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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Making Small-Volume Heat Pump Water Heaters Larger: A Design Framework for Integrated Phase Change Material Heat Exchangers

Those that use electricity for water heating, the majority use resistive elements rather than heat pump water heaters (HPWHs), the latter of which use 60-70% less energy than the former. One major barrier to wider HPWH adoption is the added equipment required, which prevents current 50-80-gallon tanks on the market from fitting into smaller utility closets sized for 30-40 gallons, such as those found in manufactured housing. Additionally, these smaller HPWHs tend to underperform relative to their larger counterparts. One solution that addresses both space and performance concerns is thermal energy storage, and in particular, phase change materials (PCMs). PCMs have been studied extensively in building envelope and HVAC systems, but remain a nascent technology in residential water heating. While water itself has a uniquely high energy storage capacity, PCMs have an even higher energy storage density, thus providing the potential to elevate the performance of 40-gallon HPWHs to that of 50-gallon or larger tanks. This research is part of a larger project that seeks to utilize thermal energy storage to enable decarbonized water heating in low-income communities. In this study, we outline the design process used to produce novel PCM heat exchangers for use in small-volume HPWH tanks, including the identification of design constraints and performance targets relevant to real-world applications. In order to ensure optimal PCM utilization and tank storage capacity, we focus here on co-maximizing surface area and PCM volume in the heat exchangers; therefore, this research targets triply periodic minimal surface (TPMS) lattices. TPMS lattices boast enhanced heat transfer capabilities compared to traditional heat exchanger geometries and offer highly tailorable designs; thus, they pair well with the growing field of additive manufacturing, or 3D printing. Starting with a suite of TPMS lattices, we demonstrate a systematic approach for narrowing down feasible designs that comply with identified constraints while meeting PCM performance objectives.

25 ENERGY STORAGE↗
DOE OSTI2022

Paintable Reflective Coatings (CRADA Final Report)

As part of the Cyclotron Road LEEP, the Cypris Materials project team conducted research on the viability of a new reflective coating technology based on a novel advanced materials platform. Building off of nearly a decade of academic research spanning multiple institutions, research efforts were designed to tackle the familiar problem of maturing a project into a minimum viable product. Fundamental technologies spawned from academic research are fraught with both scientific and technical risk, as the barriers to a successful peer reviewed publication are much lower than a commercial product with a paying customer base. It is common, especially when maturing chemical or material innovations, to encounter a number of critical assumptions or features that support the performance of the technology in an unsustainable fashion. At the outset of the project, the platform technology of Cypris Materials was no different. Specific research thrusts regarding scale-up, process optimization, technoeconomic modeling, market specific weathering performance, and market specific optical performance were tackled during the CRADA project.

36 MATERIALS SCIENCE↗
NASA NTRS2015

Application of Transfer Matrix Approach to Modeling and Decentralized Control of Lattice-Based Structures

This paper presents a modeling and control of aerostructure developed by lattice-based cellular materials/components. The proposed aerostructure concept leverages a building block strategy for lattice-based components which provide great adaptability to varying ight scenarios, the needs of which are essential for in- ight wing shaping control. A decentralized structural control design is proposed that utilizes discrete-time lumped mass transfer matrix method (DT-LM-TMM). The objective is to develop an e ective reduced order model through DT-LM-TMM that can be used to design a decentralized controller for the structural control of a wing. The proposed approach developed in this paper shows that, as far as the performance of overall structural system is concerned, the reduced order model can be as e ective as the full order model in designing an optimal stabilizing controller.

Transfer Matrix Method↗
DOE OSTI2026

Optimal experimental design using eigenvalue-based criteria with Pyomo.DoE

New developments in automated optimal experimental design within the PSE+ software ecosystem. Advancements in user experience (to reduce the time taken to perform optimal experiment design) and computational capabilities (allowing more diverse experimental design) are shown with an example relevant to critical minerals and materials. Also, a small tutorial on science-based optimal experimental design and novel contributions therein are presented.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Evaluation of the Reliability of Passive Infrared (PIR) Occupancy Sensors for Residential Indoor Lighting

