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DOE OSTI2021

Event-Based Analysis of Solar Power Distribution Feeder Using Micro-PMU Measurements

Solar distribution feeders are commonly used in solar farms that are integrated into distribution substations. In this paper, we focus on a real-world solar distribution feeder and conduct an event-based analysis by using micro-PMU measurements. The solar distribution feeder of interest is a behind-the-meter solar farm with a generation capacity of over 4 MW that has about 200 low-voltage distributed photovoltaic (PV) inverters. The event-based analysis in this study seeks to address the following practical matters. First, we conduct event detection by using an unsupervised machine learning approach. For each event, we determine the event’s source region by an impedancebased analysis, coupled with a descriptive analytic method. We segregate the events that are caused by the solar farm, i.e., locallyinduced events, versus the events that are initiated in the grid, i.e., grid-induced events, which caused a response by the solar farm. Second, for the locally-induced events, we examine the impact of solar production level and other significant parameters to make statistical conclusions. Third, for the grid-induced events, we characterize the response of the solar farm; and make comparisons with the response of an auxiliary neighboring feeder to the same events. Fourth, we scrutinize multiple specific events; such as by revealing the dynamics to the control system of the solar distribution feeder. The results and discoveries in this study are informative to utilities and solar power industry.

14 SOLAR ENERGY↗

DOE OSTI2024

Wintertime extreme warming events in the high Arctic: characteristics, drivers, trends, and the role of atmospheric rivers

Abstract. An extreme warming event near the North Pole, with 2 m temperature rising above 0 °C, was observed in late December 2015. This specific event has been attributed to cyclones and their associated moisture intrusions. However, little is known about the characteristics and drivers of similar events in the historical record. Here, using data from European Centre for Medium-Range Weather Forecasts Reanalysis, version 5 (ERA5), we study these winter extreme warming events with 2 m temperature over a grid point above 0 °C over the high Arctic (poleward of 80° N) that occurred during 1980–2021. In ERA5, such wintertime extreme warming events can only be found over the Atlantic sector. They occur rarely over many grid points, with a total absence during some winters. Furthermore, even when occurring, they tend to be short-lived, with the majority of the events lasting for less than a day. By examining their surface energy budget, we found that these events transition with increasing latitude from a regime dominated by turbulent heat flux into the one dominated by downward longwave radiation. Positive sea level pressure anomalies which resemble blocking over northern Eurasia are identified as a key ingredient in driving these events, as they can effectively deflect the eastward propagating cyclones poleward, leading to intense moisture and heat intrusions into the high Arctic. Using an atmospheric river (AR) detection algorithm, the roles of ARs in contributing to the occurrence of these extreme warming events defined at the grid-point scale are explicitly quantified. The importance of ARs in inducing these events increases with latitude. Poleward of about 83° N, 100 % of these events occurred under AR conditions, corroborating that ARs were essential in contributing to the occurrence of these events. Over the past 4 decades, both the frequency, duration, and magnitude of these events have been increasing significantly. As the Arctic continues to warm, these events are likely to increase in both frequency, duration, and magnitude, with great implications for the local sea ice, hydrological cycle, and ecosystem.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2016

The 2012 July 23 Backside Eruption: An Extreme Energetic Particle Event?

The backside coronal mass ejection (CME) of 2012 July 23 had a short Sun-to-Earth shock transit time (18.5 hr).The associated solar energetic particle (SEP) event had a greater than 10 MeV proton flux peaking at approximately 5000 pfu, and the energetic storm particle event was an order of magnitude larger, making it the most intense event in the space era at these energies. By a detailed analysis of the CME, shock, and SEP characteristics, we find that the July 23 event is consistent with a high-energy SEP event (accelerating particles to giga-electron volt energies). The times of maximum and fluence spectra in the range 10100 MeV were very hard, similar to those of ground-level enhancement (GLE) events. We found a hierarchical relationship between the CME initial speeds and the fluence spectral indices: CMEs with low initial speeds had SEP events with the softest spectra, while those with the highest initial speeds had SEP events with the hardest spectra. CMEs attaining intermediate speeds result in moderately hard spectra. The July 23 event was in the group of hard-spectrum events. During the July 23 event, the shock speed greater than (2000 km s(exp -1), the initial acceleration (approximately 1.70 km s(exp -2), and the shock-formation height (approximately 1.5 solar radii)were all typical of GLE events. The associated type II burst had emission components from meter to kilometer wavelengths, suggesting a strong shock. These observations confirm that the 2012 July 23 event is likely to be an extreme event in terms of the energetic particles it accelerated.

