Highway Pavement Research Articles

Data cleaning framework for highway asphalt pavement inspection data based on artificial neural networks

ABSTRACT The acquisition of high-quality asphalt pavement inspection data is a key factor for road maintenance and management throughout the pavement’s life cycle. This paper establishes a data cleaning framework that is based on data mining and deep learning to eliminate abnormal data points and interpolate missing points to improve the accuracy of the original road inspection dataset. The first process in the proposed framework is to analyse the influential factors that are used to evaluate data quality and calculate the abnormality of the data through the confidence interval used in Gaussian fitting. Then, a deep artificial neural network is established to learn the mapping between the inspection data and data abnormality. The abnormal points are removed according to their abnormality level. Next, a second deep artificial neural network predicts the missing point values. Finally, by defining the overall cleanliness index of the dataset as the optimisation target, the steps are repeated until the cleanliness threshold is met. In this study, the proposed framework was applied to rut depth data cleaning for a highway maintenance project in Jiangsu Province, China. The cleanliness of the rut depth data increased by 6–95.75% after one cleaning cycle.

Fast material disintegration of cement concrete in the exterior

Over the recent years the amount of fast destruction defects of cement paste matrix has increased markedly for exposed concrete structures of highway and airport pavements. The accelerated destruction of silicate structure is unusual due to its irregular occurrence. It only occurs at 30 to 50% of newly built pavements (in continuous segments). The issue is applicable to loaded as well as unloaded pavements. Detailed diagnostics found that the probable cause is based on concurrently occurring expansive reactions in capillaries, cracks and pores in the cement paste matrix. In defect spots the presence of several expansive substances was proven, wherein the biggest question poses the unexpectedly high potassium concentration. Potassium is only contained at best in trace amounts in road concrete input components in the Czech Republic. Neither existing regulations nor standards sufficiently deal with this type of defects of cement concretes. If they mention the existence of this issue at all, they are just limited to recommendations. Since the modification of the existing commercially produced cements to pavements is still improbable, the solutions to this issue seem problematic.

Settlement Analysis of Dredged Material and Its Stabilization Using Surkhi/Brick Dust

Abstract: Soil stabilization is the phenomenon by virtue of which the soils are altered to enhance their physical Properties. The process aims to increase the shear Strength of soil thus improving its load bearing capacity to support pavements and foundations. Diverse range of soil materials varying from Expansive clays to granular materials can be treated by a diverse set of Additives like silica, lime, fly-ash, cement and so on. In J&K, the most common types of soils are the alluvial soils which get deposited in river beds as a result of sedimentation. River Jhelum in J&K is one of the major hotspots for accumulated sediments with an estimate of about 36 lakh cubic meters of sediments in its river bed, leaving very little space in it to take excess water. Subsequently, it is severely threatened by the Phenomena of still higher levels of sedimentation and hence consequent Floods. Dredging practices are a challenge for the maintenance of rivers and their Spillways. In Geotechnical Engineering, the valorisation of dredging Sediments and their Use in public works is increasingly prospected by Researchers in recent Years. Moreover, Floods in Kashmir valley in September 2014 compelled the Govt. Of Jammu and Kashmir to take Necessary steps in order to avoid similar situation in near future. This project therefore intends to study the stabilization of dredged material procured from Sindh Nallah having a higher content of alluvial Soil using Surkhi/Brick dust as an additive. Soil stabilization by this means can be utilized on airport pavements, highway pavements, earthen dams and many other situations where sub-soils are not suitable for construction. Keywords: Sindh Nallah, Dredged material, Surkhi, OMC, MDD, CBR, Direct Shear test.

Microstructure, 3-chemical moduli (3CM) and micro-spectral analyses of HSDA-treated black cotton soil for sustainable subgrade construction