Solid-state lighting (SSL) technologies have penetrated the general illumination market in recent years, largely replacing conventional technologies such as incandescent and fluorescent lighting. Most of the initial excitement about light-emitting diode (LED) sources for SSL devices focused on their energy savings potential resulting from vast improvements in source efficiency and luminous efficacy compared with conventional illumination products. More recently, the focus has shifted toward other aspects of lighting application efficiency, namely intensity effectiveness and spectral efficiency, because of the ease of controlling both the light intensity of LEDs with drive voltage and the color properties of the LED-based illuminators. To capitalize on the energy savings of increased intensity effectiveness and spectral efficiency, a lighting control system (LCS) is often used. While the current penetration of LCSs is relatively modest, it is anticipated that lighting controls (i.e., connected lighting, controls and LED and conventional lighting) could have an installed penetration as higher as 46% by the year 2035, saving an additional 1.3 quads of energy. Despite the large energy savings that can be gained from using LCSs, standard test methods for evaluating sensors employed in LCSs and reliability data of the LCSs and their components are generally lacking. The National Electrical Manufacturers Association (NEMA) developed the only standard, NEMA WD 7-2011 (R2016), to test occupancy and motion sensor performance (herein referred to as “the NEMA protocol”). In a previous U.S. Department of Energy (DOE) effort, some concerns of the NEMA protocol were identified (e.g., strict height and weight limits on test subjects, large amounts of manual effort, sometimes inconsistent repeatability). During the current work, a consistent detection length test (DLT) and a Robotic Sensor Evaluation System (RoboSES) were developed to alleviate some of these concerns. RoboSES acts as a human surrogate by using thermal pads on a mannequin and a remote-controlled mobile base to test a sensor’s field of view (FOV). This report builds on the earlier DOE efforts to understand sensor technologies used in LCSs for general illumination. Specifically, this report describes the optimization of RoboSES, characterizes and establishes test methods to assess the reliability of multiple passive infrared (PIR) sensors, and reports the findings of robustness and reliability testing on two commercial PIR sensors intended for residential applications. The information presented in this report is gained from up to 4,000 hours (hrs) of accelerated stress tests (ASTs).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Carbon Capture Pilot at Vicksburg Containerboard Mill (Final Technical Report)

This is the final technical report for the DOE-OCED project DE-CD0000051. The report provides the progress at the close of the project. The objective of the project is to design and build a large pilot plant for carbon dioxide (CO 2 ) capture from a pulp and paper (P&P) mill using RTI’s non-aqueous solvent (NAS) technology at a capacity of 120,000 t-CO 2 /year, with >90% CO 2 captured. The pilot plant will be used for testing and evaluating the NAS capture process using real flue gas from the P&P mill’s power boiler for a minimum of 1 year of parametric testing and a minimum of 2,000 hours of continuous long-term testing. The testing will provide data for process optimization and scale-up for the P&P industry, provide information on interaction of flue gas contaminants on solvent performance and degradation, and inform strategies for emission control. At the end of the project, the pilot plant will be managed by International Paper (IP), the host site owner, which will continue to capture CO 2 , sequester the captured CO 2 , and be eligible for the 45Q credit.

42 ENGINEERING↗
NASA NTRS2020

OSA Spotlight Summary: Designing Miniature X-ray Optics for the SmallSat Lunar Science Mission Concept CubeX

The scientific demand for extended field X-Ray remote sensing for mapping of planetary bodies has produced the CubeSat X-ray Telescope (CubeX) lunar mission concept. Orbiting the Moon at 6,000 km for 1 year sometime during the mid-decade solar maximum, the primary objectives of CubeX are to map lunar surface elemental abundances and to assess feasibility of x-ray pulsar timing navigation. CubeX’s Miniature X-ray Optics (MiXO) design builds on heritage of existing X-ray imaging designs using new electroformed NiCo alloy replication (ENR) to create shells of 1 mm thickness. MiXO will provide 1 arcmin resolution X-Ray imaging for an extended instantaneous field of view, at various energy range sensitivities. Based on the classic Wolter-Type I design (using a paraboloid/hyperboloid grazing mirror pair), mirror parameters were expanded to allow both shell length and focal-plane offsets to vary independently. The design was optimized with a merit function that factored together four sub-merits: PSF sharpness (measured as half-power diameter), consistency across the field, minimized scattering, and maximized effective area. Monte Carlo analysis was used to predict final performance, including surface scatter effects. The demonstrated configurations include a compact 34 shell design with a diameter of 105 mm more efficient at higher energies, and a larger 130 mm/24 shell version with a larger overall effective area at lower energies. The compact design carries more expensive fabrication and assembly cost (with more shells) as well as a more challenging alignment (with denser packing). Both have overall resolution <1’ up to 26’ off-axis and <1.5’ up to 33’ off-axis, whereas a conventional design’s image quality degrades quickly beyond 15’ off-axis. This opens up new possibilities for future SmallSat missions that could use two different configurations for wide energy ranges or midsized instruments using multiple identical modules for larger collecting area.

