Use River Pollutant Modeling to Simulate and Predict the Change in the Damietta Branch Water Quality before and after Construction of the Ethiopian Dam

This research was conducted on the Damietta branch of the Nile River, Egypt. The Damietta branch receives pollution loadings from the Omar-Bek drain and two power stations located along the path of the branch. The main objective of this research consisted of comparing between the Damietta branch water quality before and after the Ethiopian Dam is built. This comparison was conducted by using the river pollutant (RP) modeling. First, the actual data and the modeling results were compared in order to prove the efficiency and validity of the RP modeling. Findings from regression analysis yielded a strong positive linear relationship (r = 0.987) between the two results. The modeling results showed that Omar-Bek drain had less impact on the Damietta branch water quality. The results also showed that the effluent discharge from the two power stations affected water quality and aquatic life because large quantities of warm and polluted water discharged back into the Damietta branch. The results also showed that constructing the Ethiopian Renaissance Dam would slightly increase pollutants concentrations in the Damietta branch and that this increase would cause a slight deterioration in water quality.

Visualization of real-time displacement time history superimposed with dynamic experiments using wireless smart sensors and augmented reality

Wireless smart sensors(WSS)process field data and inform inspectors about the infrastructure health and safety.In bridge engineering,inspectors need reliable data about changes in displacements under loads to make correct decisions about repairs and replacements.Access to displacement information in the field and in real-time remains a challenge as inspectors do not see the data in real time.Displacement data from WSS in the field undergoes additional processing and is seen at a different location.If inspectors were able to see structural displacements in real-time at the locations of interest,they could conduct additional observations,creating a new,information-based,decision-making reality in the field.This paper develops a new,human-centered interface that provides inspectors with real-time access to actionable structural data during inspection and monitoring enhanced by augmented reality(AR).It summarizes and evaluates the development and validation of the new human-infrastructure interface in laboratory experiments.The experiments demonstrate that the interface that processes all calculations in the AR device accurately estimates dynamic displacements in comparison with the laser.Using this new AR interface tool,inspectors can observe and compare displacement data,share it across space and time,visualize displacements in time history,and understand structural deflection more accurately through a displacement time history visualization.

Exploring Crowdsourced Hard—Acceleration and Braking Event Data for Evaluating Safety Performance of Low-Volume Rural Highways in Iowa

There are over four million miles of two-lane roadways across the United States, of which a substantial portion is low-volume roads (LVR). Traditionally, most traffic safety efforts and countermeasures focus on high-volume high-crash urban locations. This is because LVRs cover an extensive area, and the rarity of crashes makes it challenging to use crash data to monitor the safety performance of LVRs regularly. In addition, obtaining up-to-date roadway information, such as pavement or shoulder conditions of an extensive LVR network, can be exceptionally difficult. In recent times, crowdsourced hard-acceleration and braking event data have become commercially available, which can provide precise geolocation information and can be readily acquired from different vendors. The present paper examines the potential use of this data to identify opportunities to monitor the safety of LVRs. This research examined approximately 12 million hard-acceleration and hard-braking events over a 3-months period and 26,743 crashes, including 9373 fatal injuries over the past 5-year period. The study found a moderate correlation between hard acceleration/hard-braking events with historical crash events. This study conducted a hot spot analysis using hard-acceleration/hard-braking and crash datasets. Hotspot analysis detected spatial clusters of high-risk crash locations and detected 848 common high-risk sites. Finally, this paper proposes a combined ranking scheme that simultaneously considers historical crash events and hard-acceleration/hard-braking events. The research concludes by suggesting that agencies can potentially use the hard-acceleration and hard-braking event dataset along with the historical crash dataset to effectively supervise the safety performance of the vast network of LVRs more frequently.

