Truck Loading Research Articles

Design-truck ultimate limit states of buried modular polymer stormwater collection structures

Modular polymer stormwater structures are a relatively new class of buried structure with two horizontal platens supported by vertical columns. While structural demand at design truck loads has been quantified, the ultimate limit state to design truck loading is unknown. Full-scale physical experiments were conducted to quantify the applied load and identify the mode(s) of failure at the ultimate limit state of three types of modular structures when buried (with 0.6 m soil cover) and subject to static design truck loading. All three module types tested reached an ultimate limit state at applied loads around three times the nominal design load but had different modes of failure. The ultimate resistance for the module with columns having the lowest moment of inertia relative to length squared was caused by column buckling and top platen rupture, while the two modules with nearly twice the moment of inertia relative to length squared failed by top platen rupture and their column forces at most were 70%–75% of their short-term single column buckling resistance. The results provide new data to allow independent load rating of the buried structure, support continued assessment of column buckling, and identify the need to limit platen bending deflections.

LET’S GO

The project is entitled "Let’s Go." Let’s Go Web Application is a unified portal connecting load owners, truck brokers, transport companies, truck agents, truck and fleet owners, packers and movers, and others for efficient movement of goods. Let’s Go Web Application is convenient and intends to simplify the movement of goods by providing numerous options and creating a transparent, reliable, and time-saving approach for transactions between consignors and transporters. This help businesses by posting their loads online and receiving multiple bids from numerous transporters. Businesses save time and money by using our huge transportation network. Our platform facilitates load owners to book trucks online across India. Businesses can approach transport companies, truck owners, and logistics providers on a single platform. Let’s Go Web Application enables transporters to view multiple freight opportunities. It allows them to quote competitive truck fares to book a load. Transporters can work with numerous businesses across India and expand their trucking business. It has a user-friendly interface, and is dedicated to making each user's experience pleasant and beneficial. It's an online marketplace where the business owner and the transporter can work together in a transparent and mutually beneficial environment. Any person that has a load of material to be transported from one place to another. The person or organisation can be the owner of the load or an associate of the owner of the load. Transporters like fleet owners, truck owners, transport companies or agencies, truck brokers, business owners, etc. that have trucks available for movement from one place to another

A sequence-to-sequence model for joint bridge response forecasting

Knowledge of the structural response of bridges is extremely important for highway asset management and bridge structural health monitoring. Instrumenting every bridge in a road network and maintaining the monitoring instrumentation over decades of service can be financially infeasible. Mechanical intuition suggests a significant relationship exists between responses of two sets of bridges reasonably similar in design exposed to an identical load. This study explores the use of data-driven models to forecast the response of one bridge to a given truck load using the response of another bridge to the same loading profile. By deploying a modern monitoring system in multiple bridges in the same highway corridor integrated in a cyber-physical systems (CPS) framework, and utilizing advanced computer vision algorithms, the authors have gathered a unique dataset consisting of pairs of bridge responses to the same truck load from live traffic moving across a 32.2 km (20 miles) stretch of the I-275 highway in southeast Michigan. Signal processing techniques have been employed to isolate the response of the bridges to a single truck load in a time series of recorded responses. Then, a deep-learning-based time series forecasting framework using the encoder-decoder architecture with gated recurrent unit (GRU) and long short-term memory (LSTM) cells has been used for bridge response forecasting. Baseline models based on linear time series models are also developed to which the deep-learning forecasting models can be compared. After training the models, it is observed that deep-learning-based models can accurately forecast the response of one bridge using the response of another and reduce the forecasting root-mean-squared error (RMSE) by at least 20% relative to baseline linear models. The forecasting capabilities of the encoder-decoder architecture proposed herein outperform traditional approaches to response forecasting. Trained versions of the encoder-decoder forecasting model can be used to provide reliable estimates of bridge response using a single instrumented bridge in a corridor, thereby enhancing the value of data from instrumented bridges for asset management of bridge networks.

