New approach to unsupported ReS2 nanorod catalyst for upgrading of heavy crude oil using methane as hydrogen source

Highly active ReS₂ nanocatalysts were prepared by CVD method and characterized by XRD, BET -BJH, Raman spectroscopy, XPS, TPR, NH₃-TPD, SEM, and HRTEM techniques. Catalytic activities were used in upgrading heavy crude oil using methane as hydrogen source. The results showed a significant increase in API and decrease in sulfur and nitrogen content of crude oil. RSM technique was used to investigate the interactive effects of temperature (200–400 °C), pressure (20–40 bar) and dosage of nanocatalyst (0.5–2 wt. %) on the performance of HDS reaction. The results represent that the maximum predicted HDS activity (74.375%) was estimated under the optimal conditions (400 °C, 20 bars, and 2 wt % of nanocatalyst). Also, the effect of reaction temperature, pressure and dosage of ReS₂ nanorods catalyst on HDN of heavy crude oil was investigated and highest efficiency in the HDN process (93%) occurred at 400 °C and 40 bar using 2 wt % ReS₂.     

响应面法优化超声辅助提取杜仲叶中的绿原酸

采用超声辅助法对杜仲叶中绿原酸的提取工艺进行研究。在单因素试验的基础上,采用Box-Benhnken中心组合进行三因素三水平的试验设计,通过回归分析各工艺参数与响应值之间的关系,并由此预测最佳的工艺条件。绿原酸含量通过高效液相色谱法(high performance liquid chromatography,HPLC)测定。结果表明,杜仲叶绿原酸最佳的提取工艺条件为:提取时间75 min,甲醇体积分数70%,超声功率270 W,提取温度45℃,绿原酸的提取得率预测值为2.532%,而在此试验条件下,绿原酸提取得率为2.529%。     

Microwave vacuum drying and puffing of the meat tissue - process analysis

Tenderization based on papain and microwave vacuum drying and puffing (MVDP) as well as adequate processing conditions enabled expansion of slices of the raw meat tissue. The main aim of the study was to use the response surface method and find the conditions of puffing that could maximize the expansion of meat during MVDP. The bound was set on the expansion: the most expanded puffings should be of good quality, including a desirable porous structure. The best combination of values of the MVDP process conditions (e.g., the initial moisture content in meat slices, microwave energy, and the vacuum absolute pressure) was found during experiments using the central composite design. The volume of slices puffed under these conditions was 1.60–1.78 times greater than the volume of slices before MVDP, and the sensory quality index remained acceptable. The research showed that pretreatment reduced the hardness of sample by over 25% and increased its crispiness, which was confirmed in cryo-scanning electron microscopy images.     

Application of dielectric barrier discharge (DBD) plasma packed with glass and ceramic pellets for SO2 removal at ambient temperature: optimization and modeling using response surface methodology

Air pollution is a major health problem in developing countries and has adverse effects on human health and the environment. Non-thermal plasma is an effective air pollution treatment technology. In this research, the performance of a dielectric barrier discharge (DBD) plasma reactor packed with glass and ceramic pellets was evaluated in the removal of SO₂ as a major air pollutant from air in ambient temperature. The response surface methodology was used to evaluate the effect of three key parameters (concentration of gas, gas flow rate, and voltage) as well as their simultaneous effects and interactions on the SO₂ removal process. Reduced cubic models were derived to predict the SO₂ removal efficiency (RE) and energy yield (EY). Analysis of variance results showed that the packed-bed reactors (PBRs) studied were more energy efficient and had a high SO₂ RE which was at least four times more than that of the non-packed reactor. Moreover, the results showed that the performance of ceramic pellets was better than that of glass pellets in PBRs. This may be due to the porous surface of ceramic pellets which allows the formation of microdischarges in the fine cavities of a porous surface when placed in a plasma discharge zone. The maximum SO₂ RE and EY were obtained at 94% and 0.81 g kWh⁻¹, respectively under the optimal conditions of a concentration of gas of 750 ppm, a gas flow rate of 2 l min⁻¹, and a voltage of 18 kV, which were achieved by the DBD plasma packed with ceramic pellets. Finally, the results of the model's predictions and the experiments showed good agreement.     

