arXiv subjects

Noah Rivera

Publications and source records attributed to Noah Rivera.

3 recordsLinked to original sources

arXiv2025

Brace for Impact: A Review of Mitigation Decisions of Critical Infrastructure Operators During the 2024 Solar Maximum

The Gannon Storm in May 2024 was the largest space weather event experienced in 20 years, generating auroras latitudes as low as 35°. Such activity can pose significant operational challenges for critical infrastructure operators, particularly those managing electricity transmission networks, satellite constellations, and aviation systems. Substantial progress has been made in understanding space weather and the potential exposure of infrastructure assets to severe events. We have seen few evaluations of the types of current mitigation strategies in use to reduce our shared vulnerability to this activity, motivating this study. Firstly, we fill an important literature gap by undertaking a systematic review of the range of space weather mitigation strategies for these three critical infrastructure sectors. Secondly, we contacted 303 critical infrastructure operators (50 power, 227 satellite, 26 aviation) for participation in an anonymous online survey or interview receiving 55 unique responses (18% response rate). To capture narratives of mitigation actions taken and impacts experienced over the solar maximum, qualitative interviews were then conducted with 33 operators. The results identified 91 potential mitigation actions within the sectors and found that 149 mitigation actions were enacted due to space weather forecasts and experienced impacts. This is one of the first exhaustive studies of space weather mitigation activities, and moves beyond the traditional focus on purely impacts.

physics.space-ph↗

arXiv2024

A Reproducible Method for Mapping Electricity Transmission Infrastructure for Space Weather Risk Assessment

Space weather risk assessment is constrained by the lack of available asset information needed to model geomagnetically induced currents (GICs) in electricity transmission infrastructure. We propose a systematic method that enables risk analysts to collect their own open-source substation data. Using a web browser platform for annotation, we convert OpenStreetMap (OSM) substation locations into high-resolution, component-level mappings of electricity transmission assets. We convert an initial 1,313 high-voltage (>=230 kV) substations to 52,273 components using low-altitude, satellite, and Street View imagery accessed through Google Earth, identifying 7,949 transformers. Compared to the OSM baseline, this approach provides detailed insights on voltage levels and substation configurations. We then construct a geospatial GIC network for the Tennessee Valley Authority (TVA) region, comparing May 2024 results with the University of Illinois Urbana-Champaign 150-bus (UIUC150) synthetic network and with measured ground GICs at 13 monitoring devices. The transformer types at unannotated substations and the grounding resistances are unknown, so we sample both across a Monte Carlo ensemble. This gives a median TVA 95th-percentile peak ground GIC of 29.1 A, with a 90 percent confidence interval of 23.9-36.1 A. The UIUC150 network yields a 95th-percentile peak ground GIC of 35.8 A under the same forcing, falling within this interval, and the modeled time series broadly capture the temporal morphology of the geomagnetic storm at the monitoring sites. This method shows promise for spatially explicit, screening-level GIC assessment without requiring access to operator data.

physics.geo-ph↗

arXiv2018

44 New & Known M Dwarf Multiples In The SDSS-III/APOGEE M Dwarf Ancillary Science Sample

Binary stars make up a significant portion of all stellar systems. Consequently, an understanding of the bulk properties of binary stars is necessary for a full picture of star formation. Binary surveys indicate that both multiplicity fraction and typical orbital separation increase as functions of primary mass. Correlations with higher order architectural parameters such as mass ratio are less well constrained. We seek to identify and characterize double-lined spectroscopic binaries (SB2s) among the 1350 M dwarf ancillary science targets with APOGEE spectra in the SDSS-III Data Release 13. We measure the degree of asymmetry in the APOGEE pipeline cross-correlation functions (CCFs), and use those metrics to identify a sample of 44 high-likelihood candidate SB2s. At least 11 of these SB2s are known, having been previously identified by Deshapnde et al, and/or El Badry et al. We are able to extract radial velocities (RVs) for the components of 36 of these systems from their CCFs. With these RVs, we measure mass ratios for 29 SB2s and 5 SB3s. We use Bayesian techniques to fit maximum likelihood (but still preliminary) orbits for 4 SB2s with 8 or more distinct APOGEE observations. The observed (but incomplete) mass ratio distribution of this sample rises quickly towards unity. Two-sided Kolmogorov-Smirnov tests and probabilities of 18.3% and 18.7%, demonstrating that the mass ratio distribution of our sample is consistent with those measured by Pourbaix et al. and Fernandez et al., respectively.

astro-ph.SR↗