Gopalswamy, N.↗

DOE OSTI2022

Digital coded exposure formation of frames from event-based imagery

Abstract Event-driven neuromorphic imagers have a number of attractive properties including low-power consumption, high dynamic range, the ability to detect fast events, low memory consumption and low band-width requirements. One of the biggest challenges with using event-driven imagery is that the field of event data processing is still embryonic. In contrast, decades worth of effort have been invested in the analysis of frame-based imagery. Hybrid approaches for applying established frame-based analysis techniques to event-driven imagery have been studied since event-driven imagers came into existence. However, the process for forming frames from event-driven imagery has not been studied in detail. This work presents a principled digital coded exposure approach for forming frames from event-driven imagery that is inspired by the physics exploited in a conventional camera featuring a shutter. The technique described in this work provides a fundamental tool for understanding the temporal information content that contributes to the formation of a frame from event-driven imagery data. Event-driven imagery allows for the application of arbitrary virtual digital shutter functions to form the final frame on a pixel-by-pixel basis. The proposed approach allows for the careful control of the spatio-temporal information that is captured in the frame. Furthermore, unlike a conventional physical camera, event-driven imagery can be formed into any variety of possible frames in post-processing after the data is captured. Furthermore, unlike a conventional physical camera, coded-exposure virtual shutter functions can assume arbitrary values including positive, negative, real, and complex values. The coded exposure approach also enables the ability to perform applications of industrial interest such as digital stroboscopy without any additional hardware. The ability to form frames from event-driven imagery in a principled manner opens up new possibilities in the ability to use conventional frame-based image processing techniques on event-driven imagery.

47 OTHER INSTRUMENTATION↗

NASA NTRS1981

Revised age estimates of Brunhes palaeomagnetic events - Support for a link between geomagnetism and eccentricity

Revisions in the dates of reported geomagnetic excursions during the Brunhes Epoch are proposed in light of possible correlations between a section at Gioia Tauro, Italy, deep-sea cores, a core from Lake Biwa, Japan, and some lava flows. The anomalously long, double Blake Event reported at Gioia Tauro is here correlated with the Blake Event (approximately 110 kyr) and the Biwa 1 event (180 plus or minus 5 kyr); an hiatus may be present in the section between these two events. The alpha event at Gioia Tauro is correlated with the Biwa 2 event at about 295 kyr; the beta event with the 'Biwa 3' event at about 400 kyr; the gamma event with the Snake River event at 480 plus or minus 50; and the delta event, not recorded elsewhere, is estimated to have occurred at approximately 620 kyr. These proposed refinements in the age estimates of the excursions suggest an approximately 100 kyr cyclicity. If the events are real and the revised dating is correct, the timing of the geomagnetic events seems to coincide with times of peak eccentricity of the earth's orbit, suggesting a causal connection.

Rampino, M. R.↗

NASA NTRS2020

Candidate Brown-dwarf Microlensing Events with Very Short Timescales and Small Angular Einstein Radii

Short-timescale microlensing events are likely to be produced by substellar brown dwarfs (BDs), but it is difficult to securely identify BD lenses based on only event timescales because short-timescale events can also be produced by stellar lenses with high relative lens-source proper motions. In this paper, we report three strong candidate BD-lens events found from the search for lensing events not only with short timescales (t(E) ≲ 6 days) but also with very small angular Einstein radii (θ(E) ≲ 0.05 mas) among the events that have been found in the 2016–2019 observing seasons. These events include MOA-2017-BLG-147, MOA-2017-BLG-241, and MOA-2019-BLG-256, in which the first two events are produced by single lenses and the last event is produced by a binary lens. From the Monte Carlo simulations of Galactic events conducted with the combined t(E) and θ(E) constraint, it is estimated that the lens masses of the individual events are 0.051 (sup +0.100, sub -0.027) M(ʘ), 0.044 (sup +0.090, sub -0.023) M(ʘ), and 0.046 (sup +0.067, sub -0.023) M(ʘ)/0.038 (sup +0.056, sub -0.019) M(ʘ) and the probability of the lens mass smaller than the lower limit of stars is ~80% for all events. We point out that routine lens mass measurements of short-timescale lensing events require survey-mode space-based observations.