Performance optimization of microbial electrolysis cell (MEC) for palm oil mill effluent (POME) wastewater treatment and sustainable Bio-H2 production using response surface methodology (RSM)

Microbial electrolysis cells (MECs) are a new bio-electrochemical method for converting organic matter to hydrogen gas (H₂). Palm oil mill effluent (POME) is hazardous wastewater that is mostly formed during the crude oil extraction process in the palm oil industry. In the present study, POME was used in the MEC system for hydrogen generation as a feasible treatment technology. To enhance biohydrogen generation from POME in the MEC, an empirical model was generated using response surface methodology (RSM). A central composite design (CCD) was utilized to perform twenty experimental runs of MEC given three important variables, namely incubation temperature, initial pH, and influent dilution rate. Experimental results from CCD showed that an average value of 1.16 m³ H₂/m³ d for maximum hydrogen production rate (HPR) was produced. A second-order polynomial model was adjusted to the experimental results from CCD. The regression model showed that the quadratic term of all variables tested had a highly significant effect (P < 0.01) on maximum HPR as a defined response. The analysis of the empirical model revealed that the optimal conditions for maximum HPR were incubation temperature, initial pH, and influent dilution rate of 30.23 ^°C, 6.63, and 50.71%, respectively. Generated regression model predicted a maximum HPR of 1.1659 m³ H₂/m³ d could be generated under optimum conditions. Confirmation experimentation was conducted in the optimal conditions determined. Experimental results of the validation test showed that a maximum HPR of 1.1747 m³ H₂/m³ d was produced.     

A new synthetic metamodel methodology for liquid‐propellant engine's cooling system optimization

The present paper strives for optimization of the cooling system of a liquid‐propellant engine (LPE). To this end, the new synthetic metamodel methodology utilizing the design of experiment method and the response surface method was developed and implemented as two effective means of designing, analyzing, and optimizing. The input variables, constraints, objective functions, and their surfaces were identified. Hence, the design and development strategy of combustion chamber and nozzle was clarified, and 64 different experiments were carried out on the RD‐161 propulsion system, of which 47 experiments were approved and compatible with the problem constraints. This engine used all three modes of cooling: the radiation cooling, the regenerative cooling, and the film cooling. The response surface curves were drawn and the related objective function equations were obtained. The analysis of variance results indicate that the developed synthetic model is capable to predict the responses adequately within the limits of input parameters. The three‐dimensional response surface curves and contour plots have been developed to find out the combined effects of input parameters on responses. In addition, the precision of the models was assessed and the output was interpreted and analyzed, which showed high accuracy. Therefore, the desirability function analysis has been applied to LPE's cooling system for multiobjective optimization to maximize the total heat transfer and minimize the cooling system pressure loss simultaneously. Finally, confirmatory tests have been conducted with the optimum parametric conditions to validate the optimization techniques. In conclusion, this methodology optimizes the LPE's cooling system, a 2% increase in the total heat transfer, and a 38% decrease in the pressure loss of the cooling system. These values are considerably large for the LPE design.     

An ANFIS-RSM based modeling and multi-objective optimization of syngas powered dual-fuel engine