Intrinsic Properties of Composite Double Layer Grid Superstructures

This paper examined the opportunities of composite double-layer grid superstructures in short-to-medium span bridge decks. It was empirically shown here that a double-layer grid deck system in composite action with a thin layer of two−way reinforced concrete slab introduced several structural advantages over the conventional composite plate-girder superstructure system. These advantages included improved seismic performance, increased structural rigidity, reduced deck vibration, increased failure capacity, and so on. Optimally proportioned space grid superstructures were found to be less prone to progressive collapse, increasing structural reliability and resilience, while reducing the risk of sudden failure. Through a set of dynamic time-series experiments, considerable enhancement in load transfer efficiency in the transverse direction under dynamic truck loading was gained. Furthermore, the multi-objective generative optimization of the proposed spatial grid bridge (with integral variable depth) using evolutionary optimization methods was examined. Finally, comprehensive discussions were given on: (i) mechanical properties, such as fatigue behavior, corrosion, durability, and behavior in cold environments; (ii) health monitoring aspects, such as ease of inspection, maintenance, and access for the installation of remote monitoring devices; (iii) sustainability considerations, such as reduction of embodied Carbon and energy due to reduced material waste, along with ease of demolition, deconstruction and reuse after lifecycle design; and (iv) lean management aspects, such as support for industrialized construction and mass customization. It was concluded that the proposed spatial grid system shows promise for building essential and sustainable infrastructures of the future.

Generation of traffic input for flexible pavement design

Layered elastic theory (LET) was performed by Burmister. It helped to build mechanistic – empirical (M-E) pavement design. In this study, three different approaches were used to predict Cumulative Equivalent single axle load (C-ESAL) over the design period. Two were based on M-E and one was empirical. In each of these cases, standard axle loads were used as well as weight limits and vehicle classification, according to their axle configurations (single, tandem, tridem). Traffic data came from annual traffic census campaigns over the past ten years. Gross vehicle weight (GVW) and axle weight (AW) data came from a fixed weighing station performed during 31 days in 2020. Two road axis were considered: One having a weighing station (reference road) and one under technical studies (specific road). Traffic road data were used to perform regression analyses and predictions. AW and GVW helped to calculate Axle load equivalency factors (ALEF) and Truck equivalency factors (TEF) on the reference road. These values were projected on the specific road. Frequency distribution, gross vehicle weight distribution, axle load distribution of heavy vehicles are applied on the reference road. We performed overload AW and overload GVW analyses. Comparisons were done for the three approaches and an evaluation of technical studies was proposed, including traffic and AW monitoring and management systems. This work came as a basis for the transposition of M-E calculation of traffic inputs, more accurate and used over the passed fifty years, in Higher Income countries, called AASHTO method for USA, LCPC-SETRA method for France, to Cameroon and Sub-sahara African countries, that have been using empirical generation of traffic inputs over the same period, called CEBTP method.

An Evaluation of Asphalt Mixture Crack Resistance and Identification of Influential Factors

The crack resistance of asphalt pavement mixtures directly impact pavement service condition and pavement distress. And characterizing the crack resistance of a pavement mixture can reflect the crack resistance potential of asphalt pavement. This study analyzes several representative highway sections based on time, material, and service conditions to identify the mixture type of three layers. Semi-circular bending tests are conducted at 15 °C, and load–displacement curves are recorded. Factor independence analysis is performed, and combinations showcasing the cracking performance of the surface layer, middle layer, and bottom layer are selected. Analysis of variance (ANOVA) evaluating the indices versus selected factors for the three layers identifies significant influencing factors, and the crack resistance is analyzed based on these significant factors. The crack resistance of the middle layer with the highest truck loads is significantly lower than the two other lanes and the shoulder. Transverse crack spacing (TCS) can be used to directly evaluate the crack resistance of the mixture. The Factor dots upper rate (FUDR) and absolute Factor dots upper rate (absFUDR) indices are introduced to quantify the percentage deviation of a factor specimen from the average crack resistance index–fracture energy ratio, indicating whether the crack curve becomes sharper or flatter. The factor dots upper rate index is then applied to characterize the factors, and the results are reasonable. It is found only on the surface and middle layers that the service age has significant impacts on crack resistance, the Transverse crack spacing has significant impacts on crack resistance index, and the Factor dots upper rate can identify the brittleness of mixtures with different factors.

