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Solid wastes are increasingly used to stabilize marine soft clay. Disposals of alkali slag and steel slag cause serious problems in Lianyungang City. These two waste materials are used to produce the compound cementitious material by mixing with GGBS, replacing the cement to treat the soft clay in Xuwei Port. The raw materials are collected from fi...
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Blast furnace slag is one of the largest solid wastes in the world. The slag-based geopolymer obtained by alkali activation has many advantages, such as a high strength, a good corrosion resistance, low carbon and environmental protection. Existing studies have shown that the mechanical properties of slag-based geopolymers are related to the combin...
Citations
... The specific optimization process is shown in Fig. 19. This model has been proven to be effective in the study of highway construction [60,61]. ...
The compaction quality of a highway subgrade is influenced by the compaction parameters and soil properties. Current practice lacks reliable models to assess this multivariate situation. This paper describes a monitoring and evaluation method based on intelligent compaction (IC) and artificial neural networks (ANNs) to assess the compaction quality of a highway subgrade. Field compaction tests were conducted at various roller speeds and vibratory modes. The compactness was predicted using a particle-swarm-optimization optimized backpropagation neural network (PSO-BP-NN) model. The model was integrated into the IC system to automatically evaluate compaction quality. It also demonstrated the advantage of high prediction accuracy with multiple input variables of operation parameters and soil gradation. By efficiently controlling subgrade compaction, the model can be employed for engineering practice and facilitate IC applications.
... Several regression models have been used to assess the relationship between the ICMV and in situ data, but the accuracy is limited. Therefore, the ANN model is used to build the prediction model by integrating various characteristic values [56]. Zaman et al. [67] developed an ANN model to correlate the resilient modulus with subgrade soil properties. ...
The quality control of subgrade compaction depends on post-evaluations. The potential bias is caused by the limited coverage of spot tests at the construction site. Intelligent compaction is developed by integrating the sensing system on the vibratory roller and used at the construction site of the Rongwu highway to monitor the compaction quality in real time. The compaction meter value (CMV) is recorded for three months. The sand cone tests are performed following the roller passes. The CMV is proven to be proportional to the roller pass, and it is feasible to represent the compactness of subgrade soils. The linear regression model is developed based on the in situ measured compactness first. An artificial neural network (ANN) model is proposed to correlate the CMV and the compactness by considering the influences of soil properties and control parameters. The prediction model demonstrates good correlations. This study aims to establish a reliable model to improve the feasibility of IC, filling the gap between the continuously recorded CMV and the compactness. This model is to be integrated into the IC system for real-time assessing the compaction quality of subgrade.
Temperature segregation of asphalt mixture is one of the major reasons for pavement damage. The premise of ensuring desired properties of the asphalt mixture is to propose a reliable measuring method to monitor temperature variations before paving. Few existing studies focus on this issue due to the absence of suitable and efficient measuring instruments. This study proposes an innovative method to evaluate the temperature variation of asphalt mixture throughout the transportation process by combining the infrared camera and machine learning algorithms. Static and dynamic field tests are performed to measure the contact and non-contact temperatures of the asphalt mixture. A set of temperature measuring probes is specially designed. Influences of the measuring depth, measuring location, and environmental conditions are considered. Correlations between the infrared temperature and the contact temperature are identified using regression model, Support Vector Regression (SVR), and Extreme Gradient Boosting (XGBoost). The accuracy of the proposed model is verified against the experimental result.
Küresel ısınma ve iklim değişikliği Dünya'nın en önemli ve hızla çözülmesi gereken problemlerinden biri haline gelmiştir. Atmosferdeki kızılötesi ışınları tutarak küresel ısınma ve iklim değişikliğine sebep olan sera gazlardan bir tanesi de CO2 gazıdır ve çimento üretimi ile salınan CO2 gazı toplam salınımın %8’ini oluşturmaktadır. CO2 salınımının yanı sıra çimento üretiminde ortaya çıkan nitrik oksitler asit yağmurlarına neden olmaktadır. Atık ya da doğal mineralli malzemeler kullanılarak üretilen geopolimer beton, geleneksel betona göre daha az su kullanımı ve CO2 emisyonunu artırmaması açısından çevresel anlamda sürdürülebilirdir. Geopolimerler farklı kür koşullarında farklı malzemeler ve alkalin aktivatör kullanarak elde edilebilmektedir. Bu derleme makalede çimento yerine alümina silikat oranı yüksek atık malzemelerin bir alkalin aktivatör ile bağlayıcı özellik kazanması esasına dayanan geopolimerlerin zemin iyileştirme çalışmalarında kullanımı incelenmiştir.
