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With the increase of complexity of Computer-Aided Engineering (CAE) models and practical problems, the evaluation cost of sheet forming simulation is commonly expensive. Surrogate models have been employed for efficient evaluations but trouble the problem of inverse scattering. Moreover, the accuracy of the forming evaluation based on the widely used Forming Limit Diagram (FLD) is influenced by the non-working regions. In this study, image-processing techniques are employed. Simultaneously, two novel image-driven Generative Inverse Networks (GINs) are proposed to improve the sheet-forming design's efficiency and accuracy. Through validations, GIN Version d (GIN-Vd) is more efficient and can obtain higher accuracy. However, because the desired optimum should be given in advance, such applications might be limited. In comparison, the GIN Version g (GIN-Vg) is more flexible. [ABSTRACT FROM AUTHOR]

In this study, a new type of ecological floating bed (NT-EFB) employing ornamental plants (either Spathiphyllum floribundum, Hydrocotyle sibthorpioids, Chlorophytum comosum or Peperomia obtusifolia) was designed to purify confected eutrophic water for 39 days. The growth characteristics of the plants and the effect of water treatment were analyzed and compared. The results showed that: (1) all the four ornamental plants examined survived well in the eutrophic water and an increase of plant biomass was observed; (2) the degradation efficiency of TOC by adding plants was about 85.0%; (3) the removal rate of NH4+–N was about 97.0%; (4) all the four plants can be used as floating bed plants to treat eutrophic water and Hydrocotyle sibthorpioids had the best growth characteristics and treatment efficiency. The study provides an adequate reference for the treatment of eutrophication using ecological floating beds. [ABSTRACT FROM AUTHOR]

The amide C-N cleavage has drawn a broad interest in synthetic chemistry, biological process and pharmaceutical industry. Transition-metal, luxury ligand or excess base were always vital to the transformation. Here, we developed a transition-metal-free hydrogen-bond-assisted esterification of amides with only catalytic amount of base. The proposed crucial role of hydrogen bonding for assisting esterification was supported by control experiments, density functional theory (DFT) calculations and kinetic studies. Besides broad substrate scopes and excellent functional groups tolerance, this base-catalyzed protocol complements the conventional transition-metal-catalyzed esterification of amides and provides a new pathway to catalytic cleavage of amide C-N bonds for organic synthesis and pharmaceutical industry. [ABSTRACT FROM AUTHOR]

Different types of acid pretreatment are known to influence the removal of certain components from pine wood sawdust, due to differences in the acid hydrolysis, which also predetermine the final formation and adsorptive properties of the produced activated carbon (AC) through subsequent potassium hydroxide activation. AC made by using phosphorous acid as an acid pretreatment had the largest absorption capacity of methylene blue (MB) dye due to its highest acidity. Subsequently, the effects on the adsorption variables for this AC such as initial pH, MB concentration, contact time and temperature were investigated. The resulting adsorption process was classified as pseudo-second-order kinetic model, and the Langmuir isotherm model better described the equilibrium data in comparison with the Freundlich isotherm model. The outcome showed that a lower temperature had an increased adsorption capacity of sawdust-derived AC pretreated with phosphorous acid, which allowed maximum adsorption capacities of 303.03 mg/g at 30 °C, implying that the adsorption was an endothermic process. Phosphorous acid pretreatment and activation processes proved to be an effective strategy to prepare highly porous AC from sawdust, with high potential to cationic dye removal from liquid phases. [ABSTRACT FROM AUTHOR]

Parameter identification or estimation is important to model simulations. This paper firstly carried out a sensitivity analysis of a water quality model using the Monte Carlo method. Then, two hybrid swarm intelligence algorithms were proposed to identify the parameters of the model based on the artificial bee colony and quantum-behaved particle swarm algorithms. One hybrid strategy is to use sequential framework, and the other is to use parallel adaptive cooperative evolving. The results of sensitivity analysis reveal that the average velocity and area of the river section are well identified, and the longitudinal dispersion coefficient is difficult to identify. The velocity is the most sensitive, followed by the dispersion and area parameters. Furthermore, the posterior parameter distribution and the collaborative relationship between any two parameters can be gotten. To verify the effectiveness of the proposed hybrid algorithms, this paper compared performances of the artificial bee colony, quantum-behaved particle swarm, their sequential combinations, and parallel adaptive dual populations. The experimental results demonstrate that the parallel dual population method is more effective than the original algorithms, when the data has added noise. [ABSTRACT FROM AUTHOR]

Dry anaerobic digestion of sewage sludge can recover biogas as energy; however, its low C/N ratio limits it as a single substrate in the anaerobic digestion. Rice straw is an abundant agricultural residue in China, which is rich in carbon and can be used as carbon source. In the present study, the performance of dry co-digestion of sewage sludge and rice straw was investigated under mesophilic (35 °C) and thermophilic (55 °C) conditions. The operational factors impacting dry co-digestion of sewage sludge and rice straw such as C/N ratio, moisture content, and initial pH were explored under mesophilic conditions. The results show that low C/N ratios resulted in a higher biogas production rate, but a lower specific biogas yield; low moisture content of 65 % resulted in the instability of the digestion system and a low specific biogas yield. Initial pH ranging 7.0-9.0 did not affect the performance of the anaerobic digestion. The C/N ratio of 26-29:1, moisture content of 70-80 %, and pH 7.0-9.0 resulted in good performance in the dry mesophilic co-digestion of sewage sludge and rice straw. As compared with mesophilic digestion, thermophilic co-digestion of sewage sludge and rice straw significantly enhanced the degradation efficiency of the substrates and the specific biogas yield ( p < 0.05) at the conditions of C/N ratio 26:1, moisture content 80 %, and natural initial pH. Although high concentrations of ammonia-nitrogen (NH-N, 1500 mg/kg wet weight) were formed during thermophilic digestion, there was no obvious inhibition occurred. The results indicated that rice straw can be used as carbon source for the dry co-digestion of sewage sludge under mesophilic and thermophilic conditions. [ABSTRACT FROM AUTHOR]

The removal of gaseous carbon disulfide (CS) via dielectric barrier discharge (DBD) combined with MnO catalysis has been investigated. CS removal and energy yield (EY) had been examined as a function of catalyzer position in DBD reactor, initial CS concentration, input power, and gas residence time. The results showed that DBD combined with MnO catalyst can improve the CS energy and removal efficiency, and MnO catalyst placed in afterglow area can enhance the CS removal efficiency by about 10 % as compared with DBD treatment only. When increasing initial CS concentration and flow rate, a higher EY is obtained. The possible CS removal pathways by DBD combined with MnO were proposed based on the product identification by FT-IR. [ABSTRACT FROM AUTHOR]

Fractal method has been widely applied to many different fields since it can reveal the hidden methodological structures of the sophisticated phenomena in the natural world and obtain more reasonable prediction results. This paper deals with the feasibility of predicting dissolved oxygen (DO) in complex watershed system using fractal method. It adopted sectioned variable dimension fractal model to predict river DO, and yielded satisfactory results with relatively high prediction accuracy. The absolute values of percent relative errors were all less than 6%, most less than 4%. Fractal interpolation method was also employed to simulate river DO by plotting interpolation DO graphs. These findings have important application potential in terms of water DO prediction in complex watershed system. [ABSTRACT FROM AUTHOR]