Yuhui Wang

Use of parallel deterministic dynamic programming and hierarchical adaptive genetic algorithm for reservoir operation optimization

Reservoir operation optimization (ROO) is a complicated dynamically constrained nonlinear problem that is important in the context of reservoir system operation. In this study, parallel deterministic dynamic programming (PDDP) and a hierarchical adaptive genetic algorithm (HAGA) are proposed to solve the problem, which involves many conflicting objectives and constraints. In the PDDP method, multi-threads are found to exhibit better speed-up than single threads and to perform well for up to four threads. In the HAGA, an adaptive dynamic parameter control mechanism is applied to determine parameter settings, and an elite individual is preserved in the archive from the first hierarchy to the second hierarchy. Compared with other methods, the HAGA provides a better operational result with greater effectiveness and robustness because of the population diversity created by the archive operator. Comparison of the results of the HAGA and PDDP shows two contradictory objectives in the ROO problem-economy and reliability. The simulation results reveal that: compared with proposed PDDP, the proposed HAGA integrated with parallel model appears to be better in terms of power generation benefit and computational efficiency.

High-effective denitrification of low C/N wastewater by combined constructed wetland and biofilm-electrode reactor (CW–BER)

The low denitrification effect on constructed wetlands (CWs) treating low carbon to nitrogen ratio (C/N) wastewater was a problem. In this study, a novel coupled system by installing CW and biofilm-electrode reactor (CW-BER) was developed. In this system, the heterotrophic and autotrophic denitrifying bacteria all played their roles in denitrification process. The system was investigated systematically with simulated wastewater at different C/Ns, electric current intensities (I), hydraulic retention times (HRTs), and pH. Results showed that the optimum running conditions were C/N=0.75-1, I=15 mA, HRT=12 h, and pH=7.5. The highest removal efficiency of NO3-N and TN at the best conditions was respectively 63.03% and 98.11% for CW-BER. Also, the TN and NO3-N enhancive removal efficiency of CW-BER was 23.26% and 24.20%, respectively. No residual organic carbon source was detected in final effluent at the best parameters.

Nitrate removal and bioenergy production in constructed wetland coupled with microbial fuel cell: Establishment of electrochemically active bacteria community on anode.

The constructed wetland coupled with microbial fuel cell (CW-MFC) systems operated at different substrate concentration and pH influents were evaluated for bioelectricity generation, contaminant removal and microbial community structure. Performance of CW-MFC was evaluated at organic loading rate of 75.3gCODm-3d-1 and pH gradients of (5.18±0.14, 7.31±0.13, and 8.75±0.12) using carbon fiber felt as electrodes. Peak power density was observed at slightly neutral influent condition. Compared with the open circuit CW-MFC, average COD and NO3-N removal efficiency in CW-MFC increased by 8.3% and 40.2% respectively under slightly neutral pH of influents. However, the removal efficiency and bioenergy production have been inhibited with acidic influents. The relative abundance of beta-Proteobacteria, nitrobacteria and denitrifying bacteria was significantly promoted in closed-circuit CW-MFC. Using of CW-MFC as a biochemical method for nitrate removal and bioelectricity generation under slightly neutral and alkaline influent conditions was a promising technology.

Microbial community structure of different electrode materials in constructed wetland incorporating microbial fuel cell

The microbial fuel cell coupled with constructed wetland (CW-MFC) microcosms were operated under fed-batch mode for evaluating the effect of electrode materials on bioelectricity generation and microbial community composition. Experimental results indicated that the bioenergy output in CW-MFC increased with the substrate concentration; maximum average voltage (177mV) was observed in CW-MFC with carbon fiber felt (CFF). In addition, the four different materials resulted in the formation of significantly different microbial community distribution around the anode electrode. The relative abundance of Proteobacteria in CFF and foamed nickel (FN) was significantly higher than that in stainless steel mesh (SSM) and graphite rod (GR) samples. Notably, the findings indicate that CW-MFC utilizing FN anode electrode could apparently improve relative abundance of Dechloromonas, which has been regarded as a denitrifying and phosphate accumulating microorganism.

