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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 325 records · Page 18

Implementation of a Time-domain Cosmic-ray-muon Tagger for the NEXUS Low-background Cryogenic Facility

Quantifying the effects of radiation on the operation of qubits both as quantum information systems as well as particle detectors has emerged as a pressing issue in quantum science in recent years. We present an overview of the design, operation, and deployment of a 90-$\mathrm{in}^2$ three-panel muon detector for use in the NEXUS experimental facility at Fermilab to temporally isolate correlated errors in qubits and determine if they possess an astrophysical origin. Constructed with three scintillator-attached PMTs read out with NIM modules in a triply-coincident logic scheme, we measure a surface-level muon luminosity of 9.7425 muons per second---consistent with an average surface-level cosmic-ray flux of approximately one muon per square centimeter per minute. Integrating the NIM modules with an MCC 128 DAQ HAT and Raspberry Pi, a Python script records exactly when a muon struck the detector and writes a timestamp to a log file for follow-up cross referencing. This experiment will broadly contribute to further studies aimed at understanding the source and mitigation of information loss in qubits.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Verifying Cyber Implementation Best Practices With Malcolm

Network traffic analysis can reveal a lot about what's right or wrong with a network's cybersecurity footing. Using Malcolm, a powerful open-source network traffic analysis tool suite for network security monitoring, cyber analysts and asset owners can validate cybersecurity best practices and uncover red flags in network configuration, including: proper network segmentation east-west (cross-segment) and north-south traffic unsecure or outdated network protocols authentication using clear text credentials rogue devices and services unexpected protocols (e.g., IPv6, DNS, DHCP, update checks, etc.) suspicious file transfers

99 GENERAL AND MISCELLANEOUS↗

Implementing Automation of Foreign Obligations Tracking at SRS

Obligated Nuclear Material Principles • Stay with the originating item if at all practical. • Additional principles apply to bulk processes for pool accounting. • Fungibility: Individual units are indistinguishable therefore equal units are interchangeable. • Equivalence: Material of the same quality and same quantity • Isotopic composition • Physical and chemical form • State: fresh, irradiated, waste • Proportionality: If material is mixed and is processed, a proportion of the resultant material will be obligated in the same proportion as the originating material.

Ramsey, Catherine M. [Savannah River National Labo↗

Fermilab PIP II machine protection system digitized data noise elimination scheme and its FPGA implementation

In Fermilab's PIP-II machine protection system, beam loss signals from various detectors are digitized at 125 MS/s. Noise from both high-frequency sources and low-frequency 60 Hz AC power equipment can contaminate the data. To suppress noise across these ranges especially 60 Hz and its harmonics, which overlap with beam loss signal frequencies advanced digital processing beyond standard filtering is required. Several real-time functional blocks were simulated and tested on an FPGA: (1) a dual time-constant discharging integrator filter, (2) a de-ripple baseline extraction and storage block, and (3) a fast-recovery discharging integrator. The nonlinear IIR integrator filter removes high-frequency noise and feeds into the baseline extractor. Upon detecting abrupt beam loss, it switches to a longer time constant to prevent baseline distortion. The de-ripple block calculates a valid baseline by averaging over multiple 60 Hz periods, storing results in a 4096-word FPGA RAM. This baseline is subtracted from raw data before integration by the fast-recovery block, which resets quickly after use. All blocks achieved expected performance.

Wu, J. [Fermilab] (ORCID:0000000344329521)↗

Implementation of fuel management multi-cycle optimization capabilities in RAVEN optimization framework

Optimization in nuclear fuel-management assists the core reload engineer with finding optimal out-of-core and in-core strategies. RAVEN is INL’s open source software that is equipped with fuel-management optimization capabilities including single-cycle, single- and multi-objective optimization of pressurized water reactors (PWRs) loading patterns (LP) of a fresh core using genetic algorithm (GA) and non-dominated sorting genetic algorithm (NSGA-II). In practice, however, medium and long term planning of fuel-management needs a multi-cycle approach, where the history and availability of fuel assemblies is considered in the optimization process. In this paper, we present a description of an initial expansion of RAVEN fuel-management optimization capabilities for a multi-cycle optimization framework. N-th cycle optimization capabilities that account for the unique history of recycled fuel assembly in the core were added. The multi-cycle optimization approach taken is formulated as a cycle-wise optimization problem where out-of-core decisions are used to onset each cycle optimization. Out-of-core decisions are managed externally to the in-core optimization by a fuel inventory management module. A proof-of-concept optimization problem is also presented.

42 - ENGINEERING↗

Implementing Environmental Considerations to Molten Chloride Reactor Experiment Equipment Removal and Disposal Plan

The Molten Chloride Reactor Experiment (MCRE) will be the first operational advanced nuclear experiment to utilize molten chloride salt mixed with fissile material as both a fuel and coolant source. The MCRE experiment will investigate the instillation, operation, and removal of small fast molten salt reactors and will involve unique requirements for Equipment Removal and Disposal (ERD).

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