Mechanistic evaluation of segregation in HMA mixtures

Segregation in hot mix asphalt (HMA) mixtures is defined as the separation of the coarse aggregate particles in the mixtures from the rest of the mass. Segregation can be a result of aggregate stockpiling and handling, production, storage, truck loading practices, construction practices, and equipment adjustments. Segregation is usually evaluated visually, which is considered as a subjective method with no definite limits and depends on the evaluator’s opinion.This study uses two mechanistic surface texture indicators, i.e., mean texture depth (MTD) that is measured using sand patch method and mean profile depth (MPD) using laser texture profilometer to evaluate if a road section is segregated or not.The sand patch method is standardized in ASTM E965 -15 (2019) “for Measuring Pavement Macrotexture Depth Using Volumetric Technique”. MPD is covered by the international standards ASTM E1845-15 “Standard Practice for Calculating Pavement Macrotexture Mean Profile Depth”.Using both measured MTD values at grid point crossings, and average MPD values at 25 m intervals in the wheel paths, in addition to the use of statistical analysis of the obtained data, assuming that the obtained data are normally distributed and finding the 95% probability limits of the MTD and MPD values, it is possible to prove the closeness of the obtained texture depth indicator data, homogeneity of the road section, and that the segregation is only present at very limited localized locations.

Strength Performance of Alkali Activated Binder and Cement Stabilized Expansive Soil: A Field Study on Subgrade Layer

The dual character of expansive subgrade soil, which includes swelling and shrinkage, causes a premature collapse on the pavement surfaces. The scopes of the current study include comparison of the field performance of cement and alkali activated binder (AAB) stabilized expansive subgrade soil. To assess the strength properties, a 12 m long semi-field test section with expansive soil that has been treated with AAB, cement, and untreated expansive soil is built. Steel slag and fly ash are used as dry pozzolanic precursors in AAB, while sodium silicate and sodium hydroxide are used as an activator solution in a 0.4 water:solids ratio. AAB provides twin benefits of reducing the need for traditional binders and lowering the cost of fly ash/slag disposal in landfills. It also has a less carbon footprint than a PC-based binder, stronger mechanical strength and longer durability. By embedding a number of stress metres and strain gauges in the subgrade layer and applying a load through a dual-wheel truck load (12-tonne rear axle load) on the field track, the in-situ subgrade strength behaviour is assessed. On samples taken from the field section, the effects of AAB, curing duration, and the proportion of steel slag/fly ash in the alkaline soil mixture on the geomechanical properties of soil are examined. Additionally, using KGP-BACK software, falling weight deflectometer investigations were conducted to assess the elastic moduli of each layer. It has been noted that subgrade layers treated with AAB had larger elastic moduli than those treated with cement or left untreated. In comparison to cement-treated soil, the AAB mixture’s subgrade strength is increased by 23-26% by the combined addition of slag and fly ash. Based on the semi-field test section studies, recommendations for the effective application of AAB stabilisation for expansive soils as subgrade are given.

A hybrid approach for fatigue life prediction of in-service asphalt pavement.

Fatigue cracking is one of the main pavement failures, which makes accurate fatigue life prediction forthe design and maintenance of asphalt pavements crucial. The majority of traditional prediction methods are based entirely on the laboratory fatigue test, without considering the field condition and maintenance data. This paper aims to propose a hybrid approach to fill this gap. The key idea is that the damage condition isback-calculated by anartificial intelligence-based finite-element (FE) model updating using field-monitoring information (data-driven component), which is used to update the parameters in themechanistic composition-specific fatigue life prediction equation (model-driven component). The laboratory test of field cores gives the material non-destructive properties. The simulated pavement response subjected to truck loading shows good agreement with measured values, which indicates that the verified constitutive relationship could be used in the data-driven component. Furthermore, in view that the fatigue test is time- and money-consuming, this paper proposes a non-test estimation of thefatigue characteristic curve based on FE simulation of arepeated direct tension test. Three test pavement sections were employed as case studies. Results showed that the predicted fatigue life changes with the service time. At the early age, semi-rigid pavement has alarger fatigue life than flexible and inverted pavements. This article is part of the theme issue 'Artificial intelligence in failure analysis of transportation infrastructure and materials'.