The inhibition and adaptability of four wetland plant species to high concentration of ammonia wastewater and nitrogen removal efficiency in constructed wetlands

Four plant species, Typha orientalis, Scirpus validus, Canna indica and Iris tectorum were selected to assess their physiological response and effects on nitrogen and COD removal to high total ammoniacal nitrogen (TAN) in constructed wetlands. Results showed that high TAN caused decreased relative growth rate, net photosynthetic rate, and leaf transpiration. C. indica and T. orientalis showed higher TAN adaptability than S. validus and I. tectorum. Below TAN of 200 mg L(-1), growth of C. indica and T. orientalis was less affected or even stimulated at TAN range 100-200 mg L(-1). However, S. validus and I. tectorum was obviously suppressed when TAN was above 100 mg L(-1). High TAN generated obvious oxidative stress showing increased proline and malondialdehyde contents, and superoxide dismutase was inhibited. It indicated that the threshold for plant self-bioremediation against high TAN was 200 mg L(-1). Whats more, planted CWs showed higher nitrogen and COD removal. Removal rate of C. indica and T. orientalis was higher than S. validus and I. tectorum.

High efficiency of inorganic nitrogen removal by integrating biofilm-electrode with constructed wetland: Autotrophic denitrifying bacteria analysis

The constructed wetland coupled with biofilm-electrode reactor (CW-BER) is a novel technology to treat wastewater with a relatively high level of total inorganic nitrogen (TIN) concentration. The main objective of this study is to investigate the effects of C/Ns, TIN concentrations, current intensities, and pH on the removal of nitrogen in CW-BER; a control system (CW) was also constructed and operated with similar influent conditions. Results indicated that the current, inorganic carbon source and hydrogen generated by the micro-electric field could significantly improve the inorganic nitrogen removal with in CW-BER, and the enhancement of average removal rate on NH3-N, NO3-N, and TIN was approximately maintained at 5-28%, 5-26%, and 3-24%, respectively. The appropriate operation conditions were I=10mA and pH=7.5 in CW-BER. In addition, high-throughput sequencing analysis implied that the CW-BER reactor has been improved with the relative abundance of autotrophic denitrifying bacteria (Thiobacillus sp.).

Flood simulation using parallel genetic algorithm integrated wavelet neural networks

The conventional means of flood simulation and prediction using conceptual hydrological model or artificial neural network (ANN) has provided promising results in recent years. However, it is usually difficult to obtain ideal flood reproducing due to the structure of hydrological model. Back propagation (BP) algorithm of ANN may also reach local optimum when training nodal weights. To improve the mapping capability of neural networks, wavelet function was adopted (WANN) to strengthen the non-linear simulation accuracy and generality. In addition, genetic algorithm is integrated with WANN (GAWANN) to avoid reaching local optimum. Meanwhile, Message Passing Interface (MPI) subroutines are introduced for distributed implement considering the time consumption during nodal weights training. The GAWANN was applied in the flood simulation and prediction in arid area. The test results of 4 independent cases were compared to reveal the relations between historical rainfall and runoff under different time lags. The simulation was also carried out with Xinanjiang model to demonstrate the capability of GAWANN. The numerical experiments in this paper indicated that the parallel GAWANN has strong capability of rain-runoff mapping as well as computational efficiency and is suitable for applications of flood simulation in arid areas.

Development of efficient and cost-effective distributed hydrological modeling tool MWEasyDHM based on open-source MapWindow GIS

