Preliminary Hydrogeologic Modeling and Optimal Monitoring Network Design for a Contaminated Abandoned Mine Site Area: Application of Developed Monitoring Network Design Software

In abandoned mine sites, i.e., mine sites where mining operations have ended, wide spread contaminations are often evident, but the potential sources and pathways of contamination especially through the subsurface, are difficult to identify due to inadequate and sparse geochemical measurements available. Therefore, it is essential to design and implement a planned monitoring net-work to obtain essential information required for establishing the potential contamination source locations, i.e., waste dumps, tailing dams, pits and possible pathways through the subsurface, and to design a remediation strategy for rehabilitation. This study presents an illustrative application of modeling the flow and transport processes and monitoring network design in a study area hydrogeologically resembling an abandoned mine site in Queensland, Australia. In this preliminary study, the contaminant transport process modeled does not incorporate the reactive geochemistry of the contaminants. The transport process is modeled considering a generic conservative contaminant for the illustrative purpose of showing the potential application of an optimal monitoring design methodology. This study aims to design optimal monitoring network to: 1) minimize the contaminant solute mass estimation error;2) locate the plume boundary;3) select the monitoring locations with (potentially) high concentrations. A linked simulation optimization based methodology is utilized for optimal monitoring network design. The methodology is applied utilizing a recently developed software package CARE-GWMND, developed at James Cook University for optimal monitoring network design. Given the complexity of the groundwater systems and the sparsity of pollutant concentration observation data from the field, this software is capable of simulating the groundwater flow and solute transport with spatial interpolation of data from a sparse set of available data, and it utilizes the optimization algorithm to determine optimum locations for implementing monitoring wells.

Performance Improvement of Two-Phase Steam Ejector based on CFD Techniques,Response Surface Methodology and Genetic Algorithm

The steam ejector is a crucial component in the waste heat recovery system.Its performance determines the amount of recovered heat and system efficiency.However,poor ejector performance has always been the main bottleneck for system applications.Therefore,this study proposes an optimization methodology to improve the steam ejector's performance by utilizing computational fluid dynamics(CFD) techniques,response surface methodology(RSM),and genetic algorithm(GA).Firstly,a homogeneous equilibrium model(HEM) was established to simulate the two-phase flow in the steam ejector.Then,the orthogonal test was presented to the screening of the key decision variables that have a significant impact on the entrainment ratio(ER).Next,the RSM was used to fit a response surface regression model(RSRM).Meanwhile,the effect of the interaction of geometric parameters on the performance of the steam ejector was revealed.Finally,GA was employed to solve the RSRM's global optimal ER value.The results show that the RSRM exhibits a good fit for ER(R^(2)=0.997).After RSM and GA optimization,the maximum ejector efficiency is 27.94%,which is 48.38% higher than the initial ejector of 18.83%.Furthermore,the optimized ejector efficiency is increased by 46.4% on average under off-design conditions.Overall,the results reveal that the combination of CFD,RSM,and GA presents excellent reliability and feasibility in the optimization design of a two-phase steam ejector.

Experimental Design Technique on Removal of Hydrogen Sulfide using CaO-eggshells Dispersed onto Palm Kernel Shell Activated Carbon：Experiment,Optimization,Equilibrium and Kinetic Studies

This study presents the use of chicken eggshells waste utilizing palm kernel shell based activated carbon（PKSAC） through the modification of their surface to enhance the adsorption capacity of H2S. Response surface methodology technique was used to optimize the process conditions and they were found to be： 500 mg/L for H2S initial concentration, 540 min for contact time and 1 g for adsorbent mass. The impacts of three arrangement factors（calcination temperature of impregnated activated carbon（IAC）, the calcium solution concentration and contact time of calcination） on the H2S removal efficiency and impregnated AC yield were investigated. Both responses IAC yield（IACY, %） and removal efficiency（RE, %） were maximized to optimize the IAC preparation conditions. The optimum preparation conditions for IACY and RE were found as follows： calcination temperature of IAC of 880 ℃, calcium solution concentration of 49.3% and calcination contact time of 57.6 min, which resulted in 35.8% of IACY and 98.2% RE. In addition, the equilibrium and kinetics of the process were investigated. The adsorbent was characterized using TGA, XRD, FTIR, SEM/EDX, and BET. The maximum monolayer adsorption capacity was found to be 543.47 mg/g. The results recommended that the composite of PKSAC and Ca O could be a useful material for H2S containing wastewater treatment.