Cheongho Han↗

DOE OSTI2022

Localization based on time-reversed event sounds

A system determines an event location of an event within an indoor environment based on an event sound generated by the event. The system employs time-reversal techniques based on a received event sound to identify the event location as being in the vicinity of one of a plurality of locator devices at locator locations in the environment. The system includes a base array located within the environment that receives an indication that an event has been detected. Upon receiving the event sound, the system generates a time-reversed event sound for each transceiver and transmits via each transceiver the time-reversed event sound for that transceiver. When a locator device receives a time-reversed event sound, the locator device determines whether the event is in the vicinity of that locator location of the locator device and, if so, outputs an indication that the event occurred at that locator location.

Candy, Jim↗

DOE OSTI2022

Event detection unit

An event detection unit (EDU) for detecting an explosive event is provided. The EDU includes different types of sensors for measuring characteristics of an explosive event. The EDU includes an event notification component. The EDU also includes a processor that receives a measurement from the sensors and generates a combined non-event probability and a combined event probability based on that measurement that indicates a likelihood that an explosive event has not occurred or has occurred. The processor determines whether an explosive event has occurred based on the non-event probabilities and event probabilities. When an explosive event has been determined to occur, the processor directs the event notification component to output a notification that an explosive event has occurred.

Candy, James Vincent↗

DOE OSTI2024

Event detection unit

Candy, James Vincent↗

DOE OSTI2022

Initiating Event Rates at U.S. Nuclear Power Plants, 2021 Update

Analyzing initiating event rates is important because it indicates trends and patterns of plant performance and provides inputs to several U.S. Nuclear Regulatory Commission (NRC) risk-informed regulatory activities. This report presents an analysis of initiating event frequencies at U.S. commercial nuclear power plants from calendar year 1988 through 2021, as reported in licensee event reports. Engineers with nuclear power plant experience reviewed each event report since the last update to this report to categorize and characterize reactor trips. To be included in this study, an event had to meet all of the following criteria: (1) the event included an unplanned reactor trip (not a scheduled reactor trip on the daily operations schedule), (2) the sequence of events started when the reactor was critical and at or above the point of adding heat, (3) the event occurred at a U.S. commercial nuclear power plant (excluding Fort St. Vrain and LaCrosse), and (4) the event was reported by a licensee event report. Sixteen initiating event groupings are trended and displayed. For some of the categories, relevant events are plotted separately for boiling-water reactors (BWR) and pressurized-water reactors (PWR). P-values are given for the possible presence of a trend over the most recent 10 years. The following trends were identified for the most recent 10 years (2012–2021): • A highly statistically significant decreasing trend was identified for Loss of Offsite Power (p-value = 0.002) • A statistically significant decreasing trend was identified for BWR general transients (p-value = 0.025) • A statistically significant decreasing trend was identified for PWR general transients for the second year in a row (p-value = 0.038).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Initiating Event Rates at U.S. Nuclear Power Plants: 2022 Update

Analyzing initiating event rates is important because it indicates trends and patterns of plant performance and provides inputs to several U.S. Nuclear Regulatory Commission (NRC) risk-informed regulatory activities. This report presents an analysis of initiating event frequencies at U.S. commercial nuclear power plants from calendar year 1988 through 2022, as reported in licensee event reports. Engineers with nuclear power plant experience reviewed each event report since the last update to this report to categorize and characterize reactor trips. To be included in this study, an event had to meet all of the following criteria: (1) the event included an unplanned reactor trip (not a scheduled reactor trip on the daily operations schedule), (2) the sequence of events started when the reactor was critical and at or above the point of adding heat, (3) the event occurred at a U.S. commercial nuclear power plant (excluding Fort St. Vrain and LaCrosse), and (4) the event was reported by a licensee event report. Sixteen initiating event groupings are trended and displayed. For some of the categories, relevant events are plotted separately for boiling-water reactors (BWR) and pressurized-water reactors (PWR). P-values are given for the possible presence of a trend over the most recent 10 years.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2015