Abstract Many regions are still threatened with frequent floods and water resource shortage problems in China. Consequently, the task of reproducing and predicting the hydrological process in watersheds is hard and unavoidable for reducing the risks of damage and loss. Thus, it is necessary to develop an efficient and cost-effective hydrological tool in China as many areas should be modeled. Currently, developed hydrological tools such as Mike SHE and ArcSWAT (soil and water assessment tool based on ArcGIS) show significant power in improving the precision of hydrological modeling in China by considering spatial variability both in land cover and in soil type. However, adopting developed commercial tools in such a large developing country comes at a high cost. Commercial modeling tools usually contain large numbers of formulas, complicated data formats, and many preprocessing or postprocessing steps that may make it difficult for the user to carry out simulation, thus lowering the efficiency of the modeling process. Besides, commercial hydrological models usually cannot be modified or improved to be suitable for some special hydrological conditions in China. Some other hydrological models are open source, but integrated into commercial GIS systems. Therefore, by integrating hydrological simulation code EasyDHM, a hydrological simulation tool named MWEasyDHM was developed based on open-source MapWindow GIS, the purpose of which is to establish the first open-source GIS-based distributed hydrological model tool in China by integrating modules of preprocessing, model computation, parameter estimation, result display, and analysis. MWEasyDHM provides users with a friendly manipulating MapWindow GIS interface, selectable multifunctional hydrological processing modules, and, more importantly, an efficient and cost-effective hydrological simulation tool. The general construction of MWEasyDHM consists of four major parts: (1) a general GIS module for hydrological analysis, (2) a preprocessing module for modeling inputs, (3) a model calibration module, and (4) a postprocessing module. The general GIS module for hydrological analysis is developed on the basis of totally open-source GIS software, MapWindow, which contains basic GIS functions. The preprocessing module is made up of three submodules including a DEM-based submodule for hydrological analysis, a submodule for default parameter calculation, and a submodule for the spatial interpolation of meteorological data. The calibration module contains parallel computation, real-time computation, and visualization. The postprocessing module includes model calibration and model results spatial visualization using tabular form and spatial grids. MWEasyDHM makes it possible for efficient modeling and calibration of EasyDHM, and promises further development of cost-effective applications in various watersheds.

Parameter optimization of distributed hydrological model with a modified dynamically dimensioned search algorithm

A modified version of the dynamically dimensioned search (MDDS) is introduced for automatic calibration of watershed simulation models. The distinguishing feature of the MDDS is that the algorithm makes full use of sensitivity information in the optimization procedure. The Latin hypercube one-factor-at-a-time (LH-OAT) technique is used to calculate the sensitivity information of every parameter in the model. The performance of the MDDS is compared to that of the dynamically dimensioned search (DDS), the DDS identifying only the most sensitive parameters, and the shuffled complex evolution (SCE) method, respectively, for calibration of the easy distributed hydrological model (EasyDHM). The comparisons range from 500 to 5000 model evaluations per optimization trial. The results show the following: the MDDS algorithm outperforms the DDS algorithm, the DDS algorithm identifying the most sensitive parameters, and the SCE algorithm within a specified maximum number of function evaluations (fewer than 5000); the MDDS algorithm shows robustness compared with the DDS algorithm when the maximum number of model evaluations is less than 2500; the advantages of the MDDS algorithm are more obvious for a high-dimensional distributed hydrological model, such as the EasyDHM model; and the optimization results from the MDDS algorithm are not very sensitive to either the variance (between 0.3 and 1) for randn used in the MDDS algorithm or the number of strata used in the Latin hypercube (LH) sampling.

Influences of iron and calcium carbonate on wastewater treatment performances of algae based reactors.

The influences of iron and calcium carbonate (CaCO3) addition in wastewater treatments reactors performance were investigated. Adding different concentrations of Fe(3+) (5, 10, 30 and 50mmol/m(3)), iron and CaCO3 powder led to changes in algal characteristics and physico-chemical and microbiological properties. According to the investigation results, nutrient removal efficiency in algae based reactors was obviously increased by the addition of 10mmol/m(3) Fe(3+), iron (5mmol/m(3)) and CaCO3 powder (0.2gm(-3)) and the removal efficiencies of BOD5, TN, and TP in Stage 2 were respectively increased by 28%, 8.9%, and 22%. The improvements in physico-chemical performances were verified by microbial community tests (bacteria quantity, activity and community measured in most probable number, extracellular enzymes activity, and Biolog Eco Plates). Microbial variations indicated the coexistence of Fe ions and carbonate-bicarbonate, which triggered the synergistic effect of physico-chemical action and microbial factors in algae based reactors.