Feasibility and assessment of using recycled rubber for infrastructure applications

“The United States needs to mine billions of tons of raw natural aggregate each year. At the same time, millions of scrap tires are stockpiled every year. Therefore, replacing natural aggregate with recycled crumb rubber aggregate will be beneficial to the construction industry and environment. This research aimed to investigate the feasibility of using recycled rubber in new construction applications. Based on size, recycled rubber was selected to match its natural counterpart. Different ratios of recycled crumb rubber were used as a fine aggregate replacement in concrete masonry units (CMUs) where the rubberized units showed a lower unit weight, higher ultimate strain, and better durability. In addition, the thermal conductivity of rubberized masonry units decreased with increasing the rubber content resulting in a reduction in heating energy consumption. In a different application, recycled crumb rubber was used as a full or partial replacement of coarse aggregate in chip seal surfacing where it shows better retention especially with longer curing time. The rubberized chip seal had a rougher surface which increases driving safety. Environmentally, the toxic heavy metals leached from the rubberized chip were below that of the EPA drinking water standards with a significant reduction of heavy metal leaching when rubber was used with emulsion in the form of chip seal. The third application was utilizing the waste of scrap tire processing in a form of rubber- fiber powder (RFP) as a sand replacement within cement mortar. RFP was used as an additive to provide more corrosion resistance and less heat of hydration of cement mortar. Incorporating RFP within plastering mortar disclosed that RFP can be used as an eco-friendly additive to provide better crack resistance, thermal and acoustical insulation as well as noise reduction”--Abstract, page iv

Effect Of Vehicle Speed And Weight On Raveling Of Chip Seal Constructed Using Mineral And Tire Derived Aggregate

The characteristics of the load applied by traffic, namely, vehicle speed and load magnitude, play a critical role in the raveling performance of chip seal pavement, which is often overlooked in literature. Furthermore, a sustainable chip seal constructed out of tire derived aggregate (TDA) has been recently introduced. Unlike mineral aggregate, rubber is a time-dependent material, and its properties are greatly influenced by the magnitude and rate of loading. Introducing TDA in chip seal has increased the significance and need to investigate the effects of vehicle speed and load on chip seal. This study investigated the raveling performance of different chip seal specimens constructed out of mineral and TDA, as well as a hybrid tire derived–mineral aggregate, under various loading speeds and magnitudes using a small-wheel traffic simulation device. The findings revealed that both load and speed significantly affect the texture loss of conventional and TDA chip seals, but in opposite ways. Conventional chip seals experienced increased texture loss with higher load and speed, while TDA chip seals showed a decrease. The use of TDA as an aggregate in chip seal resulted in a 23% reduction in macrotexture loss under increased load and a 56% reduction in macrotexture loss under increased speed compared with conventional chip seal. This improved performance is attributed to the dynamic properties of TDA, such as internal hysteresis, time-dependent behavior, and load transmissibility

Raveling Performance of Conventional and Rubberized Chip Seal under Field and Laboratory Traffic Loading

Raveling, or the Loss of Surface Aggregate, is a Major Concern in Chip Seal Pavement. Previous Studies Have Used the Standard Sweep, Vialit, and Pennsylvania Tests to Evaluate Raveling, But These Tests Do Not Replicate the Stresses of Rolling Vehicle Tires on Chip Seal and Have Produced Inconsistent Results. Additionally, These Tests Mainly Evaluate Early-Stage Raveling Due to their Short Curing Time. in This Study, a Small-Wheel Traffic Simulation Device (SWTS) Was Used to Apply Similar Stresses as Rolling Vehicle Tires and Produce Comparable Raveling Results. This Was Confirmed through a 13-Month Field Observation of Chip Seal, Where the Laboratory and Field Data Were Compared and Correlated. Both Conventional (Mineral Aggregate) and Eco-Friendly Rubberized Chip Seal with 25%, 50%, and 100% Crumb Rubber as Aggregate Were Tested in the Laboratory and Field. the Effects of Different Aggregate Types, Binder Application Rates, and Crumb Rubber Contents Were Studied. the Results Showed that Each Wheel Application by SWTS is Equivalent to 2.5 to 3 Passenger Car Passes in the Field. It Was Also Found that the Majority of Macrotexture Loss Occurred in the First 50,000 Passenger Car Equivalent Load. Up to 50% Replacement of Mineral Aggregate with Crumb Rubber Did Not Significantly Affect the Raveling Resistance But using More Than 50% Rubber Impaired the Raveling Resistance. using Crumb Rubber Instead of Mineral Aggregate Also Significantly Reduced Tire Wear and Microplastic Emissions from Vehicle Tires. Moreover, It Was Found that Pennsylvania and Vialit Tests May Not Be Suitable for Assessing Aggregate Retention under Traffic Load