Machine learning approaches to determining truck type from bridge loading response

The paper is concerned with the development and comparison of alternative machine learning methods of determining the type of truck crossing a bridge from the dynamic response it induces within the bridge structure, the so-called weigh-in-motion problem. Weigh-in-motion is a rich engineering problem presenting many challenges for current machine learning technologies, and for this reason is proposed as a benchmark for guiding and assessing advances in the application of this field of artificial intelligence. A review is first provided of existing methods of determining truck types and loading attributes using both machine learning and heuristic search techniques. The most promising approach to date, that of artificial neural networks, is then compared to support vector machines in a comprehensive study considering a range of configurations of both modeling techniques. A local scatter point smoothing schema is adopted as a means of selecting an optimal set of design parameters for each model type. Three main model formats are considered: (i) a monolithic model structure with a one-versus-all truck type classification strategy; (ii) an array of sub-models each dedicated to one truck type with a one-versus-all classification strategy; and (iii) an array of sub-models each dedicated to selecting between pairs of trucks in a one-versus-one classification strategy. Overall, the formats that used an array of sub-models performed best at truck classification, with the support vector machines having a slight edge over the artificial neural networks. The paper concludes with some suggestions for extending the work to a broader scope of problems.

Assessment of the Effect of Different Loading Combinations Due to Truck Platooning and Autonomous Vehicles on the Performance of Asphalt Pavement

Autonomous vehicles and truck platooning have become the future in the transportation field. This new strategy has many benefits because it lowers fuel consumption and CO2 emissions, improves safety, optimizes transport by using roads more effectively, and reduces traffic congestion. In this research, the effect of the controlled positioning of autonomous and non-autonomous truck loadings on the long-term performance of pavement was estimated using different variables such as climate, uniform wandering values of distance between trucks, and percentage of autonomous trucks by using MEPDG/AASHTOWare Pavement ME Design software. This was achieved by first computing the strain and stress of the different loading combinations, resulting in the computation of the failures in the pavement infrastructure and the pavement thickness needed to support each combination. The second part of the research consisted of designing a platoon strategy that was developed for a series of autonomous and connected trucks such that the lateral position of the trucks and the spacing between them could be explicitly optimized to minimize flexible pavement damage. The findings revealed that a small percentage of autonomous trucks can be beneficial to pavement life and that truck platooning following a well-studied skeleton can open a whole new world of pavement design. This can be revolutionary in changing roads around the world to improve traffic and infrastructure.

Evaluation of the load distribution of timber slab bridge and the efficiency of the retrofit methods

Timber slab bridges are commonly used in rural regions because of their simple construction and low costs. However, a review of the bridge manual indicates that there is no specific guidance or very similar guidance to the current nationwide bridge codes with respect to the calculation of wheel load distribution and strengthening/enhancing methods. The objective of this research is to evaluate the load distribution for timber slab bridges and the efficiency of the retrofit methods. To achieve this objective, ten timber slab bridges were identified for a program of bridge live load tests. Three of them were tested twice, once before and once after bridge strengthening measures were employed. The data collected from the field test program was utilized to calculate the equivalent strip width (ESW), and the results were compared with the codified values. In addition, a series of finite element (FE) models were created based on these ten field-tested bridges and validated against the field-collected data. The validated FE models were utilized for a parametric study to evaluate the wheel load distribution and the performance of various retrofit methods on the bridges with different truck loading, bridge geometry, and retrofit approaches. Based on the results from the field tests and analytical simulation, an equation to predict the equivalent strip width for the timber slab bridges was developed with consideration of numerous variables.

Performance Case Study of Concrete Bridge-Rail Post on Deck Overhang

Concrete post-and-beam bridge rails are a common bridge-rail type in the U.S. However, direct investigations of their performance on bridge-deck overhangs are rare, and current specifications do not clearly address this rail type or the design of decks supporting them. In this paper, the results of a performance case study of concrete bridge-rail posts on deck overhangs are presented. This study included (1) bogie testing of a MASH TL-4 concrete post on an instrumented deck, (2) development and calibration of a corresponding LS-DYNA model, and (3) use of the calibrated model to further describe system behavior, evaluate the effect of common design alternatives on performance, and corroborate the system performance from a full-scale crash test. The results of this study indicated that current design methods of the AASHTO LRFD Bridge Design Specifications (BDS) resulted in a significant underestimation of lateral capacity, partially because their neglect of inertial resistance. In the bogie test of the concrete post, over 40% of the peak lateral resistance of the post was attributed to inertial effects. Similarly, the calibrated LS-DYNA model indicated that the full-scale system could withstand a simplified single-unit truck (SUT) loading consisting of a 150 kip pulse load while only sustaining minor damage, despite having a BDS-predicted capacity of 73 kips. Additional findings included a characterization of deck demands, performance effects of design alternatives, such as edge distance and slab thickness, and the influence of using straight versus hooked transverse deck bars.

