Systematic analysis and multi-objective optimization of an integrated power and freshwater production cycle

This study represents the results of the analysis and optimization of an integrated system for cogenerating electricity and freshwater. This setup consists of a Solid Oxide Fuel cell (SOFC) for producing electricity. Unburned fuel of the SOFC is burned in the afterburner to increase the temperature of the SOFC's outlet gasses and operate a Gas turbine (GT) to produce additional power and operate the air compressor. At the bottom of this cycle, a combined setup of a Multi-Effect Desalination (MED) and Reverse Osmosis (RO) is considered to produce freshwater from the unused heat capacity of the GT's exhaust gasses. Also, a Stirling engine is used in the fuel supply line to increase the fuel's temperature. Using LNG and the Stirling engine will replace the fuel compressor with a pump which increases the system performance and eliminates the need for the expansion valve. To study the system performance a mathematical model is developed in Engineering Equation Solver (EES) program. Then, the system's simulated data from the EES has been sent to MATLAB to promote the best operating condition based on the optimization criteria. An energetic, exergetic, economic, and environmental analysis has been performed and a Non-dominated Sorting Genetic Algorithm (NSGA-II) is used to achieve the goal. The two-objective optimization is performed to maximize the exergetic efficiency of the proposed system while minimizing the system's total cost of production. This cost is a weighted distribution of the Levelized Cost of Electricity (LCOE) and Levelized Cost of freshwater (LCOW). The results showed that the exergetic and energetic efficiencies of the system can reach 73.5% and 69.06% at the optimum point. The total electricity production of the system is 99 MW. The production cost is 11.71 Cents/kWh, of which 1.04 Cents/kWh is emission-related and environmental taxes. The freshwater production rate is 42.44 kg/s which costs 4.38 USD/m³.     

Designing Semipermeable Hydrogel Shells with Controlled Thickness through Internal Osmosis in Triple-Emulsion Droplets

Hydrogel shells that compartmentalize the water core from the aqueous surrounding provide molecular selectivity on size and charge in transmembrane transport. It is highly demanding to produce thin hydrogel shells to minimize diffusion length and maximize core volume. Here, internal osmosis in water-in-oil-in-water-in-oil (W/O/W/O) triple-emulsion droplets is used to produce thin hydrogel shells enclosing a large water core. The triple-emulsion droplets are prepared to have an ultrathin middle oil layer using a capillary microfluidic device. The innermost water droplet has a higher osmolarity than the outer water layer containing photopolymerizable hydrogel precursors, which pumps water from the outer layer to the core through the ultrathin oil layer by the osmosis. Therefore, the outer layer gets thinner and hydrogel precursors are enriched while the size of the triple-emulsion droplets remains unchanged. Through photopolymerization of precursors and phase transfer from oil to water, hydrogel shells enclosing water core are produced in the water environment; the oil layer is ruptured for molecular exchange through the shells. The thickness and composition of the hydrogel shells are precisely controllable by the osmotic conditions. The shells show a high permeation rate due to the thinness as well as controlled cut-off threshold of permeation for neutral and charged molecules.     

电厂锅炉补给水处理中全膜法处理工艺的应用研究

以某电厂为背景,针对其中的全膜法展开探讨,涉及到工艺流程、相关构筑物以及设备参数等多方面内容,并将其与离子交换法进行了对比分析,结果显示,全膜法的可行性更高,能达到无酸碱排放的效果,能够发挥出显著的社会效益,以期给相关工程提供可行参考,由此推动电厂炉给水处理工作的持续开展。     

Customization of ZrO2 loose/tight bilayer ultrafiltration membranes by reverse micelles-mediated aqueous sol-gel process for wastewater treatment