Optimizing GSHP Performance with ICT and RETScreen Plus

Under the RHO （renewable heat obligation）, public buildings in the Republic of Korea must achieve an 11% overall reduction to thermal energy consumption in buildings more than 10,0O0 m^2. RETScreen Plus is a freely available software tool developed by the Canadian Government which can be used to develop energy baselines of clean energy technologies. Using curve-fitting and statistical methods like CUSUM, the software can combine actual energy performance with near real time weather information from NASA. We developed a method to simulate the performance of a GSHP （ground source heat pump）. The three distinct energy zones involve heating, no-energy, and cooling. RETScreen Plus methodology is used to develop curve fits for each distinct zone as it builds a correlation with NASA satellite data. The model then factors the impact of ICT （information and control technologies） as a means to improve and lower the building＇s energy consumption. Two values of COP （coefficient of performance） are used--the first is a standard ICT COP, while the second is an improved ICT COP with a smart controller. This methodology can then be expanded to incorporate current and future smart meter technologies, time of use rates, energy price signals, demand response and electricity storage options. In summary, this methodology enables a building owner or energy conservation official to quickly and accurately determine the baseline energy for a building and the potential impacts of smart ICT technologies, especially for buildings equipped with GSHP technologies.

Optimized production of a novel bioflocculant M-C11 by Klebsiella sp. and its application in sludge dewatering

The optimized production of a novel bioflocculant M-C11 produced by Klebsiella sp. and its application in sludge dewatering were investigated. The optimal medium carbon source,nitrogen source, metal ion, initial pH and culture temperature for the bioflocculant production were glucose, NaNO3, MgSO4, and pH 7.0 and 25°C, respectively. A compositional analysis indicated that the purified M-C11 consisted of 91.2% sugar, 4.6% protein and 3.9% nucleic acids（m/m）. A Fourier transform infrared spectrum confirmed the presence of carboxyl, hydroxyl,methoxyl and amino groups. The microbial flocculant exhibited excellent pH and thermal stability in a kaolin suspension over a pH range of 4.0 to 8.0 and a temperature range of 20 to 60°C.The optimum bioflocculating activity was observed as 92.37% for 2.56 mL M-C11 and 0.37 g/L CaCl2 dosages using response surface methodology. The sludge resistance in filtration（SRF）decreased from 11.6 × 1012 to 4.7 × 1012m/kg, which indicated that the sludge dewaterability was remarkably enhanced by the bioflocculant conditioning. The sludge dewatering performance conditioned by M-C11 was more efficient than that of inorganic flocculating reagents,such as aluminum sulfate and polymeric aluminum chloride. The bioflocculant has advantages over traditional sludge conditioners due to its lower cost, benign biodegradability and negligible secondary pollution. In addition, the bioflocculant was favorably adapted to the specific sludge pH and salinity.

Optimization of microwave-assisted extraction of wedelolactone from Eclipta alba using response surface methodology

An efficient microwave-assisted extraction tech- nique was used to extract wedelolactone from Eclipta alba. To optimize the effects of the microwave-assisted extraction （MAE） processing parameters on the yield ofwedelolactone, a response surface methodology with a central composite rotatable design was employed. Four independent variables were investigated： microwave power, ethanol concentration, extraction time and the solvent-to-solid ratio. The optimum conditions were： microwave power, 208 W; ethanol con- centration, 90%; extraction time, 26.5 min; and solvent-to- solid ratio, 33 mL.g-~. Under the optimal conditions, the extraction yield of wedelolactone was （82.67±0.16）%, which is in close agreement with the value predicted by the statistical model. MAE was also compared to other conventional methods, including ultrasonic assisted extrac- tion, extraction at room temperature and heat reflux extraction. MAE has distinct advantages for the extraction of wedelolactone in terms of both time and efficiency. Therefore, MAE is a reliable method for the extraction of wedelolactone from Eclipta alba.

Pseudomonas sp.ZXY-1,a newly isolated and highly efficient atrazine-degrading bacterium,and optimization of biodegradation using response surface methodology

Atrazine, a widely used herbicide, is increasing the agricultural production effectively, while also causing great environmental concern. Efficient atrazine-degrading bacterium is necessary to removal atrazine rapidly to keep a safe environment. In the present study, a new atrazine-degrading strain ZXY-1, identified as Pseudomonas, was isolated. This new isolated strain has a strong ability to biodegrade atrazine with a high efficiency of 9.09 mg/L/hr.Temperature, p H, inoculum size and initial atrazine concentration were examined to further optimize the degradation of atrazine, and the synthetic effect of these factors were investigated by the response surface methodology. With a high quadratic polynomial mathematical model（R^2= 0.9821） being obtained, the highest biodegradation efficiency of 19.03 mg/L/hr was reached compared to previous reports under the optimal conditions（30.71°C, pH 7.14, 4.23%（V/V） inoculum size and 157.1 mg/L initial atrazine concentration）.Overall, this study provided an efficient bacterium and approach that could be potentially useful for the bioremediation of wastewater containing atrazine.

