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  1. 室蘭工業大学紀要
  2. 第34号 - 理工編

Development and Application of Predictor Model for Seasonal Variations in Skid Resistance (Ⅰ) ―Mechanistic Model―

http://hdl.handle.net/10258/1086
http://hdl.handle.net/10258/1086
99c9a255-25e5-43ae-a8e8-0563eb7d0061
名前 / ファイル ライセンス アクション
kiyo34_rikou_pp25-39.pdf kiyo34_rikou_pp25-39.pdf (1.4 MB)
Item type 紀要論文 / Departmental Bulletin Paper(1)
公開日 2014-03-04
タイトル
タイトル Development and Application of Predictor Model for Seasonal Variations in Skid Resistance (Ⅰ) ―Mechanistic Model―
言語 en
言語
言語 eng
資源タイプ
資源タイプ識別子 http://purl.org/coar/resource_type/c_6501
資源タイプ departmental bulletin paper
アクセス権
アクセス権 open access
アクセス権URI http://purl.org/coar/access_right/c_abf2
著者 斎藤, 和夫

× 斎藤, 和夫

ja 斎藤, 和夫

ja-Kana サイトウ, カズオ

en SAITO, Kazuo


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HENRY, John J.

× HENRY, John J.

en HENRY, John J.


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内容記述タイプ Abstract
内容記述 This paper describes a part of the findings of a three-year research program to develop a basic mechanistic model to predict the seasonal and short-term variations in skid resistance as a function of environmental and traffic conditions. The model treats the seasonal and short-term variations separately. Data were analyzed from 21 test surfaces in State College, Pennsylvania. For the seasonal trend, an exponential curve was fitted to the skid number data for the asphalt pavements, while a linear relationship best fit the data for portland cement concrete surfaces. The coefficients of the resulting seasonal variation curves were fitted to pavement and traffic parameters to provide predictors for the long term effects. Significant predictors were found to be British Pendulum Numbers (BPN) and average daily traffic (ADT). Other predictors for pavement polishing are suggested in place of BPN to predict the rate of decrease in skid resistance over an annual cycle. After the data for seasonal variations were adjusted, the remaining short-term variations were regressed against rainfall, terperature, and macrotexture parameter. The short-term variations can be predicted by dry spell factor (DSF) and pavement temperature (T_p ), but the introduction of the measured percent normalized gradient (PNG) was found to improve the regression. The developed model wes applied for predicting the level of skid resistance at the end of the year (SN_64F) and for predicting the skid resistance at any day from a measurement taken on a different day. It is concluded that mechanistic model is effective predictor model for predicting those skid resistance.
言語 en
書誌情報 ja : 室蘭工業大学研究報告. 理工編
en : Memoirs of the Muroran Institute of Technology. Science and engineering

巻 34, p. 25-39, 発行日 1984-11-30
出版者
出版者 室蘭工業大学
言語 ja
論文ID(NAID)
関連タイプ isIdenticalTo
識別子タイプ NAID
関連識別子 40003627601
日本十進分類法
主題Scheme NDC
主題 514
ISSN
収録物識別子タイプ PISSN
収録物識別子 05802415
書誌レコードID
収録物識別子タイプ NCID
収録物識別子 AN00238225
著者版フラグ
出版タイプ VoR
出版タイプResource http://purl.org/coar/version/c_970fb48d4fbd8a85
フォーマット
内容記述タイプ Other
内容記述 application/pdf
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