty between where hadronic calculations and those based on partonic degrees of freedom are expected to be accurate.Comment: 7 pages, 4 figures. arXiv admin note: substantial text overlap with arXiv:2007.1508