Failure analysis of a tool steel torque shaft

A low design load drive shaft used to deliver power from an experimental exhaust heat recovery system to the crankshaft of an experimental diesel truck engine failed during highway testing. An independent testing laboratory analyzed the failure by routine metallography and attributed the failure to fatigue induced by a banded microstructure. Visual examination by NASA of the failed shaft plus the knowledge of the torsional load that it carried pointed to a 100 percent ductile failure with no evidence of fatigue. Scanning electron microscopy confirmed this. Torsional test specimens were produced from pieces of the failed shaft and torsional overload testing produced identical failures to that which had occurred in the truck engine. This pointed to a failure caused by a high overload and although the microstructure was defective it was not the cause of the failure

Government review of the Mod-2 wind turbine (as-built)

The findings and recommendations of the Government committee formed to conduct an as-built review of the three Mod-2 wind turbine units at Goldendale, Washington are given. The purpose of the review was to identify any critical deficiencies in machine components that could result in failure, and to recommend any necessary corrective action before resuming safe machine operation. The review concluded that one of the deficiencies identified would preclude planned attended or unattended operation, provided that certain corrective actions were implemented

Taking Professional Development From 2D to 3D: Design-Based Learning, 2D Modeling, and 3D Fabrication for Authentic Standards-Aligned Lesson Plans

There is currently significant interest in 3D fabrication in middle school classrooms. At its best 3D printing can be utilized in authentic design projects that integrate math, science, and technology, which facilitate deep learning by students. In essence, students are able to tinker in a virtual world using 3D design software and then tinker in the real world using printed parts. We describe a professional development activity we designed to enable middle school teachers who had taken part in a three-year Math Science Partnership program to authentically integrate 3D printing into design-based lessons. We include some examples of successful design-based lesson plans

Naturally occurring sendai virus infection of athymic nude mice

Nude (nu/nu) mice, Balb/c derived, responded to a naturally occurring Sendai virus infection in a different manner than conventional mice. They developed a chronic debilitating disease and a persistent viral infection of the respiratory tract with intranuclear inclusion bodies in tracheal, bronchial and bronchiolar epithelial cells, laryngeal and tracheal glandular epithelium and in type I and II alveolar cells. The infection was identified by serologic and tissue culture studies, the mouse antibody production test and ultrastructural examination of pulmonary lesions. Phlebitis of pulmonary veins, suppurative rhinitis and otitis media accompanied the viral infection while some mice developed a secondary bronchopneumonia

Proton-electron spectrometer experiments on Gemini-4 and Gemini-7 Final report, 27 May 1963 - 30 Sep. 1966

Fluxes and spectra of electrons and protons in atmosphere measured by spectrometer experiments on Gemini spacecraf

How the world's collective attention is being paid to a pandemic: COVID-19 related n-gram time series for 24 languages on Twitter

In confronting the global spread of the coronavirus disease COVID-19 pandemic we must have coordinated medical, operational, and political responses. In all efforts, data is crucial. Fundamentally, and in the possible absence of a vaccine for 12 to 18 months, we need universal, well-documented testing for both the presence of the disease as well as confirmed recovery through serological tests for antibodies, and we need to track major socioeconomic indices. But we also need auxiliary data of all kinds, including data related to how populations are talking about the unfolding pandemic through news and stories. To in part help on the social media side, we curate a set of 2000 day-scale time series of $1$- and $2$-grams across 24 languages on Twitter that are most `important' for April 2020 with respect to April 2019. We determine importance through our allotaxonometric instrument, rank-turbulence divergence. We make some basic observations about some of the time series, including a comparison to numbers of confirmed deaths due to COVID-19 over time. We broadly observe across all languages a peak for the language-specific word for `virus' in January followed by a decline through February and a recent surge through April. The world's collective attention dropped away while the virus spread out from China. We host the time series on Gitlab, updating them on a daily basis while relevant. Our main intent is for other researchers to use these time series to enhance whatever analyses that may be of use during the pandemic as well as for retrospective investigations.Comment: 12 pages, 6 figures, 3 table

Allotaxonometry and rank-turbulence divergence: A universal instrument for comparing complex systems

Complex systems often comprise many kinds of components which vary over many orders of magnitude in size: Populations of cities in countries, individual and corporate wealth in economies, species abundance in ecologies, word frequency in natural language, and node degree in complex networks. Comparisons of component size distributions for two complex systems---or a system with itself at two different time points---generally employ information-theoretic instruments, such as Jensen-Shannon divergence. We argue that these methods lack transparency and adjustability, and should not be applied when component probabilities are non-sensible or are problematic to estimate. Here, we introduce `allotaxonometry' along with `rank-turbulence divergence', a tunable instrument for comparing any two (Zipfian) ranked lists of components. We analytically develop our rank-based divergence in a series of steps, and then establish a rank-based allotaxonograph which pairs a map-like histogram for rank-rank pairs with an ordered list of components according to divergence contribution. We explore the performance of rank-turbulence divergence for a series of distinct settings including: Language use on Twitter and in books, species abundance, baby name popularity, market capitalization, performance in sports, mortality causes, and job titles. We provide a series of supplementary flipbooks which demonstrate the tunability and storytelling power of rank-based allotaxonometry.Comment: 23 pages, 7 figures, 1 table; online appendices: http://compstorylab.org/allotaxonometry