Evaluation of Arterial Signal Coordination with Commercial Connected Vehicle Data: Empirical Traffic Flow Visualization and Performance Measurement

Emerging connected vehicle (CV) data sets have recently become commercially available, enabling analysts to develop a variety of powerful performance measures without deploying any field infrastructure. This paper presents several tools using CV data to evaluate traffic progression quality along a signalized corridor. These include both performance measures for high-level analysis as well as visualizations to examine details of the coordinated operation. With the use of CV data, it is possible to assess not only the movement of traffic on the corridor but also to consider its origin-destination (O-D) path through the corridor. Results for the real-world operation of an eight-intersection signalized arterial are presented. A series of high-level performance measures are used to evaluate overall performance by time of day, with differing results by metric. Next, the details of the operation are examined with the use of two visualization tools: a cyclic time-space diagram (TSD) and an empirical platoon progression diagram (PPD). Comparing flow visualizations developed with different included O-D paths reveals several features, such as the presence of secondary and tertiary platoons on certain sections that cannot be seen when only end-to-end journeys are included. In addition, speed heat maps are generated, providing both speed performance along the corridor and locations and the extent of the queue. The proposed visualization tools portray the corridor’s performance holistically instead of combining individual signal performance metrics. The techniques exhibited in this study are compelling for identifying locations where engineering solutions such as access management or timing plan change are required. The recent progress in infrastructure-free sensing technology has significantly increased the scope of CV data-based traffic management systems, enhancing the significance of this study. The study demonstrates the utility of CV trajectory data for obtaining high-level details of the corridor performance as well as drilling down into the minute specifics.

Effects of Increasing Rainfall Depths and Impervious Areas on the Hydrologic Responses

Hydrologic modeling is a popular tool for estimating the hydrological response of a watershed. However, modeling processes are becoming more complex due to land-use changes such as urbanization, industrialization, and the expansion of agricultural activities. The primary goal of the research was to use the HEC-HMS model to evaluate the impact of impervious soil layers and the increase in rainfall-runoff processes on hydrologic processes. For these purposes, the Watershed Modelling System (WMS) and Hydrologic Engineering Center’s-Hydrologic Modeling System (HEC-HMS) models were used in this study to simulate the rainfall-runoff process. To compute runoff rate, runoff volume, base flow, and flow routing methods SCS curve number, SCS unit hydrograph, recession, and loss routing methods were selected for the research, respectively. To reduce the processing time and computational complexity, a small section of the Pipestem Creek Watershed was selected to understand the methods and concepts associated with the hydrologic simulation model building. A DEM along with other required data such as land use land cover data, soil type data, and meteorological data was utilized to delineate the watershed in WMS. The output of WMS was utilized to run the HEC-HMS model for five different scenario analyses. All the relevant data were plugged in to the model to get the desired map. Subsequently, outlets at appropriate locations were selected for the sub-basin delineation for further analysis. Finally, the model was parametrized to get successful simulation results. Overall, peak discharges and runoff volumes were increased with increasing storm depths and impervious areas. Peak discharges were increased to 36% and 51% when rainfall depths were increased by 10% and 20% from the initial rainfall depth, respectively. Runoff volumes were also increased to 35% and 49% for the same scenarios, respectively. Peak discharges were increased to 12% and 78% with a 10% and 20%, respectively, increase in impervious areas. The runoff volumes were increased by 12% and 76% when impervious areas were increased by 10% and 20%, respectively. The simulation models responded well, and the peak discharges and runoff volumes increased with increasing storm depths and impervious areas.

Quantifying Operational Impacts of Variations in Work Zone Setups, Traffic Demand, and Traffic Composition: A Case Study