Optimized synthesis and photovoltaic performance of TiO_2 nanoparticles for dye-sensitized solar cell

This paper presents response surface methodology （RSM） as an efficient approach for modeling and optimizing TiO2 nanoparticles preparation via co-precipitation for dye-sensitized solar cell （DSSC） perfor- mance. Titanium （IV） bis-（acetylacetonate） di-isopropoxide （DIPBAT）, isopropanol and water were used as precursor, solvent and co-solvent, respectively. Molar ratio of water, aging temperature and calcina- tion temperature as preparation factors with main and interaction effects on particle characteristics and performances were investigated, Particle characteristics in terms of primary and secondary sizes, crys- tal orientation and morphology were determined by X-ray diffractometry （XRD） and scanning electron microscopy （SEM）. Band gap energy and power conversion efficiency of DSSCs were used for perfor- mance studies. According to analysis of variance （ANOVA） in response surface methodology （RSM）, all three independent parameters were statistically significant and the final model was accurate. The model predicted maximum power conversion efficiency （0.14%） under the optimal condition of molar ratio of DIPBAT-to-isopropanol-to-water of 1 ： 10：500, aging temperature of 36 C and calcination temperature of 400 ℃. A second set of data was adopted to validate the model at optimal conditions and was found to be 0.14 ± 0.015%, which was very close to the predicted value. This study proves the reliability of the model in identi（ving the optimal condition for maximum performance.

Optimization of bits allocation and path planning with trajectory constraint in UAV-enabled mobile edge computing system

In this paper,an Unmanned Aerial Vehicle(UAV)enabled Mobile Edge Computing(MEC)system is studied,in which UAV acts as server to offer computing offloading service to the Mobile Users(MUs)with limited computing capability and energy budget.We aim to minimize the total energy consumption of MUs by jointly optimizing the bit allocation for uplink,computing at the UAV and downlink,along with the UAV trajectory in a unified framework.To this end,a trajectory constraint model is employed to avoid sudden changes of velocity and acceleration during flying.Due to high-order information in use,we lead to a more reasonable nonconvex optimization problem than prior arts.An Alternating Direction Method of Multipliers(ADMM)method is introduced to solve the optimization problem,which is decomposed into a set of easy subproblems,to meet the requirement on the efficiency in edge computing.Numerical results demonstrate that our approach leads a smoother UAV trajectory,significantly save the energy consumption for UAV during flying.

Performance-Driven Multi-Objective Optimization Method for DLR Transonic Tandem Cascade Shape Design

Transonic tandem cascades can effectively increase the working load,and this feature conforms with the requirement of the large loads and pressure ratios of modern axial compressors.This paper presents an optimization strategy for a German Aerospace Center(DLR)transonic tandem cascade,with one front blade and two rear blades,at the inlet Mach number of 1.051.The tandem cascade profile was parameterized using 19 control parameters.Non-dominated sorting Genetic algorithm(NSGA-II)was used to drive the optimization evolution,with the computational fluid dynamics(CFD)-based cascade performances correction added for each generation.Inside the automatic optimization system,a pressure boundary condition iterative algorithm was developed for simulating the cascade performance with a constant supersonic inlet Mach number.The optimization results of the cascade showed that the deflection of the subsonic blade changed evidently.The shock wave intensity of the first blade row was weakened because of the reduced curvatures of the optimized pressure and suction sides of the front blade part and the downstream moved maximum thickness position.The total pressure losses decreased by 15.6%,20.9%and 19.9%with a corresponding increase in cascade static pressure ratio by 1.3%,1.8%and 1.7%,for the three cascade shapes in the Pareto solution sets under the near choke,the design and near stall conditions,respectively.