High-Energy Solar Particle Events in Cycle 24

The Sun is already in the declining phase of cycle 24, but the paucity of high-energy solar energetic particle (SEP) events continues with only two ground level enhancement (GLE) events as of March 31, 2015. In an attempt to understand this, we considered all the large SEP events of cycle 24 that occurred until the end of 2014. We compared the properties of the associated CMEs with those in cycle 23. We found that the CME speeds in the sky plane were similar, but almost all those cycle-24 CMEs were halos. A significant fraction of (16%) of the frontside SEP events were associated with eruptive prominence events. CMEs associated with filament eruption events accelerate slowly and attain peak speeds beyond the typical GLE release heights. When we considered only western hemispheric events that had good connectivity to the CME nose, there were only 8 events that could be considered as GLE candidates. One turned out to be the first GLE event of cycle 24 (2012 May 17). In two events, the CMEs were very fast (>2000 km/s) but they were launched into a tenuous medium (high Alfven speed). In the remaining five events, the speeds were well below the typical GLE CME speed (~2000 km/s). Furthermore, the CMEs attained their peak speeds beyond the typical heights where GLE particles are released. We conclude that several factors contribute to the low rate of high-energy SEP events in cycle 24: (i) reduced efficiency of shock acceleration (weak heliospheric magnetic field), (ii) poor latitudinal and longitudinal connectivity), and (iii) variation in local ambient conditions (e.g., high Alfven speed).

Solar Cycle 24↗

NASA NTRS2002

Two Types of Transpolar Arc Development, Event Studies with Data Set of ASTRID-2, DMSP, FAST, and SuperDARN

Aurorae which appear in the polar cap are called transpolar arcs, polar cap arcs, sun-aligned arcs, or occasionally Theta-aurora because of its spatial distribution resembling Greek character 'Theta.' Morphology, IMF (Interplanetary Magnetic Field) relationship, and ionospheric convection patterns were studied in quest of mechanisms of transpolar arcs. Four events were analyzed: 1999/Jan/22/19:00 - 23/01:30 (1 event: a) 1999/Jan/24/06:00 - 10:00 (1 event: b) 1999/Feb/1 1/20:00 - 12/02:00 (2 events: c, d), with data set of ExB drift velocity data obtained by electric field measurements of ASTRID-2 and FAST, DMSP ion driftmeter data, and line-of-sight velocity data of SuperDARN. POLAR-UVI image data were used for spatial and temporal variations of transpolar arcs and ACE data set were used for investigation of IMF relationship. IMF-Bz was strongly positive (Bz from +8nT to +20 nT) during periods of all four transpolar arcs. In events (a),(b),(c), transpolar arcs appeared immediately after the direction of IMF turned northward, though IMF was fluctuating in event (b). A sudden increase of IMF-By, from +3nT to +18nT, was observed in event (d). Two different types of transpolar arc development were observed in POLAR-UVI: one which begins as a split from dawn or dusk sector of auroral oval and shifts poleward in event (a),(c),(d), and another which is initially a patch of auroral oval disturbed by substorm but develops as a transpolar arc, forming a growing finger-like shape from midnight sector (event b). Sunward flow, associated with positive IMF-Bz, were observed within newly-created polar caps in event (a),(c),(d). Not clear ionospheric convection pattern was seen across the polar cap arc in event (b) die to limitation of data set. In event (c), O+ with energy more than 1 keV were observed by FAST within a transpolar arc, suggesting that their origin be from plasma sheet. Transpolar arcs are thought to be projection of plasma sheet bifurcation into lobe regime. There can be several ways of development of transpolar arcs and two different patterns were observed through this work.