Two types of spherical zirconyl oxalate aqueous sols were successfully customized by a reverse micelles-mediated aqueous sol-gel process, and the sols were sequentially spin-coated on porous supports to prepare ZrO₂ loose/tight bilayer ultrafiltration membranes. After three times of spin-coating process, a defect-free ZrO₂ loose ultrafiltration membrane with pure water permeability of 110.5 ± 2.25 L m^?2 h^-1 bar^-1, molecular weight cut-off (MWCO) of 16.5 kDa and excellent rejection of up to 97.5 % for bovine serum albumin was fabricated. Then, the loose ultrafiltration membrane was used as a substrate to prepare ZrO₂ tight ultrafiltration membrane. Performances of tight ultrafiltration membrane regarding to permeability, retention of polyethylene glycol and treatment of dyes wastewater were evaluated. The tight ultrafiltration membrane with a thickness of 200 nm exhibited a pure water permeability of 22.5 ± 0.3 L m^-2 h^-1 bar^-1 and MWCO of 1150 Da. Additionally, the rejections of methyl red and methyl orange by the tight ultrafiltration membrane were both <65 %, while of alizarin red, direct red, bromocresol green and methyl blue achieved maximum values of 98.5 %, 99.2 %, 99.5 % and 99.6 %, respectively. The fouled membranes could restore the virgin performance for reuse by cleaning and low-temperature calcination.     

Crystal structure,polarization properties and reverse nonlinearity of solid solutions of the KNN-PZT system in a wide range of external influences

Experimental research of the crystal structure, polarization properties, and reverse nonlinearity of ceramic solid solutions of the (1-x) (Na_0·5K_0.5)NbO₃-xPb(Ti_0·5Zr_0.5)O₃ (KNN-PZT) quasi-binary system with 0.0 = x ≤ 1.0 in a wide range of external influences (temperatures, strength of dc/ac fields) has been done. Based on the X-ray structural data, an x-T diagram of the system has been constructed, and correlations of the behavior of the macroproperties of solid solutions with the features of their phase states with the temperature change have been established. It has been concluded that it is advisable to use the proposed compositions when designing microelectronic devices operating in various extreme conditions.     

Preparation of yttria-stabilized ZrO2 nanofiltration membrane by reverse micelles-mediated sol-gel process and its application in pesticide wastewater treatment

8 mol% yttria-stabilized ZrO₂ (8YSZ) nanofiltration (NF) membranes were prepared from size-controlled spherical ZrO₂ nanoparticles with an average diameter of ˜10 nm and a particle roundness value greater than 0.90, and the nanoparticles were efficiently fabricated by a reverse micelles (RMs)-mediated sol-gel process. It was found that yttria doping not only suppressed the tetragonal to monoclinic (t-m) phase transition, ensuring the membranes integrity, but also decreased the tetragonal grain size, increased the specific surface area, narrowed the pore size distribution and thus optimized the NF performance. The as-prepared 8YSZ NF membranes with a thickness of ˜260 nm exhibited high NF performances, while the pure water permeability and molecular weight cut-off (MWCO) were 3.9-4.2 L m⁻² h^-1 bar^-1 and 800 ± 50 Da respectively. In the treatment of pesticide wastewater, the removal rate of carbofuran by 8YSZ NF membranes was more than 82%, while the maximum removal rate could reach 89%. Furthermore, the contaminated membranes could be restored as ever after alkali wash and low-temperature calcination, implementing multiple reuses.     

A new reverse reduce-error ensemble pruning algorithm

Although greedy algorithms possess high efficiency, they often receive suboptimal solutions of the ensemble pruning problem, since their exploration areas are limited in large extent. And another marked defect of almost all the currently existing ensemble pruning algorithms, including greedy ones, consists in: they simply abandon all of the classifiers which fail in the competition of ensemble selection, causing a considerable waste of useful resources and information. Inspired by these observations, an interesting greedy Reverse Reduce-Error (RRE) pruning algorithm incorporated with the operation of subtraction is proposed in this work. The RRE algorithm makes the best of the defeated candidate networks in a way that, the Worst Single Model (WSM) is chosen, and then, its votes are subtracted from the votes made by those selected components within the pruned ensemble. The reason is because, for most cases, the WSM might make mistakes in its estimation for the test samples. And, different from the classical RE, the near-optimal solution is produced based on the pruned error of all the available sequential subensembles. Besides, the backfitting step of RE algorithm is replaced with the selection step of a WSM in RRE. Moreover, the problem of ties might be solved more naturally with RRE. Finally, soft voting approach is employed in the testing to RRE algorithm. The performances of RE and RRE algorithms, and two baseline methods, i.e., the method which selects the Best Single Model (BSM) in the initial ensemble, and the method which retains all member networks of the initial ensemble (ALL), are evaluated on seven benchmark classification tasks under different initial ensemble setups. The results of the empirical investigation show the superiority of RRE over the other three ensemble pruning algorithms.