Roadway Roughness Research Articles

Assessment of aircraft landing gear cumulative stroke to develop a new runway roughness evaluation index

ABSTRACT This study was undertaken to develop a new index, the Main Landing Gear Cumulative Stroke (MLGCS) index, to evaluate airport runway roughness. Using ADAMS/Aircraft software, we first developed and validated a virtual prototype model of the Boeing B737-800 aircraft and then employed the model to predict the aircraft’s dynamic responses with regard to roughness. Using this prototype model and comparing it to the International Roughness Index (IRI) that is designed to evaluate roadway roughness, we established a landing gear cumulative stroke (LGCS) model to represent runway roughness. The results show that taxiing speed is an important factor using the LGCS model. According to the most unfavorable scenario, we determined the LGCS of the nose landing gear to be 100 km/h and that of the main landing gear to be 60 km/h. These results underscore that, based on correlation analysis, using the cumulative stroke of the main landing gear is more reasonable than using that of the nose landing gear to evaluate runway roughness. Furthermore, based on measured data for 37 runways, a comparison of commonly used roughness indices indicates that the MLGCS index proposed in this paper is superior to both the Boeing Bump Index and the IRI.

Stochastic Analysis of Rolling Resistance Energy Dissipation for a Tractor-Trailer Model

Rolling resistance because of road roughness is often the largest contributor to energy consumption in the environmental assessment of pavement life cycle. Although fuel consumption of passenger vehicles caused by roadway roughness is well studied, further research is needed for truck fuel consumption models utilizing mechanistic approaches. Existing models estimating trucks’ excess fuel consumption because of rolling resistance are based on empirical models or simplified mechanistic models such as the quarter car model. Such approaches may not fully capture the complex dynamic motion of a tractor-trailer. This study suggests a stochastic method utilizing the analytical solution based on a tractor-trailer model to calculate excess truck fuel consumption because of roughness and speed. The illustrative examples show that excess truck fuel consumption tends to increase nonlinearly with roughness; fuel consumption increases with speed but drops after 104 km/h (65 mph) because of a rapid increase in aerodynamic drag at very high speeds. The effect of new generation wide-base tires (NG-WBT) in lieu of the standard dual tire assembly was studied using the introduced model. Results indicate that NG-WBT reduced excess fuel consumption because of roughness by 11% and 8% at 56 km/h and 80 km/h (35 mph and 50 mph), respectively. Finally, Monte Carlo simulation was conducted at two speeds and the simulation results were in agreement with the analytical solution. The results from the developed model and the validation using illustrative examples confirm the impact of roughness and speed on truck fuel consumption in a quantitative manner.

Assessing the effectiveness of probe vehicle acceleration measurements in estimating road roughness

In this article, we compare roadway roughness measured using a probe vehicle with roadway roughness calculated from the measured profile using an inertial profiler. Roughness is characterised by vehicle body vertical acceleration and probe vehicle roughness index (PVRI), which approximates the international roughness index (IRI) of a full car (rather than a quarter car). The reason the PVRI is used rather than the IRI is that acceleration measurements obtained from a probe vehicle represent the response of the full car rather than a quarter car. An important aspect of this article is that the same physical quantities are compared rather than obtaining a correlation between two different physical quantities. The results suggest that the roughness calculated from probe vehicle measurements is comparable with the roughness calculated from the measured profile; however, the investigation also revealed that data sampling frequency and quarter car parameters, specifically suspension damping and tyre stiffness, can have a significant effect on the measured PVRI.

Feasibility investigation for a bridge damage identification method through moving vehicle laboratory experiment

This paper investigated the feasibility of the pseudo-static damage identification method derived from a bridge–vehicle interaction system through a moving vehicle laboratory experiment. The element stiffness index, defined as the ratio of flexural rigidity of a damaged member to that of an intact member, serves as the damage indicator. Three vehicle models and two travelling speeds were considered in the experiment to examine the effect of vehicle's dynamic characteristic and travelling speed on identified results. It is demonstrated that locations and severities of damages are detectable using the proposed method in spite of the probable changes of roadway roughness and environmental conditions. In addition, adopting higher vehicle speed as well as the vehicle with frequency close to that of the bridge increased the probability of detecting damages.

Dynamic Analysis of Non-Uniform Continuous Girder Bridge under Moving Vehicle

For non-uniform continuous bridge in actual projects, the theoretical analysis and field testing of the dynamic response under moving vehicle are carried out. Firstly, Euler-Lagrange equation is applied to derive the vibration equation of three-axle vehicle. Then one obtains the dynamic analysis model by using the finite element method and the vehicle-bridge interaction equation based on the displacement coordination relationship of the contact between wheels and bridge. Lastly, numerical solutions are presented according to the dynamic response of the bridge, compared with the real values. The results show that: the roadway roughness and vehicle speed strongly influence the impact factor.

