Wenqi Zhao¹, Wenbin Sun^1,2,3,*, Zhenbo Cao¹, Jianbang Hao¹

Journal of Renewable Materials, Vol.11, No.7, pp. 3073-3089, 2023, DOI:10.32604/jrm.2023.026409

Abstract Mine grouting reinforcement and water plugging projects often require large amounts of grouting materials. To reduce the carbon emission of grouting material production, improve the utilization of solid waste from mining enterprises, and meet the needs of mine reinforcement and seepage control, a double-liquid grouting material containing a high admixture of coal gangue powder/bottom ash geopolymer was studied. The setting time, fluidity, bleeding rate, and mechanical properties of grouting materials were studied through laboratory tests, and SEM analyzed the microstructure of the materials. The results show that the total mixture of calcined gangue does not exceed 60%. And the proportion… More >

Vaishnavi Jayaraman¹, Arun Raj Lakshminarayanan^1,*, Saravanan Parthasarathy¹, A. Suganthy²

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 301-320, 2023, DOI:10.32604/iasc.2023.037823

Abstract Waste production rises in tandem with population growth and increased utilization. The indecorous disposal of waste paves the way for huge disaster named as climate change. The National Environment Agency (NEA) of Singapore oversees the sustainable management of waste across the country. The three main contributors to the solid waste of Singapore are paper and cardboard (P&C), plastic, and food scraps. Besides, they have a negligible rate of recycling. In this study, Machine Learning techniques were utilized to forecast the amount of garbage also known as waste audits. The waste audit would aid the authorities to plan their waste infrastructure.… More >

Xueqing Lu, Yuetao Shi^*, Jinsong Li

Energy Engineering, Vol.120, No.6, pp. 1325-1352, 2023, DOI:10.32604/ee.2023.026142

Abstract In this study, a model of combined cooling, heating and power system with municipal solid waste (MSW) and liquefied natural gas (LNG) as energy sources was proposed and developed based on the energy demand of a large community, and MSW was classified and utilized. The system operated by determining power by heating load, and measures were taken to reduce operating costs by purchasing and selling LNG, natural gas (NG), cooling, heating, and power. Based on this system model, three operation strategies were proposed based on whether MSW was classified and the length of kitchen waste fermentation time, and each strategy… More > Graphic Abstract

Jithina Jose^*, T. Sasipraba

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 573-588, 2023, DOI:10.32604/iasc.2023.030479

Abstract In recent decades, the generation of Municipal Solid Waste (MSW) is steadily increasing due to urbanization and technological advancement. The collection and disposal of municipal solid waste cause considerable environmental degradation, making MSW management a global priority. Waste-to-energy (WTE) using thermochemical process has been identified as the key solution in this area. After evaluating many automated Higher Heating Value (HHV) prediction approaches, an Optimal Deep Learning-based HHV Prediction (ODL-HHVP) model for MSW management has been developed. The objective of the ODL-HHVP model is to forecast the HHV of municipal solid waste, based on its oxygen, water, hydrogen, carbon, nitrogen, sulphur… More >

Peng Zhang¹, Dongsheng Shi^1,*, Ping Han^1,2, Wenchao Jiang^1,3

Journal of Renewable Materials, Vol.11, No.2, pp. 669-688, 2023, DOI:10.32604/jrm.2022.022192

Abstract The destruction of concrete building materials in severely cold regions of the north is more severely affected by freeze-thaw cycles, and the relationship between the mechanical properties and pore structure of concrete with fine aggregate from municipal solid waste (MSW) incineration bottom ash after freeze-thaw cycles is analyzed under the degree of freeze-thaw hazard variation. In this paper, the gray correlation method is used to calculate the correlation between the relative dynamic elastic modulus, compressive strength, and microscopic porosity parameters to speculate on the most important factors affecting their changes. The GM (1,1) model was established based on the compressive… More >

Gang Yu^1,4,5, Jian Tang^2,*, Jian Zhang³, Zhonghui Wang⁶

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 273-290, 2021, DOI:10.32604/iasc.2021.016981

Abstract Kernel learning based on structure risk minimum can be employed to build a soft measuring model for analyzing small samples. However, it is difficult to select learning parameters, such as kernel parameter (KP) and regularization parameter (RP). In this paper, a soft measuring method is investigated to select learning parameters, which is based on adaptive multi-layer selective ensemble (AMLSEN) and least-square support vector machine (LSSVM). First, candidate kernels and RPs with K and R numbers are preset based on prior knowledge, and candidate sub-sub-models with K*R numbers are constructed through utilizing LSSVM. Second, the candidate sub-sub-models with same KPs and… More >

Qin Liu^*, Ruliang Zhang

Energy Engineering, Vol.117, No.2, pp. 89-98, 2020, DOI:10.32604/EE.2020.010373

Abstract With the development of urbanization in China, the problem of garbage disposal has become increasingly serious. Among the existing waste treatment technologies, pyrolysis is an emerging treatment technology, which has obvious advantages in terms of reduction and secondary pollution. It has good development prospects. This article first compares the advantages and disadvantages of various existing waste treatment technologies, and proposes an organization method that combines thermogravimetric analysis, kinetic analysis, tube furnace experiments, and domestic waste pyrolysis and low-calorie heat the decomposed gases burn together. Urban garbage is one of the main pollution sources of modern urban environmental pollution in the… More >