arXiv subjects

Kate Davis

Publications and source records attributed to Kate Davis.

4 recordsLinked to original sources

arXiv2026

COS2035: Extending COS/FUV Operations Through the 2030s

The far-ultraviolet (FUV) detector of the Cosmic Origins Spectrograph (COS) accumulates gain sag where photons land, and without continued mitigation this degradation would render the most used modes unusable. To extend COS FUV operations through the 2030s, the COS team developed the COS2035 strategy, which builds on the existing COS2025 rules with four technical breakthroughs and two new usage policies. First, SPLIT-wavecals decouple wavelength calibration from science exposures and open detector real estate above the Pt-Ne lamp light leak. Second, a hybrid lifetime position (LP) architecture allows different gratings to operate at different LPs simultaneously. Third, the LP-infinity framework removes the dependence on the eight-LP limit in the COS flight software, supported by a new table-based APT and TRANS rules architecture. Fourth, a revised gain-sag flagging method evaluates integrated column count loss against the maximum achievable signal-to-noise (S/N) per mode. The two new usage policies cap per-target S/N at the maximum achievable value set by fixed-pattern noise, and limit any single program to 2\% of the lifetime at any single LP. With LP7 and LP10 enabled in Cycle 33 and LP11 and LP12 in active commissioning for Cycles 34 and 35, the COS2035 strategy positions the FUV channel for continued high productivity through the 2030s.

astro-ph.IM↗

arXiv2025

A Scalable Automatic Model Generation Tool for Cyber-Physical Network Topologies and Data Flows for Large-Scale Synthetic Power Grid Models

Power grids and their cyber infrastructure are classified as Critical Energy Infrastructure/Information (CEII) and are not publicly accessible. While realistic synthetic test cases for power systems have been developed in recent years, they often lack corresponding cyber network models. This work extends synthetic grid models by incorporating cyber-physical representations. To address the growing need for realistic and scalable models that integrate both cyber and physical layers in electric power systems, this paper presents the Scalable Automatic Model Generation Tool (SAM-GT). This tool enables the creation of large-scale cyber-physical topologies for power system models. The resulting cyber-physical network models include power system switches, routers, and firewalls while accounting for data flows and industrial communication protocols. Case studies demonstrate the tool's application to synthetic grid models of 500, 2,000, and 10,000 buses, considering three distinct network topologies. Results from these case studies include network metrics on critical nodes, hops, and generation times, showcasing effectiveness, adaptability, and scalability of SAM-GT.

eess.SY↗

arXiv2024

Smart Grids Secured By Dynamic Watermarking: How Secure?

Unconditional security for smart grids is defined. Cryptanalyses of the watermarked security of smart grids indicate that watermarking cannot guarantee unconditional security unless the communication within the grid system is unconditionally secure. The successful attack against the dynamically watermarked smart grid remains valid even with the presence of internal noise from the grid. An open question arises: if unconditionally authenticated secure communications within the grid, together with tamper resistance of the critical elements, are satisfactory conditions to provide unconditional security for the grid operation.

cs.CR↗

arXiv2020

Generalized Contingency Analysis Based on Graph Theory and Line Outage Distribution Factor

Identifying the multiple critical components in power systems whose absence together has severe impact on system performance is a crucial problem for power systems known as (N-x) contingency analysis. However, the inherent combinatorial feature of the N-x contingency analysis problem incurs by the increase of x in the (N-x) term, making the problem intractable for even relatively small test systems. We present a new framework for identifying the N-x contingencies that captures both topology and physics of the network. Graph theory provides many ways to measure power grid graphs, i.e. buses as nodes and lines as edges, allowing researchers to characterize system structure and optimize algorithms. This paper proposes a scalable approach based on the group betweenness centrality (GBC) concept that measures the impact of multiple components in the electric power grid as well as line outage distribution factors (LODFs) that find the lines whose loss has the highest impact on the power flow in the network. The proposed approach is a quick and efficient solution for identifying the most critical lines in power networks. The proposed approach is validated using various test cases, and results show that the proposed approach is able to quickly identify multiple contingencies that result in violations.

math.OC↗