Microstructural, 3-chemical moduli (3CM) and micro-spectral analyses has been carried out in this research work on HSDA-treated black cotton soil for sustainable subgrade construction. Black cotton soil (BCS) is considered problematic and incapable of withstanding axial load due to its erratically swell-shrink behavior on exposure to moisture. Sadly, hydraulically bound structures like the subgrade of highway pavement foundations are seasonally exposed to moisture through suction or capillary rise as the water table rises. So, the effect of treatment on the surface configuration, oxide composition and micro-graphical arrangement of the BCS has been studied. The BCS was characterized and classified as A-7 group soil with high plasticity and poorly graded condition. Sawdust ash was obtained by combusting sawdust and sieving through 2.35 mm aperture sieve. It was further activated by blending it with pre-formulated activator material (a blend of 8 M NaOH solution and NaSiO2 in 1:1 ratio) to generate HSDA. The HSDA was further used in wt % of 3, 6, 9, and 12 to treat the BCS. The treated samples were studied to their structure changes, 3-chemical moduli, and micrograph changes. XRF and SEM tests were conducted to determine the pozzolanic strength via the chemical oxide composition, 3-chemical moduli (3-CM) and the microstructural arrangement of the experimental materials and the treated BCS. The XRF tests showed that the experimental materials had less pozzolanic strength, which improved with the treated blends thereby forming stabilized mass of BCS. Also, it showed the silica moduli of the 3-CM dominated the stabilization of the soil with HSDA. SEM tests showed increased formation of ettringite and gels with the addition of the HSDA. Also, the ED-XRF chemical oxide and XRD micro-spectral studies showed great outcome at 12 wt% of HSDA and BCS blend with high formation of aluminosilicates above 70% and the formation of quartz and calcite, which showed HSDA potential as good supplementary cement.

Discussion on Water Stability Construction Technology of Highway Pavement

Discussion on Water Stability Construction Technology of Highway Pavement

AHP-DEMATEL Based Research on the Influencing Factors of the Daily Maintenance Costs of China's National and Provincial Trunk Highways

Highway maintenance is equally crucial across borders; this paper first conducts statistics and case study research on daily federal and provincial highway maintenance costs in China's principal influencing factors. Finally, it looks at those results with the tools of AHP-DEMAT. Yet, the overall degree of influence of each factor of influence is collected to classify the significant influence factors. The results found that: the main factors influencing the daily maintenance costs of national and provincial trunk highways are: highway grade, traffic flow, service life, structure type, topography, pavement thickness, and pavement width; the influence of climate factors on costs can be adequately considered when formulating standards for daily maintenance costs for provinces/regions with a broad geographic range.

A framework for transportation infrastructure cost prediction: a support vector regression approach

ABSTRACT Highway agencies and Departments of Transportation (DOTs) often face a challenge in estimating annual maintenance expenditures (AMEXs) to allocate available funds to various divisions in their jurisdictions. Few AMEX models were developed in the past, which are based on traditional statistical methods. This study introduces a support vector regression (SVR) approach to predict AMEX using data on the U.S. rural interstate highway pavement performance. Results show that the best SVR model is based on the Gaussian kernel and sequential minimal optimization algorithm. The developed SVR model can reliably predict the AMEX at the state level with a root mean squared error of 1.28. Entropy analysis results indicate the existence of mutual information (MI) between all the considered variables and the AMEX, with the highest MI value of about 79% between the AMEX and the number of lane miles with IRI values greater than 1.5 m/km.

Deformation analysis of pipe-jacking process for a large-section shallow-covered project crossing highway

This paper introduces an engineering example of a large cross-section shallow soil covered rectangular pipe jacking of East-West double track crossing expressway. The cross-section size of pipe jacking is 9.90m × 8.15m, the length of single section is 1.5m, the through length of east line and west line is 80m, and the thickness of soil covering is 2.48 ∼3.13M. In order to reduce the impact of pipe jacking construction on the expressway, measures such as setting of the frontal jacking pressure, the control of the friction resistance of the slurry sleeve, the control of the slurry pressure and the settings of φ 824 ×12@1100 steel pipe concrete curtain. The vertical displacement of the steel pipe curtain and the displacement of the highway pavement was monitored. The results show that the road surface heave is controlled within 3cm: the maximum heave of the north shoulder near the pipe curtain launching shaft is 27.8mm, the heave of the central road arch is 16.2mm ∼ 19.1mm, the maximum heave of the south shoulder near the receiving shaft is 12.7mm, and the maximum heave of each section is less than 1.5mm The position is the axis of pipe jacking machine. From the cross-sections of pipe jacking crossing, the range of transverse influence area of 5mm road uplift is about 2.0 ∼ 3.0 times the width of pipe jacking machine, and the range of transverse influence area of 10mm road uplift is 1.0 ∼ 2.0 times the width of pipe jacking machine. The monitoring results show that the construction parameters of pipe jacking are reasonable