The present study investigates the possibility of increasing efficiency and lowering pollutant emissions from a syngas-powered engine by modulating operational parameters such as engine load and syngas composition. Although artificial intelligence-based technologies are becoming more common for modeling single-fuel mode engines, they are rarely employed to simulate a dual-fuel syngas/diesel engine. In the first of its kind Endeavor in the area of syngas fueled engines, a hybrid adaptive neuro-fuzzy inference system (ANFIS)-response surface methodology (RSM) is investigated. The performance of syngas (H₂+CO), a novel synthetic gaseous fuel, was studied in four different combinations. ANFIS and RSM-based prediction models were developed using engine performance and emissions data collected over the whole load range. While ANFIS surpassed RSM in model prediction, RSM was useful in establishing mathematical links between engine input and output. The ANFIS model developed had a good correlation between R (0.996–0.9998) and R² (0.992–0.9972), as well as low model errors as determined by the root means square error range (0.0086–5.936) and mean absolute percentage error range (0.0028–0.0194). Theil's U2 was used to calculate the model's uncertainty, which was estimated to be 0.0065–0.0439. The superior forecasting abilities of ANFIS models were proved by low errors and uncertainty. The performance of the syngas-powered engine was optimized using the desirability approach to achieve optimum efficiency while emitting the least amount of pollution. The ideal engine load and syngas compositions for maximum production were 67.99% engine load and 72.4:27.6 as H₂:CO syngas mix.     

Feasibility study and performance assessment for the integration of a steam-injected gas turbine and thermal desalination system

This study proposes a systematic approach for retrofitting a steam-injection gas turbine (SIGT) with a multi-effect thermal vapor compression (METVC) desalination system. The retrofitted unit's product cost of the fresh water (RUPC) was used as a performance criterion, which comprises the thermodynamic, economic, and environmental attributes when calculating the total annual cost of the SIGT–METVC system. For the feasibility study of retrofitting the SIGT plant with the METVC desalination system, the effects of two key parameters were analyzed using response surface methodology (RSM) based on a central composite design (CCD): the steam air ratio (SR) and the temperature difference between the effects of the METVC system (?T_METVC) on the fresh water production (Q_freshwater) and the net power generation (W_net) of the SIGT–METVC system. Multi-objective optimization (MOO) which minimizes the modified total annual cost (MTAC) and maximizes the fresh water flow rate was performed to optimize the RUPC of the SIGT–METVC system. The best Pareto optimal solution showed that the SIGT–METVC system with five effects is the best one among the systems with 4–6 effects. This system under optimal operating conditions can save 21.07% and 9.54% of the RUPC, compared to the systems with four and six effects, respectively.     

Efficient loading and entrapment of tamoxifen in human serum albumin based nanoparticulate delivery system by a modified desolvation technique

Herein, the poorly water-soluble drug, Tamoxifen (Tmx), was loaded in the amphipathic matrix of human serum albumin (HSA) nanoparticles by a modified desolvation method. In order to enhance the drug loading (DL) and drug entrapment efficiency (DEE) (<2% and 10%, respectively), ultrasonication of Tmx-HSA mixture was performed prior to desolvation process. Tmx loading and entrapment efficiency were optimized by employment of the response surface methodology (RSM)-central composite design (CCD) of experiments. Under the optimum conditions of 1.59 mg Tmx/ml concentration, 7.76 pH and 5 h incubation of HSA-Tmx, the DL of 6.7% and DEE of 74% are achievable. Particles with the average size of 195 nm, zeta potential of −21 mV and polydispersity index of 0.09 were produced under these conditions. A more sustained Tmx release behavior was observed from polyethylene glycol (PEG) conjugated nanoparticles in comparison to the non-PEGylated ones. The short-term stability investigation showed no alteration in physicochemical properties of nanoparticles at 4 and 37 °C, but small increase in nanoparticles size was observed after three months of storage at room temperature. This is the first report for efficient production of a Tmx delivery system based on HSA nanoparticles.     

响应面法优化催化超临界水氧化法处理制药废水的研究

采用超临界水氧化法处理制药废水,考察温度、压力、停留时间、过氧量等因素对废水COD去除效果的影响;采用响应面分析法对实验结果进行数据分析和参数优化.结果表明,在最佳操作点温度压力25 MPa,392.54℃,氧化剂过量1.254倍,停留时间52.58 s的条件下,COD去除率达到最高值（98.92％）.