The presence of work zones due to pavement repair and rehabilitation is very common in highway facilities. Lane closures associated with work zones result in capacity reduction, which, in turn, often leads to increased congestion at such locations. This paper documents findings from a study that investigated the performance of freeway facilities in the presence of work zones under various Temporary Traffic Control (TTC) and lane closure scenarios while taking under consideration traffic composition and driving behaviors. The study site was an approximately 10-mile freeway segment of Interstate 65 (I-65) located in Birmingham, AL. The testbed was coded in PTV VISSIM, a microscopic simulation analysis platform, for: 1) baseline conditions (i.e., no work zone presence) and 2) work zone conditions with single lane closure (i.e., 3-to-2 lane closure). Work zone scenarios were coded for two TTC strategies, namely, early merge and late merge control and for three different positions of the lane closure (i.e., left, right, and center lane closures). The length of the work zones varied from 1000 to 2000, and 3000 ft. Sensitivity analysis was performed to document the operational impacts of varying heavy vehicle percentages, changes in drivers’ aggressiveness, and projected traffic demand changes. The impacts were quantified using linked-based measures of effectiveness (MOEs) such as travel time, and travel time index. The study results show that there is no significant change in travel time index due to the variation of work zone length across the study corridor. Under similar traffic control and demand conditions, a center lane closure consistently results in significantly higher travel time index than a left or right lane closure and should be avoided. Consideration of operational impacts of changes in truck percentage indicates that the corridor can absorb an increase in truck percentage from 10% to 15%, while performance rapidly deteriorates when a higher percentage of trucks is present in the traffic stream. The study findings can be used to guide transportation agencies in their future efforts to develop strategic lane closure plans that minimize congestion.

The Effects of Degradation Phenomena of the Steel-Concrete Interface in Reinforced Concrete Structures

Reinforced concrete (RC) constructions are the innovation of sustainable constructions replacing masonry constructions. Despite this, the use of concrete and steel to improve the performance of structural members in service is a recurring problem due to the immediate or overtime appearance of cracks. The objective of this work was therefore to assess the damage phenomena of the steel-concrete interface in order to assess the performance of an RC structure. Samples of approximately 30 cm of reinforcement attacked by rust were taken from broken reinforced concrete columns and beams in order to determine the impact of corrosion on high adhesion steel (HA) and therefore on its ability to resist. The experimental results have shown that the corrosion degradation rates of reinforcing bars of different diameters increase as the diameter of the reinforcing bars decreases: 5% for HA12;23.75% for HA8 and 50% for HA6. Using the approach proposed by Mangat and Elgalf on the bearing capacity as a function of the progress of the corrosion phenomenon, these rates made it possible to assess the new fracture limits of corroded HA steels. For HA6 respectively HA8 and HA12, their initial limit resistances will decrease by 4/4, 3/4 and 1/4. Based on the results of this study and in order to guarantee their durability, an RC structure can be dimensioned by taking into account the effects of reinforcement corrosion.

Quantifying the Impact of Transportation Network Companies on Urban Congestion in a Medium Sized City

In the recent years,TNCs(transportation network companies)and on-demand ridesharing services have grown rapidly.Given conflicting reports on TNC impacts,a need exists to study mode choice shifts in the presence of TNC services and their effects on urban congestion.Using Birmingham,AL(Alabama)as a case study,this paper showcases the feasibility of modeling TNC services using the MATSim(Multi-Agent Transport Simulation)platform,and evaluating the impact of such services on traffic operations.Data used for the study were gathered from Uber drivers and riders through surveys,as well as the US Census.The results indicate that when 200,400,and 800 TNC vehicles are added to the network,the VKT(vehicle kilometers traveled)increase by 22%,23.6%,and 23.2%,respectively,compared to the baseline scenario(no TNC service).Analysis of hourly average speeds,hourly average travel times,and hourly volumes along study corridors further indicate that TNC services increase traffic congestion,in particular,during the AM/PM peak periods.Moreover,the study shows that the optimal TNC fleet size for the Birmingham region is 400 to 500 active TNC vehicles per day.Such fleet size minimizes idle time and the number of TNC vehicles hovering,which have adverse impacts on TNC drivers,and the environment while ensuring TNC service availability and reasonable waiting times for TNC customers.