x-ray↗
DOE OSTI2023

Assessing the Impact of Cybersecurity Attacks on Energy Systems

This paper investigates the cyber resiliency of future power systems with high penetration of distributed energy resources using advanced distributed and (or) hierarchical control architectures. Specifically, we simulate cyberattacks on three prototypical use cases, and we identify attack scenarios that are the most damaging to the overall system performance. We show that these attacks can have a significant impact on grid operation. Results provide additional insights into the robustness of the system to the most common cyberattacks.

buildings↗
DOE OSTI2024

Improving Robustness of Spectrogram Classifiers with Neural Stochastic Differential Equations

Signal analysis and classification is fraught with high levels of noise and perturbation. Computer-vision-based deep learning models applied to spectrograms have proven useful in the field of signal classification and detection; however, these methods aren't designed to handle the low signal-to-noise ratios inherent within non-vision signal processing tasks. While they are powerful, they are currently not the method of choice in the inherently noisy and dynamic critical infrastructure domain, such as smart-grid sensing, anomaly detection, and non-intrusive load monitoring. Currently, these models can be brittle, which makes them susceptible to noisy input. This also means they have sub-optimal stability of explanation outputs. Experts and technicians using these models to make decisions in real world scenarios need assurance that a model is performing as it is supposed to. The classification or prediction outputs it generates should be sound and grounded, not likely to change in the presence of shifting noise landscapes. In this work, we explore the idea of Neural Stochastic Differential Equations (NSDE's) to improve the robustness of models trained to classify time series data and the effect of NSDE's on the explainability of outputs. We then test the effectiveness of these approaches by applying them to a non-intrusive load monitoring (NILM) dataset that consists of simulated harmonic signals injected into a real building.

Brogan, Joel↗
DOE OSTI2022

Efficient high-dimensional variational data assimilation with machine-learned reduced-order models

Abstract. Data assimilation (DA) in geophysical sciences remains the cornerstone of robust forecasts from numerical models. Indeed, DA plays a crucial role in the quality of numerical weather prediction and is a crucial building block that has allowed dramatic improvements in weather forecasting over the past few decades. DA is commonly framed in a variational setting, where one solves an optimization problem within a Bayesian formulation using raw model forecasts as a prior and observations as likelihood. This leads to a DA objective function that needs to be minimized, where the decision variables are the initial conditions specified to the model. In traditional DA, the forward model is numerically and computationally expensive. Here we replace the forward model with a low-dimensional, data-driven, and differentiable emulator. Consequently, gradients of our DA objective function with respect to the decision variables are obtained rapidly via automatic differentiation. We demonstrate our approach by performing an emulator-assisted DA forecast of geopotential height. Our results indicate that emulator-assisted DA is faster than traditional equation-based DA forecasts by 4 orders of magnitude, allowing computations to be performed on a workstation rather than a dedicated high-performance computer. In addition, we describe accuracy benefits of emulator-assisted DA when compared to simply using the emulator for forecasting (i.e., without DA). Our overall formulation is denoted AIEADA (Artificial Intelligence Emulator-Assisted Data Assimilation).

58 GEOSCIENCES↗
NASA NTRS1995

Baseline experimental investigation of an electrohydrodynamically assisted heat pipe

The increases in power demand and associated thermal management requirements of future space programs such as potential Lunar/Mars missions will require enhancing the operating efficiencies of thermal management devices. Currently, the use of electrohydrodynamically (EHD) assisted thermal control devices is under consideration as a potential method of increasing thermal management system capacity. The objectives of the currently described investigation included completing build-up of the EHD-Assisted Heat Pipe Test bed, developing test procedures for an experimental evaluation of the unassisted heat pipe, developing an analytical model capable of predicting the performance limits of the unassisted heat pipe, and obtaining experimental data which would define the performance characteristics of the unassisted heat pipe. The information obtained in the currently proposed study will be used in order to provide extensive comparisons with the EHD-assisted performance observations to be obtained during the continuing investigation of EHD-Assisted heat transfer devices. Through comparisons of the baseline test bed data and the EHD assisted test bed data, accurate insight into the performance enhancing characteristics of EHD augmentation may be obtained. This may lead to optimization, development, and implementation of EHD technology for future space programs.