Intelligent control system of port turning line based on WITNESS software

Abstract In order to improve the efficiency of the intelligent control system of the port tipping line, this paper builds a port tipping line simulation intelligent control system based on WITHNESS software. Firstly, through ARTG (Konecranes Automation System) control switch, the simulation model of single-vessel loading and unloading transportation of the road network from the port front to the yard is established. Secondly, the Kalman filter algorithm and genetic algorithm are used to informally manage the port loading and unloading truck entry and exit data, and the assembly balance in the genetic algorithm is used to improve the data mining efficiency, and finally, the simulation system is tested for data. The results show that: the simulation system WITHNESS model constructed in this paper has an average time of 20.34 min for external collector trucks in the port dwell time, among which the number of vehicles with dwell time in [17/22] and [22/30] minutes is the majority accounting for a total of 60.7% of the total. Furthermore, the comparison of yard area reduction shows that the dwell time is 72.6%, 70.9%, and 87.5%, respectively, for yard area at different times. It can be seen that the simulation system WITHNESS model constructed in this paper helps to promote the development of port loading and unloading and can improve the effectiveness of loading and unloading work.

Fatigue reliability evaluation of reinforced concrete bridges under stochastic traffic loading based on truck weight limits

To investigate the fatigue reliability of reinforced concrete (RC) bridges under stochastic traffic loading and the effectiveness of limiting the truck load, this study presented an analysis method for evaluating the bridge fatigue reliability under the action of random traffic flows based on truck weight limits. Firstly, a simply RC T-beam bridge was selected as an example to illustrate the presented approach, and the traffic-induced stress spectrum of the tensile rebars in the critical girder of the bridge was obtained. Secondly, based on the collected traffic data from two specific areas, the corresponding random traffic flow was simulated respectively, and then calibrated using the weight limit referring to the current regulation and overload violation rates ( VR) to exclude overweight trucks. Finally, based on the S–N curve from Eurocode 3 and Miner’s cumulative damage model, the effects of violation rate, average daily truck traffic ( ADTT) and truck weight limit ( TWL) on the fatigue reliability index of the bridge were studied. The results show that heavy duty trucks will induce serious cumulative fatigue damage, and degrade the durability of RC bridges, while limiting the truck weight can obviously slow down the reduction of the fatigue reliability index. Both the ADTT and the VR can significantly affect the fatigue reliability of the bridge. More specifically, the bridge fatigue reliability index shows a clear downward trend with the increase in the ADTT and the VR. Furthermore, the performance to satisfy the target fatigue reliability of the bridge was compared between TWL for each type of trucks and unified TWL for all the trucks, and then the unified TWL for all the trucks are determined to ensure the target reliability index of the RC bridge after 100 years’ service life.

Load Distribution Factors For Horizontally Curved Composite Concrete-Steel Girder Bridges

This paper focuses on Load distribution factors for horizontally curved composite concrete-steel girder bridges. The finite-element analysis software“SAP2000” is used to examine the key parameters that can influence the distribution factors for horizontally curved composite steelgirders. A parametric study is conducted to study the load distribution characteristics of such bridge system due to dead loading and AASHTO truck loading using finite elements method. The key parameters considered in this study are: span-to-radius of curvature ratio, span length, number of girders, girders spacing, number of lanes, and truck loading conditions. The results have shown that the curvature is the most critical factor which plays an important role in the design of curved girders in horizontally curved composite bridges. Span length, number of girders and girder spacing generally affect the values of the moment distribution factors. Moreover, present study reveals that AASHTO Guide criterion to treat curved bridges with limited curvature as straight one is conservative. Based on the data generated from the parametric study, sets of empirical equations are developed for the moment distribution factors for straight and curved steel I-girder bridges when subjected to the AASHTO truck loading and due to dead loading.

