4,806 research outputs found

    Bio-Based Renewable Additives for Anti-Icing Applications (Phase II)

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    The performance and impacts of several agro-based anti-icers along with a traditional chloride-based anti-icer (salt brine) were evaluated. A statistical design of experiments (central composite design) was employed for developing anti-icing liquids consisting of cost-competitive chemicals such as agro-based compounds (e.g., Concord grape extract and glycerin), sodium chloride, sodium metasilicate, and sodium formate. The following experimentally obtained parameters were examined as a function of the formulation design: ice-melting capacity at 25°F (−3.9°C), splitting strength of Portland cement mortar samples after 10 freeze-thaw/deicer cycles, corrosion rate of C1010 carbon steel after 24-hour immersion, and impact on asphalt binder stiffness and m-value. One viable formula (“best performer”) was tested for thermal properties by measuring its differential scanning calorimetry (DSC) thermograms, the friction coefficient of asphalt pavement treated by this anti-icing formulation (vs. 23 wt.% NaCl and beet juice blend) at 25°F after being applied at 30 gallons per lane mile (1 hour after simulated trafficking and plowing), and other properties (pH, oxygen demand in COD). Laboratory data shed light on the selection and formulation of innovative agro-based snow- and ice-control chemicals that can significantly reduce the costs of winter maintenance operations

    The effect of short-term changes in air pollution on respiratory and cardiovascular morbidity in Nicosia, Cyprus.

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    Presented at the 6th International Conference on Urban Air Quality, Limassol, March, 2007. Short-paper was submitted for peer-review and appears in proceedings of the conference.This study investigates the effect of daily changes in levels of PM10 on the daily volume of respiratory and cardiovascular admissions in Nicosia, Cyprus during 1995-2004. After controlling for long- (year and month) and short-term (day of the week) patterns as well as the effect of weather in Generalized Additive Poisson models, some positive associations were observed with all-cause and cause-specific admissions. Risk of hospitalization increased stepwise across quartiles of days with increasing levels of PM10 by 1.3% (-0.3, 2.8), 4.9% (3.3, 6.6), 5.6% (3.9, 7.3) as compared to days with the lowest concentrations. For every 10ÎŒg/m3 increase in daily average PM10 concentration, there was a 1.2% (-0.1%, 2.4%) increase in cardiovascular admissions. With respects to respiratory admissions, an effect was observed only in the warm season with a 1.8% (-0.22, 3.85) increase in admissions per 10ÎŒg/m3 increase in PM10. The effect on respiratory admissions seemed to be much stronger in women and, surprisingly, restricted to people of adult age

    Managing Dust on Unpaved Roads and Airports

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    INE/AUTC 14.1

    Aeronautical Engineering: A special bibliography with indexes, supplement 55

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    This bibliography lists 260 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1975

    Predictive Models for ABS and TPMS based on Gaussian NaĂŻve Bays

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    The car industry is currently preoccupied with the issue of safety. The increasing number of accidents occurring around the world as a result of automobile problems is a major contributing factor to these incidents. The amount of complicated electronics that is used in vehicles is becoming more prevalent every day. A great effort has been made in evaluating vehicle features in relation to vehicle components. Through such systems, a smart architecture and complex function designs are involved. During all of this vehicle transformation and evolution, the automotive industry recognises a high demand for vehicle safety. While designing and manufacturing this system, automotive experts understand a need for a strict monitoring and feedback system for complex vehicle architecture, which can notify the end user if there is any indication of a failure ahead of time. In order to effectively participate in vehicle design activities, it is critical to grasp the significance of safety features. Tire system failures and braking system failures have played a large role in several recent traffic accidents. The failures of the tyre system and the braking system in the vehicle are addressed in this study. While investigating this system, it is discovered that it is supported by complex electrical systems, which include an ECU (electronic controller unit), sensors, and a wire system. Through the use of these technologies, censored data can be processed in a timely manner and made available for diagnostic purposes. Nevertheless, car diagnostics is needed after any vehicle failure but that does not serve the aim of maintaining vehicle safety. As a result, predictive analysis or predictive diagnostics may be a viable option for informing the driver about the health of a particular vehicle component in advance. In this study, the author discusses the concepts of vehicle prognostics for the tyre pressure monitor system and the antilock braking system, which are accomplished using a statistical method of machine learning. In today's world, machine learning is expanding in breadth, and the world is becoming more aware of its enormous potential in the field of data analytics. It is the purpose of this study to introduce methodologies by which machine learning can assist vehicle predictive analytics to attain the intended goal of vehicle safety.The author of this article discusses how Bayesian statistics may be used to produce predictions in the form of probability estimation. The prediction's outcome is thoroughly analysed

    Eleventh International Conference on the Bearing Capacity of Roads, Railways and Airfields

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    Innovations in Road, Railway and Airfield Bearing Capacity – Volume 2 comprises the second part of contributions to the 11th International Conference on Bearing Capacity of Roads, Railways and Airfields (2022). In anticipation of the event, it unveils state-of-the-art information and research on the latest policies, traffic loading measurements, in-situ measurements and condition surveys, functional testing, deflection measurement evaluation, structural performance prediction for pavements and tracks, new construction and rehabilitation design systems, frost affected areas, drainage and environmental effects, reinforcement, traditional and recycled materials, full scale testing and on case histories of road, railways and airfields. This edited work is intended for a global audience of road, railway and airfield engineers, researchers and consultants, as well as building and maintenance companies looking to further upgrade their practices in the field

    Vehicle Dynamic Simulation Possibilities Using AVL Cruise M

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    In most cases, when creating vehicle dynamics simulations, we need software that can speed up model creation and simulation. There are many programs on the market for this purpose, but they have different knowledge and user interfaces. We present in this article briefly introduces the use of one of the market's leading vehicle simulation software, the AVL Cruise M
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