Modeling, Control, And Fault Detection Of Energy Systems Under Limited High-Confidence Data Scenarios, Selorme K. Agbleze

Graduate Theses, Dissertations, and Problem Reports

Abstract

Modeling, Control, and Fault Detection of Energy Systems under Limited High-Confidence Data Scenarios

Selorme K. Agbleze

Utilizing process measurements for fault detection is an established approach for processes with adequate datasets. For systems with limited high-confidence data representing fault cases and some amount of low-confidence data, few quantitative hybrid techniques exist for performing fault detection. In real systems, it is time-consuming, expensive, and sometimes not productive to generate enough high-confidence data with fault characteristics of a specific process. The problem of limited high-confidence data scenarios may also arise due to process novelty, the need for new operating conditions, or …

Characterization And Evaluation Of Various Biochar Types As Green Adsorbents For Rare Earth Element Recovery From Aqueous Solutions, Oluwaseun Victor Famobuwa

Graduate Theses, Dissertations, and Problem Reports

Rare earth elements (REEs) are members of the lanthanide family (atomic number 57 – 71). They are significantly important to the global economy due to their applications in renewable energy, defense, and medical industries. REEs are primarily derived from bastnaesite and monazite but may also be present in xenotime, cerite, alanite, and many other types of mineralization in lesser amounts. Due to the increasing demand for REEs and their criticality in the supply chain, the need to explore secondary sources of REEs has gained tremendous importance.

Secondary sources of REEs include but are not limited to acid mine drainage (AMD), …

Strategies For Process Systems Mapping And Control Based On Operability Analysis, Victor Manuel Cunha Alves

Graduate Theses, Dissertations, and Problem Reports

This dissertation aims to develop strategies for process systems engineering (PSE) mapping using models, emerging tools and algorithms motivated by process operability analysis research. Such strategies will be employed to ensure simultaneous design and control of large-scale industrial systems. The emerging tools and techniques in this research include supervised machine learning-based (ML-based) operability mapping, automatic differentiation (AD) for implicit mapping, and the development of a systematic mapping approach for control structure selection using operability analysis. Thus far, the developed operability algorithms either recur to nonlinear programming (NLP) solutions which are computationally expensive or to linearizing the underlying modeling task at …