Narita, Yasuhito↗

NASA NTRS2012

Leveraging Data Intensive Computing to Support Automated Event Services

A large portion of Earth Science investigations is phenomenon- or event-based, such as the studies of Rossby waves, mesoscale convective systems, and tropical cyclones. However, except for a few high-impact phenomena, e.g. tropical cyclones, comprehensive records are absent for the occurrences or events of these phenomena. Phenomenon-based studies therefore often focus on a few prominent cases while the lesser ones are overlooked. Without an automated means to gather the events, comprehensive investigation of a phenomenon is at least time-consuming if not impossible. An Earth Science event (ES event) is defined here as an episode of an Earth Science phenomenon. A cumulus cloud, a thunderstorm shower, a rogue wave, a tornado, an earthquake, a tsunami, a hurricane, or an EI Nino, is each an episode of a named ES phenomenon," and, from the small and insignificant to the large and potent, all are examples of ES events. An ES event has a finite duration and an associated geolocation as a function of time; its therefore an entity in four-dimensional . (4D) spatiotemporal space. The interests of Earth scientists typically rivet on Earth Science phenomena with potential to cause massive economic disruption or loss of life, but broader scientific curiosity also drives the study of phenomena that pose no immediate danger. We generally gain understanding of a given phenomenon by observing and studying individual events - usually beginning by identifying the occurrences of these events. Once representative events are identified or found, we must locate associated observed or simulated data prior to commencing analysis and concerted studies of the phenomenon. Knowledge concerning the phenomenon can accumulate only after analysis has started. However, except for a few high-impact phenomena. such as tropical cyclones and tornadoes, finding events and locating associated data currently may take a prohibitive amount of time and effort on the part of an individual investigator. And even for these high-impact phenomena, the availability of comprehensive records is still only a recent development. A major reason for the lack of comprehensive ,records for the majority of the ES phenomena is the perception that they do not pose immediate and/or severe threat to life and property and are thus not consistently tracked. monitored, and catalogued. Many phenomena even lack commonly accepted criteria for definitions. However. the lack of comprehensive records is also due to the increasingly prohibitive volume of observations and model data that must be examined. NASA Earth Observing System Data Information System (EOSDIS) alone archives several petabytes (PB) of satellite remote sensing data and steadily increases. All of these factors contribute to the difficulty of methodically identifying events corresponding to a given phenomenon and significantly impede systematic investigations. In the following we present a couple motivating scenarios, demonstrating the issues faced by Earth scientists studying ES phenomena.

Clune, Thomas L.↗

NASA NTRS2020

Modeling the Transport Processes of a Pair of Solar Energetic Particle Events Observed by Parker Solar Probe near Perihelion

We present model calculations of the transport processes of solar energetic particles in the corona and interplanetary medium for two events detected by Parker Solar Probe near its second perihelion on 2019 April 2 and April 4. In the 2019 April 2 event, the <100 keV proton differential intensity measured by the ISOIS EPI-Lo instrument increased by more than a factor of 10 above the pre-event intensity, whereas the ~1 MeV proton differential intensity detected by the EPI-Hi instrument did not show any intensity enhancement. In the 2019 April 4 event, the ~1 MeV proton intensity showed an increase of more than a factor of 100 above the pre-event intensity, but the <100 keV proton intensity enhancement was rather low and gradual. The observational fact that only the 2019 April 4 event displayed a high-energy intensity enhancement indicates that the associated acceleration process in the second event was more energetic than the first event. However, the gradual and low enhancement of the low-energy proton intensity in the second event is at odds with the scenario. In this paper, we investigate the injection and transport processes of protons in the corona and interplanetary magnetic fields with numerical model simulations. Our model calculations suggest that the gradual and low rise of the low-energy protons in the April 4 event was probably due to the different diffusion conditions in these two events and the fact that the spacecraft was moving away from the source region during these two events.

Solar energetic particles↗

NASA NTRSDate not supplied

Evaluating Meteorological Dust Events and Machine-Learning Based Dust Identification in Geostationary Satellite Imagery

NASA scientists in the Short-term Prediction Research and Transition Center (SPoRT) developed a physically-based machine learning approach to identify dust in satellite imagery with a focus on night-time dust detection (Berndt et al. 201; DustTracker-AI). NASA/NOAA Geostationary Environmental Operational Satellite-16 (GOES-16) imagery was used for training and model inputs. The training, testing and validation data set consists of 28 events in the Southwest United States, capturing dust and null events in the region from 2018-2020.With 83 distinct images and millions of pixels a random forest model was trained and validated, correctly labeling 85% of dust pixels.For the first time, the model was run in near-real time production during the spring of 2022 and dust probability visualizations were made available to NOAA National Weather Service (NWS) forecasters to assess its utility for dust forecasting. Results indicated the model helped increase the confidence in the presence of dust and enabled dust tracking for a longer period of time into the night-time hours. Forecaster assessment and running the model in near real-time allowed for the team to determine the types of events missed, captured, and false alarms. To gain additional context on model performance,the SPoRT team sought to gather more detailed information on the training database(e.g., meteorological characteristics and drivers). The goal of this project was to identify the meteorological drivers for the dust events and create a database which synthesized information from observations, forecaster discussions, and analyses pertaining to the dust events to understand the types of events currently used to train the model. A more detailed meteorological synopsis was created for each dust event in the training, testing, and validation datasets. Following the completion of the database and documentation, the classification details revealed that 88% of the dust events were synoptically driven while mesoscale events were less prevalent in model datasets. Meteorological conditions found such as mixing layer depth and wind velocity had mean values of 645mb and 21kt respectively.With conditions of deep mixed layers and moderate to strong surface winds a mesoscale thunderstorm outflow event was considered and subsequently added to the model training data set to test the impact of additional mesoscale training data. The model was retrained and then qualitatively tested on a sample thunderstorm outflow case that the original model was unable to identify. Preliminary results showed potential that the addition of more mesoscale events included in the training data could help to better identify indistinct and localized dust events.