Duncan, A. B.↗
NASA NTRS2019

The ILRS: Approaching 20 Years and Planning for the Future

The International Laser Ranging Service (ILRS) was established by the International Association of Geodesy (IAG) in 1998 to support programs in geodesy, geophysics, fundamental constants and lunar research, and to provide the International Earth Rotation Service with data products that are essential to the maintenance and improvement in the International Terrestrial Reference Frame (ITRF), the basis for metric measurements of changes in the Earth and Earth–Moon system. Other scientific products derived from laser ranging include precise geocentric positions and motions of ground stations, satellite orbits, components of Earth’s gravity field and their temporal variations, Earth Orientation Parameters, precise lunar ephemerides and information about the internal structure of the Moon. Laser ranging systems are already measuring the one-way distance to remote optical receivers in space and are performing very accurate time transfer between remote sites in the Earth and in Space. The ILRS works closely with the IAG’s Global Geodetic Observing System. The ILRS develops (1) the standards and specifications necessary for product consistency, and (2) the priorities and tracking strategies required to maximize network efficiency. The service collects, merges, analyzes, archives and distributes satellite and lunar laser ranging data to satisfy a variety of scientific, engineering, and operational needs and encourages the application of new technologies to enhance the quality, quantity, and cost effectiveness of its data products. The ILRS works with (1) new satellite missions in the design and building of retroreflector targets to maximize data quality and quantity, and (2) science programs to optimize scientific data yield. Since its inception, the ILRS has grown to include forty laser ranging stations distributed around the world. The ILRS stations track more than ninety satellites from low Earth orbit (LEO) to the geosynchronous orbit altitude as well as retroreflector arrays on the surface of the Moon. Applications have been expanded to include time transfer, asynchronous ranging for targets at extended ranges, free space quantum telecommunications, and the tracking of space debris. Laser ranging technology is moving to lower energy, higher repetition rates (kHz), single-photon-sensitive detectors, shorter pulse widths, shorter normal point intervals for faster data acquisition, and increased pass interleaving, automated to autonomous operation with remote access, and embedded software for real-time updates and decision making. An example of pass interleaving is presented for the Yarragadee station (see Fig. 4); tracking of LEO satellites is often accommodated during break in LEO and GNSS passes. New satellites arrays provide more compact targets and work continues on the development of lighter less expensive arrays for satellites and the moon. The service now provides operational ITRF products including daily/ weekly station positions and daily resolution Earth orientation products; the flow of weekly combination of satellite orbit files for LAGEOS/Etalon-1 and -2 has recently been established. New products are under testing through a pilot project on systematic error monitoring currently underway. The article will give an overview of activities underway within the service, paths forward presently envisioned, and current issues and challenges.

Laser retroreflectors↗
DOE OSTI2020

Thermal characterization of the build chamber in electron beam melting

Electron beam powder bed fusion, commonly termed electron beam melting (EBM), offers great versatility in multiple-part processes and can produce high quality as-built components due to low residual stresses. The EBM process is complex and requires careful thermal management, including uniform and consistent preheating of the powder bed, in order to ensure quality and consistency of the product. However, most of the simulations in the literature focus on the selective melting stage of the process. As of today, optimal conditions for initial pre-heating temperatures are only available for specific materials. Thus, in order to extend the EBM technology to other desired build materials, a much better understanding of the pre-heating stages is required. In this work, numerical and experimental approaches are combined in order to investigate the effects and sensitivities of heat removal from the build plate during EBM pre-heating stages. For this purpose, a carefully reconstructed numerical model of the build chamber of an ARCAM Q20 + machine is developed. It includes all main parts of the chamber and all relevant heat transfer mechanisms, whereas special attention is paid to radiation heat exchange between various bodies. In order to validate the model, dedicated experiments are performed, in which a system of thermocouples is installed in the build chamber, allowing direct measurement of the local temperatures of the start-plate and heat shields. A good agreement between the simulation and experimental findings is achieved, leading to a better understanding of the thermal processes characteristic to the pre-heating stages. This basic analysis is followed by a representative pre-heating case, where a powder bed is also considered. The energy required to obtain the desired pre-heating temperatures is evaluated, and the role of the powder bed in heat transfer within the chamber is assessed. The pre-heating stage, simulated in the present work, is supposed to create proper conditions for sintering and consequent melting of the powder, which are highly dependent on the local temperatures and heat transfer features. Thus, the findings of the reported work present a step towards a better understanding of the thermal processes that characterize EBM. The reported model can be further used to provide realistic boundary condition inputs for other meso- or macro-scale models as a function of time and geometry. The model can serve also for verification of machine settings, i.e., jump-safe and melt-safe ones which actually provide desired preheat, and for development of settings for new powders.

