This study compares the scaling behavior of membrane distillation (MD) with that of nanophotonics-enabled solar membrane distillation (NESMD). Previous research has shown that NESMD, due to its localized surface heating driven by photothermal membrane coatings, is an energy-efficient system for off-grid desalination; however, concerns remained regarding the scaling behavior of self-heating surfaces. In this work, bench-scale experiments were performed, using model brackish water, to compare the scaling propensity of NESMD with MD. The results showed NESMD to be highly resistant to scaling; a three times higher salt concentration factor (c/c 0 ) was achieved in NESMD compared to MD without any decline in flux. Analyses of the scaling layer on NESMD membranes revealed that salt deposition was 1/4 of that observed for MD. Scaling resistance in NESMD is attributed to its lower operating temperature, which increases the solubility of common scalants and decreases salt precipitation rates. Precipitation kinetics measurements revealed an order of magnitude faster precipitation under heated conditions (62 °C, k = 8.7 × 10 −2 s −1 ) compared to ambient temperature (22 °C, k = 7.1 × 10 −3 s −1 ). These results demonstrate a distinct advantage of NESMD over MD for the treatment of high scaling potential water, where scaling is a barrier to high water recovery.
Synthesis of ultrasmall platinum nanoparticles supported on macroporous cellulose fibers for hydrogen gas and formic acid induced catalytic reduction of organic compounds in water.
Asset management provides a strategic framework for infrastructure systems and focuses on getting the most out of their performance with the available resources. To determine future budget needs, highway agencies must have the necessary data and analytical tools with which to predict the performance of highway assets over time. Currently, transportation asset management systems are at different maturity levels. Pavement and bridges are considered the big ticket of all highway assets, but the preservation of signs, signals, lighting, guardrails, and pavement markings is also crucial to protect road users. Despite its importance, one of the safety assets with fewer asset management analytical tools is guardrail systems. Transportation agencies typically replace or repair guardrails that have endured major damage from car crashes. To implement a proactive preservation program, in agreement with transportation asset management practices, various parameters must be known. These parameters include inventory information, current guardrail condition, and performance models to forecast changes in the guardrail system condition over time. This paper describes a performance-based model with an analytical method to formulate a proactive preservation program for guardrail systems. The model was developed from inventory data and predicts changes in the guardrail system condition over time. A case study estimates the annual agency costs and backlogged costs over a 10-year analysis period. This model can be integrated into an asset management system to facilitate the formulation of preservation programs for guardrail systems at the strategic level.
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