Reliability metrics and their management implications for open pond algae cultivation [electronic resource]

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Tác giả:

Ngôn ngữ: eng

Ký hiệu phân loại: 666.9 Masonry adhesives

Thông tin xuất bản: Washington, D.C. : Oak Ridge, Tenn. : United States. Dept. of Energy. Office of Energy Efficiency and Renewable Energy ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy, 2021

Mô tả vật lý: Size: Article No. 102249 : , digital, PDF file.

Bộ sưu tập: Metadata

ID: 262545

The prevalence of contaminating organisms in outdoor algae cultivation, with the often-associated dramatic crop failures, necessitates the need for metrics describing production system reliability. Standard metrics for algae cultivation reliability are critically needed to be able to map improvements in operational parameters, but do not currently exist. In this work, we present a set of standard metrics including mean time to failure (MTTF) and mean time between failures (MTBF) as the basis for the calculation of pond failure rate (FR) and reliability coefficient (RC). Metrics associated with the numbers of contaminating organisms such as abundance ratio (AR), prevalence of infection (PI), and mean intensity of infection (MII) are also relevant. These metrics, based on measured experimental values of outdoor pond performance during the Algae Testbed Public-Private Partnership (ATP3) Unified Field Studies (UFS), provide a basis for quantifying pond failure and provide insight into potential pond management and contaminant mitigation strategies. From these reliability metrics applied to this dataset, we are able to link operational parameters, such as harvest frequency and inoculum source, to pond reliability for different algae strains and seasons, and from an assessment of AR, provide contamination thresholds beyond which a culture may be unrecoverable. Ultimately, the implementation of widely-practiced and simple-tocalculate algae pond reliability metrics calculated from rapid and easy to collect data or observations will reduce risk and uncertainty in large-scale algae deployment and aid in the development of integrated pest management (IPM) strategies.
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