Growth mechanisms of perturbations in boundary layers over a compliant wall

The temporal modal and nonmodal growth of three-dimensional perturbations in the boundary-layer flow over an infinite compliant flat wall is considered. Using a wall-normal velocity/wall-normal vorticity formalism, the dynamic boundary condition at the compliant wall admits a linear dependence on the eigenvalue parameter, as compared to a quadratic one in the canonical formulation of the problem. This greatly simplifies the accurate calculation of the continuous spectrum by means of a spectral method, thereby yielding a very effective filtering of the pseudospectra as well as a clear identification of instability regions. The regime of global instability is found to be matching the regime of the favorable phase of the forcing by the flow on the compliant wall so as to enhance the amplitude of the wall. An energy-budget analysis for the least-decaying hydroelastic (static-divergence, traveling-wave-flutter and near-stationary transitional) and Tollmien--Schlichting modes in the parameter space reveals the primary routes of energy flow. Moreover, the flow exhibits a slower transient growth for the maximum growth rate of a superposition of streamwise-independent modes due to a complex dependence of the wall-boundary condition with the Reynolds number. The initial and optimal perturbations are compared with the boundary-layer flow over a solid wall; differences and similarities are discussed. Unlike the solid-wall case, viscosity plays a pivotal role in the transient growth. A slowdown of the maximum growth rate with the Reynolds number is uncovered and found to originate in the transition of the fluid-solid interaction from a two-way to a one-way coupling. Finally, a term-by-term energy budget analysis is performed to identify the key contributors to the transient growth mechanism

Identifying safety strategies for on-farm grain bins using risk analysis

The potential for grain bin accidents exists each year on Arkansas farms and farms across the nation. The trend toward increasing utilization of on-farm grain drying and storage could lead to an increase in grain bin accidents. The sharp contrast between a safe, efficient operation and one that leads to injury or death can be represented as sets of farmer-decisions and subsequent chance events. A model was constructed to define the risk associated with grain bin entry and inbin activity so that safety interventions could be identified and implemented to reduce the probability of injury and death. A survey was distributed to Arkansas grain farmers to gather data on the level of safety education, storage techniques, operations management, and other parameters. The data collected from the survey provided quantitative input of many of the model’s probability-distribution functions. Using a fault tree (with parallel modes of failure) in conjunction with a Monte Carlo simulation technique, we evaluated six safety intervention strategies and identified the one with the greatest potential for reducing the risk of serous injury or death. As part of senior design in biological engineering, plans are underway to design and test a probe that can locate and break bridged grain (a common risk factor in grain bin management) while working outside the bin on the ground

Cortical Learning of Recognition Categories: A Resolution of the Exemplar Vs. Prototype Debate

Do humans and animals learn exemplars or prototypes when they categorize objects and events in the world? How are different degrees of abstraction realized through learning by neurons in inferotemporal and prefrontal cortex? How do top-down expectations influence the course of learning? Thirty related human cognitive experiments (the 5-4 category structure) have been used to test competing views in the prototype-exemplar debate. In these experiments, during the test phase, subjects unlearn in a characteristic way items that they had learned to categorize perfectly in the training phase. Many cognitive models do not describe how an individual learns or forgets such categories through time. Adaptive Resonance Theory (ART) neural models provide such a description, and also clarify both psychological and neurobiological data. Matching of bottom-up signals with learned top-down expectations plays a key role in ART model learning. Here, an ART model is used to learn incrementally in response to 5-4 category structure stimuli. Simulation results agree with experimental data, achieving perfect categorization in training and a good match to the pattern of errors exhibited by human subjects in the testing phase. These results show how the model learns both prototypes and certain exemplars in the training phase. ART prototypes are, however, unlike the ones posited in the traditional prototype-exemplar debate. Rather, they are critical patterns of features to which a subject learns to pay attention based on past predictive success and the order in which exemplars are experienced. Perturbations of old memories by newly arriving test items generate a performance curve that closely matches the performance pattern of human subjects. The model also clarifies exemplar-based accounts of data concerning amnesia.Defense Advanced Projects Research Agency SyNaPSE program (Hewlett-Packard Company, DARPA HR0011-09-3-0001; HRL Laboratories LLC #801881-BS under HR0011-09-C-0011); Science of Learning Centers program of the National Science Foundation (NSF SBE-0354378

Bayesian Hierarchical Modelling for Tailoring Metric Thresholds

Software is highly contextual. While there are cross-cutting `global' lessons, individual software projects exhibit many `local' properties. This data heterogeneity makes drawing local conclusions from global data dangerous. A key research challenge is to construct locally accurate prediction models that are informed by global characteristics and data volumes. Previous work has tackled this problem using clustering and transfer learning approaches, which identify locally similar characteristics. This paper applies a simpler approach known as Bayesian hierarchical modeling. We show that hierarchical modeling supports cross-project comparisons, while preserving local context. To demonstrate the approach, we conduct a conceptual replication of an existing study on setting software metrics thresholds. Our emerging results show our hierarchical model reduces model prediction error compared to a global approach by up to 50%.Comment: Short paper, published at MSR '18: 15th International Conference on Mining Software Repositories May 28--29, 2018, Gothenburg, Swede