LSTM-based lane change prediction using Waymo open motion dataset: The role of vehicle operating space

Lane change prediction is critical for crash avoidance but challenging as it requires the understanding of the instantaneous driving environment.With cutting-edge artificial intelligence and sensing technologies,autonomous vehicles(AVs)are expected to have exceptional perception systems to capture instantaneously their driving environments for predicting lane changes.By exploring the Waymo open motion dataset,this study proposes a framework to explore autonomous driving data and investigate lane change behaviors.In the framework,this study develops a Long Short-Term Memory(LSTM)model to predict lane changing behaviors.The concept of Vehicle Operating Space(VOS)is introduced to quantify a vehicle's instantaneous driving environment as an important indicator used to predict vehicle lane changes.To examine the robustness of the model,a series of sensitivity analysis are conducted by varying the feature selection,prediction horizon,and training data balancing ratios.The test results show that including VOS into modeling can speed up the loss decay in the training process and lead to higher accuracy and recall for predicting lane-change behaviors.This study offers an example along with a methodological framework for transportation researchers to use emerging autonomous driving data to investigate driving behaviors and traffic environments.

Unveiling the Predictive Capabilities of Machine Learning in Air Quality Data Analysis: A Comparative Evaluation of Different Regression Models

Air quality is a critical concern for public health and environmental regulation. The Air Quality Index (AQI), a widely adopted index by the US Environmental Protection Agency (EPA), serves as a crucial metric for reporting site-specific air pollution levels. Accurately predicting air quality, as measured by the AQI, is essential for effective air pollution management. In this study, we aim to identify the most reliable regression model among linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), logistic regression, and K-nearest neighbors (KNN). We conducted four different regression analyses using a machine learning approach to determine the model with the best performance. By employing the confusion matrix and error percentages, we selected the best-performing model, which yielded prediction error rates of 22%, 23%, 20%, and 27%, respectively, for LDA, QDA, logistic regression, and KNN models. The logistic regression model outperformed the other three statistical models in predicting AQI. Understanding these models' performance can help address an existing gap in air quality research and contribute to the integration of regression techniques in AQI studies, ultimately benefiting stakeholders like environmental regulators, healthcare professionals, urban planners, and researchers.

Thermal Characteristics of Structural Lightweight Concrete

A higher cooling load is required with an increas­ing room temperature that resulted from the high thermal conductivity and low time lag of conven­tional construction materials[1].Such a high cooling load increases the carbon footprint from the energy consumption during building performance.The con­dition can be worsened with the urban heat island phenomenon,as the cooling load prolongs to night time for maintaining indoor thermal comfort.

Review of advanced road materials, structures, equipment, and detection technologies

As a vital and integral component of transportation infrastructure,pavement has a direct and tangible impact on socio-economic sustainability.In recent years,an influx of groundbreaking and state-of-the-art materials,structures,equipment,and detection technologies related to road engineering have continually and progressively emerged,reshaping the landscape of pavement systems.There is a pressing and growing need for a timely summarization of the current research status and a clear identification of future research directions in these advanced and evolving technologies.Therefore,Journal of Road Engineering has undertaken the significant initiative of introducing a comprehensive review paper with the overarching theme of“advanced road materials,structures,equipment,and detection technologies”.This extensive and insightful review meticulously gathers and synthesizes research findings from 39 distinguished scholars,all of whom are affiliated with 19 renowned universities or research institutions specializing in the diverse and multidimensional field of highway engineering.It covers the current state and anticipates future development directions in the four major and interconnected domains of road engineering:advanced road materials,advanced road structures and performance evaluation,advanced road construction equipment and technology,and advanced road detection and assessment technologies.