36 MATERIALS SCIENCE↗
DOE OSTI2022

$\mathrm{IH}$-$\mathrm{GAN}$: A conditional generative model for implicit surface-based inverse design of cellular structures

Variable-density cellular structures can overcome connectivity and manufacturability issues of topologically optimized structures, particularly those represented as discrete density maps. However, the optimization of such cellular structures is challenging due to the multiscale design problem. Past work addressing this problem generally either only optimizes the volume fraction of single-type unit cells but ignoring the effects of unit cell geometry on properties, or considers the geometry–property relation but builds this relation via heuristics. In contrast, we propose a simple yet more principled way to accurately model the property to geometry mapping using a conditional deep generative model, named Inverse Homogenization Generative Adversarial Network (IH-GAN). It learns the conditional distribution of unit cell geometries given properties and can realize the one-to-many mapping from properties to geometries. Here we further reduce the complexity of IH-GAN by using the implicit function parameterization to represent unit cell geometries. Results show that our method can 1) generate various unit cells that satisfy given material properties with high accuracy (R 2 -scores between target properties and properties of generated unit cells >98%) and 2) improve the optimized structural performance over the conventional variable-density single-type structure. In the minimum compliance example, our IH-GAN generated structure achieves a 79.7% reduction in concentrated stress and an extra 3.03% reduction in displacement. In the target deformation examples, our IH-GAN generated structure reduces the target matching error by 86.4% and 79.6% for two test cases, respectively. We also demonstrated that the connectivity issue for multi-type unit cells can be solved by transition layer blending.

42 ENGINEERING↗
DOE OSTI2025

Coal Enhanced PEEK Filament Production for Additive Manufacturing in Industrial Services

The project (Award DE-FE0032146), led by Baker Hughes in collaboration with the University of Wyoming, aims to develop composite PEEK (Polyether-ether-ketone) materials enhanced using coal-derived graphene-based additives suitable for additive manufacturing (3D printing). Coal char (CC), graphene oxide (GO), and reduced graphene oxide (rGO), derived from Powder River Basin (PRB) coal, were successfully integrated into commercial PEEK feedstock. The composite PEEK materials demonstrated tensile and flexural strengths and modulus, Shore hardness, and thermal properties similar to unfilled PEEK. Dielectric strength of 0.5% GO/PEEK is twice that of unfilled PEEK. However, tensile elongation and Izod impact toughness of the composite materials are lower than unfilled PEEK. The 10% CC/PEEK material also shows good recyclability albeit with slightly increased glass transition and cold crystallization temperatures. Filaments of the composite PEEK materials were fabricated using a Filabot system. 3D printing of the composite PEEK initially encountered feeding stoppage caused by the non-uniform diameter of the filament, which was resolved by reducing the nominal diameter from 1.75 to 1.65 mm. The printability of the composite PEEK filaments is limited in geometry and build time, driven by differences in base PEEK feedstock from the commercial PEEK filament at printing conditions. Prototype part printed using the composite filaments shows inconsistent bead width and bead interruption resulting in porosity. Preliminary process and economic evaluation using PRB coal char estimates the cost of GO to be $0.5/lb. Considering the small fraction expected in the composite PEEK, the GO cost is several orders of magnitude lower than the commercial PEEK filament. It is recommended that the printability of composite PEEK filaments to be improved by optimizing the composite PEEK material at the printing conditions and reducing the variations in filament extrusion. Also important is to identify the mechanisms of how coal-derived additives affect the composite PEEK performance and printing characteristics to allow customized material design and processing for target performance.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