Effects of Pavement Roughness on Rigid Pavement Stress

ABSTRACTPavement roughness causes pavement stress fluctuation along the road. However, the dynamic effects were not taken into account in most pavement design and studies. To investigate the influences of roadway roughness on pavement stresses, this study developed a coupled system consisting of a quarter-car model and an equivalent lump pavement model. The coupled system also incorporated measured road profiles. By means of transfer function in frequency domain, the deflections and stresses of pavements were computed in seconds. The results were validated with Westergaard's solutions satisfactorily. It was found that the critical roughness, which might cause extreme responses, is related to the vehicle speed and suspension of vehicles. The maximum tension at the bottom of pavements also depends on the size of bump. In addition, the study demonstrates the correlation between roughness index, IRI, and ISO roughness classifications. It was also found that disturbance due to model boundary affects simulation results significantly.

Specifying Automated Pavement Condition Surveys

Between 1994 and 2004, the number of U.S. and Canadian Departments of Transportation (DOTs) using automated techniques to record pavement surface distresses increased fourfold to approximately 30. Twenty more U.S. state agencies can be expected to automate techniques in the near future. The typical agency will use vans traveling at highway speeds to automatically measure roadway roughness, rutting, joint faulting, and cracking. This paper describes the upgrade of the Alabama Department of Transportation's automated pavement condition data survey specifications. The objective of the paper is to provide information concerning costs, standards, and survey methodology that will be valuable to other DOTs as they add automation to their systems.

Three-dimensional dynamic analysis for bridge–vehicle interaction with roadway roughness

A three-dimensional means of analysis is proposed for the bridge–vehicle interaction to investigate the dynamic responses of a steel girder bridge and vehicles. The governing equations of motion for a three-dimensional bridge–vehicle interaction system taking the roadway surface into account are derived using the Lagrange equation of motion while the coupled bridge–vehicle interaction system is solved using Newmark’s β method. A cargo truck, dump truck and steel girder bridge are considered numerical models and measured roadway roughness profiles are used for analyses. The analytical dynamic wheel loads and acceleration responses of the heavy vehicles and responses of the bridge are compared with data from field tests to verify the validity of the proposed procedure. The correlation between the analytical and experimental results is satisfactory.

Computer simulation for dynamic wheel loads of heavy vehicles

The characteristics of dynamic wheel loads of heavy vehicles running on bridge and rigid surface are investigated by using three-dimensional analytical model. The simulated dynamic wheel loads of vehicles are compared with the experimental results carried out by Road-Vehicles Research Institute of Netherlands Organization for Applied Scientific Research (TNO) to verify the validity of the analytical model. Also another comparison of the analytical result with the experimental one for Umeda Entrance Bridge of Hanshin Expressway in Osaka, Japan, is presented in this study. The agreement between the analytical and experimental results is satisfactory and encouraging the use of the analytical model in practice. Parametric study shows that the dynamic increment factor (DIF) of the bridge and RMS values of dynamic wheel loads are fluctuated according to vehicle speeds and vehicle types as well as roadway roughness conditions. Moreover, there exist strong dominant frequency resemblance between bounce motion of vehicle and bridge response as well as those relations between RMS values of dynamic wheel loads and dynamic increment factor (DIF) of bridges.

EFFECTS OF SMALL TRAVEL SPEED VARIATIONS ON ACTIVE VIBRATION CONTROL IN MODERN VEHICLES

A stochastic optimal control procedure, based on a perturbation criterion, is developed to study effects of small travel speed variations on active suspensions of vehicles. The vehicle speed is regarded as an uncertain parameter that randomly varies around a measured (equilibrium) mean value. The approach here separates the active suspension forces into two control (laws) forces. The first force is termed steady (unperturbed) control force that isolates a vehicle body from a roadway disturbance and functions in large (mean) nominal speed variations starting from low to very high. The second force is termed a perturbation control force that accommodates changes in the steady force due to small speed variations. Eventually, after justifying the perturbation approach, it is shown how these two control forces could be combined to function only in terms of measured signals. The investigation is made of two different suspension structures for two levels of roadway roughness. Although the approach to the problem is approximate and needs perfect knowledge of all the state variables, the results show that there are noticeable variations to the steady control laws for even small deviations from nominal travel speed. In fact, the control procedure developed here as a design tool is meaningful since optimum vibration control problems are not easy to formulate when non-stationary random vibrations are considered. Also, it can be generalized with care to handle some parametric uncertainty problems.

Effects of Long Wavelength Component of Roadway Roughness on Traffic Vibrations Caused by Heavy Running Vehicles

Effects of Long Wavelength Component of Roadway Roughness on Traffic Vibrations Caused by Heavy Running Vehicles

Evaluation of Panel Characteristics and User-Based Pavement Serviceability

The effects of raters’ characteristics, vehicle classes, and highway classifications on panel ratings are described. Development of the present serviceability index (PSI) models as well as determination of the terminal PSI values for different highway classes in Taiwan also are investigated. Freeways and provincial highways as well as city streets were selected for use in evaluating road serviceability. A rating panel of 20 people rated the selected sections while they were in passenger cars and on buses. Pavement roughness also was measured with the Mays ride meter, and a manual distress survey was conducted to collect the pavement distress data. It is found that raters’ ages did not have a significant effect on the ratings, but factors of raters’ seat location on the bus, driving experience, and gender affected the ratings significantly. Another interesting finding is that raters tended to give lower ratings for freeways and provincial highways than for city streets, even if they were equally rough. Therefore, the terminal PSI of the former (2.1) was higher than that of the latter (1.8). Two PSI models that describe the relationship between panel ratings, pavement distresses, and roadway roughness are established and presented. Due to the large percentage of passengers who travel on buses within the city, a PSI model based on the ratings of city streets by a panel of raters on buses is recommended for the city system, and a PSI model developed from data for ratings of freeways and provincial highways by a panel of raters in passenger cars is recommended for highway systems.