Key Construction Techniques of Asphalt Mixture Paving in Highway Pavement Construction

Key Construction Techniques of Asphalt Mixture Paving in Highway Pavement Construction

Discussion on Key Points and Common Problems of Quality Supervision in Highway Pavement Construction

Discussion on Key Points and Common Problems of Quality Supervision in Highway Pavement Construction

Geosynthetic Reinforced Fill Material for Tennessee Bridge Approach Slab Support

The approach slab is constructed at bridge ends to serve as a smooth transition from the highway pavement to the bridge deck. However, motorists usually complain about a sudden change in elevation (bump) at the highway/approach slab (H/S) joint that causes a potential hazard for public safety, damage to vehicles, and rider discomfort. This paper develops a finite element (FE) analysis for the differential settlement at the H/S joint when supported by a strip footing that sits on compacted layers of soil embankment with uniaxial geogrid reinforcement. A parametric study was conducted to select the optimum design that consists of five geogrid layers equally spaced within a depth of 2 [Formula: see text] below the strip footing, where [Formula: see text] is the width of the footing. The inclusion of geogrid reinforcement did not only enhance the ultimate bearing stress of the strip footing but also redistributed the vertical loads over a wider region of soil embankment and thus reduced settlement. A case study is also presented for modeling the performance of a preliminary design proposed by Tennessee Department of Transportation (TDOT) for the retrofit of bridge ends. The FE analysis showed a 30%–40% improvement in the ultimate bearing stress of the strip footing when the geogrid reinforcement proposed by TDOT is extended to a depth of 1.5 [Formula: see text] below the footing.

Development of a Pavement Evaluation Tool Using Aerial Imagery and Deep Learning

AbstractThis paper presents the research results of using Google Earth imagery for visual condition surveying of highway pavement in the United States. A screenshot tool is developed to automatical...

An improved framework for volume change of shrink/swell soils subjected to time-varying climatic effects

The ability to estimate soil volume change as a function of time is a valuable tool in the design or forensic analysis of shallow foundations and pavement structures. This paper presents an improved framework for estimating the volume change of shrink/swell soils due to time-varying climatic effects using the Lytton et al. (2005) approach with the suction envelope models created by Vann & Houston (2021) and updated considerations of short-term varying climate. The procedure can be easily implemented in any country due to its mechanistic-empirical nature. The authors present an example calculation of the proposed framework using the data from an American Association of State Highway and Transportation Officials (AASHTO) Long-Term Pavement Performance (LTPP) Seasonal Monitoring Program (SMP) section, located approximately 80 miles northeast of Dallas, Texas. The volume change estimated from the proposed framework was compared to 70 measured data points from sections from the SMP study and the results look promising. The models are universal and can be used in any part of the world provided measured data is available to calibrate for local conditions. Ongoing calibration effort with the remaining LTPP SMP sections will allow obtaining calibration factors for the proposed framework that will improve the estimation of the volume change predictions under pavements and facilitate the implementation into current design procedures.

Carbon Fiber-Based Cementitious Composites for Traffic Detection and Weighing In Motion

New self-sensing cementitious composites embedded in the highway pavement for vehicle detection and weigh during motion is fabricated. Smart carbon fiber (CF) reinforced cement-based materials with high sensitive property are used as sensors. These smart composites may be able to detect the traffic and sense the weight in motion, thanks to their piezoresistive property. Cement-based sensors capability to vehicle detection was investigated in a real field at the University of Technology campus. Findings clarify that the CF-Based cementitious composites provide have a great potential to use as sensors for detect traffic and its composition also it possibly identifies different vehicular axle loadings (weigh during motion).

Highway alignments extraction and 3D modeling from airborne laser scanning point clouds

Accurate highway alignments and three-dimensional (3D) models are essential for various intelligent transportation applications. Airborne laser scanning (ALS) provides a desirable means of data collection, which increases data quality and collection efficiency. However, automatic alignments extraction and 3D modeling remain open problems. Therefore, this paper proposes an effective framework to extract highway alignments by minimizing an elaborate energy function and reconstruct highway 3D models with the restrictions of alignments. Specifically, the proposed method contains the following steps: (1) Adopt an adaptive method based on spatially smooth and interconnected grid cells to recognize highway pavement points from ALS data. (2) Extract pavement boundaries and lane markings from the pavement areas using the α-shape algorithm and a marking tracking strategy. (3) Extract highway alignments by minimizing an energy function and reconstruct highway 3D models with the restrictions of alignments. The method was validated in scenes of various highways, where the point density is 10–25 pts/m2. The extracted alignments respectively achieved the correctness of 90.67% and 99.25% and the completeness of 87.60% and 99.55% within 10 cm and 15 cm errors. The root mean square error (RMSE) of the generated 3D model is 2.4 cm on pavement and 5.8 cm on hills and slopes.

