arXiv subjects

Brian Jowers

Publications and source records attributed to Brian Jowers.

3 recordsLinked to original sources

arXiv2026

The PUR-1 Cyber-Physical Digital Twin

Digital twin technologies have the potential to improve operational flexibility and responsiveness capabilities of nuclear systems. To provide decision support, cyber event characterization, state estimation, predictive control, and real-time dynamic processing of operational data, however, an efficient digital twin needs to integrate multiple models (data-driven as well as physics-based) with explainability while at the same time maintain two-way synchronization with the physical facility at a time constant less than its operational cycle. In this work, we present the Purdue University Reactor One Digital Twin (PUR-1 DT), a cyber-physical digital twin with a complete high-fidelity physics-based and AI-driven virtual model stack (neutronics, thermal-hydraulics, point kinetics) which provides closed-loop explainable diagnostics, forecasting, predictive control, and action recommendation back to the reactor via two-way communications and a cyber-physical testbed. We demonstrate real-time synchronized state estimation and short-term forecasting over a full reactor operational cycle and conduct a series of benchmarking experiments to validate accuracy and latency. Our results show good agreement with experimental results and lay the groundwork for further development and experimental demonstration of DT-enabled functionalities in real-world facilities.

cs.CE↗

arXiv2025

Experimental Assessment of a Multi-Class AI/ML Architecture for Real-Time Characterization of Cyber Events in a Live Research Reactor

There is increased interest in applying Artificial Intelligence and Machine Learning (AI/ML) within the nuclear industry and nuclear engineering community. Effective implementation of AI/ML could offer benefits to the nuclear domain, including enhanced identification of anomalies, anticipation of system failures, and operational schedule optimization. However, limited work has been done to investigate the feasibility and applicability of AI/ML tools in a functioning nuclear reactor. Here, we go beyond the development of a single model and introduce a multi-layered AI/ML architecture that integrates both information technology and operational technology data streams to identify, characterize, and differentiate (i) among diverse cybersecurity events and (ii) between cyber events and other operational anomalies. Leveraging Purdue Universitys research reactor, PUR-1, we demonstrate this architecture through a representative use case that includes multiple concurrent false data injections and denial-of-service attacks of increasing complexity under realistic reactor conditions. The use case includes 14 system states (1 normal, 13 abnormal) and over 13.8 million multi-variate operational and information technology data points. The study demonstrated the capability of AI/ML to distinguish between normal, abnormal, and cybersecurity-related events, even under challenging conditions such as denial-of-service attacks. Combining operational and information technology data improved classification accuracy but posed challenges related to synchronization and collection during certain cyber events. While results indicate significant promise for AI/ML in nuclear cybersecurity, the findings also highlight the need for further refinement in handling complex event differentiation and multi-class architectures.

cs.LG↗

arXiv2025

Demonstration of Quantum-Secure Communications in a Nuclear Reactor

Quantum key distribution (QKD), one of the latest cryptographic techniques, founded on the laws of quantum mechanics rather than mathematical complexity, promises for the first time unconditional secure remote communications. Integrating this technology into the next generation nuclear systems - designed for universal data collection and real-time sharing as well as cutting-edge instrumentation and increased dependency on digital technologies - could provide significant benefits enabling secure, unattended, and autonomous operation in remote areas, e.g., microreactors and fission batteries. However, any practical implementation on a critical reactor system must meet strict requirements on latency, control system compatibility, stability, and performance under operational transients. Here, we report the complete end-to-end demonstration of a phase-encoding decoy-state BB84 protocol QKD system under prototypic conditions on Purdue's fully digital nuclear reactor, PUR-1. The system was installed in PUR-1 successfully executing real-time encryption and decryption of 2,000 signals over optic fiber distances up to 82 km using OTP-based encryption and up to 140 km with AES-based encryption. For a core of 68 signals, OTP-secure communication was achieved for up to 135 km. The QKD system maintained a stable secret key rate of 320 kbps and a quantum bit error of 3.8% at 54 km. Our results demonstrate that OTP-based encryption introduces minimal latency while the more key-efficient AES and ASCON encryption schemes can significantly increase the number of signals encrypted without latency penalties. Additionally, implementation of a dynamic key pool ensures several hours of secure key availability during potential system downtimes. This work shows the potential of quantum-based secure remote communications for future digitally driven nuclear reactor technologies.

quant-ph↗