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
Risk‑Informed Markov Decision Framework for Industrial Asset Management
TS-073031 —
Operators of large, complex facilities struggle to balance revenue, maintenance, and regulatory safety constraints under uncertainty. Existing tools typically optimize only a subset of factors without a unified, real‑time view of component health and future degradation. Advanced reactors and oth…
- College: College of Engineering (COE)
- Inventors: Zhao, Yunfei; Smidts, Carol
- Licensing Officer: Giles, 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
Efficient Cyclic Redundancy Check Encoding with Low-Complexity LFSR Design
TS-071388 — The Need
Cyclic redundancy checks (CRC) are utilized in digital communication and storage systems for error detection. Current CRC encoding and decoding methods in digital communication and storage systems are complex and require a high gate count, leading to inefficiencies in hardware design. There…
- College: College of Engineering (COE)
- Inventors: Zhang, Xinmiao; Cai, Jiaxuan; Tang, Yok Jye
- Licensing Officer: Giles, David
A Generalized Mistuning Model for Bladed Disk Systems
TS-070971 — The Need
Modern gas turbines and compressors rely on bladed disks, which are highly sensitive to mistuning caused by manufacturing tolerances, wear, or damage. Existing modeling tools are fragmented, complex, and often limited to specific mistuning types. Industry will greatly benefit from a unified…
- College: College of Engineering (COE)
- Inventors: D'Souza, Kiran; Krizak, Troy
- Licensing Officer: Giles, David
Joint Activity Testing (JAT): A Testing & Evaluation Methodology for Human-Machine Teams
TS-068443 —
In high-stakes industries, the integration of humans and advanced automation systems demands evaluation methods that reliably predict performance under varying challenges. Current testing methods often focus on individual components, failing to assess how human-machine teams operate as a unit, par…
- College: College of Engineering (COE)
- Inventors: Morey, Dane; Rayo, Michael
- Licensing Officer: Giles, David
Vision System Using MDP-Based Tracking for Automated Dimensional Analysis
TS-068440 —
Accurate measurement of physical attributes, such as dimensions, alignments, and surface features, is essential for ensuring quality and consistency across industries. Traditional measurement methods, often reliant on manual tools and human oversight, are time-intensive, prone to errors, and lac…
- College: College of Engineering (COE)
- Inventors: Allen, Theodore "Ted"; Rodriguezbuno, Ramiro; Zhang, Yifei
- Licensing Officer: Giles, David
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