Utilizing Waste Latex Paint Toward Improving The Performance Of Concrete

In this paper, incorporating the waste latex paint (WLP) into the conventional concrete as a partial replacement of sand to improve its durability was investigated. The fresh and hardened characterizations, in addition to the durability of concrete, were examined. The slump test was used to evaluate the fresh properties, while the hardened properties were evaluated through the volume of voids and absorption rate, in addition to the compressive, splitting tensile, and flexural strengths tests. The durability performance was evaluated by the surface resistivity, bulk electrical resistivity, as well as freeze and thaw resistance tests. The results showed a reduction in the workability with the addition of WLP, which required high dosages of superplasticizer to maintain the same slump in all the mixtures. Although there was a reduction in the compressive, splitting tensile, and flexural strengths, incorporating the WLP into the OPC concrete improved the durability significantly. Specimens had 5% and 10% of WLP passed the 300 freeze and thaw cycles without deterioration in the relative dynamic modulus of elasticity, compared with the reference mixtures that failed after only 144 cycles. Simultaneously, the surface and bulk electrical resistivity increased by approximately 125% and 138%, respectively, as result of reducing the volume of air voids that was decreased by 9%. The SE images and EDS spectrums showed denser cementitious matrixes with a film of polymeric layer covered the hydration products with adding waste latex paint

Nanoparticle Catalyzed Hydrodesulfurization of Diesel Fuel in a Trickle Bed Reactor: Experimental and Optimization Study

This work focuses on the preparation, simulation, and optimization of the hydrodesulfurization (HDS) of dibenzothiophene (DBT) using a nanocatalyst. A homemade nanocatalyst (3 percent Co, 10 percent Mo/γ-Al2O3 nanoparticles) was used in a trickle bed reactor (TBR). The HDS kinetic model was estimated based on experimental observations over ranges of operating conditions to evaluate kinetic parameters of the HDS process and apply the key parameters. Based on these parameters, the performance of the TBR catalyzed by the nanocatalyst was evaluated and scaled up to a commercial scale. Also, the selectivity of HDS reactions was also modeled to achieve the highest yield of the desired hydrogenation product based on the desirable route of HDS. A comprehensive modeling and simulation of the HDS process in a TBR was developed and the output results were compared with experimental results. The comparison showed that the simulated and experimental data of the HDS process match well with a standard error of up to 5%. The best reaction kinetic variables obtained from the HDS pilot-plant (specific reaction rate expression, rate law, and selectivity) TBR have been utilized to develop an industrial scale HDS of DBT. The hydrodynamic key factors (effect of radial and axial dispersion) were employed to obtain the ratio of the optimal working reactor residence time to reactor diameter

Forecasting photovoltaic power generation with a stacking ensemble model

Nowadays, photovoltaics (PV) has gained popularity among other renewable energy sources because of its excellent features. However, the instability of the system’s output has become a critical problem due to the high PV penetration into the existing distribution system. Hence, it is essential to have an accurate PV power output forecast to integrate more PV systems into the grid and to facilitate energy management further. In this regard, this paper proposes a stacked ensemble algorithm (Stack-ETR) to forecast PV output power one day ahead, utilizing three machine learning (ML) algorithms, namely, random forest regressor (RFR), extreme gradient boosting (XGBoost), and adaptive boosting (AdaBoost), as base models. In addition, an extra trees regressor (ETR) was used as a meta learner to integrate the predictions from the base models to improve the accuracy of the PV power output forecast. The proposed model was validated on three practical PV systems utilizing four years of meteorological data to provide a comprehensive evaluation. The performance of the proposed model was compared with other ensemble models, where RMSE and MAE are considered the performance metrics. The proposed Stack-ETR model surpassed the other models and reduced the RMSE by 24.49%, 40.2%, and 27.95% and MAE by 28.88%, 47.2%, and 40.88% compared to the base model ETR for thin-film (TF), monocrystalline (MC), and polycrystalline (PC) PV systems, respectively

Development of Kinetic and Process Models for the Oxidative Desulfurization of Light Fuel, Using Experiments and the Parameter Estimation Technique

