Failure-Aware Evaluation for Bernoulli-Driven Water Separation: From Laboratory Evidence to Operational Control

Abstract

This critical review examines failure-aware evaluation in bernoulli-driven water separation, with links to intelligent manufacturing and evidence governance. The organizing question is how failure modes should be prioritized when nominal performance, uncertainty, and maintenance evidence disagree. Ten or more scholarly and user-supplied records are synthesized through a mechanism-to-decision framework spanning system boundaries, measurement, representation, evaluation, translation, and governance. No experiment, participant dataset, effect estimate, or production result is invented. Particular attention is given to average performance concealing rare but costly failure regimes. The review argues that credible translation requires source-level traceability, explicit validity domains, failure-aware evaluation, and revalidation triggers. Google Scholar-supplied records are retained in structured APA form, and no missing DOI or pagination field is completed by conjecture.