Field Evaluation of Method for Rating Unsurfaced Road Conditions

2003 ◽  
Vol 1819 (1) ◽  
pp. 267-272 ◽  
Author(s):  
Manoel H. A. Soria ◽  
Eliana B. Fontenele
Keyword(s):  
Surface Condition ◽  
Field Research ◽  
Field Evaluation ◽  
Condition Index ◽  
Army Corps ◽  
Army Corps Of Engineers ◽  
Sample Unit ◽  
Subjective Evaluations ◽  
Road Condition ◽  
Rating Method

Research was conducted to evaluate the performance of a method for rating the surface condition of low-volume unsurfaced roads and eventually to adapt the method to the situation prevailing in the state of São Paulo, Brazil. The rating method selected as the basis for this experiment is the unsurfaced road condition index (URCI) developed by the U.S. Army Corps of Engineers. The field research comprised subjective evaluations and URCI determinations performed by a rating panel composed of seven members. Some of the main questions underlying the research are: Are the original URCI deduct values curves adequate for the south Brazilian region? If not, is it possible to construct deduct values curves similar to URCI’s? To what extent can a rating panel be used to construct and calibrate these curves? Five unsurfaced county roads were selected according to the criteria of maximum soil and conditions variability. From these roads 14 segments 300 m length were selected and divided into 140 sample units 30 m in length. The rating panel attributed scores for the section, for each sample unit, and for each distress found in the sample unit. It was concluded that the panel scores for distress and surface condition of sample unit and section do not agree with the URCI computed by the method and that there is some coherence between the subjective scores given to the sample units and the score given to the section composed of these sample units.

scholarly journals FRF WAVE TEST BED AND BATHYMETRY INVERSION

2017 ◽  
pp. 22 ◽  
Author(s):  
Jane McKee Smith ◽  
Spicer Bak ◽  
Tyler Hesser ◽  
Mary A. Bryant ◽  
Chris Massey
Keyword(s):  
Numerical Models ◽  
Field Research ◽  
Wave Model ◽  
Army Corps ◽  
Army Corps Of Engineers ◽  
Test Bed ◽  
Inversion Algorithm ◽  
Us Army ◽  
Spectral Wave Model ◽  
Limited Application

An automated Coastal Model Test Bed has been built for the US Army Corps of Engineers Field Research Facility to evaluate coastal numerical models. In October of 2015, the test bed was expanded during a multi-investigator experiment, called BathyDuck, to evaluate two bathymetry sources: traditional survey data and bathymetry generated through the cBathy inversion algorithm using Argus video measurements. Comparisons were made between simulations using the spectral wave model STWAVE with half-hourly cBathy bathymetry and the more temporally sparse surveyed bathymetry. The simulation results using cBathy bathymetry were relatively close to those using the surveyed bathymetry. The largest differences were at the shallowest gauges within 250 m of the coast, where wave model normalized root-mean-square was approximately twice are large using the cBathy bathymetry. The nearshore errors using the cBathy input were greatest during events with wave height greater than 2 m. For this limited application, the Argus cBathy algorithm proved to be a suitable bathymetry input for nearshore wave modeling. cBathy bathymetry was easily incorporated into the modeling test bed and had the advantage of being updated on approximately the same temporal scale as the other model input conditions. cBathy has great potential for modeling applications where traditional surveys are sparse (seasonal or yearly).

Condition Index Assessment for U.S. Army Corps of Engineers Civil Works

1999 ◽  
Vol 5 (2) ◽  
pp. 52-60 ◽  
Author(s):  
David T. McKay ◽  
Kevin L. Rens ◽  
Lowell F. Greimann ◽  
James H. Stecker
Keyword(s):  
Condition Index ◽  
Army Corps ◽  
Army Corps Of Engineers ◽  
Corps Of Engineers

scholarly journals Smart Structural Health Monitoring of Flexible Pavements Using Machine Learning Methods

2020 ◽  
Author(s):  
Nader Karballaeezadeh ◽  
Danial Mohammadzadeh S. ◽  
Dariush Moazami ◽  
Narjes Nabipour ◽  
Amir Mosavi ◽  
...  
Keyword(s):  
Random Forest ◽  
Surface Condition ◽  
Monitoring And Evaluation ◽  
Condition Index ◽  
Structural Condition ◽  
Condition Assessment ◽  
Sample Unit ◽  
Safety Risks ◽  
Pavement Condition Index ◽  
Structural Condition Assessment

The construction of different roads, such as freeways, highways, major roads or minor roads must be accompanied by constant monitoring and evaluation of service delivery. Pavements are generally assessed by engineers in terms of the smoothness, surface condition, structural condition and surface safety. Pavement assessment is often conducted using the qualitative indices such as international roughness index (IRI), pavement condition index (PCI), structural condition index (SCI) and skid resistance value (SRV), which are used for smoothness assessment, surface condition assessment, structural condition assessment, and surface safety assessment, respectively. In this paper, Tehran-Qom Freeway in Iran has been selected as the case study and its smoothness and pavement surface conditions are assessed. At 2-km intervals, a 100-meter sample unit is selected in the slow-speed lane (totally, 118 sample units). In these sample units, the PCI is calculated after a visual inspection of the pavement and the recording of distresses. Then, in each sample unit, the average IRI is computed. The purpose of this study is to provide a method for estimating PCI based on IRI. The proposed theory was developed by Random Forest (RF), and Random Forest optimized by Genetic Algorithm (RF-GA) methods and these methods were validated using correlation coefficient (CC), scattered index (SI), and Willmott’s index of agreement (WI) criteria. The proposed method reduces costs, saves time and eliminates the safety risks.

scholarly journals ADVANCES IN THE UNSTRUCTURED WAVEWATCH III AND APPLICATION TO HURRICANE DORIAN

2020 ◽  
pp. 42
Author(s):  
Jane McKee Smith ◽  
Tyler Hesser ◽  
Mary Anderson Bryant ◽  
Aron Roland ◽  
Andrew Cox
Keyword(s):  
Rapid Development ◽  
Field Research ◽  
Propagation Model ◽  
Army Corps ◽  
Army Corps Of Engineers ◽  
Wavewatch Iii ◽  
Us Army ◽  
Spatial Coverage ◽  
The Us ◽  
Hurricane Storm Surge

The spectral wave generation and propagation model WAVEWATCH III (WW3) is undergoing rapid development to extend capability and applicability. An option for unstructured grids and implicit solution provides WW3 with the flexibility and efficiency to resolve complex shorelines and high-gradient wave zones to drive nearshore circulation, wave setup, and wave-driven sediment transport with multi-scale spatial coverage over approximately three orders of magnitude. The model is compatible with community-based coupling infrastructure to facilitate two-way coupling with circulation models for simulating hurricane storm surge and waves. Unstructured WW3 is applied for 2019 Hurricane Dorian and validated with National Data Buoy Center buoys and nearshore gauges at the US Army Corps of Engineers Field Research Facility.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/kz9G46xUD0k

scholarly journals Annual data summary for 1995, CHL Field Research Facility / by Michael W. Leffler ... [et al.] ; prepared for U.S. Army Corps of Engineers.

1998 ◽  
Author(s):  
Clifford F. Baron ◽  
Paul R. Hodges ◽  
Michael W. Leffler ◽  
Brian L. Scarborough ◽  
C. Ray. Townsend ◽  
...  
Keyword(s):  
Field Research ◽  
Army Corps ◽  
Annual Data ◽  
Army Corps Of Engineers ◽  
Research Facility ◽  
Corps Of Engineers
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