# of Displayed Technologies: 7 / 7


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MuAMO: an Intelligent Maintenance Optimization Framework for Safety-Critical Systems
TS-073254 — Industries operating safety‑critical and asset‑intensive systems struggle to leverage the full value of disparate maintenance data sources. Current maintenance management and optimization tools operate in silos, limiting real‑time decision‑making, automation, and scalability. No existing s…
  • College: College of Engineering (COE)
  • Inventors: Smidts, Carol; Diao, Xiaoxu; Khafizov, Marat; Pietrykowski, Michael; Vaddi, Pavan Kumar; Zhao, Yunfei
  • Licensing Officer: Giles, David

DPRA: Dynamic Probabilistic Risk Assessment for Cyber Security Risk Analysis
TS-073146 — As industrial systems become increasingly digital and interconnected, traditional risk assessment tools struggle to capture how cyber threats interact with physical processes in real time. Existing methods typically assess hardware failures or isolated cyber events, but they cannot model how attac…
  • College: College of Engineering (COE)
  • Inventors: Smidts, Carol; Diao, Xiaoxu; Vaddi, Pavan Kumar; Zhao, Yunfei
  • Licensing Officer: Giles, David

Model-Based, Multi-Criteria Optimization for Sensor Placement and Selection
TS-073138 — Designing online monitoring (OLM) for safety‑critical systems is constrained by scarce early‑stage operational data and by quantitative models that are slow to build, brittle across configurations, and costly to iterate. This creates expensive sensor networks with blind spots, poor diagnosabil…
  • College: College of Engineering (COE)
  • Inventors: Smidts, Carol; Diao, Xiaoxu; Olatubosun, Samuel; Rownak, Md Ragib; Vaddi, Pavan Kumar
  • Licensing Officer: Giles, David

Immersive VR Platform for Human Reliability Assessment for Physical Security
TS-073103 — Physical protection remains a major driver of nuclear plant operations and maintenance costs, yet current security risk models rely on conservative assumptions and sparse empirical data on how defenders and operators actually behave under extreme threat. They rarely capture errors of commission, k…
  • College: College of Engineering (COE)
  • Inventors: Smidts, Carol; Dechasuravanit, Atitarn; Diao, Xiaoxu; Olatubosun, Samuel; Rownak, Md Ragib; Shafieezadeh, Abdollah; Yilmaz, Alper; Zhao, Yunfei
  • Licensing Officer: Giles, David

BLIPS: Deductive Early‑Stage Failure Analysis for Complex Systems
TS-072984 — Complex systems are entering the market faster while safety verification grows harder, especially when detailed designs or operational data don’t yet exist. Traditional tools (FMEA, FTA, PRA) either require finalized designs, focus on forward propagation, or struggle with partial failures and fu…
  • College: College of Engineering (COE)
  • Inventors: Mansoor, Ali; Diao, Xiaoxu; Smidts, Carol
  • Licensing Officer: Mess, David

Propagation-Based Fault Detection and Sensor Optimization for Complex Industrial Systems
TS-072175 — The Need Modern industrial and energy systems are increasingly complex, making timely fault detection and discrimination critical for safety, reliability, and cost control. Existing fault diagnosis methods often struggle with transient states, require extensive historical data, or lack interpretabil…
  • College: College of Engineering (COE)
  • Inventors: Smidts, Carol; Diao, Xiaoxu; Li, Boyuan
  • Licensing Officer: Giles, David

A Model Based Assessment Approach and an Automation Environment for Qualification of Embedded Digital Devices
TS-042856 — A Framework and Automatization process designed to determine the functionality of Embedded Digital Devices.
As our technology becomes increasingly complex, so does the quantity and variation of the Embedded Digital Device [EDD] components that are required within the project. Because not every device is made perfectly to specifications due to a propagation of random error, it is important to have a dive…
  • College: College of Engineering (COE)
  • Inventors: Smidts, Carol; Diao, Xiaoxu; Li, Boyuan
  • Licensing Officer: Giles, David

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