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Catalytic pyrolysis behavior of synthesized microporous catalysts (conventional Zeolite Socony Mobil–5 (C-ZSM-5), highly uniform nanocrystalline ZSM-5 (HUN-ZSM-5) and β-zeolite), Mesoporous catalysts (highly hydrothermally stable Al-MCM-41 with accessible void defects (Al-MCM-41(hhs)), Kanemite-derived folded silica (KFS-16B) and well-ordered Al-SBA-15 (Al-SBA-15(wo)) were studied with waste polyethylene (PE) and polypropylene (PP) mixture which are the main constituents in municipal solid waste. All the catalysts were characterized by Brunauer-Emmett-Teller (BET), X-ray powder diffraction (XRD), and NH3-temperature programmed desorption (TPD). The results demonstrated that microporous catalysts exhibited high yields of gas products and high selectivity for aromatics and alkene, whereas the mesoporous catalysts showed high yields of liquid products with considerable amounts of aliphatic compounds. The differences between the microporous and mesoporous catalysts could be attributed to their characteristic acidic and textural properties. A significant amount of C2–C4 gases were produced from both types of catalysts. The composition of the liquid and gas products from catalytic pyrolysis is similar to petroleum-derived fuels. In other words, products of catalytic pyrolysis of plastic waste can be potential alternatives to the petroleum-derived fuels.

Motors are widely employed in mechatronic systems, especially in precision multiple degrees of freedom motion systems. In most applications, the dynamic equation between the motor instruction and the actual driving force is simplified as a constant. Subsequently, the static decoupling method can be utilized to design the feedback controller. However, in high-precision mechatronic systems, motor dynamics cannot be neglected, and the static decoupling performance is compromised due to discrepancies between motors. In this paper, a dynamic decoupling method is developed to improve the decoupling performance of the multiple-input multiple-output systems. The effects of transmission delays, motor dynamics, and discrepancies between different motors are taken into consideration in the dynamic decoupling method. Furthermore, a data-driven optimization method is developed to estimate the parameters of the dynamic decoupling controller. The effectiveness and superiority of the proposed method are demonstrated through numerical simulations. The experimental results show that the dynamic decoupling control method can achieve a 97.75% performance improvement at least compared to the static decoupling control method.

Due to its particularity and importance, long-distance oil and gas pipelines need to be well protected from damage by backfill materials. In this study, construction waste and expanded polystyrene (EPS) were used to replace conventional fine aggregate, and ethylene vinyl acetate-resin (EVA) was used to modify the surface of EPS to prepare lightweight controlled low strength materials (CLSM). Lightweight CLSM was tested in mechanics and physics and its microstructure was studied using microscopic analysis methods. The results revealed that the surface modification of EPS by EVA could greatly improve the compatibility of EPS with inorganic cementitious materials and prepare CLSM with a fluidity greater than 200 mm. EPS and cement content in cementitious materials play an important role in the development of material strength. When the volume ratio of EPS to construction waste was 2, and the content of cement in the cementitious materials was 35%, CLSM’s unconfined compressive strength at 28 days was only 0.48 MPa. In order to obtain the lightweight CLSM that meets the mechanical properties, the EPS content should not be too large. It can be concluded from the microscopic analysis that the increase of EPS content will lead to poor pore uniformity of the specimen, forming a loose mesh structure of defects, which is not conducive to the development of strength. In this study, EPS and construction waste are used to provide a green idea for preparing lightweight controlled low strength materials, which provides a reference for the backfill protection of the material in oil and gas pipelines in the future.

With the rapid growth of the oil and gas storage, transportation, and pipeline industries, it is necessary to improve the construction process of oil and gas pipelines. By combining the technical advantages of horizontal directional drilling and pipe jacking construction, the direct pipe laying method is suitable for pipeline crossing in different strata in the oil and gas, water conservancy and hydropower, and municipal industries due to its advantages of less construction land, high speed, and reversibility. Using the rapid jacking and laying of pipelines crossing Nanjuma River in the ‘Jingshihan’ gas pipeline double line project as a case study, this paper investigates the application status of the direct pipe laying method, summarizes the project, and introduces the construction of the working well, equipment selection, guiding control technology, supporting equipment installation, and drag reduction measures, as well as analyzes the influencing factors of thrust force and trajectory deviation combined with formation information.

Unlike some thermostatically controlled appliances (TCAs) with small capacities, Central Air-conditioner (CAC) has huge potential for demand response because of its large capacity. This paper presents a new CAC control strategy under multiple constraints. The CAC is modeled by three main modules: CAC central unit, water pumps, and temperature simulation of terminal users. The CAC’s power consumption is mainly determined by users’ load ratio. As the information and communication system have become the central nervous system of the smart grid, big data analysis is of great significance. Assuming that reliable two-way communication systems are preset, an integrated parameter priority list (IPPL) control strategy is used to control and monitor CAC. A new intelligent algorithm, Space Exploration and Unimodal Region Elimination (SEUMRE) algorithm, is introduced for solving the optimization problem of demand response targets generation under multiple constraints with the help of big data analysis. In this paper, influences and constrain factors, such as price and users’ comfortable levels are taken into account to satisfy the need of actual situation. Simulation results show that the proposed approach, when comparing with other typical optimization algorithms, yields better performances and efficiency.