YesThe oxidative desulphurization (ODS) of light gas oil (LGO) is investigated with an in-house designed cobalt 11 oxide loaded on alumina (γ-Al2O3) catalyst in the presence of air as oxidizing agent under moderate operating 12 conditions (temperature from 403 to 473 K, LHSV from 1 to 3 hr-1, initial concentration from 500 to 1000 13 ppm). Incipient Wetness Impregnation method (IWI) of cobalt oxide over gamma alumina (2% Co3O4/γ-14 Al2O3) is used for the preparation of the catalyst. The optimal design of experiments is studied to evaluate the 15 effects of a number of process variables namely temperature, liquid hourly space velocity (LHSV) and 16 concentration of dibenzothiophene and their optimal values were found to be 473 K, 1hr-1 and 1000 ppm 17 respectively. For conversion dibenzothiophene to sulphone and sulphoxide, the results indicates that the 18 Incipient Wetness Impregnation (IWI) is suitable to prepare this type of the catalyst. Based on the 19 experiments, mathematical models that represent a three phase reactor for describing the behavior of the ODS 20 process are developed. 21 In order to develop a useful model for simulation, control, design and scale-up of the oxidation process, 22 accurate evaluation of important process parameters such as reaction rate parameters is absolutely essential. 23 For this purpose, the parameter estimation technique available in gPROMS (general Process Modelling 24 System) software is employed in this work. With the estimated process parameters further simulations of the 25 process is carried out and the concentration profiles of dibenzothiophene within the reactor are generated

Optimal Design of a Trickle Bed Reactor for Light Fuel Oxidative Desulfurization based on Experiments and Modelling

YesIn this work, the performance of oxidative desulfurization (ODS) of dibenzothiophene (DBT) in light gas oil (LGO) is evaluated with a homemade manganese oxide (MnO2/γ-Al2O3) catalyst. The catalyst is prepared by Incipient Wetness Impregnation (IWI) method with air under moderate operating conditions. The effect of different reaction parameters such as reaction temperature, liquid hour space velocity and initial concentration of DBT are also investigated experimentally. Developing a detailed and a validated trickle bed reactor (TBR) process model that can be employed for design and optimization of the ODS process, it is important to develop kinetic models for the relevant reactions with high accuracy. Best kinetic model for the ODS process taking into account hydrodynamic factors (mainly, catalyst effectiveness factor, catalyst wetting efficiency and internal diffusion) and the physical properties affecting the oxidation process is developed utilizing data from pilot plant experiments. An optimization technique based upon the minimization of the sum of the squared error between the experimental and predicted composition of oxidation process is used to determine the best parameters of the kinetic models. The predicted product conversion showed very good agreement with the experimental data for a wide range of the operating condition with absolute average errors less than 5%

Convolutional Neural Networks using FPGA-based Pipelining

In order to speed up convolutional neural networks (CNNs), this study gives a complete overview of the use of FPGA-based pipelining for hardware acceleration of CNNs. These days, most people use convolutional neural networks (CNNs) to perform computer vision tasks like picture categorization and object recognition. The processing and memory demands of CNNs, however, can be excessive, especially for real-time applications. In order to speed up CNNs, FPGA-based pipelining has emerged as a viable option thanks to its parallel processing capabilities and low power consumption. The examination describes the fundamentals of FPGA-based pipelining and the basic structure of convolutional neural networks (CNNs). The current best practises for developing pipelined accelerators for CNNs on FPGAs are then reviewed, covering topics like partitioning and pipelining. Area and power limits, memory needs, and latency considerations are only some of the difficulties and trade-offs discussed in the article. In addition, the survey evaluates and contrasts the various pipelined FPGA accelerators for CNNs in terms of performance, energy consumption, and resource utilisation. Future directions and potential research areas are also discussed in the paper, such as the use of approximate computing techniques, the integration of reconfigurable architectures with emerging memory technologies, and the exploration of hybrid architectures that combine FPGAs and other hardware accelerators. This survey was created to aid researchers and practitioners in developing efficient and effective hardware accelerators for neural networks by providing a thorough overview of current trends and issues in FPGA-based pipelining for CNNs

Water Film Depth Prediction Model for Highly Textured Pavement Surface Drainage

Water film depth (WFD) is an important factor for road traffic safety because of its direct connection with skid resistance, hydroplaning speed, and the tendency of splash and spray. Increasing the pavement macrotexture reduces WFD. However, existing models for WFD prediction have not been developed on highly textured surfaces such as chip seal. Furthermore, the rainfall intensities used for developing most of these models were relatively low, leaving no or low WFD on chip seal surfaces. To propose a WFD prediction model suitable for highly textured surfaces and to consider the effect of surface material type, an experimental study was conducted with 154 different combinations of mean texture depth (MTD), surface material type, surface slope, drainage length, and rainfall intensity. The tests were carried out on chip seal specimens using a full-scale rainfall simulator. Test results from 1,784 WFD readings indicated that the Gallaway and PAVDRN models were not accurate for highly textured surfaces used in this study with MTD ranging from 0.05 to 0.20 in. Two experimental models were, therefore, proposed to predict the WFD; both models displayed a significantly higher correlation between the measured and predicted WFD compared with the existing models. Furthermore, the eco-friendly rubberized chip seal showed an enhanced drainage capability compared with conventional chip seal, especially in low slopes, because of the hydrophobic nature of crumb rubber versus the hydrophilic character of mineral aggregates. Accordingly, the proposed model incorporated a term to consider the effect of surface material type