Investigation of Backfill Compaction Effect on Buried Concrete Pipes

The present study deals with the experimental investigation of buried concrete pipes. Concrete pipes are buried in loose and dense conditions of gravelly sand soil and subjected to different surface loadings to study the effects of the backfill compaction on the pipe. The experimental investigation was accomplished using full-scale precast unreinforced concrete pipes with 300 mm internal diameter tested in a laboratory soil box test facility set up for this study. Two loading platforms are used namely, uniform loading platform and patch loading platform. The wheel load was simulated through patch loading platform which have dimensions of 254 mm *508 mm, which is used by AASHTO to model the wheel load of a HS20 truck. The pipe-soil systems were loaded up to pipes collapse. Pipes were instrumented with strain gauges to measure circumferential strains, in addition to dial gauges, for measurements of the pipe vertical deflections and settlement of the loading platforms. The test results indicated that flexure governed the buried pipe behavior. Flexural cracks formed slightly before the ultimate load. A comparison of soil backfill, between a loose and dense compaction, showed that the dense backfill improve largely the pipe installation and the strength ofpipe-soil system

Effect of support condition on the mechanical behavior of ductile iron pipes buried at shallow depth within the backfill of controlled low strength material

The effect of support condition on the performance of a ductile iron pipe (DIP) buried at shallow depth and backfilled using controlled low strength material (CLSM) is investigated in this study. CLSM as a backfill material has numerous benefits including self-leveling, no need of compaction, and fast return to traffic. However, the feasibility under critical burial condition should be further investigated. Two DIPs (diameters of 300 mm and 500 mm) installed at a shallow depth are the research objects of this study. Two support conditions are designated to evaluate DIP performance with CLSM as the backfill material. The first simulates the DIP sitting directly on a stiff underground structure such as a culvert. The second assumes that there is no support underneath the trench, simulating a situation that the soil is lost due to water leakage. These two detrimental support conditions lead to a higher than usual loading. The results show that the support condition has a significant influence on the DIP stress and the CLSM cracking behavior. The strength of the CLSM also has an effect on the cracking behavior. Overall, the two DIP specimens sustain linear reactions without plastic deformation under the design truck load. The cement-mortar lining of the DIPs only develops a few fine cracks, but neither peels nor falls off. The results of the two experiments in this study offer valuable information about the performance of DIPs buried at shallow depth and backfilled with CLSM. The observations are useful for the installation design and hazard mitigation of DIP and other pipe materials.

Evaluation of the Szapáry Long-Span Box Girder Bridge Using Static and Dynamic Load Tests

This paper presents the results of a recent field test carried out before the opening phases of the Szapáry motorway bridge across the Tisza River in central Hungary. The evaluation test was based on static and dynamic load tests that provided information on deflection, stresses, and dynamic mode shapes along the bridge. The structure has two large continuous independent steel box girders that cover spans across the floodplain and river. Various configurations of truck loading applied up to 6400 kN of loading on the deck. During the static tests, string potentiometers recorded deflections at mid-span. Additionally, strain gauges enabled strain/stress measurements at the mid-point of the longest span and directly above one support. Dynamic loadings showed variation in deflection response due to vehicle speed, and ambient vibration testing led to determining vibration modes and frequencies. A three-dimensional finite-element model produced similar deflections, stresses, and modal behavior. Measured and modeled deflections and stresses indicated that the bridge performed within design margins. The testing and analysis results will be part of a future program assessing conditioned-based maintenance.

Structural strengthening of a constructed timber bridge: Field application and numerical modeling

This paper presents the behavior of a timber bridge strengthened with lag bolts, carbon fiber reinforced polymer (CFRP) sheets, and hollow structural sections (HSS). The 83-old bridge is composed of three spans, supported by 14 Douglas Fir girders, and is tested employing truck loadings of 120 kN and 267 kN. Three-dimensional finite element models are formulated to study the flexural response of the bridge with and without the retrofit options. The magnitude of the truck load dominates the degree of dispersion in girder deflections and alters the shape of probability density functions, which are associated with behavioral uncertainty. The effectiveness of strengthening is apparent in terms of reducing the exceedance probability of deflection limits and increasing reliability indices above the design threshold of β = 3.5, stipulated in bridge specifications. Among the three methods, the stiffening efficiency of the HSS option is higher at the system level; however, the use of CFRP is most efficient at the member level. Live load distribution factors are examined and implementable recommendations are provided for practice. Parametric investigations clarify the efficacy of variable HSS sizes and the ramifications of a permit truck weighing 445 kN.