Connor Welch↗

NASA NTRS2022

Responses of Compound Daytime and Nighttime Warm-Dry and Warm-H Events to Individual Anthropogenic Forcings

Daytime heat is often associated with reduced soil moisture and cloud cover, while nighttime heat is connected to high humidity and increased cloud cover. Due to these differing mechanisms, compound daytime and nighttime heat events may respond differently to major anthropogenic forcings (greenhouse gases, anthropogenic aerosols, land-use and land-cover change). Here, we use GISS ModelE2.1-G historical single-forcing runs from 1955 to 2014 to examine how individual anthropogenic forcings affect compound heat events—specifically warm daytime and nighttime temperatures compounded with dry precipitation or high humidity conditions. We show that greenhouse gases alone amplify the natural frequency of warm-dry events by 1.5–5 times and warm-humid events by 2–9 times in tropical and extratropical latitudes. Conversely, aerosols and land-use/land-cover change reduce the frequency of these events, resulting in more modest increases and in some regions, declines, in the historical 'all-forcings' scenario. Individually, aerosol effects are stronger and more widespread compared to land-use, oftentimes reducing the natural frequency of these events by 60%–100%. The responses of these compound events are primarily driven by changes in daytime and nighttime temperatures through large-scale warming via greenhouse gases and cooling from aerosols and land-use/land-cover change. However, changes in warm-dry events are amplified in regions with concurrent precipitation declines (e.g. Central America, Mediterranean regions) and warm-humid events are amplified by global concurrent humidity increases. Additionally, we find differences between daytime and nighttime compound responses in the historical experiment that can be traced back to the individual forcings. In particular, aerosols produce a greater cooling effect on daytime relative to nighttime temperatures, which notably results in a historical reduction of Northern Hemisphere daytime warm-dry events relative to natural conditions. Our analysis provides a more comprehensive understanding of the significant impacts of different anthropogenic climate forcings on daytime and nighttime warm-dry and warm-humid events, informing future risk and impact assessments.

Anthropogenic forcings↗

DOE OSTI2021

LeptonInjector and LeptonWeighter: A neutrino event generator and weighter for neutrino observatories

In this work, we present a high-energy neutrino event generator, called LeptonInjector, alongside an event weighter, called LeptonWeighter. Both are designed for large-volume Cherenkov neutrino telescopes such as IceCube. The neutrino event generator allows for quick and flexible simulation of neutrino events within and around the detector volume, and implements the leading Standard Model neutrino interaction processes relevant for neutrino observatories: neutrino-nucleon deep-inelastic scattering and neutrino-electron annihilation. In this paper, we discuss the event generation algorithm, the weighting algorithm, and the main functions of the publicly available code, with examples. Program summary: Program Titles: LeptonInjector and LeptonWeighter CPC Library link to program files: https://doi.org/10.17632/662gkpjfd9.1 Developer's repository links: https://github.com/icecube/LeptonInjector and https://github.com/icecube/LeptonWeighter Licensing provisions: GNU Lesser General Public License, version 3. Programming Language: C++11 External Routines: • Boost • HDF5 • nuflux (https://github.com/icecube/nuflux) • nuSQuIDS (https://github.com/arguelles/nuSQuIDS) • Photospline (https://github.com/icecube/photospline) • SuiteSparse (https://github.com/DrTimothyAldenDavis/SuiteSparse) Nature of problem: LeptonInjector: Generate neutrino interaction events of all possible topologies and energies throughout and around a detector volume. LeptonWeighter: Reweight Monte Carlo events, generated by a set of LeptonInjector Generators, to any desired physical neutrino flux or cross section. Solution method: LeptonInjector: Projected ranges of generated leptons and the extent of the detector, in terms of column depth, are used to inject events in and around the detector volume. Event kinematics follow distributions provided in cross section files. LeptonWeighter: Event generation probabilities are calculated for each Generator, which are then combined into a generation weight and used to calculate an overall event weight.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