Calculation of Pavement Engineering Quantities of Mountainous Highway in Feasibility Study Stage

The reasonable estimation of the number of pavement works in the feasibility study stage of highway engineering construction project is one of the basis for the preparation of investment estimation. The selection of pavement structure layer and the calculation of thickness, the calculation of different terrain and pavement area is the main content of highway pavement quantity calculation in mountainous and hilly area. It is of great significance to select the correct calculation method according to different geological conditions. Through 10 engineering cases analysis, the paper analyzes the thickness and area calculation of the pavement structure of the mountain road. It is concluded that the pavement structure layer can be in the form of subbase + base + seal + surface layer. The influence of shoulder, subgrade retaining wall and middle separation zone should be considered in the calculation of pavement area.

Pay Factor Analysis for Highway Pavements through Percentage of Material within Specification Limits and Monte Carlo Simulation

Many state highway agencies (SHAs) have adopted pay adjustment provisions in their acceptance plans for construction and materials. In these payment adjustment acceptance plans, the percentage of material within specification limits (PWL) has been selected as the quality measure to relate production quality to pay factors, and pay equations are used to determine a pay factor for a lot based on PWL. Various pay equations have been proposed by the highway community for adoption in SHAs’ specifications. However, the effectiveness of these pay equations has not been fully evaluated. Another issue concerning the pay adjustment acceptance plans is the risk associated with single and multiple pay factors. The purpose of this study was to evaluate the effects of different pay equations commonly used by SHAs and the risks associated with pay adjustment acceptance plans. This was achieved by developing operating characteristic curves associated with various pay factors and expected pay curves and Monte Carlo simulation for assessing the effects in the long run. The methodology suggested in this paper is transferable elsewhere where similar materials and specifications are used for the acceptance of pavements.

Use of scoria waste as subbase stabilization material for highway flexible pavement

Usability of scoria waste as subbase stabilization material was investigated. Initially, the physical properties of scoria waste were examined. The usage of scoria waste in subbase layer of the pavement was investigated. In the study, experimental researches such as stability to freeze, solidity, strength, Atterberg limits and California Bearing Ratio tests were carried out on samples prepared by using scoria waste. Scoria and natural quarry materials were blended in different amounts to prove the percentage of plastic limit. Then, the limit tests were carried out on the prepared mixtures. The strength of the samples obtained by using reusable material was determined with the California Bearing Ratio (CBR) test. According to the obtained results, it was observed that the usage of scoria wastes as stabilization material in the subbase layer of flexible pavements is appropriate. Moreover, mechanical stabilization with scoria wastes has positive impact in increasing of the mechanical properties of the new mixed composite material.

Comparison of dynamic elastisty modulus with different prediction approaches for Karaman – Konya highway pavement

In pavement design and analysis processes among mechanistic-empirical pavement design method, defining the Dynamic Elasticity Modulus(E*) of asphalt layers are very important. In analysis processes, predicting the deteriorations and E* requires some special devices and a lot of time. To simplify this process different prediction models and different approaches have been developed to predict E*. These prediction approaches prepared with huge amount of input data gathered both from construction site and laboratory tests to predict the binder and the volumetric properties of the HMA. In this paper four prediction equations have been applied to predict E* and compared the results with each other. The infrastructure model has chosen as an existing highway section with known HMA material properties. The analyses have done for five different temperatures (10⁰F, 40⁰F, 70⁰F, 100⁰F and 130⁰F) by using two different frequency values (4Hz and 10 Hz). The aim of this research study is doing a comparative assessment of four widely used E* prediction models. Results have shown a large bias between compared E*prediction results due to temperature, frequency, and material properties. Higher Frequency and newest models have shown higher E* values.

An Optimized Superplasticized Microsilica Concrete for Flexible Highway Pavement

An Optimized Superplasticized Microsilica Concrete for Flexible Highway Pavement