Control of Bromate and THM Precursors Using Ozonation Combined System

Objective To investigate the feasibility of reducing THM precursors and controlling bromate taste and odor in drinking water taken from the Yellow River by an ozonation combined system. Methods The appropriate ozone dosage was determined, and then the changes of TOC, UV254 and THM formation potential （THMFP） in the combined system were evaluated. Results One mg/L ozone could effectively remove taste and odor and meet the maximum allowable bromate level in drinking water. The pre-ozonation increased THMFP, but the conventional treatment system could effectively reduce the odor. The bio-ceramic filter could partly reduce CHC13FP, but sometimes might increase CHCl2BrFP and CHClBr2FP. The biological activated carbon （BAC） filter could effectively reduce CHC13FP and CHCl2BrFP, but increase CHClBr2FP. Compared with other filters, the fresh activated carbon （FAC） filter performed better in reducing THMFP and even reduced CHClBr2FP. Conclusion The combined system can effectively reduce taste, odor, CHC13FP, and CHCl2BrFP and also bring bromate under control.

Reduction of Precursors of Chlorination By-products in Drinking Water Using Fluidized-bed Biofilm Reactor at Low Temperature

Objective To investigate the reduction of chlorination by-products （CBPs） precursors using the fluidized-bed biofdm reactor （FBBR）. Methods Reduction of total organic carbon （TOC）, ultraviolet absorbance （UV254）, tfihalomethane （THM） formation potential （THMFP）, haloacetic acid （HAA） formation potential （HAAFP）, and ammonia in FBBR were evaluated in detail. Results The reduction of TOC or UV254 was low, on average 12.6% and 4.7%, respectively, while the reduction of THMFP and HAAFP was significant. The reduction of ammonia was 30%-40% even below 3℃, however, it could quickly rise to over 50% above 3℃. Conclusions The FBBR effectively reduces CBPs and ammonia in drinking water even at low temperature and seems to be a very promising and competitive drinking water reactor for polluted surface source waters, especially in China.

Prediction of alloy composition and microhardness by random forest in maraging stainless steels based on a cluster formula

Fe-Ni-Cr-based super-high-strength maraging stainless steels were generally realized by multiple-element alloying under a given heat treatment processing. A series of alloy compositions were designed with a uniform cluster formula of [Ni16Fe192]（Cr32（Ni16-x-y-z-m-n MoxTiyNbzAlmVn）） （at.%） that was developed out of a unique alloy design tool, a cluster- plus-glue-atom model. Alloy rods with a diameter of 6 mm were prepared by copper-mold suction-cast processing under the argon atmosphere. These alloy samples were solid-solutioned at 1273 K for 1 h, followed by water-quenching, and then aged at 783 K for 3 h. The effect of the valence electron concentration, characterized with the number of valence electrons per unit cluster （VE/uc） formula of 16 atoms, on microhardness of these designed maraging stainless steels at both solid- solutioned and aged states was investigated. The relationship between alloy compositions and microhardness in maraging stainless steels was firstly established by the random forest （RF, a kind of machine learning methods） based on the experimental results. It was found that not only the microhardness of any given composition alloy within the frame of cluster formula, but also the alloy composition with a maximum microhardness for any given VE/uc, could be predicted in good agreement with the guidance of the relationship by RF. The contributions of minor-alloying elements to the microhardness of the aged alloys were also discussed.