Investigation of colloidal biogenic sulfur flocculation:Optimization using response surface analysis

The colloidal properties of biogenic elemental sulfur（S^0）cause solid–liquid separation problems,such as poor settling and membrane fouling.In this study,the separation of S^0 from bulk liquids was performed using flocculation.Polyaluminum chloride（PAC）,polyacrylamide（PAM）and microbial flocculant（MBF）were compared to investigate their abilities to flocculate S^0 produced during the treatment of sulfate-containing wastewater.A novel approach with response surface methodology（RSM）was employed to evaluate the effects and interactions of flocculant dose,pH and stirring intensity,on the treatment efficiency in terms of the S^0 flocculation and the supernatant turbidity removal.The dose optimization results indicated that the S^0 flocculation efficiency decreased in the following order PAC〉MBF〉PAM.Optimum S^0 flocculation conditions were observed at pH 4.73,a stirring speed of 129 r/min and a flocculant dose of 2.42 mg PAC/mg S.During optimum flocculation conditions,the S^0f locculation rate reached 97.53%.Confirmation experiments demonstrated that employing PAC for S^0 flocculation is feasible and RSM is an efficient approach for optimizing the process of S^0 flocculation.The results provide basic parameters and conditions for recovering sulfur during the treatment of sulfate-laden wastewaters.

Optimization and evaluation of fish oil rnicrocapsules

Fish oil microcapsules were prepared using two natural polysaccharides, alginate and chitosan, as the wall materials. A response surface methodology （RSM） was used to optimize the conditions for fish oil encapsulation efficiency （FOEE）. The FOEE was investigated with respect to three key-variables in the RSM： ratio of inner oil phase to aqueous phase （X1 w/w）; concentration of the aqueous phase （X2, wt%）; and ratio of the aqueous phase to outer oil phase （X3, v/v）. The optimal formulation obtained from the RSM model, i.e., 2.7：1 （X1）, 1.6 wt% （X2）, and 11.5：1 （X3）, gave a FOEE of 28%. The model was validated and the fish oil microcapsules prepared under the optimized conditions were characterized in terms of particle size, polydispersity index （PDI）, zeta potential, surface morphology, and in vitro release. The average droplet size, PDI, and zeta potential were 915 nm, 0.038, and ＋5.2 mV, respectively. The fish oil microcapsules were highly uniform microspheres, and had an accumulative release rate of 77.7% in 270 min in a gastrointestinal model, indicating their potential as an alternative carrier for the controlled release of fish oil. In conclusion, formulating optimal microencapsulation conditions by the RSM can be applied to the microencapsulation of various oil-soluble nutrients for food applications.

Deficiencies of streamline tracing techniques for designing hypersonic inlets and potential solutions

This work focuses on streamline tracing techniques for designing hypersonic inlets, and two deficiencies were discovered.Firstly, constriction ratios of stream-traced inlets are unpredictable and uncontrollable, which may affect the integration with airframes and combustors. Secondly, stream-traced inlets cannot exactly inherit properties from a basic flowfield through which they are traced. Then flow mechanisms underneath these phenomena were clarified. It was made clearly that properties of flow tubes captured by an inlet are what essentially determines constriction ratios as well as performances of inlets. Based on flow mechanisms, the method of calculating along streamlines(MCS) was proposed, which makes it possible to evaluate inlet performances directly. At last, optimization design methodologies were introduced to make inlet constriction ratios controllable,and simultaneously improve inlet performances as much as possible.

Modeling and multi-response optimization of machining performance while turning hardened steel with self-propelled rotary tool

There are many advanced tooling approaches in metal cutting to enhance the cutting tool performance for machining hard-to-cut materials. The self propelled rotary tool （SPRT） is one of the novel approaches to improve the cutting tool performance by providing cutting edge in the form of a disk, which rotates about its principal axis and provides a rest period for the cutting edge to cool and allow engaging a fresh cutting edge with the work piece. This paper aimed to present the cutting performance of SPRT while turning hardened EN24 steel and optimize the machining conditions. Surface roughness （Ra） and metal removal rate （rMMR） are considered as machining perfor- mance parameters to evaluate, while the horizontal incli- nation angle of the SPRT, depth of cut, feed rate and spindle speed are considered as process variables. Initially, design of experiments （DOEs） is employed to minimize the number of experiments. For each set of chosen process variables, the machining experiments are conducted on computer numerical control （CNC） lathe to measure the machining responses. Then, the response surface method- ology （RSM） is used to establish quantitative relationships for the output responses in terms of the input variables. Analysis of variance （ANOVA） is used to check the adequacy of the model. The influence of input variables on the output responses is also determined. Consequently, these models are formulated as a multi-response optimi- zation problem to minimize the Ra and maximize the rMMR simultaneously. Non-dominated sorting genetic algorithm-II （NSGA-II） is used to derive the set of Pareto-optimal solutions. The optimal results obtained through the pro- posed methodology are also compared with the results of validation experimental runs and good correlation is found between them.