Bridge dynamics and dynamic amplification factors — a review of analytical and experimental findings

The dynamic amplification factor (DAF) is an important parameter in the design of highway bridges and yet no worldwide consensus has been reached so far as to its value. Some disagreement exists between provisions of various national bridge codes. This is because the DAF depends, in addition to the maximum span or the natural frequency, on many other parameters that are difficult to take into account with reasonable accuracy. Vehicle speed, weight, and dynamic characteristics, the state of the structure, roadway roughness, expansion joints, the type of bridge supports, soil–structure interaction, and influence of secondary elements are some aspects influencing the DAF. This study reviews the analytical and experimental findings on bridge dynamics and the evaluation of the DAF. Key words: bridges, vibrations, bridge testing, bridge design codes, dynamic amplification factor.

Experimental Study of Bridge Monitoring Technique

Laboratory model tests were conducted to examine the feasibility of detecting structural deterioration in highway bridges by vibrational signature analysis. The model is a two‐span aluminum plate‐girder bridge that permits vibrations to be induced using vehicular excitation. The ambient vibration method was used to obtain vibrational signature elements. Data was processed both by curve fitting and by using a more automatable analytical approach. Using low‐mass vehicular excitation, ambient vibration results compare well with conventional modal analyses for resonant frequencies and mode shapes, but damping is overestimated. Roadway roughness and vehicle velocity do not influence resonant frequencies or mode shapes, although variable mass can have a significant impact on resonant frequencies. Vehicular mass influences on mode shapes appear to be minimal. Major structural degradation can cause significant changes to both resonant frequencies and mode shapes. Degradation is detectable using a readily automata...

NUMERICAL DATA BASE ON ROADWAY ROUGHNESS OF HIGHWAY BRIDGES

In this paper, the numerical data base (BINS) on roadway roughness of highway bridges is presented. The BINS is composed of the data bases (BINS 1 and BINS 2) of two kinds on longitudinal roughness and roughness of expansion joint point based on the roughness data measured by the authors. The BINS is supported by IBM computer 370/3090, and is made by EXEC I/O procedure using REXX language. IBM computer VM/SP above re-lease 4 is possible to use the system of the BINS.The applied examples of the BINS are presented to quantitatively investigate the characteristics of roadway roughness, and to give the technical data using the vibration problems of highway bridges under moving vehicles.

EFFECTS OF ROADWAY ROUGHNESS TO DYNAMIC RESPONSE OF HIGHWAY BRIDGES UNDER MOVING VEHICLES

The dynamic behavior of highway bridges under moving vehicles is analyzed, and then the effects of roadway roughness to dynamic response of the bridges are investigated quantitatively. In this study the dynamic behavior of bridges under moving vehicles is termed the “dynamic factor”, and the spectral characteristics of roadway roughness on bridges is classified into the four categories according to the method of evaluation of roadway condition indicating by authors's investigation. Numerical calculations are presented to investigate the effects of roadway characteristics to the dynamic response.

Standards and measurement of rail, road, and off‐road roughness

The application of surface roughness descriptions to vehicle roadways is reviewed in general terms. Vehicle roadways include railroad track, streets and roads (road vehicles), and off‐road terrain (agricultural tractors, earthmoving machines, etc.). The parameters of interest, measurement and analysis considerations, related standards, and the practical use of the data are discussed. The wavelengths of interest range from a few inches to a few thousand feet. The amplitudes of interest range from fractions of an inch to 10 or 12 ft. The application of fundamental descriptions of surface roughness to vehicle vibration theory illustrates and quantifies what we all observe, that the roadway roughness has much more influence on vehicle vibration than does the vehicle suspension. It is not practical to offset poor or deteriorated roads with improved suspension systems.

An Analytical and Experimental Study of Automobile Dynamics With Random Roadway Inputs

This paper presents the results of an analytical and experimental study of ride vibrations in an automobile over roads of various degrees of roughness. Roadway roughness inputs were measured. Three different linear mathematical models were employed to predict the acceleration response of the vehicle body. The models used included two, four, and seven degrees of freedom, primarily for vertical direction motion. The results show that the prime source of errors in predicting responses of this type lies in the common assumptions made for roadway roughness spectra. With adequate description of the roadway inputs, the results showed that the seven degree of freedom model accurately predicted the low frequency response (up to 10 Hz). Using the seven degree of freedom model, predicted accelerations compare well with measured data for a wide range of roadways in the low frequency range. Higher frequency components in the measured acceleration response are significant and are illustrated here.