比较三种稳定剂对FeS纳米颗粒的稳定效果及对水土中镉的固定与去除性能的影响

本研究评估了三种多糖稳定剂(羧甲基纤维素钠(CMC)、羧甲基淀粉钠(CMS)和一种水溶性淀粉)用于稳定FeS纳米颗粒的有效性,并测试了相应稳定化纳米颗粒在水和土壤中固定Cd^(2+)的性能。使用0.010 wt%CMC、0.025 wt%CMS或0.065 wt%淀粉可获得完全稳定的FeS纳米颗粒(100 mg/L FeS)。CMC-FeS表现出较高的zeta负电位,淀粉-FeS保持中性,而CMS-FeS则表现出中等负电位。CMCFeS对Cd^(2+)的吸附速率最快,吸附容量也最高。当用100 mg/L CMC-FeS或CMS-FeS处理一种含Cd土壤(58.3 mg/kg Cd)后,Cd的TCLP浸出率分别降低了88.4%和68.0%。CMC-FeS和CMS-FeS均可在模型土壤中运移,显示出其在土壤中原位固定Cd^(2+)方面的潜力。土壤穿透曲线实验表明,CMC-FeS在4.5个孔体积,CMS-FeS在约25个孔体积处几乎完全穿透。柱实验结果表明,当用55个孔体积的CMC-FeS或CMS-FeS悬浮液(100 mg/L)处理该含Cd土壤后,Cd的水浸出率分别降低了98.2%和98.0%。根据目标污染物、材料在土壤中的传输特性和材料成本,可找到这三种稳定剂在土壤修复中的最佳应用。

Preface:Heavy metal(loid)s at mining&metallurgical sites:Fate,risk and remediation

The contamination of heavy metal(loid)s at mining&metallurgical sites has been a major environmental challenge worldwide[1].Typically,large amounts of metal(loid)s-bearing wastes are generated at these sites,such as smelting slag,combustion residues,mine tailings,wastewater,and exhaust gas[2].Due to their high mobility in the environment,the released heavy metal(loid)s can easily enter the soil and water environment,posing long-term and widespread threats to ecological and human health[3].

Damage detection of a thin plate using modal curvature via macrostrain measurement

Plate structures are employed as important structural components in many engineering applications. Hence, assessing the structural conditions of in-service plate structures is critical to monitoring global structural health. Modal curvature-based damage detection techniques have recently garnered considerable attention from the research community, and have become a promising vibration-based structural health monitoring solution. However, computing errors arise when calculating modal curvatures from lateral mode shapes, which result from unavoidable measurement errors in the mode shapes as identified from lateral vibration signals; this makes curvature-based algorithms that use a lateral measurement only theoretically feasible, but practically infeasible. Therefore, in this study, long-gauge fiber Bragg grating strain sensors are employed to obtain a modal curvature without a numerical differentiation procedure in order to circumvent the computing errors. Several damage indices based on modal curvatures that were developed to locate beam damage are employed. Both numerical and experimental studies are performed to validate the proposed approach. However, although previous studies have reported relative success with the application of these damage indices on a simple beam, only one damage index demonstrated the capability to locate damage when the stiffness of the local region changed near the sensor.

Effect of competing solutes on arsenic(Ⅴ) adsorption using iron and aluminum oxides

The study focused on the effect of several typical competing solutes on removal of arsenic with Fe2O3 and Al2O3. The test results indicate that chloride, nitrate and sulfate did not have detectable effects, and that selenium（Ⅳ） （Se（Ⅳ）） and vanadium（Ⅴ） （V（Ⅴ）） showed slight effects on the adsorption of As（Ⅴ） with Fe2O3. The results also showed that adsorption of As（Ⅴ） on A12O3 was not affected by chloride and nitrate anions, but slightly by Se（Ⅳ） and V（Ⅴ） ions. Unlike the adsorption of As（Ⅴ） with Fe2O3, that with Fe2O3 was affected by the presence of sulfate in water solutions. Both phosphate and silica have significant adverse effects on the adsorption of As（Ⅴ） adsorption with Fe2O3 and Al2O3. Compared to the other tested anions, phosphate anion was found to be the most prominent solute affecting the As（Ⅴ） adsorption with Fe2O3 and Al2O3. In general, Fe2O3 has a better performance than Al2O3 in removal of As（Ⅴ） within a water environment where multi competing solutes are present.

