Final Report for Phase I SBIR “Wastewater Grown Algae Feedstock Production and Processing to Bioproducts”
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The aim of this study is the sustainable recovery of phosphorus as high-quality calcium phosphate from anaerobic membrane bioreactor treated swine permeate for targeted use as fertilizer or raw material for the fertilizer industry. Phosphorus removal efficiencies from treated swine permeate were evaluated by adding various calcium/phosphorus molar ratios ranging from 1/1 to 12/1. Results showed that removal efficiencies were inconsistent in duplicate trials at the same calcium doses (maximum P removal 93% in Trial 1 and <20% removal in Trial 2). The variability in P removal was due to the high bicarbonate alkalinity of the swine permeate, which buffered the system and thereby prevented it from reaching alkaline pH conditions ideal for P removal. Total alkalinity and initial solution pH had the greatest impact on P removal and caused unintended precipitation of non-specific calcium minerals (Calcite). Further, the carbonate alkalinity from the permeate was removed using process modifications that included acid addition and aeration for removal as CO 2 . Carbonate removal resulted in 97% P removal with increased total P content (11.8% P) in the final product and better solubility. Additional COD removal was also observed during the flocculation process.
Metakaolin-based alkali activated mortars (AAM) - with and without CuSO{sub 4}·5H{sub 2}O and ZnO addition (mass ratio M{sup n+}/solid binder 0.08% to 1.7%) - were casted and exposed within an extensive long-term field campaign over the period of 20 months to a sewer basin, strongly affected by biogenic acid corrosion. (Un-)exposed AAM were tested regarding their physicochemical and microstructural properties, bioreceptivity and overall durability. Metal addition led to a retarding effect during alkali-activation reaction, as well as to an increase in open porosity of up to 3.0% and corresponding lower compressive strength of up to 10.9%. Reduced microbial colonization and diversity were observed on AAM with Cu, while Zn addition led to increased biodiversity. We propose that the observed higher durability of Cu-doped AAM is due to antibacterial effects and associated reduction of biogenic acid production, superseding overall negative effects of metal-dosage on physical material properties. Observed lower durability of Zn-doped AAM was related to combined negative physicochemical and microbial effects.
The advent of affordable computing, low-cost sensor hardware, and high-speed and reliable communications have spurred installation of ubiquitous sensors in complex engineered systems. However, ensuring reliable data quality remains a challenge. Exploitation of redundancy among sensor signals can help improving the precision of measured variables, detecting the presence of gross errors, and identifying faulty sensors. The cost of sensor ownership, maintenance efforts in particular, can still be cost-prohibitive however. Maximizing the ability to assess and control data quality while minimizing the cost of ownership thus requires a careful sensor placement. To solve this challenge, in this work we develop a generally applicable method to solve the multi-objective sensor placement problem in systems governed by linear and bilinear balance equations. Importantly, the method computes all Pareto-optimal sensor layouts with conventional computational resources and requires no information about the expected sensor quality.
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