3,097 research outputs found

    Nondestructive testing of railroad wheels and rails by ultrasonics

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    Quality control of wheels and rails can be improved by using ultrasonic technique developed for measuring stresses in metallic materials. In addition, parts already in use can be tested and replaced if they are found to be unsafe. Test equipment includes two transducers

    Ultrasonic measurement of stress in 2219-T87 aluminum plate

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    The basic relationship of ultrasonic signal velocity to directional subsurface stress is reviewed. Inappropriateness of dependency on a single correlative value of constant for a three dimensional stress field in metallic materials is discussed. Implementation of conventional ultrasonic nondestructive testing capabilities integrated to provide a composite technique for the measurement of orthogonal stress components is described, and the procedures for performing the preparatory calibration and subsequent stress field measurements are presented. In conclusion, the prime effect of stress on ultrasonic signal velocity occurs only in the direction of material excitation or particle motion

    Ultrasonic measurement of stress in railroad wheels and in long lengths of welded rail

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    The failure of high speed emergency braking is discussed for railroad wheels and track. It is shown that high compressive residual stresses exist in the rims of new wheels which generate excessive heat, reducing the stress levels. Thermal stresses that build up in continuous lengths of welded track are reported and nondestructive methods of measuring stresses in thick steel are presented for identification, replacement, or adjustment before hazardous failures occur

    Program on application of communications satellites to educational development: Design of a 12 channel FM microwave receiver

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    The design, fabrication, and performance of elements of a low cost FM microwave satellite ground station receiver is described. It is capable of accepting 12 contiguous color television equivalent bandwidth channels in the 11.72 to 12.2 GHz band. Each channel is 40 MHz wide and incorporates a 4 MHz guard band. The modulation format is wideband FM and the channels are frequency division multiplexed. Twelve independent CATV compatible baseband outputs are provided. The overall system specifications are first discussed, then consideration is given to the receiver subsystems and the signal branching network

    Design of a 12 channel fm microwave receiver

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    The design, fabrication, and performance of elements of a low cost FM microwave satellite ground station receiver is described. It is capable of accepting 12 contiguous color television equivalent bandwidth channels in the 11.72 to 12.2 GHz band. Each channel is 40 MHz wide and incorporates a 4 MHz guard band. The modulation format is wideband FM and the channels are frequency division multiplexed. Twelve independent CATV compatible baseband outputs are provided. The overall system specifications are first discussed, then consideration is given to the receiver subsystems and the signal branching network

    Environmental drivers of seasonal shifts in abundance of wild pigs (Sus scrofa) in a tropical island environment

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    Four raster datasets are included that were developed using data derived from game camera traps. These data were used as inputs in a species distribution modeling approach using environmental correlates (please find more detailed information in the referenced publication). The resulting raster datasets are a relative abundance index (0 - 100) of feral pigs on Maui using seasonal (Fall and Spring) and combined annual data as well as an averaged ensemble model using seasonal outputs. For those interested in a single model that best represents average pig distribution please use the averaged ensemble model (Maui_pig_ensemble_distribution.tif). *Please note: Additional raster datasets for feral goat (Maui_feralgoats_distribution.tif) and Axis deer (Maui_axisdeer_distribution.tif) distributions are included but are currently unpublished data. Please reach out should you have any questions.Background: Non-native wild pigs (Sus scrofa) threaten sensitive flora and fauna, cost billions of dollars in economic damage, and pose a significant human–wildlife conflict risk. Despite growing interest in wild pig research, basic life history information is often lacking throughout their introduced range and particularly in tropical environments. Similar to other large terrestrial mammals, pigs possess the ability to shift their range based on local climatic conditions or resource availability, further complicating management decisions. The objectives of this study were to (i) model the distribution and abundance of wild pigs across two seasons within a single calendar year; (ii) determine the most important environmental variables driving changes in pig distribution and abundance; and (iii) highlight key differences between seasonal models and their potential management implications. These study objectives were achieved using zero-inflated models constructed from abundance data obtained from extensive field surveys and remotely sensed environmental variables. Results: Our models demonstrate a considerable change in distribution and abundance of wild pigs throughout a single calendar year. Rainfall and vegetation height were among the most influential variables for pig distribution during the spring, and distance to adjacent forest and vegetation density were among the most significant for the fall. Further, our seasonal models show that areas of high conservation value may be more vulnerable to threats from wild pigs at certain times throughout the year, which was not captured by more traditional modeling approaches using aggregated data. Conclusions: Our results suggest that (i) wild pigs can considerably shift their range throughout the calendar year, even in tropical environments; (ii) pigs prefer dense forested areas in the presence of either hunting pressure or an abundance of frugivorous plants, but may shift to adjacent areas in the absence of either of these conditions; and (iii) seasonal models provide valuable biological information that would otherwise be missed by common modeling approaches that use aggregated data over many years. These findings highlight the importance of considering biologically relevant time scales that provide key information to better inform management strategies, particularly for species whose ranges inc

    A comparison of abundance and distribution model outputs using camera traps and sign surveys for feral pigs

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    Two raster datasets are included that were developed using data derived from game camera traps (Oahu_pigcam_distribution.tif) and visual sign surveys (Oahu_pigsign_distribution.tif). These data were used as inputs in a species distribution modeling approach using environmental correlates (please find more detailed information in the referenced publication). The resulting raster datasets are a relative abundance index (0 - 100) of feral pigs on Oʻahu.Species distribution models play a central role in informing wildlife management. For models to be useful, they must be based on data that best represent the presence or abundance of the species. Data used as inputs in the development of these models can be obtained through numerous methods, each subject to different biases and limitations but, to date, few studies have examined whether these biases result in different predictive spatial models, potentially influencing conservation decisions. In this study, we compare distribution model predictions of feral pig (Sus scrofa) relative abundance using the two most common monitoring methods: detections from camera traps and visual surveys of pig sign. These data were collected during the same period using standardised methods at survey sites generated using a random stratified sampling design. We found that although site-level observed sign data were only loosely correlated with observed camera detections (R2 ¼ 0.32–0.45), predicted sign and camera counts from zero-inflated models were well correlated (R2 ¼ 0.78–0.88). In this study we show one example in which fitting two different forms of abundance data using environmental covariates explains most of the variance between datasets. We conclude that, as long as outputs are produced through appropriate modelling techniques, these two common methods of obtaining abundance data may be used interchangeably to produce comparable distribution maps for decision-making purposes. However, for monitoring purposes, sign and camera trap data may not be used interchangeably at the site level
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