ASCR Workshop Position Paper: Challenges and Opportunities in High Energy Physics

High energy particle physics and cosmology concern themselves with estimating fundamental parameters of nature, such as the masses and interactions of fundamental particles like the Higgs boson and the rate of expansion of the universe. In doing so, they analyze exabyte-scale datasets, some of the largest in all of science, and face many challenges in subsequent data analysis. These challenges are shared between the two disciplines, but we focus on particle physics to highlight one specific domain. In particle physics, the standard method for estimating parameters involves performing Monte Carlo (MC) integration as a function of both parameters of interest and nuisance parameters using an expensive simulator, counting the number of observed collision events (i.i.d. samples) from an experiment in the corresponding integration domains, and forming a Poisson likelihood function. This likelihood function is then used in a Frequentist manner to construct a maximum likelihood point estimate (MLE) and confidence set for the parameters. To sufficiently populate the high-dimensional integration domains, simulators consume billions of CPU-hours annually and produce hundreds of petabytes of intermediate output data. Several techniques have been developed to: optimize definitions of the integration domains so as to be maximally sensitive to a particular subset of parameters, efficiently estimate the integrals, and build robust surrogate models by interpolating between integral evaluations at different parameter points. One can view this whole endeavor as classical Simulation-Based Inference (SBI).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2015

Daytime Cognitive Performance in Response to Sunlight or Fluorescent Light Controlling for Sleep Duration

Light is the primary synchronizer of the human circadian rhythm and also has acute alerting effects. Our study involves and comparing the alertness, performance and sleep of participants in the NASA Ames Sustainability Base, which uses sunlight as its primary light source, to in a traditional office building which uses overhead florescent lighting and varying exposure to natural light. The purpose of this study is to determine whether the use of natural lighting as a primary light source improves daytime cognitive function and promotes nighttime sleep. Participants from the Sustainability Base will be matched by gender and age to individuals working in other NASA buildings. In a prior study we found no differences in performance between those working in the Sustainability Base and those working in other buildings. Unexpectedly, we found that the average sleep duration among participants in both buildings was short, which likely obscured our ability to detect a difference the effect of light exposure on alertness. Given that such sleep deprivation has negative effects on cognitive performance, in this iteration of the study we are asking the participants to maintain a regular schedule with eight hours in bed each night in order to control for the effect of self-selected sleep restriction. Over the course of one week, we will ask the participants to wear actiwatches continuously, complete a psychomotor vigilance task (PVT) and digit symbol substitution task (DSST) three times per day, and keep daily sleepwork diaries. We hope that this study will provide data to support the idea that natural lighting and green architectural design are optimal to enhance healthy nighttime sleep patterns and daytime cognitive performance.

cognitive performance↗
DOE OSTI2022

Considerations for Optimizing the Photometric Classification of Supernovae from the Rubin Observatory

The Vera C. Rubin Observatory will increase the number of observed supernovae (SNe) by an order of magnitude; however, it is impossible to spectroscopically confirm the class for all SNe discovered. Thus, photometric classification is crucial, but its accuracy depends on the not-yet-finalized observing strategy of Rubin Observatory's Legacy Survey of Space and Time (LSST). We quantitatively analyze the impact of the LSST observing strategy on SNe classification using simulated multiband light curves from the Photometric LSST Astronomical Time-Series Classification Challenge (PLAsTiCC). First, we augment the simulated training set to be representative of the photometric redshift distribution per SNe class, the cadence of observations, and the flux uncertainty distribution of the test set. Then we build a classifier using the photometric transient classification library snmachine, based on wavelet features obtained from Gaussian process fits, yielding a similar performance to the winning PLAsTiCC entry. We study the classification performance for SNe with different properties within a single simulated observing strategy. We find that season length is important, with light curves of 150 days yielding the highest performance. Cadence also has an important impact on SNe classification; events with median inter-night gap <3.5 days yield higher classification performance. Interestingly, we find that large gaps (>10 days) in light-curve observations do not impact performance if sufficient observations are available on either side, due to the effectiveness of the Gaussian process interpolation. This analysis is the first exploration of the impact of observing strategy on photometric SN classification with LSST.

79 ASTRONOMY AND ASTROPHYSICS↗