Evaluation of surface textures and skid resistance of pervious concrete pavement

Surface textures had long been recognized as primary factors to provide the skid resistance on pavements; however, no measurement of skid resistance on pervious concrete pavement with various surface texture parameters had been made. Fractal geometry was introduced in the present work to accurately simulate transect contour curves of pervious concrete specimens through fractal interpolation. It is proved that its fractal dimension (D) can be adopted to measure the skid resistance on pervious concrete pavement, overcoming the shortcomings of both macrotexture depth (DT ) and British portable pendulum number (NBP). Combined with Fujikawa-Koike tire/road contact model, the optimization method of all surface textures was recommended for designing and constructing excellently skid-resistant and noise-absorptive pervious concrete pavement. In addition, evaluating of the abrasion process and attenuation of the surface textures on concrete pavement slabs was also the focus of this work based on accelerated abrasion test. Results show that the surface textures on pervious concrete pavement slabs is extremely durable, compared to those on conventional grooved or exposed aggregate concrete pavement slabs.

Application of wavelet transform in structural health monitoring

Structural health monitoring(SHM)is a process of implementing a damage detection strategy in existing structures to evaluate their condition to ensure safety.The changes in the material,geometric and/or structural properties affect structural responses,which can be captured and analyzed for condition assessment.Various vibration-based damage detection algorithms have been developed in the past few decades.Among them,wavelet transform(WT)gained popularity as an efficient method of signal processing to build a framework to identify modal properties and detect damage in structures.This article presents the state-of-the-art implementation of various WT tools in SHM with a focus on civil structures.The unique features and limitations of WT,and a comparison of WT and other signal processing methods,are further discussed.The comprehensive literature review in this study will help interested researchers to investigate the use of WT in SHM to meet their specific needs.

Mechanical properties of pervious cement concrete

Compressive and flexural strength,fracture energy,as well as fatigue property of pervious cement concrete with either supplementary cementitious materials (SCMs) or polymer intensified,were analyzed.Test results show that the strength development of SCM-modified pervious concrete (SPC) differs from that of polymer-intensified pervious concrete (PPC),and porosity has little effect on their strength growth.PPC has higher flexural strength and remarkably higher flexural-to-compressive strength ratio than SPC at the same porosity level.Results from fracture test of pervious concrete mixes with porosity around 19.5% show that the fracture energy increases with increasing the dosage of polymer,reflecting the ductile damage features rather than brittleness.PPC displays far longer fatigue life than SPC for any given failure probability and at any stress level.It is proved that two-parameter Weibull probability function describes the flexural fatigue of pervious concrete.

Time-domain solution for transient dynamic response of a large-diameter thin-walled pipe pile

The propagation of stress waves in a large-diameter pipe pile for low strain dynamic testing cannot be explained properly by traditional 1D wave theories. A new computational model is established to obtain a wave equation that can describe the dynamic response of a large-diameter thin-walled pipe pile to a transient point load during a low strain integrity test. An analytical solution in the time domain is deduced using the separation of variables and variation of constant methods. The validity of this new solution is verifi ed by an existing analytical solution under free boundary conditions. The results of this time domain solution are also compared with the results of a frequency domain solution and fi eld test data. The comparisons indicate that the new solution agrees well with the results of previous solutions. Parametric studies using the new solution with reference to a case study are also carried out. The results show that the mode number affects the accuracy of the dynamic response. A mode number greater than 10 is required to enable the calculated dynamic responses to be independent of the mode number. The dynamic response is also greatly affected by soil properties. The larger the side resistance, the smaller the displacement response and the smaller the refl ected velocity wave crest. The displacement increases as the stress waves propagate along the pile when the pile shaft is free. The incident waves of displacement and velocity responses of the pile are not the same among different points in the circumferential direction on the pile top. However, the arrival time and peak value of the pile tip refl ected waves are almost the same among different points on the pile top.