Детальная информация

Название: Antiskid prediction model for cement pavements in seasonal frost regions // Magazine of Civil Engineering. – 2020 № 6 (98)
Авторы: Zhao Q. Q.; Zhang H. T.; Fediuk R. S.; Wang J. W.
Выходные сведения: 2020
Коллекция: Общая коллекция
Тематика: Транспорт; Транспортные сооружения; road surfaces; cement surfaces; anti-skid; slip prediction; numerical simulation; seasonal frost; concrete; дорожные покрытия; цементные покрытия; противоскольжение; прогнозирование скольжения; численное моделирование; сезонные морозы; бетоны
УДК: 624
ББК: 39.11
Тип документа: Статья, доклад
Тип файла: PDF
Язык: Английский
DOI: 10.18720/MCE.98.7
Права доступа: Свободный доступ из сети Интернет (чтение, печать, копирование)

Разрешенные действия: Прочитать Загрузить (0,5 Мб)

Группа: Анонимные пользователи

Сеть: Интернет

Аннотация

The antiskid performance of the cement concrete pavement in the seasonal frost regions is an important factor determining the safety of road use. However, due to the low efficiency and high cost of on-site detection, it is very important to reasonably predict it. Five key factors such as ice film thickness, tire pressure, tire load, driving speed, and structural depth were determined. The response surface test was performed to determine the corresponding range of the five factors when the model was optimally predicted. A prediction model of antiskid performance for cement concrete pavement in the seasonal frost regions was created, the goodness of model fitting and the normal distribution of the model were tested, and the applicability of the model was verified. The results show that when the thickness of the ice film is 1.5 mm ~ 3 mm, the tire pressure is 180 kPa ~ 240 kPa, the driving speed is 40 km/h ~ 80 km/h, the structural depth is 0.24 mm ~ 0.62 mm and the tire load is 3250 N ~ 4000 N , the prediction level of the model is the best; SRI can be interpreted by the model accounting for 98.5 %, and the regression model has a high degree of fit, which meets the assumption of normal distribution; the model's SRI predicted value fits the field measured SRI value to 0.995, and the degree of fit is high. The prediction model of antiskid performance is of great significance to prolong the service life of cement concrete pavement in seasonal frost regions.

Права на использование объекта хранения

Место доступа Группа пользователей Действие
Локальная сеть ИБК СПбПУ Все Прочитать Печать Загрузить
-> Интернет Все Прочитать Печать Загрузить

Оглавление

  • Antiskid prediction model for cement pavements in seasonal frost regions
    • 1. Introduction
    • 2. Methods
      • 2.1. Screening of influencing factors for antiskid
      • 2.2. Identification of key factors
      • 2.3. Determination of model parameter value range
      • 2.4. Determination of the optimal prediction space of the model
    • 3. Results and Discussion
      • 3.1. Establishment of Model Relationship
      • 3.2. Significance test of regression equation
      • 3.3. Significance test of regression coefficient
      • 3.4. Model goodness of fit test
      • 3.5. Model normal distribution test
      • 3.6. Model verification
    • 4. Conclusions
    • 5. Acknowledgements

Статистика использования

stat Количество обращений: 52
За последние 30 дней: 0
Подробная статистика