Strapdown inertial measurement unit computer, volume 1 Final report

Strapdown inertial measurement unit design, calculations, and operating instruction

Laser Interferometer Gravitational-Wave Observatory beam tube component and module leak testing

Laser Interferometer Gravitational-Wave Observatory (LIGO) is a joint project of the California Institute of Technology and the Massachusetts Institute of Technology funded by the National Science Foundation. The project is designed to detect gravitational waves from astrophysical sources such as supernova and black holes. The LIGO project constructed observatories at two sites in the U.S. Each site includes two beam tubes (each 4 km long) joined to form an "L" shape. The beam tube is a 1.25 m diam 304 L stainless steel, ultrahigh vacuum tube that will operate at 1×10^–9 Torr or better. The beam tube was manufactured using a custom spiral weld tube mill from material processed to reduce the outgassing rate in order to minimize pumping costs. The integrity of the beam tube was assured by helium mass spectrometer leak testing each component of the beam tube system prior to installation. Each 2 km long, isolatable beam tube module was then leak tested after completion

Effects of wall compliance on the laminar–turbulent transition of torsional Couette flow

Torsional Couette flow between a rotating disk and a stationary wall is studied experimentally. The surface of the disk is either rigid or covered with a compliant coating. The influence of wall compliance on characteristic flow instabilities and on the laminar–turbulent flow transition is investigated. Data obtained from analysing flow visualizations are discussed. It is found that wall compliance favours two of the three characteristic wave patterns associated with the transition process and broadens the parameter regime in which these patterns are observed. The results for the effects of wall compliance on the third pattern are inconclusive. However, the experiments indicate that the third pattern is not a primary constituent of the laminar–turbulent transition process of torsional Couette flow

Barkhausen Noise and Critical Scaling in the Demagnetization Curve

The demagnetization curve, or initial magnetization curve, is studied by examining the embedded Barkhausen noise using the non-equilibrium, zero temperature random-field Ising model. The demagnetization curve is found to reflect the critical point seen as the system's disorder is changed. Critical scaling is found for avalanche sizes and the size and number of spanning avalanches. The critical exponents are derived from those related to the saturation loop and subloops. Finally, the behavior in the presence of long range demagnetizing fields is discussed. Results are presented for simulations of up to one million spins.Comment: 4 pages, 4 figures, submitted to Physical Review Letter

What is the influence on water quality in temperate eutrophic lakes of a reduction of planktivorous and benthivorous fish? A systematic review protocol

Background: In lakes that have become eutrophic due to sewage discharges or nutrient runoff from land, problems such as algal blooms and oxygen deficiency often persist even when nutrient supplies have been reduced. One reason is that phosphorus stored in the sediments can exchange with the water. There are indications that the high abundance of phytoplankton, turbid water and lack of submerged vegetation seen in many eutrophic lakes may represent a semi-stable state. For that reason, a shift back to more natural clear-water conditions could be difficult to achieve. In some cases, though, temporary mitigation of eutrophication-related problems has been accomplished through biomanipulation: stocks of zooplanktivorous fish have been reduced by intensive fishing, leading to increased populations of phytoplankton-feeding zooplankton. Moreover, reduction of benthivorous fish may result in lower phosphorus fluxes from the sediments. An alternative to reducing the dominance of planktivores and benthivores by fishing is to stock lakes with piscivorous fish. These two approaches have often been used in combination. The implementation of the EU Water Framework Directive has recently led to more stringent demands for measures against eutrophication, and a systematic review could clarify whether biomanipulation is efficient as a measure of that kind. Methods: The review will examine primary field studies of how large-scale biomanipulation has affected water quality and community structure in eutrophic lakes or reservoirs in temperate regions. Such studies can be based on comparison between conditions before and after manipulation, on comparison between treated and non-treated water bodies, or both. Relevant outcomes include Secchi depth, concentrations of oxygen, nutrients, suspended solids and chlorophyll, abundance and composition of phytoplankton, zooplankton and fish, and coverage of submerged macrophytes.A Systematic review to this article was published on 22 May 2015: ernes, C., Carpenter, S.R., Gårdmark, A. et al. What is the influence of a reduction of planktivorous and benthivorous fish on water quality in temperate eutrophic lakes? A systematic review. Environ Evid 4, 7 (2015). DOI: 10.1186/s13750-015-0032-9Mistr